Development of a high-throughput in vitro assay using a novel Caco-2/rat hepatocyte system for the prediction of oral plasma area under the concentration versus time curve (AUC) in rats.

PubMed

Cheng, K-C; Li, Cheng; Hsieh, Yunsheng; Montgomery, Diana; Liu, Tongtong; White, Ronald E

2006-01-01

Previously, we have shown that a novel Caco-2/human hepatocyte system is a useful model for the prediction of oral bioavailability in humans. In this study, we attempted to use a similar system in a high-throughput screening mode for the selection of new compound entities (NCE) in drug discovery. A total of 72 compounds randomly selected from three different chemotypes were dosed orally in rats. In vivo plasma area under the concentration versus time curve (AUC) from 0-6 h of the parent compound was determined. The same compounds were also tested in the Caco-2/rat hepatocyte system. In vitro AUC from 0-3 h in the Caco-2 rat hepatocyte system was determined. The predictive usefulness of the Caco-2/rat hepatocyte system was evaluated by comparing the in vivo plasma AUC and the in vitro AUC. Linear regression analysis showed a reasonable correlation (R2 = 0.5) between the in vivo AUC and the in vitro AUC. Using 0.4 microM h in vivo AUC as a cut-off, compounds were categorized as either low or high AUC. The in vitro AUC successfully matched the corresponding in vivo category for sixty-three out of seventy-two compounds. The results presented in this study suggest that the Caco-2/rat hepatocyte system may be used as a high-throughput screen in drug discovery for pharmacokinetic behaviors of compounds in rats.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome.

PubMed

Lalonde, Michel; Wells, R Glenn; Birnie, David; Ruddy, Terrence D; Wassenaar, Richard

2014-07-01

Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lalonde, Michel, E-mail: mlalonde15@rogers.com; Wassenaar, Richard; Wells, R. Glenn

2014-07-15

Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: Aboutmore » 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). Conclusions: A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.« less

Relationships between antimicrobial effect and area under the concentration-time curve as a basis for comparison of modes of antibiotic administration: meropenem bolus injections versus continuous infusions.

PubMed Central

Firsov, A A; Mattie, H

1997-01-01

In comparative studies of different modes of administration (MAs) simulated in in vitro dynamic models, only one dose of antibiotic is usually mimicked. Such an experimental design can provide a prediction of the antimicrobial effect (AME) of a given combination of drug, clinical isolate, and infection site, but may be inappropriate for accurate comparison of MAs. An alternative design providing comparison of different MAs with various antibiotic doses in a wide range and with evaluation of the respective relationships between AME and the AUC was proposed and examined. Two series of meropenem pharmacokinetic profiles, i.e., monoexponentially decreasing concentrations (bolus doses) and constant concentrations (6-h continuous infusion), were in vitro simulated. The simulated initial concentrations (Co[from 0.62 to 48 micrograms/ml]) and steady-state concentrations (Css[from 0.016 to 8 micrograms/ml]) were chosen to provide similar AUC for 0 to 6 h (AUC0-6) ranges for both MAs (from 0.070 to 50.0 micrograms.h/ml and from 0.09 to 48.0 micrograms.h/ml, respectively). The AME of meropenem on Staphylococcus aureus ATCC 25923 (MIC, 0.06 micrograms/ml) was determined at each time (t) point as a difference (E) between the logarithms of viable counts (N) in the control cultures without antibiotic (NC) and in cultures exposed to antibiotics (NA). Time courses of E observed at different Co of Css levels were compared in terms of the areas under the E-t curves (ABBCt). The finite values of the ABBCt observed by the end of the 6 -h observation period, which are equivalent to the area between bacterial count-time curves observed in the absence and presence of antibiotic (ABBC), were plotted versus the respective AUCs produced by each of the MAs. The ABBC versus AUC curves had a similar pattern: a plateau achieved at high AUCs followed by a steep rise in ABBC at relatively low AUCs was inherent in both of the MAs. The superiority of bolus dosing over the infusions could be documented only for meropenem concentrations below the MIC. At higher Co or Css (i.e., at an AUC of > or = 0.4 micrograms.h/ml), the ABBC versus AUC curves plotted for each of the MAs could practically be superimposed. On the whole, both MAs appeared to be equiefficient in terms of the ABBC. These results suggest that AUC analysis of the AME may be a useful tool for comparing different MAs. Such comparative studies should be designed in a manner that provides the use of similar AUC ranges, since the AUC may be considered as a common pharmacokinetic denominator in comparing one MA or dosing regimen to another. PMID:9021191

Polygenic risk score analysis of pathologically confirmed Alzheimer disease.

PubMed

Escott-Price, Valentina; Myers, Amanda J; Huentelman, Matt; Hardy, John

2017-08-01

Previous estimates of the utility of polygenic risk score analysis for the prediction of Alzheimer disease have given area under the curve (AUC) estimates of <80%. However, these have been based on the genetic analysis of clinical case-control series. Here, we apply the same analytic approaches to a pathological case-control series and show a predictive AUC of 84%. We suggest that this analysis has clinical utility and that there is limited room for further improvement using genetic data. Ann Neurol 2017;82:311-314. © 2017 American Neurological Association.

The average receiver operating characteristic curve in multireader multicase imaging studies

PubMed Central

Samuelson, F W

2014-01-01

Objective: In multireader, multicase (MRMC) receiver operating characteristic (ROC) studies for evaluating medical imaging systems, the area under the ROC curve (AUC) is often used as a summary metric. Owing to the limitations of AUC, plotting the average ROC curve to accompany the rigorous statistical inference on AUC is recommended. The objective of this article is to investigate methods for generating the average ROC curve from ROC curves of individual readers. Methods: We present both a non-parametric method and a parametric method for averaging ROC curves that produce a ROC curve, the area under which is equal to the average AUC of individual readers (a property we call area preserving). We use hypothetical examples, simulated data and a real-world imaging data set to illustrate these methods and their properties. Results: We show that our proposed methods are area preserving. We also show that the method of averaging the ROC parameters, either the conventional bi-normal parameters (a, b) or the proper bi-normal parameters (c, da), is generally not area preserving and may produce a ROC curve that is intuitively not an average of multiple curves. Conclusion: Our proposed methods are useful for making plots of average ROC curves in MRMC studies as a companion to the rigorous statistical inference on the AUC end point. The software implementing these methods is freely available from the authors. Advances in knowledge: Methods for generating the average ROC curve in MRMC ROC studies are formally investigated. The area-preserving criterion we defined is useful to evaluate such methods. PMID:24884728

Evaluation of postprandial glucose excursion using a novel minimally invasive glucose area-under-the-curve monitoring system.

PubMed

Kuranuki, Sachi; Sato, Toshiyuki; Okada, Seiki; Hosoya, Samiko; Seko, Akinobu; Sugihara, Kaya; Nakamura, Teiji

2013-01-01

To develop a minimally invasive interstitial fluid extraction technology (MIET) to monitor postprandial glucose area under the curve (AUC) without blood sampling, we evaluated the accuracy of glucose AUC measured by MIET and compared with that by blood sampling after food intake. Interstitial fluid glucose AUC (IG-AUC) following consumption of 6 different types of foods was measured by MIET. MIET consisted of stamping microneedle arrays, placing hydrogel patches on the areas, and calculating IG-AUC based on glucose levels in the hydrogels. Glycemic index (GI) was determined using IG-AUC and reference AUC measured by blood sampling. IG-AUC strongly correlated with reference AUC (R = 0.91), and GI determined using IG-AUC showed good correlation with that determined by reference AUC (R = 0.88). IG-AUC obtained by MIET can accurately predict the postprandial glucose excursion without blood sampling. In addition, feasibility of GI measurement by MIET was confirmed.

The impact of new partial AUC parameters for evaluating the bioequivalence of prolonged-release formulations.

PubMed

Boily, Michaël; Dussault, Catherine; Massicotte, Julie; Guibord, Pascal; Lefebvre, Marc

2015-01-23

To demonstrate bioequivalence (BE) between two prolonged-release (PR) drug formulations, single dose studies under fasting and fed state as well as at least one steady-state study are currently required by the European Medicines Agency (EMA). Recently, however, there have been debates regarding the relevance of steady-state studies. New requirements in single-dose investigations have also been suggested by the EMA to address the absence of a parameter that can adequately assess the equivalence of the shape of the curves. In the draft guideline issued in 2013, new partial area under the curve (pAUC) pharmacokinetic (PK) parameters were introduced to that effect. In light of these potential changes, there is a need of supportive clinical evidence to evaluate the impact of pAUCs on the evaluation of BE between PR formulations. In this retrospective analysis, it was investigated whether the newly defined parameters were associated with an increase in discriminatory ability or a change in variability compared to the conventional PK parameters. Among the single dose studies that met the requirements already in place, 20% were found unable to meet the EMA's new requirements in regards to the pAUC PK parameters. When pairing fasting and fed studies for a same formulation, the failure rate increased to 40%. In some cases, due to the high variability of these parameters, an increase of the sample size would be required to prove BE. In other cases however, the pAUC parameters demonstrated a robust ability to detect differences between the shapes of the curves of PR formulations. The present analysis should help to better understand the impact of the upcoming changes in European regulations on PR formulations and in the design of future BE studies. Copyright © 2014 Elsevier B.V. All rights reserved.

Estimation of abbreviated mycophenolic acid area under the concentration-time curve during early posttransplant period by limited sampling strategy.

PubMed

Mohammadpour, A-H; Nazemian, F; Abtahi, B; Naghibi, M; Gholami, K; Rezaee, S; Nazari, M-R A; Rajabi, O

2008-12-01

Area under the concentration curve (AUC) of mycophenolic acid (MPA) could help to optimize therapeutic drug monitoring during the early post-renal transplant period. The aim of this study was to develop a limited sampling strategy to estimate an abbreviated MPA AUC within the first month after renal transplantation. In this study we selected 19 patients in the early posttransplant period with normal renal graft function (glomerular filtration rate > 70 mL/min). Plasma MPA concentrations were measured using reverse-phase high-performance liquid chromatography. MPA AUC(0-12h) was calculated using the linear trapezoidal rule. Multiple stepwise regression analysis was used to determine the minimal and convenient time points of MPA levels that could be used to derive model equations best fitted to MPA AUC(0-12h). The regression equation for AUC estimation that gave the best performance was AUC = 14.46 C(10) + 15.547 (r(2) = .882). The validation of the method was performed using the jackknife method. Mean prediction error of this model was not different from zero (P > .05) and had a high root mean square prediction error (8.06). In conclusion, this limited sampling strategy provided an effective approach for therapeutic drug monitoring during the early posttransplant period.

Predictors of Gestational Diabetes Mellitus in Chinese Women with Polycystic Ovary Syndrome: A Cross-Sectional Study.

PubMed

Zhang, Ya-Jie; Jin, Hua; Qin, Zhen-Li; Ma, Jin-Long; Zhao, Han; Zhang, Ling; Chen, Zi-Jiang

2016-01-01

This study aims to explore the independent predictors of gestational diabetes mellitus (GDM) in Chinese women with polycystic ovary syndrome (PCOS). This cross-sectional study analyzed primigravid women with PCOS and classified them as those with and without GDM. Independent risk factors and model performance were analyzed using multivariate logistic regression and the area under the curve (AUC) of receiver operating characteristic (ROC), respectively. Maternal body mass index, waist circumference, waist-to-hip ratio (WHR), fasting glucose, insulin, sex hormone-binding globulin (SHBG), homeostasis model assessment-insulin resistance (HOMA-IR) before pregnancy, gestation weight gain before 24 weeks and the incidence of family history of diabetes were different in the 2 groups. Logistic regression analysis showed that pre-pregnancy WHR, SHBG, HOMA-IR and gestation weight gain before 24 weeks were the independent predictors of GDM. ROC curve analysis confirmed that gestation weight gain before 24 weeks (AUC 0.767, 95% CI 0.688-0.841), pre-pregnant WHR (AUC 0.725, 95% CI 0.649-0.802), HOMA-IR (AUC 0.711, 95% CI 0.632-0.790) and SHBG levels (AUC 0.709, 95% CI 0.625-0.793) were the strong risk factors. In Chinese women with PCOS, factors of gestation weight gain before 24 weeks, pre-pregnant WHR, HOMA-IR and SHBG levels are strongly associated with subsequent development of GDM. © 2015 S. Karger AG, Basel.

Pharmacodynamic analysis of ceftriaxone, gatifloxacin,and levofloxacin against Streptococcus pneumoniae with the use of Monte Carlo simulation.

PubMed

Frei, Christopher R; Burgess, David S

2005-09-01

To evaluate the pharmacodynamics of four intravenous antimicrobial regimens-ceftriaxone 1 g, gatifloxacin 400 mg, levofloxacin 500 mg, and levofloxacin 750 mg, each every 24 hours-against recent Streptococcus pneumoniae isolates. Pharmacodynamic analysis using Monte Carlo simulation. The Surveillance Network (TSN) 2002 database. Streptococcus pneumoniae isolates (7866 isolates) were stratified according to penicillin susceptibilities as follows: susceptible (4593), intermediate (1986), and resistant (1287). Risk analysis software was used to simulate 10,000 patients by integrating published pharmacokinetic parameters, their variability, and minimum inhibitory concentration (MIC) distributions from the TSN database. Probability of target attainment was determined for percentage of time above the MIC (%T > MIC) from 0-100% for ceftriaxone and area under the concentration-time curve (AUC):MIC ratio from 0-150 for the fluoroquinolones. For ceftriaxone, probability of target attainment remained 90% or greater against the three isolate groups until a %T > MIC of 70% or greater, and it remained 90% or greater against susceptible and intermediate isolates over the entire interval (%T > MIC 0-100%). For levofloxacin 500 mg, probability of target attainment was 90% at an AUC:MIC < or = 30, but the curve declined sharply with further increases in pharmacodynamic target. Levofloxacin 750 mg achieved a probability of target attainment of 99% at an AUC:MIC ratio < or = 30; the probability remained approximately 90% until a target of 70 or greater, when it declined steeply. Gatifloxacin demonstrated a high probability (99%) of target attainment at an AUC:MIC ratio < or = 30, and it remained above 90% until a target of 70. Ceftriaxone maintained high probability of target attainment over a broad range of pharmacodynamic targets regardless of penicillin susceptibility (%T > MIC 0-60%). Levofloxacin 500 mg maintained high probability of target attainment for AUC:MIC ratios 0-30; whereas, levofloxacin 750 mg and gatifloxacin maintained high probability of target attainment for AUC:MIC ratios 0-60. Rate of decline in the pharmacodynamic curve was most pronounced for the two levofloxacin regimens and more gradual for gatifloxacin and ceftriaxone.

Improving the prediction of pathologic outcomes in patients undergoing radical prostatectomy: the value of prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine.

PubMed

Ferro, Matteo; Lucarelli, Giuseppe; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Perruolo, Giuseppe; Marino, Ada; Cosimato, Vincenzo; Giorgio, Emilia; Tagliamonte, Virginia; Bottero, Danilo; De Cobelli, Ottavio; Terracciano, Daniela

2015-02-01

Several efforts have been made to find biomarkers that could help clinicians to preoperatively determine prostate cancer (PCa) pathological characteristics and choose the best therapeutic approach, avoiding over-treatment. On this effort, prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine have been presented as promising tools. We evaluated the ability of these biomarkers to predict the pathologic PCa characteristics within a prospectively collected contemporary cohort of patients who underwent radical prostatectomy (RP) for clinically localized PCa at a single high-volume Institution. The prognostic performance of PCA3, phi and sarcosine were evaluated in 78 patients undergoing RP for biopsy-proven PCa. Receiver operating characteristic (ROC) curve analyses tested the accuracy (area under the curve (AUC)) in predicting PCa pathological characteristics. Decision curve analyses (DCA) were used to assess the clinical benefit of the three biomarkers. We found that PCA3, phi and sarcosine levels were significantly higher in patients with tumor volume (TV)≥0.5 ml, pathologic Gleason sum (GS)≥7 and pT3 disease (all p-values≤0.01). ROC curve analysis showed that phi is an accurate predictor of high-stage (AUC 0.85 [0.77-0.93]), high-grade (AUC 0.83 [0.73-0.93]) and high-volume disease (AUC 0.94 [0.88-0.99]). Sarcosine showed a comparable AUC (0.85 [0.76-0.94]) only for T3 stage prediction, whereas PCA3 score showed lower AUCs, ranging from 0.74 (for GS) to 0.86 (for TV). PCA3, phi and sarcosine are predictors of PCa characteristics at final pathology. Successful clinical translation of these findings would reduce the frequency of surveillance biopsies and may enhance acceptance of active surveillance (AS). Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Development of a Bayesian model to estimate health care outcomes in the severely wounded

PubMed Central

Stojadinovic, Alexander; Eberhardt, John; Brown, Trevor S; Hawksworth, Jason S; Gage, Frederick; Tadaki, Douglas K; Forsberg, Jonathan A; Davis, Thomas A; Potter, Benjamin K; Dunne, James R; Elster, E A

2010-01-01

Background: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations. Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN) and step-wise logistic regression (LR). Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC) from receiver operating characteristics (ROC) curves. Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79), intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81), and wound healing (AUC: LR, 0.91; BBN, 0.72) showed strong AUC. Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold cross-validation and further confirmed through logistic regression modeling. The method warrants further development and independent validation in other, more diverse patient populations. PMID:21197361

Effect of blood sampling schedule and method of calculating the area under the curve on validity and precision of glycaemic index values.

PubMed

Wolever, Thomas M S

2004-02-01

To evaluate the suitability for glycaemic index (GI) calculations of using blood sampling schedules and methods of calculating area under the curve (AUC) different from those recommended, the GI values of five foods were determined by recommended methods (capillary blood glucose measured seven times over 2.0 h) in forty-seven normal subjects and different calculations performed on the same data set. The AUC was calculated in four ways: incremental AUC (iAUC; recommended method), iAUC above the minimum blood glucose value (AUCmin), net AUC (netAUC) and iAUC including area only before the glycaemic response curve cuts the baseline (AUCcut). In addition, iAUC was calculated using four different sets of less than seven blood samples. GI values were derived using each AUC calculation. The mean GI values of the foods varied significantly according to the method of calculating GI. The standard deviation of GI values calculating using iAUC (20.4), was lower than six of the seven other methods, and significantly less (P<0.05) than that using netAUC (24.0). To be a valid index of food glycaemic response independent of subject characteristics, GI values in subjects should not be related to their AUC after oral glucose. However, calculating GI using AUCmin or less than seven blood samples resulted in significant (P<0.05) relationships between GI and mean AUC. It is concluded that, in subjects without diabetes, the recommended blood sampling schedule and method of AUC calculation yields more valid and/or more precise GI values than the seven other methods tested here. The only method whose results agreed reasonably well with the recommended method (ie. within +/-5 %) was AUCcut.

Optimizing area under the ROC curve using semi-supervised learning

PubMed Central

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M.

2014-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.1 PMID:25395692

Exploration of Analysis Methods for Diagnostic Imaging Tests: Problems with ROC AUC and Confidence Scores in CT Colonography

PubMed Central

Mallett, Susan; Halligan, Steve; Collins, Gary S.; Altman, Doug G.

2014-01-01

Background Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. Methods In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Results Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. Conclusions The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests. PMID:25353643

Exploration of analysis methods for diagnostic imaging tests: problems with ROC AUC and confidence scores in CT colonography.

PubMed

Mallett, Susan; Halligan, Steve; Collins, Gary S; Altman, Doug G

2014-01-01

Different methods of evaluating diagnostic performance when comparing diagnostic tests may lead to different results. We compared two such approaches, sensitivity and specificity with area under the Receiver Operating Characteristic Curve (ROC AUC) for the evaluation of CT colonography for the detection of polyps, either with or without computer assisted detection. In a multireader multicase study of 10 readers and 107 cases we compared sensitivity and specificity, using radiological reporting of the presence or absence of polyps, to ROC AUC calculated from confidence scores concerning the presence of polyps. Both methods were assessed against a reference standard. Here we focus on five readers, selected to illustrate issues in design and analysis. We compared diagnostic measures within readers, showing that differences in results are due to statistical methods. Reader performance varied widely depending on whether sensitivity and specificity or ROC AUC was used. There were problems using confidence scores; in assigning scores to all cases; in use of zero scores when no polyps were identified; the bimodal non-normal distribution of scores; fitting ROC curves due to extrapolation beyond the study data; and the undue influence of a few false positive results. Variation due to use of different ROC methods exceeded differences between test results for ROC AUC. The confidence scores recorded in our study violated many assumptions of ROC AUC methods, rendering these methods inappropriate. The problems we identified will apply to other detection studies using confidence scores. We found sensitivity and specificity were a more reliable and clinically appropriate method to compare diagnostic tests.

Optimizing area under the ROC curve using semi-supervised learning.

PubMed

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M

2015-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.

Assessment of insulin sensitivity by the hyperinsulinemic euglycemic clamp: Comparison with the spectral analysis of photoplethysmography.

PubMed

De Souza, Aglecio Luiz; Batista, Gisele Almeida; Alegre, Sarah Monte

2017-01-01

We compare spectral analysis of photoplethysmography (PTG) with insulin resistance measured by the hyperinsulinemic euglycemic clamp (HEC) technique. A total of 100 nondiabetic subjects, 43 men and 57 women aged 20-63years, 30 lean, 42 overweight and 28 obese were enrolled in the study. These patients underwent an examination with HEC, and an examination with the PTG spectral analysis and calculation of the PTG Total Power (PTG-TP). Receiver-operating characteristic (ROC) curves were constructed to determine the specificity and sensitivity of PTG-TP in the assessment of insulin resistance. There is a moderate correlation between insulin sensitivity (M-value) and PTG-TP (r=- 0.64, p<0.0001). The ROC curves showed that the most relevant cutoff to the whole study group was a PTG-TP>406.2. This cut-off had a sensitivity=95.7%, specificity =84,4% and the area under the ROC curve (AUC)=0.929 for identifying insulin resistance. All AUC ROC curve analysis were significant (p<0.0001). The use of the PTG-TP marker measured from the PTG spectral analysis is a useful tool in screening and follow up of IR, especially in large-scale studies. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Is the area under blood pressure curve the best parameter to evaluate 24-h ambulatory blood pressure monitoring data?

PubMed

Nobre, Fernando; Mion, Décio

2005-10-01

Ambulatory blood pressure monitoring (ABPM) provides relevant data about blood pressure over a 24-h period. The analysis of parameters to determine the blood pressure profile from these data is of great importance. To calculate areas under systolic and diastolic blood pressure curves (SBP-AUC/DBP-AUC) and compare with systolic and diastolic blood pressure load (SBPL/DBPL) and 24-h systolic and diastolic blood pressure (24-h SBP/24-h DBP) in order to determine which provides the best correlation with left ventricular mass index (LVMI). ABPM measurements (1143 individuals) were analyzed to obtain 24-h SBP/24-h DBP, SBPL/DBPL, and SBP-AUC/ DBP-AUC, using Spacelabs (90207) and CardioSistemas devices. Left ventricular mass was determined using an echocardiograph HP Sonos 5500 and LVMI was calculated. The correlations between all possible pairs within the group 24-h SBP/SBPL/SBP-AUC and 24-h DBP/DBPL/DBP-AUC were high and statistically significant. The correlations between 24-h SBP/24-h DBP and SBP-AUC/DBP-AUC with SBPL/DBPL close to 100%, were lower than those mentioned above. The correlations of the parameters obtained by ABPM with LVMI were also high and statistically significant, except for blood pressure load between 90 and 100%, and for 24-h SBP of 135 mmHg or less and SBPL higher than 50%. SBPL/DBPL and SBP-AUC/DBP-AUC can be used for the evaluation of ABPM data owing to the strong correlation with 24-h SBP/24-h DBP and with LVMI, except when SBPL is close to 100% or 24-h SBP is below 135 mmHg but SBPL is above 50%. SBP-AUC/DBP-AUC, however, are a better alternative because they do not have the limitations of blood pressure load or even of 24-h blood pressure present.

Prognostic indices for early mortality in ischaemic stroke - meta-analysis.

PubMed

Mattishent, K; Kwok, C S; Mahtani, A; Pelpola, K; Myint, P K; Loke, Y K

2016-01-01

Several models have been developed to predict mortality in ischaemic stroke. We aimed to evaluate systematically the performance of published stroke prognostic scores. We searched MEDLINE and EMBASE in February 2014 for prognostic models (published between 2003 and 2014) used in predicting early mortality (<6 months) after ischaemic stroke. We evaluated discriminant ability of the tools through meta-analysis of the area under the curve receiver operating characteristic curve (AUROC) or c-statistic. We evaluated the following components of study validity: collection of prognostic variables, neuroimaging, treatment pathways and missing data. We identified 18 articles (involving 163 240 patients) reporting on the performance of prognostic models for mortality in ischaemic stroke, with 15 articles providing AUC for meta-analysis. Most studies were either retrospective, or post hoc analyses of prospectively collected data; all but three reported validation data. The iSCORE had the largest number of validation cohorts (five) within our systematic review and showed good performance in four different countries, pooled AUC 0.84 (95% CI 0.82-0.87). We identified other potentially useful prognostic tools that have yet to be as extensively validated as iSCORE - these include SOAR (2 studies, pooled AUC 0.79, 95% CI 0.78-0.80), GWTG (2 studies, pooled AUC 0.72, 95% CI 0.72-0.72) and PLAN (1 study, pooled AUC 0.85, 95% CI 0.84-0.87). Our meta-analysis has identified and summarized the performance of several prognostic scores with modest to good predictive accuracy for early mortality in ischaemic stroke, with the iSCORE having the broadest evidence base. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Easy and accurate variance estimation of the nonparametric estimator of the partial area under the ROC curve and its application.

PubMed

Yu, Jihnhee; Yang, Luge; Vexler, Albert; Hutson, Alan D

2016-06-15

The receiver operating characteristic (ROC) curve is a popular technique with applications, for example, investigating an accuracy of a biomarker to delineate between disease and non-disease groups. A common measure of accuracy of a given diagnostic marker is the area under the ROC curve (AUC). In contrast with the AUC, the partial area under the ROC curve (pAUC) looks into the area with certain specificities (i.e., true negative rate) only, and it can be often clinically more relevant than examining the entire ROC curve. The pAUC is commonly estimated based on a U-statistic with the plug-in sample quantile, making the estimator a non-traditional U-statistic. In this article, we propose an accurate and easy method to obtain the variance of the nonparametric pAUC estimator. The proposed method is easy to implement for both one biomarker test and the comparison of two correlated biomarkers because it simply adapts the existing variance estimator of U-statistics. In this article, we show accuracy and other advantages of the proposed variance estimation method by broadly comparing it with previously existing methods. Further, we develop an empirical likelihood inference method based on the proposed variance estimator through a simple implementation. In an application, we demonstrate that, depending on the inferences by either the AUC or pAUC, we can make a different decision on a prognostic ability of a same set of biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Anthropometric Indicators as Body Fat Discriminators in Children and Adolescents: A Systematic Review and Meta-Analysis.

PubMed

Alves Junior, Carlos As; Mocellin, Michel C; Gonçalves, Eliane C Andrade; Silva, Diego As; Trindade, Erasmo Bsm

2017-09-01

We analyzed the discriminatory capacity of anthropometric indicators for body fat in children and adolescents. This systematic review and meta-analysis included cross-sectional and clinical studies comprising children and adolescents aged 2-19 y that tested the discriminatory value for body fat measured by anthropometric methods or indexes generated by anthropometric variables compared with precision methods in the diagnosis of body fat [dual-energy X-ray absorptiometry (DXA), computed tomography, air displacement plethysmography (ADP), or MRI]. Five studies met the eligibility criteria and presented high methodologic quality. The anthropometric indicators that had high discriminatory power to identify high body fat were body mass index (BMI) in males [area under the curve (AUC): 0.975] and females (AUC: 0.947), waist circumference (WC) in males (AUC: 0.975) and females (AUC: 0.959), and the waist-to-height ratio (WTHR) in males (AUC: 0.897) and females (AUC: 0.914). BMI, WC, and WTHR can be used by health professionals to assess body fat in children and adolescents. © 2017 American Society for Nutrition.

Smelling the Diagnosis: The Electronic Nose as Diagnostic Tool in Inflammatory Arthritis. A Case-Reference Study.

PubMed

Brekelmans, Marjolein P; Fens, Niki; Brinkman, Paul; Bos, Lieuwe D; Sterk, Peter J; Tak, Paul P; Gerlag, Daniëlle M

2016-01-01

To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls. In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored. Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60-0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61-0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55-0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups. Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.

Why Does Rebalancing Class-Unbalanced Data Improve AUC for Linear Discriminant Analysis?

PubMed

Xue, Jing-Hao; Hall, Peter

2015-05-01

Many established classifiers fail to identify the minority class when it is much smaller than the majority class. To tackle this problem, researchers often first rebalance the class sizes in the training dataset, through oversampling the minority class or undersampling the majority class, and then use the rebalanced data to train the classifiers. This leads to interesting empirical patterns. In particular, using the rebalanced training data can often improve the area under the receiver operating characteristic curve (AUC) for the original, unbalanced test data. The AUC is a widely-used quantitative measure of classification performance, but the property that it increases with rebalancing has, as yet, no theoretical explanation. In this note, using Gaussian-based linear discriminant analysis (LDA) as the classifier, we demonstrate that, at least for LDA, there is an intrinsic, positive relationship between the rebalancing of class sizes and the improvement of AUC. We show that the largest improvement of AUC is achieved, asymptotically, when the two classes are fully rebalanced to be of equal sizes.

Proposal for a standardised identification of the mono-exponential terminal phase for orally administered drugs.

PubMed

Scheerans, Christian; Derendorf, Hartmut; Kloft, Charlotte

2008-04-01

The area under the plasma concentration-time curve from time zero to infinity (AUC(0-inf)) is generally considered to be the most appropriate measure of total drug exposure for bioavailability/bioequivalence studies of orally administered drugs. However, the lack of a standardised method for identifying the mono-exponential terminal phase of the concentration-time curve causes variability for the estimated AUC(0-inf). The present investigation introduces a simple method, called the two times t(max) method (TTT method) to reliably identify the mono-exponential terminal phase in the case of oral administration. The new method was tested by Monte Carlo simulation in Excel and compared with the adjusted r squared algorithm (ARS algorithm) frequently used in pharmacokinetic software programs. Statistical diagnostics of three different scenarios, each with 10,000 hypothetical patients showed that the new method provided unbiased average AUC(0-inf) estimates for orally administered drugs with a monophasic concentration-time curve post maximum concentration. In addition, the TTT method generally provided more precise estimates for AUC(0-inf) compared with the ARS algorithm. It was concluded that the TTT method is a most reasonable tool to be used as a standardised method in pharmacokinetic analysis especially bioequivalence studies to reliably identify the mono-exponential terminal phase for orally administered drugs showing a monophasic concentration-time profile.

Identification of the time-point which gives a plasma rabeprazole concentration that adequately reflects the area under the concentration-time curve.

PubMed

Niioka, Takenori; Uno, Tsukasa; Yasui-Furukori, Norio; Shimizu, Mikiko; Sugawara, Kazunobu; Tateishi, Tomonori

2006-10-01

The purpose of this study is to evaluate whether a simple formula using limited blood samples can predict the area under the plasma rabeprazole concentration-time curve (AUC) in co-administration with CYP inhibitors. A randomized double-blind placebo-controlled crossover study design in three phases was conducted at intervals of 2 weeks. Twenty-one healthy Japanese volunteers, including three CYP2C19 genotype groups, took a single oral 20-mg dose of rabeprazole after three 6-day pretreatments, i.e., clarithromycin 800 mg/day, fluvoxamine 50 mg/day, and placebo. Prediction formulas of the AUC were derived from pharmacokinetics data of 21 subjects in three phases using multiple linear regression analysis. Ten blood samples were collected over 24 h to calculate AUC. Plasma concentrations of rabeprazole was measured by an HPLC-assay (l.l.q.=1 ng/ml). The AUC was based on all the data sets (n=63). The linear regression using two points (C3 and C6) could predict AUC(0-infinity) precisely, irrespective of CYP2C19 genotypes and CYP inhibitors (AUC(0-infinity)=1.39xC3+7.17xC6+344.14, r (2)=0.825, p<0.001). The present study demonstrated that the AUC of rabeprazole can be estimated by the simple formula using two-point concentrations. This formula can be more accurate for the prediction of AUC estimation than that reflected by CYP2C19 genotypes without any determination, even if there are significant differences for the CYP2C19 genotypes. Therefore, this prediction formula might be useful to evaluate whether CYP2C19 genotypes really reflects the curative effect of rabeprazole.

Suitability of the AUC Ratio as an Indicator of the Pharmacokinetic Advantage in HIPEC.

PubMed

Mas-Fuster, Maria Isabel; Ramon-Lopez, Amelia; Lacueva, Javier; Más-Serrano, Patricio; Nalda-Molina, Ricardo

2018-02-01

The purpose of this study was to evaluate the area under the concentration-time curve (AUC) ratio as an optimal indicator of the pharmacokinetic advantage during hyperthermic intraperitoneal perioperative chemotherapy. The impact on the AUC ratio on the variables related to the calculation of systemic drug exposure, instillation time, and peripheral drug distribution was evaluated through simulations as well as through a retrospective analysis of studies published in the literature. Both model simulations and the retrospective analysis showed that the 3 variables evaluated had an impact on the AUC ratio value if the complete systemic exposure was not fully considered. However, when that complete systemic exposure was considered, none of these variables affected the AUC ratio value. AUC ratio is not a characteristic parameter of a drug if the calculated systemic drug exposure is not complete. Thus, AUC ratio is not valid for comparing the pharmacokinetic advantage of 2 drugs, and it should not be employed to prove whether a drug can be used in hyperthermic intraperitoneal perioperative chemotherapy safely with regard to toxicity. As an alternative, the study of the absorption rate constant and the bioavailability are proposed as the true and independent parameters that reflect the amount of drug absorbed. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Comparing Postural Stability Entropy Analyses to Differentiate Fallers and Non-Fallers

PubMed Central

Fino, Peter C.; Mojdehi, Ahmad R.; Adjerid, Khaled; Habibi, Mohammad; Lockhart, Thurmon E.; Ross, Shane D.

2015-01-01

The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure (COP) of elderly individuals: 1.) eyes open (EO) versus eyes closed (EC) and 2.) fallers (F) versus non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic (ROC) curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis. PMID:26464267

Comparing Postural Stability Entropy Analyses to Differentiate Fallers and Non-fallers.

PubMed

Fino, Peter C; Mojdehi, Ahmad R; Adjerid, Khaled; Habibi, Mohammad; Lockhart, Thurmon E; Ross, Shane D

2016-05-01

The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure of elderly individuals: (1) eyes open (EO) vs. eyes closed (EC) and (2) fallers (F) vs. non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis.

Multivariate adaptive regression splines analysis to predict biomarkers of spontaneous preterm birth.

PubMed

Menon, Ramkumar; Bhat, Geeta; Saade, George R; Spratt, Heidi

2014-04-01

To develop classification models of demographic/clinical factors and biomarker data from spontaneous preterm birth in African Americans and Caucasians. Secondary analysis of biomarker data using multivariate adaptive regression splines (MARS), a supervised machine learning algorithm method. Analysis of data on 36 biomarkers from 191 women was reduced by MARS to develop predictive models for preterm birth in African Americans and Caucasians. Maternal plasma, cord plasma collected at admission for preterm or term labor and amniotic fluid at delivery. Data were partitioned into training and testing sets. Variable importance, a relative indicator (0-100%) and area under the receiver operating characteristic curve (AUC) characterized results. Multivariate adaptive regression splines generated models for combined and racially stratified biomarker data. Clinical and demographic data did not contribute to the model. Racial stratification of data produced distinct models in all three compartments. In African Americans maternal plasma samples IL-1RA, TNF-α, angiopoietin 2, TNFRI, IL-5, MIP1α, IL-1β and TGF-α modeled preterm birth (AUC train: 0.98, AUC test: 0.86). In Caucasians TNFR1, ICAM-1 and IL-1RA contributed to the model (AUC train: 0.84, AUC test: 0.68). African Americans cord plasma samples produced IL-12P70, IL-8 (AUC train: 0.82, AUC test: 0.66). Cord plasma in Caucasians modeled IGFII, PDGFBB, TGF-β1 , IL-12P70, and TIMP1 (AUC train: 0.99, AUC test: 0.82). Amniotic fluid in African Americans modeled FasL, TNFRII, RANTES, KGF, IGFI (AUC train: 0.95, AUC test: 0.89) and in Caucasians, TNF-α, MCP3, TGF-β3 , TNFR1 and angiopoietin 2 (AUC train: 0.94 AUC test: 0.79). Multivariate adaptive regression splines models multiple biomarkers associated with preterm birth and demonstrated racial disparity. © 2014 Nordic Federation of Societies of Obstetrics and Gynecology.

Influence Analysis for the Area Under the Receiver Operating Characteristic Curve.

PubMed

Ke, Bo-Shiang; Chiang, An Jen; Chang, Yuan-Chin Ivan

2018-01-01

Classification measures play essential roles in the assessment and construction of classifiers. Hence, determining how to prevent these measures from being affected by individual observations has become an important problem. In this paper, we propose several indexes based on the influence function and the concept of local influence to identify influential observations that affect the estimate of the area under the receiver operating characteristic curve (AUC), an important and commonly used measure. Cumulative lift charts are also used to equipoise the disagreements among the proposed indexes. Both the AUC indexes and the graphical tools only rely on the classification scores, and both are applicable to classifiers that can produce real-valued classification scores. A real data set is used for illustration.

Pharmacokinetics of mycophenolic acid and determination of area under the curve by abbreviated sampling strategy in Chinese liver transplant recipients.

PubMed

Chen, Hao; Peng, Chenghong; Yu, Zhicheng; Shen, Baiyong; Deng, Xiaxing; Qiu, Weihua; Fei, Yue; Shen, Chuan; Zhou, Guangwen; Yang, Weiping; Li, Hongwei

2007-01-01

This study aimed to: (i) define the clinical pharmacokinetics of mycophenolic acid (MPA) in Chinese liver transplant recipients; and (ii) develop a regression model best fitted for the prediction of MPA area under the plasma concentration-time curve from 0 to 12 hours (AUC(12)) by abbreviated sampling strategy. Forty liver transplant patients received mycophenolate mofetil 1g as a single dose twice daily in combination with tacrolimus. MPA concentrations were determined by high-performance liquid chromatography before dose (C(0)) and at 0.5 (C(0.5)), 1 (C(1)), 1.5 (C(1.5)), 2 (C(2)), 4 (C(4)), 6 (C(6)), 8 (C(8)), 10 (C(10)) and 12 (C(12)) hours after administration on days 7 and 14. A total of 72 pharmacokinetic profiles were obtained. MPA AUC(12) was calculated with 3P97 software. The trough concentrations (C(0)) of tacrolimus and hepatic function were also measured simultaneously. Multiple linear regression analysis was used to establish the models for estimated MPA AUC(12). The agreement between predicted MPA AUC(12) and observed MPA AUC(12) was investigated by Bland-Altman analysis. The pattern of MPA concentrations during the 12-hour interval on day 7 was very similar to that on day 14. In the total of 72 profiles, the mean maximum plasma concentration (C(max)) and time to reach C(max) (t(max)) were 9.79 +/- 5.26 mg/L and 1.43 +/- 0.78 hours, respectively. The mean MPA AUC(12) was 46.50 +/- 17.42 mg . h/L (range 17.99-98.73 mg . h/L). Correlation between MPA C(0) and MPA AUC(12) was poor (r(2) = 0.300, p = 0.0001). The best model for prediction of MPA AUC(12) was by using 1, 2, 6 and 8 hour timepoint MPA concentrations (r(2) = 0.921, p = 0.0001). The regression equation for estimated MPA AUC(12) was 5.503 + 0.919 . C(1) + 1.871 . C(2) + 3.176 . C(6) + 3.664 . C(8). This model had minimal mean prediction error (1.24 +/- 11.19%) and minimal mean absolute prediction error (8.24 +/- 7.61%). Sixty-three of 72 (88%) estimated MPA AUC(12) were within 15% of MPA AUC(12). Bland-Altman analysis also revealed the best agreement of this model compared with the others and a mean error of +/-9.89 mg . h/mL. This study showed the wide variability in MPA AUC(12) in Chinese liver transplant recipients. Single timepoint MPA concentration during the 12-hour dosing interval cannot reflect MPA AUC(12). MPA AUC(12) could be predicted accurately using 1, 2, 6 and 8 hour timepoint MPA concentrations by abbreviated sampling strategy.

HIV-1 envelope sequence-based diversity measures for identifying recent infections

PubMed Central

Kafando, Alexis; Fournier, Eric; Serhir, Bouchra; Martineau, Christine; Doualla-Bell, Florence; Sangaré, Mohamed Ndongo; Sylla, Mohamed; Chamberland, Annie; El-Far, Mohamed; Charest, Hugues

2017-01-01

Identifying recent HIV-1 infections is crucial for monitoring HIV-1 incidence and optimizing public health prevention efforts. To identify recent HIV-1 infections, we evaluated and compared the performance of 4 sequence-based diversity measures including percent diversity, percent complexity, Shannon entropy and number of haplotypes targeting 13 genetic segments within the env gene of HIV-1. A total of 597 diagnostic samples obtained in 2013 and 2015 from recently and chronically HIV-1 infected individuals were selected. From the selected samples, 249 (134 from recent versus 115 from chronic infections) env coding regions, including V1-C5 of gp120 and the gp41 ectodomain of HIV-1, were successfully amplified and sequenced by next generation sequencing (NGS) using the Illumina MiSeq platform. The ability of the four sequence-based diversity measures to correctly identify recent HIV infections was evaluated using the frequency distribution curves, median and interquartile range and area under the curve (AUC) of the receiver operating characteristic (ROC). Comparing the median and interquartile range and evaluating the frequency distribution curves associated with the 4 sequence-based diversity measures, we observed that the percent diversity, number of haplotypes and Shannon entropy demonstrated significant potential to discriminate recent from chronic infections (p<0.0001). Using the AUC of ROC analysis, only the Shannon entropy measure within three HIV-1 env segments could accurately identify recent infections at a satisfactory level. The env segments were gp120 C2_1 (AUC = 0.806), gp120 C2_3 (AUC = 0.805) and gp120 V3 (AUC = 0.812). Our results clearly indicate that the Shannon entropy measure represents a useful tool for predicting HIV-1 infection recency. PMID:29284009

HIV-1 envelope sequence-based diversity measures for identifying recent infections.

PubMed

Kafando, Alexis; Fournier, Eric; Serhir, Bouchra; Martineau, Christine; Doualla-Bell, Florence; Sangaré, Mohamed Ndongo; Sylla, Mohamed; Chamberland, Annie; El-Far, Mohamed; Charest, Hugues; Tremblay, Cécile L

2017-01-01

Identifying recent HIV-1 infections is crucial for monitoring HIV-1 incidence and optimizing public health prevention efforts. To identify recent HIV-1 infections, we evaluated and compared the performance of 4 sequence-based diversity measures including percent diversity, percent complexity, Shannon entropy and number of haplotypes targeting 13 genetic segments within the env gene of HIV-1. A total of 597 diagnostic samples obtained in 2013 and 2015 from recently and chronically HIV-1 infected individuals were selected. From the selected samples, 249 (134 from recent versus 115 from chronic infections) env coding regions, including V1-C5 of gp120 and the gp41 ectodomain of HIV-1, were successfully amplified and sequenced by next generation sequencing (NGS) using the Illumina MiSeq platform. The ability of the four sequence-based diversity measures to correctly identify recent HIV infections was evaluated using the frequency distribution curves, median and interquartile range and area under the curve (AUC) of the receiver operating characteristic (ROC). Comparing the median and interquartile range and evaluating the frequency distribution curves associated with the 4 sequence-based diversity measures, we observed that the percent diversity, number of haplotypes and Shannon entropy demonstrated significant potential to discriminate recent from chronic infections (p<0.0001). Using the AUC of ROC analysis, only the Shannon entropy measure within three HIV-1 env segments could accurately identify recent infections at a satisfactory level. The env segments were gp120 C2_1 (AUC = 0.806), gp120 C2_3 (AUC = 0.805) and gp120 V3 (AUC = 0.812). Our results clearly indicate that the Shannon entropy measure represents a useful tool for predicting HIV-1 infection recency.

Dynamic contrast–enhanced magnetic resonance imaging in patients with pulmonary arterial hypertension

PubMed Central

Condliffe, Robin; Marshall, Helen; Elliot, Charlie; Kiely, David G.; Wild, Jim M.

2014-01-01

Abstract Dynamic contrast–enhanced (DCE) time-resolved magnetic resonance (MR) imaging is a technique whereby the passage of an intravenous contrast bolus can be tracked through the pulmonary vascular system. The aim of this study was to investigate the prognostic significance of DCE-MR pulmonary blood transit times in patients with pulmonary arterial hypertension (PAH). Seventy-nine patients diagnosed with PAH underwent pulmonary DCE imaging at 1.5 T using a time-resolved three-dimensional spoiled gradient echo sequence. The prognostic significance of two DCE parameters, full width at half maximum (FWHM) of the first-pass clearance curve and pulmonary transit time (PTT), along with demographic and invasive catheter measurements, was evaluated by univariate and bivariate Cox proportional hazards regression and Kaplan-Meier analysis. DCE-MR transit times were most closely correlated with cardiac index (CI) and pulmonary vascular resistance index (PVRI) and were both found to be accurate for detecting reduced CI (FWHM area under the curve [AUC] at receiver operating characteristic analysis = 0.91 and PTT AUC = 0.92, respectively) and for detecting elevated PVRI (FWHM AUC = 0.88 and PTT AUC = 0.84, respectively). During the follow-up period, 25 patients died. Patients with longer measurements of FWHM (P = 0.0014) and PTT (P = 0.004) were associated with poor outcome at Kaplan-Meier analysis, and both parameters were strong predictors of adverse outcome from Cox proportional hazards analysis (P = 0.013 and 0.010, respectively). At bivariate analysis, DCE measurements predicted mortality independent of age, gender, and World Health Organization functional class; however, invasive hemodynamic indexes CI, PVRI, and DCE measurements were not independent of one another. In conclusion, DCE-MR transit times predict mortality in patients with PAH and are closely associated with clinical gold standards CI and PVRI. PMID:25006422

Dynamic contrast-enhanced magnetic resonance imaging in patients with pulmonary arterial hypertension.

PubMed

Swift, Andrew J; Telfer, Adam; Rajaram, Smitha; Condliffe, Robin; Marshall, Helen; Capener, Dave; Hurdman, Judith; Elliot, Charlie; Kiely, David G; Wild, Jim M

2014-03-01

Dynamic contrast-enhanced (DCE) time-resolved magnetic resonance (MR) imaging is a technique whereby the passage of an intravenous contrast bolus can be tracked through the pulmonary vascular system. The aim of this study was to investigate the prognostic significance of DCE-MR pulmonary blood transit times in patients with pulmonary arterial hypertension (PAH). Seventy-nine patients diagnosed with PAH underwent pulmonary DCE imaging at 1.5 T using a time-resolved three-dimensional spoiled gradient echo sequence. The prognostic significance of two DCE parameters, full width at half maximum (FWHM) of the first-pass clearance curve and pulmonary transit time (PTT), along with demographic and invasive catheter measurements, was evaluated by univariate and bivariate Cox proportional hazards regression and Kaplan-Meier analysis. DCE-MR transit times were most closely correlated with cardiac index (CI) and pulmonary vascular resistance index (PVRI) and were both found to be accurate for detecting reduced CI (FWHM area under the curve [AUC] at receiver operating characteristic analysis = 0.91 and PTT AUC = 0.92, respectively) and for detecting elevated PVRI (FWHM AUC = 0.88 and PTT AUC = 0.84, respectively). During the follow-up period, 25 patients died. Patients with longer measurements of FWHM (P = 0.0014) and PTT (P = 0.004) were associated with poor outcome at Kaplan-Meier analysis, and both parameters were strong predictors of adverse outcome from Cox proportional hazards analysis (P = 0.013 and 0.010, respectively). At bivariate analysis, DCE measurements predicted mortality independent of age, gender, and World Health Organization functional class; however, invasive hemodynamic indexes CI, PVRI, and DCE measurements were not independent of one another. In conclusion, DCE-MR transit times predict mortality in patients with PAH and are closely associated with clinical gold standards CI and PVRI.

Identification of Serum Periostin as a Potential Diagnostic and Prognostic Marker for Colorectal Cancer.

PubMed

Dong, Dong; Zhang, Lufang; Jia, Li; Ji, Wei; Wang, Zhiyong; Ren, Li; Niu, Ruifang; Zhou, Yunli

2018-06-01

Periostin (POSTN) plays an important role in numerous cancers, especially in gastrointestinal malignancy. The objective of this study was to investigate the diagnostic and prognostic role of serum POSTN in colorectal cancer (CRC). Serum periostin, together with CEA, CA19.9, CA72.4, and CA242 levels were measured in samples from 108 patients with CRC and 56 healthy controls, and their correlation with clinical characteristics was further analyzed. Receiver operating curves (ROC), Kaplan-Meier curves, and log-rank analyses were used to evaluate diagnostic and prognostic significance. Serum POSTN levels were significantly higher in patients with CRC compared with healthy controls (p < 0.0001) and associated with clinical stages (p < 0.001). ROC analysis revealed that POSTN was a biomarker comparable to CEA, CA19.9, and CA72.4 to distinguish all CRC from healthy controls (AUC = 0.75). Moreover, POSTN retained its diagnostic ability for CEA-negative (AUC = 0.69) and CA19.9-negative CRC patients (AUC = 0.71). Survival analysis revealed that patients with lower serum POSTN had longer overall survival than those with high serum POSTN (p = 0.0146). Serum POSTN might be a novel diagnostic and prognostic biomarker for patients with CRC.

Discovery and Validation of Novel Expression Signature for Postcystectomy Recurrence in High-Risk Bladder Cancer

PubMed Central

Lam, Lucia L.; Ghadessi, Mercedeh; Erho, Nicholas; Vergara, Ismael A.; Alshalalfa, Mohammed; Buerki, Christine; Haddad, Zaid; Sierocinski, Thomas; Triche, Timothy J.; Skinner, Eila C.; Davicioni, Elai; Daneshmand, Siamak; Black, Peter C.

2014-01-01

Background Nearly half of muscle-invasive bladder cancer patients succumb to their disease following cystectomy. Selecting candidates for adjuvant therapy is currently based on clinical parameters with limited predictive power. This study aimed to develop and validate genomic-based signatures that can better identify patients at risk for recurrence than clinical models alone. Methods Transcriptome-wide expression profiles were generated using 1.4 million feature-arrays on archival tumors from 225 patients who underwent radical cystectomy and had muscle-invasive and/or node-positive bladder cancer. Genomic (GC) and clinical (CC) classifiers for predicting recurrence were developed on a discovery set (n = 133). Performances of GC, CC, an independent clinical nomogram (IBCNC), and genomic-clinicopathologic classifiers (G-CC, G-IBCNC) were assessed in the discovery and independent validation (n = 66) sets. GC was further validated on four external datasets (n = 341). Discrimination and prognostic abilities of classifiers were compared using area under receiver-operating characteristic curves (AUCs). All statistical tests were two-sided. Results A 15-feature GC was developed on the discovery set with area under curve (AUC) of 0.77 in the validation set. This was higher than individual clinical variables, IBCNC (AUC = 0.73), and comparable to CC (AUC = 0.78). Performance was improved upon combining GC with clinical nomograms (G-IBCNC, AUC = 0.82; G-CC, AUC = 0.86). G-CC high-risk patients had elevated recurrence probabilities (P < .001), with GC being the best predictor by multivariable analysis (P = .005). Genomic-clinicopathologic classifiers outperformed clinical nomograms by decision curve and reclassification analyses. GC performed the best in validation compared with seven prior signatures. GC markers remained prognostic across four independent datasets. Conclusions The validated genomic-based classifiers outperform clinical models for predicting postcystectomy bladder cancer recurrence. This may be used to better identify patients who need more aggressive management. PMID:25344601

A comparison of methods for analyzing glucose and insulin areas under the curve following nine months of exercise in overweight adults.

PubMed

Potteiger, J A; Jacobsen, D J; Donnelly, J E

2002-01-01

We examined three methods for calculating the area under the curve (AUC) following an oral glucose tolerance test (OGTT) in overweight adults prior to and after 9 months of exercise. Subjects (n=27) were randomly assigned to a control (CON, n=9) or intervention (INT, n=18) group. INT performed supervised exercise 5 days per week, 45 min per session, at 65% of heart rate reserve. OGTTs were administered pre- and post-training. Blood was collected during a 75 g OGTT and analyzed for glucose (GLU) and insulin (INS) concentrations. AUCs were calculated using the incremental, positive incremental, and total AUC methods and the difference scores for pre- and post-training were determined. No differences were observed among the methods for glucose AUC for either group. Significant differences were observed for INT insulin AUC with total AUC (1525+/-3291 microU/1/180 min) significantly greater than incremental AUC (1112+/-3229 microU/1/180 min) or positive incremental AUC (1085+/-3195 microU/I/180 min). Total insulin AUC was significantly reduced following training for INT, while incremental and positive incremental insulin AUCs showed no change. These data suggest that the method of used to calculate AUC may affect the interpretation of whether or not an intervention was effective.

Accuracy of noncycloplegic retinoscopy, retinomax autorefractor, and SureSight vision screener for detecting significant refractive errors.

PubMed

Kulp, Marjean Taylor; Ying, Gui-Shuang; Huang, Jiayan; Maguire, Maureen; Quinn, Graham; Ciner, Elise B; Cyert, Lynn A; Orel-Bixler, Deborah A; Moore, Bruce D

2014-03-06

To evaluate, by receiver operating characteristic (ROC) analysis, the ability of noncycloplegic retinoscopy (NCR), Retinomax Autorefractor (Retinomax), and SureSight Vision Screener (SureSight) to detect significant refractive errors (RE) among preschoolers. Refraction results of eye care professionals using NCR, Retinomax, and SureSight (n = 2588) and of nurse and lay screeners using Retinomax and SureSight (n = 1452) were compared with masked cycloplegic retinoscopy results. Significant RE was defined as hyperopia greater than +3.25 diopters (D), myopia greater than 2.00 D, astigmatism greater than 1.50 D, and anisometropia greater than 1.00 D interocular difference in hyperopia, greater than 3.00 D interocular difference in myopia, or greater than 1.50 D interocular difference in astigmatism. The ability of each screening test to identify presence, type, and/or severity of significant RE was summarized by the area under the ROC curve (AUC) and calculated from weighted logistic regression models. For detection of each type of significant RE, AUC of each test was high; AUC was better for detecting the most severe levels of RE than for all REs considered important to detect (AUC 0.97-1.00 vs. 0.92-0.93). The area under the curve of each screening test was high for myopia (AUC 0.97-0.99). Noncycloplegic retinoscopy and Retinomax performed better than SureSight for hyperopia (AUC 0.92-0.99 and 0.90-0.98 vs. 0.85-0.94, P ≤ 0.02), Retinomax performed better than NCR for astigmatism greater than 1.50 D (AUC 0.95 vs. 0.90, P = 0.01), and SureSight performed better than Retinomax for anisometropia (AUC 0.85-1.00 vs. 0.76-0.96, P ≤ 0.07). Performance was similar for nurse and lay screeners in detecting any significant RE (AUC 0.92-1.00 vs. 0.92-0.99). Each test had a very high discriminatory power for detecting children with any significant RE.

Bioavailability of fluoride in drinking water: a human experimental study.

PubMed

Maguire, A; Zohouri, F V; Mathers, J C; Steen, I N; Hindmarch, P N; Moynihan, P J

2005-11-01

It has been suggested that systemic fluoride absorption from drinking water may be influenced by the type of fluoride compound in the water and by water hardness. Using a human double-blind cross-over trial, we conducted this study to measure c(max), T(max), and Area Under the Curve (AUC) for plasma F concentration against time, following the ingestion of naturally fluoridated hard and soft waters, artificially fluoridated hard and soft waters, and a reference water. Mean AUC over 0 to 8 hours was 1330, 1440, 1679, 1566, and 1328 ng F.min.mL(-1) for naturally fluoridated soft, naturally fluoridated hard, artificially fluoridated soft, artificially fluoridated hard, and reference waters, respectively, with no statistically significant differences among waters for AUC, c(max), or T(max). Any differences in fluoride bioavailability between drinking waters in which fluoride is present naturally or added artificially, or the waters are hard or soft, were small compared with large within- and between-subject variations in F absorption. Abbreviations used: F, fluoride; AUC, Area under the Curve for plasma F concentration against time; AUC(0-3), Area under the Curve for plasma F concentration against time for 0 to 3 hours following water ingestion; AUC(0-8), Area under the Curve for plasma F concentration against time for 0 to 8 hours following water ingestion; c(max), maximum plasma F concentration corrected for baseline plasma F and dose (i.e., F concentration of individual waters); T(max), time of c(max).

Effect of Truncating AUC at 12, 24 and 48 hr When Evaluating the Bioequivalence of Drugs with a Long Half-Life.

PubMed

Moreno, Isabel; Ochoa, Dolores; Román, Manuel; Cabaleiro, Teresa; Abad-Santos, Francisco

2016-01-01

Bioequivalence studies of drugs with a long half-life require long periods of time for pharmacokinetic sampling. The latest update of the European guideline allows the area under the curve (AUC) truncated at 72 hr to be used as an alternative to AUC0-t as the primary parameter. The objective of this study was to evaluate the effect of truncating the AUC at 48, 24 and 12 hr on the acceptance of the bioequivalence criterion as compared with truncation at 72 hr in bioequivalence trials. The effect of truncated AUC on the within-individual coefficient of variation (CVw) and on the ratio of the formulations was also analysed. Twenty-eight drugs were selected from bioequivalence trials. Pharmacokinetic data were analysed using WinNonLin 2.0 based on the trapezoidal method. Analysis of variance (ANOVA) was performed to obtain the ratios and 90% confidence intervals for AUC at different time-points. The degree of agreement of AUC0-72 in relation to AUC0-48 and AUC0-24, according to the Landis and Koch classification, was 'almost perfect'. Statistically significant differences were observed when the CVw of AUC truncated at 72, 48 and 24 hr was compared with the CVw of AUC0-12. There were no statistically significant differences in the AUC ratio at any time-point. Compared to AUC0-72, Pearson's correlation coefficient for mean AUC, AUC ratio and AUC CVw was worse for AUC0-12 than AUC0-24 or AUC0-48. These preliminary results could suggest that AUC truncation at 24 or 48 hr is adequate to determine whether two formulations are bioequivalent. © 2015 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Basal progesterone level as the main determinant of progesterone elevation on the day of hCG triggering in controlled ovarian stimulation cycles.

PubMed

Papaleo, Enrico; Corti, Laura; Vanni, Valeria Stella; Pagliardini, Luca; Ottolina, Jessica; De Michele, Francesca; La Marca, Antonio; Viganò, Paola; Candiani, Massimo

2014-07-01

Modest increases of serum progesterone at human chorionic gonadotrophin (hCG) administration in controlled ovarian hyperstimulation (COH) cycles have been shown to have a negative impact on pregnancy outcomes. The aim of this study was to identify early predictors of progesterone elevation at hCG. Pregnancy outcome of 303 consecutive patients undergoing COH and fresh day-3 embryo transfer was analysed. Considering the non-linear relationship between progesterone at hCG triggering and pregnancy outcomes, partial area under the curve (pAUC) analysis was used to implement marker identification potential of receiver operating characteristic (ROC) curve analysis. Multivariate logistic analysis was then performed to identify predictors of progesterone rise. Pregnancy outcomes could be predicted by pAUC analysis (pAUC = 0.58, 95 % CI 0.51-0.66, p = 0.02) and a significant detrimental cut-off could be calculated (progesterone at hCG > 1.35 ng/ml). Total dose of rFSH administered, E2 level at hCG but mostly basal progesterone level (OR = 12.21, 95 % CI 1.82-81.70) were predictors of progesterone rise above the cut-off. Basal progesterone is shown to be the main prognostic factor for progesterone elevation. This observation should be taken into consideration in the clinical management of IVF/ICSI cycles to improve pregnancy outcomes.

Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods

NASA Astrophysics Data System (ADS)

Chen, Xue; Li, Xiaohui; Yu, Xin; Chen, Deying; Liu, Aichun

2018-01-01

Diagnosis of malignancies is a challenging clinical issue. In this work, we present quick and robust diagnosis and discrimination of lymphoma and multiple myeloma (MM) using laser-induced breakdown spectroscopy (LIBS) conducted on human serum samples, in combination with chemometric methods. The serum samples collected from lymphoma and MM cancer patients and healthy controls were deposited on filter papers and ablated with a pulsed 1064 nm Nd:YAG laser. 24 atomic lines of Ca, Na, K, H, O, and N were selected for malignancy diagnosis. Principal component analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k nearest neighbors (kNN) classification were applied to build the malignancy diagnosis and discrimination models. The performances of the models were evaluated using 10-fold cross validation. The discrimination accuracy, confusion matrix and receiver operating characteristic (ROC) curves were obtained. The values of area under the ROC curve (AUC), sensitivity and specificity at the cut-points were determined. The kNN model exhibits the best performances with overall discrimination accuracy of 96.0%. Distinct discrimination between malignancies and healthy controls has been achieved with AUC, sensitivity and specificity for healthy controls all approaching 1. For lymphoma, the best discrimination performance values are AUC = 0.990, sensitivity = 0.970 and specificity = 0.956. For MM, the corresponding values are AUC = 0.986, sensitivity = 0.892 and specificity = 0.994. The results show that the serum-LIBS technique can serve as a quick, less invasive and robust method for diagnosis and discrimination of human malignancies.

Urinary neutrophil gelatinase-associated lipocalin for diagnosis and estimating activity in lupus nephritis: a meta-analysis.

PubMed

Fang, Y G; Chen, N N; Cheng, Y B; Sun, S J; Li, H X; Sun, F; Xiang, Y

2015-12-01

Urinary neutrophil gelatinase-associated lipocalin (uNGAL) is relatively specific in lupus nephritis (LN) patients. However, its diagnostic value has not been evaluated. The aim of this review was to determine the value of uNGAL for diagnosis and estimating activity in LN. A comprehensive search was performed on PubMed, EMBASE, Web of Knowledge, Cochrane electronic databases through December 2014. Meta-analysis of sensitivity and specificity was performed with a random-effects model. Additionally, summary receiver operating characteristic (SROC) curves and area under the curve (AUC) values were calculated. Fourteen studies were selected for this review. With respect to diagnosing LN, the pooled sensitivity and specificity were 73.6% (95% confidence interval (CI), 61.9-83.3) and 78.1% (95% CI, 69.0-85.6), respectively. The SROC-AUC value was 0.8632. Regarding estimating LN activity, the pooled sensitivity and specificity were 66.2% (95% CI, 60.4-71.7) and 62.1% (95% CI, 57.9-66.3), respectively. The SROC-AUC value was 0.7583. In predicting renal flares, the pooled sensitivity and specificity were 77.5% (95% CI, 68.1-85.1) and 65.3% (95% CI, 60.0-70.3), respectively. The SROC-AUC value was 0.7756. In conclusion, this meta-analysis indicates that uNGAL has relatively fair sensitivity and specificity in diagnosing LN, estimating LN activity and predicting renal flares, suggesting that uNGAL is a potential biomarker in diagnosing LN and monitoring LN activity. © The Author(s) 2015.

[Blood glucose and insulin responses to two hypocaloric enteral formulas in patients with diabetes mellitus type 2].

PubMed

de Luis, D A; Izaola, O; de la Fuente, B; Araújo, K

2013-01-01

The aim of this study is to compare the glycaemic and insulinemic response of type 2 diabetic patients after oral administration of 250 ml of two enteral formulas: a specific formula (Novasource Diabet Smartflex) against a standard isocaloric formula. The design was a cross-over study, with the diabetic patients (n = 15) receiving one of the two formulas in random order. Glycaemia and insulinemia curves were performed at 0, 10, 20, 30,60, 90,120,150 and 180 minutes. The variables studied were the area under the curve (AUC(0)-t), maximum concentration (Cmax), the time to reach maximum concentration (Tmax) and the concentrations of biochemical parameters in each study period. We studied 11 males (73.3%) and 4 females (26.7%), the mean age was 56.9 ± 10.9 years. Patients receiving Novasource Diabet showed a lower mean AUC(0)-t of glucose, mean difference - 4,753.26 mg/min/dl (95% CI: -7,256.7 to -2,249.82), also showed a mean insulinemia significantly lower AUC(0)-t, mean difference: 930.27 uU/min/ml (95% CI -1,696.34 to -164.2). The Cmax showed a significantly lower mean blood glucose levels with the specific formula, mean difference -26.89 mg/dl (95% CI -42.11 to -11.67) and insulin, mean difference: -5.39 uU/ml (95% CI: -10.37 to -1.43). The analysis shows that the mean Tmax of glucose with the specific formula are significantly lower, mean difference -19.82 min (95% CI: -32.11 to -7.33), however there was no difference in Tmax of insulin. Finally the analysis of glucose concentrations in the total study shows that the group with the specific formula has a lower mean glucose 25.77 mg / dl (95% CI 18.29 to 33.25), the same fact was detected with insulinemia 4.39 mU/ml (95% CI: 0.927 to 7.87). Diabetic patients treated diabet Novasource had significantly lower mean AUC0-t, Cmax and Tmax in blood glucose curves, also had lower mean AUC(0)-t and Cmax in insulin curves. Copyright © AULA MEDICA EDICIONES 2013. Published by AULA MEDICA. All rights reserved.

Differentiation of Recurrent Glioblastoma from Delayed Radiation Necrosis by Using Voxel-based Multiparametric Analysis of MR Imaging Data.

PubMed

Yoon, Ra Gyoung; Kim, Ho Sung; Koh, Myeong Ju; Shim, Woo Hyun; Jung, Seung Chai; Kim, Sang Joon; Kim, Jeong Hoon

2017-10-01

Purpose To assess a volume-weighted voxel-based multiparametric (MP) clustering method as an imaging biomarker to differentiate recurrent glioblastoma from delayed radiation necrosis. Materials and Methods The institutional review board approved this retrospective study and waived the informed consent requirement. Seventy-five patients with pathologic analysis-confirmed recurrent glioblastoma (n = 42) or radiation necrosis (n = 33) who presented with enlarged contrast material-enhanced lesions at magnetic resonance (MR) imaging after they completed concurrent chemotherapy and radiation therapy were enrolled. The diagnostic performance of the total MP cluster score was determined by using the area under the receiver operating characteristic curve (AUC) with cross-validation and compared with those of single parameter measurements (10% histogram cutoffs of apparent diffusion coefficient [ADC10] or 90% histogram cutoffs of normalized cerebral blood volume and initial time-signal intensity AUC). Results Receiver operating characteristic curve analysis showed that an AUC for differentiating recurrent glioblastoma from delayed radiation necrosis was highest in the total MP cluster score and lowest for ADC10 for both readers. The total MP cluster score had significantly better diagnostic accuracy than any single parameter (corrected P = .001-.039 for reader 1; corrected P = .005-.041 for reader 2). The total MP cluster score was the best predictor of recurrent glioblastoma (cross-validated AUCs, 0.942-0.946 for both readers), with a sensitivity of 95.2% for reader 1 and 97.6% for reader 2. Conclusion Quantitative analysis with volume-weighted voxel-based MP clustering appears to be superior to the use of single imaging parameters to differentiate recurrent glioblastoma from delayed radiation necrosis. © RSNA, 2017 Online supplemental material is available for this article.

Evaluating the Relationship between Vancomycin Trough Concentration and 24-Hour Area under the Concentration-Time Curve in Neonates.

PubMed

Tseng, Sheng-Hsuan; Lim, Chuan Poh; Chen, Qi; Tang, Cheng Cai; Kong, Sing Teang; Ho, Paul Chi-Lui

2018-04-01

Bacterial sepsis is a major cause of morbidity and mortality in neonates, especially those involving methicillin-resistant Staphylococcus aureus (MRSA). Guidelines by the Infectious Diseases Society of America recommend the vancomycin 24-h area under the concentration-time curve to MIC ratio (AUC 24 /MIC) of >400 as the best predictor of successful treatment against MRSA infections when the MIC is ≤1 mg/liter. The relationship between steady-state vancomycin trough concentrations and AUC 24 values (mg·h/liter) has not been studied in an Asian neonatal population. We conducted a retrospective chart review in Singapore hospitals and collected patient characteristics and therapeutic drug monitoring data from neonates on vancomycin therapy over a 5-year period. A one-compartment population pharmacokinetic model was built from the collected data, internally validated, and then used to assess the relationship between steady-state trough concentrations and AUC 24 A Monte Carlo simulation sensitivity analysis was also conducted. A total of 76 neonates with 429 vancomycin concentrations were included for analysis. Median (interquartile range) was 30 weeks (28 to 36 weeks) for postmenstrual age (PMA) and 1,043 g (811 to 1,919 g) for weight at the initiation of treatment. Vancomycin clearance was predicted by weight, PMA, and serum creatinine. For MRSA isolates with a vancomycin MIC of ≤1, our major finding was that the minimum steady-state trough concentration range predictive of achieving an AUC 24 /MIC of >400 was 8 to 8.9 mg/liter. Steady-state troughs within 15 to 20 mg/liter are unlikely to be necessary to achieve an AUC 24 /MIC of >400, whereas troughs within 10 to 14.9 mg/liter may be more appropriate. Copyright © 2018 American Society for Microbiology.

Initial Validation of a Comprehensive Assessment Instrument for Bereavement-Related Grief Symptoms and Risk of Complications: The Indicator of Bereavement Adaptation—Cruse Scotland (IBACS)

PubMed Central

Schut, Henk; Stroebe, Margaret S.; Wilson, Stewart; Birrell, John

2016-01-01

Objective This study assessed the validity of the Indicator of Bereavement Adaptation Cruse Scotland (IBACS). Designed for use in clinical and non-clinical settings, the IBACS measures severity of grief symptoms and risk of developing complications. Method N = 196 (44 male, 152 female) help-seeking, bereaved Scottish adults participated at two timepoints: T1 (baseline) and T2 (after 18 months). Four validated assessment instruments were administered: CORE-R, ICG-R, IES-R, SCL-90-R. Discriminative ability was assessed using ROC curve analysis. Concurrent validity was tested through correlation analysis at T1. Predictive validity was assessed using correlation analyses and ROC curve analysis. Optimal IBACS cutoff values were obtained by calculating a maximal Youden index J in ROC curve analysis. Clinical implications were compared across instruments. Results ROC curve analysis results (AUC = .84, p < .01, 95% CI between .77 and .90) indicated the IBACS is a good diagnostic instrument for assessing complicated grief. Positive correlations (p < .01, 2-tailed) with all four instruments at T1 demonstrated the IBACS' concurrent validity, strongest with complicated grief measures (r = .82). Predictive validity was shown to be fair in T2 ROC curve analysis results (n = 67, AUC = .78, 95% CI between .65 and .92; p < .01). Predictive validity was also supported by stable positive correlations between IBACS and other instruments at T2. Clinical indications were found not to differ across instruments. Conclusions The IBACS offers effective grief symptom and risk assessment for use by non-clinicians. Indications are sufficient to support intake assessment for a stepped model of bereavement intervention. PMID:27741246

Assessment of single-item literacy questions, age, and education level in the prediction of low health numeracy.

PubMed

Johnson, Tim V; Abbasi, Ammara; Kleris, Renee S; Ehrlich, Samantha S; Barthwaite, Echo; DeLong, Jennifer; Master, Viraj A

2013-08-01

Determining a patient's health literacy is important to optimum patient care. Single-item questions exist for screening written health literacy. We sought to assess the predictive potential of three common screening questions, along with patient age and education level, in the prediction of low health numerical literacy (numeracy). After demographic and educational information was obtained, 441 patients were administered three health literacy screening questions. The three-item Schwartz-Woloshin Numeracy Scale was then administered to assess for low health numeracy (score of 0 out of 3). This score served as the reference standard for Receiver Operating Characteristics (ROC) curve analysis. ROC curves were constructed and used to determine the area under the curve (AUC); a higher AUC suggests increased statistical significance. None of the three screening questions were significant predictors of low health numeracy. However, education level was a significant predictor of low health numeracy, with an AUC (95% CI) of 0.811 (0.720-0.902). This measure had a specificity of 95.3% at the cutoff of 12 years of education (<12 versus > or = 12 years of education) but was non-sensitive. Common single-item questions used to screen for written health literacy are ineffective screening tools for health numeracy. However, low education level is a specific predictor of low health numeracy.

CT-based radiomics signature for differentiating Borrmann type IV gastric cancer from primary gastric lymphoma.

PubMed

Ma, Zelan; Fang, Mengjie; Huang, Yanqi; He, Lan; Chen, Xin; Liang, Cuishan; Huang, Xiaomei; Cheng, Zixuan; Dong, Di; Liang, Changhong; Xie, Jiajun; Tian, Jie; Liu, Zaiyi

2017-06-01

To evaluate the value of CT-based radiomics signature for differentiating Borrmann type IV gastric cancer (GC) from primary gastric lymphoma (PGL). 40 patients with Borrmann type IV GC and 30 patients with PGL were retrospectively recruited. 485 radiomics features were extracted and selected from the portal venous CT images to build a radiomics signature. Subjective CT findings, including gastric wall peristalsis, perigastric fat infiltration, lymphadenopathy below the renal hila and enhancement pattern, were assessed to construct a subjective findings model. The radiomics signature, subjective CT findings, age and gender were integrated into a combined model by multivariate analysis. The diagnostic performance of these three models was assessed with receiver operating characteristics curves (ROC) and were compared using DeLong test. The subjective findings model, the radiomics signature and the combined model showed a diagnostic accuracy of 81.43% (AUC [area under the curve], 0.806; 95% CI [confidence interval]: 0.696-0.917; sensitivity, 63.33%; specificity, 95.00%), 84.29% (AUC, 0.886 [95% CI: 0.809-0.963]; sensitivity, 86.67%; specificity, 82.50%), 87.14% (AUC, 0.903 [95%CI: 0.831-0.975]; sensitivity, 70.00%; specificity, 100%), respectively. There were no significant differences in AUC among these three models (P=0.051-0.422). Radiomics analysis has the potential to accurately differentiate Borrmann type IV GC from PGL. Copyright © 2017 Elsevier B.V. All rights reserved.

Diagnostic value of stool DNA testing for multiple markers of colorectal cancer and advanced adenoma: a meta-analysis.

PubMed

Yang, Hua; Xia, Bing-Qing; Jiang, Bo; Wang, Guozhen; Yang, Yi-Peng; Chen, Hao; Li, Bing-Sheng; Xu, An-Gao; Huang, Yun-Bo; Wang, Xin-Ying

2013-08-01

The diagnostic value of stool DNA (sDNA) testing for colorectal neoplasms remains controversial. To compensate for the lack of large-scale unbiased population studies, a meta-analysis was performed to evaluate the diagnostic value of sDNA testing for multiple markers of colorectal cancer (CRC) and advanced adenoma. The PubMed, Science Direct, Biosis Review, Cochrane Library and Embase databases were systematically searched in January 2012 without time restriction. Meta-analysis was performed using a random-effects model using sensitivity, specificity, diagnostic OR (DOR), summary ROC curves, area under the curve (AUC), and 95% CIs as effect measures. Heterogeneity was measured using the χ(2) test and Q statistic; subgroup analysis was also conducted. A total of 20 studies comprising 5876 individuals were eligible. There was no heterogeneity for CRC, but adenoma and advanced adenoma harboured considerable heterogeneity influenced by risk classification and various detection markers. Stratification analysis according to risk classification showed that multiple markers had a high DOR for the high-risk subgroups of both CRC (sensitivity 0.759 [95% CI 0.711 to 0.804]; specificity 0.883 [95% CI 0.846 to 0.913]; AUC 0.906) and advanced adenoma (sensitivity 0.683 [95% CI 0.584 to 0.771]; specificity 0.918 [95% CI 0.866 to 0.954]; AUC 0.946) but not for the average-risk subgroups of either. In the methylation subgroup, sDNA testing had significantly higher DOR for CRC (sensitivity 0.753 [95% CI 0.685 to 0.812]; specificity 0.913 [95% CI 0.860 to 0.950]; AUC 0.918) and advanced adenoma (sensitivity 0.623 [95% CI 0.527 to 0.712]; specificity 0.926 [95% CI 0.882 to 0.958]; AUC 0.910) compared with the mutation subgroup. There was no significant heterogeneity among studies for subgroup analysis. sDNA testing for multiple markers had strong diagnostic significance for CRC and advanced adenoma in high-risk subjects. Methylation makers had more diagnostic value than mutation markers.

Contrast-enhanced transrectal ultrasound for prediction of prostate cancer aggressiveness: The role of normal peripheral zone time-intensity curves.

PubMed

Huang, Hui; Zhu, Zheng-Qiu; Zhou, Zheng-Guo; Chen, Ling-Shan; Zhao, Ming; Zhang, Yang; Li, Hong-Bo; Yin, Li-Ping

2016-12-08

To assess the role of time-intensity curves (TICs) of the normal peripheral zone (PZ) in the identification of biopsy-proven prostate nodules using contrast-enhanced transrectal ultrasound (CETRUS). This study included 132 patients with 134 prostate PZ nodules. Arrival time (AT), peak intensity (PI), mean transit time (MTT), area under the curve (AUC), time from peak to one half (TPH), wash in slope (WIS) and time to peak (TTP) were analyzed using multivariate linear logistic regression and receiver operating characteristic (ROC) curves to assess whether combining nodule TICs with normal PZ TICs improved the prediction of prostate cancer (PCa) aggressiveness. The PI, AUC (p < 0.001 for both), MTT and TPH (p = 0.011 and 0.040 respectively) values of the malignant nodules were significantly higher than those of the benign nodules. Incorporating the PI and AUC values (both, p < 0.001) of the normal PZ TIC, but not the MTT and TPH values (p = 0.076 and 0.159 respectively), significantly improved the AUC for prediction of malignancy (PI: 0.784-0.923; AUC: 0.758-0.891) and assessment of cancer aggressiveness (p < 0.001). Thus, all these findings indicate that incorporating normal PZ TICs with nodule TICs in CETRUS readings can improve the diagnostic accuracy for PCa and cancer aggressiveness assessment.

Validation of HOMA-IR in a model of insulin-resistance induced by a high-fat diet in Wistar rats.

PubMed

Antunes, Luciana C; Elkfury, Jessica L; Jornada, Manoela N; Foletto, Kelly C; Bertoluci, Marcello C

2016-04-01

Objective The present study aimed to validate homeostasis model assessment of insulin resistance (HOMA-IR) in relation to the insulin tolerance test (ITT) in a model of insulin-resistance in Wistar rats induced by a 19-week high-fat diet. Materials and methods A total of 30 male Wistar rats weighing 200-300 g were allocated into a high-fat diet group (HFD) (55% fat-enriched chow, ad lib, n = 15) and a standard-diet group (CD) standard chow, ad lib, n = 15), for 19 weeks. ITT was determined at baseline and in the 19th week. HOMA-IR was determined between the 18-19th week in three different days and the mean was considered for analysis. Area under the curve (AUC-ITT) of the blood glucose excursion along 120 minutes after intra-peritoneal insulin injection was determined and correlated with the corresponding fasting values for HOMA-IR. Results AUC-ITT and HOMA-IR were significantly greater after 19th week in HFD compared to CD (p < 0.001 for both). AUC-OGTT was also higher in HFD rats (p = 0.003). HOMA-IR was strongly correlated (Pearson's) with AUC-ITT r = 0.637; p < 0.0001. ROC curves of HOMA-IR and AUC-ITT showed similar sensitivity and specificity. Conclusion HOMA-IR is a valid measure to determine insulin-resistance in Wistar rats. Arch Endocrinol Metab. 2016;60(2):138-42.

Combination of cephalosporins with vancomycin or teicoplanin enhances antibacterial effect of glycopeptides against heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) and VISA.

PubMed

Lai, Chih-Cheng; Chen, Chi-Chung; Chuang, Yin-Ching; Tang, Hung-Jen

2017-01-31

Eight heterogeneous vancomycin-intermediate S. aureus (h-VISA) and seven VISA clinical isolates confirmed by the population analysis profile/area under the curve ratio (PAP/AUC) were collected. We further performed the PAP/AUC, time-killing methods and MIC tests using vancomycin/teicoplanin alone or combination with susceptible breakpoint concentrations of cefazolin, cefmetazole, cefotaxime, and cefepime for these isolates. The PAP/AUC MIC curve shifted left after addition of cephalosporins with vancomycin or teicoplanin for both h-VISA and VISA isolates. With the combination of different cephalosporins with vancomycin or teicoplanin, the AUC/Mu3 AUC ratio decreased to <0.9 for the standard Mu3 isolate which are compatible with the definition of vancomycin susceptible S. aureus. These decreases ranged between 1.81-2.02 and 2.37-2.85-fold for h-VISA treated with cephalosporins and vancomycin or teicoplanin, and 2.05-4.59, and 2.93-4,89-fold for VISA treated with cephalosporins with vancomycin or teicoplanin. As measured by time-killing assays, the combinations of different cephalosporins with vancomycin concentrations at 1/2 and 1/4 MIC, exhibited a bactericidal and bacteriostatic effect in VISA. The mean fold of MIC decline for vancomycin base combinations ranged from 1.81-3.83 and 2.71-9.33 for h-VISA and VISA, respectively. Overall, this study demonstrated the enhanced antibacterial activity of vancomycin/teicoplanin after adding cephalosporins against clinical h-VISA/VISA isolates.

Estimation of chloroform inhalation dose by other routes based on the relationship of area under the blood concentration-time curve (AUC)-inhalation dose to chloroform distribution in the blood of rats.

PubMed

Take, Makoto; Takeuchi, Tetsuya; Haresaku, Mitsuru; Matsumoto, Michiharu; Nagano, Kasuke; Yamamoto, Seigo; Takamura-Enya, Takeji; Fukushima, Shoji

2014-01-01

The present study investigated the time-course changes of concentration of chloroform (CHCl3) in the blood during and after exposure of male rats to CHCl3 by inhalation. Increasing the dose of CHCl3 in the inhalation exposed groups caused a commensurate increase in the concentration of CHCl3 in the blood and the area under the blood concentration-time curve (AUC). There was good correlation (r = 0.988) between the inhalation dose and the AUC/kg body weight. Based on the AUC/kg body weight-inhalation dose curve and the AUC/kg body weight after oral administration, inhalation equivalent doses of orally administered CHCl3 were calculated. Calculation of inhalation equivalent doses allows the body burden due to CHCl3 by inhalation exposure and oral exposure to be directly compared. This type of comparison facilitates risk assessment in humans exposed to CHCl3 by different routes. Our results indicate that when calculating inhalation equivalent doses of CHCl3, it is critical to include the AUC from the exposure period in addition to the AUC after the end of the exposure period. Thus, studies which measure the concentration of volatile organic compounds in the blood during the inhalation exposure period are crucial. The data reported here makes an important contribution to the physiologically based pharmacokinetic (PBPK) database of CHCl3 in rodents.

Application of impulse oscillometry and bronchial dilation test for analysis in patients with asthma and chronic obstructive pulmonary disease

PubMed Central

Li, Yueyue; Chen, Yang; Wang, Ping

2015-01-01

Impulse oscillometry (IOS) is a good method for measuring airway resistance. The aim of this study was to assess the diagnostic contribution of IOS combined with bronchial dilation test (BDT) when distinguishing between patients with asthma and those with chronic obstructive pulmonary disease (COPD). 870 were enrolled in the study including 561 patients with asthma, 100 patients with COPD and 209 patients with chronic coughing or normal subjects. All the participants underwent routine pulmonary function tests, IOS and BDT examination. And IOS examination was before and after BDT. IOS parameters (R5, R20, R25, R35, X5, X20, X25, X35, Fres, Zrs & RP) and forced expiratory volume in one second (FEV1) were recorded. Receiver operating characteristics (ROC) curve analysis was performed to evaluate the diagnostic ability to differentiate asthma and COPD. The discriminative power of the various parameters studied was determined by means of ROC curves: the area under the curve (AUC), sensitivity and specificity. The X5, X20, X25, X35, Fres, Zrs and Rp correlated better with COPD. In particular, X5, Fres and X25 have been found to be significantly correlated with COPD. The diagnostic efficiency of X5, Fres and X25 when diagnosis COPD, expressed by ROC curve parameters, was as follows: AUC (0.725, 0.730, 0.724), sensitivity (67%, 77%, 83%) and specificity (68%, 65%, 58%), respectively. The diagnostic efficiency of Zrs, R5 and X35 when diagnosis asthma, expressed by ROC curve parameters, was as follows: AUC (0.721, 0.710, 0.695), sensitivity (62%, 72%, 53%) and specificity (72%, 61%, 76%), respectively. Our findings show, that X5, X25 and Fres may be useful for predictions and evaluations for COPD. And R5, X35 and Zrs may provide useful IOS parameters for asthma. IOS combined BDT could be useful diagnostic and differential diagnosis between asthma and COPD. PMID:25785124

Application of impulse oscillometry and bronchial dilation test for analysis in patients with asthma and chronic obstructive pulmonary disease.

PubMed

Li, Yueyue; Chen, Yang; Wang, Ping

2015-01-01

Impulse oscillometry (IOS) is a good method for measuring airway resistance. The aim of this study was to assess the diagnostic contribution of IOS combined with bronchial dilation test (BDT) when distinguishing between patients with asthma and those with chronic obstructive pulmonary disease (COPD). 870 were enrolled in the study including 561 patients with asthma, 100 patients with COPD and 209 patients with chronic coughing or normal subjects. All the participants underwent routine pulmonary function tests, IOS and BDT examination. And IOS examination was before and after BDT. IOS parameters (R5, R20, R25, R35, X5, X20, X25, X35, Fres, Zrs & RP) and forced expiratory volume in one second (FEV1) were recorded. Receiver operating characteristics (ROC) curve analysis was performed to evaluate the diagnostic ability to differentiate asthma and COPD. The discriminative power of the various parameters studied was determined by means of ROC curves: the area under the curve (AUC), sensitivity and specificity. The X5, X20, X25, X35, Fres, Zrs and Rp correlated better with COPD. In particular, X5, Fres and X25 have been found to be significantly correlated with COPD. The diagnostic efficiency of X5, Fres and X25 when diagnosis COPD, expressed by ROC curve parameters, was as follows: AUC (0.725, 0.730, 0.724), sensitivity (67%, 77%, 83%) and specificity (68%, 65%, 58%), respectively. The diagnostic efficiency of Zrs, R5 and X35 when diagnosis asthma, expressed by ROC curve parameters, was as follows: AUC (0.721, 0.710, 0.695), sensitivity (62%, 72%, 53%) and specificity (72%, 61%, 76%), respectively. Our findings show, that X5, X25 and Fres may be useful for predictions and evaluations for COPD. And R5, X35 and Zrs may provide useful IOS parameters for asthma. IOS combined BDT could be useful diagnostic and differential diagnosis between asthma and COPD.

Limited sampling strategy for determining metformin area under the plasma concentration–time curve

PubMed Central

Santoro, Ana Beatriz; Stage, Tore Bjerregaard; Struchiner, Claudio José; Christensen, Mette Marie Hougaard; Brosen, Kim

2016-01-01

Aim The aim was to develop and validate limited sampling strategy (LSS) models to predict the area under the plasma concentration–time curve (AUC) for metformin. Methods Metformin plasma concentrations (n = 627) at 0–24 h after a single 500 mg dose were used for LSS development, based on all subsets linear regression analysis. The LSS‐derived AUC(0,24 h) was compared with the parameter ‘best estimate’ obtained by non‐compartmental analysis using all plasma concentration data points. Correlation between the LSS‐derived and the best estimated AUC(0,24 h) (r 2), bias and precision of the LSS estimates were quantified. The LSS models were validated in independent cohorts. Results A two‐point (3 h and 10 h) regression equation with no intercept estimated accurately the individual AUC(0,24 h) in the development cohort: r 2 = 0.927, bias (mean, 95% CI) –0.5, −2.7–1.8% and precision 6.3, 4.9–7.7%. The accuracy of the two point LSS model was verified in study cohorts of individuals receiving single 500 or 1000 mg (r 2 = –0.933–0.934) or seven 1000 mg daily doses (r 2 = 0.918), as well as using data from 16 published studies covering a wide range of metformin doses, demographics, clinical and experimental conditions (r 2 = 0.976). The LSS model reproduced previously reported results for effects of polymorphisms in OCT2 and MATE1 genes on AUC(0,24 h) and renal clearance of metformin. Conclusions The two point LSS algorithm may be used to assess the systemic exposure to metformin under diverse conditions, with reduced costs of sampling and analysis, and saving time for both subjects and investigators. PMID:27324407

Relationships of the Area under the Curve/MIC Ratio to Different Integral Endpoints of the Antimicrobial Effect: Gemifloxacin Pharmacodynamics in an In Vitro Dynamic Model

PubMed Central

Firsov, Alexander A.; Lubenko, Irene Y.; Portnoy, Yury A.; Zinner, Stephen H.; Vostrov, Sergey N.

2001-01-01

Most integral endpoints of the antimicrobial effect are determined over an arbitrarily chosen time period, such as the dosing interval (τ), regardless of the actual effect duration. Unlike the τ-related endpoints, the intensity of the antimicrobial effect (IE) does consider its duration—from time zero to the time when bacterial counts on the regrowth curve achieve the same maximal numbers as in the absence of the antimicrobial. To examine the possible impact of this fundamental difference on the relationships of the antimicrobial effect to the ratio of the area under the concentration-time curve (AUC) to the MIC, a clinical isolate of Staphylococcus aureus was exposed to simulated gemifloxacin pharmacokinetics over a 40-fold range of AUC/MIC ratios, from 11 to 466 h. In each run, IE and four τ-related endpoints, including the area under the time-kill curve (AUBC), the area above the curve (AAC), the area between the control growth and time-kill curves (ABBC), and the ABBC related to the area under the control growth curve (AUGC), were calculated for τ = 24 h. Unlike the IE, which displayed pseudolinear relationships with the AUC/MIC ratio; each τ-related endpoint showed a distinct saturation at potentially therapeutic AUC/MIC ratios (116 to 466 h) when the antimicrobial effect persisted longer than τ. This saturation results from the underestimation of the true effect and may be eliminated if ABBC, AAC, and AUBC (but not AUGC) are modified and determined in the same manner as the IE to consider the actual effect duration. These data suggest a marginal value of the τ-related endpoints as indices of the total antimicrobial effect. Since all of them respond to AUC/MIC ratio changes less than the IE, the latter is preferable in comparative pharmacodynamic studies. PMID:11181382

The Diagnostic Value of Gastrin-17 Detection in Atrophic Gastritis

PubMed Central

Wang, Xu; Ling, Li; Li, Shanshan; Qin, Guiping; Cui, Wei; Li, Xiang; Ni, Hong

2016-01-01

Abstract A meta-analysis was performed to assess the diagnostic value of gastrin-17 (G-17) for the early detection of chronic atrophic gastritis (CAG). An extensive literature search was performed, with the aim of selecting publications that reported the accuracy of G-17 in predicting CAG, in the following databases: PubMed, Science Direct, Web of Science, Chinese Biological Medicine, Chinese National Knowledge Infrastructure, Wanfang, and VIP. To assess the diagnostic value of G-17, the following statistics were estimated and described: sensitivity, specificity, diagnostic odds ratios (DOR), summary receiver operating characteristic curves, area under the curve (AUC), and 95% confidence intervals (CIs). Thirteen studies that met the inclusion criteria were included in this meta-analysis, comprising 894 patients and 1950 controls. The pooled sensitivity and specificity of these studies were 0.48 (95% CI: 0.45–0.51) and 0.79 (95% CI: 0.77–0.81), respectively. The DOR was 5.93 (95% CI: 2.93–11.99), and the AUC was 0.82. G-17 may have potential diagnostic value because it has good specificity and a moderate DOR and AUC for CAG. However, more studies are needed to improve the sensitivity of this diagnostic tool in the future. PMID:27149493

Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression.

PubMed

Kraus, Virginia Byers; Feng, Sheng; Wang, ShengChu; White, Scott; Ainslie, Maureen; Brett, Alan; Holmes, Anthony; Charles, H Cecil

2009-12-01

To evaluate the effectiveness of using subchondral bone texture observed on a radiograph taken at baseline to predict progression of knee osteoarthritis (OA) over a 3-year period. A total of 138 participants in the Prediction of Osteoarthritis Progression study were evaluated at baseline and after 3 years. Fractal signature analysis (FSA) of the medial subchondral tibial plateau was performed on fixed flexion radiographs of 248 nonreplaced knees, using a commercially available software tool. OA progression was defined as a change in joint space narrowing (JSN) or osteophyte formation of 1 grade according to a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new model based on correlating the overall shape of a fractal dimension curve with radius. Fractal signature of the medial tibial plateau at baseline was predictive of medial knee JSN progression (area under the curve [AUC] 0.75, of a receiver operating characteristic curve) but was not predictive of osteophyte formation or progression of JSN in the lateral compartment. Traditional covariates (age, sex, body mass index, knee pain), general bone mineral content, and joint space width at baseline were no more effective than random variables for predicting OA progression (AUC 0.52-0.58). The predictive model with maximum effectiveness combined fractal signature at baseline, knee alignment, traditional covariates, and bone mineral content (AUC 0.79). We identified a prognostic marker of OA that is readily extracted from a plain radiograph using FSA. Although the method needs to be validated in a second cohort, our results indicate that the global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression.

Decomposing genomic variance using information from GWA, GWE and eQTL analysis.

PubMed

Ehsani, A; Janss, L; Pomp, D; Sørensen, P

2016-04-01

A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the overall variance into subcomponents may provide further insight into the genetic basis of complex traits. To test this approach, we performed a whole-genome variance components analysis and partitioned the genomic variance using information from GWA, GWE and eQTL analyses of growth-related traits in a mouse F2 population. We characterized the mouse trait genetic architecture by ordering single nucleotide polymorphisms (SNPs) based on their P-values and studying the areas under the curve (AUCs). The observed traits were found to have a genomic variance profile that differed significantly from that expected of a trait under an infinitesimal model. This situation was particularly true for both body weight and body fat, for which the AUCs were much higher compared with that of glucose. In addition, SNPs with a high degree of trait-specific regulatory potential (SNPs associated with subset of transcripts that significantly associated with a specific trait) explained a larger proportion of the genomic variance than did SNPs with high overall regulatory potential (SNPs associated with transcripts using traditional eQTL analysis). We introduced AUC measures of genomic variance profiles that can be used to quantify relative importance of SNPs as well as degree of deviation of a trait's inheritance from an infinitesimal model. The shape of the curve aids global understanding of traits: The steeper the left-hand side of the curve, the fewer the number of SNPs controlling most of the phenotypic variance. © 2015 Stichting International Foundation for Animal Genetics.

Prediction of the severity of acute pancreatitis on admission by urinary trypsinogen activation peptide: A meta-analysis

PubMed Central

Huang, Wei; Altaf, Kiran; Jin, Tao; Xiong, Jun-Jie; Wen, Li; Javed, Muhammad A; Johnstone, Marianne; Xue, Ping; Halloran, Christopher M; Xia, Qing

2013-01-01

AIM: To undertake a meta-analysis on the value of urinary trypsinogen activation peptide (uTAP) in predicting severity of acute pancreatitis on admission. METHODS: Major databases including Medline, Embase, Science Citation Index Expanded and the Cochrane Central Register of Controlled Trials in the Cochrane Library were searched to identify all relevant studies from January 1990 to January 2013. Pooled sensitivity, specificity and the diagnostic odds ratios (DORs) with 95%CI were calculated for each study and were compared to other systems/biomarkers if mentioned within the same study. Summary receiver-operating curves were conducted and the area under the curve (AUC) was evaluated. RESULTS: In total, six studies of uTAP with a cut-off value of 35 nmol/L were included in this meta-analysis. Overall, the pooled sensitivity and specificity of uTAP for predicting severity of acute pancreatitis, at time of admission, was 71% and 75%, respectively (AUC = 0.83, DOR = 8.67, 95%CI: 3.70-20.33). When uTAP was compared with plasma C-reactive protein, the pooled sensitivity, specificity, AUC and DOR were 0.64 vs 0.67, 0.77 vs 0.75, 0.82 vs 0.79 and 6.27 vs 6.32, respectively. Similarly, the pooled sensitivity, specificity, AUC and DOR of uTAP vs Acute Physiology and Chronic Health Evaluation II within the first 48 h of admission were found to be 0.64 vs 0.69, 0.77 vs 0.61, 0.82 vs 0.73 and 6.27 vs 4.61, respectively. CONCLUSION: uTAP has the potential to act as a stratification marker on admission for differentiating disease severity of acute pancreatitis. PMID:23901239

NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

PubMed

Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

2015-10-15

In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to systematically reveal multi-biomarker panel from genomic and clinical data. It can serve as a useful tool to identify prognostic biomarkers for survival analysis. NCC-AUC is available at http://doc.aporc.org/wiki/NCC-AUC. ywang@amss.ac.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Beyond the morphology of the glucose curve following an oral glucose tolerance test in obese youth.

PubMed

Nolfe, Giuseppe; Spreghini, Maria Rita; Sforza, Rita Wietrzycowska; Morino, Giuseppe; Manco, Melania

2012-01-01

To describe the morphology of glucose curve during the oral glucose tolerance test (OGTT) and any association with glucose tolerance, insulin action and secretion in obese youth. Cross-sectional. OGTT data of 553 patients were analysed. Subjects were divided in groups based on the morphology (i.e. monophasic, biphasic, triphasic and upward monotonous) of glucose curve. Insulin action was estimated by the homeostasis model assessment of insulin resistance, the insulin sensitivity, the muscle insulin sensitivity and the hepatic insulin resistance indexes (HIRI), and the oral glucose insulin sensitivity (OGIS). Insulin secretion was estimated by the insulinogenic index (IGI). Disposition index, including the insulin secretion-sensitivity index-2, and areas under glucose (AUC(G)) and insulin (AUC(I)) curves were computed. In patients with normal glucose tolerance (n=522), prevalent morphology of the glucose curve was monophasic (n=285, 54%). Monophasic morphology was associated with the highest concentration of 1 h plasma glucose (P<0.0001) and AUC(G) (P<0.0001); biphasic morphology with better insulin sensitivity as estimated by OGIS (P<0.03) and lower AUC(I) (P<0.0001); triphasic morphology with the highest values of HIRI (P<0.02) and IGI (P<0.007). By combining morphologies of glucose and insulin curves or time of the glucose peak, a deeper characterisation of different phenotypes of glucose metabolism emerged. Morphologies of the glucose curve seem reflecting different metabolic phenotypes of insulin action and secretion, particularly when combined with morphologies of insulin curve or time of glucose peak. Such findings may deserve validation in cohort study, in which glucose metabolism would be estimated by using gold standard techniques.

A Comparison of Frailty Indexes for the Prediction of Falls, Disability, Fractures and Mortality in Older Men

PubMed Central

Ensrud, Kristine E.; Ewing, Susan K.; Cawthon, Peggy M.; Fink, Howard A.; Taylor, Brent C.; Cauley, Jane A.; Dam, Thuy-Tien; Marshall, Lynn M.; Orwoll, Eric S.; Cummings, Steven R.

2010-01-01

Objective To compare validity of a parsimonious frailty index (components: weight loss, inability to rise from a chair, and poor energy [SOF index]) with that of the more complex CHS index (components: unintentional weight loss, low grip strength, poor energy, slowness, and low physical activity) for prediction of adverse outcomes in older men. Design Prospective cohort study Setting Six U.S. centers Participants 3132 men ≥67 years Measurements Men classified as robust, intermediate stage or frail using SOF index and criteria similar to those used in CHS index. Falls reported tri-annually for 1 year. Disability (≥1 new impairment in performing IADL) ascertained at 1 year. Fractures and deaths ascertained during 3 years of follow-up. Area under the curve (AUC) statistics from receiver operating characteristic curve analysis compared for models containing SOF index versus CHS index. Results Greater evidence of frailty as defined by either index was associated with increased risks of adverse outcomes. Frail men had a higher age-adjusted risk of recurrent falls (odds ratio [OR] 3.0–3.6), disability (OR 5.3–7.5), nonspine fracture (hazards ratio [HR] 2.2–2.3), and death (HR 2.5–3.5) (P<0.001 for all models). AUC comparisons revealed no differences between models with SOF index versus models with CHS index in discriminating falls (AUC=0.63, P= 0.97), disability (AUC=0.68, P=0.86), nonspine fracture (AUC=0.63, P=0.90), or death (AUC=0.71 for model with SOF index and 0.72 for model with CHS index, P=0.19). Conclusion The simple SOF index predicts risk of falls, disability, fracture and mortality in men as well as the more complex CHS index. PMID:19245414

Association of peak factor VIII levels and area under the curve with bleeding in patients with haemophilia A on every third day pharmacokinetic-guided prophylaxis.

PubMed

Valentino, L A; Pipe, S W; Collins, P W; Blanchette, V S; Berntorp, E; Fischer, K; Ewenstein, B M; Oh, M; Spotts, G

2016-07-01

We previously showed that pharmacokinetic-guided prophylaxis (PKP) allows the dosing interval to be extended while maintaining a specific trough level. However, the associations of peak factor VIII (FVIII) levels and area under the curve (AUC) with breakthrough bleeding have not been investigated. The aim of this study was to analyse data from the PKP arm to determine whether peak FVIII levels, AUC and time with FVIII levels in a haemostatically effective range are independent predictors of bleeding during prophylaxis. Post hoc analysis of the association of FVIII levels and AUC with annualized bleeding rate in 34 patients on PKP. During 1 year of PKP, 131 bleeding episodes occurred in 24/34 patients. Average peak FVIII levels ranged from 24 to 168 IU dL(-1) , with higher values associated with a decreased risk for all bleeding (joint and non-joint; P < 0.01) and joint bleeding (P < 0.01). Following rFVIII infusion, median percent of time spent with FVIII levels >20 IU dL(-1) was 22%; median AUC was 1363. Both values were significantly associated with a lower ABR when targeting a 1% trough at 72 h. When PKP was administered every third day, higher peak FVIII levels, higher AUC and more time spent per week with FVIII levels >20 IU dL(-1) provided increased protection from joint and non-joint bleeding. These data highlight the potential impact of variability in individual pharmacokinetic and bleeding risk and support the need for high peak levels and AUC in some patients treated every third day. The findings do not necessarily apply to alternate-day or other prophylactic dosing regimens. © 2016 The Authors. Haemophilia Published by John Wiley & Sons Ltd.

High-frequency Electrocardiogram Analysis in the Ability to Predict Reversible Perfusion Defects during Adenosine Myocardial Perfusion Imaging

NASA Technical Reports Server (NTRS)

Tragardh, Elin; Schlegel, Todd T.; Carlsson, Marcus; Pettersson, Jonas; Nilsson, Klas; Pahlm, Olle

2007-01-01

Background: A previous study has shown that analysis of high-frequency QRS components (HF-QRS) is highly sensitive and reasonably specific for detecting reversible perfusion defects on myocardial perfusion imaging (MPI) scans during adenosine. The purpose of the present study was to try to reproduce those findings. Methods: 12-lead high-resolution electrocardiogram recordings were obtained from 100 patients before (baseline) and during adenosine Tc-99m-tetrofosmin MPI tests. HF-QRS were analyzed regarding morphology and changes in root mean square (RMS) voltages from before the adenosine infusion to peak infusion. Results: The best area under the curve (AUC) was found in supine patients (AUC=0.736) in a combination of morphology and RMS changes. None of the measurements, however, were statistically better than tossing a coin (AUC=0.5). Conclusion: Analysis of HF-QRS was not significantly better than tossing a coin for determining reversible perfusion defects on MPI scans.

Accuracy of Noncycloplegic Retinoscopy, Retinomax Autorefractor, and SureSight Vision Screener for Detecting Significant Refractive Errors

PubMed Central

Kulp, Marjean Taylor; Ying, Gui-shuang; Huang, Jiayan; Maguire, Maureen; Quinn, Graham; Ciner, Elise B.; Cyert, Lynn A.; Orel-Bixler, Deborah A.; Moore, Bruce D.

2014-01-01

Purpose. To evaluate, by receiver operating characteristic (ROC) analysis, the ability of noncycloplegic retinoscopy (NCR), Retinomax Autorefractor (Retinomax), and SureSight Vision Screener (SureSight) to detect significant refractive errors (RE) among preschoolers. Methods. Refraction results of eye care professionals using NCR, Retinomax, and SureSight (n = 2588) and of nurse and lay screeners using Retinomax and SureSight (n = 1452) were compared with masked cycloplegic retinoscopy results. Significant RE was defined as hyperopia greater than +3.25 diopters (D), myopia greater than 2.00 D, astigmatism greater than 1.50 D, and anisometropia greater than 1.00 D interocular difference in hyperopia, greater than 3.00 D interocular difference in myopia, or greater than 1.50 D interocular difference in astigmatism. The ability of each screening test to identify presence, type, and/or severity of significant RE was summarized by the area under the ROC curve (AUC) and calculated from weighted logistic regression models. Results. For detection of each type of significant RE, AUC of each test was high; AUC was better for detecting the most severe levels of RE than for all REs considered important to detect (AUC 0.97–1.00 vs. 0.92–0.93). The area under the curve of each screening test was high for myopia (AUC 0.97–0.99). Noncycloplegic retinoscopy and Retinomax performed better than SureSight for hyperopia (AUC 0.92–0.99 and 0.90–0.98 vs. 0.85–0.94, P ≤ 0.02), Retinomax performed better than NCR for astigmatism greater than 1.50 D (AUC 0.95 vs. 0.90, P = 0.01), and SureSight performed better than Retinomax for anisometropia (AUC 0.85–1.00 vs. 0.76–0.96, P ≤ 0.07). Performance was similar for nurse and lay screeners in detecting any significant RE (AUC 0.92–1.00 vs. 0.92–0.99). Conclusions. Each test had a very high discriminatory power for detecting children with any significant RE. PMID:24481262

Potential role of TCF7L2 gene variants on cardiac sympathetic/parasympathetic activity.

PubMed

Boccardi, Virginia; Ambrosino, Immacolata; Papa, Michela; Fiore, Daniela; Rizzo, Maria Rosaria; Paolisso, Giuseppe; Barbieri, Michelangela

2010-12-01

Variants in transcription factor 7-like 2 (266096218TCF7L2266096218USuser266096218Gene names have been italicized per house style. Please check and confirm whether there are other instances that need to be italicized or instances where italics have been inappropriately applied.) gene have been found strongly associated with an increased risk of type 2 diabetes, as well as with an impairment of glucagon-like peptide-1 (GLP-1) signalling chain. In rats, stimulation of central GLP-1 receptors increases heart rate and activates autonomic regulatory neurons. We aimed to evaluate the potential role of TCF7L2 gene polymorphisms on sympathovagal response in relation to changes in plasma insulin and/or GLP-1 concentration after glucose ingestion. Genotyping was performed for rs12255372 and rs7903146 TCF7L2 gene variants in 250 non-related healthy volunteers (mean age 27±3 years). Consistent with previous reports, both single-nucleotide polymorphisms were in strong linkage disequilibrium (D'=0.87, r(2)=0.76). A subset of 167 patients underwent an oral glucose tolerance test while a continuous recording of heart rate variability was performed. At baseline, no differences in fasting plasma insulin, in GLP-1 levels and in LF/HF (low frequency/high frequency) ratio between the three genotypes were found. Along with glucose ingestion TT subjects had lower INS(AUC) (insulin area under curve), as well as higher LF/HF(AUC) (LF/HF area under curve) values. No difference in GLP-1(AUC) (GLP-1 area under curve) between TCF7L2 gene variants was found. A multivariate analysis including multiple covariates showed that only INS(AUC,) GLP-1(AUC) and TCF7L2 gene variants were independently associated with LF/HF(AUC). In conclusion, TT genotype of rs12255372 and rs7903146 TCF7L2 gene variants is associated with lower insulin secretion and higher cardiosympathetic activity. Moreover, such effect is independent of GLP-1 and insulin plasma concentrations suggesting a potential role of such gene variants in increasing cardiovascular risk through enhanced sympathetic nervous system activity.

A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.

PubMed

Feng, Dai; Cortese, Giuliana; Baumgartner, Richard

2017-12-01

The receiver operating characteristic (ROC) curve is frequently used as a measure of accuracy of continuous markers in diagnostic tests. The area under the ROC curve (AUC) is arguably the most widely used summary index for the ROC curve. Although the small sample size scenario is common in medical tests, a comprehensive study of small sample size properties of various methods for the construction of the confidence/credible interval (CI) for the AUC has been by and large missing in the literature. In this paper, we describe and compare 29 non-parametric and parametric methods for the construction of the CI for the AUC when the number of available observations is small. The methods considered include not only those that have been widely adopted, but also those that have been less frequently mentioned or, to our knowledge, never applied to the AUC context. To compare different methods, we carried out a simulation study with data generated from binormal models with equal and unequal variances and from exponential models with various parameters and with equal and unequal small sample sizes. We found that the larger the true AUC value and the smaller the sample size, the larger the discrepancy among the results of different approaches. When the model is correctly specified, the parametric approaches tend to outperform the non-parametric ones. Moreover, in the non-parametric domain, we found that a method based on the Mann-Whitney statistic is in general superior to the others. We further elucidate potential issues and provide possible solutions to along with general guidance on the CI construction for the AUC when the sample size is small. Finally, we illustrate the utility of different methods through real life examples.

IV busulfan dose individualization in children undergoing hematopoietic stem cell transplant: limited sampling strategies.

PubMed

Dupuis, L Lee; Sibbald, Cathryn; Schechter, Tal; Ansari, Marc; Gassas, Adam; Théorêt, Yves; Kassir, Nastya; Champagne, Martin A; Doyle, John

2008-05-01

We currently calculate area under the busulfan concentration time curve (AUC) using 7 plasma busulfan concentrations (AUC7) drawn after the first of 16 i.v. busulfan doses given as a 2-hour infusion every 6 hours. The aim of this study was to develop and validate limited sampling strategies (LSSs) using 3 or fewer busulfan concentration values with which to reliably calculate AUC in children undergoing hematopoietic stem cell transplant (HSCT). Children in the development group (44) received i.v. busulfan at Sick Kids; the validation group consisted of 35 children who received care at CHU Ste-Justine. Busulfan doses given and subsequent plasma busulfan concentrations were recorded. LSSs using 1 to 3 concentration-time points were developed using multiple linear regression. LSS were considered to be acceptable when adjusted r(2) > 0.9, mean bias <15% and precision <15%. Extent of agreement between the AUC7 values and the LSS AUC was assessed by the intraclass correlation coefficient (ICC) and Bland-Altman (BA) analysis. Agreement was considered to be excellent when the lower limit of the 95% confidence limit of the ICC exceeded 0.9 and when the limits of agreement in the BA analysis were +/-15% for both AUC and dose. Administration of the theoretic adjusted busulfan doses based on each LSS was simulated and cases where the resulting AUC was >1500 or <900 microM x min were noted. LSSs using 1, 2, or 3 plasma busulfan concentrations were developed that showed excellent agreement with AUC7 and adjusted busulfan doses. In the validation sample, only the 2- and 3-point LSSs demonstrated acceptable precision and lack of bias. LSSs using 2 or 3 plasma busulfan concentrations can be used to reliably estimate busulfan AUC after IV administration in children undergoing HSCT.

Performance of procalcitonin in diagnosing parapneumonic pleural effusions: A clinical study and meta-analysis.

PubMed

He, Chao; Wang, Bo; Li, Danni; Xu, Huan; Shen, Yongchun

2017-08-01

Parapneumonic pleural effusion (PPE) is a common complication of pneumonia. The accurate diagnosis of PPE remains a challenge. Recent studies suggest that procalcitonin (PCT) emerges as a potential biomarker for PPE. Our study aimed to determine the diagnostic value of PCT for PPE by a clinical study and summarize the overall diagnostic performance of PCT through a meta-analysis. Demographic and clinical data of the patients with PPE and controls were collected in our clinical study. The diagnostic performances of serum PCT (s-PCT) were analyzed via receiver operating characteristic (ROC) curve analysis, using area under the curve (AUC) as a measure of accuracy. Literature databases were systematically searched for the studies examining the accuracy of PCT for diagnosing PPE. Data on sensitivity, specificity, positive/negative likelihood ratio (PLR/NLR), and diagnostic odds ratio (DOR) were pooled. Summary ROC curves and AUC were used to evaluate overall test performance. In our clinical study, 47 patients with PPE and 101 controls were included. The s-PCT levels were significantly increased in the setting of PPE (5.44 ± 9.82 ng/mL) compared with malignant PE (0.15 ± 0.19 ng/mL), tuberculous PE (0.18 ± 0.16 ng/mL), and transudates (0.09 ± 0.03 ng/mL) (P < .001). Using a cutoff value of 0.195 ng/mL, the sensitivity and specificity of s-PCT in diagnosing PPE were 0.83 and 0.80, respectively, and AUC was 0.89. In addition, 11 studies were included in our meta-analysis. Summary performance estimates for s-PCT in diagnosing PPE were as follows: sensitivity, 0.78 (95% CI: 0.71-0.84); specificity, 0.74 (95% CI: 0.69-0.78); PLR, 3.46 (95% CI: 2.09-5.74); NLR, 0.27 (95% CI: 0.14-0.54); DOR, 12.37 (95% CI: 4.34-41.17); and AUC, 0.84. The corresponding estimates for p-PCT were as follows: sensitivity, 0.62 (95% CI: 0.57-0.67); specificity, 0.71 (95% CI: 0.68-0.75); PLR 2.31 (95% CI: 1.81-2.95); NLR, 0.47 (95% CI: 0.35-0.63); DOR, 5.48 (95% CI: 3.07-9.77); and AUC, 0.80. Both s-PCT and p-PCT might have modest performance in diagnosing PPE. However, more studies on a large scale should be performed to confirm our findings.

Joint confidence region estimation for area under ROC curve and Youden index.

PubMed

Yin, Jingjing; Tian, Lili

2014-03-15

In the field of diagnostic studies, the area under the ROC curve (AUC) serves as an overall measure of a biomarker/diagnostic test's accuracy. Youden index, defined as the overall correct classification rate minus one at the optimal cut-off point, is another popular index. For continuous biomarkers of binary disease status, although researchers mainly evaluate the diagnostic accuracy using AUC, for the purpose of making diagnosis, Youden index provides an important and direct measure of the diagnostic accuracy at the optimal threshold and hence should be taken into consideration in addition to AUC. Furthermore, AUC and Youden index are generally correlated. In this paper, we initiate the idea of evaluating diagnostic accuracy based on AUC and Youden index simultaneously. As the first step toward this direction, this paper only focuses on the confidence region estimation of AUC and Youden index for a single marker. We present both parametric and non-parametric approaches for estimating joint confidence region of AUC and Youden index. We carry out extensive simulation study to evaluate the performance of the proposed methods. In the end, we apply the proposed methods to a real data set. Copyright © 2013 John Wiley & Sons, Ltd.

Role of CYP24A1, VDR and GC gene polymorphisms on deferasirox pharmacokinetics and clinical outcomes.

PubMed

Allegra, S; Cusato, J; De Francia, S; Arduino, A; Longo, F; Pirro, E; Massano, D; De Nicolò, A; Piga, A; D'Avolio, A

2018-05-22

β-Thalassemia patients develop deficiency in vitamin D absorption and liver hydroxylation, resulting in extremely low calcitriol levels. We explored the role of single-nucleotide polymorphisms (SNPs) involved in vitamin D metabolism, transport and activity on deferasirox pharmacokinetics and outcomes (effectiveness trough levels (C trough ) and the area under the curve (AUC) cutoffs of 20 μg ml -1 and 360 μg ml -1  h -1 , respectively; nonresponse AUC limit of 250 μg ml -1  h -1 ). Ninety-nine β-thalassemic patients were enrolled. Drug plasma C trough and AUC were measured by the high-performance liquid chromatography system coupled with an ultraviolet determination method. Allelic discrimination for VDR, CYP24A1, CYP27B1 and GC gene SNPs was performed by real-time PCR. CYP24A1 22776 TT significantly influenced C min and negatively predicted it in regression analysis. CYP24A1 3999 CC was associated with C trough and C min and was a negative predictor of T max , whereas CYP24A1 8620 GG seemed to have a role in C trough , AUC, t 1/2 and C min , and was an AUC negative predictor factor. Considering treatment outcome, Cdx2 and GC 1296 were retained in regression analysis as AUC efficacy cutoff negative predictors.

Development and Validation of the PREMM5 Model for Comprehensive Risk Assessment of Lynch Syndrome.

PubMed

Kastrinos, Fay; Uno, Hajime; Ukaegbu, Chinedu; Alvero, Carmelita; McFarland, Ashley; Yurgelun, Matthew B; Kulke, Matthew H; Schrag, Deborah; Meyerhardt, Jeffrey A; Fuchs, Charles S; Mayer, Robert J; Ng, Kimmie; Steyerberg, Ewout W; Syngal, Sapna

2017-07-01

Purpose Current Lynch syndrome (LS) prediction models quantify the risk to an individual of carrying a pathogenic germline mutation in three mismatch repair (MMR) genes: MLH1, MSH2, and MSH6. We developed a new prediction model, PREMM 5 , that incorporates the genes PMS2 and EPCAM to provide comprehensive LS risk assessment. Patients and Methods PREMM 5 was developed to predict the likelihood of a mutation in any of the LS genes by using polytomous logistic regression analysis of clinical and germline data from 18,734 individuals who were tested for all five genes. Predictors of mutation status included sex, age at genetic testing, and proband and family cancer histories. Discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), and clinical impact was determined by decision curve analysis; comparisons were made to the existing PREMM 1,2,6 model. External validation of PREMM 5 was performed in a clinic-based cohort of 1,058 patients with colorectal cancer. Results Pathogenic mutations were detected in 1,000 (5%) of 18,734 patients in the development cohort; mutations included MLH1 (n = 306), MSH2 (n = 354), MSH6 (n = 177), PMS2 (n = 141), and EPCAM (n = 22). PREMM 5 distinguished carriers from noncarriers with an AUC of 0.81 (95% CI, 0.79 to 0.82), and performance was similar in the validation cohort (AUC, 0.83; 95% CI, 0.75 to 0.92). Prediction was more difficult for PMS2 mutations (AUC, 0.64; 95% CI, 0.60 to 0.68) than for other genes. Performance characteristics of PREMM 5 exceeded those of PREMM 1,2,6 . Decision curve analysis supported germline LS testing for PREMM 5 scores ≥ 2.5%. Conclusion PREMM 5 provides comprehensive risk estimation of all five LS genes and supports LS genetic testing for individuals with scores ≥ 2.5%. At this threshold, PREMM 5 provides performance that is superior to the existing PREMM 1,2,6 model in the identification of carriers of LS, including those with weaker phenotypes and individuals unaffected by cancer.

Development and Validation of the PREMM5 Model for Comprehensive Risk Assessment of Lynch Syndrome

PubMed Central

Uno, Hajime; Ukaegbu, Chinedu; Alvero, Carmelita; McFarland, Ashley; Yurgelun, Matthew B.; Kulke, Matthew H.; Schrag, Deborah; Meyerhardt, Jeffrey A.; Fuchs, Charles S.; Mayer, Robert J.; Ng, Kimmie; Steyerberg, Ewout W.; Syngal, Sapna

2017-01-01

Purpose Current Lynch syndrome (LS) prediction models quantify the risk to an individual of carrying a pathogenic germline mutation in three mismatch repair (MMR) genes: MLH1, MSH2, and MSH6. We developed a new prediction model, PREMM5, that incorporates the genes PMS2 and EPCAM to provide comprehensive LS risk assessment. Patients and Methods PREMM5 was developed to predict the likelihood of a mutation in any of the LS genes by using polytomous logistic regression analysis of clinical and germline data from 18,734 individuals who were tested for all five genes. Predictors of mutation status included sex, age at genetic testing, and proband and family cancer histories. Discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), and clinical impact was determined by decision curve analysis; comparisons were made to the existing PREMM1,2,6 model. External validation of PREMM5 was performed in a clinic-based cohort of 1,058 patients with colorectal cancer. Results Pathogenic mutations were detected in 1,000 (5%) of 18,734 patients in the development cohort; mutations included MLH1 (n = 306), MSH2 (n = 354), MSH6 (n = 177), PMS2 (n = 141), and EPCAM (n = 22). PREMM5 distinguished carriers from noncarriers with an AUC of 0.81 (95% CI, 0.79 to 0.82), and performance was similar in the validation cohort (AUC, 0.83; 95% CI, 0.75 to 0.92). Prediction was more difficult for PMS2 mutations (AUC, 0.64; 95% CI, 0.60 to 0.68) than for other genes. Performance characteristics of PREMM5 exceeded those of PREMM1,2,6. Decision curve analysis supported germline LS testing for PREMM5 scores ≥ 2.5%. Conclusion PREMM5 provides comprehensive risk estimation of all five LS genes and supports LS genetic testing for individuals with scores ≥ 2.5%. At this threshold, PREMM5 provides performance that is superior to the existing PREMM1,2,6 model in the identification of carriers of LS, including those with weaker phenotypes and individuals unaffected by cancer. PMID:28489507

Fragments of Citrullinated and MMP-degraded Vimentin and MMP-degraded Type III Collagen Are Novel Serological Biomarkers to Differentiate Crohn's Disease from Ulcerative Colitis.

PubMed

Mortensen, Joachim Høg; Godskesen, Line Elbjerg; Jensen, Michael Dam; Van Haaften, Wouter Tobias; Klinge, Lone Gabriels; Olinga, Peter; Dijkstra, Gerard; Kjeldsen, Jens; Karsdal, Morten Asser; Bay-Jensen, Anne-Christine; Krag, Aleksander

2015-10-01

A hallmark of inflammatory bowel disease [IBD] is chronic inflammation, which leads to excessive extracellular matrix [ECM] remodelling and release of specific protein fragments, called neoepitopes. We speculated that the biomarker profile panel for ulcerative colitis [UC] and Crohn's disease [CD] represent a heterogeneous expression pattern, and may be applied as a tool to aid in the differentiation between UC and CD. Serum biomarkers of degraded collagens I, III-IV [C1M, C3M, and C4M], collagen type 1 and IV formation [P1NP, P4NP], and citrullinated and MMP-degraded vimentin [VICM] were studied with a competitive ELISA assay system in a cohort including 164 subjects [CD n = 72, UC n = 60, and non-IBD controls n = 32] and a validation cohort of 61 subjects [CD n = 46, and UC n = 15]. Receiver operating characteristic curve analysis and logistic regression modelling were carried out to evaluate the discriminative power of the biomarkers. All biomarkers were corrected for confounding factors. VICM and C3M demonstrated the highest diagnostic power, alone, to differentiate CD from UC with an area under the curve [AUC] of 0.77 and 0.69, respectively. Furthermore, the biomarkers C1M [AUC = 0.81], C3M [AUC = 0.83], VICM [AUC = 0.83], and P1NP [AUC = 0.77] were best to differentiate UC from non-IBD. The best combinations of biomarkers to differentiate CD from UC and UC from non-IBD were VICM, C3M, C4M [AUC = 0.90] and VICM, C3M [AUC = 0.98] respectively. Specific extracellular matrix degradation markers are elevated in IBD and can discriminate CD from UC and UC from non-IBD controls with a high diagnostic accuracy. Copyright © 2015 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Prospective multi-institutional study evaluating the performance of prostate cancer risk calculators.

PubMed

Nam, Robert K; Kattan, Michael W; Chin, Joseph L; Trachtenberg, John; Singal, Rajiv; Rendon, Ricardo; Klotz, Laurence H; Sugar, Linda; Sherman, Christopher; Izawa, Jonathan; Bell, David; Stanimirovic, Aleksandra; Venkateswaran, Vasundara; Diamandis, Eleftherios P; Yu, Changhong; Loblaw, D Andrew; Narod, Steven A

2011-08-01

Prostate cancer risk calculators incorporate many factors to evaluate an individual's risk for prostate cancer. We validated two common North American-based, prostate cancer risk calculators. We conducted a prospective, multi-institutional study of 2,130 patients who underwent a prostate biopsy for prostate cancer detection from five centers. We evaluated the performance of the Sunnybrook nomogram-based prostate cancer risk calculator (SRC) and the Prostate Cancer Prevention Trial (PCPT) -based risk calculator (PRC) to predict the presence of any cancer and high-grade cancer. We examined discrimination, calibration, and decision curve analysis techniques to evaluate the prediction models. Of the 2,130 patients, 867 men (40.7%) were found to have cancer, and 1,263 (59.3%) did not have cancer. Of the patients with cancer, 403 (46.5%) had a Gleason score of 7 or more. The area under the [concentration-time] curve (AUC) for the SRC was 0.67 (95% CI, 0.65 to 0.69); the AUC for the PRC was 0.61 (95% CI, 0.59 to 0.64). The AUC was higher for predicting aggressive disease from the SRC (0.72; 95% CI, 0.70 to 0.75) compared with that from the PRC (0.67; 95% CI, 0.64 to 0.70). Decision curve analyses showed that the SRC performed better than the PRC for risk thresholds of more than 30% for any cancer and more than 15% for aggressive cancer. The SRC performed better than the PRC, but neither one added clinical benefit for risk thresholds of less than 30%. Further research is needed to improve the AUCs of the risk calculators, particularly for higher-grade cancer.

Tools to identify linear combination of prognostic factors which maximizes area under receiver operator curve.

PubMed

Todor, Nicolae; Todor, Irina; Săplăcan, Gavril

2014-01-01

The linear combination of variables is an attractive method in many medical analyses targeting a score to classify patients. In the case of ROC curves the most popular problem is to identify the linear combination which maximizes area under curve (AUC). This problem is complete closed when normality assumptions are met. With no assumption of normality search algorithm are avoided because it is accepted that we have to evaluate AUC n(d) times where n is the number of distinct observation and d is the number of variables. For d = 2, using particularities of AUC formula, we described an algorithm which lowered the number of evaluations of AUC from n(2) to n(n-1) + 1. For d > 2 our proposed solution is an approximate method by considering equidistant points on the unit sphere in R(d) where we evaluate AUC. The algorithms were applied to data from our lab to predict response of treatment by a set of molecular markers in cervical cancers patients. In order to evaluate the strength of our algorithms a simulation was added. In the case of no normality presented algorithms are feasible. For many variables computation time could be increased but acceptable.

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer.

PubMed

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Chang, Shu-Shya; Rau, Cheng-Shyuan; Tai, Hsueh-Ling; Peng, Shu-Hui; Lin, Yi-Chun; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-03-02

The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR). There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score. ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P <0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance. The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer.

Combination of cephalosporins with vancomycin or teicoplanin enhances antibacterial effect of glycopeptides against heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) and VISA

PubMed Central

Lai, Chih-Cheng; Chen, Chi-Chung; Chuang, Yin-Ching; Tang, Hung-Jen

2017-01-01

Eight heterogeneous vancomycin-intermediate S. aureus (h-VISA) and seven VISA clinical isolates confirmed by the population analysis profile/area under the curve ratio (PAP/AUC) were collected. We further performed the PAP/AUC, time-killing methods and MIC tests using vancomycin/teicoplanin alone or combination with susceptible breakpoint concentrations of cefazolin, cefmetazole, cefotaxime, and cefepime for these isolates. The PAP/AUC MIC curve shifted left after addition of cephalosporins with vancomycin or teicoplanin for both h-VISA and VISA isolates. With the combination of different cephalosporins with vancomycin or teicoplanin, the AUC/Mu3 AUC ratio decreased to <0.9 for the standard Mu3 isolate which are compatible with the definition of vancomycin susceptible S. aureus. These decreases ranged between 1.81–2.02 and 2.37–2.85-fold for h-VISA treated with cephalosporins and vancomycin or teicoplanin, and 2.05–4.59, and 2.93–4,89-fold for VISA treated with cephalosporins with vancomycin or teicoplanin. As measured by time-killing assays, the combinations of different cephalosporins with vancomycin concentrations at 1/2 and 1/4 MIC, exhibited a bactericidal and bacteriostatic effect in VISA. The mean fold of MIC decline for vancomycin base combinations ranged from 1.81–3.83 and 2.71–9.33 for h-VISA and VISA, respectively. Overall, this study demonstrated the enhanced antibacterial activity of vancomycin/teicoplanin after adding cephalosporins against clinical h-VISA/VISA isolates. PMID:28139739

Diagnostic performance of qualitative shear-wave elastography according to different color map opacities for breast masses.

PubMed

Kim, Hana; Youk, Ji Hyun; Gweon, Hye Mi; Kim, Jeong-Ah; Son, Eun Ju

2013-08-01

To compare the diagnostic performance of qualitative shear-wave elastography (SWE) according to three different color map opacities for breast masses 101 patients aged 21-77 years with 113 breast masses underwent B-mode US and SWE under three different color map opacities (50%, 19% and 100%) before biopsy or surgery. Following SWE features were reviewed: visual pattern classification (pattern 1-4), color homogeneity (Ehomo) and six-point color score of maximum elasticity (Ecol). Combined with B-mode US and SWE, the likelihood of malignancy (LOM) was also scored. The area under the curve (AUC) was obtained by ROC curve analysis to assess the diagnostic performance under each color opacity. A visual color pattern, Ehomo, Ecol and LOM scoring were significantly different between benign and malignant lesions under all color opacities (P<0.001). For 50% opacity, AUCs of visual color pattern, Ecol, Ehomo and LOM scoring were 0.902, 0.951, 0.835 and 0.975. But, for each SWE feature, there was no significant difference in the AUC among three different color opacities. For all color opacities, visual color pattern and Ecol showed significantly higher AUC than Ehomo. In addition, a combined set of B-mode US and SWE showed significantly higher AUC than SWE alone for color patterns, Ehomo, but no significant difference was found in Ecol. Qualitative SWE was useful to differentiate benign from malignant breast lesion under all color opacities. The difference in color map opacity did not significantly influence diagnostic performance of SWE. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

[Successful cyclosporine treatment in 2 patients with refractory CIDP, involving monitoring of both AUC(0-4h) and trough levels].

PubMed

Takeuchi, Akiko; Shirai, Shinichi; Horiuchi, Kazuhiro; Takahashi, Ikuko; Matsushima, Masaaki; Hirotani, Makoto; Kano, Takahiro; Yabe, Ichiro; Matumoto, Akihisa; Sasaki, Hidenao

2012-01-01

Cyclosporine A (CYA) treatment has been reported to be probably useful for patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) that is resistant to conventional treatment. Although several studies have shown that appropriate area under the concentration-time curve (AUC) monitoring of CYA levels results in improved outcomes for refractory nephrotic syndrome patients, the importance of using AUC analysis for CIDP remains unclear. In this study, we measured both trough and AUC from 0 to 4 h (AUC(0-4 h)) levels of CYA in 2 patients with CIDP and compared the findings for the clinical parameters. On the basis of the CYA dosing recommendations for patients with nephrotic syndrome, we used a CYA concentration of 150 ng/ml for the trough level and an AUC(0-4 h) value of 2,500 ng/(ml·h). Patient 1 showed a significant increase in grip strength and a prolonged remission period. Patient 2 showed improvement in the modified Rankin scale and manual muscle test (MMT) scores. Monitoring both AUC(0-4 h) and trough levels of CYA seems to be a better option than monitoring the trough level alone because it leads to improved estimation of the efficacy and safety of CYA treatment in the case of CIDP patients.

Intranasal Pharmacokinetic Data for Triptans Such as Sumatriptan and Zolmitriptan Can Render Area Under the Curve (AUC) Predictions for the Oral Route: Strategy Development and Application.

PubMed

Srinivas, Nuggehally R; Syed, Muzeeb

2016-01-01

Limited pharmacokinetic sampling strategy may be useful for predicting the area under the curve (AUC) for triptans and may have clinical utility as a prospective tool for prediction. Using appropriate intranasal pharmacokinetic data, a Cmax vs. AUC relationship was established by linear regression models for sumatriptan and zolmitriptan. The predictions of the AUC values were performed using published mean/median Cmax data and appropriate regression lines. The quotient of observed and predicted values rendered fold-difference calculation. The mean absolute error (MAE), mean positive error (MPE), mean negative error (MNE), root mean square error (RMSE), correlation coefficient (r), and the goodness of the AUC fold prediction were used to evaluate the two triptans. Also, data from the mean concentration profiles at time points of 1 hour (sumatriptan) and 3 hours (zolmitriptan) were used for the AUC prediction. The Cmax vs. AUC models displayed excellent correlation for both sumatriptan (r = .9997; P < .001) and zolmitriptan (r = .9999; P < .001). Irrespective of the two triptans, the majority of the predicted AUCs (83%-85%) were within 0.76-1.25-fold difference using the regression model. The prediction of AUC values for sumatriptan or zolmitriptan using the concentration data that reflected the Tmax occurrence were in the proximity of the reported values. In summary, the Cmax vs. AUC models exhibited strong correlations for sumatriptan and zolmitriptan. The usefulness of the prediction of the AUC values was established by a rigorous statistical approach.

The absorption of chlortetracycline following transscrotal instillation for the treatment of primary hydrocele testis.

PubMed

Bødker, A; Rasmussen, T B; Christensen, M B

1991-04-01

We describe the absorption of chlortetracycline from the emptied hydrocele sac, which was instilled to treat a primary hydrocele of the testis. The study included 7 patients and 2 control subjects who were given 500 mg. chlortetracycline. Plasma concentration was determined at 0, 1/2, 1, 2, 4, 6, 12 and 24 hours after instillation, and in 2 patients plasma levels also were determined at 48 and 72 hours. The area under the plasma concentration-time curve (AUC1) was calculated in each case by using the trapezoidal rule. In the control group the plasma level was determined at 0, 1, 2, 4 and 6 hours after instillation. The area under the plasma concentration-time curve (AUC2) was calculated by the formula AUC2 = Co/Kc. The fraction F of absorption can be expressed as F = AUC1/AUC2; median F = 0.67 (range 0.41 to 0.92). We conclude that chlortetracycline passes readily and almost completely through the tunica vaginalis lining the hydrocele sac.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

PubMed

Sidhu, Harbir S; Benigno, Salvatore; Ganeshan, Balaji; Dikaios, Nikos; Johnston, Edward W; Allen, Clare; Kirkham, Alex; Groves, Ashley M; Ahmed, Hashim U; Emberton, Mark; Taylor, Stuart A; Halligan, Steve; Punwani, Shonit

2017-06-01

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.

PubMed

Jafarzadeh, S Reza; Johnson, Wesley O; Gardner, Ian A

2016-03-15

The area under the receiver operating characteristic (ROC) curve (AUC) is used as a performance metric for quantitative tests. Although multiple biomarkers may be available for diagnostic or screening purposes, diagnostic accuracy is often assessed individually rather than in combination. In this paper, we consider the interesting problem of combining multiple biomarkers for use in a single diagnostic criterion with the goal of improving the diagnostic accuracy above that of an individual biomarker. The diagnostic criterion created from multiple biomarkers is based on the predictive probability of disease, conditional on given multiple biomarker outcomes. If the computed predictive probability exceeds a specified cutoff, the corresponding subject is allocated as 'diseased'. This defines a standard diagnostic criterion that has its own ROC curve, namely, the combined ROC (cROC). The AUC metric for cROC, namely, the combined AUC (cAUC), is used to compare the predictive criterion based on multiple biomarkers to one based on fewer biomarkers. A multivariate random-effects model is proposed for modeling multiple normally distributed dependent scores. Bayesian methods for estimating ROC curves and corresponding (marginal) AUCs are developed when a perfect reference standard is not available. In addition, cAUCs are computed to compare the accuracy of different combinations of biomarkers for diagnosis. The methods are evaluated using simulations and are applied to data for Johne's disease (paratuberculosis) in cattle. Copyright © 2015 John Wiley & Sons, Ltd.

A minimally invasive system for glucose area under the curve measurement using interstitial fluid extraction technology: evaluation of the accuracy and usefulness with oral glucose tolerance tests in subjects with and without diabetes.

PubMed

Sakaguchi, Kazuhiko; Hirota, Yushi; Hashimoto, Naoko; Ogawa, Wataru; Sato, Toshiyuki; Okada, Seiki; Hagino, Kei; Asakura, Yoshihiro; Kikkawa, Yasuo; Kojima, Junko; Maekawa, Yasunori; Nakajima, Hiromu

2012-06-01

Recent studies have highlighted the importance of managing postprandial hyperglycemia, but adequate monitoring of postprandial glucose remains difficult because of wide variations in levels. We have therefore developed a minimally invasive system to monitor postprandial glucose area under the curve (AUC). This system involves no blood sampling and uses interstitial fluid glucose (IG) AUC (IG-AUC) as a surrogate marker of postprandial glucose. This study aimed to evaluate the usefulness of this system by comparing data with the findings of oral glucose tolerance tests (OGTTs) in subjects with and without diabetes. The glucose AUC monitoring system was validated by OGTTs in 37 subjects with and 10 subjects without diabetes. A plastic microneedle array was stamped on the forearm to extract IG. A hydrogel patch was then placed on the pretreated area to accumulate IG. Glucose and sodium ion concentrations in the hydrogel were measured to calculate IG-AUC at 2-h postload glucose. Plasma glucose (PG) levels were measured every 30 min to calculate reference PG-AUC. IG-AUC correlated strongly with reference PG-AUC (r=0.93) over a wide range. The level of correlation between IG-AUC and maximum PG level was also high (r=0.86). The painless nature of the technique was confirmed by the response of patients to questionnaires. The glucose AUC monitoring system using IG provided good estimates of reference PG-AUC and maximum PG level during OGTTs in subjects with and without diabetes. This system provides easy-to-use monitoring of glucose AUC, which is a good indicator of postprandial glucose.

Diagnostic efficiency of truncated area under the curve from 0 to 2 h (AUC₀₋₂) of mycophenolic acid in kidney transplant recipients receiving mycophenolate mofetil and concomitant tacrolimus.

PubMed

Lampón, Natalia; Tutor-Crespo, María J; Romero, Rafael; Tutor, José C

2011-07-01

Recently, the use of the truncated area under the curve from 0 to 2 h (AUC(0-2)) of mycophenolic acid (MPA) has been proposed for therapeutic monitoring in liver transplant recipients. The aim of our study was the evaluation of the clinical usefulness of truncated AUC(0-2) in kidney transplant patients. Plasma MPA was measured in samples taken before the morning dose of mycophenolate mofetil, and one-half and 2 h post-dose, completing 63 MPA concentration-time profiles from 40 adult kidney transplant recipients. The AUC from 0 to 12 h (AUC(0-12)) was calculated using the validated algorithm of Pawinski et al. The truncated AUC(0-2) was calculated using the linear trapezoidal rule, and extrapolated to 0-12 h (trapezoidal extrapolated AUC(0-12)) as previously described. Algorithm calculated and trapezoidal extrapolated AUC(0-12) values showed high correlation (r=0.995) and acceptable dispersion (ma68=0.71 μg·h/mL), median prediction error (6.6%) and median absolute prediction error (12.6%). The truncated AUC(0-2) had acceptable diagnostic efficiency (87%) in the classification of subtherapeutic, therapeutic or supratherapeutic values with respect to AUC(0-12). However, due to the high inter-individual variation of the drug absorption-rate, the dispersion between both pharmacokinetic variables (ma68=6.9 μg·h/mL) was unacceptable. The substantial dispersion between truncated AUC(0-2) and AUC(0-12) values may be a serious objection for the routine use of MPA AUC(0-2) in clinical practice.

Diagnostic value of tumor markers for lung adenocarcinoma-associated malignant pleural effusion: a validation study and meta-analysis.

PubMed

Feng, Mei; Zhu, Jing; Liang, Liqun; Zeng, Ni; Wu, Yanqiu; Wan, Chun; Shen, Yongchun; Wen, Fuqiang

2017-04-01

Pleural effusion is one of the most common complications of lung adenocarcinoma and is diagnostically challenging. This study aimed to investigate the diagnostic performance of carcinoembryonic antigen (CEA), cytokeratin fragment (CYFRA) 21-1, and cancer antigen (CA) 19-9 for lung adenocarcinoma-associated malignant pleural effusion (MPE) through a validation study and meta-analysis. Pleural effusion samples were collected from 81 lung adenocarcinoma-associated MPEs and 96 benign pleural effusions. CEA, CYFRA 21-1, and CA19-9 were measured by electrochemiluminescence immunoassay. The capacity of tumor markers was assessed with receiver operating characteristic curve analyses and the area under the curve (AUC) was calculated. Standard methods for meta-analysis of diagnostic studies were used to summarize the diagnostic performance of CEA, CYFRA 21-1, and CA19-9 for lung adenocarcinoma-associated MPE. The pleural levels of CEA, CYFRA 21-1, and CA19-9 were significantly increased in lung adenocarcinoma-associated MPE compared to benign pleural effusion. The cut-off points for CEA, CYFRA 21-1, and CA19-9 were optimally set at 4.55 ng/ml, 43.10 μg/ml, and 12.89 U/ml, and corresponding AUCs were 0.93, 0.85, and 0.81, respectively. The combination of CEA, CYFRA 21-1, and CA19-9 increased the sensitivity to 95.06%, with an AUC of 0.95. Eight studies were included in this meta-analysis. CEA showed the best diagnostic performance with pooled sensitivity, specificity, positive/negative likelihood ratio, and diagnostic odds ratio of 0.75, 0.96, 16.01, 0.23, and 81.49, respectively. The AUC was 0.93. CEA, CYFRA 21-1, and CA19-9 play a role in the diagnosis of lung adenocarcinoma-associated MPE. The combination of these tumor markers increases the diagnostic accuracy.

Arterial injuries after penetrating brain injury in civilians: risk factors on admission head computed tomography.

PubMed

Bodanapally, Uttam K; Saksobhavivat, Nitima; Shanmuganathan, Kathirkamanathan; Aarabi, Bizhan; Roy, Ashis K

2015-01-01

The object of this study was to determine the specific CT findings of the injury profile in penetrating brain injury (PBI) that are risk factors related to intracranial arterial injuries. The authors retrospectively evaluated admission head CTs and accompanying digital subtraction angiography (DSA) studies from patients with penetrating trauma to the head in the period between January 2005 and December 2012. Two authors reviewed the CT images to determine the presence or absence of 30 injury profile variables and quantified selected variables. The CT characteristics in patients with and without arterial injuries were compared using univariate analysis, multivariate analysis, and receiver operating characteristic (ROC) curve analysis to determine the respective risk factors, independent predictors, and optimal threshold values for the continuous variables. Fifty-five patients were eligible for study inclusion. The risk factors for an intracranial arterial injury on univariate analysis were an entry wound over the frontobasal-temporal regions, a bihemispheric wound trajectory, a wound trajectory in proximity to the circle of Willis (COW), a subarachnoid hemorrhage (SAH), a higher SAH score, an intraventricular hemorrhage (IVH), and a higher IVH score. A trajectory in proximity to the COW was the best predictor of injury (OR 6.8 and p = 0.005 for all penetrating brain injuries [PBIs]; OR 13.3 and p = 0.001 for gunshot wounds [GSWs]). Significant quantitative variables were higher SAH and IVH scores. An SAH score of 3 (area under the ROC curve [AUC] for all PBIs 0.72; AUC for GSWs 0.71) and an IVH score of 3 (AUC for all PBIs 0.65; AUC for GSWs 0.65) could be used as threshold values to suggest an arterial injury. The risk factors identified may help radiologists suggest the possibility of arterial injury and prioritize neurointerventional consultation and potential DSA studies.

Evaluation of erythrocyte dysmorphism by light microscopy with lowering of the condenser lens: A simple and efficient method.

PubMed

Barros Silva, Gyl Eanes; Costa, Roberto Silva; Ravinal, Roberto Cuan; Saraiva e Silva, Jucélia; Dantas, Marcio; Coimbra, Terezila Machado

2010-03-01

To demonstrate that the evaluation of erythrocyte dysmorphism by light microscopy with lowering of the condenser lens (LMLC) is useful to identify patients with a haematuria of glomerular or non-glomerular origin. A comparative double-blind study between phase contrast microscopy (PCM) and LMLC is reported to evaluate the efficacy of these techniques. Urine samples of 39 patients followed up for 9 months were analyzed, and classified as glomerular and non-glomerular haematuria. The different microscopic techniques were compared using receiver-operator curve (ROC) analysis and area under curve (AUC). Reproducibility was assessed by coefficient of variation (CV). Specific cut-offs were set for each method according to their best rate of specificity and sensitivity as follows: 30% for phase contrast microscopy and 40% for standard LMLC, reaching in the first method the rate of 95% and 100% of sensitivity and specificity, respectively, and in the second method the rate of 90% and 100% of sensitivity and specificity, respectively. In ROC analysis, AUC for PCM was 0.99 and AUC for LMLC was 0.96. The CV was very similar in glomerular haematuria group for PCM (35%) and LMLC (35.3%). LMLC proved to be effective in contributing to the direction of investigation of haematuria, toward the nephrological or urological side. This method can substitute PCM when this equipment is not available.

Usefulness of Time-Point Serum Cortisol and ACTH Measurements for the Adjustment of Glucocorticoid Replacement in Adrenal Insufficiency.

PubMed

Rousseau, Elise; Joubert, Michael; Trzepla, Géraldine; Parienti, Jean Jacques; Freret, Thomas; Vanthygem, Marie Christine; Desailloud, Rachel; Lefebvre, Hervé; Coquerel, Antoine; Reznik, Yves

2015-01-01

Adjustment of daily hydrocortisone dose on clinical criteria lacks sensitivity for fine tuning. Long term hydrocortisone (HC) over-replacement may lead to increased morbidity and mortality in patients with adrenal insufficiency (AI). Biochemical criteria may help detecting over- or under-replacement but have been poorly evaluated. Multicenter, institutional, pharmacokinetic study on ACTH and cortisol plasma profiles during HC replacement in 27 AI patients compared to 29 matched controls. All AI patients were administered HC thrice daily at doses of 6, 10 and 14 mg/m2/d. Blood samples were drawn hourly from 0800h to 1900h. The main outcome measures were: i) plasma peak cortisol and cortisol area under the curve (AUC) in AI patients compared to controls, ii) correlations between cortisol AUC vs single-point cortisol or ACTH decrease from baseline (ΔACTH) and iii) the predictive value of the two latters for obtaining AI patients' cortisol AUC in the control range. Cortisol peaks were observed 1h after each HC intake and a dose response was demonstrated for cortisol peak and cortisol AUC. The comparison of AI patients' cortisol AUC to controls showed that 81.5% AI patients receiving 6mg/m2/d were adequately replaced, whereas most patients receiving higher doses were over-replaced. The correlation coefficient between 1000h/1400h cortisol concentrations and 0800-1900h cortisol AUC were 0.93/0.88 respectively, whereas the 0800-1200h ΔACTH fairly correlated with 0800-1900h cortisol AUC (R = 0.57). ROC curve analysis indicated that the 1000h and 1400h cortisol concentrations best predicted over-replacement. Patients receiving a 6mg/m2 hydrocortisone daily dose exhibited the most physiological daytime cortisol profile. Single point plasma cortisol correlated with daytime cortisol AUC in AI patients. Although hydrocortisone dose should be currently determined on clinical grounds, our data suggest that single point plasma cortisol may be an adjunct for further hydrocortisone dose adjustment in AI patients.

Usefulness of Time-Point Serum Cortisol and ACTH Measurements for the Adjustment of Glucocorticoid Replacement in Adrenal Insufficiency

PubMed Central

Trzepla, Géraldine; Parienti, Jean Jacques; Freret, Thomas; Vanthygem, Marie Christine; Desailloud, Rachel; Lefebvre, Hervé; Coquerel, Antoine; Reznik, Yves

2015-01-01

Background Adjustment of daily hydrocortisone dose on clinical criteria lacks sensitivity for fine tuning. Long term hydrocortisone (HC) over-replacement may lead to increased morbidity and mortality in patients with adrenal insufficiency (AI). Biochemical criteria may help detecting over- or under-replacement but have been poorly evaluated. Methods Multicenter, institutional, pharmacokinetic study on ACTH and cortisol plasma profiles during HC replacement in 27 AI patients compared to 29 matched controls. All AI patients were administered HC thrice daily at doses of 6, 10 and 14 mg/m2/d. Blood samples were drawn hourly from 0800h to 1900h. The main outcome measures were: i) plasma peak cortisol and cortisol area under the curve (AUC) in AI patients compared to controls, ii) correlations between cortisol AUC vs single-point cortisol or ACTH decrease from baseline (ΔACTH) and iii) the predictive value of the two latters for obtaining AI patients’ cortisol AUC in the control range. Results Cortisol peaks were observed 1h after each HC intake and a dose response was demonstrated for cortisol peak and cortisol AUC. The comparison of AI patients’ cortisol AUC to controls showed that 81.5% AI patients receiving 6mg/m2/d were adequately replaced, whereas most patients receiving higher doses were over-replaced. The correlation coefficient between 1000h/1400h cortisol concentrations and 0800-1900h cortisol AUC were 0.93/0.88 respectively, whereas the 0800-1200h ΔACTH fairly correlated with 0800-1900h cortisol AUC (R = 0.57). ROC curve analysis indicated that the 1000h and 1400h cortisol concentrations best predicted over-replacement. Conclusions Patients receiving a 6mg/m2 hydrocortisone daily dose exhibited the most physiological daytime cortisol profile. Single point plasma cortisol correlated with daytime cortisol AUC in AI patients. Although hydrocortisone dose should be currently determined on clinical grounds, our data suggest that single point plasma cortisol may be an adjunct for further hydrocortisone dose adjustment in AI patients. PMID:26317782

Validating a Predictive Model of Acute Advanced Imaging Biomarkers in Ischemic Stroke.

PubMed

Bivard, Andrew; Levi, Christopher; Lin, Longting; Cheng, Xin; Aviv, Richard; Spratt, Neil J; Lou, Min; Kleinig, Tim; O'Brien, Billy; Butcher, Kenneth; Zhang, Jingfen; Jannes, Jim; Dong, Qiang; Parsons, Mark

2017-03-01

Advanced imaging to identify tissue pathophysiology may provide more accurate prognostication than the clinical measures used currently in stroke. This study aimed to derive and validate a predictive model for functional outcome based on acute clinical and advanced imaging measures. A database of prospectively collected sub-4.5 hour patients with ischemic stroke being assessed for thrombolysis from 5 centers who had computed tomographic perfusion and computed tomographic angiography before a treatment decision was assessed. Individual variable cut points were derived from a classification and regression tree analysis. The optimal cut points for each assessment variable were then used in a backward logic regression to predict modified Rankin scale (mRS) score of 0 to 1 and 5 to 6. The variables remaining in the models were then assessed using a receiver operating characteristic curve analysis. Overall, 1519 patients were included in the study, 635 in the derivation cohort and 884 in the validation cohort. The model was highly accurate at predicting mRS score of 0 to 1 in all patients considered for thrombolysis therapy (area under the curve [AUC] 0.91), those who were treated (AUC 0.88) and those with recanalization (AUC 0.89). Next, the model was highly accurate at predicting mRS score of 5 to 6 in all patients considered for thrombolysis therapy (AUC 0.91), those who were treated (0.89) and those with recanalization (AUC 0.91). The odds ratio of thrombolysed patients who met the model criteria achieving mRS score of 0 to 1 was 17.89 (4.59-36.35, P <0.001) and for mRS score of 5 to 6 was 8.23 (2.57-26.97, P <0.001). This study has derived and validated a highly accurate model at predicting patient outcome after ischemic stroke. © 2017 American Heart Association, Inc.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates.

PubMed

LeDell, Erin; Petersen, Maya; van der Laan, Mark

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates

PubMed Central

Petersen, Maya; van der Laan, Mark

2015-01-01

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC. PMID:26279737

Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Juhun, E-mail: leej15@upmc.edu; Nishikawa, Robert M.; Reiser, Ingrid

2015-09-15

Purpose: The purpose of this study is to measure the effectiveness of local curvature measures as novel image features for classifying breast tumors. Methods: A total of 119 breast lesions from 104 noncontrast dedicated breast computed tomography images of women were used in this study. Volumetric segmentation was done using a seed-based segmentation algorithm and then a triangulated surface was extracted from the resulting segmentation. Total, mean, and Gaussian curvatures were then computed. Normalized curvatures were used as classification features. In addition, traditional image features were also extracted and a forward feature selection scheme was used to select the optimalmore » feature set. Logistic regression was used as a classifier and leave-one-out cross-validation was utilized to evaluate the classification performances of the features. The area under the receiver operating characteristic curve (AUC, area under curve) was used as a figure of merit. Results: Among curvature measures, the normalized total curvature (C{sub T}) showed the best classification performance (AUC of 0.74), while the others showed no classification power individually. Five traditional image features (two shape, two margin, and one texture descriptors) were selected via the feature selection scheme and its resulting classifier achieved an AUC of 0.83. Among those five features, the radial gradient index (RGI), which is a margin descriptor, showed the best classification performance (AUC of 0.73). A classifier combining RGI and C{sub T} yielded an AUC of 0.81, which showed similar performance (i.e., no statistically significant difference) to the classifier with the above five traditional image features. Additional comparisons in AUC values between classifiers using different combinations of traditional image features and C{sub T} were conducted. The results showed that C{sub T} was able to replace the other four image features for the classification task. Conclusions: The normalized curvature measure contains useful information in classifying breast tumors. Using this, one can reduce the number of features in a classifier, which may result in more robust classifiers for different datasets.« less

Comparative study of CEA and CA19-9 in esophageal, gastric and colon cancers individually and in combination (ROC curve analysis).

PubMed

Bagaria, Bhawna; Sood, Sadhna; Sharma, Rameshwaram; Lalwani, Soniya

2013-09-01

To determine the clinical serum levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9), individually and in combination, for the diagnosis of 50 healthy subjects and 150 cases of esophageal, gastric, and colon cancers. The sensitivities of the two markers were compared individually and in combination, with specificity set at 100%. Receiver operating characteristic (ROC) curves were plotted. Serum CEA levels were significantly higher in cancer patients than in the control group. The sensitivity of CEA was determined: in esophageal cancer, sensitivity=28%, negative predictive value (NPV)=61.72%, and AUC=0.742 
(SE=0.05), with a significance level of P<0.0001; in gastric cancer, sensitivity=30%, NPV=58.82%, and AUC=0.734 (SE=0.05), with a significance level of P<0.0001; in colon cancer, sensitivity=74%, NPV=79.36%, and AUC=0.856 
(SE=0.04), with a significance level of P<0.0001. The sensitivity of CA19-9 was also evaluated: in esophageal cancer, sensitivity=18%, NPV=54.94%, and AUC=0.573 (SE =0.05), with a significance level of P=0.2054. In gastric cancer, sensitivity=42%, NPV=63.29%, and AUC=0.679 (SE =0.05), with a significance level of P<0.0011. In colon cancer, sensitivity=26%, NPV=57.47%, and AUC=0.580 (SE =0.05), with a significance level of P=0.1670. The following were the sensitivities of CEA/CA19-9 combined: in esophageal cancer, sensitivity=42%, NPV=63.29%, SE=0.078 (95% CI: 0.0159-0.322); gastric cancer, sensitivity=58%, NPV=70.42%, SE=0.072 (95% CI: -0.0866-0.198); and colon cancer, sensitivity=72%, NPV=78.12%, SE=0.070 (95% CI: 0.137-0.415). CEA exhibited the highest sensitivity for colon cancer, and CA19-9 exhibited the highest sensitivity for gastric cancer. Combined analysis indicated an increase in diagnostic sensitivity in esophageal and gastric cancer compared with that in colon cancer.

Shape information from glucose curves: Functional data analysis compared with traditional summary measures

PubMed Central

2013-01-01

Background Plasma glucose levels are important measures in medical care and research, and are often obtained from oral glucose tolerance tests (OGTT) with repeated measurements over 2–3 hours. It is common practice to use simple summary measures of OGTT curves. However, different OGTT curves can yield similar summary measures, and information of physiological or clinical interest may be lost. Our mean aim was to extract information inherent in the shape of OGTT glucose curves, compare it with the information from simple summary measures, and explore the clinical usefulness of such information. Methods OGTTs with five glucose measurements over two hours were recorded for 974 healthy pregnant women in their first trimester. For each woman, the five measurements were transformed into smooth OGTT glucose curves by functional data analysis (FDA), a collection of statistical methods developed specifically to analyse curve data. The essential modes of temporal variation between OGTT glucose curves were extracted by functional principal component analysis. The resultant functional principal component (FPC) scores were compared with commonly used simple summary measures: fasting and two-hour (2-h) values, area under the curve (AUC) and simple shape index (2-h minus 90-min values, or 90-min minus 60-min values). Clinical usefulness of FDA was explored by regression analyses of glucose tolerance later in pregnancy. Results Over 99% of the variation between individually fitted curves was expressed in the first three FPCs, interpreted physiologically as “general level” (FPC1), “time to peak” (FPC2) and “oscillations” (FPC3). FPC1 scores correlated strongly with AUC (r=0.999), but less with the other simple summary measures (−0.42≤r≤0.79). FPC2 scores gave shape information not captured by simple summary measures (−0.12≤r≤0.40). FPC2 scores, but not FPC1 nor the simple summary measures, discriminated between women who did and did not develop gestational diabetes later in pregnancy. Conclusions FDA of OGTT glucose curves in early pregnancy extracted shape information that was not identified by commonly used simple summary measures. This information discriminated between women with and without gestational diabetes later in pregnancy. PMID:23327294

Shape information from glucose curves: functional data analysis compared with traditional summary measures.

PubMed

Frøslie, Kathrine Frey; Røislien, Jo; Qvigstad, Elisabeth; Godang, Kristin; Bollerslev, Jens; Voldner, Nanna; Henriksen, Tore; Veierød, Marit B

2013-01-17

Plasma glucose levels are important measures in medical care and research, and are often obtained from oral glucose tolerance tests (OGTT) with repeated measurements over 2-3  hours. It is common practice to use simple summary measures of OGTT curves. However, different OGTT curves can yield similar summary measures, and information of physiological or clinical interest may be lost. Our mean aim was to extract information inherent in the shape of OGTT glucose curves, compare it with the information from simple summary measures, and explore the clinical usefulness of such information. OGTTs with five glucose measurements over two hours were recorded for 974 healthy pregnant women in their first trimester. For each woman, the five measurements were transformed into smooth OGTT glucose curves by functional data analysis (FDA), a collection of statistical methods developed specifically to analyse curve data. The essential modes of temporal variation between OGTT glucose curves were extracted by functional principal component analysis. The resultant functional principal component (FPC) scores were compared with commonly used simple summary measures: fasting and two-hour (2-h) values, area under the curve (AUC) and simple shape index (2-h minus 90-min values, or 90-min minus 60-min values). Clinical usefulness of FDA was explored by regression analyses of glucose tolerance later in pregnancy. Over 99% of the variation between individually fitted curves was expressed in the first three FPCs, interpreted physiologically as "general level" (FPC1), "time to peak" (FPC2) and "oscillations" (FPC3). FPC1 scores correlated strongly with AUC (r=0.999), but less with the other simple summary measures (-0.42≤r≤0.79). FPC2 scores gave shape information not captured by simple summary measures (-0.12≤r≤0.40). FPC2 scores, but not FPC1 nor the simple summary measures, discriminated between women who did and did not develop gestational diabetes later in pregnancy. FDA of OGTT glucose curves in early pregnancy extracted shape information that was not identified by commonly used simple summary measures. This information discriminated between women with and without gestational diabetes later in pregnancy.

Pharmacogenetics-based area-under-curve model can predict efficacy and adverse events from axitinib in individual patients with advanced renal cell carcinoma.

PubMed

Yamamoto, Yoshiaki; Tsunedomi, Ryouichi; Fujita, Yusuke; Otori, Toru; Ohba, Mitsuyoshi; Kawai, Yoshihisa; Hirata, Hiroshi; Matsumoto, Hiroaki; Haginaka, Jun; Suzuki, Shigeo; Dahiya, Rajvir; Hamamoto, Yoshihiko; Matsuyama, Kenji; Hazama, Shoichi; Nagano, Hiroaki; Matsuyama, Hideyasu

2018-03-30

We investigated the relationship between axitinib pharmacogenetics and clinical efficacy/adverse events in advanced renal cell carcinoma (RCC) and established a model to predict clinical efficacy and adverse events using pharmacokinetic and gene polymorphisms related to drug metabolism and efflux in a phase II trial. We prospectively evaluated the area under the plasma concentration-time curve (AUC) of axitinib, objective response rate, and adverse events in 44 consecutive advanced RCC patients treated with axitinib. To establish a model for predicting clinical efficacy and adverse events, polymorphisms in genes including ABC transporters ( ABCB1 and ABCG2 ), UGT1A , and OR2B11 were analyzed by whole-exome sequencing, Sanger sequencing, and DNA microarray. To validate this prediction model, calculated AUC by 6 gene polymorphisms was compared with actual AUC in 16 additional consecutive patients prospectively. Actual AUC significantly correlated with the objective response rate ( P = 0.0002) and adverse events (hand-foot syndrome, P = 0.0055; and hypothyroidism, P = 0.0381). Calculated AUC significantly correlated with actual AUC ( P < 0.0001), and correctly predicted objective response rate ( P = 0.0044) as well as adverse events ( P = 0.0191 and 0.0082, respectively). In the validation study, calculated AUC prior to axitinib treatment precisely predicted actual AUC after axitinib treatment ( P = 0.0066). Our pharmacogenetics-based AUC prediction model may determine the optimal initial dose of axitinib, and thus facilitate better treatment of patients with advanced RCC.

Pharmacogenetics-based area-under-curve model can predict efficacy and adverse events from axitinib in individual patients with advanced renal cell carcinoma

PubMed Central

Yamamoto, Yoshiaki; Tsunedomi, Ryouichi; Fujita, Yusuke; Otori, Toru; Ohba, Mitsuyoshi; Kawai, Yoshihisa; Hirata, Hiroshi; Matsumoto, Hiroaki; Haginaka, Jun; Suzuki, Shigeo; Dahiya, Rajvir; Hamamoto, Yoshihiko; Matsuyama, Kenji; Hazama, Shoichi; Nagano, Hiroaki; Matsuyama, Hideyasu

2018-01-01

We investigated the relationship between axitinib pharmacogenetics and clinical efficacy/adverse events in advanced renal cell carcinoma (RCC) and established a model to predict clinical efficacy and adverse events using pharmacokinetic and gene polymorphisms related to drug metabolism and efflux in a phase II trial. We prospectively evaluated the area under the plasma concentration–time curve (AUC) of axitinib, objective response rate, and adverse events in 44 consecutive advanced RCC patients treated with axitinib. To establish a model for predicting clinical efficacy and adverse events, polymorphisms in genes including ABC transporters (ABCB1 and ABCG2), UGT1A, and OR2B11 were analyzed by whole-exome sequencing, Sanger sequencing, and DNA microarray. To validate this prediction model, calculated AUC by 6 gene polymorphisms was compared with actual AUC in 16 additional consecutive patients prospectively. Actual AUC significantly correlated with the objective response rate (P = 0.0002) and adverse events (hand-foot syndrome, P = 0.0055; and hypothyroidism, P = 0.0381). Calculated AUC significantly correlated with actual AUC (P < 0.0001), and correctly predicted objective response rate (P = 0.0044) as well as adverse events (P = 0.0191 and 0.0082, respectively). In the validation study, calculated AUC prior to axitinib treatment precisely predicted actual AUC after axitinib treatment (P = 0.0066). Our pharmacogenetics-based AUC prediction model may determine the optimal initial dose of axitinib, and thus facilitate better treatment of patients with advanced RCC. PMID:29682213

[Application of decision curve on evaluation of MRI predictive model for early assessing pathological complete response to neoadjuvant therapy in breast cancer].

PubMed

He, Y J; Li, X T; Fan, Z Q; Li, Y L; Cao, K; Sun, Y S; Ouyang, T

2018-01-23

Objective: To construct a dynamic enhanced MR based predictive model for early assessing pathological complete response (pCR) to neoadjuvant therapy in breast cancer, and to evaluate the clinical benefit of the model by using decision curve. Methods: From December 2005 to December 2007, 170 patients with breast cancer treated with neoadjuvant therapy were identified and their MR images before neoadjuvant therapy and at the end of the first cycle of neoadjuvant therapy were collected. Logistic regression model was used to detect independent factors for predicting pCR and construct the predictive model accordingly, then receiver operating characteristic (ROC) curve and decision curve were used to evaluate the predictive model. Results: ΔArea(max) and Δslope(max) were independent predictive factors for pCR, OR =0.942 (95% CI : 0.918-0.967) and 0.961 (95% CI : 0.940-0.987), respectively. The area under ROC curve (AUC) for the constructed model was 0.886 (95% CI : 0.820-0.951). Decision curve showed that in the range of the threshold probability above 0.4, the predictive model presented increased net benefit as the threshold probability increased. Conclusions: The constructed predictive model for pCR is of potential clinical value, with an AUC>0.85. Meanwhile, decision curve analysis indicates the constructed predictive model has net benefit from 3 to 8 percent in the likely range of probability threshold from 80% to 90%.

BMI or BIA: Is Body Mass Index or Body Fat Mass a Better Predictor of Cardiovascular Risk in Overweight or Obese Children and Adolescents? A German/Austrian/Swiss Multicenter APV Analysis of 3,327 Children and Adolescents.

PubMed

Bohn, Barbara; Müller, Manfred James; Simic-Schleicher, Gunter; Kiess, Wieland; Siegfried, Wolfgang; Oelert, Monika; Tuschy, Sabine; Berghem, Stefan; Holl, Reinhard W

2015-01-01

Body fat (BF) percentiles for German children and adolescents have recently been published. This study aims to evaluate the association between bioelectrical impedance analysis (BIA)-derived BF and cardiovascular risk factors and to investigate whether BF is better suited than BMI in children and adolescents. Data of 3,327 children and adolescents (BMI > 90th percentile) were included. Spearman's correlation and receiver operating characteristics (ROCs) were applied determining the associations between BMI or BF and cardiovascular risk factors (hypertension, dyslipidemia, elevated liver enzymes, abnormal carbohydrate metabolism). Area under the curve (AUC) was calculated to predict cardiovascular risk factors. A significant association between both obesity indices and hypertension was present (all p < 0.0001), but the correlation with BMI was stronger (r = 0.22) compared to BF (r = 0.13). There were no differences between BMI and BF regarding their correlation with other cardiovascular risk factors. BF significantly predicted hypertension (AUC = 0.61), decreased HDL-cholesterol (AUC = 0.58), elevated LDL-cholesterol (AUC = 0.59), elevated liver enzymes (AUC = 0.61) (all p < 0.0001), and elevated triglycerides (AUC = 0.57, p < 0.05), but not abnormal carbohydrate metabolism (AUC = 0.54, p = 0.15). For the prediction of cardiovascular risk factors, no significant differences between BMI and BF were observed. BIA-derived BF was not superior to BMI to predict cardiovascular risk factors in overweight or obese children and adolescents.

Identification of benign and malignant thyroid nodules by in vivo iodine concentration measurement using single-source dual energy CT

PubMed Central

Gao, Shun-Yu; Zhang, Xiao-Yan; Wei, Wei; Li, Xiao-Ting; Li, Yan-Ling; Xu, Min; Sun, Ying-Shi; Zhang, Xiao-Peng

2016-01-01

Abstract This study proposed to determine whether in vivo iodine concentration measurement by single-source dual energy (SSDE) CT can improve differentiation between benign and malignant thyroid nodules. In total, 53 patients presenting with thyroid nodules underwent SSDE CT scanning. Iodine concentrations were measured for each nodule and normal thyroid tissue using the GSI-viewer image analysis software. A total of 26 thyroid nodules were malignant in 26 patients and confirmed by surgery; 33 nodules from 27 patients were benign, with 10 confirmed by surgery and others after follow-up. Iodine concentrations with plain CT were significantly lower in malignant than benign nodules (0.47 ± 0.20 vs 1.17 ± 0.38 mg/mL, P = 0.00). Receiver operating characteristic (ROC) curve showed an area under the curve (AUC) of 0.93; with a cutoff of 0.67, iodine concentration showed 92.3% sensitivity and 88.5% specificity in diagnosing malignancy. Iodine concentration obtained by enhanced and plain CT were significantly higher in malignant than benign nodules (9.05 ± 3.35 vs 3.46 ± 2.24 mg/mL, P = 0.00). ROC curve analysis showed an AUC of 0.93; with a cutoff value of 3.37, iodine concentration displayed 78% sensitivity, 95% specificity in diagnosing malignancy. Combining unenhanced with enhanced iodine concentrations, the diagnostic equation was: Y = –8.641 × unenhanced iodine concentration + 0.663 × iodine concentration. ROC curve showed an AUC of 0.98 (95% CI, 0.94, 1.00). With Y ≥ –2 considered malignancy, diagnostic sensitivity and specificity were 96%, 96.3%, respectively. This study concluded that SSDE CT can detect the differences in iodine uptake and blood supply between benign and malignant thyroid lesions. PMID:27684811

Digital image analysis supports a nuclear-to-cytoplasmic ratio cutoff value of 0.5 for atypical urothelial cells.

PubMed

Hang, Jen-Fan; Charu, Vivek; Zhang, M Lisa; VandenBussche, Christopher J

2017-09-01

An elevated nuclear-to-cytoplasmic (N:C) ratio of ≥0.5 is a required criterion for the diagnosis of atypical urothelial cells (AUC) in The Paris System for Reporting Urinary Cytology. To validate the N:C ratio cutoff value and its predictive power for high-grade urothelial carcinoma (HGUC), the authors retrospectively reviewed the urinary tract cytology specimens of 15 cases of AUC with HGUC on follow-up (AUC-HGUC) and 33 cases of AUC without HGUC on follow-up (AUC-N-HGUC). The number of atypical cells in each case was recorded, and each atypical cell was photographed and digitally examined to calculate the nuclear size and N:C ratio. On average, the maximum N:C ratios of atypical cells were significantly different between the AUC-HGUC and AUC-N-HGUC cohorts (0.53 vs 0.43; P =.00009), whereas the maximum nuclear sizes of atypical cells (153.43 μM 2 vs 201.47 μM 2 ; P = .69) and the number of atypical cells per case (10.13 vs 7.88; P = .12) were not found to be significantly different. Receiver operating characteristic analysis demonstrated that the maximum N:C ratio alone had high discriminatory capacity (area under the curve, 79.19%; 95% confidence interval, 64.19%-94.19%). The optimal maximum N:C ratio threshold was 0.486, giving a sensitivity of 73.3% and a specificity of 84.8% for predicting HGUC on follow-up. The identification of AUC with an N:C ratio >0.486 has a high predictive power for HGUC on follow-up in AUC specimens. This justifies using the N:C ratio as a required criterion for the AUC category. Individual laboratories using different cytopreparation methods may require independent validation of the N:C ratio cutoff value. Cancer Cytopathol 2017;125:710-6. © 2017 American Cancer Society. © 2017 American Cancer Society.

Appropriate body mass index and waist circumference cutoffs for middle and older age group in Thailand: data of 19,621 participants from Thai epidemiologic stroke (TES) study.

PubMed

Samsen, Maiyadhaj; Hanchaiphiboolkul, Suchat; Puthkhao, Pimchanok; Tantirittisak, Tasanee; Towanabut, Somchai

2012-09-01

To determine the appropriate body mass index (BMI) and waist circumference (WC) cutoff point for identification of at least one cardiovascular risk factor (hypertension, dyslipidemia, and type 2 diabetes) in Thailand, and to compare the discrimination ability of BMI with that of WC for discrimination of at least one cardiovascular risk factor. Baseline health survey data of participants of Thai Epidemiologic Stroke (TES) Study, who were free from stroke, enrolled from five geographic regions around the country, were studied as cross-sectional analysis. Receiver operating characteristics curve (ROC) analysis was performed to determine the appropriate cutoff points of BMI and WC in identifying those with presence of at least one cardiovascular risk factors. The BMI or WC value with the shortest distance on the ROC curve was considered to be appropriate cutoffs. Comparing the ability of BMI in discrimination of at least one cardiovascular risk factor with that of WC was performed by comparing ROC area under curve (AUC). Among 19,621 (6,608 men and 13,013 women) participants with age range of 45 to 80 years, the average age was 59.8 years for men and 58.5 years for women. The appropriate cutoff point of BMI was 23 kg/m2 in men and 24 kg/m2 in women. The cutoffs of WC were 80 cm and 78 cm in men and women, respectively. In both gender, waist circumference (WC) (AUC in men = 0.684; 95% CI, 0.672-0.695, AUC in women = 0.673; 95% CI, 0.665-0.681) was significantly (p < 0.001) better than BMI (AUC in men = 0.667; 95% CI, 0.656-0.679, AUC in women = 0.636; 95% CI, 0.628-0.644) in discrimination of at least one cardiovascular risk factor. In Thai adults aged 45 to 80 years, the cutoff points of BMI should be 23 kg/m2 in men and 24 kg/m2 in women. For WC, 80 cm and 78 cm should be considered to be appropriate cutoffs for men and women, respectively. Waist circumference (WC) as a simple obesity index should be advocated for public health screening.

Quantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints.

PubMed

Fiocco, Ugo; Stramare, Roberto; Martini, Veronica; Coran, Alessandro; Caso, Francesco; Costa, Luisa; Felicetti, Mara; Rizzo, Gaia; Tonietto, Matteo; Scanu, Anna; Oliviero, Francesca; Raffeiner, Bernd; Vezzù, Maristella; Lunardi, Francesca; Scarpa, Raffaele; Sacerdoti, David; Rubaltelli, Leopoldo; Punzi, Leonardo; Doria, Andrea; Grisan, Enrico

2017-02-01

To develop quantitative imaging biomarkers of synovial tissue perfusion by pixel-based contrast-enhanced ultrasound (CEUS), we studied the relationship between CEUS synovial vascular perfusion and the frequencies of pathogenic T helper (Th)-17 cells in psoriatic arthritis (PsA) joints. Eight consecutive patients with PsA were enrolled in this study. Gray scale CEUS evaluation was performed on the same joint immediately after joint aspiration, by automatic assessment perfusion data, using a new quantification approach of pixel-based analysis and the gamma-variate model. The set of perfusional parameters considered by the time intensity curve includes the maximum value (peak) of the signal intensity curve, the blood volume index or area under the curve, (BVI, AUC) and the contrast mean transit time (MTT). The direct ex vivo analysis of the frequencies of SF IL17A-F + CD161 + IL23 + CD4 + T cells subsets were quantified by fluorescence-activated cell sorter (FACS). In cross-sectional analyses, when tested for multiple comparison setting, a false discovery rate at 10%, a common pattern of correlations between CEUS Peak, AUC (BVI) and MTT parameters with the IL17A-F + IL23 + - IL17A-F + CD161 + - and IL17A-F + CD161 + IL23 + CD4 + T cells subsets, as well as lack of correlation between both peak and AUC values and both CD4 + T and CD4 + IL23 + T cells, was observed. The pixel-based CEUS assessment is a truly measure synovial inflammation, as a useful tool to develop quantitative imaging biomarker for monitoring target therapeutics in PsA.

Development and prospective multicenter evaluation of the long noncoding RNA MALAT-1 as a diagnostic urinary biomarker for prostate cancer

PubMed Central

Lu, Ji; Shi, Xiaolei; Zhu, Yasheng; Zhang, Wei; Jing, Taile; Zhang, Chao; Shen, Jian; Xu, Chuanliang; Wang, Huiqing; Wang, Haifeng; Wang, Yang; Liu, Bin; Li, Yaoming; Fang, Ziyu; Guo, Fei; Qiao, Meng; Wu, Chengyao; Wei, Qiang; Xu, Danfeng; Shen, Dan; Lu, Xin; Gao, Xu; Hou, Jianguo; Sun, Yinghao

2014-01-01

The current strategy for diagnosing prostate cancer (PCa) is mainly based on the serum prostate-specific antigen (PSA) test. However, PSA has low specificity and has led to numerous unnecessary biopsies. We evaluated the effectiveness of urinary metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1), a long noncoding RNA, for predicting the risk of PCa before biopsy. The MALAT-1 score was tested in a discovery phase and a multi-center validation phase. The predictive power of the MALAT-1 score was evaluated by the area under receiver operating characteristic (ROC) curve (AUC) and by decision curve analysis. As an independent predictor of PCa, the MALAT-1 score was significantly higher in men with a positive biopsy than in those with a negative biopsy. The ROC analysis showed a higher AUC for the MALAT-1 score (0.670 and 0.742) vs. the total PSA (0.545 and 0.601) and percent free PSA (0.622 and 0.627) in patients with PSA values of 4.0-10 ng/ml. According to the decision curve analysis, using a probability threshold of 25%, the MALAT-1 model would prevent 30.2%-46.5% of unnecessary biopsies in PSA 4–10 ng/ml cohorts, without missing any high-grade cancers. Our results demonstrate that urine MALAT-1 is a promising biomarker for predicting prostate cancer risk. PMID:25526029

Comparison of computer display monitors for computed radiography diagnostic application in a radiology PACS.

PubMed

Sim, L; Manthey, K; Esdaile, P; Benson, M

2004-09-01

A study to compare the performance of the following display monitors for application as PACS CR diagnostic workstations is described. 1. Diagnostic quality, 3 megapixel, 21 inch monochrome LCD monitors. 2. Commercial grade, 2 megapixel, 20 inch colour LCD monitors. Two sets of fifty radiological studies each were presented separately to five radiologists on two occasions, using different displays on each occasion. The two sets of radiological studies were CR of the chest, querying the presence of pneumothorax, and CR of the wrist, querying the presence of a scaphoid fracture. Receiver Operating Characteristic (ROC) curves were constructed for diagnostic performance for each presentation. Areas under the ROC curves (AUC) for diagnosis using different monitors were compared for each image set and the following results obtained: Set 1: Monochrome AUC = 0.873 +/- 0.026; Colour AUC = 0.831 +/- 0.032; Set 2: Monochrome AUC = 0.945 +/- 0.014; Colour AUC = 0.931 +/- 0.019; Differences in AUC were attributed to the different monitors. While not significant at a 95% confidence level, the results have supported a cautious approach to consideration of the use of commercial grade LCD colour monitors for diagnostic application.

A prediction model-based algorithm for computer-assisted database screening of adverse drug reactions in the Netherlands.

PubMed

Scholl, Joep H G; van Hunsel, Florence P A M; Hak, Eelko; van Puijenbroek, Eugène P

2018-02-01

The statistical screening of pharmacovigilance databases containing spontaneously reported adverse drug reactions (ADRs) is mainly based on disproportionality analysis. The aim of this study was to improve the efficiency of full database screening using a prediction model-based approach. A logistic regression-based prediction model containing 5 candidate predictors was developed and internally validated using the Summary of Product Characteristics as the gold standard for the outcome. All drug-ADR associations, with the exception of those related to vaccines, with a minimum of 3 reports formed the training data for the model. Performance was based on the area under the receiver operating characteristic curve (AUC). Results were compared with the current method of database screening based on the number of previously analyzed associations. A total of 25 026 unique drug-ADR associations formed the training data for the model. The final model contained all 5 candidate predictors (number of reports, disproportionality, reports from healthcare professionals, reports from marketing authorization holders, Naranjo score). The AUC for the full model was 0.740 (95% CI; 0.734-0.747). The internal validity was good based on the calibration curve and bootstrapping analysis (AUC after bootstrapping = 0.739). Compared with the old method, the AUC increased from 0.649 to 0.740, and the proportion of potential signals increased by approximately 50% (from 12.3% to 19.4%). A prediction model-based approach can be a useful tool to create priority-based listings for signal detection in databases consisting of spontaneous ADRs. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Total Thrombus-formation Analysis System Predicts Periprocedural Bleeding Events in Patients With Coronary Artery Disease Undergoing Percutaneous Coronary Intervention.

PubMed

Oimatsu, Yu; Kaikita, Koichi; Ishii, Masanobu; Mitsuse, Tatsuro; Ito, Miwa; Arima, Yuichiro; Sueta, Daisuke; Takahashi, Aya; Iwashita, Satomi; Yamamoto, Eiichiro; Kojima, Sunao; Hokimoto, Seiji; Tsujita, Kenichi

2017-04-24

Periprocedural bleeding events are common after percutaneous coronary intervention. We evaluated the association of periprocedural bleeding events with thrombogenicity, which was measured quantitatively by the Total Thrombus-formation Analysis System equipped with microchips and thrombogenic surfaces (collagen, platelet chip [PL]; collagen plus tissue factor, atheroma chip [AR]). Between August 2013 and March 2016, 313 consecutive patients with coronary artery disease undergoing elective percutaneous coronary intervention were enrolled. They were divided into those with or without periprocedural bleeding events. We determined the bleeding events as composites of major bleeding events defined by the International Society on Thrombosis and Hemostasis and minor bleeding events (eg, minor hematoma, arteriovenous shunt and pseudoaneurysm). Blood samples obtained at percutaneous coronary intervention were analyzed for thrombus formation area under the curve (PL 24 -AUC 10 for PL chip; AR 10 -AUC 30 for AR chip) by the Total Thrombus-formation Analysis System and P2Y12 reaction unit by the VerifyNow system. Periprocedural bleeding events occurred in 37 patients. PL 24 -AUC 10 levels were significantly lower in patients with such events than those without ( P =0.002). Multiple logistic regression analyses showed association between low PL 24 -AUC 10 levels and periprocedural bleeding events (odds ratio, 2.71 [1.22-5.99]; P =0.01) and association between PL 24 -AUC 10 and periprocedural bleeding events in 176 patients of the femoral approach group (odds ratio, 2.88 [1.11-7.49]; P =0.03). However, PL 24 -AUC 10 levels in 127 patients of the radial approach group were not significantly different in patients with or without periprocedural bleeding events. PL 24 -AUC 10 measured by the Total Thrombus-formation Analysis System is a potentially useful predictor of periprocedural bleeding events in coronary artery disease patients undergoing elective percutaneous coronary intervention. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

AUC-Maximizing Ensembles through Metalearning.

PubMed

LeDell, Erin; van der Laan, Mark J; Petersen, Maya

2016-05-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

AUC-Maximizing Ensembles through Metalearning

PubMed Central

LeDell, Erin; van der Laan, Mark J.; Peterson, Maya

2016-01-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree. PMID:27227721

Correlation of the plasma sphingoid base profile with results from oral glucose tolerance tests in gestational diabetes mellitus

PubMed Central

Khan, Abad; Hornemann, Thorsten

2017-01-01

Oral glucose tolerance test (OGTT) is usually insufficient to accurately predict the risk for type 2 diabetes mellitus (T2DM), it is therefore necessary to identify an additional biomarker that would most likely improve the accuracy of OGTT. The current OGTT was performed in 53 volunteers after ingestion of 75 g glucose in 250 ml water to each volunteer. Similarly the sphingoid base profile of these volunteers was explored using liquid-chromatography linked with mass spectrometer (LC-MS) and correlated with the different time-points glucose values of OGTT as well as with total area under the curve (tAUC), incremental area under the curve (iAUC), and positive incremental area under the curve (pAUC). The findings showed that 1-deoxysphinganine (1-deoxySA) was significantly positively correlated with the 1-hour, 2-hour, and 3-hour plasma glucose level as well as with total, incremental, and positive incremental AUC while 1-deoxysphingosine (1-deoxySO) was correlated only with 1-hour, 2-hour glucose levels and tAUC of OGTT. The C18SAdiene was negatively correlated with all-time points glucose values and AUCs followed by negative correlation of C18SO, C16SO and C17SO with 2-hour glucose and tAUC of OGTT. The ratios of 1-deoxySA and 1-deoxySO with respect to C18SAdiene have shown significant correlation with 2-hour and AUCs. These ratios were higher in subjects with gestational diabetes in comparison with normal subjects. These findings underlined that 1-deoxysphingolipids (1-deoxySLs) and their ratios with C18SAdiene could be significantly correlated with the glucose load of OGTT and might be used as predictive biomarkers along with OGTT for the risk assessment of diabetes. PMID:28694753

Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.

PubMed

Wu, Jia; Gong, Guanghua; Cui, Yi; Li, Ruijiang

2016-11-01

To predict pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). In this Institutional Review Board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using 3T DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with high temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast washout were statistically significant (P < 0.05) after correcting for multiple testing, with area under the receiver operating characteristic (ROC) curve (AUC) or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (P = 0.002) in leave-one-out cross-validation. This improved upon conventional imaging predictors such as tumor volume (AUC = 0.53) and texture features based on whole-tumor analysis (AUC = 0.65). The heterogeneity of the tumor subregion associated with fast washout on DCE-MRI predicted pathological response to NAC in breast cancer. J. Magn. Reson. Imaging 2016;44:1107-1115. © 2016 International Society for Magnetic Resonance in Medicine.

Regional autonomy changes in resting-state functional MRI in patients with HIV associated neurocognitive disorder

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Chockanathan, Udaysankar; Wismüller, Axel

2018-03-01

In this study, we investigate whether there are discernable changes in influence that brain regions have on themselves once patients show symptoms of HIV Associated Neurocognitive Disorder (HAND) using functional MRI (fMRI). Simple functional connectivity measures, such as correlation cannot reveal such information. To this end, we use mutual connectivity analysis (MCA) with Local Models (LM), which reveals a measure of influence in terms of predictability. Once such measures of interaction are obtained, we train two classifiers to characterize difference in patterns of regional self-influence between healthy subjects and subjects presenting with HAND symptoms. The two classifiers we use are Support Vector Machines (SVM) and Localized Generalized Matrix Learning Vector Quantization (LGMLVQ). Performing machine learning on fMRI connectivity measures is popularly known as multi-voxel pattern analysis (MVPA). By performing such an analysis, we are interested in studying the impact HIV infection has on an individual's brain. The high area under receiver operating curve (AUC) and accuracy values for 100 different train/test separations using MCA-LM self-influence measures (SVM: mean AUC=0.86, LGMLVQ: mean AUC=0.88, SVM and LGMLVQ: mean accuracy=0.78) compared with standard MVPA analysis using cross-correlation between fMRI time-series (SVM: mean AUC=0.58, LGMLVQ: mean AUC=0.57), demonstrates that self-influence features can be more discriminative than measures of interaction between time-series pairs. Furthermore, our results suggest that incorporating measures of self-influence in MVPA analysis used commonly in fMRI analysis has the potential to provide a performance boost and indicate important changes in dynamics of regions in the brain as a consequence of HIV infection.

Comparison of Diagnostic Accuracy of Clinical Measures of Breast Cancer–Related Lymphedema: Area Under the Curve

PubMed Central

Smoot, Betty J.; Wong, Josephine F.; Dodd, Marylin J.

2013-01-01

Objective To compare diagnostic accuracy of measures of breast cancer–related lymphedema (BCRL). Design Cross-sectional design comparing clinical measures with the criterion standard of previous diagnosis of BCRL. Setting University of California San Francisco Translational Science Clinical Research Center. Participants Women older than 18 years and more than 6 months posttreatment for breast cancer (n=141; 70 with BCRL, 71 without BCRL). Interventions Not applicable. Main Outcome Measures Sensitivity, specificity, receiver operator characteristic curve, and area under the curve (AUC) were used to evaluate accuracy. Results A total of 141 women were categorized as having (n=70) or not having (n=71) BCRL based on past diagnosis by a health care provider, which was used as the reference standard. Analyses of ROC curves for the continuous outcomes yielded AUC of .68 to .88 (P<.001); of the physical measures bioimpedance spectroscopy yielded the highest accuracy with an AUC of .88 (95% confidence interval, .80–.96) for women whose dominant arm was the affected arm. The lowest accuracy was found using the 2-cm diagnostic cutoff score to identify previously diagnosed BCRL (AUC, .54–.65). Conclusions Our findings support the use of bioimpedance spectroscopy in the assessment of existing BCRL. Refining diagnostic cutoff values may improve accuracy of diagnosis and warrant further investigation. PMID:21440706

Usability verification of the Emergency Trauma Score (EMTRAS) and Rapid Emergency Medicine Score (REMS) in patients with trauma: A retrospective cohort study.

PubMed

Park, Hyun Oh; Kim, Jong Woo; Kim, Sung Hwan; Moon, Seong Ho; Byun, Joung Hun; Kim, Ki Nyun; Yang, Jun Ho; Lee, Chung Eun; Jang, In Seok; Kang, Dong Hun; Kim, Seong Chun; Kang, Changwoo; Choi, Jun Young

2017-11-01

Early estimation of mortality risk in patients with trauma is essential. In this study, we evaluate the validity of the Emergency Trauma Score (EMTRAS) and Rapid Emergency Medicine Score (REMS) for predicting in-hospital mortality in patients with trauma. Furthermore, we compared the REMS and the EMTRAS with 2 other scoring systems: the Revised Trauma Score (RTS) and Injury Severity score (ISS).We performed a retrospective chart review of 6905 patients with trauma reported between July 2011 and June 2016 at a large national university hospital in South Korea. We analyzed the associations between patient characteristics, treatment course, and injury severity scoring systems (ISS, RTS, EMTRAS, and REMS) with in-hospital mortality. Discriminating power was compared between scoring systems using the areas under the curve (AUC) of receiver operating characteristic (ROC) curves.The overall in-hospital mortality rate was 3.1%. Higher EMTRAS and REMS scores were associated with hospital mortality (P < .001). The ROC curve demonstrated adequate discrimination (AUC = 0.957 for EMTRAS and 0.9 for REMS). After performing AUC analysis followed by Bonferroni correction for multiple comparisons, EMTRAS was significantly superior to REMS and ISS in predicting in-hospital mortality (P < .001), but not significantly different from the RTS (P = .057). The other scoring systems were not significantly different from each other.The EMTRAS and the REMS are simple, accurate predictors of in-hospital mortality in patients with trauma.

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

PubMed Central

Wray, Naomi R.; Yang, Jian; Goddard, Michael E.; Visscher, Peter M.

2010-01-01

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator. PMID:20195508

Comparative proteomic profiling of the serum differentiates pancreatic cancer from chronic pancreatitis.

PubMed

Saraswat, Mayank; Joenväärä, Sakari; Seppänen, Hanna; Mustonen, Harri; Haglund, Caj; Renkonen, Risto

2017-07-01

Finland ranks sixth among the countries having highest incidence rate of pancreatic cancer with mortality roughly equaling incidence. The average age of diagnosis for pancreatic cancer is 69 years in Nordic males, whereas the average age of diagnosis of chronic pancreatitis is 40-50 years, however, many cases overlap in age. By radiology, the evaluation of a pancreatic mass, that is, the differential diagnosis between chronic pancreatitis and pancreatic cancer is often difficult. Preoperative needle biopsies are difficult to obtain and are demanding to interpret. New blood based biomarkers are needed. The accuracy of the only established biomarker for pancreatic cancer, CA 19-9 is rather poor in differentiating between benign and malignant mass of the pancreas. In this study, we have performed mass spectrometry analysis (High Definition MS E ) of serum samples from patients with chronic pancreatitis (13) and pancreatic cancer (22). We have quantified 291 proteins and performed detailed statistical analysis such as principal component analysis, orthogonal partial least square discriminant analysis and receiver operating curve analysis. The proteomic signature of chronic pancreatitis versus pancreatic cancer samples was able to separate the two groups by multiple statistical techniques. Some of the enriched pathways in the proteomic dataset were LXR/RXR activation, complement and coagulation systems and inflammatory response. We propose that multiple high-confidence biomarker candidates in our pilot study including Inter-alpha-trypsin inhibitor heavy chain H2 (Area under the curve, AUC: 0.947), protein AMBP (AUC: 0.951) and prothrombin (AUC: 0.917), which should be further evaluated in larger patient series as potential new biomarkers for differential diagnosis. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Color-coded perfusion analysis of CEUS for pre-interventional diagnosis of microvascularisation in cases of vascular malformations.

PubMed

Teusch, V I; Wohlgemuth, W A; Piehler, A P; Jung, E M

2014-01-01

Aim of our pilot study was the application of a contrast-enhanced color-coded ultrasound perfusion analysis in patients with vascular malformations to quantify microcirculatory alterations. 28 patients (16 female, 12 male, mean age 24.9 years) with high flow (n = 6) or slow-flow (n = 22) malformations were analyzed before intervention. An experienced examiner performed a color-coded Doppler sonography (CCDS) and a Power Doppler as well as a contrast-enhanced ultrasound after intravenous bolus injection of 1 - 2.4 ml of a second-generation ultrasound contrast medium (SonoVue®, Bracco, Milan). The contrast-enhanced examination was documented as a cine sequence over 60 s. The quantitative analysis based on color-coded contrast-enhanced ultrasound (CEUS) images included percentage peak enhancement (%peak), time to peak (TTP), area under the curve (AUC), and mean transit time (MTT). No side effects occurred after intravenous contrast injection. The mean %peak in arteriovenous malformations was almost twice as high as in slow-flow-malformations. The area under the curve was 4 times higher in arteriovenous malformations compared to the mean value of other malformations. The mean transit time was 1.4 times higher in high-flow-malformations compared to slow-flow-malformations. There was no difference regarding the time to peak between the different malformation types. The comparison between all vascular malformation and surrounding tissue showed statistically significant differences for all analyzed data (%peak, TTP, AUC, MTT; p < 0.01). High-flow and slow-flow vascular malformations had statistically significant differences in %peak (p < 0.01), AUC analysis (p < 0.01), and MTT (p < 0.05). Color-coded perfusion analysis of CEUS seems to be a promising technique for the dynamic assessment of microvasculature in vascular malformations.

Multicenter external validation of two malignancy risk prediction models in patients undergoing 18F-FDG-PET for solitary pulmonary nodule evaluation.

PubMed

Perandini, Simone; Soardi, G A; Larici, A R; Del Ciello, A; Rizzardi, G; Solazzo, A; Mancino, L; Zeraj, F; Bernhart, M; Signorini, M; Motton, M; Montemezzi, S

2017-05-01

To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models. Two hundred and fifty-nine solitary pulmonary nodules (SPNs) collected from four major hospitals which underwent 18-FDG-PET characterization were included in this multicentre retrospective study. The Herder model was tested on all available lesions (group A). A subgroup of 180 SPNs (group B) was used to provide unbiased comparison between the Herder and BIMC models. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to assess diagnostic accuracy. Decision analysis was performed by adopting the risk threshold stated in British Thoracic Society (BTS) guidelines. Unbiased comparison performed In Group B showed a ROC AUC for the Herder model of 0.807 (95 % CI 0.742-0.862) and for the BIMC model of 0.822 (95 % CI 0.758-0.875). Both the Herder and the BIMC models were proven to accurately predict the risk of malignancy when tested on a large multicentre external case series. The BIMC model seems advantageous on the basis of a more favourable decision analysis. • The Herder model showed a ROC AUC of 0.807 on 180 SPNs. • The BIMC model showed a ROC AUC of 0.822 on 180 SPNs. • Decision analysis is more favourable to the BIMC model.

Automated noninvasive classification of renal cancer on multiphase CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linguraru, Marius George; Wang, Shijun; Shah, Furhawn

2011-10-15

Purpose: To explore the added value of the shape of renal lesions for classifying renal neoplasms. To investigate the potential of computer-aided analysis of contrast-enhanced computed-tomography (CT) to quantify and classify renal lesions. Methods: A computer-aided clinical tool based on adaptive level sets was employed to analyze 125 renal lesions from contrast-enhanced abdominal CT studies of 43 patients. There were 47 cysts and 78 neoplasms: 22 Von Hippel-Lindau (VHL), 16 Birt-Hogg-Dube (BHD), 19 hereditary papillary renal carcinomas (HPRC), and 21 hereditary leiomyomatosis and renal cell cancers (HLRCC). The technique quantified the three-dimensional size and enhancement of lesions. Intrapatient and interphasemore » registration facilitated the study of lesion serial enhancement. The histograms of curvature-related features were used to classify the lesion types. The areas under the curve (AUC) were calculated for receiver operating characteristic curves. Results: Tumors were robustly segmented with 0.80 overlap (0.98 correlation) between manual and semi-automated quantifications. The method further identified morphological discrepancies between the types of lesions. The classification based on lesion appearance, enhancement and morphology between cysts and cancers showed AUC = 0.98; for BHD + VHL (solid cancers) vs. HPRC + HLRCC AUC = 0.99; for VHL vs. BHD AUC = 0.82; and for HPRC vs. HLRCC AUC = 0.84. All semi-automated classifications were statistically significant (p < 0.05) and superior to the analyses based solely on serial enhancement. Conclusions: The computer-aided clinical tool allowed the accurate quantification of cystic, solid, and mixed renal tumors. Cancer types were classified into four categories using their shape and enhancement. Comprehensive imaging biomarkers of renal neoplasms on abdominal CT may facilitate their noninvasive classification, guide clinical management, and monitor responses to drugs or interventions.« less

Is it possible to shorten ambulatory blood pressure monitoring?

PubMed

Wolak, Talya; Wilk, Lior; Paran, Esther; Wolak, Arik; Gutmacher, Bella; Shleyfer, Elena; Friger, Michael

2013-08-01

The aim of this investigation was to find a time segment in which average blood pressure (BP) has the best correlation with 24-hour BP control. A total of 240 patients with full ambulatory BP monitoring (ABPM) were included; 120 had controlled BP (systolic BP [SBP] ≤135 mm Hg and diastolic BP [DBP] ≤85 mm Hg) and 120 had uncontrolled BP (SBP >135 mm Hg and/or DBP >85 mm Hg). Each ABPM was divided into 6- and 8-hour segments. Evaluation for correlation between mean BP for each time segment and 24-hour BP control was performed using receiver operating characteristic curve analysis and Youden's index for threshold with the best sensitivity and specificity. The mean BP in the following segments showed the highest area under the curve (AUC) compared with average controlled 24-hour BP: SBP 2 am to 8 am (AUC, 0.918; threshold value of 133.5 mm Hg, sensitivity-0.752 and specificity-0.904); SBP 2 pm to 10 pm (AUC, 0.911; threshold value of 138.5 mm Hg, sensitivity-0.803 and specificity-0.878); and SBP 6 am to 2 pm (AUC, 0.903; threshold value of 140.5 mm Hg, sensitivity-0.778 and specificity-0.888). The time segment 2 pm to 10 pm was shown to have good correlation with 24-hour BP control (AUC >0.9; sensitivity and specificity >80%). This time segment might replace full ABPM as a screening measure for BP control or as abbreviated ABPM for patients with difficulty in performing full ABPM. © 2013 Wiley Periodicals, Inc.

The cut-off values of anthropometric variables for predicting mild cognitive impairment in Malaysian older adults: a large population based cross-sectional study.

PubMed

Won, Huiloo; Abdul, Manaf Zahara; Mat Ludin, Arimi Fitri; Omar, Mohd Azahadi; Razali, Rosdinom; Shahar, Suzana

2017-01-01

Older adults are at risk of mild cognitive impairment (MCI), and simple anthropometric measurements can be used to screen for this condition. Thus, the aim of this study was to explore the cut-off values of body mass index (BMI) and waist circumference (WC) for predicting the risk of MCI in older Malaysian adults. A total of 2,240 Malaysian older adults aged ≥60 years were recruited using multistage random sampling in a population based cross-sectional study. Receiver operating characteristic (ROC) curve was used to determine the cut-off values of BMI and WC with optimum sensitivity and specificity for the detection of MCI. Age, gender, years of education, smoking habit, alcohol consumption, depression, and medical conditions were used as confounding factors in this analysis. A BMI cut-off value of 26 kg/m 2 (area under the receiver operating characteristic curve [AUC] 0.725; sensitivity 90.5%; specificity 38.8%) was appropriate in identifying the risk of getting MCI in both men and women. The optimum WC cut-offs for likelihood of MCI were 90 cm (AUC 0.745; sensitivity 78.0%; specificity 59.8%) for men and 82 cm (AUC 0.714; sensitivity 84.3%; specificity 49.7%) for women. The optimum calf circumference (CC) cut-off values for identifying MCI were 29 cm (AUC 0.731; sensitivity 72.6%; specificity 61.1%) for men and 26 cm (AUC 0.598; sensitivity 79.1%; specificity 45.3%) for women. The cut-off values could be advocated and used as part of the screening of MCI among older Malaysian adults. There is a need to further determine the predictive values of these cut-off points on outcomes through longitudinal study design.

Oxidative status in different settings and with different methodological approaches compared by Receiver Operating Characteristic curve analysis.

PubMed

Cighetti, Giuliana; Bamonti, Fabrizia; Aman, Caroline S; Gregori, Dario; De Giuseppe, Rachele; Novembrino, Cristina; de Liso, Federica; Maiavacca, Rita; Paroni, Rita

2015-01-01

To test the performance of different analytical approaches in highlighting the occurrence of deregulated redox status in various physio-pathological situations. 35 light and 61 heavy smokers, 19 chronic renal failure, 59 kidney transplanted patients, and 87 healthy controls were retrospectively considered for the study. Serum oxidative stress and antioxidant status, assessed by spectrophotometric Reactive Oxygen Metabolites (d-ROMs) and Total Antioxidant Capacity (TAC) tests, respectively, were compared with plasma free (F-MDA) and total (T-MDA) malondialdehyde, both quantified by isotope-dilution-gas chromatography-mass spectrometry (ID-GC-MS). Sensitivity, specificity and cut-off points of T-MDA, F-MDA, d-ROMs and TAC were evaluated by both Receiver Operating Characteristic (ROC) analyses and area under the ROC curve (AUC). Only T-MDA assay showed a clear absence of oxidative stress in controls and significant increase in all patients (AUC 1.00, sensitivity and specificity 100%). Accuracy was good for d-ROMs (AUC 0.87, sensitivity 72.8%, specificity 100%) and F-MDA (AUC 0.82, sensitivity 74.7%, specificity 83.9%), but not high enough for TAC to show in patients impaired antioxidant defense (AUC 0.66, sensitivity 52.0%, specificity 92.9%). This study reveals T-MDA as the best marker to detect oxidative stress, shows the ability of d-ROMs to identify modified oxidative status particularly in the presence of high damages, and evidences the poor TAC performance. d-ROMs and TAC assays could be useful for routine purposes; however, for an accurate clinical data evaluation, their comparison versus a "gold standard method" is required. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Anthropometric measurements in the diagnosis of pelvic size: an analysis of maternal height and shoe size and computed tomography pelvimetric data.

PubMed

Awonuga, Awoniyi O; Merhi, Zaher; Awonuga, Modupe T; Samuels, Terri-Ann; Waller, Jennifer; Pring, David

2007-11-01

To determine whether measurements of maternal height and shoe size are predictors of pelvic size, using erect lateral computerized tomography (CT) pelvimetry as gold standard. Three hundred and fifty three obstetric patients out of a sequential population of 6112 (5.8%) had CT pelvimetry performed between January 1990 and December 1991 at the Department of Obstetrics and Gynecology, York District Hospital, United Kingdom. Multivariable logistic regression models were built using maternal height (n = 322), shoe size (314) and weight at last clinic visit (n = 318). The reference standard for pelvic size was CT Pelvimetry. Pelvic adequacy was defined as an anterior-posterior diameter of the inlet of > or =11 cm and an anterior-posterior diameter of the outlet > or =10 cm on erect lateral CT pelvimetry. Women with values lower than these were regarded as having an inadequate pelvis. The diagnostic accuracy of the models was determined by the area under the receiver operating characteristic curve (AUC). The area under the curve (AUC) for maternal height (0.768) was not significantly greater than that for shoe size (0.686, p = 0.163 for the difference in AUC's) and weight at the last clinic visit (0.655, p = 0.057 for the difference in the AUCs). The change in the AUC for each of the models (the full model with height, shoe size and weight [0.769]; model for height and shoe size [0.767] model for just height [0.768]) was also not significantly different. Measurements of maternal height, shoe size and weight at the last clinic visit are not useful for the identification of women with inadequate pelvis.

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer

PubMed Central

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Chang, Shu-Shya; Rau, Cheng-Shyuan; Tai, Hsueh-Ling; Peng, Shu-Hui; Lin, Yi-Chun; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-01-01

Background The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR). Materials and methods There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score. Results ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P<0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance. Conclusion The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer. PMID:29568393

Accuracy of i-Scan for Optical Diagnosis of Colonic Polyps: A Meta-Analysis

PubMed Central

Guo, Chuan-Guo; Ji, Rui; Li, Yan-Qing

2015-01-01

Background i-Scan is a novel virtual chromoendoscopy system designed to enhance surface and vascular patterns to improve optical diagnostic performance. Numerous prospective studies have been done to evaluate the accuracy of i-Scan in differentiating colonic neoplasms from non-neoplasms. i-Scan could be an effective endoscopic technique for optical diagnosis of colonic polyps. Objective Our aim of this study was to perform a meta-analysis of published data to establish the diagnostic accuracy of i-Scan for optical diagnosis of colonic polyps. Methods We searched PubMed, Medline, Elsevier ScienceDirect and Cochrane Library databases. We used a bivariate meta-analysis following a random effects model to summarize the data and plotted hierarchical summary receiver-operating characteristic (HSROC) curves. The area under the HSROC curve (AUC) serves as an indicator of the diagnostic accuracy. Results The meta-analysis included a total of 925 patients and 2312 polyps. For the overall studies, the area under the HSROC curve was 0.96. The summary sensitivity was 90.4% (95%CI 85%-94.1%) and specificity was 90.9% (95%CI 84.3%-94.9%). In 11 studies predicting polyps histology in real-time, the summary sensitivity and specificity was 91.5% (95%CI 85.7%-95.1%) and 92.1% (95%CI 84.5%-96.1%), respectively, with the AUC of 0.97. For three different diagnostic criteria (Kudo, NICE, others), the sensitivity was 86.3%, 93.0%, 85.0%, respectively and specificity was 84.8%, 94.4%, 91.8%, respectively. Conclusions Endoscopic diagnosis with i-Scan has accurate optical diagnostic performance to differentiate neoplastic from non-neoplastic polyps with an area under the HSROC curve exceeding 0.90. Both the sensitivity and specificity for diagnosing colonic polyps are over 90%. PMID:25978459

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

Liu, Bangjian; Huang, Yujing; Sun, Yuanjue; Zhang, Jianjun; Yao, Yang; Shen, Zan; Xiang, Dongxi; He, Aina

2016-01-01

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients. PMID:28008988

Latent information in fluency lists predicts functional decline in persons at risk for Alzheimer disease.

PubMed

Clark, D G; Kapur, P; Geldmacher, D S; Brockington, J C; Harrell, L; DeRamus, T P; Blanton, P D; Lokken, K; Nicholas, A P; Marson, D C

2014-06-01

We constructed random forest classifiers employing either the traditional method of scoring semantic fluency word lists or new methods. These classifiers were then compared in terms of their ability to diagnose Alzheimer disease (AD) or to prognosticate among individuals along the continuum from cognitively normal (CN) through mild cognitive impairment (MCI) to AD. Semantic fluency lists from 44 cognitively normal elderly individuals, 80 MCI patients, and 41 AD patients were transcribed into electronic text files and scored by four methods: traditional raw scores, clustering and switching scores, "generalized" versions of clustering and switching, and a method based on independent components analysis (ICA). Random forest classifiers based on raw scores were compared to "augmented" classifiers that incorporated newer scoring methods. Outcome variables included AD diagnosis at baseline, MCI conversion, increase in Clinical Dementia Rating-Sum of Boxes (CDR-SOB) score, or decrease in Financial Capacity Instrument (FCI) score. Receiver operating characteristic (ROC) curves were constructed for each classifier and the area under the curve (AUC) was calculated. We compared AUC between raw and augmented classifiers using Delong's test and assessed validity and reliability of the augmented classifier. Augmented classifiers outperformed classifiers based on raw scores for the outcome measures AD diagnosis (AUC .97 vs. .95), MCI conversion (AUC .91 vs. .77), CDR-SOB increase (AUC .90 vs. .79), and FCI decrease (AUC .89 vs. .72). Measures of validity and stability over time support the use of the method. Latent information in semantic fluency word lists is useful for predicting cognitive and functional decline among elderly individuals at increased risk for developing AD. Modern machine learning methods may incorporate latent information to enhance the diagnostic value of semantic fluency raw scores. These methods could yield information valuable for patient care and clinical trial design with a relatively small investment of time and money. Published by Elsevier Ltd.

Fluoroquinolone resistance in Streptococcus pneumoniae: area under the concentration-time curve/MIC ratio and resistance development with gatifloxacin, gemifloxacin, levofloxacin, and moxifloxacin.

PubMed

LaPlante, Kerry L; Rybak, Michael J; Tsuji, Brian; Lodise, Thomas P; Kaatz, Glenn W

2007-04-01

The potential for resistance development in Streptococcus pneumoniae secondary to exposure to gatifloxacin, gemifloxacin, levofloxacin, and moxifloxacin at various levels was examined at high inoculum (10(8.5) to 10(9) log10 CFU/ml) over 96 h in an in vitro pharmacodynamic (PD) model using two fluoroquinolone-susceptible isolates. The pharmacokinetics of each drug was simulated to provide a range of free areas under the concentration-time curves (fAUC) that correlated with various fluoroquinolone doses. Potential first (parC and parE)- and second-step (gyrA and gyrB) mutations in isolates with raised MICs were identified by sequence analysis. PD models simulating fAUC/MICs of 51 andgatifloxacin>moxifloxacin=gemifloxacin, which may be related to structural differences within the class.

Limited Sampling Strategy for the Prediction of Area Under the Curve (AUC) of Statins: Reliability of a Single Time Point for AUC Prediction for Pravastatin and Simvastatin.

PubMed

Srinivas, N R

2016-02-01

Statins are widely prescribed medicines and are also available in fixed dose combinations with other drugs to treat several chronic ailments. Given the safety issues associated with statins it may be important to assess feasibility of a single time concentration strategy for prediction of exposure (area under the curve; AUC). The peak concentration (Cmax) was used to establish relationship with AUC separately for pravastatin and simvastatin using published pharmacokinetic data. The regression equations generated for statins were used to predict the AUC values from various literature references. The fold difference of the observed divided by predicted values along with correlation coefficient (r) were used to judge the feasibility of the single time point approach. Both pravastatin and simvastatin showed excellent correlation of Cmax vs. AUC values with r value ≥ 0.9638 (p<0.001). The fold difference was within 0.5-fold to 2-fold for 220 out of 227 AUC predictions and >81% of the predicted values were in a narrower range of >0.75-fold but <1.5-fold difference. Predicted vs. observed AUC values showed excellent correlation for pravastatin (r=0.9708, n=115; p<0.001) and simvastatin (r=0.9810; n=117; p<0.001) suggesting the utility of Cmax for AUC predictions. On the basis of the present work, it is feasible to develop a single concentration time point strategy that coincides with Cmax occurrence for both pravastatin and simvastatin from a therapeutic drug monitoring perspective. © Georg Thieme Verlag KG Stuttgart · New York.

Antimüllerian hormone as a predictor of live birth following assisted reproduction: an analysis of 85,062 fresh and thawed cycles from the Society for Assisted Reproductive Technology Clinic Outcome Reporting System database for 2012-2013.

PubMed

Tal, Reshef; Seifer, David B; Wantman, Ethan; Baker, Valerie; Tal, Oded

2018-02-01

To determine if serum antimüllerian hormone (AMH) is associated with and/or predictive of live birth assisted reproductive technology (ART) outcomes. Retrospective analysis of Society for Assisted Reproductive Technology Clinic Outcome Reporting System database from 2012 to 2013. Not applicable. A total of 69,336 (81.8%) fresh and 15,458 (18.2%) frozen embryo transfer (FET) cycles with AMH values. None. Live birth. A total of 85,062 out of 259,499 (32.7%) fresh and frozen-thawed autologous non-preimplantation genetic diagnosis cycles had AMH reported for cycles over this 2-year period. Of those, 70,565 cycles which had embryo transfers were included in the analysis. Serum AMH was significantly associated with live birth outcome per transfer in both fresh and FET cycles. Multiple logistic regression demonstrated that AMH is an independent predictor of live birth in fresh transfer cycles and FET cycles when controlling for age, body mass index, race, day of transfer, and number of embryos transferred. Receiver operating characteristic (ROC) curves demonstrated that the areas under the curve (AUC) for AMH as predictors of live birth in fresh cycles and thawed cycles were 0.631 and 0.540, respectively, suggesting that AMH alone is a weak independent predictor of live birth after ART. Similar ROC curves were obtained also when elective single-embryo transfer (eSET) cycles were analyzed separately in either fresh (AUC 0.655) or FET (AUC 0.533) cycles, although AMH was not found to be an independent predictor in eSET cycles. AMH is a poor independent predictor of live birth outcome in either fresh or frozen embryo transfer for both eSET and non-SET transfers. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Hyperglycemic clamp and oral glucose tolerance test for 3-year prediction of clinical onset in persistently autoantibody-positive offspring and siblings of type 1 diabetic patients.

PubMed

Balti, Eric V; Vandemeulebroucke, Evy; Weets, Ilse; Van De Velde, Ursule; Van Dalem, Annelien; Demeester, Simke; Verhaeghen, Katrijn; Gillard, Pieter; De Block, Christophe; Ruige, Johannes; Keymeulen, Bart; Pipeleers, Daniel G; Decochez, Katelijn; Gorus, Frans K

2015-02-01

In preparation of future prevention trials, we aimed to identify predictors of 3-year diabetes onset among oral glucose tolerance test (OGTT)- and hyperglycemic clamp-derived metabolic markers in persistently islet autoantibody positive (autoAb(+)) offspring and siblings of patients with type 1 diabetes (T1D). The design is a registry-based study. Functional tests were performed in a hospital setting. Persistently autoAb(+) first-degree relatives of patients with T1D (n = 81; age 5-39 years). We assessed 3-year predictive ability of OGTT- and clamp-derived markers using receiver operating characteristics (ROC) and Cox regression analysis. Area under the curve of clamp-derived first-phase C-peptide release (AUC(5-10 min); min 5-10) was determined in all relatives and second-phase release (AUC(120-150 min); min 120-150) in those aged 12-39 years (n = 62). Overall, the predictive ability of AUC(5-10 min) was better than that of peak C-peptide, the best predictor among OGTT-derived parameters (ROC-AUC [95%CI]: 0.89 [0.80-0.98] vs 0.81 [0.70-0.93]). Fasting blood glucose (FBG) and AUC(5-10 min) provided the best combination of markers for prediction of diabetes within 3 years; (ROC-AUC [95%CI]: 0.92 [0.84-1.00]). In multivariate Cox regression analysis, AUC(5-10 min)) (P = .001) was the strongest independent predictor and interacted significantly with all tested OGTT-derived parameters. AUC(5-10 min) below percentile 10 of controls was associated with 50-70% progression to T1D regardless of age. Similar results were obtained for AUC(120-150 min). Clamp-derived first-phase C-peptide release can be used as an efficient and simple screening strategy in persistently autoAb(+) offspring and siblings of T1D patients to predict impending diabetes.

Advances toward fully automated in vivo assessment of oral epithelial dysplasia by nuclear endomicroscopy-A pilot study.

PubMed

Liese, Jan; Winter, Karsten; Glass, Änne; Bertolini, Julia; Kämmerer, Peer Wolfgang; Frerich, Bernhard; Schiefke, Ingolf; Remmerbach, Torsten W

2017-11-01

Uncertainties in detection of oral epithelial dysplasia (OED) frequently result from sampling error especially in inflammatory oral lesions. Endomicroscopy allows non-invasive, "en face" imaging of upper oral epithelium, but parameters of OED are unknown. Mucosal nuclei were imaged in 34 toluidine blue-stained oral lesions with a commercial endomicroscopy. Histopathological diagnosis showed four biopsies in "dys-/neoplastic," 23 in "inflammatory," and seven in "others" disease groups. Strength of different assessment strategies of nuclear scoring, nuclear count, and automated nuclear analysis were measured by area under ROC curve (AUC) to identify histopathological "dys-/neoplastic" group. Nuclear objects from automated image analysis were visually corrected. Best-performing parameters of nuclear-to-image ratios were the count of large nuclei (AUC=0.986) and 6-nearest neighborhood relation (AUC=0.896), and best parameters of nuclear polymorphism were the count of atypical nuclei (AUC=0.996) and compactness of nuclei (AUC=0.922). Excluding low-grade OED, nuclear scoring and count reached 100% sensitivity and 98% specificity for detection of dys-/neoplastic lesions. In automated analysis, combination of parameters enhanced diagnostic strength. Sensitivity of 100% and specificity of 87% were seen for distances of 6-nearest neighbors and aspect ratios even in uncorrected objects. Correction improved measures of nuclear polymorphism only. The hue of background color was stronger than nuclear density (AUC=0.779 vs 0.687) to detect dys-/neoplastic group indicating that macroscopic aspect is biased. Nuclear-to-image ratios are applicable for automated optical in vivo diagnostics for oral potentially malignant disorders. Nuclear endomicroscopy may promote non-invasive, early detection of dys-/neoplastic lesions by reducing sampling error. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A New Harmonized Approach to Estimate Busulfan Exposure Predicts Survival and Toxicity after Hematopoietic Cell Transplantation in Children and Young Adults: a Multicenter Retrospective Cohort Analysis

PubMed Central

Bartelink, I.H.; Lalmohamed, Arief; van Reij, Elisabeth M.L.; Dvorak, Chris C.; Savic, Rada M.; Zwaveling, Juliette; Bredius, Robbert. G.M.; Egberts, Antoine C.G.; Bierings, M.; Kletzel, M.; Shaw, Peter J.; Nath, Christa E.; Hempel, George; Ansari, M.; Krajinovic, M.; Theoret, Yves; Duval, Michel; Keizer, Ron J.; Bittencourt, Henriette; Hassan, Moustapha; Güngör, Tayfun; Wynn, Robert F.; Veys, Paul; Cuvelier, Geoff D.E.; Marktel, Sarah; Chiesa, Robert; Cowan, Morton J.; Slatter, Mary A.; Stricherz, Melisa K.; Jennissen, Cathryn; Long-Boyle, Janel R.; Boelens, Jaap Jan

2016-01-01

Background Intravenous-busulfan (IV-busulfan) combined with therapeutic drug monitoring to guide dosing improves outcomes after allogeneic hematopoietic cell transplantation (allo-HCT). The best method to estimate busulfan exposure and the optimal exposure in children/young adults remains unclear. We therefore evaluated three approaches to estimate IV-Bu exposure (expressed as cumulative-area-under-the-curve; AUC) and associated busulfan-AUC with clinical outcomes in children/young adults undergoing allo-HCT. Methods In this retrospective analysis, patients (0.1–30.4 years) receiving busulfan-based conditioning regimen from 15 centers were included. Cumulative AUC was calculated by numerical integration using non-linear mixed effect modeling (AUCNONMEM), non-compartmental analysis (AUC0-infinity and AUC to the end of the dose interval AUC0-tau) and by individual centers using a variety of approaches (AUCcenter). Main outcome of interest was event-free survival (EFS). Other outcomes of interest were overall survival, graft-failure, relapse, transplantation related mortality (TRM), acute toxicity (veno-occlusive disease (VOD) and/or acute graft versus-host disease (aGvHD), chronic GvHD (cGvHD) and cGVHD-free event-free survival (GEFS). Propensity score adjusted cox proportional hazard models, Weibull models, and Fine-Gray competing risk regressions were used. Results 674 patients were included (41% malignant, 59% non-malignant) Estimated 2-year EFS was 69.7%. The median busulfan AUCNONMEM was 74.4 mg*h/L (CI95% 31.1–104.6 mg*h/L). The median AUCNONMEM correlated poorly with AUCcenter (R2 = 0.254). Patients with optimal IV-busulfan AUC of 78–101 mg*h/L showed 81% EFS at 2 years compared to 66.1% and 49.5% in the low (<78 mg*h/L) and high (>101 mg*h/L) busulfan AUC group respectively (P=0.011). Graft-failure/relapse occurred more frequently in the low AUC group (HR=1.75 P<0.001). Acute toxicity, cGvHD and TRM was significantly higher in the high AUC group (HR 1.69, 2.99 and 1.30), independent of indication. Interpretation These results demonstrate that improved clinical outcomes may be achieved by targeting the busulfan-AUC to 78–101 mg*h/L using a new validated pharmacokinetic-model for all indications. PMID:27746112

PAX1 and SOX1 methylation as an initial screening method for cervical cancer: a meta-analysis of individual studies in Asians

PubMed Central

Cui, Zhaolei; Xiao, Zhenzhou; Hu, Minhua; Jiang, Chuanhui; Lin, Yingying; Chen, Yansong

2016-01-01

Background Epigenetic alterations of gene or DNA methylation have been highlighted as promising biomarkers for early cervical cancer screening. Herein, we evaluated the diagnostic performance of paired boxed gene 1 (PAX1) and sex determining region Y-box 1 (SOX1) methylation for cervical cancer detection. Methods Eligible studies were retrieved by searching the electronic databases. Study quality was assessed according to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) checklist. The bivariate meta-analysis model was employed to plot the summary receiver operator characteristic (SROC) curve using Stata 12.0 software. Results The pooled sensitivity of PAX1 methylation was estimated to be 0.73 [95% confidence interval (CI): 0.70–0.75] in differentiating patients with HSIL (high-grade squamous intraepithelial lesion) or CIN3+ (cervical intraepithelial neoplasia type III/worse) or cervical cancer from normal individuals, corresponding to a specificity of 0.87 (95% CI: 0.85–0.89) and area under the curve (AUC) of 0.91. The SOX1 methylation test yielded an AUC of 0.82, under which, the pooled sensitivity was 0.71 (95% CI: 0.67–0.74) and specificity was 0.64 (95% CI: 0.61–0.67). Notably, the stratified analysis suggested that combing parallel testing of PAX1 methylation and human papillomavirus (HPV) DNA (AUC, sensitivity, and specificity of 0.89, 0.75, and 0.81, respectively) achieved higher accuracy than single HPV DNA testing (AUC, sensitivity, and specificity of 0.77, 0.81, and 0.70, respectively). Conclusions PAX1 or SOX1 methylation has a prospect to be an auxiliary biomarker for cervical cancer screening, and parallel testing of PAX1 methylation and HPV DNA in cervical swabs confers an improved diagnostic accuracy than single HPV DNA testing. PMID:27826568

Vancomycin AUC/MIC ratio and 30-day mortality in patients with Staphylococcus aureus bacteremia.

PubMed

Holmes, Natasha E; Turnidge, John D; Munckhof, Wendy J; Robinson, J Owen; Korman, Tony M; O'Sullivan, Matthew V N; Anderson, Tara L; Roberts, Sally A; Warren, Sanchia J C; Gao, Wei; Howden, Benjamin P; Johnson, Paul D R

2013-04-01

A ratio of the vancomycin area under the concentration-time curve to the MIC (AUC/MIC) of ≥ 400 has been associated with clinical success when treating Staphylococcus aureus pneumonia, and this target was recommended by recently published vancomycin therapeutic monitoring consensus guidelines for treating all serious S. aureus infections. Here, vancomycin serum trough levels and vancomycin AUC/MIC were evaluated in a "real-world" context by following a cohort of 182 patients with S. aureus bacteremia (SAB) and analyzing these parameters within the critical first 96 h of vancomycin therapy. The median vancomycin trough level at this time point was 19.5 mg/liter. There was a significant difference in vancomycin AUC/MIC when using broth microdilution (BMD) compared with Etest MIC (medians of 436.1 and 271.5, respectively; P < 0.001). Obtaining the recommended vancomycin target AUC/MIC of ≥ 400 using BMD was not associated with lower 30-day all-cause or attributable mortality from SAB (P = 0.132 and P = 0.273, respectively). However, an alternative vancomycin AUC/MIC of >373, derived using classification and regression tree analysis, was associated with reduced mortality (P = 0.043) and remained significant in a multivariable model. This study demonstrated that we obtained vancomycin trough levels in the target therapeutic range early during the course of therapy and that obtaining a higher vancomycin AUC/MIC (in this case, >373) within 96 h was associated with reduced mortality. The MIC test method has a significant impact on vancomycin AUC/MIC estimation. Clinicians should be aware that the current target AUC/MIC of ≥ 400 was derived using the reference BMD method, so adjustments to this target need to be made when calculating AUC/MIC ratio using other MIC testing methods.

Vancomycin AUC/MIC Ratio and 30-Day Mortality in Patients with Staphylococcus aureus Bacteremia

PubMed Central

Turnidge, John D.; Munckhof, Wendy J.; Robinson, J. Owen; Korman, Tony M.; O'Sullivan, Matthew V. N.; Anderson, Tara L.; Roberts, Sally A.; Warren, Sanchia J. C.; Gao, Wei; Howden, Benjamin P.; Johnson, Paul D. R.

2013-01-01

A ratio of the vancomycin area under the concentration-time curve to the MIC (AUC/MIC) of ≥400 has been associated with clinical success when treating Staphylococcus aureus pneumonia, and this target was recommended by recently published vancomycin therapeutic monitoring consensus guidelines for treating all serious S. aureus infections. Here, vancomycin serum trough levels and vancomycin AUC/MIC were evaluated in a “real-world” context by following a cohort of 182 patients with S. aureus bacteremia (SAB) and analyzing these parameters within the critical first 96 h of vancomycin therapy. The median vancomycin trough level at this time point was 19.5 mg/liter. There was a significant difference in vancomycin AUC/MIC when using broth microdilution (BMD) compared with Etest MIC (medians of 436.1 and 271.5, respectively; P < 0.001). Obtaining the recommended vancomycin target AUC/MIC of ≥400 using BMD was not associated with lower 30-day all-cause or attributable mortality from SAB (P = 0.132 and P = 0.273, respectively). However, an alternative vancomycin AUC/MIC of >373, derived using classification and regression tree analysis, was associated with reduced mortality (P = 0.043) and remained significant in a multivariable model. This study demonstrated that we obtained vancomycin trough levels in the target therapeutic range early during the course of therapy and that obtaining a higher vancomycin AUC/MIC (in this case, >373) within 96 h was associated with reduced mortality. The MIC test method has a significant impact on vancomycin AUC/MIC estimation. Clinicians should be aware that the current target AUC/MIC of ≥400 was derived using the reference BMD method, so adjustments to this target need to be made when calculating AUC/MIC ratio using other MIC testing methods. PMID:23335735

Diagnosis of adrenal insufficiency.

PubMed

Dorin, Richard I; Qualls, Clifford R; Crapo, Lawrence M

2003-08-05

The cosyntropin stimulation test is the initial endocrine evaluation of suspected primary or secondary adrenal insufficiency. To critically review the utility of the cosyntropin stimulation test for evaluating adrenal insufficiency. The MEDLINE database was searched from 1966 to 2002 for all English-language papers related to the diagnosis of adrenal insufficiency. Studies with fewer than 5 persons with primary or secondary adrenal insufficiency or with fewer than 10 persons as normal controls were excluded. For secondary adrenal insufficiency, only studies that stratified participants by integrated tests of adrenal function were included. Summary receiver-operating characteristic (ROC) curves were generated from all studies that provided sensitivity and specificity data for 250-microg and 1-microg cosyntropin tests; these curves were then compared by using area under the curve (AUC) methods. All estimated values are given with 95% CIs. At a specificity of 95%, sensitivities were 97%, 57%, and 61% for summary ROC curves in tests for primary adrenal insufficiency (250-microg cosyntropin test), secondary adrenal insufficiency (250-microg cosyntropin test), and secondary adrenal insufficiency (1-microg cosyntropin test), respectively. The area under the curve for primary adrenal insufficiency was significantly greater than the AUC for secondary adrenal insufficiency for the high-dose cosyntropin test (P < 0.001), but AUCs for the 250-microg and 1-microg cosyntropin tests did not differ significantly (P > 0.5) for secondary adrenal insufficiency. At a specificity of 95%, summary ROC analysis for the 250-microg cosyntropin test yielded a positive likelihood ratio of 11.5 (95% CI, 8.7 to 14.2) and a negative likelihood ratio of 0.45 (CI, 0.30 to 0.60) for the diagnosis of secondary adrenal insufficiency. Cortisol response to cosyntropin varies considerably among healthy persons. The cosyntropin test performs well in patients with primary adrenal insufficiency, but the lower sensitivity in patients with secondary adrenal insufficiency necessitates use of tests involving stimulation of the hypothalamus if the pretest probability is sufficiently high. The operating characteristics of the 250-microg and 1-microg cosyntropin tests are similar.

Proposal for defining the relevance of drug accumulation derived from single dose study data for modified release dosage forms

PubMed Central

Scheerans, Christian; Heinig, Roland; Mueck, Wolfgang

2015-01-01

Recently, the European Medicines Agency (EMA) published the new draft guideline on the pharmacokinetic and clinical evaluation of modified release (MR) formulations. The draft guideline contains the new requirement of performing multiple dose (MD) bioequivalence studies, in the case when the MR formulation is expected to show ‘relevant’ drug accumulation at steady state (SS). This new requirement reveals three fundamental issues, which are discussed in the current work: first, measurement for the extent of drug accumulation (MEDA) predicted from single dose (SD) study data; second, its relationship with the percentage residual area under the plasma concentration–time curve (AUC) outside the dosing interval (τ) after SD administration, %AUC(τ-∞)SD; and third, the rationale for a threshold of %AUC(τ-∞)SD that predicts ‘relevant’ drug accumulation at SS. This work revealed that the accumulation ratio RA,AUC, derived from the ratio of the time-averaged plasma concentrations during τ at SS and after SD administration, respectively, is the ‘preferred’ MEDA for MR formulations. A causal relationship was derived between %AUC(τ-∞)SD and RA,AUC, which is valid for any drug (product) that shows (dose- and time-) linear pharmacokinetics regardless of the shape of the plasma concentration–time curve. Considering AUC thresholds from other guidelines together with the causal relationship between %AUC(τ-∞)SD and RA,AUC indicates that values of %AUC(τ-∞)SD ≤ 20%, resulting in RA,AUC ≤ 1.25, can be considered as leading to non-relevant drug accumulation. Hence, the authors suggest that 20% for %AUC(τ-∞)SD is a reasonable threshold and selection criterion between SD or MD study designs for bioequivalence studies of new MR formulations. © 2014 The Authors Biopharmaceutics & Drug Disposition Published by John Wiley & Sons Ltd. PMID:25327367

PAX1 Methylation Hallmarks Promising Accuracy for Cervical Cancer Screening in Asians: Results from a Meta-Analysis.

PubMed

Kong, Ling-Ying; Du, Wei; Wang, Li; Yang, Zhi; Zhang, Hong-Sheng

2015-01-01

DNA methylation has been proposed as a potential biomarker for cervical cancer detection. This study aimed to evaluate the diagnostic role of paired boxed gene 1 (PAX1) methylation for cervical cancer screening in Asians. Eligible studies were retrieved by searching the electronic databases, and the quality of the enrolled studies was assessed via the quality assessment for studies of diagnostic accuracy (QUADAS) tool. The bivariate meta-analysis model was employed to generate the summary receiver operator characteristic (SROC) curve using Stata 12.0 software. Cochran's Q test and I2 statistics were applied to assess heterogeneity among studies. Publication bias was evaluated by the Deeks' funnel plot asymmetry test. A total of 9 articles containing 15 individual studies were included. The SROC analysis showed that single PAX1 methylation allowed for the discrimination between cancer/high-grade squamous intraepithelial lesion (HSIL) patients and normal individuals with a sensitivity (95% confidence interval) of 0.80 (0.70 - 0.87) and specificity of 0.89 (0.86 - 0.92), corresponding to an area under curve (AUC) of 0.92. Notably, our subgroup analysis suggested that combing parallel testing of PAX1 methylation and HPV DNA (AUC, sensitivity, and specificity of 0.90, 0.82, and 0.84, respectively) seemed to harbor higher accuracy than single HPV DNA testing (AUC, sensitivity, and specificity of 0.81, 0.86, and 0.67, respectively). PAX1 methylation hallmarks a potential diagnostic value for cervical cancer screening in Asians, and parallel testing of PAX1 methylation and HPV in cervical scrapings confers an improved accuracy than single HPV DNA testing.

Bioequivalence Study of Rivastigmine 6 mg Capsules (Single Dose) in Healthy Volunteers.

PubMed

Abhyankar, Dhiraj; Shedage, Ashish; Gole, Milind; Raut, Preeti

2017-09-01

To assess the bioequivalence of generic formulation of rivastigmine (test) and Exelon (reference). This randomized, open-label, 2-period, single-dose, 2-treatment, 2-sequence, crossover study was conducted in 40 healthy men under fed condition. Participants were randomized to receive a single dose of Exelon or rivastigmine capsule. A total of 31 participants completed the study. Area under the concentration-time curve from time zero to time t (AUC 0- t ) and area under the concentration-time curve from time zero to infinity (AUC 0-∞ ) for Exelon (mean [standard deviation], h·ng/mL) were 126.40 (56.95) and 129.46 (59.94), respectively, while they were 122.73 (43.46) and 125.08 (45.39) for rivastigmine. Geometric mean ratios of rivastigmine/Exelon were 99.17% for AUC 0- t , 98.81% for AUC 0-∞ , and 105% for maximum observed plasma concentration ( C max ). The 90% confidence intervals (CIs) were 94.14% to 104.46%, 93.77% to 104.12%, and 93.08% to 118.44%, respectively. Both formulations were well tolerated. The generic and reference formulations were bioequivalent, as the 90% CIs for C max , AUC 0- t , and AUC 0-∞ were within the range of 80% to 125%.

Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue.

PubMed

Adubeiro, Nuno; Nogueira, Maria Luísa; Nunes, Rita G; Ferreira, Hugo Alexandre; Ribeiro, Eduardo; La Fuente, José Maria Ferreira

Determining optimal b-value pair for differentiation between normal and prostate cancer (PCa) tissues. Forty-three patients with diagnosis or PCa symptoms were included. Apparent diffusion coefficient (ADC) was estimated using minimum and maximum b-values of 0, 50, 100, 150, 200, 500s/mm2 and 500, 800, 1100, 1400, 1700 and 2000s/mm2, respectively. Diagnostic performances were evaluated when Area-under-the-curve (AUC)>95%. 15 of the 35 b-values pair surpassed this AUC threshold. The pair (50, 2000s/mm2) provided the highest AUC (96%) with ADC cutoff 0.89×10- 3 mm 2 /s, sensitivity 95.5%, specificity 93.2% and accuracy 94.4%. The best b-value pair was b=50, 2000s/mm2. Copyright © 2017 Elsevier Inc. All rights reserved.

Diagnostic efficiency of an ability-focused battery.

PubMed

Miller, Justin B; Fichtenberg, Norman L; Millis, Scott R

2010-05-01

An ability-focused battery (AFB) is a selected group of well-validated neuropsychological measures that assess the conventional range of cognitive domains. This study examined the diagnostic efficiency of an AFB for use in clinical decision making with a mixed sample composed of individuals with neurological brain dysfunction and individuals referred for cognitive assessment without evidence of neurological disorders. Using logistic regression analyses and ROC curve analysis, a five-domain model composed of attention, processing speed, visual-spatial reasoning, language/verbal reasoning, and memory domain scores was fitted that had an AUC of.89 (95% CI =.84-.95). A more parsimonious two-domain model using processing speed and memory was also fitted that had an AUC of.90 (95% confidence interval =.84-.95). A model composed of a global ability score calculated from the mean of the individual domain scores was also fitted with an AUC of.88 (95% CI =.82-.94).

Comparative Pharmacodynamics and Antimutant Potentials of Doripenem and Imipenem with Ciprofloxacin-Resistant Pseudomonas aeruginosa in an In Vitro Model

PubMed Central

Gilbert, Deborah; Greer, Kenneth; Portnoy, Yury A.; Zinner, Stephen H.

2012-01-01

To compare the antipseudomonal efficacy of doripenem and imipenem as well as their abilities to restrict the enrichment of resistant Pseudomonas aeruginosa, multiple-dosing regimens of each drug were simulated at comparable values of the cumulative percentages of a 24-h period that the drug concentration exceeds the MIC under steady-state pharmacokinetic conditions (T>MIC) and ratios of the 24-hour area under the curve (AUC24) to the MIC. Three clinical isolates of ciprofloxacin-resistant P. aeruginosa (MIC of doripenem, 1 μg/ml; MICs of imipenem, 1, 2, and 2 μg/ml) were exposed to thrice-daily doripenem or imipenem for 3 days at AUC24/MIC ratios of from 50 to 170 h (doripenem) and from 30 to 140 h (imipenem). The antimicrobial effects for susceptible and resistant subpopulations of bacteria were expressed by the areas between control growth and time-kill curves (IEs) and areas under the bacterial mutant concentration curves (AUBCMs), respectively. With each antibiotic, the IE and AUBCM versus log AUC24/MIC relationships were bacterial strain independent. At similar AUC24/MIC ratios, doripenem was slightly less efficient than imipenem against susceptible and resistant subpopulations of bacteria. However, doripenem appeared to be somewhat more efficient than imipenem at clinically achievable AUC24s related to the means of the MICs for the three studied strains and had higher antimutant potentials for two of the three strains. PMID:22203591

Work Ability Index as tool to identify workers at risk of premature work exit.

PubMed

Roelen, Corné A M; Heymans, Martijn W; Twisk, Jos W R; van der Klink, Jac J L; Groothoff, Johan W; van Rhenen, Willem

2014-12-01

To investigate the Work Ability Index (WAI) as tool for identifying workers at risk of premature work exit in terms of disability pension, unemployment, or early retirement. Prospective cohort study of 11,537 male construction workers (mean age 45.5 years), who completed the WAI at baseline and reported their work status (employed, unemployed, disability pension, or retired) after mean 2.3 years of follow-up. Associations between WAI scores and work status were investigated by multinomial logistic regression analysis. The ability of the WAI to discriminate between workers at high and low risk of premature work exit was analyzed by the area (AUC) under the receiver operating characteristic curve. 9,530 (83 %) construction workers had complete data for analysis. At follow-up, 336 (4 %) workers reported disability pension, 125 (1 %) unemployment, and 255 (3 %) retirement. WAI scores were prospectively associated with the risk of disability pension at follow-up, but not with the risk of unemployment and early retirement. The WAI showed fair discrimination to identify workers at risk of disability pension [AUC = 0.74; 95 % confidence interval (CI) 0.70-0.77]. The discriminative ability decreased with age from AUC = 0.78 in workers aged 30-39 years to AUC = 0.69 in workers ≥50 years of age. Discrimination failed for unemployment (AUC = 0.51; 95 % CI 0.47-0.55) and early retirement (AUC = 0.58; 95 % CI 0.53-0.61). The WAI can be used to identify construction workers <50 years of age at increased risk of disability pension and invite them for preventive interventions.

ABT492 and levofloxacin: comparison of their pharmacodynamics and their abilities to prevent the selection of resistant Staphylococcus aureus in an in vitro dynamic model.

PubMed

Firsov, Alexander A; Vostrov, Sergey N; Lubenko, Irene Yu; Arzamastsev, Alexander P; Portnoy, Yury A; Zinner, Stephen H

2004-07-01

To compare the kinetics of killing/regrowth of differentially susceptible clinical isolates of Staphylococcus aureus exposed to ABT492 and levofloxacin and to explore their relative abilities to prevent the selection of resistant mutants. Three clinical isolates of S. aureus--including two ciprofloxacin-susceptible S. aureus, 201 and 480--and a ciprofloxacin-resistant S. aureus 866, were exposed to clinically achievable ratios of area under the curve (AUC) to MIC in a dynamic model that simulated human pharmacokinetics of ABT492 (400 mg) and levofloxacin (500 mg) as a single dose. In addition, S. aureus 201 was exposed to single and multiple doses of ABT492 and levofloxacin (both once daily for 3 days) over wide ranges of 24 h AUC/MIC (AUC24/MIC) including clinically achievable AUC24/MIC ratios. With each isolate, ABT492 at clinically achievable AUC/MICs produced greater anti-staphylococcal effects than levofloxacin. Areas between the control growth and the time--kill curves (ABBC in single dose simulations and the sum of ABBCs determined after the first, second and third dosing in multiple dose simulations--ABBC(1+2+3)) were higher with ABT492 than levofloxacin. Moreover, at comparable AUC/MICs and AUC24/MICs, the maximal reductions in the starting inoculum of ABT492-exposed S. aureus were more pronounced than with levofloxacin. Loss in susceptibility of S. aureus 201 exposed to ABT492 or levofloxacin depended on the simulated AUC24/MIC. Although the maximal increase in MIC (MICfinal) related to its initial value (MICinitial) was seen at a higher AUC24/MIC ratio of ABT492 (120 h) than levofloxacin (50 h), similar AUC24/MICs (240 and 200 h, respectively) were protective against the selection of resistant S. aureus. These threshold values are readily achievable with 400 mg ABT492 (AUC24/MIC 870 h) but not with 500 mg levofloxacin (AUC24/MIC 70 h). Overall, these findings predict greater efficacy of clinically achievable AUC/MIC (or AUC24/MIC) of ABT492 both in terms of the anti-staphylococcal effect and prevention of the selection of resistant mutants.

Relationship between day 1 and day 2 Vancomycin area under the curve values and emergence of heterogeneous Vancomycin-intermediate Staphylococcus aureus (hVISA) by Etest® macromethod among patients with MRSA bloodstream infections: a pilot study.

PubMed

Martirosov, Dmitriy M; Bidell, Monique R; Pai, Manjunath P; Scheetz, Marc H; Rosenkranz, Susan L; Faragon, Corey; Malik, M; Mendes, R E; Jones, R N; McNutt, Louise-Anne; Lodise, Thomas P

2017-08-02

In vitro data suggests that suboptimal initial vancomycin exposure may select for heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) infections. However, no clinical studies have evaluated the relationship between initial vancomycin exposure and emergence of hVISA. This pilot study seeks to assess the relationship between day 1 and day 2 vancomycin area under the curve (AUC) and emergence of hVISA bloodstream infections (BSIs) by Etest® macromethod among patients with a non-hVISA BSI at baseline. This was a retrospective cohort study of patients with methicillin-resistant Staphylococcus aureus (MRSA) BSIs at Albany Medical Center Hospital (AMCH) between January 2005 and June 2009. The vancomycin AUC exposure variables on day 1 (AUC 0-24h ) and day 2 (AUC 24-48h ) were estimated using the maximal a posteriori probability (MAP) procedure in ADAPT 5. There were 238 unique episodes of MRSA BSIs during the study period, 119 of which met inclusion criteria. Overall, hVISA emerged in 7/119 (5.9%) of patients. All 7 cases of hVISA involved patients who did not achieve area under the curve over broth microdilution minimum inhibitory concentration (AUC 0-24h /MIC BMD ) ratio of 521 or an AUC 24-48h /MIC BMD ratio of 650. No associations between other day 1 and day 2 AUC variables and emergence of hVISA were noted. Although more data are needed to draw definitive conclusions, these findings suggest that hVISA emergence among patients with non-hVISA MRSA BSIs at baseline may be partially explained by suboptimal exposure to vancomycin in the first 1 to 2 days of therapy. At a minimum, these findings support further study of the relationship between initial vancomycin exposure and hVISA emergence among patients with MRSA BSIs in a well-powered, multi-center, prospective trial.

Waist circumference and insulin resistance: a cross-sectional study of Japanese men

PubMed Central

Tabata, Shinji; Yoshimitsu, Shinichiro; Hamachi, Tadamichi; Abe, Hiroshi; Ohnaka, Keizo; Kono, Suminori

2009-01-01

Background Visceral obesity is positively related to insulin resistance. The nature of the relationship between waist circumference and insulin resistance has not been known in Japanese populations. This study examined the relationship between waist circumference and insulin resistance and evaluated the optimal cutoff point for waist circumference in relation to insulin resistance in middle-aged Japanese men. Methods Study subjects included 4800 Japanese men aged 39 to 60 years. Insulin resistance was evaluated by the homeostasis model assessment of insulin resistance (HOMA-IR). The relationship of waist circumference with HOMA-IR was assessed by use of adjusted means of HOMA-IR and odds ratios of elevated HOMA-IR defined as the highest quintile (≥2.00). Receiver operating characteristics (ROC) curve analysis using Youden index and the area under curve (AUC) was employed to determine optimal cutoffs of waist circumference in relation to HOMA-IR. Results Adjusted geometric means of HOMA-IR and prevalence odds of elevated HOMA-IR were progressively higher with increasing levels of waist circumference. In the ROC curve analysis, the highest value of Youden index was obtained for a cutoff point of 85 cm in waist circumference across different values of HOMA-IR. Multiple logistic regression analysis also indicated that the AUC was consistently the largest for a waist circumference of 85 cm. Conclusion Waist circumference is linearly related to insulin resistance, and 85 cm in waist circumference is an optimal cutoff in predicting insulin resistance in middle-aged Japanese men. PMID:19138424

A Novel Data-Driven Approach to Preoperative Mapping of Functional Cortex Using Resting-State Functional Magnetic Resonance Imaging

PubMed Central

Mitchell, Timothy J.; Hacker, Carl D.; Breshears, Jonathan D.; Szrama, Nick P.; Sharma, Mohit; Bundy, David T.; Pahwa, Mrinal; Corbetta, Maurizio; Snyder, Abraham Z.; Shimony, Joshua S.

2013-01-01

BACKGROUND: Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping. OBJECTIVE: To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks. METHODS: This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy. RESULTS: The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively. CONCLUSION: A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions. ABBREVIATIONS: AUC, area under the curve BA, Brodmann area BOLD, blood oxygen level dependent ECS, electrocortical stimulation fMRI, functional magnetic resonance imaging ICA, independent component analysis MLP, multilayer perceptron MP-RAGE, magnetization-prepared rapid gradient echo ROC, receiver-operating characteristic rs-fMRI, resting-state functional magnetic resonance imaging RSN, resting-state network PMID:24264234

The use of intraoperative triggered electromyography to detect misplaced pedicle screws: a systematic review and meta-analysis.

PubMed

Mikula, Anthony L; Williams, Seth K; Anderson, Paul A

2016-04-01

Insertion of instruments or implants into the spine carries a risk for injury to neural tissue. Triggered electromyography (tEMG) is an intraoperative neuromonitoring technique that involves electrical stimulation of a tool or screw and subsequent measurement of muscle action potentials from myotomes innervated by nerve roots near the stimulated instrument. The authors of this study sought to determine the ability of tEMG to detect misplaced pedicle screws (PSs). The authors searched the U.S. National Library of Medicine, the Web of Science Core Collection database, and the Cochrane Central Register of Controlled Trials for PS studies. A meta-analysis of these studies was performed on a per-screw basis to determine the ability of tEMG to detect misplaced PSs. Sensitivity, specificity, and receiver operating characteristic (ROC) area under the curve (AUC) were calculated overall and in subgroups. Twenty-six studies were included in the systematic review. The authors analyzed 18 studies in which tEMG was used during PS placement in the meta-analysis, representing data from 2932 patients and 15,065 screws. The overall sensitivity of tEMG for detecting misplaced PSs was 0.78, and the specificity was 0.94. The overall ROC AUC was 0.96. A tEMG current threshold of 10-12 mA (ROC AUC 0.99) and a pulse duration of 300 µsec (ROC AUC 0.97) provided the most accurate testing parameters for detecting misplaced screws. Screws most accurately conducted EMG signals (ROC AUC 0.98). Triggered electromyography has very high specificity but only fair sensitivity for detecting malpositioned PSs.

Evaluation of a minimally invasive system for measuring glucose area under the curve during oral glucose tolerance tests: usefulness of sweat monitoring for precise measurement.

PubMed

Sakaguchi, Kazuhiko; Hirota, Yushi; Hashimoto, Naoko; Ogawa, Wataru; Hamaguchi, Tomoya; Matsuo, Toshihiro; Miyagawa, Jun-ichiro; Namba, Mitsuyoshi; Sato, Toshiyuki; Okada, Seiki; Tomita, Koji; Matsuhisa, Munehide; Kaneto, Hideaki; Kosugi, Keisuke; Maegawa, Hiroshi; Nakajima, Hiromu; Kashiwagi, Atsunori

2013-05-01

We developed a system for measuring glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET). Sweat contamination during interstitial fluid glucose (IG) extraction affects the accuracy of glucose AUC measurement, because this technology uses extracted sodium ion levels as an internal standard. Therefore, we developed a sweat monitoring patch to reduce this effect and investigated its efficacy in volunteers undergoing oral glucose tolerance tests (OGTTs). Fifty diabetes mellitus inpatients and 10 healthy subjects undergoing the 75 g OGTT were included. Two sites on the forearm were pretreated with microneedle arrays, then hydrogels for interstitial fluid extraction were placed on the treated sites. Simultaneously, hydrogels for sweat monitoring were placed on untreated sites near the treated sites. Plasma glucose (PG) levels were measured every 30 min for 2 h to calculate reference AUC values. Using MIET, IG AUC was calculated from extracted glucose and sodium ion levels after attachment of the hydrogel for 2 h. Good correlation between IG AUC measurements using MIET and reference AUCs measured using PG levels was confirmed over a wide AUC range (202-610 mg/h/dl) after correction for the sweat-induced error detected by the hydrogel patches on the nonpretreated skin. Strong correlation between IG AUC and peak glucose levels indicates that glucose spikes can be easily detected by this system. We confirmed the effectiveness of a sweat monitoring patch for precise AUC measurement using MIET. This novel, easy-to-use system has potential for glucose excursion evaluation in daily clinical practice. © 2013 Diabetes Technology Society.

Association of hepatic insulin resistance indexes to nonalcoholic fatty liver disease and related biomarkers.

PubMed

Sesti, G; Fiorentino, T V; Hribal, M L; Sciacqua, A; Perticone, F

2013-12-01

Nonalcoholic fatty liver disease (NAFLD) is linked with insulin resistance, however, if it is differentially associated with surrogate hepatic insulin resistance indexes is still undefined. We examined the relationship between these indexes, NAFLD and its related biomarkers (alanine aminotransferase [ALT], aspartate aminotransferase [AST], gamma-glutamyltransferase [GGT], alkaline phosphatase [ALK], high-sensitive C reactive protein [hsCRP], insulin-like growth factor-1 [IGF-1]). 473 Caucasians subjects underwent liver ultrasonography and oral glucose tolerance tests; homeostasis model assessment (HOMA), glucose(0-30) (area under the curve [AUC]) × insulin(0-30) (AUC) and liver insulin resistance (liver IR) indexes were computed. Liver IR index correlated more strongly than HOMA with GGT, ALK, hsCRP, ALT and AST and more strongly than glucose(0-30) (AUC) × insulin(0-30) (AUC) index with ALT, AST, GGT, ALK, hsCRP, and IGF-1. The ability of these indexes to identify NAFLD was evaluated by the area under the ROC curve; the ROC AUC for liver IR index was higher (0.733) than the ones for HOMA (0.685) and glucose(0-30) (AUC) × insulin(0-30) (AUC) (0.663) indexes. In a logistic regression model subjects in the highest quartile of the three indexes had a higher risk of having NAFLD than those in the lowest quartile (9.85-, 5.12- or 3.99-fold higher for liver IR index, HOMA, glucose(0-30) (AUC) × insulin(0-30) (AUC) index respectively). we documented significant cross-sectional associations of NAFLD and liver biomarkers with three validated indexes of hepatic insulin resistance, with liver IR index showing the stronger correlation. © 2013 Elsevier B.V. All rights reserved.

Simple Decision-Analytic Functions of the AUC for Ruling Out a Risk Prediction Model and an Added Predictor.

PubMed

Baker, Stuart G

2018-02-01

When using risk prediction models, an important consideration is weighing performance against the cost (monetary and harms) of ascertaining predictors. The minimum test tradeoff (MTT) for ruling out a model is the minimum number of all-predictor ascertainments per correct prediction to yield a positive overall expected utility. The MTT for ruling out an added predictor is the minimum number of added-predictor ascertainments per correct prediction to yield a positive overall expected utility. An approximation to the MTT for ruling out a model is 1/[P (H(AUC model )], where H(AUC) = AUC - {½ (1-AUC)} ½ , AUC is the area under the receiver operating characteristic (ROC) curve, and P is the probability of the predicted event in the target population. An approximation to the MTT for ruling out an added predictor is 1 /[P {(H(AUC Model:2 ) - H(AUC Model:1 )], where Model 2 includes an added predictor relative to Model 1. The latter approximation requires the Tangent Condition that the true positive rate at the point on the ROC curve with a slope of 1 is larger for Model 2 than Model 1. These approximations are suitable for back-of-the-envelope calculations. For example, in a study predicting the risk of invasive breast cancer, Model 2 adds to the predictors in Model 1 a set of 7 single nucleotide polymorphisms (SNPs). Based on the AUCs and the Tangent Condition, an MTT of 7200 was computed, which indicates that 7200 sets of SNPs are needed for every correct prediction of breast cancer to yield a positive overall expected utility. If ascertaining the SNPs costs $500, this MTT suggests that SNP ascertainment is not likely worthwhile for this risk prediction.

Evaluation of a Minimally Invasive System for Measuring Glucose Area under the Curve during Oral Glucose Tolerance Tests: Usefulness of Sweat Monitoring for Precise Measurement

PubMed Central

Sakaguchi, Kazuhiko; Hirota, Yushi; Hashimoto, Naoko; Ogawa, Wataru; Hamaguchi, Tomoya; Toshihiro, Matsuo; Miyagawa, Jun-ichiro; Namba, Mitsuyoshi; Sato, Toshiyuki; Okada, Seiki; Tomita, Koji; Matsuhisa, Munehide; Kaneto, Hideaki; Kosugi, Keisuke; Maegawa, Hiroshi; Nakajima, Hiromu; Kashiwagi, Atsunori

2013-01-01

Aims: We developed a system for measuring glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET). Sweat contamination during interstitial fluid glucose (IG) extraction affects the accuracy of glucose AUC measurement, because this technology uses extracted sodium ion levels as an internal standard. Therefore, we developed a sweat monitoring patch to reduce this effect and investigated its efficacy in volunteers undergoing oral glucose tolerance tests (OGTTs). Materials and Methods: Fifty diabetes mellitus inpatients and 10 healthy subjects undergoing the 75 g OGTT were included. Two sites on the forearm were pretreated with microneedle arrays, then hydrogels for interstitial fluid extraction were placed on the treated sites. Simultaneously, hydrogels for sweat monitoring were placed on untreated sites near the treated sites. Plasma glucose (PG) levels were measured every 30 min for 2 h to calculate reference AUC values. Using MIET, IG AUC was calculated from extracted glucose and sodium ion levels after attachment of the hydrogel for 2 h. Results: Good correlation between IG AUC measurements using MIET and reference AUCs measured using PG levels was confirmed over a wide AUC range (202–610 mg/h/dl) after correction for the sweat-induced error detected by the hydrogel patches on the nonpretreated skin. Strong correlation between IG AUC and peak glucose levels indicates that glucose spikes can be easily detected by this system. Conclusion: We confirmed the effectiveness of a sweat monitoring patch for precise AUC measurement using MIET. This novel, easy-to-use system has potential for glucose excursion evaluation in daily clinical practice. PMID:23759401

A modified Wald interval for the area under the ROC curve (AUC) in diagnostic case-control studies

PubMed Central

2014-01-01

Background The area under the receiver operating characteristic (ROC) curve, referred to as the AUC, is an appropriate measure for describing the overall accuracy of a diagnostic test or a biomarker in early phase trials without having to choose a threshold. There are many approaches for estimating the confidence interval for the AUC. However, all are relatively complicated to implement. Furthermore, many approaches perform poorly for large AUC values or small sample sizes. Methods The AUC is actually a probability. So we propose a modified Wald interval for a single proportion, which can be calculated on a pocket calculator. We performed a simulation study to compare this modified Wald interval (without and with continuity correction) with other intervals regarding coverage probability and statistical power. Results The main result is that the proposed modified Wald intervals maintain and exploit the type I error much better than the intervals of Agresti-Coull, Wilson, and Clopper-Pearson. The interval suggested by Bamber, the Mann-Whitney interval without transformation and also the interval of the binormal AUC are very liberal. For small sample sizes the Wald interval with continuity has a comparable coverage probability as the LT interval and higher power. For large sample sizes the results of the LT interval and of the Wald interval without continuity correction are comparable. Conclusions If individual patient data is not available, but only the estimated AUC and the total sample size, the modified Wald intervals can be recommended as confidence intervals for the AUC. For small sample sizes the continuity correction should be used. PMID:24552686

A modified Wald interval for the area under the ROC curve (AUC) in diagnostic case-control studies.

PubMed

Kottas, Martina; Kuss, Oliver; Zapf, Antonia

2014-02-19

The area under the receiver operating characteristic (ROC) curve, referred to as the AUC, is an appropriate measure for describing the overall accuracy of a diagnostic test or a biomarker in early phase trials without having to choose a threshold. There are many approaches for estimating the confidence interval for the AUC. However, all are relatively complicated to implement. Furthermore, many approaches perform poorly for large AUC values or small sample sizes. The AUC is actually a probability. So we propose a modified Wald interval for a single proportion, which can be calculated on a pocket calculator. We performed a simulation study to compare this modified Wald interval (without and with continuity correction) with other intervals regarding coverage probability and statistical power. The main result is that the proposed modified Wald intervals maintain and exploit the type I error much better than the intervals of Agresti-Coull, Wilson, and Clopper-Pearson. The interval suggested by Bamber, the Mann-Whitney interval without transformation and also the interval of the binormal AUC are very liberal. For small sample sizes the Wald interval with continuity has a comparable coverage probability as the LT interval and higher power. For large sample sizes the results of the LT interval and of the Wald interval without continuity correction are comparable. If individual patient data is not available, but only the estimated AUC and the total sample size, the modified Wald intervals can be recommended as confidence intervals for the AUC. For small sample sizes the continuity correction should be used.

Mycophenolic acid AUC in Thai kidney transplant recipients receiving low dose mycophenolate and its association with UGT2B7 polymorphisms.

PubMed

Pithukpakorn, Manop; Tiwawanwong, Tiwat; Lalerd, Yupaporn; Assawamakin, Anunchai; Premasathian, Nalinee; Tasanarong, Adis; Thongnoppakhun, Wanna; Vongwiwatana, Attapong

2014-01-01

Despite use of a lower mycophenolate dose in Thai kidney transplant patients, acceptable graft and patient outcomes can be achieved. We therefore examined the pharmacokinetics of mycophenolic acid (MPA) by area under the curve (AUC) and investigated genetic contribution in mycophenolate metabolism in this population. Kidney transplant recipients with stable graft function who were receiving mycophenolate mofetil 1,000 mg/d in combination with either cyclosporine or tacrolimus, and prednisolone were studied. The MPA concentration was measured by fluorescence polarization immunoassay (FPIA), at predose and 1, 1.5, 2, 4, 6, 8, 10, and 12 hours after dosing. Genetic polymorphisms in UGT1A8, UGT1A9, and UGT2B7 were examined by denaturing high-performance liquid chromatography (DHPLC)-based single-base extension (SBE) analysis. A total 138 patients were included in study. The mean AUC was 39.49 mg-h/L (28.39-89.58 mg-h/L), which was in the therapeutic range. The correlation between the predose MPA concentration and AUC was poor. The mean AUC in the tacrolimus group was higher than that in the cyclosporine group. Polymorphisms in UGT2B7 showed significant association with AUC. Most of our patients with reduced mycophenolate dose had the AUC within the therapeutic range. Genetic polymorphisms in UGT2B7 may play a role in MPA metabolism in Thai kidney transplant patients.

A study on risk factors and diagnostic efficiency of posthepatectomy liver failure in the nonobstructive jaundice.

PubMed

Wang, He; Lu, Shi-Chun; He, Lei; Dong, Jia-Hong

2018-02-01

Liver failure remains as the most common complication and cause of death after hepatectomy, and continues to be a challenge for doctors.t test and χ test were used for single factor analysis of data-related variables, then results were introduced into the model to undergo the multiple factors logistic regression analysis. Pearson correlation analysis was performed for related postoperative indexes, and a diagnostic evaluation was performed using the receiver operating characteristic (ROC) of postoperative indexes.Differences in age, body mass index (BMI), portal vein hypertension, bile duct cancer, total bilirubin, alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), operation time, cumulative portal vein occlusion time, intraoperative blood volume, residual liver volume (RLV)/entire live rvolume, ascites volume at postoperative day (POD)3, supplemental albumin amount at POD3, hospitalization time after operation, and the prothrombin activity (PTA) were statistically significant. Furthermore, there were significant differences in total bilirubin and the supplemental albumin amount at POD3. ROC analysis of the average PTA, albumin amounts, ascites volume at POD3, and their combined diagnosis were performed, which had diagnostic value for postoperative liver failure (area under the curve (AUC): 0.895, AUC: 0.798, AUC: 0.775, and AUC: 0.903).Preoperative total bilirubin level and the supplemental albumin amount at POD3 were independent risk factors. PTA can be used as the index of postoperative liver failure, and the combined diagnosis of the indexes can improve the early prediction of postoperative liver failure.

A local equation for differential diagnosis of β-thalassemia trait and iron deficiency anemia by logistic regression analysis in Southeast Iran.

PubMed

Sargolzaie, Narjes; Miri-Moghaddam, Ebrahim

2014-01-01

The most common differential diagnosis of β-thalassemia (β-thal) trait is iron deficiency anemia. Several red blood cell equations were introduced during different studies for differential diagnosis between β-thal trait and iron deficiency anemia. Due to genetic variations in different regions, these equations cannot be useful in all population. The aim of this study was to determine a native equation with high accuracy for differential diagnosis of β-thal trait and iron deficiency anemia for the Sistan and Baluchestan population by logistic regression analysis. We selected 77 iron deficiency anemia and 100 β-thal trait cases. We used binary logistic regression analysis and determined best equations for probability prediction of β-thal trait against iron deficiency anemia in our population. We compared diagnostic values and receiver operative characteristic (ROC) curve related to this equation and another 10 published equations in discriminating β-thal trait and iron deficiency anemia. The binary logistic regression analysis determined the best equation for best probability prediction of β-thal trait against iron deficiency anemia with area under curve (AUC) 0.998. Based on ROC curves and AUC, Green & King, England & Frazer, and then Sirdah indices, respectively, had the most accuracy after our equation. We suggest that to get the best equation and cut-off in each region, one needs to evaluate specific information of each region, specifically in areas where populations are homogeneous, to provide a specific formula for differentiating between β-thal trait and iron deficiency anemia.

Dynamics of Nampt/visfatin and high molecular weight adiponectin in response to oral glucose load in obese and lean women.

PubMed

Unlütürk, Uğur; Harmanci, Ayla; Yildiz, Bülent Okan; Bayraktar, Miyase

2010-04-01

High molecular weight adiponectin (HMWA) is the active circulating form of adiponectin. Nampt/visfatin is the enzyme secreted from adipocytes in an active form and is one of the putative regulators of insulin secretion. To investigate the dynamics of total adiponectin (TA), HMWA and Nampt/visfatin in obese and lean women during oral glucose tolerance test (OGTT). We studied normal glucose-tolerant (NGT), age-matched, 30 obese and 30 lean women. All subjects underwent a standard 75 g, 2-h OGTT, and area under the curve (AUC) during OGTT for glucose, insulin, Nampt/visfatin, TA and HMWA was calculated. Body fat mass was assessed by bioimpedance analysis. Results Obese women had significantly higher basal and AUC values for insulin and Nampt/visfatin, whereas basal and AUC-HMWA were significantly lower in this group. Alternatively, obese and lean groups had similar basal and AUC values for glucose and TA. Basal insulin levels were negatively correlated with HMWA levels, but not with basal Nampt/visfatin. AUC-insulin was correlated positively with AUC-visfatin, and negatively with AUC-HMWA. Total and truncal body fat mass showed positive correlation with basal and AUC-visfatin, and negative correlation with basal and AUC-HMWA. In the NGT state, obese women have higher Nampt/visfatin and lower HMWA levels, both basally and in response to oral glucose challenge. The dynamics of Nampt/visfatin and HMWA during OGTT appear to be linked with insulin and adiposity. Counter-regulatory adaptations in HMWA and Nampt/visfatin might have an impact on suggested adipoinsular axis, contributing to maintenance of normal glucose tolerance.

Accuracy of Blood Pressure-to-Height Ratio to Define Elevated Blood Pressure in Children and Adolescents: The CASPIAN-IV Study.

PubMed

Kelishadi, Roya; Bahreynian, Maryam; Heshmat, Ramin; Motlagh, Mohammad Esmail; Djalalinia, Shirin; Naji, Fatemeh; Ardalan, Gelayol; Asayesh, Hamid; Qorbani, Mostafa

2016-02-01

The aim of this study was to propose a simple practical diagnostic criterion for pre-hypertension (pre-HTN) and hypertension (HTN) in the pediatric age group. This study was conducted on a nationally representative sample of 14,880 students, aged 6-18 years. HTN and pre-HTN were defined as systolic blood pressure (SBP) and/or diastolic blood pressure (DBP) ≥ 95 and 90-95th percentile for age, gender, and height, respectively. By using the area under the curve (AUC) of the receiver operator characteristic curves, we estimated the diagnostic accuracy of two indexes of SBP-to-height ratio (SBPHR) and DBP-to-height (DBPHR) to define pre-HTN and HTN. Overall, SBPHR performed relatively well in classifying subjects to HTN (AUC 0.80-0.85) and pre-HTN (AUC 0.84-0.90). Likewise, DBPHR performed relatively well in classifying subjects to HTN (AUC 0.90-0.97) and pre-HTN (AUC 0.70-0.83). Two indexes of SBPHR and DBPHR are considered as valid, simple, inexpensive, and accurate tools to diagnose pre-HTN and HTN in pediatric age group.

Is 'gut feeling' by medical staff better than validated scores in estimation of mortality in a medical intensive care unit? - The prospective FEELING-ON-ICU study.

PubMed

Radtke, Anne; Pfister, Roman; Kuhr, Kathrin; Kochanek, Matthias; Michels, Guido

2017-10-01

The aim of the FEELING-ON-ICU study was to compare mortality estimations of critically ill patients based on 'gut feeling' of medical staff and by Acute Physiology And Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II and Sequential Organ Failure Assessment (SOFA). Medical staff estimated patients' mortality risks via questionnaires. APACHE II, SAPS II and SOFA were calculated retrospectively from records. Estimations were compared with actual in-hospital mortality using receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC). 66 critically ill patients (60.6% male, mean age 63±15years (range 30-86)) were evaluated each by a nurse (n=66, male 32.4%) and a physician (n=66, male 67.6%). 15 (22.7%) patients died on the intensive care unit. AUC was largest for estimations by physicians (AUC 0.814 (95% CI 0.705-0.923)), followed by SOFA (AUC 0.749 (95% CI 0.629-0.868)), SAPS II (AUC 0.723 (95% CI 0.597-0.849)), APACHE II (AUC 0.721 (95% CI 0.595-0.847)) and nursing staff (AUC 0.669 (95% CI 0.529-0.810)) (p<0.05 for all results). The concept of physicians' 'gut feeling' was comparable to classical objective scores in mortality estimations of critically ill patients. Concerning practicability physicians' evaluations were advantageous to complex score calculation. Copyright © 2017 Elsevier Inc. All rights reserved.

Hounsfield unit of screw trajectory as a predictor of pedicle screw loosening after single level lumber interbody fusion.

PubMed

Sakai, Yusuke; Takenaka, Shota; Matsuo, Yohei; Fujiwara, Hiroyasu; Honda, Hirotsugu; Makino, Takahiro; Kaito, Takashi

2018-06-01

This study aims to clarify the clinical potential of Hounsfield unit (HU), measured on computed tomography (CT) images, as a predictor of pedicle screw (PS) loosening, compared to bone mineral density (BMD). A total of 206 screws in 52 patients (21 men and 31 women; mean age 68.2 years) were analyzed retrospectively. The screws were classified into two groups depending on their screw loosening status on 3-month follow-up CT (loosening screw group vs. non-loosening screw group). Preoperative HU of the trajectory was evaluated by superimposing preoperative and postoperative CT images using three-dimensional image analysis software. Age, sex, body mass index, screw size, BMD of lumbar, and HU of screw trajectory were analyzed in association with screw loosening. Multivariate logistic regression analysis was performed, and the thresholds for PS loosening risk factors were evaluated using a continuous numerical variable and receiver operating characteristic (ROC) curve analyses. The area under the curve (AUC) was used to determine the diagnostic performance, and values > 0.75 were considered to represent good performance. The loosening screw group contained 24 screws (12%). Multivariate analysis revealed that the significant independent risk factors were not BMD but male sex [P = 0.028; odds ratio (OR) 2.852, 95% confidence interval (CI) 1.120-7.258] and HU of screw trajectory (P = 0.006; OR 0.989, 95% CI 0.980-0.997). ROC curve analysis demonstrated that the AUC for HU of screw trajectory for women was 0.880 (95% CI 0.798-0.961). The cutoff value was 153.5. AUC for men was 0.635 (95% CI 0.449-0.821), which was not considered to be a good performance. Low HU of screw trajectories was identified as a risk factor of PS loosening for women. For female patients with low HU, additional augmentation is recommended to prevent PS loosening. Copyright © 2018 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Measurement properties of the Dizziness Handicap Inventory by cross-sectional and longitudinal designs

PubMed Central

2009-01-01

Background The impact of dizziness on quality of life is often assessed by the Dizziness Handicap Inventory (DHI), which is used as a discriminate and evaluative measure. The aim of the present study was to examine reliability and validity of a translated Norwegian version (DHI-N), also examining responsiveness to important change in the construct being measured. Methods Two samples (n = 92 and n = 27) included participants with dizziness of mainly vestibular origin. A cross-sectional design was used to examine the factor structure (exploratory factor analysis), internal consistency (Cronbach's α), concurrent validity (Pearson's product moment correlation r), and discriminate ability (ROC curve analysis). Longitudinal designs were used to examine test-retest reliability (intraclass correlation coefficient (ICC) statistics, smallest detectable difference (SDD)), and responsiveness (Pearson's product moment correlation, ROC curve analysis; area under the ROC curve (AUC), and minimally important change (MIC)). The DHI scores range from 0 to 100. Results Factor analysis revealed a different factor structure than the original DHI, resulting in dismissal of subscale scores in the DHI-N. Acceptable internal consistency was found for the total scale (α = 0.95). Concurrent correlations between the DHI-N and other related measures were moderate to high, highest with Vertigo Symptom Scale-short form-Norwegian version (r = 0.69), and lowest with preferred gait (r = - 0.36). The DHI-N demonstrated excellent ability to discriminate between participants with and without 'disability', AUC being 0.89 and best cut-off point = 29 points. Satisfactory test-retest reliability was demonstrated, and the change for an individual should be ≥ 20 DHI-N points to exceed measurement error (SDD). Correlations between change scores of DHI-N and other self-report measures of functional health and symptoms were high (r = 0.50 - 0.57). Responsiveness of the DHI-N was excellent, AUC = 0.83, discriminating between self-perceived 'improved' versus 'unchanged' participants. The MIC was identified as 11 DHI-N points. Conclusions The DHI-N total scale demonstrated satisfactory measurement properties. This is the first study that has addressed and demonstrated responsiveness to important change of the DHI, and provided values of SDD and MIC to help interpret change scores. PMID:20025754

Dissecting the relationship between obesity and hyperinsulinemia: Role of insulin secretion and insulin clearance.

PubMed

Kim, Mee Kyoung; Reaven, Gerald M; Kim, Sun H

2017-02-01

The aim of this study was to better delineate the complex interrelationship among insulin resistance (IR), secretion rate (ISR), and clearance rate (ICR) to increase plasma insulin concentrations in obesity. Healthy volunteers (92 nondiabetic individuals) had an insulin suppression test to measure IR and graded-glucose infusion test to measure ISR and ICR. Obesity was defined as a body mass index (BMI) ≥30 kg/m 2 , and IR was defined as steady-state plasma glucose (SSPG) ≥10 mmol/L during the insulin suppression test. Plasma glucose and insulin concentrations, ISR, and ICR were compared in three groups: insulin sensitive/overweight; insulin sensitive/obesity; and insulin resistant/obesity. Compared with the insulin-sensitive/overweight group, the insulin-sensitive/obesity had significantly higher insulin area under the curve (AUC) and ISR AUC during the graded-glucose infusion test (P < 0.001). Glucose AUC and ICR were similar. The insulin-resistant/obesity group had higher insulin AUC and ISR AUC compared with the insulin-sensitive/obesity but also had higher glucose AUC and decreased ICR (P < 0.01). In multivariate analysis, both BMI and SSPG were significantly associated with ISR. Plasma insulin concentration and ISR are increased in individuals with obesity, irrespective of degree of IR, but a decrease in ICR is confined to the subset of individuals with IR. © 2016 The Obesity Society.

Basic arterial blood gas biomarkers as a predictor of mortality in tetralogy of Fallot patients.

PubMed

Bhardwaj, Vandana; Kapoor, Poonam Malhotra; Irpachi, Kalpana; Ladha, Suruchi; Chowdhury, Ujjwal Kumar

2017-01-01

Serum lactate and base deficit have been shown to be a predictor of morbidity and mortality in critically ill patients. Poor preoperative oxygenation appears to be one of the significant factors that affects early mortality in tetralogy of Fallot (TOF). There is little published literature evaluating the utility of serum lactate, base excess (BE), and oxygen partial pressure (PO 2 ) as simple, widely available, prognostic markers in patients undergoing surgical repair of TOF. This prospective, observational study was conducted in 150 TOF patients, undergoing elective intracardiac repair. PO 2 , BE, and lactate levels at three different time intervals were recorded. Arterial blood samples were collected after induction (T1), after cardiopulmonary bypass (T2), and 48 h (T3) after surgery in the Intensive Care Unit (ICU). To observe the changes in PO 2 , BE, and lactate levels over a period of time, repeated measures analysis was performed with Bonferroni method. The receiver operating characteristics (ROC) analysis was used to find area under curve (AUC) and cutoff values of various biomarkers for predicting mortality in ICU. The patients who could not survive showed significant elevated lactate levels at baseline (T1) and postoperatively (T2) as compared to patients who survived after surgery (P < 0.001). However, in nonsurvivors, the BE value decreased significantly in the postoperative period in comparison to survivors (-2.8 ± 4.27 vs. 5.04 ± 2.06) (P < 0.001). In nonsurvivors, there was a significant fall of PO 2 to a mean value of 59.86 ± 15.09 in ICU (T3), whereas those who survived had a PO 2 of 125.86 ± 95.09 (P < 0.001). The ROC curve analysis showed that lactate levels (T3) have highest mortality predictive value (AUC: 96.9%) as compared to BE (AUC: 94.5%) and PO 2 (AUC: 81.1%). Serum lactate and BE may be used as prognostic markers to predict mortality in patients undergoing TOF repair. The routine analysis of these simple, fast, widely available, and cost-effective biomarkers should be encouraged to predict prognosis of TOF patients.

Comparative bioavailability of two oral formulations of ketorolac tromethamine: Dolac and Exodol.

PubMed

Flores-Murrieta, F J; Granados-Soto, V; Castañeda-Hernández, G; Herrera, J E; Hong, E

1994-03-01

The bioavailability of ketorolac after administration of two oral formulations containing 10 mg of ketorolac tromethamine, Exodol and Dolac, to 12 healthy Mexican volunteers was compared. Subjects received both formulations according to a randomized crossover design and blood samples were drawn at selected times during 24 h. Ketorolac plasma concentrations were determined by HPLC and individual plasma-concentration-against-time curves were constructed. Maximal plasma concentration and AUC0-24 values were compared by analysis of variance followed by Westlake's confidence interval test. 90% confidence limits ranged from 80 to 125% for Cmax and from 85 to 118% for AUC0-24. It is concluded that the two assayed formulations are bioequivalent.

Diagnostic value of quantitative contrast-enhanced ultrasound (CEUS) for early detection of renal hyperperfusion in diabetic kidney disease.

PubMed

Wang, Ling; Wu, Jian; Cheng, Jia-Fen; Liu, Xin-Ying; Ma, Fang; Guo, Le-Hang; Xu, Jun-Mei; Wu, Tianfu; Mohan, Chandra; Peng, Ai; Xu, Hui-Xiong; Song, Ya-Xiang

2015-12-01

To investigate the diagnostic value of quantitative contrast-enhanced ultrasound (CEUS) for early detection of renal hyperperfusion in diabetic kidney disease (DKD). 55 DKD patients with estimated glomerular filtration rate (eGFR) >30 ml/min/1.73 m(2) and 26 normal controls (NCs) were enrolled. Clinical data was well documented. Blood samples were drawn for evaluation of renal function including blood urea nitrogen (BUN), serum creatinine (SCr) and serum uric acid (SUA), and urine samples were assayed for total protein quantification, and various microprotein markers. According to eGFR level, DKD patients were divided into early-stage DKD (eGFR ≥90 ml/min/1.73 m(2), n = 18) and middle-stage DKD (eGFR 30-90 ml/min/1.73 m(2), n = 37). Based on urinary microalbumin/creatinine ratio (MALB/UCR), early-stage DKD patients were further classified into two groups: MALB/UCR <10 g/mol (n = 11) and MALB/UCR ≥10 g/mol (n = 7). Then, CEUS was performed to observe the real-time renal perfusion, and low acoustic power contrast-specific imaging was used for quantitative analysis. The renal perfusion images of CEUS were well developed successively. The corresponding perfusion curves based on echo-power signals in time series were constructed. Quantitative analysis showed that area under the descending curve (AUC2) was significantly increased in early-stage DKD compared to middle-stage DKD (p < 0.05), but AUC showed no significant difference. Further comparison between different MALB/UCR levels of early-stage DKD showed that patients with MALB/UCR ≥10 g/mol had significantly increased levels of AUC, AUC2 and proteinuria than patients with low MALB/UCR (p < 0.05). Also, high MALB/UCR DKD patients had increased proteinuria but similar eGFR compared to low MALB/UCR patients. Renal microvascular hyperperfusion may be responsible for overt proteinuria until decline of renal filtration in DKD. AUC2 could be an early and sensitive marker for early renal injury and renal microvascular hyperperfusion in DKD.

Diagnostic performance of semi-quantitative and quantitative stress CMR perfusion analysis: a meta-analysis.

PubMed

van Dijk, R; van Assen, M; Vliegenthart, R; de Bock, G H; van der Harst, P; Oudkerk, M

2017-11-27

Stress cardiovascular magnetic resonance (CMR) perfusion imaging is a promising modality for the evaluation of coronary artery disease (CAD) due to high spatial resolution and absence of radiation. Semi-quantitative and quantitative analysis of CMR perfusion are based on signal-intensity curves produced during the first-pass of gadolinium contrast. Multiple semi-quantitative and quantitative parameters have been introduced. Diagnostic performance of these parameters varies extensively among studies and standardized protocols are lacking. This study aims to determine the diagnostic accuracy of semi- quantitative and quantitative CMR perfusion parameters, compared to multiple reference standards. Pubmed, WebOfScience, and Embase were systematically searched using predefined criteria (3272 articles). A check for duplicates was performed (1967 articles). Eligibility and relevance of the articles was determined by two reviewers using pre-defined criteria. The primary data extraction was performed independently by two researchers with the use of a predefined template. Differences in extracted data were resolved by discussion between the two researchers. The quality of the included studies was assessed using the 'Quality Assessment of Diagnostic Accuracy Studies Tool' (QUADAS-2). True positives, false positives, true negatives, and false negatives were subtracted/calculated from the articles. The principal summary measures used to assess diagnostic accuracy were sensitivity, specificity, andarea under the receiver operating curve (AUC). Data was pooled according to analysis territory, reference standard and perfusion parameter. Twenty-two articles were eligible based on the predefined study eligibility criteria. The pooled diagnostic accuracy for segment-, territory- and patient-based analyses showed good diagnostic performance with sensitivity of 0.88, 0.82, and 0.83, specificity of 0.72, 0.83, and 0.76 and AUC of 0.90, 0.84, and 0.87, respectively. In per territory analysis our results show similar diagnostic accuracy comparing anatomical (AUC 0.86(0.83-0.89)) and functional reference standards (AUC 0.88(0.84-0.90)). Only the per territory analysis sensitivity did not show significant heterogeneity. None of the groups showed signs of publication bias. The clinical value of semi-quantitative and quantitative CMR perfusion analysis remains uncertain due to extensive inter-study heterogeneity and large differences in CMR perfusion acquisition protocols, reference standards, and methods of assessment of myocardial perfusion parameters. For wide spread implementation, standardization of CMR perfusion techniques is essential. CRD42016040176 .

Limited sampling strategies to predict the area under the concentration-time curve for rifampicin.

PubMed

Medellín-Garibay, Susanna E; Correa-López, Tania; Romero-Méndez, Carmen; Milán-Segovia, Rosa C; Romano-Moreno, Silvia

2014-12-01

Rifampicin (RMP) is the most effective first-line antituberculosis drug. One of the most critical aspects of using it in fixed-drug combination formulations is to ensure it reaches therapeutic levels in blood. The determination of the area under the concentration-time curve (AUC) and appropriate dose adjustment of this drug may contribute to optimization of therapy. Even when the maximal concentration (Cmax) of RMP also predicts its sterilizing effect, the time to reach it (Tmax) takes 40 minutes to 6 hours. The aim of this study was to develop a limited sampling strategy (LSS) for therapeutic drug monitoring assistance for RMP. Full concentration-time curves were obtained from 58 patients with tuberculosis (TB) after the oral administration of RMP in fixed-drug combination formulation. A validated high-performance liquid chromatographic method was used. Pharmacokinetic parameters were estimated with a noncompartmental model. Generalized linear models were obtained by forward steps, and bootstrapping was performed to develop LSS to predict AUC curve from time 0 to the last measured at 24 hours postdose (AUC0-24). The predictive performance of the proposed models was assessed using RMP profiles from 25 other TB patients by comparing predicted and observed AUC0-24. The mean AUC0-24 in the current study was 91.46 ± 36.7 mg·h·L, and the most convenient sampling time points to predict it were 2, 4 and 12 hours postdose (slope [m] = 0.955 ± 0.06; r = 0.92). The mean prediction error was -0.355%, and the root mean square error was 5.6% in the validation group. Alternate LSSs are proposed with 2 of these sampling time points, which also provide good predictions when the 3 most convenient are not feasible. The AUC0-24 for RMP in TB patients can be predicted with acceptable precision through a 2- or 3-point sampling strategy, despite wide interindividual variability. These LSSs could be applied in clinical practice to optimize anti-TB therapy based on therapeutic drug monitoring.

Alzheimer disease identification using amyloid imaging and reserve variables

PubMed Central

Roe, C.M.; Mintun, M.A.; Ghoshal, N.; Williams, M.M.; Grant, E.A.; Marcus, D.S.; Morris, J.C.

2010-01-01

Objective: Several factors may influence the relationship between Alzheimer disease (AD) lesions and the expression of dementia, including those related to brain and cognitive reserve. Other factors may confound the association between AD pathology and dementia. We tested whether factors thought to influence the association of AD pathology and dementia help to accurately identify dementia of the Alzheimer type (DAT) when considered together with amyloid imaging. Methods: Participants with normal cognition (n = 180) and with DAT (n = 25), aged 50 years or older, took part in clinical, neurologic, and psychometric assessments. PET with the Pittsburgh compound B (PiB) tracer was used to measure brain amyloid, yielding a mean cortical binding potential (MCBP) reflecting PiB uptake. Logistic regression was used to generate receiver operating characteristic curves, and the areas under those curves (AUC), to compare the predictive accuracy of using MCBP alone vs MCBP together with other variables selected using a stepwise selection procedure to identify participants with DAT vs normal cognition. Results: The AUC resulting from MCBP alone was 0.84 (95% confidence interval [CI] = 0.73–0.94; cross-validated AUC = 0.80, 95% CI = 0.68–0.92). The AUC for the predictive equation generated by a stepwise model including education, normalized whole brain volume, physical health rating, gender, and use of medications that may interfere with cognition was 0.94 (95% CI = 0.90–0.98; cross-validated AUC = 0.91, 95% CI = 0.85–0.96), an improvement (p = 0.025) over that yielded using MCBP alone. Conclusion: Results suggest that factors reported to influence associations between AD pathology and dementia can improve the predictive accuracy of amyloid imaging for the identification of symptomatic AD. GLOSSARY A β = amyloid-β; AD = Alzheimer disease; AUC = area under receiver operating characteristic curve; BP = binding potential; CDR = Clinical Dementia Rating; CI = confidence interval; DAT = dementia of the Alzheimer type; DV = distribution volume; MCBP = mean cortical binding potential; nWBV = normalized whole brain volume; OR = odds ratio; PiB = Pittsburgh compound B; ROC = receiver operating characteristic curve; ROI = region of interest. PMID:20603484

Quantitative Differentiation of LV Myocardium with and without Layer-Specific Fibrosis Using MRI in Hypertrophic Cardiomyopathy and Layer-Specific Strain TTE Analysis.

PubMed

Funabashi, Nobusada; Takaoka, Hiroyuki; Ozawa, Koya; Kamata, Tomoko; Uehara, Masae; Komuro, Issei; Kobayashi, Yoshio

2018-05-30

To achieve further risk stratification in hypertrophic cardiomyopathy (HCM) patients, we localized and quantified layer-specific LVM fibrosis on MRI in HCM patients using regional layer-specific peak longitudinal strain (PLS) and peak circumferential strain (PCS) in LV myocardium (LVM) on speckle tracking transthoracic echocardiography (TTE). A total of 18 HCM patients (14 males; 58 ± 17 years) underwent 1.5T-MRI and TTE. PLS and PCS in each layer of the LVM (endocardium, epicardium, and whole-layer myocardium) were calculated for 17 AHA-defined lesions. MRI assessment showed that fibrosis was classified as endocardial, epicardial, or whole-layer (= either or both of these). Regional PLS was smaller in fibrotic endocardial lesions than in non-fibrotic endocardial lesions (P = 0.004). To detect LV endocardial lesions with fibrosis, ROC curves of regional PLS revealed an area under the curve (AUC) of 0.609 and a best cut-off point of 13.5%, with sensitivity of 65.3% and specificity of 54.3%. Regional PLS was also smaller in fibrotic epicardial lesions than in non-fibrotic epicardial lesions (P < 0.001). To detect LV epicardial lesions with fibrosis, ROC curves of PLS revealed an AUC of 0.684 and a best cut-off point of 9.5%, with sensitivity of 73.5% and specificity of 55.5%. Using whole-layer myocardium analysis, PLS was smaller in fibrotic lesions than in non-fibrotic lesions (P < 0.001). To detect whole-layer LV lesions with fibrosis, ROC curves of regional PLS revealed an AUC of 0.674 and a best cut-off point of 12.5%, with sensitivity of 79.0% and specificity of 50.7%. There were no significant differences in PCS of LV myocardium (endocardium, epicardium, and whole-layer) between fibrotic and non-fibrotic lesions. Quantitative regional PLS but not PCS in LV endocardium, epicardium, and whole-layer myocardium provides useful non-invasive information for layer-specific localization of fibrosis in HCM patients.

Evaluating risk assessments using receiver operating characteristic analysis: rationale, advantages, insights, and limitations.

PubMed

Mossman, Douglas

2013-01-01

The last two decades have witnessed major changes in the way that mental health professionals assess, describe, and think about persons' risk for future violence. Psychiatrists and psychologists have gone from believing that they could not predict violence to feeling certain they can assess violence risk with well-above-chance accuracy. Receiver operating characteristic (ROC) analysis has played a central role in changing this view. This article reviews the key concepts underlying ROC methods, the meaning of the area under the ROC curve (AUC), the relationship between AUC and effect size d, and what these two indices tell us about evaluations of violence risk. The area under the ROC curve and d provide succinct but incomplete descriptions of discrimination capacity. These indices do not provide details about sensitivity-specificity trade-offs; they do not tell us how to balance false-positive and false-negative errors; and they do not determine whether a diagnostic system is accurate enough to make practically useful distinctions between violent and non-violent subject groups. Justifying choices or clinical practices requires a contextual investigation of outcomes, a process that takes us beyond simply knowing global indices of accuracy. Copyright © 2013 John Wiley & Sons, Ltd.

Doppler Audio Signal Analysis as an Additional Tool in Evaluation of Umbilical Artery Circulation.

PubMed

Thuring, Ann; Källén, Karin; Brännström, K Jonas; Jansson, Tomas; Maršál, Karel

2017-10-01

Purpose  To investigate the predictive capacity of a new method for sound spectrum analysis of Doppler signals recorded from the umbilical artery in high-risk pregnancies. Material and Methods  The retrospective study comprised 127 pregnant women with various pregnancy complications between 23 and 39 gestational weeks. Umbilical artery blood flow velocity waveforms were recorded with Doppler ultrasound and characterized by pulsatility index (PI) and blood flow class (BFC). Doppler audio signals were stored on a digital video recorder and the sound frequency at the energy level 15 dB below its peak (MAX peak-15 dB ) was estimated off-line. The prediction of probability for composite adverse pregnancy outcome (operative delivery for fetal distress, admission to neonatal intensive care unit, perinatal death) was evaluated using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve. Results  With increasing umbilical artery BFC, the MAX peak-15 dB frequencies decreased (p < 0.0001) and the PI increased (p < 0.0001). The ROC AUCs for adverse outcome for MAX peak-15 dB and for PI were 0.842 and 0.836 (p = 0.88), respectively. For the combination of MAX peak-15 dB and PI, the corresponding AUC was 0.894, significantly higher than that of PI (p < 0.03) and of MAX peak-15 dB (p < 0.05). Conclusion  Umbilical artery Doppler sound spectrum analysis might be a useful supplement to PI in the clinical evaluation of fetoplacental circulation. © Georg Thieme Verlag KG Stuttgart · New York.

Digital obstructive arterial disease can be detected by laser Doppler measurements with high sensitivity and specificity.

PubMed

Mahe, Guillaume; Liedl, David A; McCarter, Charlene; Shepherd, Roger; Gloviczki, Peter; McPhail, Ian R; Rooke, Thom W; Wennberg, Paul W

2014-04-01

This study was conducted to determine the sensitivity and specificity of laser Doppler flowmetry (LDF) measurements for digital obstructive arterial disease (DOAD) using angiography as the reference standard and to compare the accuracy of different classical tests used to assess DOAD. Diagnosis of vascular abnormalities at the digital level is challenging. Angiography is the gold standard for assessment of DOAD but is invasive and expensive to perform. We performed a retrospective analysis of consecutive patients referred at Mayo Clinic (Rochester, Minn) for upper extremity arterial assessment during a 27-month period. Finger-brachial index, skin blood flow (in arbitrary units [a.u.]), and skin temperature (in degrees Celsius) were recorded in each digit on the pulp at baseline and after a thermal challenge test (hand placed in a thermal box at 47.0°C for 15 minutes). Angiogram analysis was blinded and performed by a radiologist using a vascularization scale ranging from 0 (no vessel) to 4 (normal). The receiver operating characteristic curve was used to define a specific cutoff point to detect DOAD. Twenty-two patients had LDF measurements and complete angiograms. A total of 185 digits were analyzed because some patients had only analysis of one hand. The best area under the curve (AUC) was 0.98 (range, 0.94-0.99) for postwarming skin blood flow, with a cutoff point of ≤206 a.u. This AUC was statistically different from AUCs of all the other tests (P < .01). Sensitivity and specificity were 93% (95% confidence interval, 85%-97%) and 96% (95% confidence interval, 90%-99%), respectively. LDF combined with a thermal challenge is highly accurate, safe, and noninvasive means to detect DOAD. Copyright © 2014 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

Quantitative evaluation of diffusion-kurtosis imaging for grading endometrial carcinoma: a comparative study with diffusion-weighted imaging.

PubMed

Chen, T; Li, Y; Lu, S-S; Zhang, Y-D; Wang, X-N; Luo, C-Y; Shi, H-B

2017-11-01

To evaluate the diagnostic performance of histogram analysis of diffusion kurtosis magnetic resonance imaging (DKI) and standard diffusion-weighted imaging (DWI) in discriminating tumour grades of endometrial carcinoma (EC). Seventy-three patients with EC were included in this study. The apparent diffusion coefficient (ADC) value from standard DWI, apparent diffusion for Gaussian distribution (D app ), and apparent kurtosis coefficient (K app ) from DKI were acquired using a 3 T magnetic resonance imaging (MRI) system. The measurement was based on an entire-tumour analysis. Histogram parameters (D app , K app , and ADC) were compared between high-grade (grade 3) and low-grade (grade 1 and 2) tumours. The diagnostic performance of imaging parameters for discriminating high- from low-grade tumours was analysed using a receiver operating characteristic curve (ROC). The area under the ROC curve (AUC) of the 10th percentile of D app , 90th percentile of K app and 10th percentile of ADC were higher than other parameters in distinguishing high-grade tumours from low-grade tumours (AUC=0.821, 0.891 and 0.801, respectively). The combination of 10th percentile of D app and 90th percentile of K app improved the AUC to 0.901, which was significantly higher than that of the 10th percentile of ADC (0.810, p=0.0314) in differentiating high- from low-grade EC. Entire-tumour volume histogram analysis of DKI and standard DWI were feasible for discriminating histological tumour grades of EC. DKI was relatively better than DWI in distinguishing high-grade from low-grade tumour in EC. Copyright © 2017. Published by Elsevier Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, J; Gong, G; Cui, Y

Purpose: To predict early pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multi-region analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). Methods: In this institution review board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with a high-temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitativemore » Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Results: Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast wash-out were statistically significant (p< 0.05) after correcting for multiple testing, with area under the ROC curve or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (p = 0.002) in leave-one-out cross validation. This improved upon conventional imaging predictors such as tumor volume (AUC=0.53) and texture features based on whole-tumor analysis (AUC=0.65). Conclusion: The heterogeneity of the tumor subregion associated with fast wash-out on DCE-MRI predicted early pathological response to neoadjuvant chemotherapy in breast cancer.« less

Radiological indeterminate vestibular schwannoma and meningioma in cerebellopontine angle area: differentiating using whole-tumor histogram analysis of apparent diffusion coefficient.

PubMed

Xu, Xiao-Quan; Li, Yan; Hong, Xun-Ning; Wu, Fei-Yun; Shi, Hai-Bin

2017-02-01

To assess the role of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating radiological indeterminate vestibular schwannoma (VS) from meningioma in cerebellopontine angle (CPA). Diffusion-weighted (DW) images (b = 0 and 1000 s/mm 2 ) of pathologically confirmed and radiological indeterminate CPA meningioma (CPAM) (n = 27) and VS (n = 12) were retrospectively collected and processed with mono-exponential model. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including the mean ADC (ADC mean ), median ADC (ADC median ), 10th/25th/75th/90th percentile ADC (ADC 10 , ADC 25 , ADC 75 and ADC 90 ), skewness and kurtosis. The differences of ADC histogram parameters between CPAM and VS were compared using unpaired t-test. Multiple receiver operating characteristic (ROC) curves analysis was used to determine and compare the diagnostic value of each significant parameter. Significant differences were found on the ADC mean , ADC median , ADC 10 , ADC 25 , ADC 75 and ADC 90 between CPAM and VS (all p values < 0.001), while no significant difference was found on kurtosis (p = 0.562) and skewness (p = 0.047). ROC curves analysis revealed, a cut-off value of 1.126 × 10 -3 mm 2 /s for the ADC 90 value generated highest area under curves (AUC) for differentiating CPAM from VS (AUC, 0.975; sensitivity, 100%; specificity, 88.9%). Histogram analysis of ADC maps based on whole tumor can be a useful tool for differentiating radiological indeterminate CPAM from VS. The ADC 90 value was the most promising parameter for differentiating these two entities.

Automated segmentation of retinal blood vessels and identification of proliferative diabetic retinopathy

NASA Astrophysics Data System (ADS)

Jelinek, Herbert F.; Cree, Michael J.; Leandro, Jorge J. G.; Soares, João V. B.; Cesar, Roberto M.; Luckie, A.

2007-05-01

Proliferative diabetic retinopathy can lead to blindness. However, early recognition allows appropriate, timely intervention. Fluorescein-labeled retinal blood vessels of 27 digital images were automatically segmented using the Gabor wavelet transform and classified using traditional features such as area, perimeter, and an additional five morphological features based on the derivatives-of-Gaussian wavelet-derived data. Discriminant analysis indicated that traditional features do not detect early proliferative retinopathy. The best single feature for discrimination was the wavelet curvature with an area under the curve (AUC) of 0.76. Linear discriminant analysis with a selection of six features achieved an AUC of 0.90 (0.73-0.97, 95% confidence interval). The wavelet method was able to segment retinal blood vessels and classify the images according to the presence or absence of proliferative retinopathy.

Modelling the habitat suitability of cetaceans: Example of the sperm whale in the northwestern Mediterranean Sea

NASA Astrophysics Data System (ADS)

Praca, Emilie; Gannier, Alexandre; Das, Krishna; Laran, Sophie

2009-04-01

Cetaceans are mobile and spend long periods underwater. Because of this, modelling their habitat could be subject to a serious problem of false absence. Furthermore, extensive surveys at sea are time and money consuming, and presence-absence data are difficult to apply. This study compares the ability of two presence-absence and two presence-only habitat modelling methods and uses the example of the sperm whale ( Physeter macrocephalus) in the northwestern Mediterranean Sea. The data consist of summer visual and acoustical detections of sperm whales, compiled between 1998 and 2005. Habitat maps were computed using topographical and hydrological eco-geographical variables. Four methods were compared: principal component analysis (PCA), ecological niche factor analysis (ENFA), generalized linear model (GLM) and multivariate adaptive regression splines (MARS). The evaluation of the models was achieved by calculating the receiver operating characteristic (ROC) of the models and their respective area under the curve (AUC). Presence-absence methods (GLM, AUC=0.70, and MARS, AUC=0.79) presented better AUC than presence-only methods (PCA, AUC=0.58, and ENFA, AUC=0.66), but this difference was not statistically significant, except between the MARS and the PCA models. The four models showed an influence of both topographical and hydrological factors, but the resulting habitat suitability maps differed. The core habitat on the continental slope was well highlighted by the four models, while GLM and MARS maps also showed a suitable habitat in the offshore waters. Presence-absence methods are therefore recommended for modelling the habitat suitability of cetaceans, as they seem more accurate to highlight complex habitat. However, the use of presence-only techniques, in particular ENFA, could be very useful for a first model of the habitat range or when important surveys at sea are not possible.

Relationship between the cortisol awakening response and other features of the diurnal cortisol rhythm: the Multi-Ethnic Study of Atherosclerosis.

PubMed

Golden, Sherita Hill; Sánchez, Brisa N; Wu, Meihua; Champaneri, Shivam; Diez Roux, Ana V; Seeman, Teresa; Wand, Gary S

2013-11-01

Cumulative cortisol burden is known to influence neuropsychiatric and metabolic disorders. To better understand the relationship between daily cortisol exposure and measures of the diurnal circadian cortisol rhythm, we examined the cross-sectional association of the cortisol awakening response (CAR) with wake-up cortisol, bedtime cortisol, diurnal slope, and total cortisol area under the curve (AUC). Up to 18 salivary cortisol samples were collected over 3 days from 935 White, Hispanic, and Black individuals (mean age 65 ± 9.8 years) in the Multi-Ethnic Study of Atherosclerosis. Outcome measures included awakening cortisol, CAR (awakening to 30 min post-awakening), early decline (30 min to 2h post-awakening), late decline (2h post-awakening to bedtime), and the corresponding AUCs. Total cortisol AUC was a summary measure of cumulative cortisol exposure. Higher CAR was associated with significantly lower wake-up cortisol (β=-0.56; 95% CI: -0.59 to -0.53) and a higher early decline AUC (β=0.38; 95% CI: 0.34-0.42) but was not associated with total cortisol AUC (β=0.04; 95% CI: -0.01 to 0.09), or other diurnal cortisol curve components following multivariable adjustment. Total cortisol AUC was significantly and positively associated with wake-up cortisol (β=0.36; 95% CI: 0.32-0.40), bedtime cortisol (β=0.61; 95% CI: 0.58-0.64), and other AUC measures, following multivariable adjustment. Associations were similar by sex, race/ethnicity, and age categories. We conclude that bedtime cortisol showed the strongest correlation with total cortisol AUC, suggesting it may be a marker of daily cortisol exposure. Copyright © 2013 Elsevier Ltd. All rights reserved.

Fully automated structural MRI of the brain in clinical dementia workup.

PubMed

Persson, Karin; Selbæk, Geir; Brækhus, Anne; Beyer, Mona; Barca, Maria; Engedal, Knut

2017-06-01

Background The dementia syndrome has been regarded a clinical diagnosis but the focus on supplemental biomarkers is increasing. An automatic magnetic resonance imaging (MRI) volumetry method, NeuroQuant® (NQ), has been developed for use in clinical settings. Purpose To evaluate the clinical usefulness of NQ in distinguishing Alzheimer's disease dementia (AD) from non-dementia and non-AD dementia. Material and Methods NQ was performed in 275 patients diagnosed according to the criteria of ICD-10 for AD, vascular dementia and Parkinson's disease dementia (PDD); the Winblad criteria for mild cognitive impairment; the Lund-Manchester criteria for frontotemporal dementia; and the revised consensus criteria for Lewy body dementia (LBD). Receiver operating curve (ROC) analyses with calculation of area under the curve (AUC) and regression analyses were carried out. Results Forebrain parenchyma (AUC 0.82), hippocampus (AUC 0.80), and inferior lateral ventricles (AUC 0.78) yielded the highest AUCs for AD/non-dementia discrimination. Only hippocampus (AUC 0.62) and cerebellum (AUC 0.67) separated AD from non-AD dementia. Cerebellum separated AD from PDD-LBD (AUC 0.83). Separate multiple regression analyses adjusted for age and gender, showed that memory (CERAD 10-word delayed recall) (beta 0.502, P < 0.001) was more strongly associated to the hippocampus volume than the diagnostic distinction of AD versus non-dementia (beta -0.392, P < 0.001). Conclusion NQ measures could separate AD from non-dementia fairly well but generally poorer from non-AD dementia. Degree of memory impairment, age, and gender, but not diagnostic distinction, were associated to the hippocampus volume in adjusted analyses. Surprisingly, cerebellum was found relevant in separating AD from PDD-LBD.

Knowledge of Fecal Calprotectin and Infliximab Trough Levels Alters Clinical Decision-making for IBD Outpatients on Maintenance Infliximab Therapy.

PubMed

Huang, Vivian W; Prosser, Connie; Kroeker, Karen I; Wang, Haili; Shalapay, Carol; Dhami, Neil; Fedorak, Darryl K; Halloran, Brendan; Dieleman, Levinus A; Goodman, Karen J; Fedorak, Richard N

2015-06-01

Infliximab is an effective therapy for inflammatory bowel disease (IBD). However, more than 50% of patients lose response. Empiric dose intensification is not effective for all patients because not all patients have objective disease activity or subtherapeutic drug level. The aim was to determine how an objective marker of disease activity or therapeutic drug monitoring affects clinical decisions regarding maintenance infliximab therapy in outpatients with IBD. Consecutive patients with IBD on maintenance infliximab therapy were invited to participate by providing preinfusion stool and blood samples. Fecal calprotectin (FCP) and infliximab trough levels (ITLs) were measured by enzyme linked immunosorbent assay. Three decisions were compared: (1) actual clinical decision, (2) algorithmic FCP or ITL decisions, and (3) expert panel decision based on (a) clinical data, (b) clinical data plus FCP, and (c) clinical data plus FCP plus ITL. In secondary analysis, Receiver-operating curves were used to assess the ability of FCP and ITL in predicting clinical disease activity or remission. A total of 36 sets of blood and stool were available for analysis; median FCP 191.5 μg/g, median ITLs 7.3 μg/mL. The actual clinical decision differed from the hypothetical decision in 47.2% (FCP algorithm); 69.4% (ITL algorithm); 25.0% (expert panel clinical decision); 44.4% (expert panel clinical plus FCP); 58.3% (expert panel clinical plus FCP plus ITL) cases. FCP predicted clinical relapse (area under the curve [AUC] = 0.417; 95% confidence interval [CI], 0.197-0.641) and subtherapeutic ITL (AUC = 0.774; 95% CI, 0.536-1.000). ITL predicted clinical remission (AUC = 0.498; 95% CI, 0.254-0.742) and objective remission (AUC = 0.773; 95% CI, 0.622-0.924). Using FCP and ITLs in addition to clinical data results in an increased number of decisions to optimize management in outpatients with IBD on stable maintenance infliximab therapy.

Role of FDG-PET/MRI, FDG-PET/CT, and Dynamic Susceptibility Contrast Perfusion MRI in Differentiating Radiation Necrosis from Tumor Recurrence in Glioblastomas.

PubMed

Hojjati, Mojgan; Badve, Chaitra; Garg, Vasant; Tatsuoka, Curtis; Rogers, Lisa; Sloan, Andrew; Faulhaber, Peter; Ros, Pablo R; Wolansky, Leo J

2018-01-01

To compare the utility of quantitative PET/MRI, dynamic susceptibility contrast (DSC) perfusion MRI (pMRI), and PET/CT in differentiating radiation necrosis (RN) from tumor recurrence (TR) in patients with treated glioblastoma multiforme (GBM). The study included 24 patients with GBM treated with surgery, radiotherapy, and temozolomide who presented with progression on imaging follow-up. All patients underwent PET/MRI and pMRI during a single examination. Additionally, 19 of 24 patients underwent PET/CT on the same day. Diagnosis was established by pathology in 17 of 24 and by clinical/radiologic consensus in 7 of 24. For the quantitative PET/MRI and PET/CT analysis, a region of interest (ROI) was drawn around each lesion and within the contralateral white matter. Lesion to contralateral white matter ratios for relative maximum, mean, and median were calculated. For pMRI, lesion ROI was drawn on the cerebral blood volume (CBV) maps and histogram metrics were calculated. Diagnostic performance for each metric was assessed using receiver operating characteristic curve analysis and area under curve (AUC) was calculated. In 24 patients, 28 lesions were identified. For PET/MRI, relative mean ≥ 1.31 resulted in AUC of .94 with both sensitivity and negative predictive values (NPVs) of 100%. For pMRI, CBV max ≥3.32 yielded an AUC of .94 with both sensitivity and NPV measuring 100%. The joint model utilizing r-mean (PET/MRI) and CBV mode (pMRI) resulted in AUC of 1.0. Our study demonstrates that quantitative PET/MRI parameters in combination with DSC pMRI provide the best diagnostic utility in distinguishing RN from TR in treated GBMs. © 2017 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.

Clinical-genetic model predicts incident impulse control disorders in Parkinson's disease.

PubMed

Kraemmer, Julia; Smith, Kara; Weintraub, Daniel; Guillemot, Vincent; Nalls, Mike A; Cormier-Dequaire, Florence; Moszer, Ivan; Brice, Alexis; Singleton, Andrew B; Corvol, Jean-Christophe

2016-10-01

Impulse control disorders (ICD) are commonly associated with dopamine replacement therapy (DRT) in patients with Parkinson's disease (PD). Our aims were to estimate ICD heritability and to predict ICD by a candidate genetic multivariable panel in patients with PD. Data from de novo patients with PD, drug-naïve and free of ICD behaviour at baseline, were obtained from the Parkinson's Progression Markers Initiative cohort. Incident ICD behaviour was defined as positive score on the Questionnaire for Impulsive-Compulsive Disorders in PD. ICD heritability was estimated by restricted maximum likelihood analysis on whole exome sequencing data. 13 candidate variants were selected from the DRD2, DRD3, DAT1, COMT, DDC, GRIN2B, ADRA2C, SERT, TPH2, HTR2A, OPRK1 and OPRM1 genes. ICD prediction was evaluated by the area under the curve (AUC) of receiver operating characteristic (ROC) curves. Among 276 patients with PD included in the analysis, 86% started DRT, 40% were on dopamine agonists (DA), 19% reported incident ICD behaviour during follow-up. We found heritability of this symptom to be 57%. Adding genotypes from the 13 candidate variants significantly increased ICD predictability (AUC=76%, 95% CI (70% to 83%)) compared to prediction based on clinical variables only (AUC=65%, 95% CI (58% to 73%), p=0.002). The clinical-genetic prediction model reached highest accuracy in patients initiating DA therapy (AUC=87%, 95% CI (80% to 93%)). OPRK1, HTR2A and DDC genotypes were the strongest genetic predictive factors. Our results show that adding a candidate genetic panel increases ICD predictability, suggesting potential for developing clinical-genetic models to identify patients with PD at increased risk of ICD development and guide DRT management. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Correcting AUC for Measurement Error.

PubMed

Rosner, Bernard; Tworoger, Shelley; Qiu, Weiliang

2015-12-01

Diagnostic biomarkers are used frequently in epidemiologic and clinical work. The ability of a diagnostic biomarker to discriminate between subjects who develop disease (cases) and subjects who do not (controls) is often measured by the area under the receiver operating characteristic curve (AUC). The diagnostic biomarkers are usually measured with error. Ignoring measurement error can cause biased estimation of AUC, which results in misleading interpretation of the efficacy of a diagnostic biomarker. Several methods have been proposed to correct AUC for measurement error, most of which required the normality assumption for the distributions of diagnostic biomarkers. In this article, we propose a new method to correct AUC for measurement error and derive approximate confidence limits for the corrected AUC. The proposed method does not require the normality assumption. Both real data analyses and simulation studies show good performance of the proposed measurement error correction method.

The cut-off values of anthropometric variables for predicting mild cognitive impairment in Malaysian older adults: a large population based cross-sectional study

PubMed Central

Won, Huiloo; Abdul, Manaf Zahara; Mat Ludin, Arimi Fitri; Omar, Mohd Azahadi; Razali, Rosdinom; Shahar, Suzana

2017-01-01

Purpose Older adults are at risk of mild cognitive impairment (MCI), and simple anthropometric measurements can be used to screen for this condition. Thus, the aim of this study was to explore the cut-off values of body mass index (BMI) and waist circumference (WC) for predicting the risk of MCI in older Malaysian adults. Methods A total of 2,240 Malaysian older adults aged ≥60 years were recruited using multistage random sampling in a population based cross-sectional study. Receiver operating characteristic (ROC) curve was used to determine the cut-off values of BMI and WC with optimum sensitivity and specificity for the detection of MCI. Age, gender, years of education, smoking habit, alcohol consumption, depression, and medical conditions were used as confounding factors in this analysis. Results A BMI cut-off value of 26 kg/m2 (area under the receiver operating characteristic curve [AUC] 0.725; sensitivity 90.5%; specificity 38.8%) was appropriate in identifying the risk of getting MCI in both men and women. The optimum WC cut-offs for likelihood of MCI were 90 cm (AUC 0.745; sensitivity 78.0%; specificity 59.8%) for men and 82 cm (AUC 0.714; sensitivity 84.3%; specificity 49.7%) for women. The optimum calf circumference (CC) cut-off values for identifying MCI were 29 cm (AUC 0.731; sensitivity 72.6%; specificity 61.1%) for men and 26 cm (AUC 0.598; sensitivity 79.1%; specificity 45.3%) for women. Conclusion The cut-off values could be advocated and used as part of the screening of MCI among older Malaysian adults. There is a need to further determine the predictive values of these cut-off points on outcomes through longitudinal study design. PMID:28223785

Slow recovery of blood glucose in the insulin tolerance test during the prepartum transition period negatively impacts the nutritional status and reproductive performance postpartum of dairy cows.

PubMed

Lee, Hsu-Hsun; Kida, Katsuya; Miura, Ryotaro; Inokuma, Hisashi; Miyamoto, Akio; Kawashima, Chiho; Haneda, Shingo; Miyake, Yoh-Ichi; Matsui, Motozumi

2012-04-01

In peripartum dairy cows, insulin resistance (IR) increases to adjust the direction of energy to lactation after calving. To investigate the effect of prepartum IR on postpartum reproductive performance, the insulin tolerance test (ITT) was applied to 15 cows at 3 weeks (Pre21) and 10 days (Pre10) before the predicted calving date. Blood glucose area under the curve (AUC(glu)) within 120 min after administration of 0.05 IU/kg-BW insulin was calculated. The occurrence of first ovulation, days to first artificial insemination (AI) and first AI conception rate were recorded. Nutritional status postpartum was evaluated by blood chemical analysis. Based on AUC(glu) changes from Pre21 to Pre10, cows were classified into either the AUC-up group (AUC(glu) increase, n=5) or the AUC-down group (AUC(glu) decrease, n=10). There was no difference in the decrease in blood glucose at 30 min after insulin injection between groups, although glucose recovery from 30 to 60 min during the ITT was slow at Pre10 in the AUC-up group. The AUC-up group had a higher number of days to first AI and high glucose, total protein, globulin, γ-glutamyltransferase, triacylglycerol levels and a low albumin-globulin ratio at the 14th day postpartum. The present study infers that prepartum slow glucose recovery rather than insulin sensitivity might increase the potential for subclinical health problems postpartum and thus suppress reproductive performance. During the prepartum transition period, glucose dynamics in the ITT can be considered as a new indicator for the postpartum metabolic status and reproductive performance of dairy cows.

Urinary microRNA-192 and microRNA-21 as potential indicators for liver fluke-associated cholangiocarcinoma risk group.

PubMed

Silakit, Runglawan; Loilome, Watcharin; Yongvanit, Puangrat; Thongchot, Suyanee; Sithithaworn, Paiboon; Boonmars, Thidarut; Koonmee, Supinda; Titapun, Attapol; Khuntikeo, Narong; Chamadol, Nittaya; Techasen, Anchalee; Namwat, Nisana

2017-08-01

Opisthorchis viverrini infection induces chronic inflammation in the bile ducts, leading to periductal fibrosis (PDF), which possibly associates to cholangiocarcinoma (CCA). Patients with CCA have a poor prognosis, which is linked to asymptomatic disease and late diagnosis. Hence, detecting early stage CCA is essential. Secretory miRNAs have been promoted as biomarkers for pathological changes associated with parasitic infections, fibrosis and/or cancer. We aimed to determine levels of miR-192 and miR-21 in the urine of O. viverrini infected, periductal fibrosis (PDF) and CCA groups using qRT-PCR. We found that miR-192 was significantly higher in O. viverrini infected, PDF and also CCA groups (p<0.05) than in healthy controls. By utilizing the Receiver Operation Characteristics (ROC) analysis, miR-192 differentiated patients with opisthorchiasis (the area under the curve; AUC=0.766), PDF subjects (AUC=0.781) and CCA patients (AUC=0.682) from healthy controls. MiR-21 was significantly higher in PDF and CCA groups (p<0.05) than in healthy controls. MiR-21 discriminated PDF subjects (AUC=0.735) and CCA patients (AUC=0.682) from healthy controls. Combined levels of these two miRNAs revealed an increased AUC of 0.812 for separating opisthorchiasis, AUC of 0.815 in discriminating PDF subjects, and AUC of 0.849 in differentiating CCA from healthy controls. Odds ratios (OR) indicated high levels of miR-192/miR-21 as risk predictors for opisthorchiasis, PDF and CCA. Levels of these miRNAs declined significantly for patients following praziquantel treatment. In conclusion, urinary miR-192/miR-21 have potential as risk indicators for opisthorchiasis and PDF-associated CCA in the endemic region. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Pharmacokinetics of Rolapitant in Patients With Mild to Moderate Hepatic Impairment.

PubMed

Wang, Jing; Wang, Xiaodong; Zhang, Zhi-Yi; Arora, Sujata; Lu, Sharon; Kansra, Vikram

2018-05-01

Rolapitant is a selective and long-acting neurokinin-1 receptor antagonist approved in an oral formulation in combination with other antiemetic agents for the prevention of delayed chemotherapy-induced nausea and vomiting in adults. This was a phase 1 open-label, parallel-group pharmacokinetic and safety study of a single oral dose of 180 mg of rolapitant and its major active metabolite, M19, in subjects with mild and moderate hepatic impairment compared with healthy matched controls. Pharmacokinetics were assessed by a mixed-model analysis of variance of log-transformed values for maximum observed plasma concentration (C max ), observed time at C max (t max ), area under the plasma concentration-time curve (AUC) from time 0 to the time of the last quantifiable concentration (AUC 0-t ), and AUC from time 0 to 120 hours (AUC 0-120 ), with hepatic group as a fixed effect. Mean rolapitant C max , AUC 0-t , and AUC 0-120 were similar in the mild hepatic impairment and healthy control groups. In subjects with moderate hepatic impairment, AUC 0-t was similar and C max was 25% lower than in healthy controls. Mean M19 C max and AUC 0-t were similar in the mild hepatic impairment group and healthy controls, but <20% lower in those with moderate hepatic impairment versus healthy controls. Fraction of unbound rolapitant was comparable in all groups for rolapitant and M19. Rolapitant was well tolerated in all groups, without serious adverse events. Pharmacokinetic differences between healthy subjects and those with mild or moderate hepatic impairment are unlikely to pose a safety risk and do not warrant predefined dosage adjustment in the presence of hepatic impairment. © 2018, The American College of Clinical Pharmacology.

Automatically-computed prehospital severity scores are equivalent to scores based on medic documentation.

PubMed

Reisner, Andrew T; Chen, Liangyou; McKenna, Thomas M; Reifman, Jaques

2008-10-01

Prehospital severity scores can be used in routine prehospital care, mass casualty care, and military triage. If computers could reliably calculate clinical scores, new clinical and research methodologies would be possible. One obstacle is that vital signs measured automatically can be unreliable. We hypothesized that Signal Quality Indices (SQI's), computer algorithms that differentiate between reliable and unreliable monitored physiologic data, could improve the predictive power of computer-calculated scores. In a retrospective analysis of trauma casualties transported by air ambulance, we computed the Triage Revised Trauma Score (RTS) from archived travel monitor data. We compared the areas-under-the-curve (AUC's) of receiver operating characteristic curves for prediction of mortality and red blood cell transfusion for 187 subjects with comparable quantities of good-quality and poor-quality data. Vital signs deemed reliable by SQI's led to significantly more discriminatory severity scores than vital signs deemed unreliable. We also compared automatically-computed RTS (using the SQI's) versus RTS computed from vital signs documented by medics. For the subjects in whom the SQI algorithms identified 15 consecutive seconds of reliable vital signs data (n = 350), the automatically-computed scores' AUC's were the same as the medic-based scores' AUC's. Using the Prehospital Index in place of RTS led to very similar results, corroborating our findings. SQI algorithms improve automatically-computed severity scores, and automatically-computed scores using SQI's are equivalent to medic-based scores.

The Value of 18F-FDG PET/CT Mathematical Prediction Model in Diagnosis of Solitary Pulmonary Nodules

PubMed Central

Chen, Yao; Tang, Kun; Lin, Jie

2018-01-01

Purpose To establish an 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) mathematical prediction model to improve the diagnosis of solitary pulmonary nodules (SPNs). Materials and Methods We retrospectively reviewed 177 consecutive patients who underwent 18F-FDG PET/CT for evaluation of SPNs. The mathematical model was established by logistic regression analysis. The diagnostic capabilities of the model were calculated, and the areas under the receiver operating characteristic curve (AUC) were compared with Mayo and VA model. Results The mathematical model was y = exp⁡(x)/[1 + exp⁡(x)], x = −7.363 + 0.079 × age + 1.900 × lobulation + 1.024 × vascular convergence + 1.530 × pleural retraction + 0.359 × the maximum of standardized uptake value (SUVmax). When the cut-off value was set at 0.56, the sensitivity, specificity, and accuracy of our model were 86.55%, 74.14%, and 81.4%, respectively. The area under the receiver operating characteristic curve (AUC) of our model was 0.903 (95% confidence interval (CI): 0.860 to 0.946). The AUC of our model was greater than that of the Mayo model, the VA model, and PET (P < 0.05) and has no difference with that of PET/CT (P > 0.05). Conclusion The mathematical predictive model has high accuracy in estimating the malignant probability of patients with SPNs. PMID:29789808

The Memory Alteration Test Discriminates between Cognitively Healthy Status, Mild Cognitive Impairment and Alzheimer's Disease.

PubMed

Custodio, Nilton; Lira, David; Herrera-Perez, Eder; Nuñez Del Prado, Liza; Parodi, José; Guevara-Silva, Erik; Castro-Suarez, Sheila; Montesinos, Rosa; Cortijo, Patricia

2014-05-01

Dementia is a worldwide public health problem and there are several diagnostic tools for its assessment. The aim of this study was to evaluate the performance of the Memory Alteration Test (M@T) to discriminate between patients with early Alzheimer's disease (AD), patients with amnestic mild cognitive impairment (a-MCI), and subjects with a cognitively healthy status (CHS). The discriminative validity was assessed in a sample of 90 patients with AD, 45 patients with a-MCI, and 180 subjects with CHS. Clinical, functional, and cognitive studies were independently performed in a blinded fashion and the gold standard diagnosis was established by consensus on the basis of these results. The test performance was assessed by means of a receiver operating characteristic curve analysis as area under the curve (AUC). M@T mean scores were 17.7 (SD = 5.7) in AD, 30.8 (SD = 2.3) in a-MCI, and 44.5 (SD = 3.1) in CHS. A cutoff score of 37 points had a sensitivity of 98.3% and a specificity of 97.8% to differentiate a-MCI from CHS (AUC = 0.999). A cutoff score of 27 points had a sensitivity of 100% and a specificity of 98.9% to differentiate mild AD from a-MCI and from CHS (AUC = 1.000). The M@T had a high performance in the discrimination between early AD, a-MCI and CHS.

Characteristic of entire corneal topography and tomography for the detection of sub-clinical keratoconus with Zernike polynomials using Pentacam.

PubMed

Xu, Zhe; Li, Weibo; Jiang, Jun; Zhuang, Xiran; Chen, Wei; Peng, Mei; Wang, Jianhua; Lu, Fan; Shen, Meixiao; Wang, Yuanyuan

2017-11-28

The study aimed to characterize the entire corneal topography and tomography for the detection of sub-clinical keratoconus (KC) with a Zernike application method. Normal subjects (n = 147; 147 eyes), sub-clinical KC patients (n = 77; 77 eyes), and KC patients (n = 139; 139 eyes) were imaged with the Pentacam HR system. The entire corneal data of pachymetry and elevation of both the anterior and posterior surfaces were exported from the Pentacam HR software. Zernike polynomials fitting was used to quantify the 3D distribution of the corneal thickness and surface elevation. The root mean square (RMS) values for each order and the total high-order irregularity were calculated. Multimeric discriminant functions combined with individual indices were built using linear step discriminant analysis. Receiver operating characteristic curves determined the diagnostic accuracy (area under the curve, AUC). The 3rd-order RMS of the posterior surface (AUC: 0.928) obtained the highest discriminating capability in sub-clinical KC eyes. The multimeric function, which consisted of the Zernike fitting indices of corneal posterior elevation, showed the highest discriminant ability (AUC: 0.951). Indices generated from the elevation of posterior surface and thickness measurements over the entire cornea using the Zernike method based on the Pentacam HR system were able to identify very early KC.

Geodesic topological analysis of trabecular bone microarchitecture from high-spatial resolution magnetic resonance images.

PubMed

Carballido-Gamio, Julio; Krug, Roland; Huber, Markus B; Hyun, Ben; Eckstein, Felix; Majumdar, Sharmila; Link, Thomas M

2009-02-01

In vivo assessment of trabecular bone microarchitecture could improve the prediction of fracture risk and the efficacy of osteoporosis treatment and prevention. Geodesic topological analysis (GTA) is introduced as a novel technique to quantify the trabecular bone microarchitecture from high-spatial resolution magnetic resonance (MR) images. Trabecular bone parameters that quantify the scale, topology, and anisotropy of the trabecular bone network in terms of its junctions are the result of GTA. The reproducibility of GTA was tested with in vivo images of human distal tibiae and radii (n = 6) at 1.5 Tesla; and its ability to discriminate between subjects with and without vertebral fracture was assessed with ex vivo images of human calcanei at 1.5 and 3.0 Tesla (n = 30). GTA parameters yielded an average reproducibility of 4.8%, and their individual areas under the curve (AUC) of the receiver operating characteristic curve analysis for fracture discrimination performed better at 3.0 than at 1.5 Tesla reaching values of up to 0.78 (p < 0.001). Logistic regression analysis demonstrated that fracture discrimination was improved by combining GTA parameters, and that GTA combined with bone mineral density (BMD) allow for better discrimination than BMD alone (AUC = 0.95; p < 0.001). Results indicate that GTA can substantially contribute in studies of osteoporosis involving imaging of the trabecular bone microarchitecture. Copyright 2009 Wiley-Liss, Inc.

Evaluation of a Novel Glucose Area Under the Curve (AUC) Monitoring System: Comparison with the AUC by Continuous Glucose Monitoring

PubMed Central

Maegawa, Hiroshi; Morino, Katsutaro; Nishio, Yoshihiko; Sato, Toshiyuki; Okada, Seiki; Kikkawa, Yasuo; Watanabe, Toshihiro; Nakajima, Hiromu; Kashiwagi, Atsunori

2016-01-01

Background Management of postprandial hyperglycemia is a key aspect in diabetes treatment. We developed a novel system to measure glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET) for simple monitoring of postprandial glucose excursions. In this study, we evaluated the relationship between our system and continuous glucose monitoring (CGM) by comparing glucose AUC obtained using MIET with that obtained using CGM for a long duration. Methods Twenty diabetic inpatients wearing a CGM system were enrolled. For MIET measurement, a plastic microneedle array was applied to the skin as pretreatment, and hydrogels were placed on the pretreated area to collect interstitial fluid. Hydrogels were replaced every 2 or 4 hours and AUC was predicted on the basis of glucose and sodium ion levels. Results AUC predicted by MIET correlated well with that measured by CGM (r=0.93). Good performances of both consecutive 2- and 4-hour measurements were observed (measurement error: 11.7%±10.2% for 2 hours and 11.1%±7.9% for 4 hours), indicating the possibility of repetitive measurements up to 8 hours. The influence of neither glucose fluctuation nor average glucose level over the measurement accuracy was observed through 8 hours. Conclusion Our system showed good relationship with AUC values from CGM up to 8 hours, indicating that single pretreatment can cover a large portion of glucose excursion in a day. These results indicated possibility of our system to contribute to convenient monitoring of glucose excursions for a long duration. PMID:27535643

Evaluation of a Novel Glucose Area Under the Curve (AUC) Monitoring System: Comparison with the AUC by Continuous Glucose Monitoring.

PubMed

Ugi, Satoshi; Maegawa, Hiroshi; Morino, Katsutaro; Nishio, Yoshihiko; Sato, Toshiyuki; Okada, Seiki; Kikkawa, Yasuo; Watanabe, Toshihiro; Nakajima, Hiromu; Kashiwagi, Atsunori

2016-08-01

Management of postprandial hyperglycemia is a key aspect in diabetes treatment. We developed a novel system to measure glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET) for simple monitoring of postprandial glucose excursions. In this study, we evaluated the relationship between our system and continuous glucose monitoring (CGM) by comparing glucose AUC obtained using MIET with that obtained using CGM for a long duration. Twenty diabetic inpatients wearing a CGM system were enrolled. For MIET measurement, a plastic microneedle array was applied to the skin as pretreatment, and hydrogels were placed on the pretreated area to collect interstitial fluid. Hydrogels were replaced every 2 or 4 hours and AUC was predicted on the basis of glucose and sodium ion levels. AUC predicted by MIET correlated well with that measured by CGM (r=0.93). Good performances of both consecutive 2- and 4-hour measurements were observed (measurement error: 11.7%±10.2% for 2 hours and 11.1%±7.9% for 4 hours), indicating the possibility of repetitive measurements up to 8 hours. The influence of neither glucose fluctuation nor average glucose level over the measurement accuracy was observed through 8 hours. Our system showed good relationship with AUC values from CGM up to 8 hours, indicating that single pretreatment can cover a large portion of glucose excursion in a day. These results indicated possibility of our system to contribute to convenient monitoring of glucose excursions for a long duration.

Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

PubMed

Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

2018-02-01

1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE < 10.3%. The external data evaluation showed that the models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas.

PubMed

Kinoshita, Manabu; Sakai, Mio; Arita, Hideyuki; Shofuda, Tomoko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki; Nakanishi, Katsuyuki; Kanemura, Yonehiro

2016-01-01

Reports have suggested that tumor textures presented on T2-weighted images correlate with the genetic status of glioma. Therefore, development of an image analyzing framework that is capable of objective and high throughput image texture analysis for large scale image data collection is needed. The current study aimed to address the development of such a framework by introducing two novel parameters for image textures on T2-weighted images, i.e., Shannon entropy and Prewitt filtering. Twenty-two WHO grade 2 and 28 grade 3 glioma patients were collected whose pre-surgical MRI and IDH1 mutation status were available. Heterogeneous lesions showed statistically higher Shannon entropy than homogenous lesions (p = 0.006) and ROC curve analysis proved that Shannon entropy on T2WI was a reliable indicator for discrimination of homogenous and heterogeneous lesions (p = 0.015, AUC = 0.73). Lesions with well-defined borders exhibited statistically higher Edge mean and Edge median values using Prewitt filtering than those with vague lesion borders (p = 0.0003 and p = 0.0005 respectively). ROC curve analysis also proved that both Edge mean and median values were promising indicators for discrimination of lesions with vague and well defined borders and both Edge mean and median values performed in a comparable manner (p = 0.0002, AUC = 0.81 and p < 0.0001, AUC = 0.83, respectively). Finally, IDH1 wild type gliomas showed statistically lower Shannon entropy on T2WI than IDH1 mutated gliomas (p = 0.007) but no difference was observed between IDH1 wild type and mutated gliomas in Edge median values using Prewitt filtering. The current study introduced two image metrics that reflect lesion texture described on T2WI. These two metrics were validated by readings of a neuro-radiologist who was blinded to the results. This observation will facilitate further use of this technique in future large scale image analysis of glioma.

LB02.06: CLINICAL IMPLICATIONS OF THE DIASTOLIC BLOOD PRESSURE 'J CURVE' IN TREATED HYPERTENSIVE PATIENTS.

PubMed

Lip, S; McCallum, L; Touyz, R H; Dominiczak, A F; Padmanabhan, S

2015-06-01

Recent studies have shown that low diastolic blood pressure is associated with increased cardiovascular outcomes especially in those with pre-existing cardiovascular disease (DBP 'J' Curve). Whether this has practical implications in real life hypertension practice is unknown. We analysed the achieved blood pressure of 6,072 patients between years 2 and 5 following initial presentation to the Glasgow Blood Pressure Clinic. Patients were classified into nine groups based on the area under the curve(AUC) of at least 3 blood pressure(BP) readings during this period. Multivariable adjusted 30 years survival analysis was performed using Cox proportional hazards model. The age of first visit was 53±13 years, BMI 27.6 ± 5.2, baseline BP 169 ± 29/100 ± 18 mmHg, 52% were females, 60% drank more than 6 units of alcohol/week, 44% were ever smokers, 26% had prevalent CVD and 26% had eGFR<60. Of 6,072 individuals, 418(7%) achieved AUC-BP =<140/80; 365(12%) had isolated systolic hypertension(ISH) (>140/<80mmHg) of whom 98 had severe ISH (SBP>160/ DBP<80). There were only 199(0.7%) subjects with AUC-DBP<70 mmHg. 30 year survival data was available for 5,451 individuals with 1,662 all-cause deaths and 65,430 person-years of follow-up. Figure 1 presents the adjusted hazard ratios for cardiovascular mortality showing significant excess risk associated with DBP<80 only in subjects with SBP>160.(Figure is included in full-text article.) : In treated hypertensive patients, the DBP 'J 'curve is not apparent with achieved BP 2 - 5 years from presentation. This may be explained partly by the low likelihood of achieving DBP<70 2-5 years after commencing treatment.

R- and S-citalopram concentrations have differential effects on neuropsychiatric scores in elders with dementia and agitation.

PubMed

Ho, Thang; Pollock, Bruce G; Mulsant, Benoit H; Schantz, Oliver; Devanand, Devangere P; Mintzer, Jacobo E; Porsteinsson, Anton P; Schneider, Lon S; Weintraub, Daniel; Yesavage, Jerome; Drye, Lea T; Munro, Cynthia A; Shade, David M; Lyketsos, Constantine; Bies, Robert

2016-09-01

The aim was to determine the relationship between (R) and (S)-citalopram enantiomer exposure (AUC(0,24 h)) and therapeutic response in agitated individuals greater than 60 years old with Alzheimer's dementia (AD). Citalopram enantiomer exposures (AUC(0,24 h)) derived from an established population pharmacokinetic analysis were utilized to explore the relationship between (R)- and (S)-citalopram area under the curve (AUC(0,24 )) and Mini-Mental State Examination (MMSE), Neurobehavioural Rating Scale-Agitation Subscale (NBRS-A), modified Alzheimer's Disease Cooperative Study-Clinical Global Impression of Change (mADCS-CGIC) and Neuropsychiatric Inventory Agitation subscale (NPIA) scores. Time dependent changes in these scores (disease progression) were accounted for prior to exploring the exposure effect relationship for each enantiomer. These relationships were evaluated using a non-linear-mixed effects modelling approach as implemented in nonmem v7.3. (S)-AUC(0,24 h) and (R)-AUC(0,24 h) each contributed to improvement in NBRS-A scores (k3(R) -0.502; k4(S) -0.712) as did time in treatment. However, increasing (R)-AUC(0,24 h) decreased the probability of patient response (maximum Δ -0.182%/AUC(0,24 h)) based on the CGIC while (S)-AUC(0,24 h) improved the probability of response (maximum Δ 0.112%/AUC(0,24 h)). (R)-AUC(0,24 h) was also associated with worsening in MMSE scores (-0.5 points). Our results suggest that citalopram enantiomers contributed differentially to treatment outcomes. (R)-citalopram accounted for a greater proportion of the adverse consequences associated with racemic citalopram treatment in patients with AD including a decreased probability of treatment response as measured by the CGIC and a reduction in MMSE scores. The S-enantiomer was associated with increased probability of response based on the CGIC. © 2016 The British Pharmacological Society.

Detection of Prostate Cancer: Quantitative Multiparametric MR Imaging Models Developed Using Registered Correlative Histopathology.

PubMed

Metzger, Gregory J; Kalavagunta, Chaitanya; Spilseth, Benjamin; Bolan, Patrick J; Li, Xiufeng; Hutter, Diane; Nam, Jung W; Johnson, Andrew D; Henriksen, Jonathan C; Moench, Laura; Konety, Badrinath; Warlick, Christopher A; Schmechel, Stephen C; Koopmeiners, Joseph S

2016-06-01

Purpose To develop multiparametric magnetic resonance (MR) imaging models to generate a quantitative, user-independent, voxel-wise composite biomarker score (CBS) for detection of prostate cancer by using coregistered correlative histopathologic results, and to compare performance of CBS-based detection with that of single quantitative MR imaging parameters. Materials and Methods Institutional review board approval and informed consent were obtained. Patients with a diagnosis of prostate cancer underwent multiparametric MR imaging before surgery for treatment. All MR imaging voxels in the prostate were classified as cancer or noncancer on the basis of coregistered histopathologic data. Predictive models were developed by using more than one quantitative MR imaging parameter to generate CBS maps. Model development and evaluation of quantitative MR imaging parameters and CBS were performed separately for the peripheral zone and the whole gland. Model accuracy was evaluated by using the area under the receiver operating characteristic curve (AUC), and confidence intervals were calculated with the bootstrap procedure. The improvement in classification accuracy was evaluated by comparing the AUC for the multiparametric model and the single best-performing quantitative MR imaging parameter at the individual level and in aggregate. Results Quantitative T2, apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), reflux rate constant (kep), and area under the gadolinium concentration curve at 90 seconds (AUGC90) were significantly different between cancer and noncancer voxels (P < .001), with ADC showing the best accuracy (peripheral zone AUC, 0.82; whole gland AUC, 0.74). Four-parameter models demonstrated the best performance in both the peripheral zone (AUC, 0.85; P = .010 vs ADC alone) and whole gland (AUC, 0.77; P = .043 vs ADC alone). Individual-level analysis showed statistically significant improvement in AUC in 82% (23 of 28) and 71% (24 of 34) of patients with peripheral-zone and whole-gland models, respectively, compared with ADC alone. Model-based CBS maps for cancer detection showed improved visualization of cancer location and extent. Conclusion Quantitative multiparametric MR imaging models developed by using coregistered correlative histopathologic data yielded a voxel-wise CBS that outperformed single quantitative MR imaging parameters for detection of prostate cancer, especially when the models were assessed at the individual level. (©) RSNA, 2016 Online supplemental material is available for this article.

Very early diagnosis of chest pain by point-of-care testing: comparison of the diagnostic efficiency of a panel of cardiac biomarkers compared with troponin measurement alone in the RATPAC trial.

PubMed

Collinson, Paul; Goodacre, Steve; Gaze, David; Gray, Alasdair

2012-02-01

To assess the impact of triple marker testing on patient management and the diagnostic efficiencies of different biomarker strategies examined. A prospective randomised trial of triple marker testing by point-of-care testing (POCT); the Randomised Assessment of Panel Assay of Cardiac markers (RATPAC) study. Six emergency departments. Low-risk patients presenting with chest pain to diagnostic assessment with a cardiac panel measured by POCT or to diagnosis when biomarker measurement was based on central laboratory testing. Interventions 1125 patients were randomly assigned to POCT measurement of the triple marker panel of cardiac troponin I (cTnI), myoglobin and the MB isoenzyme of creatine kinase (CK-MB) on admission and 90 min from admission. Myocardial infarction (MI) was defined by the universal definition of MI. The following diagnostic strategies were compared by receiver operator characteristic (ROC) curve analysis and comparison of area under the curve (AUC): individual marker values, change (Δ) in CK-MB and myoglobin and the combination of presentation or 90 min value plus Δ value. Admission sample measurement of cTnI was the most diagnostically efficient AUC 0.96 (0.93-0.98) with areas under the ROC curve statistically significantly greater than CK-MB 0.85 (0.80-0.90) and myoglobin 0.75 (0.68-0.81). At 90 min cTnI measurement had the highest AUC 0.95 (0.87-1.00) but was statistically significantly different only from Δmyoglobin and ΔCK-MB. Measurement of cTnI alone is sufficient for diagnosis. Measurement of a marker panel does not facilitate diagnosis.

External validation and comparison of three pediatric clinical dehydration scales.

PubMed

Jauregui, Joshua; Nelson, Daniel; Choo, Esther; Stearns, Branden; Levine, Adam C; Liebmann, Otto; Shah, Sachita P

2014-01-01

To prospectively validate three popular clinical dehydration scales and overall physician gestalt in children with vomiting or diarrhea relative to the criterion standard of percent weight change with rehydration. We prospectively enrolled a non-consecutive cohort of children ≤ 18 years of age with an acute episode of diarrhea or vomiting. Patient weight, clinical scale variables and physician clinical impression, or gestalt, were recorded before and after fluid resuscitation in the emergency department and upon hospital discharge. The percent weight change from presentation to discharge was used to calculate the degree of dehydration, with a weight change of ≥ 5% considered significant dehydration. Receiver operating characteristics (ROC) curves were constructed for each of the three clinical scales and physician gestalt. Sensitivity and specificity were calculated based on the best cut-points of the ROC curve. We approached 209 patients, and of those, 148 were enrolled and 113 patients had complete data for analysis. Of these, 10.6% had significant dehydration based on our criterion standard. The Clinical Dehydration Scale (CDS) and Gorelick scales both had an area under the ROC curve (AUC) statistically different from the reference line with AUCs of 0.72 (95% CI 0.60, 0.84) and 0.71 (95% CI 0.57, 0.85) respectively. The World Health Organization (WHO) scale and physician gestalt had AUCs of 0.61 (95% CI 0.45, 0.77) and 0.61 (0.44, 0.78) respectively, which were not statistically significant. The Gorelick scale and Clinical Dehydration Scale were fair predictors of dehydration in children with diarrhea or vomiting. The World Health Organization scale and physician gestalt were not helpful predictors of dehydration in our cohort.

External Validation and Comparison of Three Pediatric Clinical Dehydration Scales

PubMed Central

Jauregui, Joshua; Nelson, Daniel; Choo, Esther; Stearns, Branden; Levine, Adam C.; Liebmann, Otto; Shah, Sachita P.

2014-01-01

Objective To prospectively validate three popular clinical dehydration scales and overall physician gestalt in children with vomiting or diarrhea relative to the criterion standard of percent weight change with rehydration. Methods We prospectively enrolled a non-consecutive cohort of children ≤ 18 years of age with an acute episode of diarrhea or vomiting. Patient weight, clinical scale variables and physician clinical impression, or gestalt, were recorded before and after fluid resuscitation in the emergency department and upon hospital discharge. The percent weight change from presentation to discharge was used to calculate the degree of dehydration, with a weight change of ≥ 5% considered significant dehydration. Receiver operating characteristics (ROC) curves were constructed for each of the three clinical scales and physician gestalt. Sensitivity and specificity were calculated based on the best cut-points of the ROC curve. Results We approached 209 patients, and of those, 148 were enrolled and 113 patients had complete data for analysis. Of these, 10.6% had significant dehydration based on our criterion standard. The Clinical Dehydration Scale (CDS) and Gorelick scales both had an area under the ROC curve (AUC) statistically different from the reference line with AUCs of 0.72 (95% CI 0.60, 0.84) and 0.71 (95% CI 0.57, 0.85) respectively. The World Health Organization (WHO) scale and physician gestalt had AUCs of 0.61 (95% CI 0.45, 0.77) and 0.61 (0.44, 0.78) respectively, which were not statistically significant. Conclusion The Gorelick scale and Clinical Dehydration Scale were fair predictors of dehydration in children with diarrhea or vomiting. The World Health Organization scale and physician gestalt were not helpful predictors of dehydration in our cohort. PMID:24788134

Magnetic Resonance Imaging of Intracranial Hypotension: Diagnostic Value of Combined Qualitative Signs and Quantitative Metrics.

PubMed

Aslan, Kerim; Gunbey, Hediye Pinar; Tomak, Leman; Ozmen, Zafer; Incesu, Lutfi

The aim of this study was to investigate whether the use of combination quantitative metrics (mamillopontine distance [MPD], pontomesencephalic angle, and mesencephalon anterior-posterior/medial-lateral diameter ratios) with qualitative signs (dural enhancement, subdural collections/hematoma, venous engorgement, pituitary gland enlargements, and tonsillar herniations) provides a more accurate diagnosis of intracranial hypotension (IH). The quantitative metrics and qualitative signs of 34 patients and 34 control subjects were assessed by 2 independent observers. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of quantitative metrics and qualitative signs, and for the diagnosis of IH, optimum cutoff values of quantitative metrics were found with ROC analysis. Combined ROC curve was measured for the quantitative metrics, and qualitative signs combinations in determining diagnostic accuracy and sensitivity, specificity, and positive and negative predictive values were found, and the best model combination was formed. Whereas MPD and pontomesencephalic angle were significantly lower in patients with IH when compared with the control group (P < 0.001), mesencephalon anterior-posterior/medial-lateral diameter ratio was significantly higher (P < 0.001). For qualitative signs, the highest individual distinctive power was dural enhancement with area under the ROC curve (AUC) of 0.838. For quantitative metrics, the highest individual distinctive power was MPD with AUC of 0.947. The best accuracy in the diagnosis of IH was obtained by combination of dural enhancement, venous engorgement, and MPD with an AUC of 1.00. This study showed that the combined use of dural enhancement, venous engorgement, and MPD had diagnostic accuracy of 100 % for the diagnosis of IH. Therefore, a more accurate IH diagnosis can be provided with combination of quantitative metrics with qualitative signs.

Association of the clinical efficacy of vancomycin with the novel pharmacokinetic parameter area under the trough level (AUTL) in elderly patients with hospital-acquired pneumonia.

PubMed

Fukumori, S; Tsuji, Y; Mizoguchi, A; Kasai, H; Ishibashi, T; Iwamura, N; To, H

2016-08-01

The pharmacokinetic-pharmacodynamic parameter that best predicts the efficacy of vancomycin is the ratio of the area under the concentration versus time curve (AUC) to the minimum inhibitory concentration (MIC). A 24-h AUC (AUC24 )/MIC ratio ≥ 400 was recommended in an American consensus review, but vancomycin treatment occasionally fails despite maintenance of AUC24 /MIC ≥ 400. We evaluated the association between clinical efficacy of vancomycin and two novel pharmacokinetic parameters, the 'area under the trough level' (AUTL) and the 'area above the trough level' (AATL), in hospitalized elderly patients with methicillin-resistant Staphylococcus aureus (MRSA) pneumonia. The subjects were hospitalized elderly patients who were administered vancomycin for treatment of MRSA pneumonia between 2006 and 2012 at Sasebo Chuo Hospital (Nagasaki, Japan). Pharmacokinetic parameters of vancomycin were estimated for each patient by Bayesian analysis using population pharmacokinetic parameters for Japanese patients. Based on the patient-specific parameters thus obtained, AUC24 values were calculated as the vancomycin dosage divided by vancomycin clearance. AUTL was calculated as the trough serum concentration multiplied by 24 h, whereas AATL was calculated by subtracting AUTL from AUC24 . Logistic regression analysis demonstrated that efficacy of vancomycin was more strongly associated with AUTL than AUC24 . The optimal cut-off value of AUTL was 331 μg∙h/mL, which means that the optimal cut-off value of the trough serum concentration was 13·8 μg/mL. Efficacy of vancomycin was associated with AUTL, a novel pharmacokinetic parameter. Determining the target AUTL or trough concentration may enhance the efficacy of vancomycin therapy in elderly patients with MRSA pneumonia. Given that nephrotoxicity may increase with a Ctrough in excess of 15 μg/mL, this level should ideally not be exceeded. © 2016 John Wiley & Sons Ltd.

Validation of the Framingham Heart Study and CHARGE-AF Risk Scores for Atrial Fibrillation in Hispanics, African-Americans, and Non-Hispanic Whites.

PubMed

Shulman, Eric; Kargoli, Faraj; Aagaard, Philip; Hoch, Ethan; Di Biase, Luigi; Fisher, John; Gross, Jay; Kim, Soo; Krumerman, Andrew; Ferrick, Kevin J

2016-01-01

A risk score for atrial fibrillation (AF) has been developed by the Framingham Heart Study and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF consortium. However, validation of these risk scores in an inner-city population is uncertain. Thus, a validation model was built using the Framingham Risk Score for AF and CHARGE-AF covariates. An in and outpatient electrocardiographic database was interrogated from 2000 to 2013 for the development of AF. Patients were included if their age was >45 and <95 years, had <10-year follow-up, if their initial electrocardiogram was without AF, had ≥ 2 electrocardiograms, and declared a race and/or ethnicity as non-Hispanic white, African-American, or Hispanic. For the Framingham Heart Study, 49,599 patients met inclusion criteria, of which 4,860 developed AF. Discrimination analysis using area under the curve (AUC) for original risk equations: non-Hispanic white AUC = 0.712 (95% confidence interval [CI] 0.694 to 0.731), African-American AUC = 0.733 (95% CI 0.716 to 0.751), and Hispanic AUC = 0.740 (95% CI 0.723 to 0.757). For the CHARGE-AF, 45,571 patients met inclusion criteria, of which 4,512 developed AF. Non-Hispanic white AUC = 0.673 (95% CI 0.652 to 0.694), African-American AUC = 0.706 (95% CI 0.685 to 0.727), and Hispanic AUC = 0.711 (95% CI 0.691 to 0.732). Calibration analysis showed qualitative similarities between cohorts. In conclusion, this is the first study to validate both the Framingham Heart Study and CHARGE-AF risk scores in both a Hispanic and African-American cohort. All models predicted AF well across all race and ethnic cohorts. Copyright © 2016 Elsevier Inc. All rights reserved.

Association of osteolytic lesions, bone mineral loss and trabecular sclerosis with prevalent vertebral fractures in patients with multiple myeloma.

PubMed

Borggrefe, J; Giravent, S; Campbell, G; Thomsen, F; Chang, D; Franke, M; Günther, A; Heller, M; Wulff, A

2015-11-01

In patients with multiple myeloma (MM), computed tomography is widely used for staging and to detect fractures. Detecting patients at severe fracture risk is of utmost importance. However the criteria for impaired stability of vertebral bodies are not yet clearly defined. We investigated the performance of parameters that can be detected by the radiologist for discrimination of patients with and without fractures. We analyzed 128 whole body low-dose CT of MM patients. In all scans a QCT calibration phantom was integrated into the positioning mat (Image Analysis Phantom(®)). A QCT-software (Structural Insight) performed the volumetric bone mineral density (vBMD) measurements. Description of fracture risk was provided from the clinical radiological report. Suspected progressive disease (PD) was reported by the referring clinicians. Two radiologists that were blinded to study outcome reported on the following parameters based on predefined criteria: reduced radiodensity in the massa lateralis of the os sacrum (RDS), trabecular thickening and sclerosis of three or more vertebrae (TTS), extraosseous MM manifestations (EOM), visible small osteolytic lesions up to a length of 8mm (SO) and osteolytic lesions larger than 8mm (LO). Prevalent vertebral fractures (PVF) were defined by Genant criteria. Age-adjusted standardized odds ratios (sOR) per standard deviation change were derived from logistic regression analysis and area under the curve (AUC) from receiver operating characteristics (ROC) analyses were calculated. ROC curves were compared using the DeLong method. 45% of the 128 patients showed PVF (29 of 75 men, 24 of 53 women). Patients with PVF were not significantly older than patients without fractures (64.6 ± 9.2 vs. 63.3 ± 12.3 years: mean ± SD, p=0.5). The prevalence of each parameter did not differ significantly by sex. Significant fracture discrimination for age adjusted single models was provided by the parameters vBMD (OR 3.5 [1.4-8.8], AUC=0.64 ± 0.14), SO (sOR 1.6[1.1-2.2], AUC=0.63 ± 0.05), LO (sOR 2.1[1.1-4.2] AUC=0.69 ± 0.05) and RDS (sOR 2.6[1.6-4.7], AUC=0.69 ± 0.05). Multivariate models of these four parameters showed a significantly stronger association with the development of PVF (AUC=0.80 ± 0.04) than single variables. TTS showed a significant association with PVF in men(sOR 1.5 [0.8-3.0], AUC=0.63 ± 0.08), but not in women (sOR 2.3[1.4-3.7], AUC=0.70 ± 0.07). PD was significantly associated with PVF in women (sOR 1.9[1.1-3.6], AUC=0.67 ± 0.08) but not in men (sOR 1.4[0.9-2.3], AUC=0.57 ± .07). EOM were not associated with PVF (sOR 1.0[0.4-2.6], AUC=0.51 ± .05). In multiple myeloma, focal skeletal changes in low dose CT scans show a significant association with prevalent vertebral fractures. The combination of large osteolytic lesions and loss in radiodensity as can be detected with simple CT Hounsfield measurements of the os sacrum or BMD measurements showed the strongest association to fractures and may be of value for prospective studies. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The impact of composite AUC estimates on the prediction of systemic exposure in toxicology experiments.

PubMed

Sahota, Tarjinder; Danhof, Meindert; Della Pasqua, Oscar

2015-06-01

Current toxicity protocols relate measures of systemic exposure (i.e. AUC, Cmax) as obtained by non-compartmental analysis to observed toxicity. A complicating factor in this practice is the potential bias in the estimates defining safe drug exposure. Moreover, it prevents the assessment of variability. The objective of the current investigation was therefore (a) to demonstrate the feasibility of applying nonlinear mixed effects modelling for the evaluation of toxicokinetics and (b) to assess the bias and accuracy in summary measures of systemic exposure for each method. Here, simulation scenarios were evaluated, which mimic toxicology protocols in rodents. To ensure differences in pharmacokinetic properties are accounted for, hypothetical drugs with varying disposition properties were considered. Data analysis was performed using non-compartmental methods and nonlinear mixed effects modelling. Exposure levels were expressed as area under the concentration versus time curve (AUC), peak concentrations (Cmax) and time above a predefined threshold (TAT). Results were then compared with the reference values to assess the bias and precision of parameter estimates. Higher accuracy and precision were observed for model-based estimates (i.e. AUC, Cmax and TAT), irrespective of group or treatment duration, as compared with non-compartmental analysis. Despite the focus of guidelines on establishing safety thresholds for the evaluation of new molecules in humans, current methods neglect uncertainty, lack of precision and bias in parameter estimates. The use of nonlinear mixed effects modelling for the analysis of toxicokinetics provides insight into variability and should be considered for predicting safe exposure in humans.

Detecting recurrent major depressive disorder within primary care rapidly and reliably using short questionnaire measures.

PubMed

Thapar, Ajay; Hammerton, Gemma; Collishaw, Stephan; Potter, Robert; Rice, Frances; Harold, Gordon; Craddock, Nicholas; Thapar, Anita; Smith, Daniel J

2014-01-01

Major depressive disorder (MDD) is often a chronic disorder with relapses usually detected and managed in primary care using a validated depression symptom questionnaire. However, for individuals with recurrent depression the choice of which questionnaire to use and whether a shorter measure could suffice is not established. To compare the nine-item Patient Health Questionnaire (PHQ-9), the Beck Depression Inventory, and the Hospital Anxiety and Depression Scale against shorter PHQ-derived measures for detecting episodes of DSM-IV major depression in primary care patients with recurrent MDD. Diagnostic accuracy study of adults with recurrent depression in primary care predominantly from Wales Scores on each of the depression questionnaire measures were compared with the results of a semi-structured clinical diagnostic interview using Receiver Operating Characteristic curve analysis for 337 adults with recurrent MDD. Concurrent questionnaire and interview data were available for 272 participants. The one-month prevalence rate of depression was 22.2%. The area under the curve (AUC) and positive predictive value (PPV) at the derived optimal cut-off value for the three longer questionnaires were comparable (AUC = 0.86-0.90, PPV = 49.4-58.4%) but the AUC for the PHQ-9 was significantly greater than for the PHQ-2. However, by supplementing the PHQ-2 score with items on problems concentrating and feeling slowed down or restless, the AUC (0.91) and the PPV (55.3%) were comparable with those for the PHQ-9. A novel four-item PHQ-based questionnaire measure of depression performs equivalently to three longer depression questionnaires in identifying depression relapse in patients with recurrent MDD.

Waist circumference is a potential indicator of metabolic syndrome in Singaporean Chinese.

PubMed

Nurjono, Milawaty; Lee, Jimmy

2013-05-01

Metabolic Syndrome (MetS) is associated with cardiovascular morbidity and mortality. Studies proposed that waist circumference (WC) and body mass index (BMI) are good indicators of MetS. In this study, we examined and compared the predictive utility of clinical measures such as WC, blood pressure and BMI and determined the cutoff points in which these measures are most reliable in identifying MetS in Singaporean Chinese. Two hundred and forty-four subjects aged between 21 and 50 years of Chinese ethnicity were recruited into the study. Sociodemographic, height, weight and blood pressure information were obtained. High-density lipoprotein cholesterol (HDL-C), triglycerides (TG) and glucose levels were evaluated. Presence of MetS was examined according to American Heart Association (AHA)/National Heart, Lung and Blood Institute (NHLBI) guidelines. Predictive utility of BP, WC and BMI was examined using receiver operating curve and discriminant indices were determined accordingly. Forty-one (16.8%) subjects were identified to have MetS. Our analysis revealed that waist circumference was most accurate in identifying MetS (area under the curve (AUC) = 0.88, 95% confidence interval (CI), 0.83 to 0.93, P <0.001) followed by BMI (AUC = 0.84, 95% CI, 0.77 to 0.91, P = 0.035), systolic BP (AUC = 0.83, 95% CI, 0.76 to 0.90, P = 0.036) and diastolic BP (AUC = 0.80, 95% CI, 0.71 to 0.88, P = 0.042). Waist circumference cut-off values of >92.5 cm in males and >86.5 cm in females were found to be most sensitive and specific in discriminating MetS. Our finding has immediate and significant clinical implications as WC can be easily obtained. However, as the study included only Singaporean Chinese, findings cannot be generalised for other ethnic groups.

Age threshold for moderate and severe periodontitis among Korean adults without diabetes mellitus, hypertension, metabolic syndrome, and/or obesity.

PubMed

Han, Kyungdo; Park, Jun-Beom

2017-08-01

The purpose of this study is to determine an appropriate age threshold at which to recommend the evaluation of moderate and severe periodontitis among Korean adults.This study involved a cross-sectional analysis using data from the Korean National Health and Nutrition Examination Survey from 2012 to 2014. Incidence rates of periodontitis with the 95% confidence interval (CI) were evaluated. The predictive accuracy of age for periodontitis was determined by calculating the area under curve (AUC) on the basis of the receiver operating characteristic (ROC) curve.The cutoff value of age was 43 years in men having periodontitis with an AUC of 0.70 with 95% CI of 0.69 to 0.72. The AUC was 0.72 (95% CI: 0.70-0.73), and the cutoff value of age (49 years) was identified for the moderate periodontitis in women. The cutoff values for age with AUCs and 95% CI for individuals with periodontitis were 46 years (0.72 [0.71-0.73]), 43 years (0.73 [0.72, 0.74]), 45 years (0.71 [0.70,0.72]), 43 years (0.73 [0.72, 0.74]), and 45 years (0.74 [0.72, 0.75]) for no obesity, no abdominal obesity, no diabetes mellitus, no hypertension, and no metabolic syndrome groups, respectively.This study proposed the guideline for the appropriate age threshold at which to recommend the evaluation of moderate and severe periodontitis for the general population and additionally added the guideline for the individuals without systemic disease including diabetes mellitus, hypertension, metabolic syndrome, and obesity. This study suggests that the participants with certain age may be recommended for the regular periodontal evaluation.

Age threshold for moderate and severe periodontitis among Korean adults without diabetes mellitus, hypertension, metabolic syndrome, and/or obesity

PubMed Central

Han, Kyungdo; Park, Jun-Beom

2017-01-01

Abstract The purpose of this study is to determine an appropriate age threshold at which to recommend the evaluation of moderate and severe periodontitis among Korean adults. This study involved a cross-sectional analysis using data from the Korean National Health and Nutrition Examination Survey from 2012 to 2014. Incidence rates of periodontitis with the 95% confidence interval (CI) were evaluated. The predictive accuracy of age for periodontitis was determined by calculating the area under curve (AUC) on the basis of the receiver operating characteristic (ROC) curve. The cutoff value of age was 43 years in men having periodontitis with an AUC of 0.70 with 95% CI of 0.69 to 0.72. The AUC was 0.72 (95% CI: 0.70–0.73), and the cutoff value of age (49 years) was identified for the moderate periodontitis in women. The cutoff values for age with AUCs and 95% CI for individuals with periodontitis were 46 years (0.72 [0.71–0.73]), 43 years (0.73 [0.72, 0.74]), 45 years (0.71 [0.70,0.72]), 43 years (0.73 [0.72, 0.74]), and 45 years (0.74 [0.72, 0.75]) for no obesity, no abdominal obesity, no diabetes mellitus, no hypertension, and no metabolic syndrome groups, respectively. This study proposed the guideline for the appropriate age threshold at which to recommend the evaluation of moderate and severe periodontitis for the general population and additionally added the guideline for the individuals without systemic disease including diabetes mellitus, hypertension, metabolic syndrome, and obesity. This study suggests that the participants with certain age may be recommended for the regular periodontal evaluation. PMID:28816984

Asthma Control and Sputum Eosinophils: A Longitudinal Study in Daily Practice.

PubMed

Demarche, Sophie F; Schleich, Florence N; Paulus, Virginie A; Henket, Monique A; Van Hees, Thierry J; Louis, Renaud E

Longitudinal trials have suggested that asthma control may be influenced by fluctuations in eosinophilic inflammation. This association has however never been confirmed in daily practice. To investigate the relationship between asthma control and sputum eosinophils in clinical practice. A retrospective longitudinal study was conducted on 187 patients with asthma with at least 2 successful sputum inductions at our Asthma Clinic. Linear mixed models were used to assess the relationship between asthma control and individual changes in sputum eosinophils. Receiver-operating characteristic curves were constructed to define minimal important differences (MIDs) of sputum eosinophils associated with a change of at least 0.5 in Asthma Control Questionnaire (ACQ) score. Then, a validation cohort of 79 patients with asthma was recruited to reassess this relationship and the accuracy of the MID values. A multivariate analysis showed that asthma control was independently associated with individual fluctuations in sputum eosinophil count (P < .001). In patients with intermittent/persistently eosinophilic asthma, we calculated a minimal important decrease of 4.3% in the percentage of sputum eosinophils (area under the curve [AUC], 0.69; P < .001) or 3.4-fold (AUC, 0.65; P = .003) for a significant improvement in asthma control and a minimal important increase of 3.5% (AUC, 0.67; P = .004) or 1.8-fold (AUC, 0.63; P = .02) for a significant worsening in asthma control. The association between asthma control and sputum eosinophils and the accuracy of the MIDs of sputum eosinophils were confirmed in the validation cohort. At the individual level, asthma control was associated with fluctuations in sputum eosinophil count over time. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Respiratory variation of systolic and diastolic time intervals within radial arterial waveform: a comparison with dynamic preload index.

PubMed

Park, Ji Hyun; Hwang, Gyu-Sam

2016-08-01

A blood pressure (BP) waveform contains various pieces of information related to respiratory variation. Systolic time interval (STI) reflects myocardial performance, and diastolic time interval (DTI) represents diastolic filling. This study examined whether respiratory variations of STI and DTI within radial arterial waveform are comparable to dynamic indices. During liver transplantation, digitally recorded BP waveform and stroke volume variation (SVV) were retrospectively analyzed. Beat-to-beat STI and DTI were extracted within each BP waveform, which were separated by dicrotic notch. Systolic time variation (STV) was calculated by the average of 3 consecutive respiratory cycles: [(STImax- STImin)/STImean]. Similar formula was used for diastolic time variation (DTV) and pulse pressure variation (PPV). Receiver operating characteristic analysis with area under the curve (AUC) was used to assess thresholds predictive of SVV ≥12% and PPV ≥12%. STV and DTV showed significant correlations with SVV (r= 0.78 and r= 0.67, respectively) and PPV (r= 0.69 and r= 0.69, respectively). Receiver operating characteristic curves demonstrated that STV ≥11% identified to predict SVV ≥12% with 85.7% sensitivity and 89.3% specificity (AUC = 0.935; P< .001). DTV ≥11% identified to predict SVV ≥12% with 71.4% sensitivity and 85.7% specificity (AUC = 0.829; P< .001). STV ≥12% and DTV ≥11% identified to predict PPV ≥12% with an AUC of 0.881 and 0.885, respectively. Respiratory variations of STI and DTI derived from radial arterial contour have a potential to predict hemodynamic response as a surrogate for SVV or PPV. Copyright © 2016 Elsevier Inc. All rights reserved.

Inflammation scores predict survival for hepatitis B virus-related hepatocellular carcinoma patients after transarterial chemoembolization

PubMed Central

Zhou, Dong-Sheng; Xu, Li; Luo, Yao-Ling; He, Feng-Ying; Huang, Jun-Ting; Zhang, Yao-Jun; Chen, Min-Shan

2015-01-01

AIM: To compare the prognostic ability of inflammation scores for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). METHODS: Data of 224 consecutive patients who underwent TACE for unresectable HBV-related HCC from September 2009 to November 2011 were retrieved from a prospective database. The association of inflammation scores with clinicopathologic variables and overall survival (OS) were analyzed, and receiver operating characteristic curves were generated, and the area under the curve (AUC) was calculated to evaluate the discriminatory ability of each inflammation score and staging system, including tumor-node-metastasis, Barcelona Clinic Liver Cancer, and Cancer of the Liver Italian Program (CLIP) scores. RESULTS: The median follow-up period was 390 d, the one-, two-, and three-year OS were 38.4%, 18.3%, and 11.1%, respectively, and the median OS was 390 d. The Glasgow Prognostic Score (GPS), modifed GPS, neutrophil-lymphocyte ratio, and Prognostic Index were associated with OS. The GPS consistently had a higher AUC value at 6 mo (0.702), 12 mo (0.676), and 24 mo (0.687) in comparison with other inflammation scores. CLIP consistently had a higher AUC value at 6 mo (0.656), 12 mo (0.711), and 24 mo (0.721) in comparison with tumor-node-metastasis and Barcelona Clinic Liver Cancer staging systems. Multivariate analysis revealed that alanine aminotransferase, GPS, and CLIP were independent prognostic factors for OS. The combination of GPS and CLIP (AUC = 0.777) was superior to CLIP or GPS alone in prognostic ability for OS. CONCLUSION: The prognostic ability of GPS is superior to other inflammation scores for HCC patients undergoing TACE. Combining GPS and CLIP improved the prognostic power for OS. PMID:25987783

Quality of life and discriminating power of two questionnaires in fibromyalgia patients: Fibromyalgia Impact Questionnaire and Medical Outcomes Study 36-Item Short-Form Health Survey.

PubMed

Assumpção, Ana; Pagano, Tatiana; Matsutani, Luciana A; Ferreira, Elizabeth A G; Pereira, Carlos A B; Marques, Amélia P

2010-01-01

Fibromyalgia is a painful syndrome characterized by widespread chronic pain and associated symptoms with a negative impact on quality of life. Considering the subjectivity of quality of life measurements, the aim of this study was to verify the discriminating power of two quality of life questionnaires in patients with fibromyalgia: the generic Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) and the specific Fibromyalgia Impact Questionnaire (FIQ). A cross-sectional study was conducted on 150 participants divided into Fibromyalgia Group (FG) and Control Group (CG) (n=75 in each group). The participants were evaluated using the SF-36 and the FIQ. The data were analyzed by the Student t-test (α=0.05) and inferential analysis using the Receiver Operating Characteristics (ROC) Curve--sensitivity, specificity and area under the curve (AUC). The significance level was 0.05. The sample was similar for age (CG: 47.8 ± 8.1; FG: 47.0 ± 7.7 years). A significant difference was observed in quality of life assessment in all aspects of both questionnaires (p<0.05). Higher sensibility, specificity and AUC were obtained by the FIQ (96%, 96%, 0.985, respectively), followed by the SF-36 (88%, 89% and 0.948 AUC). The FIQ presented the highest sensibility, specificity and AUC showing the most discriminating power. However the SF-36 is also a good instrument to assess quality of life in fibromyalgia patients, and we suggest that both should be used in parallel because they evaluate relevant and complementary aspects of quality of life.

Design and Validation of a Prehospital Scale to Predict Stroke Severity: The Cincinnati Prehospital Stroke Severity Scale

PubMed Central

Katz, Brian S.; McMullan, Jason T.; Sucharew, Heidi; Adeoye, Opeolu; Broderick, Joseph P.

2015-01-01

Background and Purpose We derived and validated the Cincinnati Prehospital Stroke Severity Scale (CPSSS) to identify patients with severe strokes and large vessel occlusion (LVO). Methods CPSSS was developed with regression tree analysis, objectivity, anticipated ease in administration by EMS personnel, and the presence of cortical signs. We derived and validated the tool using the two NINDS t-PA Stroke Study trials and IMS III Trial cohorts, respectively, to predict severe stroke [NIH stroke scale (NIHSS) ≥15] and LVO. Standard test characteristics were determined and receiver operator curves were generated and summarized by the area under the curve (AUC). Results CPSSS score ranges from 0-4; composed and scored by individual NIHSS items: 2 points for presence of conjugate gaze (NIHSS ≥1); 1 point for presence of arm weakness (NIHSS ≥2); and 1 point for presence abnormal level of consciousness (LOC) commands and questions (NIHSS LOC ≥1 each). In the derivation set, CPSSS had an AUC of 0.89; score ≥2 was 89% sensitive and 73% specific in identifying NIHSS ≥15. Validation results were similar with an AUC of 0.83; score ≥2 was 92% sensitive, 51% specific, a positive likelihood ratio (PLR) of 3.3 and a negative likelihood ratio (NLR) of 0.15 in predicting severe stroke. For 222/303 IMS III subjects with LVO, CPSSS had an AUC of 0.67; a score ≥2 was 83% sensitive, 40% specific, PLR of 1.4, and NLR of 0.4 in predicting LVO. Conclusions CPSSS can identify stroke patients with NIHSS ≥15 and LVO. Prospective prehospital validation is warranted. PMID:25899242

Elucidation of the pharmacokinetic/pharmacodynamic determinants of fosfomycin activity against Pseudomonas aeruginosa using a dynamic in vitro model.

PubMed

Bilal, Hajira; Peleg, Anton Y; McIntosh, Michelle P; Styles, Ian K; Hirsch, Elizabeth B; Landersdorfer, Cornelia B; Bergen, Phillip J

2018-06-01

To identify the fosfomycin pharmacokinetic (PK)/pharmacodynamic (PD) index (fT>MIC, fAUC/MIC or fCmax/MIC) most closely correlated with activity against Pseudomonas aeruginosa and determine the PK/PD target associated with various extents of bacterial killing and the prevention of emergence of resistance. Dose fractionation was conducted over 24 h in a dynamic one-compartment in vitro PK/PD model utilizing P. aeruginosa ATCC 27853 and two MDR clinical isolates (CR 1005 and CW 7). In total, 35 different dosing regimens were examined across the three strains. Microbiological response was examined by log changes and population analysis profiles. A Hill-type Emax model was fitted to the killing effect data (expressed as the log10 ratio of the area under the cfu/mL curve for treated regimens versus controls). Bacterial killing of no more than ∼3 log10 cfu/mL was achieved irrespective of regimen. The fAUC/MIC was the PK/PD index most closely correlated with efficacy (R2 = 0.80). The fAUC/MIC targets required to achieve 1 and 2 log10 reductions in the area under the cfu/mL curve relative to growth control were 489 and 1024, respectively. No regimen was able to suppress the emergence of resistance, and near-complete replacement of susceptible with resistant subpopulations occurred with virtually all regimens. Bacterial killing for fosfomycin against P. aeruginosa was most closely associated with the fAUC/MIC. Suppression of fosfomycin-resistant subpopulations could not be achieved even with fosfomycin exposures well above those that can be safely achieved clinically.

Can we improve the clinical utility of respiratory rate as a monitored vital sign?

PubMed

Chen, Liangyou; Reisner, Andrew T; Gribok, Andrei; McKenna, Thomas M; Reifman, Jaques

2009-06-01

Respiratory rate (RR) is a basic vital sign, measured and monitored throughout a wide spectrum of health care settings, although RR is historically difficult to measure in a reliable fashion. We explore an automated method that computes RR only during intervals of clean, regular, and consistent respiration and investigate its diagnostic use in a retrospective analysis of prehospital trauma casualties. At least 5 s of basic vital signs, including heart rate, RR, and systolic, diastolic, and mean arterial blood pressures, were continuously collected from 326 spontaneously breathing trauma casualties during helicopter transport to a level I trauma center. "Reliable" RR data were identified retrospectively using automated algorithms. The diagnostic performances of reliable versus standard RR were evaluated by calculation of the receiver operating characteristic curves using the maximum-likelihood method and comparison of the summary areas under the receiver operating characteristic curves (AUCs). Respiratory rate shows significant data-reliability differences. For identifying prehospital casualties who subsequently receive a respiratory intervention (hospital intubation or tube thoracotomy), standard RR yields an AUC of 0.59 (95% confidence interval, 0.48-0.69), whereas reliable RR yields an AUC of 0.67 (0.57-0.77), P < 0.05. For identifying casualties subsequently diagnosed with a major hemorrhagic injury and requiring blood transfusion, standard RR yields an AUC of 0.60 (0.49-0.70), whereas reliable RR yields 0.77 (0.67-0.85), P < 0.001. Reliable RR, as determined by an automated algorithm, is a useful parameter for the diagnosis of respiratory pathology and major hemorrhage in a trauma population. It may be a useful input to a wide variety of clinical scores and automated decision-support algorithms.

Sex differences in the prediction of the effectiveness of paroxetine for patients with major depressive disorder identified using a receiver operating characteristic curve analysis for early response.

PubMed

Tomita, Tetsu; Yasui-Furukori, Norio; Norio, Yasui-Furukori; Sato, Yasushi; Nakagami, Taku; Tsuchimine, Shoko; Kaneda, Ayako; Kaneko, Sunao

2014-01-01

We investigated cutoff values for the early response of patients with major depressive disorder to paroxetine and their sex differences by using a receiver operating characteristic (ROC) curve analysis to predict the effectiveness of paroxetine. In total, 120 patients with major depressive disorder were enrolled and treated with 10-40 mg/day paroxetine for 6 weeks; 89 patients completed the protocol. A clinical evaluation using the Montgomery-Asberg Depression Rating Scale (MADRS) was performed at weeks 0, 1, 2, 4, and 6. In male subjects, the cutoff values for MADRS improvement rating in week 1, week 2, and week 4 were 20.9%, 34.9%, and 33.3%, respectively. The sensitivities and the specificities were 83.3% and 80.0%, 83.3% and 80.0%, and 100% and 90%, respectively. The areas under the curve (AUC) were 0.908, 0.821, and 0.979, respectively. In female subjects, the cutoff values for the MADRS improvement rating in week 1, week 2, and week 4 were 21.4%, 35.7%, and 32.3%, respectively. The sensitivities and the specificities were 71.4% and 84.6%, 73.8% and 76.9%, and 90.5% and 76.9%, respectively. The AUCs were 0.781, 0.735, and 0.904, respectively. Early improvement with paroxetine may predict the long-term response. The accuracy of the prediction for the response is higher in male subjects.

Is being female a risk factor for shallow anterior chamber? The associations between anterior chamber depth and age, sex, and body height

PubMed Central

Hsu, Wei-Cherng; Shen, Elizabeth P; Hsieh, Yi-Ting

2014-01-01

Aim of Study: To analyze the association between anterior chamber depth (ACD) and age, sex, and body height (BH). Materials and Methods: One thousand four hundred eighty eyes of 1480 adults 40 years of age and older receiving preoperative evaluation for cataract surgery were recruited consecutively from June 1, 2006, to December 31, 2010. ACD was measured with the Zeiss IOLMaster. Univariate and multivariate linear regression models were used to analyze the correlations, and receiving operator characteristic (ROC) curves and the area under the curve (AUC) were used for evaluating the predictability of an ACD less than 2.70 mm. Results: ACD was negatively correlated with age and positively correlated with BH in both univariate and multivariate regression analysis (P < 0.001). Sex was associated with ACD in univariate analysis, but not after adjustment with age and BH. In predicting an ACD less than 2.70 mm, the AUCs of ROC curves for ‘age and sex’, ‘age and BH’, and ‘age, sex, and BH’ were 0.687, 0.689, and 0.689, respectively. Conclusion: Age and BH were independent associating factors of ACD; however, sex was not. Older people and shorter ones likely had shallower ACD, and therefore were predisposed to Primary angle closure glaucoma (PACG). The predictability of ACD by age and BH solely was low, and adding sex did not increase it. PMID:24145564

Can CT imaging features of ground-glass opacity predict invasiveness? A meta-analysis.

PubMed

Dai, Jian; Yu, Guoyou; Yu, Jianqiang

2018-04-01

A meta-analysis was conducted to investigate the diagnostic performance of computed tomography (CT) imaging features of ground-glass opacity (GGO) to predict invasiveness. Two reviewers independently searched PubMed, Medline, Web of Science, Cochrane Embase and CNKI for relevant studies. CT imaging signs of bubble lucency, speculation, lobulated margin, and pleural indentation were used as diagnostic references to discriminate pre-invasive and invasive disease. The sensitivity, specificity, diagnostic odds ratio (DOR), summary receiver operating characteristic (SROC) curves, and the area under the SROC curve (AUC) were calculated to evaluate diagnostic efficiency. Twelve studies were finally included. Diagnostic performance ranged from 0.41 to 0.52 for sensitivity and 0.56 to 0.63 for specificity. The diagnostic positive and negative likelihood ratios ranged from 1.03 to 2.13 and 0.52 to 1.05, respectively. The DORs of the GGO CT features for discriminating invasive disease ranged from 1.02 to 4.00. The area under the ROC curve was also low, with a range of 0.60 to 0.67 for discriminating pre-invasive and invasive disease. The diagnostic value of a single CT imaging sign of GGO, such as bubble lucency, speculation, lobulated margin, or pleural indentation is limited for discriminating pre-invasive and invasive disease because of low sensitivity, specificity, and AUC. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

The use of real-time optical feedback to improve outcomes

NASA Astrophysics Data System (ADS)

Magaña, Isidro B.; Adhikari, Pratik; Yendluri, Raghuvara B.; Goodrich, Glenn P.; Schwartz, Jon A.; O'Neal, D. P.

2014-03-01

More than a decade into the development of gold nanoparticles for cancer therapies, with multiple clinical trials underway, ongoing pre-clinical research continues towards better understanding in vivo interactions with the goal of treatment optimization through improved best practices. In an effort to collect information for healthcare providers, enabling informed decisions in a relevant time frame, instrumentation for real-time plasma concentration (multi-wavelength pulse photometry) and protocols for rapid elemental analysis (energy dispersive X-Ray fluorescence) of biopsied tumor tissue have been developed in a murine model. An initial analysis, designed to demonstrate the robust nature and utility of the techniques, revealed that area under the bioavailability curve (AUC) alone does not currently inform tumor accumulation with a high degree of accuracy (R2=0.32), This finding suggests that the control of additional experimental and physiological variables may yield more predictable tumor accumulation. Subject core temperature are blood pressure were monitored, but did not demonstrate clear trends. An effort to modulate AUC has produced an adjuvant therapy which is employed to enhance circulation parameters, including the AUC, of nanorods and gold nanoshells. Preliminary studies demonstrated a greater than 300% increase in average AUC through the use of a reticuloendothelial blockade agent versus control groups. Given a better understanding of the relative importance of the physiological factors which impact rates of tumor accumulation, a proposed set of experimental best practices is presented.

Waist-to-Height Ratio and Triglycerides/High-Density Lipoprotein Cholesterol Were the Optimal Predictors of Metabolic Syndrome in Uighur Men and Women in Xinjiang, China.

PubMed

Chen, Bang-Dang; Yang, Yi-Ning; Ma, Yi-Tong; Pan, Shuo; He, Chun-Hui; Liu, Fen; Ma, Xiang; Fu, Zhen-Yan; Li, Xiao-Mei; Xie, Xiang; Zheng, Ying-Ying

2015-06-01

This study aimed to identify the best single predictor of metabolic syndrome by comparing the predictive ability of various anthropometric and atherogenic parameters among a Uighur population in Xinjiang, northwest China. A total of 4767 Uighur participants were selected from the Cardiovascular Risk Survey (CRS), which was carried out from October, 2007, to March, 2010. Anthropometric data, blood pressure, serum concentration of serum total cholesterol (TC), triglycerides (TGs), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and fasting glucose were documented. Prevalence of metabolic syndrome and its individual components were confirmed according to International Diabetes Federation (IDF) criteria. Area under the receiver operating characteristic curve (AUC) of each variable for the presence of metabolic syndrome was compared. The sensitivity (Sen), specificity (Spe), distance in the receiver operating characteristic (ROC) curve, and cutoffs of each variable for the presence of metabolic syndrome were calculated. In all, 23.7% of men had the metabolic syndrome, whereas 40.1% of women had the metabolic syndrome in a Uighur population in Xinjiang; the prevalence of metabolic syndrome in women was significantly higher than that in men (P<0.001). In men, the waist-to-height ratio (WHtR) had the highest AUC value (AUC=0.838); it was followed by TGs/HDL-C (AUC=0.826), body mass index (BMI) (AUC=0.812), waist-to-hip ratio (WHR) (AUC=0.781), and body adiposity index (BAI) (AUC=0.709). In women, the TGs/HDL-C had the highest AUC value (AUC=0.815); it was followed by WHtR (AUC=0.780), WHR (AUC=0.730), BMI (AUC=0.719), and BAI (AUC=0.699). Similarly, among all five anthropometric and atherogenic parameters, the WHtR had the shortest ROC distance of 0.32 (Sen=85.40%, Spe=71.6%), and the optimal cutoff for WHtR was 0.55 in men. In women, TGs/HDL-C had the shortest ROC distance of 0.35 (Sen=75.29%, Spe=75.18%), and the optimal cutoff of TGs/HDL-C was 1.22. WHtR was the best predictor of metabolic syndrome in Uighur men, whereas TGs/HDL-C was the best predictor of metabolic syndrome in Uighur women in Xinjiang.

Power calculation for comparing diagnostic accuracies in a multi-reader, multi-test design.

PubMed

Kim, Eunhee; Zhang, Zheng; Wang, Youdan; Zeng, Donglin

2014-12-01

Receiver operating characteristic (ROC) analysis is widely used to evaluate the performance of diagnostic tests with continuous or ordinal responses. A popular study design for assessing the accuracy of diagnostic tests involves multiple readers interpreting multiple diagnostic test results, called the multi-reader, multi-test design. Although several different approaches to analyzing data from this design exist, few methods have discussed the sample size and power issues. In this article, we develop a power formula to compare the correlated areas under the ROC curves (AUC) in a multi-reader, multi-test design. We present a nonparametric approach to estimate and compare the correlated AUCs by extending DeLong et al.'s (1988, Biometrics 44, 837-845) approach. A power formula is derived based on the asymptotic distribution of the nonparametric AUCs. Simulation studies are conducted to demonstrate the performance of the proposed power formula and an example is provided to illustrate the proposed procedure. © 2014, The International Biometric Society.

Comparison of two correlated ROC curves at a given specificity or sensitivity level

PubMed Central

Bantis, Leonidas E.; Feng, Ziding

2017-01-01

The receiver operating characteristic (ROC) curve is the most popular statistical tool for evaluating the discriminatory capability of a given continuous biomarker. The need to compare two correlated ROC curves arises when individuals are measured with two biomarkers, which induces paired and thus correlated measurements. Many researchers have focused on comparing two correlated ROC curves in terms of the area under the curve (AUC), which summarizes the overall performance of the marker. However, particular values of specificity may be of interest. We focus on comparing two correlated ROC curves at a given specificity level. We propose parametric approaches, transformations to normality, and nonparametric kernel-based approaches. Our methods can be straightforwardly extended for inference in terms of ROC−1(t). This is of particular interest for comparing the accuracy of two correlated biomarkers at a given sensitivity level. Extensions also involve inference for the AUC and accommodating covariates. We evaluate the robustness of our techniques through simulations, compare to other known approaches and present a real data application involving prostate cancer screening. PMID:27324068

Computer-aided diagnosis in phase contrast imaging X-ray computed tomography for quantitative characterization of ex vivo human patellar cartilage.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismuller, Axel

2013-10-01

Visualization of ex vivo human patellar cartilage matrix through the phase contrast imaging X-ray computed tomography (PCI-CT) has been previously demonstrated. Such studies revealed osteoarthritis-induced changes to chondrocyte organization in the radial zone. This study investigates the application of texture analysis to characterizing such chondrocyte patterns in the presence and absence of osteoarthritic damage. Texture features derived from Minkowski functionals (MF) and gray-level co-occurrence matrices (GLCM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These texture features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). The best classification performance was observed with the MF features perimeter (AUC: 0.94 ±0.08 ) and "Euler characteristic" (AUC: 0.94 ±0.07 ), and GLCM-derived feature "Correlation" (AUC: 0.93 ±0.07). These results suggest that such texture features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix, enabling classification of cartilage as healthy or osteoarthritic with high accuracy.

New graphic AUC-based method to estimate overall survival benefit: pomalidomide reanalysis.

PubMed

Fenix-Caballero, S; Diaz-Navarro, J; Prieto-Callejero, B; Rios-Sanchez, E; Alegre-del Rey, E J; Borrero-Rubio, J M

2016-02-01

Difference in median survival is an erratic measure and sometimes does not provide a good assessment of survival benefit. The aim of this study was to reanalyse the overall survival benefit of pomalidomide from pivotal clinical trial using a new area under curve (AUC)-based method. In the pivotal trial, pomalidomide plus low-dose dexamethasone showed a significant survival benefit over high-dose dexamethasone, with a difference between medians of 4.6 months. The new AUC method applied to the survival curves, obtained an overall survival benefit of 2.6 months for the pomalidomide treatment. This average difference in OS was calculated for the 61.5% of patients for whom the time to event is reliable enough. This 2-month differential would have major clinical and pharmacoeconomic implications, on both cost-effectiveness studies and on the willingness of the healthcare systems to pay for this treatment. © 2015 John Wiley & Sons Ltd.

Comparison of the Absorption of Calcium Carbonate and Calcium Citrate after Roux-en-Y Gastric Bypass

PubMed Central

Tondapu, P.; Provost, D.; Adams-Huet, B.; Sims, T.; Chang, C.; Sakhaee, K.

2015-01-01

Introduction Roux-en-Y gastric bypass (RYGB) restricts food intake. Consequently, patients consume less calcium. In addition, food no longer passes through the duodenum, the main site of calcium absorption. Therefore, calcium absorption is significantly impaired. The goal of this study is to compare two common calcium supplements in gastric bypass patients. Method Nineteen patients were enrolled in a randomized, double-blinded, crossover study comparing the absorption of calcium from calcium carbonate and calcium citrate salts. Serum and urine calcium levels were assessed for peak values (Cmax) and cumulative calcium increment (area under the curve [AUC]). Serum PTH was assessed for minimum values (PTHmin) and cumulative PTH decrement (AUC). Statistical analysis was performed using a repeated analysis of variance model. Results Eighteen subjects completed the study. Calcium citrate resulted in a significantly higher serum Cmax (9.4+0.4 mg/dl vs. 9.2+0.3 mg/dl, p=0.02) and serum AUC (55+2 mg/dl vs. 54+2 mg/dl, p=0.02). Calcium citrate resulted in a significantly lower PTHmin (24+11 pg/ml vs. 30+13 pg/ml, p=0.01) and a higher AUC (−32+51 pg/ml vs. −3+56 pg/ml, p=0.04). There was a non-significant trend for higher urinary AUC in the calcium citrate group (76.13+36.39 mg/6 h vs. 66.04+40.82, p=0.17). Conclusion Calcium citrate has superior bioavailability than calcium carbonate in RYGB patients. PMID:19437082

Predictive ability of the ISS, NISS, and APACHE II score for SIRS and sepsis in polytrauma patients.

PubMed

Mica, L; Furrer, E; Keel, M; Trentz, O

2012-12-01

Systemic inflammatory response syndrome (SIRS) and sepsis as causes of multiple organ dysfunction syndrome (MODS) remain challenging to treat in polytrauma patients. In this study, the focus was set on widely used scoring systems to assess their diagnostic quality. A total of 512 patients (mean age: 39.2 ± 16.2, range: 16-88 years) who had an Injury Severity Score (ISS) ≥17 were included in this retrospective study. The patients were subdivided into four groups: no SIRS, slight SIRS, severe SIRS, and sepsis. The ISS, New Injury Severity Score (NISS), Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, and prothrombin time were collected at admission. The Kruskal-Wallis test and χ(2)-test, multinomial regression analysis, and kernel density estimates were performed. Receiver operating characteristic (ROC) analysis is reported as the area under the curve (AUC). Data were considered as significant if p < 0.05. All variables were significantly different in all groups (p < 0.001). The odds ratio increased with increasing SIRS severity for NISS (slight vs. no SIRS, 1.06, p = 0.07; severe vs. no SIRS, 1.07, p = 0.04; and sepsis vs. no SIRS, 1.11, p = 0.0028) and APACHE II score (slight vs. no SIRS, 0.97, p = 0.44; severe vs. no SIRS, 1.08, p = 0.02; and sepsis vs. no SIRS, 1.12, p = 0.0028). ROC analysis revealed that the NISS (slight vs. no SIRS, AUC 0.61; severe vs. no SIRS, AUC 0.67; and sepsis vs. no SIRS, AUC 0.77) and APACHE II score (slight vs. no SIRS, AUC 0.60; severe vs. no SIRS, AUC 0.74; and sepsis vs. no SIRS, AUC 0.82) had the best predictive ability for SIRS and sepsis. Quick assessment with the NISS or APACHE II score could preselect possible candidates for sepsis following polytrauma and provide guidance in trauma surgeons' decision-making.

Estimating systemic exposure to ethinyl estradiol from an oral contraceptive.

PubMed

Westhoff, Carolyn L; Pike, Malcolm C; Tang, Rosalind; DiNapoli, Marianne N; Sull, Monica; Cremers, Serge

2015-05-01

This study was conducted to compare single-dose pharmacokinetics of ethinyl estradiol in an oral contraceptive with steady-state values and to assess whether any simpler measures could provide an adequate proxy of the "gold standard" 24-hour steady-state area under the curve (AUC) value. Identification of a simple, less expensive measure of systemic ethinyl estradiol exposure would be useful for larger studies that are designed to assess the relationship between an individual's ethinyl estradiol exposure and side-effects. We collected 13 samples over 24 hours for pharmacokinetic analysis on days 1 and 21 of the first cycle of a monophasic oral contraceptive that contained 30 μg ethinyl estradiol and 150 μg levonorgestrel in 17 nonobese healthy white women. We also conducted an abbreviated single-dose 9-sample pharmacokinetic analysis after a month washout. Ethinyl estradiol was measured by liquid chromatography-tandem mass spectrometry. We compared results of a full 13-sample steady-state pharmacokinetic analysis with results that had been calculated with the use of fewer samples (9 or 5) and after the single doses. We calculated Pearson correlation coefficients to evaluate the relationships between these estimates of systemic ethinyl estradiol exposure. The AUC, maximum, and 24-hour values were similar after the 2 single oral contraceptive doses (AUC; r=0.92). The steady-state 13-sample 24-hour AUC value was correlated highly with the average 9-sample AUC value after the 2 single doses (r=0.81; P=.0002). This correlation remained the same if the number of single-dose samples was reduced to 4, taken at time 1, 2.5, 4, and 24 hours. The 24-hour value at steady-state was correlated highly with the 24-hour steady-state AUC value (r=0.92; P<.0001). The average of the 24-hour values after the 2 single doses was also correlated quite highly with the steady-state AUC value (r=0.72; P=.0026). Limited blood sampling, including results from 2 single doses, gave highly correlated estimates of an oral contraceptive user's steady-state ethinyl estradiol exposure. Copyright © 2015 Elsevier Inc. All rights reserved.

Lack of effect of lacosamide on the pharmacokinetic and pharmacodynamic profiles of warfarin.

PubMed

Stockis, Armel; van Lier, Jan Jaap; Cawello, Willi; Kumke, Thomas; Eckhardt, Klaus

2013-07-01

The aim of this study was to evaluate the effect of the antiepileptic drug lacosamide on the pharmacokinetics and pharmacodynamics of the anticoagulant warfarin. In this open-label, two-treatment crossover study, 16 healthy adult male volunteers were randomized to receive a single 25-mg dose of warfarin alone in one period and lacosamide 200 mg twice daily on days 1-9 with a single 25 mg dose of warfarin coadministered on day 3 in the other period. There was a 2-week washout between treatments. Pharmacokinetic end points were area under the plasma concentration-time curve (AUC(0,last) and AUC(0,∞) ) and maximum plasma concentration (Cmax ) for S- and R-warfarin. Pharmacodynamic end points were area under the international normalized ratio (INR)-time curve (AUCINR ), maximum INR (INRmax ), maximum prothrombin time (PTmax ) and area under the PT-time curve (AUCPT ). Following warfarin and lacosamide coadministration, Cmax and AUC of S- and R-warfarin, as well as peak value and AUC of PT and INR, were equivalent to those after warfarin alone. In particular, the AUC(0,∞) ratio (90% confidence interval) for coadministration of warfarin and lacosamide versus warfarin alone was 0.97 (0.94-1.00) for S-warfarin and 1.05 (1.02-1.09) for R-warfarin, and the AUCINR ratio was 1.04 (1.01-1.06). All participants completed the study. Coadministration of lacosamide 400 mg/day did not alter the pharmacokinetics of warfarin 25 mg or the anticoagulation level. These results suggest that there is no need for dose adjustment of warfarin when coadministered with lacosamide. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Combining Biomarkers Linearly and Nonlinearly for Classification Using the Area Under the ROC Curve

PubMed Central

Fong, Youyi; Yin, Shuxin; Huang, Ying

2016-01-01

In biomedical studies, it is often of interest to classify/predict a subject’s disease status based on a variety of biomarker measurements. A commonly used classification criterion is based on AUC - Area under the Receiver Operating Characteristic Curve. Many methods have been proposed to optimize approximated empirical AUC criteria, but there are two limitations to the existing methods. First, most methods are only designed to find the best linear combination of biomarkers, which may not perform well when there is strong nonlinearity in the data. Second, many existing linear combination methods use gradient-based algorithms to find the best marker combination, which often result in sub-optimal local solutions. In this paper, we address these two problems by proposing a new kernel-based AUC optimization method called Ramp AUC (RAUC). This method approximates the empirical AUC loss function with a ramp function, and finds the best combination by a difference of convex functions algorithm. We show that as a linear combination method, RAUC leads to a consistent and asymptotically normal estimator of the linear marker combination when the data is generated from a semiparametric generalized linear model, just as the Smoothed AUC method (SAUC). Through simulation studies and real data examples, we demonstrate that RAUC out-performs SAUC in finding the best linear marker combinations, and can successfully capture nonlinear pattern in the data to achieve better classification performance. We illustrate our method with a dataset from a recent HIV vaccine trial. PMID:27058981

Area Under the Curve as a Novel Metric of Behavioral Economic Demand for Alcohol

PubMed Central

Amlung, Michael; Yurasek, Ali; McCarty, Kayleigh N.; MacKillop, James; Murphy, James G.

2015-01-01

Behavioral economic purchase tasks can be readily used to assess demand for a number of addictive substances including alcohol, tobacco and illicit drugs. However, several methodological limitations associated with the techniques used to quantify demand may reduce the utility of demand measures. In the present study, we sought to introduce area under the curve (AUC), commonly used to quantify degree of delay discounting, as a novel index of demand. A sample of 207 heavy drinking college students completed a standard alcohol purchase task and provided information about typical weekly drinking patterns and alcohol-related problems. Level of alcohol demand was quantified using AUC – which reflects the entire amount of consumption across all drink prices - as well as the standard demand indices (e.g., intensity, breakpoint, Omax, Pmax, and elasticity). Results indicated that AUC was significantly correlated with each of the other demand indices (rs = .42–.92), with particularly strong associations with Omax (r = .92). In regression models, AUC and intensity were significant predictors of weekly drinking quantity and AUC uniquely predicted alcohol-related problems, even after controlling for drinking level. In a parallel set of analyses, Omax also predicted drinking quantity and alcohol problems, although Omax was not a unique predictor of the latter. These results offer initial support for using AUC as an index of alcohol demand. Additional research is necessary to further validate this approach and to examine its utility in quantifying demand for other addictive substances such as tobacco and illicit drugs. PMID:25895013

Comparison of Glasgow-Blatchford score and full Rockall score systems to predict clinical outcomes in patients with upper gastrointestinal bleeding.

PubMed

Mokhtare, Marjan; Bozorgi, Vida; Agah, Shahram; Nikkhah, Mehdi; Faghihi, Amirhossein; Boghratian, Amirhossein; Shalbaf, Neda; Khanlari, Abbas; Seifmanesh, Hamidreza

2016-01-01

Various risk scoring systems have been recently developed to predict clinical outcomes in patients with upper gastrointestinal bleeding (UGIB). The two commonly used scoring systems include full Rockall score (RS) and the Glasgow-Blatchford score (GBS). Bleeding scores were assessed in terms of prediction of clinical outcomes in patients with UGIB. Two hundred patients (age >18 years) with obvious symptoms of UGIB in the emergency department of Rasoul Akram Hospital were enrolled. Full RS and GBS were calculated. We followed the patients for records of rebleeding and 1-month mortality. A receiver operating characteristic curve by using areas under the curve (AUCs) was used to statistically identify the best cutoff point. Eighteen patients were excluded from the study due to failure to follow-up. Rebleeding and mortality rate were 9.34% (n=17) and 11.53% (n=21), respectively. Regarding 1-month mortality, full RS was better than GBS (AUC, 0.648 versus 0.582; P =0.021). GBS was more accurate in terms of detecting transfusion need (AUC, 0.757 versus 0.528; P =0.001), rebleeding rate (AUC, 0.722 versus 0.520; P =0.002), intensive care unit admission rate (AUC, 0.648 versus 0.582; P =0.021), and endoscopic intervention rate (AUC, 0.771 versus 0.650; P <0.001). We found the full RS system is better for 1-month mortality prediction while GBS system is better for prediction of other outcomes.

[Establishment of risk evaluation model of peritoneal metastasis in gastric cancer and its predictive value].

PubMed

Zhao, Junjie; Zhou, Rongjian; Zhang, Qi; Shu, Ping; Li, Haojie; Wang, Xuefei; Shen, Zhenbin; Liu, Fenglin; Chen, Weidong; Qin, Jing; Sun, Yihong

2017-01-25

To establish an evaluation model of peritoneal metastasis in gastric cancer, and to assess its clinical significance. Clinical and pathologic data of the consecutive cases of gastric cancer admitted between April 2015 and December 2015 in Department of General Surgery, Zhongshan Hospital of Fudan University were analyzed retrospectively. A total of 710 patients were enrolled in the study after 18 patients with other distant metastasis were excluded. The correlations between peritoneal metastasis and different factors were studied through univariate (Pearson's test or Fisher's exact test) and multivariate analyses (Binary Logistic regression). Independent predictable factors for peritoneal metastasis were combined to establish a risk evaluation model (nomogram). The nomogram was created with R software using the 'rms' package. In the nomogram, each factor had different scores, and every patient could have a total score by adding all the scores of each factor. A higher total score represented higher risk of peritoneal metastasis. Receiver operating characteristic (ROC) curve analysis was used to compare the sensitivity and specificity of the established nomogram. Delong. Delong. Clarke-Pearson test was used to compare the difference of the area under the curve (AUC). The cut-off value was determined by the AUC, when the ROC curve had the biggest AUC, the model had the best sensitivity and specificity. Among 710 patients, 47 patients had peritoneal metastasis (6.6%), including 30 male (30/506, 5.9%) and 17 female (17/204, 8.3%); 31 were ≥ 60 years old (31/429, 7.2%); 38 had tumor ≥ 3 cm(38/461, 8.2%). Lauren classification indicated that 2 patients were intestinal type(2/245, 0.8%), 8 patients were mixed type(8/208, 3.8%), 11 patients were diffuse type(11/142, 7.7%), and others had no associated data. CA19-9 of 13 patients was ≥ 37 kU/L(13/61, 21.3%); CA125 of 11 patients was ≥ 35 kU/L(11/36, 30.6%); CA72-4 of 11 patients was ≥ 10 kU/L(11/39, 28.2%). Neutrophil/lymphocyte ratio (NLR) of 26 patients was ≥ 2.37(26/231, 11.3%). Multivariate analysis showed that Lauren classification (HR=8.95, 95%CI:1.32-60.59, P=0.025), CA125(HR=17.45, 95%CI:5.54-54.89, P=0.001), CA72-4(HR=20.06, 95%CI:5.05-79.68, P=0.001), and NLR (HR=4.16, 95%CI:1.17-14.75, P=0.032) were independent risk factors of peritoneal metastasis in gastric cancer. In the nomogram, the highest score was 241, including diffuse or mixed Lauren classification (54 score), CA125 ≥ 35 kU/L (66 score), CA72-4 ≥ 10 kU/L (100 score), and NLR ≥ 2.37 (21 score), which represented a highest risk of peritoneal metastasis (more than 90%). The AUC of nomogram was 0.912, which was superior than any single variable (AUC of Lauren classification: 0.678; AUC of CA125: 0.720; AUC of CA72-4: 0.792; AUC of NLR: 0.613, all P=0.000). The total score of nomogram increased according to the TNM stage, and was highest in the peritoneal metastasis group (F=49.1, P=0.000). When the cut-off value calculated by ROC analysis was set at 140, the model could best balanced the sensitivity (0.79) and the specificity (0.87). Only 5% of patients had peritoneal metastasis when their nomogram scores were lower than 140, while 58% of patients had peritoneal metastasis when their scores were ≥ 140(χ 2 =69.1, P=0.000). The risk evaluation model established with Lauren classification, CA125, CA72-4 and NLR can effectively predict the risk of peritoneal metastasis in gastric cancer, and provide the reference to preoperative staging and choice of therapeutic strategy.

Peripheral Venous Waveform Analysis for Detecting Hemorrhage and Iatrogenic Volume Overload in a Porcine Model.

PubMed

Hocking, Kyle M; Sileshi, Ban; Baudenbacher, Franz J; Boyer, Richard B; Kohorst, Kelly L; Brophy, Colleen M; Eagle, Susan S

2016-10-01

Unrecognized hemorrhage and unguided resuscitation is associated with increased perioperative morbidity and mortality. The authors investigated peripheral venous waveform analysis (PIVA) as a method for quantitating hemorrhage as well as iatrogenic fluid overload during resuscitation. The authors conducted a prospective study on Yorkshire Pigs (n = 8) undergoing hemorrhage, autologous blood return, and administration of balanced crystalloid solution beyond euvolemia. Intra-arterial blood pressure, electrocardiogram, and pulse oximetry were applied to each subject. Peripheral venous pressure was measured continuously through an upper extremity standard peripheral IV catheter and analyzed with LabChart. The primary outcome was comparison of change in the first fundamental frequency (f1) of PIVA with standard and invasive monitoring and shock index (SI). Hemorrhage, return to euvolemia, and iatrogenic fluid overload resulted in significantly non-zero slopes of f1 amplitude. There were no significant differences in heart rate or mean arterial pressure, and a late change in SI. For the detection of hypovolemia the PIVA f1 amplitude change generated an receiver operator curves (ROC) curve with an area under the curve (AUC) of 0.93; heart rate AUC = 0.61; mean arterial pressure AUC = 0.48, and SI AUC = 0.72. For hypervolemia the f1 amplitude generated an ROC curve with an AUC of 0.85, heart rate AUC = 0.62, mean arterial pressure AUC = 0.63, and SI AUC = 0.65. In this study, PIVA demonstrated a greater sensitivity for detecting acute hemorrhage, return to euvolemia, and iatrogenic fluid overload compared with standard monitoring and SI. PIVA may provide a low-cost, minimally invasive monitoring solution for monitoring and resuscitating patients with perioperative hemorrhage.

Eigentumors for prediction of treatment failure in patients with early-stage breast cancer using dynamic contrast-enhanced MRI: a feasibility study

NASA Astrophysics Data System (ADS)

Chan, H. M.; van der Velden, B. H. M.; E Loo, C.; Gilhuijs, K. G. A.

2017-08-01

We present a radiomics model to discriminate between patients at low risk and those at high risk of treatment failure at long-term follow-up based on eigentumors: principal components computed from volumes encompassing tumors in washin and washout images of pre-treatment dynamic contrast-enhanced (DCE-) MR images. Eigentumors were computed from the images of 563 patients from the MARGINS study. Subsequently, a least absolute shrinkage selection operator (LASSO) selected candidates from the components that contained 90% of the variance of the data. The model for prediction of survival after treatment (median follow-up time 86 months) was based on logistic regression. Receiver operating characteristic (ROC) analysis was applied and area-under-the-curve (AUC) values were computed as measures of training and cross-validated performances. The discriminating potential of the model was confirmed using Kaplan-Meier survival curves and log-rank tests. From the 322 principal components that explained 90% of the variance of the data, the LASSO selected 28 components. The ROC curves of the model yielded AUC values of 0.88, 0.77 and 0.73, for the training, leave-one-out cross-validated and bootstrapped performances, respectively. The bootstrapped Kaplan-Meier survival curves confirmed significant separation for all tumors (P  <  0.0001). Survival analysis on immunohistochemical subgroups shows significant separation for the estrogen-receptor subtype tumors (P  <  0.0001) and the triple-negative subtype tumors (P  =  0.0039), but not for tumors of the HER2 subtype (P  =  0.41). The results of this retrospective study show the potential of early-stage pre-treatment eigentumors for use in prediction of treatment failure of breast cancer.

Relation of epicardial adipose tissue with arterial compliance and stiffness in patients with hypertension.

PubMed

Korkmaz, Levent; Cirakoglu, Omer Faruk; Ağaç, Mustafa Tarik; Erkan, Hakan; Korkmaz, Ayca Ata; Acar, Zeydin; Kul, Selim; Hatem, Engin; Çelik, Şükrü

2014-09-01

The main aim of the present study was to investigate the association between epicardial adipose tissue (EAT) and arterial function in patients with asymptomatic hypertension. Patients with hypertension (n = 155) were enrolled consecutively. Patients with decreased arterial compliance (AC) and increased cardioankle vascular index (CAVI) had higher EAT values compared with those with normal AC and CAVI (6.23 ± 1.67 vs 4.91 ± 1.40, P < .001 and 6.02 ± 1.61 vs 4.96 ± 1.46, P = .01, respectively). Analysis using the receiver-operating characteristics curve demonstrated that EAT 5.5 mm constitutes the cutoff value for the presence of increased CAVI with 67% sensitivity and 62% specificity (area under the curve [AUC]: 0.702, 95% confidence interval [CI] 0.590-0.814) and decreased AC with 77% sensitivity and 65% specificity (AUC: 0.756, 95% CI 0.645-0.867). Assessment of EAT during echocardiography examination may provide information on arterial function in patients with asymptomatic hypertension. The link between EAT and arterial stiffness deserves further investigation. © The Author(s) 2013.

The Long Exercise Test in Periodic Paralysis: A Bayesian Analysis.

PubMed

Simmons, Daniel B; Lanning, Julie; Cleland, James C; Puwanant, Araya; Twydell, Paul T; Griggs, Robert C; Tawil, Rabi; Logigian, Eric L

2018-05-12

The long exercise test (LET) is used to assess the diagnosis of periodic paralysis (PP), but LET methodology and normal "cut-off" values vary. To determine optimal LET methodology and cut-offs, we reviewed LET data (abductor digiti minimi (ADM) motor response amplitude, area) from 55 PP patients (32 genetically definite) and 125 controls. Receiver operating characteristic (ROC) curves were constructed and area-under-the-curve (AUC) calculated to compare 1) peak-to-nadir versus baseline-to-nadir methodologies, and 2) amplitude versus area decrements. Using Bayesian principles, optimal "cut-off" decrements that achieved 95% post-test probability of PP were calculated for various pre-test probabilities (PreTPs). AUC was highest for peak-to-nadir methodology and equal for amplitude and area decrements. For PreTP ≤50%, optimal decrement cut-offs (peak-to-nadir) were >40% (amplitude) or >50% (area). For confirmation of PP, our data endorse the diagnostic utility of peak-to-nadir LET methodology using 40% amplitude or 50% area decrement cut-offs for PreTPs ≤50%. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Impact of perioperative blood pressure variability on health resource utilization after cardiac surgery: an analysis of the ECLIPSE trials.

PubMed

Aronson, Solomon; Levy, Jerrold H; Lumb, Philip D; Fontes, Manuel; Wang, Yamei; Crothers, Tracy A; Sulham, Katherine A; Navetta, Marco S

2014-06-01

To examine the impact of blood pressure control on hospital health resource utilization using data from the ECLIPSE trials. Post-hoc analysis of data from 3 prospective, open-label, randomized clinical trials (ECLIPSE trials). Sixty-one medical centers in the United States. Patients 18 years or older undergoing cardiac surgery. Clevidipine was compared with nitroglycerin, sodium nitroprusside, and nicardipine. The ECLIPSE trials included 3 individual randomized open-label studies comparing clevidipine to nitroglycerin, sodium nitroprusside, and nicardipine. Blood pressure control was assessed as the integral of the cumulative area under the curve (AUC) outside specified systolic blood pressure ranges, such that lower AUC represents less variability. This analysis examined surgery duration, time to extubation, as well as intensive care unit (ICU) and hospital length of stay (LOS) in patients with AUC≤10 mmHg×min/h compared to patients with AUC>10 mmHg×min/h. One thousand four hundred ten patients were included for analysis; 736 patients (52%) had an AUC≤10 mmHg×min/h, and 674 (48%) had an AUC>10 mmHg×min/h. The duration of surgery and ICU LOS were similar between groups. Time to extubation and postoperative LOS were both significantly shorter (p = 0.05 and p<0.0001, respectively) in patients with AUC≤10. Multivariate analysis demonstrates AUC≤10 was significantly and independently associated with decreased time to extubation (hazard ratio 1.132, p = 0.0261) and postoperative LOS (hazard ratio 1.221, p = 0.0006). Based on data derived from the ECLIPSE studies, increased perioperative BP variability is associated with delayed time to extubation and increased postoperative LOS. Copyright © 2014 Elsevier Inc. All rights reserved.

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing.

PubMed

Van Hertem, T; Bahr, C; Schlageter Tello, A; Viazzi, S; Steensels, M; Romanini, C E B; Lokhorst, C; Maltz, E; Halachmi, I; Berckmans, D

2016-09-01

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

Validation of limited sampling strategy for the estimation of mycophenolic acid exposure in Chinese adult liver transplant recipients.

PubMed

Hao, Chen; Erzheng, Chen; Anwei, Mao; Zhicheng, Yu; Baiyong, Shen; Xiaxing, Deng; Weixia, Zhang; Chenghong, Peng; Hongwei, Li

2007-12-01

Mycophenolate mofetil (MMF) is indicated as immunosuppressive therapy in liver transplantation. The abbreviated models for the estimation of mycophenolic acid (MPA) area under the concentration-time curve (AUC) have been established by limited sampling strategies (LSSs) in adult liver transplant recipients. In the current study, the performance of the abbreviated models to predict MPA exposure was validated in an independent group of patients. A total of 30 MPA pharmacokinetic profiles from 30 liver transplant recipients receiving MMF in combination with tacrolimus were used to compare 8 models' performance with a full 10 time-point MPA-AUC. Linear regression analysis and Bland-Altman analysis were used to compare the estimated MPA-AUC0-12h from each model against the measured MPA-AUC0-12h. A wide range of agreement was shown when estimated MPA-AUC0-12h was compared with measured MPA-AUC0-12h, and the range of coefficient of determination (r2) was from 0.479 to 0.936. The model based on MPA pharmacokinetic parameters C1h, C2h, C6h, and C8h had the best ability to predict measured MPA-AUC0-12h, with the best coefficient of determination (r2=0.936), the excellent prediction bias (2.18%), the best prediction precision (5.11%), and the best prediction variation (2SD=+/-7.88 mg.h/L). However, the model based on MPA pharmacokinetic sampling time points C1h, C2h, and C4h was more suitable when concerned with clinical convenience, which had shorter sampling interval, an excellent coefficient of determination (r2=0.795), an excellent prediction bias (3.48%), an acceptable prediction precision (14.37%), and a good prediction variation (2SD=+/-13.23 mg.h/L). Measured MPA-AUC0-12h could be best predicted by using MPA pharmacokinetic parameters C1h, C2h, C6h, and C8h. The model based on MPA pharmacokinetic parameters C1h, C2h, and C4h was more feasible in clinical application. Copyright (c) 2007 AASLD.

Maximum a posteriori Bayesian estimation of mycophenolic Acid area under the concentration-time curve: is this clinically useful for dosage prediction yet?

PubMed

Staatz, Christine E; Tett, Susan E

2011-12-01

This review seeks to summarize the available data about Bayesian estimation of area under the plasma concentration-time curve (AUC) and dosage prediction for mycophenolic acid (MPA) and evaluate whether sufficient evidence is available for routine use of Bayesian dosage prediction in clinical practice. A literature search identified 14 studies that assessed the predictive performance of maximum a posteriori Bayesian estimation of MPA AUC and one report that retrospectively evaluated how closely dosage recommendations based on Bayesian forecasting achieved targeted MPA exposure. Studies to date have mostly been undertaken in renal transplant recipients, with limited investigation in patients treated with MPA for autoimmune disease or haematopoietic stem cell transplantation. All of these studies have involved use of the mycophenolate mofetil (MMF) formulation of MPA, rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation. Bias associated with estimation of MPA AUC using Bayesian forecasting was generally less than 10%. However some difficulties with imprecision was evident, with values ranging from 4% to 34% (based on estimation involving two or more concentration measurements). Evaluation of whether MPA dosing decisions based on Bayesian forecasting (by the free website service https://pharmaco.chu-limoges.fr) achieved target drug exposure has only been undertaken once. When MMF dosage recommendations were applied by clinicians, a higher proportion (72-80%) of subsequent estimated MPA AUC values were within the 30-60 mg · h/L target range, compared with when dosage recommendations were not followed (only 39-57% within target range). Such findings provide evidence that Bayesian dosage prediction is clinically useful for achieving target MPA AUC. This study, however, was retrospective and focussed only on adult renal transplant recipients. Furthermore, in this study, Bayesian-generated AUC estimations and dosage predictions were not compared with a later full measured AUC but rather with a further AUC estimate based on a second Bayesian analysis. This study also provided some evidence that a useful monitoring schedule for MPA AUC following adult renal transplant would be every 2 weeks during the first month post-transplant, every 1-3 months between months 1 and 12, and each year thereafter. It will be interesting to see further validations in different patient groups using the free website service. In summary, the predictive performance of Bayesian estimation of MPA, comparing estimated with measured AUC values, has been reported in several studies. However, the next step of predicting dosages based on these Bayesian-estimated AUCs, and prospectively determining how closely these predicted dosages give drug exposure matching targeted AUCs, remains largely unaddressed. Further prospective studies are required, particularly in non-renal transplant patients and with the EC-MPS formulation. Other important questions remain to be answered, such as: do Bayesian forecasting methods devised to date use the best population pharmacokinetic models or most accurate algorithms; are the methods simple to use for routine clinical practice; do the algorithms actually improve dosage estimations beyond empirical recommendations in all groups that receive MPA therapy; and, importantly, do the dosage predictions, when followed, improve patient health outcomes?

Investigating changes in resting-state connectivity from functional MRI data in patients with HIV associated neurocognitive disorder using MCA and machine learning

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Wismüller, Axel

2017-03-01

Infection of the brain by the Human Immunodeficiency Virus (HIV) causes irreversible damage to the synaptic connections resulting in cognitive impairment. Patients with HIV infection, showing signs of impairment in multiple cognitive domains, as assessed by neuropsychological testing, are said to exhibit symptoms of HIV Associated Neurocognitive Disorder (HAND). In this study, we use resting-state functional MRI (fMRI) data to distinguish between healthy subjects and subjects with symptoms of HAND. To this end, we first establish a measure of interaction between pairs of regional time-series by quantifying their non-linear functional connectivity using Mutual Connectivity Analysis (MCA). Subsequently, we use a classifier to distinguish patterns of interaction between healthy and diseased individuals. Our results, quantified as the mean Area under the ROC curve (AUC) over 75 iterations, indicate that, using fMRI data, we can discriminate between the two cohorts well (AUC > 0.8). Specifically, we find that MCA (mean AUC = 0.89) based connectivity features perform significantly better (p < 0.05) when compared to cross-correlation (mean AUC = 0.82) at the classification task. A higher AUC using our approach suggests that such a nonlinear approach is better able to capture connectivity changes between brain regions and has potential for the development of novel neuro-imaging biomarkers.

Limited sampling strategy models for estimating the AUC of gliclazide in Chinese healthy volunteers.

PubMed

Huang, Ji-Han; Wang, Kun; Huang, Xiao-Hui; He, Ying-Chun; Li, Lu-Jin; Sheng, Yu-Cheng; Yang, Juan; Zheng, Qing-Shan

2013-06-01

The aim of this work is to reduce the cost of required sampling for the estimation of the area under the gliclazide plasma concentration versus time curve within 60 h (AUC0-60t ). The limited sampling strategy (LSS) models were established and validated by the multiple regression model within 4 or fewer gliclazide concentration values. Absolute prediction error (APE), root of mean square error (RMSE) and visual prediction check were used as criterion. The results of Jack-Knife validation showed that 10 (25.0 %) of the 40 LSS based on the regression analysis were not within an APE of 15 % using one concentration-time point. 90.2, 91.5 and 92.4 % of the 40 LSS models were capable of prediction using 2, 3 and 4 points, respectively. Limited sampling strategies were developed and validated for estimating AUC0-60t of gliclazide. This study indicates that the implementation of an 80 mg dosage regimen enabled accurate predictions of AUC0-60t by the LSS model. This study shows that 12, 6, 4, 2 h after administration are the key sampling times. The combination of (12, 2 h), (12, 8, 2 h) or (12, 8, 4, 2 h) can be chosen as sampling hours for predicting AUC0-60t in practical application according to requirement.

Evaluation of carotid plaque echogenicity based on the integral of the cumulative probability distribution using gray-scale ultrasound images.

PubMed

Huang, Xiaowei; Zhang, Yanling; Meng, Long; Abbott, Derek; Qian, Ming; Wong, Kelvin K L; Zheng, Rongqing; Zheng, Hairong; Niu, Lili

2017-01-01

Carotid plaque echogenicity is associated with the risk of cardiovascular events. Gray-scale median (GSM) of the ultrasound image of carotid plaques has been widely used as an objective method for evaluation of plaque echogenicity in patients with atherosclerosis. We proposed a computer-aided method to evaluate plaque echogenicity and compared its efficiency with GSM. One hundred and twenty-five carotid plaques (43 echo-rich, 35 intermediate, 47 echolucent) were collected from 72 patients in this study. The cumulative probability distribution curves were obtained based on statistics of the pixels in the gray-level images of plaques. The area under the cumulative probability distribution curve (AUCPDC) was calculated as its integral value to evaluate plaque echogenicity. The classification accuracy for three types of plaques is 78.4% (kappa value, κ = 0.673), when the AUCPDC is used for classifier training, whereas GSM is 64.8% (κ = 0.460). The receiver operating characteristic curves were produced to test the effectiveness of AUCPDC and GSM for the identification of echolucent plaques. The area under the curve (AUC) was 0.817 when AUCPDC was used for training the classifier, which is higher than that achieved using GSM (AUC = 0.746). Compared with GSM, the AUCPDC showed a borderline association with coronary heart disease (Spearman r = 0.234, p = 0.050). Our experimental results suggest that AUCPDC analysis is a promising method for evaluation of plaque echogenicity and predicting cardiovascular events in patients with plaques.

Comparison of Glucose Area Under the Curve Measured Using Minimally Invasive Interstitial Fluid Extraction Technology with Continuous Glucose Monitoring System in Diabetic Patients

PubMed Central

Uemura, Mei; Suzuki, Toshinari; Yasuma, Taro; Sato, Toshiyuki; Morimoto, Aya; Hosoya, Samiko; Suminaka, Chihiro; Nakajima, Hiromu; Gabazza, Esteban C.; Takei, Yoshiyuki

2017-01-01

Background Continuous glucose monitoring (CGM) is reported to be a useful technique, but difficult or inconvenient for some patients and institutions. We are developing a glucose area under the curve (AUC) monitoring system without blood sampling using a minimally invasive interstitial fluid extraction technology (MIET). Here we evaluated the accuracy of interstitial fluid glucose (IG) AUC measured by MIET in patients with diabetes for an extended time interval and the potency of detecting hyperglycemia using CGM data as a reference. Methods Thirty-eight inpatients with diabetes undergoing CGM were enrolled. MIET comprised a pretreatment step using a plastic microneedle array and glucose accumulation step with a hydrogel patch, which was placed on two sites from 9:00 AM to 5:00 PM or from 10:00 PM to 6:00 AM. IG AUC was calculated by accumulated glucose extracted by hydrogel patches using sodium ion as standard. Results A significant correlation was observed between the predicted AUC by MIET and CGM in daytime (r=0.76) and nighttime (r=0.82). The optimal cutoff for the IG AUC value of MIET to predict hyperglycemia over 200 mg/dL measured by CGM for 8 hours was 1,067.3 mg·hr/dL with 88.2% sensitivity and 81.5% specificity. Conclusion We showed that 8-hour IG AUC levels using MIET were valuable in estimating the blood glucose AUC without blood sampling. The results also supported the concept of using this technique for evaluating glucose excursion and for screening hyperglycemia during 8 hours in patients with diabetes at any time of day. PMID:28868824

Comparison of Glucose Area Under the Curve Measured Using Minimally Invasive Interstitial Fluid Extraction Technology with Continuous Glucose Monitoring System in Diabetic Patients.

PubMed

Uemura, Mei; Yano, Yutaka; Suzuki, Toshinari; Yasuma, Taro; Sato, Toshiyuki; Morimoto, Aya; Hosoya, Samiko; Suminaka, Chihiro; Nakajima, Hiromu; Gabazza, Esteban C; Takei, Yoshiyuki

2017-08-01

Continuous glucose monitoring (CGM) is reported to be a useful technique, but difficult or inconvenient for some patients and institutions. We are developing a glucose area under the curve (AUC) monitoring system without blood sampling using a minimally invasive interstitial fluid extraction technology (MIET). Here we evaluated the accuracy of interstitial fluid glucose (IG) AUC measured by MIET in patients with diabetes for an extended time interval and the potency of detecting hyperglycemia using CGM data as a reference. Thirty-eight inpatients with diabetes undergoing CGM were enrolled. MIET comprised a pretreatment step using a plastic microneedle array and glucose accumulation step with a hydrogel patch, which was placed on two sites from 9:00 AM to 5:00 PM or from 10:00 PM to 6:00 AM. IG AUC was calculated by accumulated glucose extracted by hydrogel patches using sodium ion as standard. A significant correlation was observed between the predicted AUC by MIET and CGM in daytime (r=0.76) and nighttime (r=0.82). The optimal cutoff for the IG AUC value of MIET to predict hyperglycemia over 200 mg/dL measured by CGM for 8 hours was 1,067.3 mg·hr/dL with 88.2% sensitivity and 81.5% specificity. We showed that 8-hour IG AUC levels using MIET were valuable in estimating the blood glucose AUC without blood sampling. The results also supported the concept of using this technique for evaluating glucose excursion and for screening hyperglycemia during 8 hours in patients with diabetes at any time of day. Copyright © 2017 Korean Diabetes Association

Glucose-dependent leukocyte activation in patients with type 2 diabetes mellitus, familial combined hyperlipidemia and healthy controls.

PubMed

de Vries, Marijke A; Alipour, Arash; Klop, Boudewijn; van de Geijn, Gert-Jan M; Janssen, Hans W; Njo, Tjin L; van der Meulen, Noëlle; Rietveld, Arie P; Liem, Anho H; Westerman, Elsbeth M; de Herder, Wouter W; Cabezas, Manuel Castro

2015-02-01

Leukocyte activation has been associated with vascular complications in type 2 diabetes mellitus (T2DM). Hyperglycemia may be involved in this leukocyte activation. Our aim was to investigate the role of elevated glucose concentrations on leukocyte activation in patients with a wide range of insulin sensitivity. Leukocyte activation was determined after ingestion of 75 gram glucose in subjects with T2DM, familial combined hyperlipidemia (FCH) and healthy controls. Leukocyte activation markers were measured by flow cytometry. Postprandial changes were calculated as the area under the curve (AUC), and the incremental area under the curve corrected for baseline values (dAUC). 51 Subjects (20 T2DM, 17 FCH and 14 controls) were included. Fasting neutrophil CD66b expression and CD66b-AUC were respectively 36% and 39% higher in T2DM patients than in controls (p=0.004 and p=0.003). Fasting neutrophil CD66b expression correlated positively with glucose-AUC (Spearman's rho 0.481, p<0.001) and HbA1c (rho 0.433, p=0.002). Although fasting monocyte CD11b expression was not significantly different between subjects, monocyte CD11b-AUC was 26% higher in T2DM than in controls (p=0.006). Similar trends were observed for FCH patients. Monocyte CD11b-dAUC correlated positively with glucose-AUC (rho 0.322, p=0.022) and HbA1c (rho 0.319, p=0.023). These data suggest that both acute and chronic hyperglycemia, associated with insulin resistance as seen in T2DM and FCH, are involved in the increased fasting and postprandial leukocyte activation observed in these conditions. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparative pharmacodynamics of the new fluoroquinolone ABT492 and ciprofloxacin with Escherichia coli and Pseudomonas aeruginosa in an in vitro dynamic model.

PubMed

Zinner, Stephen H; Vostrov, Sergey N; Alferova, Irene V; Lubenko, Irene Yu; Portnoy, Yury A; Firsov, Alexander A

2004-08-01

The killing kinetics of Escherichia coli and Pseudomonas aeruginosa were compared when exposed to ABT492 and ciprofloxacin. E. coli ATCC 25922 and a clinical isolate of P. aeruginosa 4226 were exposed to ABT492 (single dose) and ciprofloxacin (two 12 h doses) at the ratios of area under the curve (AUC) to MIC varying from 60 to 480 h and at clinically achievable AUC/MIC ratios of ABT492 (1,740 and 140 h, respectively) and ciprofloxacin (2,200 and 120 h, respectively) that correspond to a 400 mg dose of ABT492 and two 500 mg doses of ciprofloxacin. In addition, a double dose of ABT492 (800 mg; AUC/MIC 280 h) and two 12 h doses of ABT492 (2 x 400 mg) were used with P. aeruginosa. Maximal reductions in the starting inoculum of E. coli and P. aeruginosa were greater with ABT492 than with ciprofloxacin at a given AUC/MIC ratio (60-480 h), whereas the times to regrowth were shorter with ABT492. A specific AUC/MIC relationship of the antimicrobial effect was inherent in each quinolone-pathogen pair. With both E. coli and P. aeruginosa, AUC/MIC plots of the area between the control growth and the time-kill curves (I(E)) were steeper for ciprofloxacin than ABT492 and they were species-independent. The effect of ABT492 on E. coli at the clinically achievable AUC/MIC ratio (1740h) was more pronounced than the respective AUC/MIC of ciprofloxacin (2,200 h). With P. aeruginosa, a 140 h AUC/MIC of ABT492 (400 mg as a single dose) provided 1.8-fold less effect than a 120 h AUC/MIC of ciprofloxacin (2 x 500 mg). However, two 12 h doses of ABT492 (AUC/MIC 2 x 140 h) but not a double single dose (800 mg) were more efficient than ciprofloxacin. These findings predict comparable efficacies of clinically achievable AUC/MICs of ABT492 and ciprofloxacin against E. coli (q.d. versus b.i.d. quinolone dosing) and P. aeruginosa at b.i.d. but not at q.d. ABT492.

Second-meal effects of pulses on blood glucose and subjective appetite following a standardized meal 2 h later.

PubMed

Mollard, Rebecca C; Wong, Christina L; Luhovyy, Bohdan L; Cho, France; Anderson, G Harvey

2014-07-01

This study investigated whether pulses (chickpeas, yellow peas, navy beans, lentils) have an effect on blood glucose (BG) and appetite following a fixed-size meal 2 h later. Over the following 2 h, all pulses lowered BG area under the curve (AUC) and lentils reduced appetite AUC compared with white bread (p < 0.05). Following the meal, BG was lower after lentils and chickpeas at 150 and 165 min, and AUC was lower after lentils compared with white bread (p < 0.05).

Peak Measurement for Vancomycin AUC Estimation in Obese Adults Improves Precision and Lowers Bias.

PubMed

Pai, Manjunath P; Hong, Joseph; Krop, Lynne

2017-04-01

Vancomycin area under the curve (AUC) estimates may be skewed in obese adults due to weight-dependent pharmacokinetic parameters. We demonstrate that peak and trough measurements reduce bias and improve the precision of vancomycin AUC estimates in obese adults ( n = 75) and validate this in an independent cohort ( n = 31). The precision and mean percent bias of Bayesian vancomycin AUC estimates are comparable between covariate-dependent ( R 2 = 0.774, 3.55%) and covariate-independent ( R 2 = 0.804, 3.28%) models when peaks and troughs are measured but not when measurements are restricted to troughs only ( R 2 = 0.557, 15.5%). Copyright © 2017 American Society for Microbiology.

Construction of a pathological risk model of occult lymph node metastases for prognostication by semi-automated image analysis of tumor budding in early-stage oral squamous cell carcinoma

PubMed Central

Pedersen, Nicklas Juel; Jensen, David Hebbelstrup; Lelkaitis, Giedrius; Kiss, Katalin; Charabi, Birgitte; Specht, Lena; von Buchwald, Christian

2017-01-01

It is challenging to identify at diagnosis those patients with early oral squamous cell carcinoma (OSCC), who have a poor prognosis and those that have a high risk of harboring occult lymph node metastases. The aim of this study was to develop a standardized and objective digital scoring method to evaluate the predictive value of tumor budding. We developed a semi-automated image-analysis algorithm, Digital Tumor Bud Count (DTBC), to evaluate tumor budding. The algorithm was tested in 222 consecutive patients with early-stage OSCC and major endpoints were overall (OS) and progression free survival (PFS). We subsequently constructed and cross-validated a binary logistic regression model and evaluated its clinical utility by decision curve analysis. A high DTBC was an independent predictor of both poor OS and PFS in a multivariate Cox regression model. The logistic regression model was able to identify patients with occult lymph node metastases with an area under the curve (AUC) of 0.83 (95% CI: 0.78–0.89, P <0.001) and a 10-fold cross-validated AUC of 0.79. Compared to other known histopathological risk factors, the DTBC had a higher diagnostic accuracy. The proposed, novel risk model could be used as a guide to identify patients who would benefit from an up-front neck dissection. PMID:28212555

Perioperative hemoglobin area under the curve is an independent predictor of renal failure after cardiac surgery. Results from a Spanish multicenter retrospective cohort study

PubMed Central

Duque-Sosa, Paula; Iribarren, María Josefa; Rábago, Gregorio

2017-01-01

Perioperative anemia is an important risk factor for cardiac surgery-associated acute kidney injury (CSA-AKI). Nonetheless, the severity of the anemia and the time in the perioperative period in which the hemoglobin level should be considered as a risk factor is conflicting. The present study introduces the concept of perioperative hemoglobin area under the curve (pHb-AUC) as a surrogate marker of the evolution of perioperative hemoglobin concentration. Through a retrospective analysis of prospectively collected data, we assessed this new variable as a risk factor for the development of acute kidney injury after cardiac surgery in 966 adult patients who underwent cardiac surgery with cardiopulmonary bypass, at twenty-three academic hospitals in Spain. Exclusion criteria were patients on renal replacement therapy, who needed a reoperation because of bleeding and/or with missing perioperative hemoglobin or creatinine values. Using a multivariate regression analysis, we found that a pHb-AUC <19 g/dL was an independent risk factor for CSA-AKI even after adjustment for intraoperative red blood cell transfusion (OR 1.41, p <0.05). It was also associated with mortality (OR 2.48, p <0.01) and prolonged hospital length of stay (4.67 ± 0.99 days, p <0.001) PMID:28225801

Accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue.

PubMed

Zhang, Jing; Fan, Yimeng; He, Min; Ma, Xuelei; Song, Yanlin; Liu, Ming; Xu, Jianguo

2017-05-30

Raman spectroscopy could be applied to distinguish tumor from normal tissues. This meta-analysis was conducted to assess the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. PubMed and Embase were searched to identify suitable studies prior to Jan 1st, 2016. We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (LR), diagnostic odds ratio (DOR), and constructed summary receiver operating characteristics (SROC) curves to identity the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. A total of six studies with 1951 spectra were included. For glioma, the pooled sensitivity and specificity of Raman spectroscopy were 0.96 (95% CI 0.94-0.97) and 0.99 (95% CI 0.98-0.99), respectively. The area under the curve (AUC) was 0.9831. For meningioma, the pooled sensitivity and specificity were 0.98 (95% CI 0.94-1.00) and 1.00 (95% CI 0.98-1.00), respectively. The AUC was 0.9955. This meta-analysis suggested that Raman spectroscopy could be an effective and accurate tool for differentiating glioma and meningioma from normal brain tissue, which would help us both avoid removal of normal tissue and minimize the volume of residual tumor.

Clinical value of serum anti-mullerian hormone and inhibin B in prediction of ovarian response in patients with polycystic ovary syndrome.

PubMed

Zhang, Fan; Liu, Xiao-Ling; Rong, Nan; Huang, Xiao-Wen

2017-02-01

The present study aimed to investigate the clinical value of serum anti-mullerian hormone (AMH) and inhibin B (INHB) in predicting the ovarian response of patients with polycystic ovary syndrome (PCOS). A total of 120 PCOS patients were enrolled and divided into three groups in terms of the ovarian response: a low-response group (n=36), a normal-response group (n=44), and a high-response group (n=40). The serum AMH and INHB levels were measured by enzyme-linked immunosorbent assay (ELISA). The follicle stimulating hormone (FSH), luteinizing hormone (LH), and estradiol (E2) levels were determined by chemiluminescence microparticle immunoassay. The correlation of the serum AMH and INHB levels with other indicators was analyzed. A receiver operating characteristic (ROC) curve was established to analyze the prediction of ovarian response by AMH and INHB. The results showed that there were significant differences in age, body mass index (BMI), FSH, total gonadotropin-releasing hormone (GnRH), LH, E2, and antral follicle counts (AFCs) between the groups (P<0.05). The serum AMH and INHB levels were increased significantly with the ovarian response of PCOS patients increasing (P<0.05). The serum AMH and INHB levels were negatively correlated with the age, BMI, FSH level, Gn, and E2 levels (P<0.05). They were positively correlated with the LH levels and AFCs (P<0.05). ROC curve analysis of serum AMH and INHB in prediction of a low ovarian response showed that the area under the ROC curve (AUC) value of the serum AMH level was 0.817, with a cut-off value of 1.29 ng/mL. The sensitivity and specificity were 71.2% and 79.6%, respectively. The AUC value of serum INHB was 0.674, with a cut-off value of 38.65 ng/mL, and the sensitivity and specificity were 50.7% and 74.5%, respectively. ROC curve analysis showed when the serum AMH and INHB levels were used to predict a high ovarian response, the AUC value of the serum AMH level was 0.742, with a cut-off value of 2.84 ng/mL, and the sensitivity and specificity were 72.7% and 65.9%, respectively; the AUC value of the serum INHB level was 0.551 with a cut-off of 45.76 ng/mL, and the sensitivity and specificity were 76.3% and 40.2%, respectively. It was suggested the serum AMH and INHB levels have high clinical value in predicting the ovarian response of PCOS patients.

Meta-analysis of stratus OCT glaucoma diagnostic accuracy.

PubMed

Chen, Hsin-Yi; Chang, Yue-Cune

2014-09-01

To evaluate the diagnostic accuracy of glaucoma in different stages, different types of glaucoma, and different ethnic groups using Stratus optical coherence tomography (OCT). We searched MEDLINE to identify available articles on diagnostic accuracy of glaucoma published between January 2004 and December 2011. A PubMed (National Center for Biotechnology Information) search using medical subject headings and keywords was executed using the following terms: "diagnostic accuracy" or "receiver operator characteristic" or "area under curve" or "AUC" and "Stratus OCT" and "glaucoma." The search was subsequently limited to publications in English. The area under a receiver operator characteristic (AUC) curve was used to measure the diagnostic performance. A random-effects model was used to estimate the pooled AUC value of the 17 parameters (average retinal nerve fiber layer thickness, temporal quadrant, superior quadrant, nasal quadrant, inferior quadrant, and 1 to 12 o'clock). Meta-regression analysis was used to check the significance of some important factors: (1) glaucoma severity (five stages), (2) glaucoma types (four types), and (3) ethnicity (four categories). The orders of accuracy among those parameters were as follows: average > inferior > superior > 7 o'clock > 6 o'clock > 11 o'clock > 12 o'clock > 1 o'clock > 5 o'clock > nasal > temporal > 2 o'clock > 10 o'clock > 8 o'clock > 9 o'clock > 4 o'clock > 3 o'clock. After adjusting for the effects of age, glaucoma severity, glaucoma types, and ethnicity, the average retinal nerve fiber layer thickness provided highest accuracy compared with the other parameters of OCT. The diagnostic accuracy in Asian populations was significantly lower than that in whites and the other two ethnic types. Stratus OCT demonstrated good diagnostic capability in differentiating glaucomatous from normal eyes. However, we should be more cautious in applying this instrument in Asian groups in glaucoma management.

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women

NASA Astrophysics Data System (ADS)

Daye, Dania; Bobo, Ezra; Baumann, Bethany; Ioannou, Antonios; Conant, Emily F.; Maidment, Andrew D. A.; Kontos, Despina

2011-03-01

Mammographic parenchymal texture patterns have been shown to be related to breast cancer risk. Yet, little is known about the biological basis underlying this association. Here, we investigate the potential of mammographic parenchymal texture patterns as an inherent phenotypic imaging marker of endogenous hormonal exposure of the breast tissue. Digital mammographic (DM) images in the cranio-caudal (CC) view of the unaffected breast from 138 women diagnosed with unilateral breast cancer were retrospectively analyzed. Menopause status was used as a surrogate marker of endogenous hormonal activity. Retroareolar 2.5cm2 ROIs were segmented from the post-processed DM images using an automated algorithm. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, grey-level spatial correlation, and fractal dimension were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance in distinguishing between 72 pre- and 66 post-menopausal women. Logistic regression was performed to assess the independent effect of each texture feature in predicting menopause status. ROC analysis showed that texture features have inherent capacity to distinguish between pre- and post-menopausal statuses (AUC>0.5, p<0.05). Logistic regression including all texture features yielded an ROC curve with an AUC of 0.76. Addition of age at menarche, ethnicity, contraception use and hormonal replacement therapy (HRT) use lead to a modest model improvement (AUC=0.78) while texture features maintained significant contribution (p<0.05). The observed differences in parenchymal texture features between pre- and post- menopausal women suggest that mammographic texture can potentially serve as a surrogate imaging marker of endogenous hormonal activity.

Diagnostic Value of Selected Echocardiographic Variables to Identify Pulmonary Hypertension in Dogs with Myxomatous Mitral Valve Disease.

PubMed

Tidholm, A; Höglund, K; Häggström, J; Ljungvall, I

2015-01-01

Pulmonary hypertension (PH) is commonly associated with myxomatous mitral valve disease (MMVD). Because dogs with PH present without measureable tricuspid regurgitation (TR), it would be useful to investigate echocardiographic variables that can identify PH. To investigate associations between estimated systolic TR pressure gradient (TRPG) and dog characteristics and selected echocardiographic variables. 156 privately owned dogs. Prospective observational study comparing the estimations of TRPG with dog characteristics and selected echocardiographic variables in dogs with MMVD and measureable TR. Tricuspid regurgitation pressure gradient was significantly (P < .05) associated with body weight corrected right (RVIDDn) and left (LVIDDn) ventricular end-diastolic and systolic (LVIDSn) internal diameters, pulmonary arterial (PA) acceleration to deceleration time ratio (AT/DT), heart rate, left atrial to aortic root ratio (LA/Ao), and the presence of congestive heart failure. Four variables remained significant in the multiple regression analysis with TRPG as a dependent variable: modeled as linear variables LA/Ao (P < .0001) and RVIDDn (P = .041), modeled as second order polynomial variables: AT/DT (P = .0039) and LVIDDn (P < .0001) The adjusted R(2) -value for the final model was 0.45 and receiver operating characteristic curve analysis suggested the model's performance to predict PH, defined as 36, 45, and 55 mmHg as fair (area under the curve [AUC] = 0.80), good (AUC = 0.86), and excellent (AUC = 0.92), respectively. In dogs with MMVD, the presence of PH might be suspected with the combination of decreased PA AT/DT, increased RVIDDn and LA/Ao, and a small or great LVIDDn. Copyright © 2015 The Authors Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Comparison of Photo Optical Imaging with Musculoskeletal Ultrasound and Clinical Examination in the Assessment of Inflammatory Activity in Proximal Interphalangeal Joints in Rheumatoid Arthritis and Osteoarthritis.

PubMed

Amitai, Isabella; Werner, Stephanie; Schicke, Bernd; Burmester, Gerd-Rüdiger; Minet, Olaf; Zabaryło, Urszula; Backhaus, Marina; Ohrndorf, Sarah

2015-09-01

Lightscan is a novel, rapid, low-cost, easily operated and noninvasive imaging technology used to assess inflammatory activity in proximal interphalangeal (PIP) joints. The results are calculated automatically. To our knowledge, this is the first comparative study of photo optical imaging (POI), with clinical examination (CE), disease activity score at 28 joints (DAS28)-erythrocyte sedimentation rate (ESR), and musculoskeletal ultrasonography (US) in healthy subjects and patients with rheumatoid arthritis (RA) or osteoarthritis (OA). There were 688 PIP joints of both hands examined in 87 subjects (38 RA, 21 OA, 28 healthy) by Lightscan and compared with CE for clinically swollen and tender joints, DAS28-ESR (only RA), and US. With US as reference, POI had a sensitivity of 74% and a specificity of 93%. In the receiver-operating curve (ROC) analysis, the Lightscan showed a higher sensitivity and specificity [area under the curve (AUC) 0.879] for the distinction of healthy subjects versus patients (OA, RA) than US in greyscale (GSUS; AUC 0.797) and power Doppler (PDUS; AUC 0.67). POI correlated significantly with GSUS (r 0.473, p < 0.01) and PDUS (r 0.486, p < 0.01). The agreement rates between POI and GSUS were up to 79%, between POI and PDUS up to 92%, and between POI and CE up to 66%. POI did not correlate with DAS28-ESR. The Lightscan is a new technology offering sensitive imaging detection of inflammatory changes in subjects with RA and OA with PIP arthritis. POI was more sensitive than CE and correlated significantly to GSUS and PDUS, while presenting a higher sensitivity and specificity for the detection of healthy subjects versus patients (RA, OA) based on the ROC analysis.

Establishment of a mathematic model for predicting malignancy in solitary pulmonary nodules.

PubMed

Zhang, Man; Zhuo, Na; Guo, Zhanlin; Zhang, Xingguang; Liang, Wenhua; Zhao, Sheng; He, Jianxing

2015-10-01

The aim of this study was to establish a model for predicting the probability of malignancy in solitary pulmonary nodules (SPNs) and provide guidance for the diagnosis and follow-up intervention of SPNs. We retrospectively analyzed the clinical data and computed tomography (CT) images of 294 patients with a clear pathological diagnosis of SPN. Multivariate logistic regression analysis was used to screen independent predictors of the probability of malignancy in the SPN and to establish a model for predicting malignancy in SPNs. Then, another 120 SPN patients who did not participate in the model establishment were chosen as group B and used to verify the accuracy of the prediction model. Multivariate logistic regression analysis showed that there were significant differences in age, smoking history, maximum diameter of nodules, spiculation, clear borders, and Cyfra21-1 levels between subgroups with benign and malignant SPNs (P<0.05). These factors were identified as independent predictors of malignancy in SPNs. The area under the curve (AUC) was 0.910 [95% confidence interval (CI), 0.857-0.963] in model with Cyfra21-1 significantly better than 0.812 (95% CI, 0.763-0.861) in model without Cyfra21-1 (P=0.008). The area under receiver operating characteristic (ROC) curve of our model is significantly higher than the Mayo model, VA model and Peking University People's (PKUPH) model. Our model (AUC =0.910) compared with Brock model (AUC =0.878, P=0.350), the difference was not statistically significant. The model added Cyfra21-1 could improve prediction. The prediction model established in this study can be used to assess the probability of malignancy in SPNs, thereby providing help for the diagnosis of SPNs and the selection of follow-up interventions.

AucPR: an AUC-based approach using penalized regression for disease prediction with high-dimensional omics data.

PubMed

Yu, Wenbao; Park, Taesung

2014-01-01

It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. We propose an AUC-based approach using penalized regression (AucPR), which is a parametric method used for obtaining a linear combination for maximizing the AUC. To obtain the AUC maximizer in a high-dimensional context, we transform a classical parametric AUC maximizer, which is used in a low-dimensional context, into a regression framework and thus, apply the penalization regression approach directly. Two kinds of penalization, lasso and elastic net, are considered. The parametric approach can avoid some of the difficulties of a conventional non-parametric AUC-based approach, such as the lack of an appropriate concave objective function and a prudent choice of the smoothing parameter. We apply the proposed AucPR for gene selection and classification using four real microarray and synthetic data. Through numerical studies, AucPR is shown to perform better than the penalized logistic regression and the nonparametric AUC-based method, in the sense of AUC and sensitivity for a given specificity, particularly when there are many correlated genes. We propose a powerful parametric and easily-implementable linear classifier AucPR, for gene selection and disease prediction for high-dimensional data. AucPR is recommended for its good prediction performance. Beside gene expression microarray data, AucPR can be applied to other types of high-dimensional omics data, such as miRNA and protein data.

Screening of hearing in elderly people: assessment of accuracy and reproducibility of the whispered voice test.

PubMed

Labanca, Ludimila; Guimarães, Fernando Sales; Costa-Guarisco, Letícia Pimenta; Couto, Erica de Araújo Brandão; Gonçalves, Denise Utsch

2017-11-01

Given the high prevalence of presbycusis and its detrimental effect on quality of life, screening tests can be useful tools for detecting hearing loss in primary care settings. This study therefore aimed to determine the accuracy and reproducibility of the whispered voice test as a screening method for detecting hearing impairment in older people. This cross-sectional study was carried out with 210 older adults aged between 60 and 97 years who underwent the whispered voice test employing ten different phrases and using audiometry as a reference test. Sensitivity, specificity and positive and negative predictive values were calculated and accuracy was measured by calculating the area under the ROC curve. The test was repeated on 20% of the ears by a second examiner to assess inter-examiner reproducibility (IER). The words and phrases that showed the highest area under the curve (AUC) and IER values were: "shoe" (AUC = 0.918; IER = 0.877), "window" (AUC = 0.917; IER = 0.869), "it looks like it's going to rain" (AUC = 0.911; IER = 0.810), and "the bus is late" (AUC = 0.900; IER = 0.810), demonstrating that the whispered voice test is a useful screening tool for detecting hearing loss among older people. It is proposed that these words and phrases should be incorporated into the whispered voice test protocol.

Predictive Validity of the HKT-R Risk Assessment Tool: Two and 5-Year Violent Recidivism in a Nationwide Sample of Dutch Forensic Psychiatric Patients.

PubMed

Bogaerts, Stefan; Spreen, Marinus; Ter Horst, Paul; Gerlsma, Coby

2018-06-01

This study has examined the predictive validity of the Historical Clinical Future [ Historisch Klinisch Toekomst] Revised risk assessment scheme in a cohort of 347 forensic psychiatric patients, which were discharged between 2004 and 2008 from any of 12 highly secure forensic centers in the Netherlands. Predictive validity was measured 2 and 5 years after release. Official reconviction data obtained from the Dutch Ministry of Security and Justice were used as outcome measures. Violent reoffending within 2 and 5 years after discharge was assessed. With regard to violent reoffending, results indicated that the predictive validity of the Historical domain was modest for 2 (area under the curve [AUC] = .75) and 5 (AUC = .74) years. The predictive validity of the Clinical domain was marginal for 2 (admission: AUC = .62; discharge: AUC = .63) and 5 (admission: AUC = .69; discharge: AUC = .62) years after release. The predictive validity of the Future domain was modest (AUC = .71) for 2 years and low for 5 (AUC = .58) years. The total score of the instrument was modest for 2 years (AUC = .78) and marginal for 5 (AUC = .68) years. Finally, the Final Risk Judgment was modest for 2 years (AUC = .78) and marginal for 5 (AUC = .63) years time at risk. It is concluded that this risk assessment instrument appears to be a satisfactory instrument for risk assessment.

Effects of non-nutritive (artificial vs natural) sweeteners on 24-h glucose profiles.

PubMed

Tey, S L; Salleh, N B; Henry, C J; Forde, C G

2017-09-01

Replacing nutritive sweetener with non-nutritive sweeteners (NNS) has the potential to improve glycaemic control. The objective of this study was to investigate the effects of consuming artificial NNS (that is, aspartame), natural NNS (that is, monk fruit and stevia), and sucrose-sweetened beverages on 24-h glucose profiles. Ten healthy males took part in this randomised, crossover study with the following four treatments: aspartame-, monk fruit-, stevia-, and sucrose- (65 g) sweetened beverages. Participants were asked to consume the test beverage as a preload mid-morning. Medtronic iPro2 continuous glucose monitoring system was used to measure mean 24-h glucose, incremental area under the curve (iAUC) and total area under the curve (AUC) for glucose, and 24-h glycaemic variability. Overall no significant differences were found in mean 24-h glucose, iAUC and total AUC for glucose, and 24-h glycaemic variability between the four test beverages. Twenty-four-hour glucose profiles did not differ between beverages sweetened with non-nutritive (artificial vs natural) and nutritive sweeteners. The simple exchange of a single serving of sucrose-sweetened beverage with NNS over a day appears to have minimal effect on 24-h glucose profiles in healthy males.

Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study)123

PubMed Central

Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

2015-01-01

Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve’s capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Results: Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). Conclusions: The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. The POUNDS Lost study was registered at clinicaltrials.gov as NCT00072995. PMID:25733628

Similar associations of total adiponectin and high molecular weight adiponectin with cardio-metabolic risk factors in a population of overweight and obese postmenopausal women: a MONET study.

PubMed

Elisha, B; Ziai, S; Karelis, A D; Rakel, A; Coderre, L; Imbeault, P; Rabasa-Lhoret, R

2010-07-01

The aim of the study was to examine the association between total adiponectin and high molecular weight (HMW) adiponectin levels with cardio-metabolic risk factors in a population of sedentary, overweight, and obese postmenopausal women. Cross-sectional study was carried out on 55 nondiabetic sedentary overweight and obese postmenopausal women aged between 50 and 70 years. Insulin sensitivity was assessed by euglycemic-hyperinsulinemic clamp technique. Body composition and visceral fat were measured using dual X-ray absorptiometry and computed tomography, respectively. Other cardio-metabolic risk factors included: plasma lipids, hsC-reactive protein, energy expenditure (doubly labeled water), peak oxygen consumption, muscle strength (using weight training equipment) as well as total and HMW adiponectin. Correlations of total and HMW adiponectin with various cardio-metabolic risk factors were comparable. In addition, regression analysis results showed similar independent predictors of total and HMW adiponectin. Finally, the receiver operator characteristic (ROC) curves for total and HMW adiponectin to predict insulin sensitivity showed no difference between the areas under curve (AUC) (AUC total adiponectin=0.80 [95% CI: 0.66-0.95] versus AUC HMW adiponectin=0.76 [95% CI: 0.60-0.91], p=0.36). The present study indicates that HMW adiponectin does not seem to provide additional information than total adiponectin in relation to cardio-metabolic risk factors in overweight/obese postmenopausal women. (c) Georg Thieme Verlag KG Stuttgart . New York.

The Memory Alteration Test Discriminates between Cognitively Healthy Status, Mild Cognitive Impairment and Alzheimer's Disease

PubMed Central

Custodio, Nilton; Lira, David; Herrera-Perez, Eder; Nuñez del Prado, Liza; Parodi, José; Guevara-Silva, Erik; Castro-Suarez, Sheila; Montesinos, Rosa; Cortijo, Patricia

2014-01-01

Background/Aims Dementia is a worldwide public health problem and there are several diagnostic tools for its assessment. The aim of this study was to evaluate the performance of the Memory Alteration Test (M@T) to discriminate between patients with early Alzheimer's disease (AD), patients with amnestic mild cognitive impairment (a-MCI), and subjects with a cognitively healthy status (CHS). Methods The discriminative validity was assessed in a sample of 90 patients with AD, 45 patients with a-MCI, and 180 subjects with CHS. Clinical, functional, and cognitive studies were independently performed in a blinded fashion and the gold standard diagnosis was established by consensus on the basis of these results. The test performance was assessed by means of a receiver operating characteristic curve analysis as area under the curve (AUC). Results M@T mean scores were 17.7 (SD = 5.7) in AD, 30.8 (SD = 2.3) in a-MCI, and 44.5 (SD = 3.1) in CHS. A cutoff score of 37 points had a sensitivity of 98.3% and a specificity of 97.8% to differentiate a-MCI from CHS (AUC = 0.999). A cutoff score of 27 points had a sensitivity of 100% and a specificity of 98.9% to differentiate mild AD from a-MCI and from CHS (AUC = 1.000). Conclusions The M@T had a high performance in the discrimination between early AD, a-MCI and CHS. PMID:25298775

Diagnostic value of T1 and T2 * relaxation times and off-resonance saturation effects in the evaluation of Achilles tendinopathy by MRI at 3T.

PubMed

Grosse, Ulrich; Syha, Roland; Hein, Tobias; Gatidis, Sergios; Grözinger, Gerd; Schabel, Christoph; Martirosian, Petros; Schick, Fritz; Springer, Fabian

2015-04-01

To evaluate and compare the diagnostic value of T1 , T2 * relaxation times and off-resonance saturation ratios (OSR) in healthy controls and patients with different clinical and morphological stages of Achilles tendinopathy. Forty-two healthy Achilles tendons and 34 tendons of 17 patients with symptomatic and asymptomatic tendinopathy were investigated clinically with conventional magnetic resonance imaging (MRI) sequences on a 3T whole-body MR scanner and a dynamic ultrasound examination. In addition, T1 and T2 * relaxation times were assessed using an ultrashort echo time (UTE) imaging sequence with flip angle and echo time variation. For the calculation of OSR values a Gaussian off-resonance saturation pulse (frequency offset: 750-5000 Hz) was used. The diagnostic value of the derived MR values was assessed and compared using receiver operating characteristic (ROC) curves. ROC curves demonstrate the highest overall test performance for OSR values at 2000 Hz off-resonance in differentiating slightly (OSR-2000 [AUC: 0.930] > T2 * [AUC: 0.884] > T1 [AUC: 0.737]) and more severe pathologically altered tendon areas (OSR-2000 [AUC: 0.964] > T2 * [AUC: 0.917] > T1 [AUC: 0.819]) from healthy ones. OSR values at a frequency offset of 2000 Hz demonstrated a better sensitivity and specificity for detecting mild and severe stages of tendinopathy compared to T2 * and particularly when compared to T1 relaxation times. © 2014 Wiley Periodicals, Inc.

Area under the curve as a novel metric of behavioral economic demand for alcohol.

PubMed

Amlung, Michael; Yurasek, Ali; McCarty, Kayleigh N; MacKillop, James; Murphy, James G

2015-06-01

Behavioral economic purchase tasks can be readily used to assess demand for a number of addictive substances, including alcohol, tobacco, and illicit drugs. However, several methodological limitations associated with the techniques used to quantify demand may reduce the utility of demand measures. In the present study, we sought to introduce area under the curve (AUC), commonly used to quantify degree of delay discounting, as a novel index of demand. A sample of 207 heavy-drinking college students completed a standard alcohol purchase task and provided information about typical weekly drinking patterns and alcohol-related problems. Level of alcohol demand was quantified using AUC--which reflects the entire amount of consumption across all drink prices--as well as the standard demand indices (e.g., intensity, breakpoint, Omax, Pmax, and elasticity). Results indicated that AUC was significantly correlated with each of the other demand indices (rs = .42-.92), with particularly strong associations with Omax (r = .92). In regression models, AUC and intensity were significant predictors of weekly drinking quantity, and AUC uniquely predicted alcohol-related problems, even after controlling for drinking level. In a parallel set of analyses, Omax also predicted drinking quantity and alcohol problems, although Omax was not a unique predictor of the latter. These results offer initial support for using AUC as an index of alcohol demand. Additional research is necessary to further validate this approach and to examine its utility in quantifying demand for other addictive substances such as tobacco and illicit drugs. (c) 2015 APA, all rights reserved).

One-shot estimate of MRMC variance: AUC.

PubMed

Gallas, Brandon D

2006-03-01

One popular study design for estimating the area under the receiver operating characteristic curve (AUC) is the one in which a set of readers reads a set of cases: a fully crossed design in which every reader reads every case. The variability of the subsequent reader-averaged AUC has two sources: the multiple readers and the multiple cases (MRMC). In this article, we present a nonparametric estimate for the variance of the reader-averaged AUC that is unbiased and does not use resampling tools. The one-shot estimate is based on the MRMC variance derived by the mechanistic approach of Barrett et al. (2005), as well as the nonparametric variance of a single-reader AUC derived in the literature on U statistics. We investigate the bias and variance properties of the one-shot estimate through a set of Monte Carlo simulations with simulated model observers and images. The different simulation configurations vary numbers of readers and cases, amounts of image noise and internal noise, as well as how the readers are constructed. We compare the one-shot estimate to a method that uses the jackknife resampling technique with an analysis of variance model at its foundation (Dorfman et al. 1992). The name one-shot highlights that resampling is not used. The one-shot and jackknife estimators behave similarly, with the one-shot being marginally more efficient when the number of cases is small. We have derived a one-shot estimate of the MRMC variance of AUC that is based on a probabilistic foundation with limited assumptions, is unbiased, and compares favorably to an established estimate.

Bioequivalence of generic and branded amoxicillin capsules in healthy human volunteers

PubMed Central

Pathak, Priyanka; Pandit, Vijaya A.; Dhande, Priti P.

2017-01-01

CONTEXT: The Medical Council of India urges doctors to prescribe generic drugs as far as possible. The Indian Medical Association had responded earlier saying that it requires guarantees on the quality of generic forms of drugs. Although no published scientific reports are available on the issue of therapeutic inequivalence, unconfirmed clinician accounts and newspaper reports of therapeutic inequivalence exist. AIM: This study was planned to ascertain whether bioequivalence of branded and generic amoxicillin capsule is comparable. SETTINGS AND DESIGN: An open-label, randomized, single-dose, two-treatment, two-sequence, two-period crossover oral bioequivalence study was conducted in 12 healthy, adult human subjects under fasting condition. MATERIALS AND METHODS: Serum samples, collected at 8 time points, were analyzed by a validated ultraviolet spectrophotometer method. Pharmacokinetic (PK) parameters such as area under the curve (AUC)0–t, AUC0–∞, Cmax, and Tmax were determined along with time above minimum inhibitory concentration (MIC). STATISTICAL ANALYSIS USED: The log-transformed PK parameters (Cmax, AUC0–t, AUC0–∞) were analyzed using a Two One-Sided Test ANOVA in SAS for each parameter. Tmax and MIC were analyzed by Wilcoxon rank-sum test in GraphPad Prism. RESULTS: Geometric mean ratio of Cmax fell within bioequivalence criteria. The upper and lower confidence limits of both AUC0–t and AUC0–∞ geometric mean ratio fell below bioequivalence criteria. Time above MIC of generic preparation was significantly lower than that of branded version. CONCLUSIONS: The generic capsule was not bioequivalent to the branded amoxicillin capsule. PMID:28706331

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

PubMed

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (p<0.05), with the exception of between K 10th , K 90th and histological grades. In contrast, significant negative correlations were observed between 25th, 50th percentiles and mean values of ADC and D, as well as ADC 10th , with tumour T stages (p< 0.05). Meanwhile, lower 75th and 90th percentiles of ADC and D values were also correlated inversely with nodal involvement (p< 0.05). K mean showed a relatively higher area under the curve (AUC) and higher specificity than other percentiles for differentiation of lesions with nodal involvement. DKI metrics with whole-tumour volume histogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

Identifying Low Muscle Mass in Patients with Hip Fracture: Validation of Biolectrical Impedance Analysis and Anthropometry Compared to Dual Energy X-ray Absorptiometry.

PubMed

Steihaug, O M; Gjesdal, C G; Bogen, B; Ranhoff, A H

2016-01-01

Older hip fracture patients often have reduced muscle mass, which is associated with adverse outcomes. Dual energy X-ray absorptiometry (DXA) can determine muscle mass, but is not practical in the acute phase. We investigated bioelectrical impedance analysis (BIA) and anthropometry compared against DXA for detecting low muscle mass in hip fracture patients. This was a cross-sectional validation study at two Norwegian hospitals on 162 hip fracture patients aged ≥ 65 years. Appendicular lean mass (ALM) was determined by DXA, BIA and anthropometry 3 months after hip fracture. ALM by BIA was calculated by the Kyle, Janssen, Tengvall and Sergi equations, and ALM by anthropometry by the Heymsfield and Villani equations. The area under the receiver operating characteristic curve (AUC) was used to compare BIA and anthropometry for determining low ALM (≤5.67 kg/m2 for women and ≤7.25kg/m2 for men). Mean age was 79 years (SD 7.9), 74% were female. Mean ALM by DXA was 14.8 kg (SD 2.3) for women and 20.8 kg (SD 4.2) for men and 45% of women and 60% of men had low ALM. BIA (Kyle) in women (AUC 0.81, 95% confidence interval 0.72-0.89) and BIA (Sergi) in men (AUC 0.89, 95% CI 0.80-0.98) were best able to discriminate between low and normal ALM. Anthropometry (Heymsfield) was less accurate than BIA in women (AUC 0.64, 95% CI 0.54-0.75), and equal to BIA in men (AUC 0.72, 95% CI 0.72 0.56-0.87). BIA (Sergi, Kyle and Tengvall) and anthropometry (Heymsfield) can identify low muscle mass in hip fracture patients.

Cut-Offs and Response Criteria for the Hospital Universitario La Princesa Index (HUPI) and Their Comparison to Widely-Used Indices of Disease Activity in Rheumatoid Arthritis.

PubMed

González-Álvaro, Isidoro; Castrejón, Isabel; Ortiz, Ana M; Toledano, Esther; Castañeda, Santos; García-Vadillo, Alberto; Carmona, Loreto

2016-01-01

To estimate cut-off points and to establish response criteria for the Hospital Universitario La Princesa Index (HUPI) in patients with chronic polyarthritis. Two cohorts, one of early arthritis (Princesa Early Arthritis Register Longitudinal [PEARL] study) and other of long-term rheumatoid arthritis (Estudio de la Morbilidad y Expresión Clínica de la Artritis Reumatoide [EMECAR]) including altogether 1200 patients were used to determine cut-off values for remission, and for low, moderate and high activity through receiver operating curve (ROC) analysis. The areas under ROC (AUC) were compared to those of validated indexes (SDAI, CDAI, DAS28). ROC analysis was also applied to establish minimal and relevant clinical improvement for HUPI. The best cut-off points for HUPI are 2, 5 and 9, classifying RA activity as remission if ≤2, low disease activity if >2 and ≤5), moderate if >5 and <9 and high if ≥9. HUPI's AUC to discriminate between low-moderate activity was 0.909 and between moderate-high activity 0.887. DAS28's AUCs were 0.887 and 0.846, respectively; both indices had higher accuracy than SDAI (AUCs: 0.832 and 0.756) and CDAI (AUCs: 0.789 and 0.728). HUPI discriminates remission better than DAS28-ESR in early arthritis, but similarly to SDAI. The HUPI cut-off for minimal clinical improvement was established at 2 and for relevant clinical improvement at 4. Response criteria were established based on these cut-off values. The cut-offs proposed for HUPI perform adequately in patients with either early or long term arthritis.

Cut-Offs and Response Criteria for the Hospital Universitario La Princesa Index (HUPI) and Their Comparison to Widely-Used Indices of Disease Activity in Rheumatoid Arthritis

PubMed Central

Castrejón, Isabel; Ortiz, Ana M.; Toledano, Esther; Castañeda, Santos; García-Vadillo, Alberto; Carmona, Loreto

2016-01-01

Objective To estimate cut-off points and to establish response criteria for the Hospital Universitario La Princesa Index (HUPI) in patients with chronic polyarthritis. Methods Two cohorts, one of early arthritis (Princesa Early Arthritis Register Longitudinal [PEARL] study) and other of long-term rheumatoid arthritis (Estudio de la Morbilidad y Expresión Clínica de la Artritis Reumatoide [EMECAR]) including altogether 1200 patients were used to determine cut-off values for remission, and for low, moderate and high activity through receiver operating curve (ROC) analysis. The areas under ROC (AUC) were compared to those of validated indexes (SDAI, CDAI, DAS28). ROC analysis was also applied to establish minimal and relevant clinical improvement for HUPI. Results The best cut-off points for HUPI are 2, 5 and 9, classifying RA activity as remission if ≤2, low disease activity if >2 and ≤5), moderate if >5 and <9 and high if ≥9. HUPI’s AUC to discriminate between low-moderate activity was 0.909 and between moderate-high activity 0.887. DAS28’s AUCs were 0.887 and 0.846, respectively; both indices had higher accuracy than SDAI (AUCs: 0.832 and 0.756) and CDAI (AUCs: 0.789 and 0.728). HUPI discriminates remission better than DAS28-ESR in early arthritis, but similarly to SDAI. The HUPI cut-off for minimal clinical improvement was established at 2 and for relevant clinical improvement at 4. Response criteria were established based on these cut-off values. Conclusions The cut-offs proposed for HUPI perform adequately in patients with either early or long term arthritis. PMID:27603313

How to interpret a small increase in AUC with an additional risk prediction marker: decision analysis comes through.

PubMed

Baker, Stuart G; Schuit, Ewoud; Steyerberg, Ewout W; Pencina, Michael J; Vickers, Andrew; Vickers, Andew; Moons, Karel G M; Mol, Ben W J; Lindeman, Karen S

2014-09-28

An important question in the evaluation of an additional risk prediction marker is how to interpret a small increase in the area under the receiver operating characteristic curve (AUC). Many researchers believe that a change in AUC is a poor metric because it increases only slightly with the addition of a marker with a large odds ratio. Because it is not possible on purely statistical grounds to choose between the odds ratio and AUC, we invoke decision analysis, which incorporates costs and benefits. For example, a timely estimate of the risk of later non-elective operative delivery can help a woman in labor decide if she wants an early elective cesarean section to avoid greater complications from possible later non-elective operative delivery. A basic risk prediction model for later non-elective operative delivery involves only antepartum markers. Because adding intrapartum markers to this risk prediction model increases AUC by 0.02, we questioned whether this small improvement is worthwhile. A key decision-analytic quantity is the risk threshold, here the risk of later non-elective operative delivery at which a patient would be indifferent between an early elective cesarean section and usual care. For a range of risk thresholds, we found that an increase in the net benefit of risk prediction requires collecting intrapartum marker data on 68 to 124 women for every correct prediction of later non-elective operative delivery. Because data collection is non-invasive, this test tradeoff of 68 to 124 is clinically acceptable, indicating the value of adding intrapartum markers to the risk prediction model. Copyright © 2014 John Wiley & Sons, Ltd.

Evaluation of the antithrombotic abilities of non-vitamin K antagonist oral anticoagulants using the Total Thrombus-formation Analysis System®.

PubMed

Idemoto, Yoshiaki; Miura, Shin-Ichiro; Norimatsu, Kenji; Suematsu, Yasunori; Hitaka, Yuka; Shiga, Yuhei; Morii, Joji; Imaizumi, Satoshi; Kuwano, Takashi; Iwata, Atsushi; Zhang, Bo; Ogawa, Masahiro; Saku, Keijiro

2017-03-01

The Total Thrombus-formation Analysis System (T-TAS ® ) is a novel automated microchip flow-chamber system for the quantitative evaluation of thrombus formation under blood flow conditions. T-TAS ® uses two types of microchip to evaluate thrombus formation: the AR-chip quantifies white thrombus formation and the PL-chip quantifies platelet thrombus formation. We assessed the antithrombotic abilities of various non-vitamin K antagonist oral anticoagulants (NOACs) using T-TAS ® . One hundred and three consecutive patients who were hospitalized with cardiovascular diseases were enrolled. We divided the patients into 2 groups; a control group that did not receive an anticoagulant (non-AC group) and an anticoagulant group (AC group). The AC group was further divided into warfarin, dabigatran, rivaroxaban and apixaban groups. We performed common coagulation tests and evaluated the area under the flow pressure curve (AR-AUC and PL-AUC) to quantify antithrombotic ability using T-TAS ® at the trough. There were no significant differences in patient characteristics between the non-AC and AC groups. Only 55.1 % of patients in the AC group achieved the target blood pressure (BP) of less than 130/80 mmHg. Compared with the non-AC group, AR-AUC was significantly decreased in the AC, warfarin, dabigatran and apixaban groups. Only the rivaroxaban group did not show a significant decrease in AR-AUC. NOACs showed a significant decrease in PL-AUC compared with the non-AC group. In conclusion, T-TAS ® was a useful tool for evaluating anticoagulation activity. NOACs was significantly effective as an antiplatelet agent. BP control should be a higher priority than the selection of an anticoagulant drug, especially NOACs.

Subclinical keratoconus detection by pattern analysis of corneal and epithelial thickness maps with optical coherence tomography

PubMed Central

Li, Yan; Chamberlain, Winston; Tan, Ou; Brass, Robert; Weiss, Jack L.; Huang, David

2016-01-01

PURPOSE To screen for subclinical keratoconus by analyzing corneal, epithelial, and stromal thickness map patterns with Fourier-domain optical coherence tomography (OCT). SETTING Four centers in the United States. DESIGN Cross-sectional observational study. METHODS Eyes of normal subjects, subclinical keratoconus eyes, and the topographically normal eye of a unilateral keratoconus patient were studied. Corneas were scanned using a 26 000 Hz Fourier-domain OCT system (RTVue). Normal subjects were divided into training and evaluation groups. Corneal, epithelial, and stromal thickness maps and derived diagnostic indices, including pattern standard deviation (PSD) variables and pachymetric map–based keratoconus risk scores were calculated from the OCT data. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the diagnostic accuracy of the indices. RESULTS The study comprised 150 eyes of 83 normal subjects, 50 subclinical keratoconus eyes of 32 patients, and 1 topographically normal eye of a unilateral keratoconus patient. Subclinical keratoconus was characterized by inferotemporal thinning of the cornea, epithelium, and stroma. The PSD values for corneal (P < .001), epithelial (P < .001), and stromal (P = .049) thickness maps were all significantly higher in subclinical keratoconic eyes than in the normal group. The diagnostic accuracy was significantly higher for PSD variables (pachymetric PSD, AUC = 0.941; epithelial PSD, AUC = 0.985; stromal PSD, AUC = 0.924) than for the pachymetric map–based keratoconus risk score (AUC = 0.735). CONCLUSIONS High-resolution Fourier-domain OCT could map corneal, epithelial, and stromal thicknesses. Corneal and sublayer thickness changes in subclinical keratoconus could be detected with high accuracy using PSD variables. These new diagnostic variables might be useful in the detection of early keratoconus. PMID:27026454

Comparison of two correlated ROC curves at a given specificity or sensitivity level.

PubMed

Bantis, Leonidas E; Feng, Ziding

2016-10-30

The receiver operating characteristic (ROC) curve is the most popular statistical tool for evaluating the discriminatory capability of a given continuous biomarker. The need to compare two correlated ROC curves arises when individuals are measured with two biomarkers, which induces paired and thus correlated measurements. Many researchers have focused on comparing two correlated ROC curves in terms of the area under the curve (AUC), which summarizes the overall performance of the marker. However, particular values of specificity may be of interest. We focus on comparing two correlated ROC curves at a given specificity level. We propose parametric approaches, transformations to normality, and nonparametric kernel-based approaches. Our methods can be straightforwardly extended for inference in terms of ROC -1 (t). This is of particular interest for comparing the accuracy of two correlated biomarkers at a given sensitivity level. Extensions also involve inference for the AUC and accommodating covariates. We evaluate the robustness of our techniques through simulations, compare them with other known approaches, and present a real-data application involving prostate cancer screening. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Impact of AUC-Based Monitoring on Pharmacist-Directed Vancomycin Dose Adjustments in Complicated Methicillin-Resistant Staphylococcus aureus Infection.

PubMed

Stoessel, Andrew M; Hale, Cory M; Seabury, Robert W; Miller, Christopher D; Steele, Jeffrey M

2018-01-01

This study aimed to assess the impact of area under the curve (AUC)-based vancomycin monitoring on pharmacist-initiated dose adjustments after transitioning from a trough-only to an AUC-based monitoring method at our institution. A retrospective cohort study of patients treated with vancomycin for complicated methicillin-resistant Staphylococcus aureus (MRSA) infection between November 2013 and December 2016 was conducted. The frequency of pharmacist-initiated dose adjustments was assessed for patients monitored via trough-only and AUC-based approaches for trough ranges: 10 to 14.9 mg/L and 15 to 20 mg/L. Fifty patients were included: 36 in the trough-based monitoring and 14 in the AUC-based-monitoring group. The vancomycin dose was increased in 71.4% of patients when troughs were 10 to 14.9 mg/L when a trough-only approach was used and in only 25% of patients when using AUC estimation ( P = .048). In the AUC group, the dose was increased only when AUC/minimum inhibitory concentration (MIC) <400; unchanged regimens had an estimated AUC/MIC ≥400. The AUC-based monitoring did not significantly increase the frequency of dose reductions when trough concentrations were 15 to 20 mg/L (AUC: 33.3% vs trough: 4.6%; P = .107). The AUC-based monitoring resulted in fewer patients with dose adjustments when trough levels were 10 to 14.9 mg/L. The AUC-based monitoring has the potential to reduce unnecessary vancomycin exposure and warrants further investigation.

Plasma glucose and insulin response to two oral nutrition supplements in adults with type 2 diabetes mellitus.

PubMed

Huhmann, Maureen B; Smith, Kristen N; Schwartz, Sherwyn L; Haller, Stacie K; Irvin, Sarah; Cohen, Sarah S

2016-01-01

The purpose of this clinical trial was to compare the glucose usage of two oral nutritional supplement (ONS) products and to assess whether a diabetes-specific formulation provides improved glucose stabilization and management compared with a standard formula. A total of 12 subjects with type 2 diabetes (7 males and 5 females) completed a randomized, cross-over design trial. Each subject consumed isocaloric amounts of either the standard ONS or the diabetes-specific formula ONS on different dates, 1 week apart. Glucose and insulin measures were recorded at baseline, and 10, 20, 30, 60, 90, 120, 150, 180, 210 and 240 min after the beverage was consumed and then used to calculate area under the curve (AUC) for each subject. The mean glucose AUC was lower in the diabetes-specific ONS group than in the standard group (p<0.0001), but there was not a significant difference observed for mean insulin AUC (p=0.068). A sensitivity analysis of the mean insulin AUC measures was performed by removing a potential outlier from the analysis, and this resulted in a significant difference between the groups (p=0.012). First-phase insulin measures and an insulinogenic index calculated for the beverages showed no significant differences. On the basis of the results of this trial of 12 subjects, the diabetes-specific ONS appears to provide better glucose maintenance in persons with type 2 diabetes when compared to the standard formula ONS. NCT02612675.

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis.

PubMed

Lau, Susanna K P; Lee, Kim-Chung; Lo, George C S; Ding, Vanessa S Y; Chow, Wang-Ngai; Ke, Tony Y H; Curreem, Shirly O T; To, Kelvin K W; Ho, Deborah T Y; Sridhar, Siddharth; Wong, Sally C Y; Chan, Jasper F W; Hung, Ivan F N; Sze, Kong-Hung; Lam, Ching-Wan; Yuen, Kwok-Yung; Woo, Patrick C Y

2016-02-27

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

PubMed Central

Lau, Susanna K. P.; Lee, Kim-Chung; Lo, George C. S.; Ding, Vanessa S. Y.; Chow, Wang-Ngai; Ke, Tony Y. H.; Curreem, Shirly O. T.; To, Kelvin K. W.; Ho, Deborah T. Y.; Sridhar, Siddharth; Wong, Sally C. Y.; Chan, Jasper F. W.; Hung, Ivan F. N.; Sze, Kong-Hung; Lam, Ching-Wan; Yuen, Kwok-Yung; Woo, Patrick C. Y.

2016-01-01

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis. PMID:26927094

NanoString nCounter® Approach in Breast Cancer: A Comparative Analysis with Quantitative Real-Time Polymerase Chain Reaction, In Situ Hybridization, and Immunohistochemistry.

PubMed

Hyeon, Jiyeon; Cho, Soo Youn; Hong, Min Eui; Kang, So Young; Do, Ingu; Im, Young Hyuck; Cho, Eun Yoon

2017-09-01

Accurate testing for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) is essential for breast cancer treatment. At present, immunohistochemistry (IHC)/florescence in situ hybridization (FISH) are widely accepted as the standard testing methods. To investigate the value of NanoString nCounter®, we performed its comparative analysis with IHC/FISH and real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) for the assessment of ER, PR, and HER2. Data on IHC/FISH results for ER, PR, and HER2 in 240 patients from a single tertiary hospital in Korea were collected and compared with NanoString nCounter® and qRT-PCR results at a single institution. Expression levels for each gene using NanoString nCounter® showed good correlation with the corresponding data for protein expression by IHC ( p <0.001) and gene amplification status for HER2 ( p <0.001). Comparisons between gene expression and IHC data showed good overall agreement with a high area under the curve (AUC) for ESR1 /ER (AUC=0.939), PgR /PR (AUC=0.796), and HER2 /HER2 (AUC=0.989) ( p <0.001). The quantification of ER , PgR , and HER2 mRNA expression with NanoString nCounter® may be a viable alternative to conventional IHC/FISH methods.

Preoperative serum alkaline phosphatase: a predictive factor for early hypocalcaemia following parathyroidectomy of primary hyperparathyroidism.

PubMed

Sun, Longhao; He, Xianghui; Liu, Tong

2014-01-01

Postoperative hypocalcemia is one of the most common complications following parathyroidectomy for primary hyperparathyroidism (PHPT). The aim of this study was to analyze the predictive value of biochemical parameters as indicators for episodes of hypocalcemia in patients undergoing parathyroidectomy for PHPT. The patients with PHPT who underwent parathyroidectomy between February 2004 and February 2014 were studied retrospectively at a single medical center. The patients were divided into biochemical, clinical, and no postoperative hypocalcemia groups, based on different clinical manifestations. Potential risk factors for postoperative hypocalcemia were identified and investigated by univariate and multivariate Logistic regression analysis. Of the 139 cases, 25 patients (18.0%) were diagnosed with postoperative hypocalcemia according to the traditional criterion. Univariate analysis revealed only alkaline phosphatase (ALP) and the small area under the curve (AUC) of receiver operating characteristics (ROC) curve for ALP demonstrates low accuracy in predicting the occurrence of postoperative hypocalcemia. Based on new criteria, 22 patients were added to the postoperative hypocalcemia group and similar biochemical parameters were compared. The serum ALP was a significant independent risk factor for postoperative hypocalcemia (P = 0.000) and its AUC of ROC curve was 0.783. The optimal cutoff point was 269 U/L and the sensitivity and specificity for prediction were 89.2% and 64.3%, respectively. The risk of postoperative hypocalcemia after parathyroidectomy should be emphasized for patients with typical symptoms of hypocalcemia despite their serum calcium level is in normal or a little higher range. Serum ALP is a predictive factor for the occurrence of postoperative hypocalcemia.

Diagnostic value of fibronectin discriminant score for predicting liver fibrosis stages in chronic hepatitis C virus patients.

PubMed

Attallah, Abdelfattah M; Abdallah, Sanaa O; Attallah, Ahmed A; Omran, Mohamed M; Farid, Khaled; Nasif, Wesam A; Shiha, Gamal E; Abdel-Aziz, Abdel-Aziz F; Rasafy, Nancy; Shaker, Yehia M

2013-01-01

Several noninvasive predictive models were developed to substitute liver biopsy for fibrosis assessment. To evaluate the diagnostic value of fibronectin which reflect extracellular matrix metabolism and standard liver functions tests which reflect alterations in hepatic functions. Chronic hepatitis C (CHC) patients (n = 145) were evaluated using ROC curves and stepwise multivariate discriminant analysis (MDA) and was validated in 180 additional patients. Liver biochemical profile including transaminases, bilirubin, alkaline phosphatase, albumin, complete blood count were estimated. Fibronectin concentration was determined using monoclonal antibody and ELISA. A novel index named fibronectin discriminant score (FDS) based on fibronectin, APRI and albumin was developed. FDS produced areas under ROC curves (AUC) of 0.91 for significant fibrosis and 0.81 for advanced fibrosis. The FDS correctly classified 79% of the significant liver fibrosis patients (F2-F4) with 87% sensitivity and 75% specificity. The relative risk [odds ratio (OR)] of having significant liver fibrosis using the cut-off values determined by ROC curve analyses were 6.1 for fibronectin, 4.9 for APRI, and 4.2 for albumin. FDS predicted liver fibrosis with an OR of 16.8 for significant fibrosis and 8.6 for advanced fibrosis. The FDS had similar AUC and OR in the validation group to the estimation group without statistically significant difference. FDS predicted liver fibrosis with high degree of accuracy, potentially decreasing the number of liver biopsy required.

Comparison of mental health screening tools for detecting antenatal depression and anxiety disorders in South African women

PubMed Central

Honikman, Simone; Tomlinson, Mark; Field, Sally; Myer, Landon

2018-01-01

Background Antenatal depression and anxiety disorders are highly prevalent in low and middle-income countries. Screening of pregnant women in primary care antenatal settings provides an opportunity for entry to care, but data are needed on the performance of different screening tools. We compared five widely-used questionnaires in a sample of pregnant women in urban South Africa. Method Pregnant women attending a primary care antenatal clinic were administered five tools by trained research assistants: the Edinburgh Postnatal Depression Scale (EPDS), the Patient Health Questionnaire (PHQ-9), the Kessler Psychological Distress scale (K10) and a shortened 6-item version (K6), the Whooley questions and the two-item Generalised Anxiety Disorder scale (GAD-2). Following this, a registered mental health counsellor administered the MINI Plus, a structured clinical diagnostic interview. The Area Under the Curve (AUC) from Receiver Operator Characteristic curve analysis was used to summarise screening test performance and Cronbach’s α used to assess internal consistency. Results Of 376 participants, 32% were diagnosed with either MDE and/or anxiety disorders. All five questionnaires demonstrated moderate to high performance (AUC = 0.78–0.85). The EPDS was the best performing instrument for detecting MDE and the K10 and K6 for anxiety disorder. For MDE and/or anxiety disorders, the EPDS had the highest AUC (0.83). Of the short instruments, the K10 (AUC = 0.85) and the K6 (AUC = 0.85) performed the best, with the K6 showing good balance between sensitivity (74%) and specificity (85%) and a good positive predictive value (70%). The Whooley questions (AUC = 0.81) were the best performing ultra-short instrument. Internal consistency ranged from good to acceptable (α = 0.89–0.71). However, the PPV of the questionnaires compared with the diagnostic interview, ranged from 54% to 71% at the optimal cut-off scores. Conclusions Universal screening for case identification of antenatal depression and anxiety disorders in low-resource settings can be conducted with a number of commonly used screening instruments. Short and ultra-short screening instruments such as the K6 and the Whooley questions may be feasible and acceptable for use in these settings. PMID:29668725

Comparison of performance of computer display monitors for radiological diagnosis; "diagnostic" high brightness monochrome LCD, 3MP vs "clinical review" colour LCD, 2MP.

PubMed

Sim, L; Manthey, K; Stuckey, S

2007-06-01

A study to compare performance of the following display monitors for application as PACS CR diagnostic workstations is described. 1. Diagnostic quality, 3 Mega Pixel, 21 inch monochrome LCD monitors--Planar C3i. 2. Clinical review quality, 2 Mega Pixel, 21 inch colour LCD monitors--Planar PX212. Two sets of seventy radiological studies were presented to four senior radiologists on two occasions, using different displays on each occasion. The clinical condition used for this investigation was to query for the presence of a solitary pulmonary nodule. Receiver Operating Characteristic (ROC) curves were constructed for diagnostic performance for each presentation. Areas under the ROC curves (AUC) for diagnosis using different monitors were compared and the following results obtained: Monochrome AUC = 0.813 +/- 0.02, Colour AUC = 0.801 +/- 0.021. These results indicate that there is no statistically significant difference in the performance of these monitor types at a 95% confidence level.

Comparative pharmacodynamics of the new fluoroquinolone ABT492 and levofloxacin with Streptococcus pneumoniae in an in vitro dynamic model.

PubMed

Firsov, Alexander A; Alferova, Irene V; Smirnova, Maria V; Lubenko, Irene Yu; Portnoy, Yury A; Zinner, Stephen H

2005-05-01

The kinetics of killing of Streptococcus pneumoniae exposed to ABT492 or levofloxacin were compared. S. pneumoniae ATCC 49619 and four ciprofloxacin-resistant clinical isolates, S. pneumoniae 1149, 391, 79 and 804, were exposed to ABT492 and levofloxacin as a single dose in a dynamic model that simulates human pharmacokinetics of the quinolones. With S. pneumoniae ATCC 49619 eight-fold ranging AUC/MIC ratios (60-500 h) were simulated for each quinolone. In addition, two larger AUC/MICs, i.e., 1080 and 2150 h for ABT492 and 1460 and 3660 h for levofloxacin which correspond to 100 and 200 mg doses of ABT492 and 200 and 500 mg doses of levofloxacin, respectively, were mimicked. Each ciprofloxacin-resistant organism was exposed to the clinical doses of ABT492 (400 mg) and levofloxacin (500 mg); the respective AUC/MIC ratios were from 580 to 3470 h and from 28 to 110 h. At comparable AUC/MICs (from 60 to 500 h), regrowth of S. pneumoniae ATCC 49619 followed initial killing, and the times to regrowth were longer with levofloxacin than ABT492. However, no regrowth of S. pneumoniae ATCC 49619 occurred at the higher AUC/MICs of ABT492 (1080 and 2150 h) and levofloxacin (1460 and 3660 h). Killing of S. pneumoniae 1149, 391 and 79 without bacterial regrowth, was provided by ABT492 (AUC/MIC 3470, 2310 and 1160 h, respectively) but not levofloxacin (AUC/MIC 55, 110 and 28 h, respectively). Regrowth of S. pneumoniae 804 was observed with both ABT492 and levofloxacin (AUC/MIC 580 and 55 h, respectively). Areas between the control growth curve and the time-kill curve (ABBCs) for ABT492 against S. pneumoniae 1149, 391 and 79 were 2.6-4.2 times larger than the respective ABBCs for levofloxacin, whereas similar ABBCs were found with S. pneumoniae 804 exposed to both quinolones. These findings predict significantly greater efficacy of ABT492 than levofloxacin at clinically achievable AUC/MIC ratios against ciprofloxacin-resistant S. pneumoniae and similar efficacies of the two quinolones against susceptible organisms.

Lung injury induced by secondhand smoke exposure detected with hyperpolarized helium-3 diffusion MR.

PubMed

Wang, Chengbo; Mugler, John P; de Lange, Eduard E; Patrie, James T; Mata, Jaime F; Altes, Talissa A

2014-01-01

To determine whether helium-3 diffusion MR can detect the changes in the lungs of healthy nonsmoking individuals who were regularly exposed to secondhand smoke. Three groups were studied (age: 59 ± 9 years): 23 smokers, 37 exposure-to-secondhand-smoke subjects, and 29 control subjects. We measured helium-3 diffusion values at diffusion times from 0.23 to 1.97 s. One-way analysis of variance revealed that the mean area under the helium-3 diffusion curves (ADC AUC) of the smokers was significantly elevated compared with the controls and to the exposure-to-secondhand-smoke subjects (P < 0.001 both). No difference between the mean ADC AUC of the exposure-to-secondhand-smoke subjects and that of the controls was found (P = 0.115). However, application of a receiver operator characteristic-derived rule to classify subjects as either a "control" or a "smoker," based on ADC AUC, revealed that 30% (11/37) of the exposure-to-secondhand subjects were classified as "smokers" indicating an elevation of the ADC AUC. Using helium-3 diffusion MR, elevated ADC values were detected in 30% of nonsmoking healthy subjects who had been regularly exposed to secondhand smoke, supporting the concept that, in susceptible individuals, secondhand smoke causes mild lung damage. Copyright © 2013 Wiley Periodicals, Inc.

Wavelet coherence analysis: A new approach to distinguish organic and functional tremor types.

PubMed

Kramer, G; Van der Stouwe, A M M; Maurits, N M; Tijssen, M A J; Elting, J W J

2018-01-01

To distinguish tremor subtypes using wavelet coherence analysis (WCA). WCA enables to detect variations in coherence and phase difference between two signals over time and might be especially useful in distinguishing functional from organic tremor. In this pilot study, polymyography recordings were studied retrospectively of 26 Parkinsonian (PT), 26 functional (FT), 26 essential (ET), and 20 enhanced physiological (EPT) tremor patients. Per patient one segment of 20 s in duration, in which tremor was present continuously in the same posture, was selected. We studied several coherence and phase related parameters, and analysed all possible muscle combinations of the flexor and extensor muscles of the upper and fore arm. The area under the receiver operating characteristic curve (AUC-ROC) was applied to compare WCA and standard coherence analysis to distinguish tremor subtypes. The percentage of time with significant coherence (PTSC) and the number of periods without significant coherence (NOV) proved the most discriminative parameters. FT could be discriminated from organic (PT, ET, EPT) tremor by high NOV (31.88 vs 21.58, 23.12 and 10.20 respectively) with an AUC-ROC of 0.809, while standard coherence analysis resulted in an AUC-ROC of 0.552. EMG-EMG WCA analysis might provide additional variables to distinguish functional from organic tremor. WCA might prove to be of additional value to discriminate between tremor types. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance.

PubMed

Du, Tingting; Yuan, Gang; Zhang, Muxun; Zhou, Xinrong; Sun, Xingxing; Yu, Xuefeng

2014-10-20

To directly compare traditional lipid ratios (total cholesterol [TC]/high density lipoprotein cholesterol [HDL-C], non-HDL-C/HDL-C, low density lipoprotein cholesterol [LDL-C]/HDL-C, and triglycerides [TG]/HDL-C), apolipoprotein B (apoB)/apolipoprotein A-I (apoA-I) ratio, visceral adiposity index (VAI), lipid accumulation product (LAP), and the product of TG and fasting glucose (TyG) for strength and independence as risk factors for insulin resistance (IR). We conducted a cross-sectional analysis of 7629 Chinese adults using data from the China Health and Nutrition Survey 2009. For all lipid ratios (traditional lipid ratios and apoB/apoA-I), among both sexes, TG/HDL-C explained the most additional percentage of variation in HOMA-IR (2.9% in men, and 2.3% in women); for all variables of interest, the variability in HOMA-IR explained by VAI and TG/HDL-C were comparable; TyG had the most significant association with HOMA-IR, which explained 9.1% for men and 7.8% for women of the variability in HOMA-IR. Logistic regression analysis showed the similar patterns. Receiver operating characteristic (ROC) curve analysis showed that, among both sexes, TG/HDL-C was a better discriminator of IR than apoB/apoA-I; the area under the ROC curve (AUC) for VAI (0.695 in men and 0.682 in women) was greater than that for TG/HDL-C (AUC 0.665 in men and 0.664 in women); TyG presented the greatest value of AUC (0.709 in men and 0.711 in women). The apoB/apoA-I performs no better than any of the traditional lipid ratios in correlating with IR. The TG/HDL-C, VAI and TyG are better markers for early identification of IR individuals.

Hematoma Shape, Hematoma Size, Glasgow Coma Scale Score and ICH Score: Which Predicts the 30-Day Mortality Better for Intracerebral Hematoma?

PubMed Central

Wang, Chih-Wei; Liu, Yi-Jui; Lee, Yi-Hsiung; Hueng, Dueng-Yuan; Fan, Hueng-Chuen; Yang, Fu-Chi; Hsueh, Chun-Jen; Kao, Hung-Wen; Juan, Chun-Jung; Hsu, Hsian-He

2014-01-01

Purpose To investigate the performance of hematoma shape, hematoma size, Glasgow coma scale (GCS) score, and intracerebral hematoma (ICH) score in predicting the 30-day mortality for ICH patients. To examine the influence of the estimation error of hematoma size on the prediction of 30-day mortality. Materials and Methods This retrospective study, approved by a local institutional review board with written informed consent waived, recruited 106 patients diagnosed as ICH by non-enhanced computed tomography study. The hemorrhagic shape, hematoma size measured by computer-assisted volumetric analysis (CAVA) and estimated by ABC/2 formula, ICH score and GCS score was examined. The predicting performance of 30-day mortality of the aforementioned variables was evaluated. Statistical analysis was performed using Kolmogorov-Smirnov tests, paired t test, nonparametric test, linear regression analysis, and binary logistic regression. The receiver operating characteristics curves were plotted and areas under curve (AUC) were calculated for 30-day mortality. A P value less than 0.05 was considered as statistically significant. Results The overall 30-day mortality rate was 15.1% of ICH patients. The hematoma shape, hematoma size, ICH score, and GCS score all significantly predict the 30-day mortality for ICH patients, with an AUC of 0.692 (P = 0.0018), 0.715 (P = 0.0008) (by ABC/2) to 0.738 (P = 0.0002) (by CAVA), 0.877 (P<0.0001) (by ABC/2) to 0.882 (P<0.0001) (by CAVA), and 0.912 (P<0.0001), respectively. Conclusion Our study shows that hematoma shape, hematoma size, ICH scores and GCS score all significantly predict the 30-day mortality in an increasing order of AUC. The effect of overestimation of hematoma size by ABC/2 formula in predicting the 30-day mortality could be remedied by using ICH score. PMID:25029592

ACCURACY OF PLASMA FREE METANEPHRINES IN THE DIAGNOSIS OF PHEOCHROMOCYTOMA AND PARAGANGLIOMA: A SYSTEMATIC REVIEW AND META-ANALYSIS.

PubMed

Chen, Yan; Xiao, Huangmeng; Zhou, Xieda; Huang, Xiaoyu; Li, Yanbing; Xiao, Haipeng; Cao, Xiaopei

2017-10-01

Various studies have validated plasma free metanephrines (MNs) as biomarkers for pheochromocytoma and paraganglioma (PPGL). This meta-analysis aimed to estimate the overall diagnostic accuracy of this biochemical test for PPGL. We searched the PubMed, the Cochrane Library, Web of Science, Embase, Scopus, OvidSP, and ProQuest Dissertations & Theses databases from January 1, 1995 to December 2, 2016 and selected studies written in English that assessed plasma free MNs in the diagnosis of PPGL. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to evaluate the quality of the included studies. We calculated pooled sensitivities, specificities, positive and negative likelihood ratios, diagnostic odds ratios (DORs) and areas under curve (AUCs) with their 95% confidence intervals (95% CIs). Heterogeneity was assessed by I 2 . To identify the source of heterogeneity, we evaluated the threshold effect and performed a meta-regression. Deeks' funnel plot was selected for investigating any potential publication bias. Although the combination of metanephrine (MN) and normetanephrine (NMN) carried lower specificity (0.94, 95% CI 0.90-0.97) than NMN (0.97, 95% CI 0.92-0.99), NMN was generally more accurate than individual tests, with the highest AUC (0.99, 95% CI 0.97-0.99), DOR (443.35, 95% CI 216.9-906.23), and pooled sensitivity (0.97, 95% CI 0.94-0.98) values. Threshold effect and meta-regression analyses showed that different cut-offs, blood sampling positions, study types and test methods contributed to heterogeneity. This meta-analysis suggested an effective value for combined plasma free MNs for the diagnosis of PPGL, but testing for MNs requires more standardization using tightly regulated studies. AUC = area under curve; CI = confidence interval; DOR = diagnostic odds ratio; EIA = enzyme immunoassay; LC-ECD = liquid chromatography-electrochemical detection; LC-MS/MS = liquid chromatography-tandem mass spectrometry; MN = metanephrine; NMN = normetaneprhine; PPGL = pheochromocytoma and paraganglioma; QUADAS-2 = Quality Assessment of Diagnostic Accuracy Studies 2.

Development and Validation of Limited-Sampling Strategies for Predicting Amoxicillin Pharmacokinetic and Pharmacodynamic Parameters

PubMed Central

Suarez-Kurtz, Guilherme; Ribeiro, Frederico Mota; Vicente, Flávio L.; Struchiner, Claudio J.

2001-01-01

Amoxicillin plasma concentrations (n = 1,152) obtained from 48 healthy subjects in two bioequivalence studies were used to develop limited-sampling strategy (LSS) models for estimating the area under the concentration-time curve (AUC), the maximum concentration of drug in plasma (Cmax), and the time interval of concentration above MIC susceptibility breakpoints in plasma (T>MIC). Each subject received 500-mg amoxicillin, as reference and test capsules or suspensions, and plasma concentrations were measured by a validated microbiological assay. Linear regression analysis and a “jack-knife” procedure revealed that three-point LSS models accurately estimated (R2, 0.92; precision, <5.8%) the AUC from 0 h to infinity (AUC0-∞) of amoxicillin for the four formulations tested. Validation tests indicated that a three-point LSS model (1, 2, and 5 h) developed for the reference capsule formulation predicts the following accurately (R2, 0.94 to 0.99): (i) the individual AUC0-∞ for the test capsule formulation in the same subjects, (ii) the individual AUC0-∞ for both reference and test suspensions in 24 other subjects, and (iii) the average AUC0-∞ following single oral doses (250 to 1,000 mg) of various amoxicillin formulations in 11 previously published studies. A linear regression equation was derived, using the same sampling time points of the LSS model for the AUC0-∞, but using different coefficients and intercept, for estimating Cmax. Bioequivalence assessments based on LSS-derived AUC0-∞'s and Cmax's provided results similar to those obtained using the original values for these parameters. Finally, two-point LSS models (R2 = 0.86 to 0.95) were developed for T>MICs of 0.25 or 2.0 μg/ml, which are representative of microorganisms susceptible and resistant to amoxicillin. PMID:11600352

Measurement of serum isoform [-2]proPSA derivatives shows superior accuracy to magnetic resonance imaging in the diagnosis of prostate cancer in patients with a total prostate-specific antigen level of 2-10 ng/ml.

PubMed

Furuya, Kazuhiro; Kawahara, Takashi; Narahara, Masaki; Tokita, Takashi; Fukui, Sachi; Imano, Masashi; Mitome, Taku; Ito, Yusuke; Izumi, Koji; Osaka, Kimito; Yokomizo, Yumiko; Hayashi, Narihiko; Hasumi, Hisashi; Nawata, Shintaro; Kawano, Tsuyoshi; Yao, Masahiro; Uemura, Hiroji

2017-08-01

More accurate diagnostic procedures for prostate cancer are needed to avoid unnecessary biopsy due to the low specificity of prostate-specific antigen (PSA). Recent studies showed that the percentage of serum isoform [-2]proPSA (p2PSA) to free PSA (%p2PSA), the Prostate Health Index (PHI) and magnetic resonance imaging (MRI) were more accurate than PSA. The aim of this study was to test the accuracy of %p2PSA, PHI and MRI in discriminating patients with and without prostate cancer. The subjects were 50 consecutive men with a PSA level of 2.0-10.0 ng/ml, who underwent prostate biopsy from October 2012 to July 2014. These patients underwent multiparametric MRI before biopsy, and their serum samples were measured for PSA, free PSA and p2PSA. The sensitivity, specificity and accuracy of PHI, %p2PSA and MRI were compared with PSA in the diagnosis of biopsy-confirmed prostate cancer. In a univariate analysis, %p2PSA [area under the curve (AUC): 0.811] and PHI (AUC 0.795) were more accurate than MRI (AUC: 0.583) and PSA (AUC: 0.554) for prostate cancer detection. At 60% sensitivity, the specificity of PHI (76.5%) was higher than that of MRI (52.9%). For significant cancer detection, %p2PSA (AUC: 0.745), PHI (AUC: 0.791) and MRI (AUC: 0.739) were marginally more accurate than PSA (AUC: 0.696). At 85% sensitivity, the specificity of MRI (62.1%) was higher than that of PHI (34.5%). PHI and %p2PSA can be used for screening the general population and MRI can be used for detection of significant cancer in patients suspected, from screening tests, of having prostate cancer.

Pharmacokinetics and Biliary Excretion of Fisetin in Rats.

PubMed

Huang, Miao-Chan; Hsueh, Thomas Y; Cheng, Yung-Yi; Lin, Lie-Chwen; Tsai, Tung-Hu

2018-06-14

The hypothesis of this study is that fisetin and phase II conjugated forms of fisetin may partly undergo biliary excretion. To investigate this hypothesis, male Sprague-Dawley rats were used for the experiment, and their bile ducts were cannulated with polyethylene tubes for bile sampling. The pharmacokinetic results demonstrated that the average area-under-the-curve (AUC) ratios ( k (%) = AUC conjugate /AUC free-form ) of fisetin, its glucuronides, and its sulfates were 1:6:21 in plasma and 1:4:75 in bile, respectively. Particularly, the sulfated metabolites were the main forms that underwent biliary excretion. The biliary excretion rate ( k BE (%) = AUC bile /AUC plasma ) indicates the amount of fisetin eliminated by biliary excretion. The biliary excretion rates of fisetin, its glucuronide conjugates, and its sulfate conjugates were approximately 144, 109, and 823%, respectively, after fisetin administration (30 mg/kg, iv). Furthermore, biliary excretion of fisetin is mediated by P-glycoprotein.

Balancing vancomycin efficacy and nephrotoxicity: should we be aiming for trough or AUC/MIC?

PubMed

Patel, Karisma; Crumby, Ashley S; Maples, Holly D

2015-04-01

Sixty years later, the question that still remains is how to appropriately utilize vancomycin in the pediatric population. The Infectious Diseases Society of America published guidelines in 2011 that provide guidance for dosing and monitoring of vancomycin in adults and pediatrics. However, goal vancomycin trough concentrations of 15-20 μg/mL for invasive infections caused by methicillin-resistant Staphylococcus aureus were based primarily on adult pharmacokinetic and pharmacodynamic data that achieved an area under the curve to minimum inhibitory concentration ratio (AUC/MIC) of ≥400. Recent pediatric literature shows that vancomycin trough concentrations needed to achieve the target AUC/MIC are different than the adult goal troughs cited in the guidelines. This paper addresses several thoughts, including the role of vancomycin AUC/MIC in dosing strategies and safety monitoring, consistency in laboratory reporting, and future directions for calculating AUC/MIC in pediatrics.

Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality: A systematic review and meta-analysis.

PubMed

Gagné, Mathieu; Moore, Lynne; Beaudoin, Claudia; Batomen Kuimi, Brice Lionel; Sirois, Marie-Josée

2016-03-01

The International Classification of Diseases (ICD) is the main classification system used for population-based injury surveillance activities but does not contain information on injury severity. ICD-based injury severity measures can be empirically derived or mapped, but no single approach has been formally recommended. This study aimed to compare the performance of ICD-based injury severity measures to predict in-hospital mortality among injury-related admissions. A systematic review and a meta-analysis were conducted. MEDLINE, EMBASE, and Global Health databases were searched from their inception through September 2014. Observational studies that assessed the performance of ICD-based injury severity measures to predict in-hospital mortality and reported discriminative ability using the area under a receiver operating characteristic curve (AUC) were included. Metrics of model performance were extracted. Pooled AUC were estimated under random-effects models. Twenty-two eligible studies reported 72 assessments of discrimination on ICD-based injury severity measures. Reported AUC ranged from 0.681 to 0.958. Of the 72 assessments, 46 showed excellent (0.80 ≤ AUC < 0.90) and 6 outstanding (AUC ≥ 0.90) discriminative ability. Pooled AUC for ICD-based Injury Severity Score (ICISS) based on the product of traditional survival proportions was significantly higher than measures based on ICD mapped to Abbreviated Injury Scale (AIS) scores (0.863 vs. 0.825 for ICDMAP-ISS [p = 0.005] and ICDMAP-NISS [p = 0.016]). Similar results were observed when studies were stratified by the type of data used (trauma registry or hospital discharge) or the provenance of survival proportions (internally or externally derived). However, among studies published after 2003 the Trauma Mortality Prediction Model based on ICD-9 codes (TMPM-9) demonstrated superior discriminative ability than ICISS using the product of traditional survival proportions (0.850 vs. 0.802, p = 0.002). Models generally showed poor calibration. ICISS using the product of traditional survival proportions and TMPM-9 predict mortality more accurately than those mapped to AIS codes and should be preferred for describing injury severity when ICD is used to record injury diagnoses. Systematic review and meta-analysis, level III.

SU-D-204-04: Correlations Between Dosimetric Indices and Follow-Up Data for Salivary Glands Six Months After Radiation Therapy for Head and Neck Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chera, B; Price, A; Kostich, M

Purpose: To investigate the correlation between different dosimetric indices of salivary glands (as separate or combined structures) to patient-reported dry mouth 6 months post radiotherapy using the novel patient reported outcome version of the CTCAE (PRO-CTCAE). Methods: Forty-three patients with oropharyngeal squamous cell carcinoma were treated on a prospective multi-institutional study. All patients received de-intensified 60 Gy intensity modulated radiotherapy. Dosimetric constraints were used for the salivary glands (e.g. mean dose to the contralateral-parotid < 26 Gy). We investigated correlations of individual patient dosimetric data of the parotid and submandibular glands (as separate or combined structures) to their self-reported 6more » month post-treatment dry mouth responses. Moderate dry mouth responses were most prevalent and were used as the clinical endpoint indicating response. The correlation of Dmean, Dmax and a range of dosevolume (VD) points were assessed through the area under the Receiver Operating Characteristic curve (ROC) and Odds Ratios (OR). Results: Patients reporting non/mild dry mouth response (N=22) had average Dmean = 19.6 ± 6.2Gy to the contralateral-parotid compared to an average Dmean = 28.0 ± 8.3Gy and an AUC = 0.758 for the patients reporting moderate/severe/very severe dry mouth (N=21). Analysis of the range of VD’s for patients who had reported dry mouth showed that for the contralateral-parotid the indices V18 through V22 had the highest area under the curves (AUC) (0.762 – 0.772) compared to a more traditional dosimetric index V30, which had an AUC = 0.732. The highest AUC was observed for the combination of contralateral parotid and contralateral submandibular glands, for which V16 through V28 had AUC = 0.801 – 0.834. Conclusion: Patients who report moderate/severe/very severe dry mouth 6 months post radiotherapy had on average higher Dmean. The V16-V28 of the combination of the contralateral glands showed the highest correlation with the clinical endpoint.« less

The percentage of prostate-specific antigen (PSA) isoform [-2]proPSA and the Prostate Health Index improve the diagnostic accuracy for clinically relevant prostate cancer at initial and repeat biopsy compared with total PSA and percentage free PSA in men aged ≤65 years.

PubMed

Boegemann, Martin; Stephan, Carsten; Cammann, Henning; Vincendeau, Sébastien; Houlgatte, Alain; Jung, Klaus; Blanchet, Jean-Sebastien; Semjonow, Axel

2016-01-01

To prospectively test the diagnostic accuracy of the percentage of prostate specific antigen (PSA) isoform [-2]proPSA (%p2PSA) and the Prostate Health Index (PHI), and to determine their role for discrimination between significant and insignificant prostate cancer at initial and repeat prostate biopsy in men aged ≤65 years. The diagnostic performance of %p2PSA and PHI were evaluated in a multicentre study. In all, 769 men aged ≤65 years scheduled for initial or repeat prostate biopsy were recruited in four sites based on a total PSA (t-PSA) level of 1.6-8.0 ng/mL World Health Organization (WHO) calibrated (2-10 ng/mL Hybritech-calibrated). Serum samples were measured for the concentration of t-PSA, free PSA (f-PSA) and p2PSA with Beckman Coulter immunoassays on Access-2 or DxI800 instruments. PHI was calculated as (p2PSA/f-PSA × √t-PSA). Uni- and multivariable logistic regression models and an artificial neural network (ANN) were complemented by decision curve analysis (DCA). In univariate analysis %p2PSA and PHI were the best predictors of prostate cancer detection in all patients (area under the curve [AUC] 0.72 and 0.73, respectively), at initial (AUC 0.67 and 0.69) and repeat biopsy (AUC 0.74 and 0.74). t-PSA and %f-PSA performed less accurately for all patients (AUC 0.54 and 0.62). For detection of significant prostate cancer (based on Prostate Cancer Research International Active Surveillance [PRIAS] criteria) the %p2PSA and PHI equally demonstrated best performance (AUC 0.70 and 0.73) compared with t-PSA and %f-PSA (AUC 0.54 and 0.59). In multivariate analysis PHI we added to a base model of age, prostate volume, digital rectal examination, t-PSA and %f-PSA. PHI was strongest in predicting prostate cancer in all patients, at initial and repeat biopsy and for significant prostate cancer (AUC 0.73, 0.68, 0.78 and 0.72, respectively). In DCA for all patients the ANN showed the broadest threshold probability and best net benefit. PHI as single parameter and the base model + PHI were equivalent with threshold probability and net benefit nearing those of the ANN. For significant cancers the ANN was the strongest parameter in DCA. The present multicentre study showed that %p2PSA and PHI have a superior diagnostic performance for detecting prostate cancer in the PSA range of 1.6-8.0 ng/mL compared with t-PSA and %f-PSA at initial and repeat biopsy and for predicting significant prostate cancer in men aged ≤65 years. They are equally superior for counselling patients before biopsy. © 2015 The Authors BJU International © 2015 BJU International Published by John Wiley & Sons Ltd.

Association between Vancomycin Day 1 Exposure Profile and Outcomes among Patients with Methicillin-Resistant Staphylococcus aureus Infective Endocarditis

PubMed Central

Casapao, Anthony M.; Lodise, Thomas P.; Davis, Susan L.; Claeys, Kimberly C.; Kullar, Ravina; Levine, Donald P.

2015-01-01

Given the critical importance of early appropriate therapy, a retrospective cohort (2002 to 2013) was performed at the Detroit Medical Center to evaluate the association between the day 1 vancomycin exposure profile and outcomes among patients with MRSA infective endocarditis (IE). The day 1 vancomycin area under the concentration-time curve (AUC0–24) and the minimum concentration at 24 h (Cmin 24) was estimated for each patient using the Bayesian procedure in ADAPT 5, an approach shown to accurately predict the vancomycin exposure with low bias and high precision with limited pharmacokinetic sampling. Initial MRSA isolates were collected and vancomycin MIC was determined by broth microdilution (BMD) and Etest. The primary outcome was failure, defined as persistent bacteremia (≥7 days) or 30-day attributable mortality. Classification and regression tree analysis (CART) was used to determine the vancomycin exposure variables associated with an increased probability of failure. In total, 139 patients met study criteria; 76.3% had right-sided IE, 16.5% had left-sided IE, and 7.2% had both left and right-sided IE. A total of 89/139 (64%) experienced failure by composite definition. In the CART analysis, failure was more pronounced in patients with an AUC0–24/MIC as determined by BMD of ≤600 relative to those with AUC0–24/MIC as determined by BMD of >600 (69.8% versus 54.7%, respectively, P = 0.073). In the logistic regression analysis, an AUC/MIC as determined by BMD of ≤600 (adjusted odds ratio, 2.3; 95% confidence interval, 1.01 to 5.37; P = 0.047) was independently associated with failure. Given the retrospective nature of the present study, further prospective studies are required but these data suggest that patients with an AUC0–24/MIC as determined by BMD of ≤600 present an increased risk of failure. PMID:25753631

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

PubMed

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease.

PubMed

Collij, Lyduine E; Heeman, Fiona; Kuijer, Joost P A; Ossenkoppele, Rik; Benedictus, Marije R; Möller, Christiane; Verfaillie, Sander C J; Sanz-Arigita, Ernesto J; van Berckel, Bart N M; van der Flier, Wiesje M; Scheltens, Philip; Barkhof, Frederik; Wink, Alle Meije

2016-12-01

Purpose To investigate whether multivariate pattern recognition analysis of arterial spin labeling (ASL) perfusion maps can be used for classification and single-subject prediction of patients with Alzheimer disease (AD) and mild cognitive impairment (MCI) and subjects with subjective cognitive decline (SCD) after using the W score method to remove confounding effects of sex and age. Materials and Methods Pseudocontinuous 3.0-T ASL images were acquired in 100 patients with probable AD; 60 patients with MCI, of whom 12 remained stable, 12 were converted to a diagnosis of AD, and 36 had no follow-up; 100 subjects with SCD; and 26 healthy control subjects. The AD, MCI, and SCD groups were divided into a sex- and age-matched training set (n = 130) and an independent prediction set (n = 130). Standardized perfusion scores adjusted for age and sex (W scores) were computed per voxel for each participant. Training of a support vector machine classifier was performed with diagnostic status and perfusion maps. Discrimination maps were extracted and used for single-subject classification in the prediction set. Prediction performance was assessed with receiver operating characteristic (ROC) analysis to generate an area under the ROC curve (AUC) and sensitivity and specificity distribution. Results Single-subject diagnosis in the prediction set by using the discrimination maps yielded excellent performance for AD versus SCD (AUC, 0.96; P < .01), good performance for AD versus MCI (AUC, 0.89; P < .01), and poor performance for MCI versus SCD (AUC, 0.63; P = .06). Application of the AD versus SCD discrimination map for prediction of MCI subgroups resulted in good performance for patients with MCI diagnosis converted to AD versus subjects with SCD (AUC, 0.84; P < .01) and fair performance for patients with MCI diagnosis converted to AD versus those with stable MCI (AUC, 0.71; P > .05). Conclusion With automated methods, age- and sex-adjusted ASL perfusion maps can be used to classify and predict diagnosis of AD, conversion of MCI to AD, stable MCI, and SCD with good to excellent accuracy and AUC values. © RSNA, 2016.

Differentiating pheochromocytoma from lipid-poor adrenocortical adenoma by CT texture analysis: feasibility study.

PubMed

Zhang, Gu-Mu-Yang; Shi, Bing; Sun, Hao; Jin, Zheng-Yu; Xue, Hua-Dan

2017-09-01

To investigate the feasibility of using CT texture analysis (CTTA) to differentiate pheochromocytoma from lipid-poor adrenocortical adenoma (lp-ACA). Ninety-eight pheochromocytomas and 66 lp-ACAs were included in this retrospective study. CTTA was performed on unenhanced and enhanced images. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different for the objective. Diagnostic accuracies were evaluated using the cutoff values of texture parameters with the highest AUCs. Compared to lp-ACAs, pheochromocytomas had significantly higher mean gray-level intensity (Mean), entropy, and mean of positive pixels (MPP), but lower skewness and kurtosis on unenhanced images (P < 0.001). On enhanced images, these texture-quantifiers followed a similar trend where Mean, entropy, and MPP were higher, but skewness and kurtosis were lower in pheochromocytomas. Standard deviation (SD) was also significantly higher in pheochromocytomas on enhanced images. Mean and MPP quantified from no filtration on unenhanced CT images yielded the highest AUC of 0.86 ± 0.03 (95% CI 0.81-0.91) at a cutoff value of 34.0 for Mean and MPP, respectively (sensitivity = 79.6%, specificity = 83.3%, accuracy = 81.1%). It was feasible to use CTTA to differentiate pheochromocytoma from lp-ACA.

Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging.

PubMed

Banerjee, Imon; Malladi, Sadhika; Lee, Daniela; Depeursinge, Adrien; Telli, Melinda; Lipson, Jafi; Golden, Daniel; Rubin, Daniel L

2018-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is sensitive but not specific to determining treatment response in early stage triple-negative breast cancer (TNBC) patients. We propose an efficient computerized technique for assessing treatment response, specifically the residual tumor (RT) status and pathological complete response (pCR), in response to neoadjuvant chemotherapy. The proposed approach is based on Riesz wavelet analysis of pharmacokinetic maps derived from noninvasive DCE-MRI scans, obtained before and after treatment. We compared the performance of Riesz features with the traditional gray level co-occurrence matrices and a comprehensive characterization of the lesion that includes a wide range of quantitative features (e.g., shape and boundary). We investigated a set of predictive models ([Formula: see text]) incorporating distinct combinations of quantitative characterizations and statistical models at different time points of the treatment and some area under the receiver operating characteristic curve (AUC) values we reported are above 0.8. The most efficient models are based on first-order statistics and Riesz wavelets, which predicted RT with an AUC value of 0.85 and pCR with an AUC value of 0.83, improving results reported in a previous study by [Formula: see text]. Our findings suggest that Riesz texture analysis of TNBC lesions can be considered a potential framework for optimizing TNBC patient care.

Pharmacokinetics and bioequivalence study of a fixed dose combination of rabeprazole and itopride in healthy Indian volunteers.

PubMed

Sahoo, Bijay Kumar; Das, Ayan; Agarwal, Sangita; Bhaumik, Uttam; Bose, Anirbandeep; Ghosh, Debotri; Roy, Bikash; Pal, Tapan Kumar

2009-01-01

The aim of the present study was to compare the pharmacokinetics of rabeprazole (CAS 117976-89-3) and itopride (CAS 122898-67-3) after oral administration of a rabeprazole (20 mg)-itopride (150 mg) fixed dose combination (FDC) in healthy human volunteers. The bioequivalence of two formulations (test and reference) was determined in 12 healthy Indian male volunteers (age: 25.25 +/- 4.69 years; weight: 60.50 +/- 5.04 kg) in a randomized, single-dose, two-period, two-treatment crossover study. Both formulations were administered orally as a single dose, with the treatments separated by a washout period of 1 week. Rabeprazole and itopride plasma levels were determined by a validated HPLC method using UV detection. The formulations were compared using the pharmacokinetic parameters area under the plasma concentration-time curve (AUC(0-t)), area under the plasma concentration-time curve from zero to infinity (AUC(0-infinity)) and peak plasma concentration (Cmax). General linear model (GLM) procedures were used in which sources of variation were subject, treatment and period. The results indicated that there were no statistically significant differences (P > 0.05) between the logarithmically transformed AUC(0-infinity) and Cmax values between test and reference formulation. The 90% confidence interval for the ratio of the logarithmically transformed AUC(0-t), AUC(0-infinity) and Cmax were within the bioequivalence limits of 0.8-1.25 and the relative bioavailability of rabeprazole and itopride test and reference formulations was 98.24 and 93.65%, respectively.

Analysis of glottal source parameters in Parkinsonian speech.

PubMed

Hanratty, Jane; Deegan, Catherine; Walsh, Mary; Kirkpatrick, Barry

2016-08-01

Diagnosis and monitoring of Parkinson's disease has a number of challenges as there is no definitive biomarker despite the broad range of symptoms. Research is ongoing to produce objective measures that can either diagnose Parkinson's or act as an objective decision support tool. Recent research on speech based measures have demonstrated promising results. This study aims to investigate the characteristics of the glottal source signal in Parkinsonian speech. An experiment is conducted in which a selection of glottal parameters are tested for their ability to discriminate between healthy and Parkinsonian speech. Results for each glottal parameter are presented for a database of 50 healthy speakers and a database of 16 speakers with Parkinsonian speech symptoms. Receiver operating characteristic (ROC) curves were employed to analyse the results and the area under the ROC curve (AUC) values were used to quantify the performance of each glottal parameter. The results indicate that glottal parameters can be used to discriminate between healthy and Parkinsonian speech, although results varied for each parameter tested. For the task of separating healthy and Parkinsonian speech, 2 out of the 7 glottal parameters tested produced AUC values of over 0.9.

Short-term vs. long-term heart rate variability in ischemic cardiomyopathy risk stratification.

PubMed

Voss, Andreas; Schroeder, Rico; Vallverdú, Montserrat; Schulz, Steffen; Cygankiewicz, Iwona; Vázquez, Rafael; Bayés de Luna, Antoni; Caminal, Pere

2013-01-01

In industrialized countries with aging populations, heart failure affects 0.3-2% of the general population. The investigation of 24 h-ECG recordings revealed the potential of nonlinear indices of heart rate variability (HRV) for enhanced risk stratification in patients with ischemic heart failure (IHF). However, long-term analyses are time-consuming, expensive, and delay the initial diagnosis. The objective of this study was to investigate whether 30 min short-term HRV analysis is sufficient for comparable risk stratification in IHF in comparison to 24 h-HRV analysis. From 256 IHF patients [221 at low risk (IHFLR) and 35 at high risk (IHFHR)] (a) 24 h beat-to-beat time series (b) the first 30 min segment (c) the 30 min most stationary day segment and (d) the 30 min most stationary night segment were investigated. We calculated linear (time and frequency domain) and nonlinear HRV analysis indices. Optimal parameter sets for risk stratification in IHF were determined for 24 h and for each 30 min segment by applying discriminant analysis on significant clinical and non-clinical indices. Long- and short-term HRV indices from frequency domain and particularly from nonlinear dynamics revealed high univariate significances (p < 0.01) discriminating between IHFLR and IHFHR. For multivariate risk stratification, optimal mixed parameter sets consisting of 5 indices (clinical and nonlinear) achieved 80.4% AUC (area under the curve of receiver operating characteristics) from 24 h HRV analysis, 84.3% AUC from first 30 min, 82.2 % AUC from daytime 30 min and 81.7% AUC from nighttime 30 min. The optimal parameter set obtained from the first 30 min showed nearly the same classification power when compared to the optimal 24 h-parameter set. As results from stationary daytime and nighttime, 30 min segments indicate that short-term analyses of 30 min may provide at least a comparable risk stratification power in IHF in comparison to a 24 h analysis period.

Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation.

PubMed

Zhao, Jianhua; Lui, Harvey; Kalia, Sunil; Zeng, Haishan

2015-11-01

In a recent study, we have demonstrated that real-time Raman spectroscopy could be used for skin cancer diagnosis. As a translational study, the objective of this study is to validate previous findings through a completely independent clinical test. In total, 645 confirmed cases were included in the analysis, including a cohort of 518 cases from a previous study, and an independent cohort of 127 new cases. Multi-variant statistical data analyses including principal component with general discriminant analysis (PC-GDA) and partial least squares (PLS) were used separately for lesion classification, which generated similar results. When the previous cohort (n = 518) was used as training and the new cohort (n = 127) was used as testing, the area under the receiver operating characteristic curve (ROC AUC) was found to be 0.889 (95 % CI 0.834-0.944; PLS); when the two cohorts were combined, the ROC AUC was 0.894 (95 % CI 0.870-0.918; PLS) with the narrowest confidence intervals. Both analyses were comparable to the previous findings, where the ROC AUC was 0.896 (95 % CI 0.846-0.946; PLS). The independent study validates that real-time Raman spectroscopy could be used for automatic in vivo skin cancer diagnosis with good accuracy.

Biological and analytical stability of a peripheral blood gene expression score for obstructive coronary artery disease in the PREDICT and COMPASS studies.

PubMed

Daniels, Susan E; Beineke, Philip; Rhees, Brian; McPherson, John A; Kraus, William E; Thomas, Gregory S; Rosenberg, Steven

2014-10-01

A gene expression score (GES) for obstructive coronary artery disease (CAD) has been validated in two multicenter studies. Receiver-operating characteristics (ROC) analysis of the GES on an expanded Personalized Risk Evaluation and Diagnosis in the Coronary Tree (PREDICT) cohort (NCT no. 00500617) with CAD defined by quantitative coronary angiography (QCA) or clinical reads yielded similar performance (area under the curve (AUC)=0.70, N=1,502) to the original validation cohort (AUC=0.70, N=526). Analysis of 138 non-Caucasian and 1,364 Caucasian patients showed very similar performance (AUCs=0.72 vs. 0.70). To assess analytic stability, stored samples of the original validation cohort (N=526) was re-tested after 5 years, and the mean score changed from 20.3 to 19.8 after 5 years (N=501, 95 %). To assess patient scores over time, GES was determined on samples from 173 Coronary Obstruction Detection by Molecular Personalized Gene Expression (COMPASS) study (NCT no. 01117506) patients at approximately 1 year post-enrollment. Mean scores increased slightly from 15.9 to 17.3, corresponding to a 2.5 % increase in obstructive CAD likelihood. Changes in cardiovascular medications did not show a significant change in GES.

Adapted Finnegan scoring list for observation of anti-depressant exposed infants.

PubMed

Kieviet, Noera; van Ravenhorst, Mariëtte; Dolman, Koert M; van de Ven, Peter M; Heres, Marion; Wennink, Hanneke; Honig, Adriaan

2015-01-01

The Finnegan scoring list (FSL) is widely used to screen for poor neonatal adaptation in infants exposed to anti-depressants in utero. However, the large number of FSL-items and differential weighing of each item is time consuming. The aim of this study was to shorten and simplify the FSL yet preserving its clinimetric properties. This observational study examined infants exposed to an anti-depressant during pregnancy admitted for at least 72 h on a maternity ward. Trained nurses completed the FSL three times daily. Items for the adapted FSL were selected through forward analysis whereby the number of selected items was based on the area under the curve (AUC). Internal validity was assessed by cross-validation. 183 infants met the inclusion criteria. By forward analysis eight equally-weighed items resulted in an AUC of 0.91. In cross-validation, the mean AUC was 0.89 for 8 items. This adapted FSL had a sensitivity of 97.7% and specificity of 37.0% and a sensitivity of 41.9% and specificity of 86.2% regarding a cut-off of, respectively, 1 and 2. An adapted FSL with eight equally-weighed items has acceptable clinimetric properties and can serve as an easy to apply screening tool in infants exposed to anti-depressants during pregnancy.

A Meta-analysis for the Diagnostic Performance of Transient Elastography for Clinically Significant Portal Hypertension.

PubMed

You, Myung-Won; Kim, Kyung Won; Pyo, Junhee; Huh, Jimi; Kim, Hyoung Jung; Lee, So Jung; Park, Seong Ho

2017-01-01

We aimed to evaluate the correlation between liver stiffness measurement using transient elastography (TE-LSM) and hepatic venous pressure gradient and the diagnostic performance of TE-LSM in assessing clinically significant portal hypertension through meta-analysis. Eleven studies were included from thorough literature research and selection processes. The summary correlation coefficient was 0.783 (95% confidence interval [CI], 0.737-0.823). Summary sensitivity, specificity and area under the hierarchical summary receiver operating characteristic curve (AUC) were 87.5% (95% CI, 75.8-93.9%), 85.3 % (95% CI, 76.9-90.9%) and 0.9, respectively. The subgroup with low cut-off values of 13.6-18 kPa had better summary estimates (sensitivity 91.2%, specificity 81.3% and partial AUC 0.921) than the subgroup with high cut-off values of 21-25 kPa (sensitivity 71.2%, specificity 90.9% and partial AUC 0.769). In summary, TE-LSM correlated well with hepatic venous pressure gradient and represented good diagnostic performance in diagnosing clinically significant portal hypertension. For use as a sensitive screening tool, we propose using low cut-off values of 13.6-18 kPa in TE-LSM. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Which anthropometric measures best indicate type 2 diabetes among Russian, Somali and Kurdish origin migrants in Finland? A cross-sectional study.

PubMed

Skogberg, Natalia; Laatikainen, Tiina; Lundqvist, Annamari; Lilja, Eero; Härkänen, Tommi; Koponen, Päivikki

2018-05-17

To compare the performance of body mass index (BMI), waist-to-height ratio (WHtR), waist circumference (WC) and waist-to-hip ratio (WHR) in detecting type 2 diabetes among Russian, Somali and Kurdish (born in Iraq/Iran) origin migrants and Finns. Cross-sectional study comparing health examination survey data of Russian, Somali and Kurdish origin migrants (n=917) aged 30-64 years who took part in the Migrant Health and Wellbeing Survey with the general Finnish population in the Health 2011 Survey (n=887). Participants were randomly selected from the National Population Register. Six cities in Finland, where a substantial majority of migrants live. Anthropometric measures included objectively measured BMI, WHtR, WC and WHR. Type 2 diabetes was defined based on self-report, laboratory measures of glycated haemoglobin and register data. Test performance was assessed using receiver operating characteristics curves, using area under the curve (AUC) as a measure of accuracy. Among Finns, test performance was highest for WC (AUC=0.81, 95% CI 0.74 to 0.87) and WHtR (AUC=0.81, 95% CI 0.75 to 0.87). Test performance was similar for BMI (AUC=0.80, 95% CI 0.67 to 0.92), WC (AUC=0.79, 95% CI 0.67 to 0.91) and WHtR (AUC=0.70, 95% CI 0.66 to 0.93) among Russians. WC and WHtR had highest test performance also among Somali (AUC=0.74, 95% CI 0.64 to 0.84 for WC and AUC=0.75, 95% CI 0.65 to 0.85 for WHtR) and Kurds (AUC=0.71, 95% CI 0.61 to 0.81 for WC and AUC=0.70, 95% CI 0.59 to 0.80 for WHtR).Among migrants, WHR had the poorest test performance. WC and WHtR performed overall the best across all study groups, however, accuracy of detection was lower particularly among Somali and Kurds. Currently used diabetes risk assessment tools assume a strong association between anthropometrics and diabetes. These tools need to be validated among non-Western populations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Which anthropometric measures best indicate type 2 diabetes among Russian, Somali and Kurdish origin migrants in Finland? A cross-sectional study

PubMed Central

Laatikainen, Tiina; Lundqvist, Annamari; Lilja, Eero; Härkänen, Tommi; Koponen, Päivikki

2018-01-01

Objectives To compare the performance of body mass index (BMI), waist-to-height ratio (WHtR), waist circumference (WC) and waist-to-hip ratio (WHR) in detecting type 2 diabetes among Russian, Somali and Kurdish (born in Iraq/Iran) origin migrants and Finns. Design and participants Cross-sectional study comparing health examination survey data of Russian, Somali and Kurdish origin migrants (n=917) aged 30–64 years who took part in the Migrant Health and Wellbeing Survey with the general Finnish population in the Health 2011 Survey (n=887). Participants were randomly selected from the National Population Register. Setting Six cities in Finland, where a substantial majority of migrants live. Outcome measures Anthropometric measures included objectively measured BMI, WHtR, WC and WHR. Type 2 diabetes was defined based on self-report, laboratory measures of glycated haemoglobin and register data. Test performance was assessed using receiver operating characteristics curves, using area under the curve (AUC) as a measure of accuracy. Results Among Finns, test performance was highest for WC (AUC=0.81, 95% CI 0.74 to 0.87) and WHtR (AUC=0.81, 95% CI 0.75 to 0.87). Test performance was similar for BMI (AUC=0.80, 95% CI 0.67 to 0.92), WC (AUC=0.79, 95% CI 0.67 to 0.91) and WHtR (AUC=0.70, 95% CI 0.66 to 0.93) among Russians. WC and WHtR had highest test performance also among Somali (AUC=0.74, 95% CI 0.64 to 0.84 for WC and AUC=0.75, 95% CI 0.65 to 0.85 for WHtR) and Kurds (AUC=0.71, 95% CI 0.61 to 0.81 for WC and AUC=0.70, 95% CI 0.59 to 0.80 for WHtR). Among migrants, WHR had the poorest test performance. Conclusion WC and WHtR performed overall the best across all study groups, however, accuracy of detection was lower particularly among Somali and Kurds. Currently used diabetes risk assessment tools assume a strong association between anthropometrics and diabetes. These tools need to be validated among non-Western populations. PMID:29773697

Sedation and mechanical antinociception after intravenous administration of detomidine in donkeys: a dosage-effect study.

PubMed

Lizarraga, Ignacio; Castillo-Alcala, Fernanda; Varner, Kelley M; Robinson, Lauren S

2015-02-21

There is limited, useful, scientific information on detomidine in donkeys. This study compared the effects of intravenous saline, detomidine (10, 13.5, 17 and 20 μg/kg) and acepromazine (50 μg/kg) in donkeys by computing areas under the curve for 0-30, 30-60 and 60-120 minutes (AUC0-30, AUC30-60 and AUC60-120) for sedation scores, head heights and mechanical nociceptive thresholds (MNTs). For sedation scores, all detomidine treatments, except 10 μg/kg, increased AUC0-30 values compared with saline, and AUC0-30 values were larger for 17 μg/kg detomidine than for acepromazine. All head height AUC values were lower for detomidine than for saline (except AUC60-120 for 10 μg/kg detomidine) and acepromazine (except AUC0-30 for 10 and 20 μg/kg detomidine, and AUC60-120 for 10 μg/kg detomidine). For MNTs, all detomidine treatments increased AUC0-30 and AUC30-60 values compared with saline and acepromazine; AUC30-60 values were smaller for 10 μg/kg than for 17 and 20 μg/kg detomidine. MNT AUC60-120 values were larger for 20 μg/kg detomidine than for saline, 10 μg/kg detomidine and acepromazine. Detomidine induced sedation and antinociception, but only antinociception was dosage dependent. Selection of detomidine dosage for donkeys may depend on the required duration of sedation and/or degree of analgesia. British Veterinary Association.

Prediction of small-for-gestational-age neonate by third-trimester fetal biometry and impact of ultrasound-delivery interval.

PubMed

Reboul, Q; Delabaere, A; Luo, Z C; Nuyt, A-M; Wu, Y; Chauleur, C; Fraser, W; Audibert, F

2017-03-01

To compare third-trimester ultrasound screening methods to predict small-for-gestational age (SGA), and to evaluate the impact of the ultrasound-delivery interval on screening performance. In this prospective study, data were collected from a multicenter singleton cohort study investigating the links between various exposures during pregnancy with birth outcome and later health in children. We included women, recruited in the first trimester, who had complete outcome data and had undergone third-trimester ultrasound examination. Demographic, clinical and biological variables were also collected from both parents. We compared prediction of delivery of a SGA neonate (birth weight < 10 th percentile) by the following methods: abdominal circumference (AC) Z-score based on Hadlock curves (Hadlock AC), on INTERGROWTH-21 st Project curves (Intergrowth AC) and on Salomon curves (Salomon AC); estimated fetal weight (EFW) Z-score based on Hadlock curves (Hadlock EFW) and on customized curves from Gardosi (Gardosi EFW); and fetal growth velocity based on change in AC between second and third trimesters (FGVAC). We also assessed the following ultrasound-delivery intervals: ≤ 4 weeks, ≤ 6 weeks and ≤ 10 weeks. Third-trimester ultrasound was performed in 1805 patients with complete outcome data, of whom 158 (8.8%) delivered a SGA neonate. Ultrasound examination was at a median gestational age of 32 (interquartile range, 31-33) weeks. The ultrasound-delivery interval was ≤ 4 weeks in 17.2% of cases, ≤ 6 weeks in 48.1% of cases and ≤ 10 weeks in 97.3% of cases. Areas under the receiver-operating characteristics curve (AUC) were 0.772 for Salomon AC, 0.768 for Hadlock EFW, 0.766 for Hadlock AC, 0.765 for Intergrowth AC, 0.708 for Gardosi EFW and 0.674 for FGVAC (all P < 0.0001). The screening method with the highest AUC for an ultrasound-delivery interval ≤ 4 weeks was Salomon AC (AUC, 0.856), ≤ 6 weeks was Hadlock AC (AUC, 0.824) and ≤ 10 weeks was Salomon AC (AUC, 0.780). At a fixed 10% false-positive rate, the best detection rates were 60.0%, 54.1% and 42.1% for intervals ≤ 4, ≤ 6 and ≤ 10 weeks, respectively. Third-trimester ultrasound measurements provide poor to moderate prediction of SGA. A shorter ultrasound-delivery interval provides better prediction than does a longer interval. Further studies are needed to test the effect of including maternal or biological characteristics in SGA screening. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Quantitative Assessment of Neovascularization after Indirect Bypass Surgery: Color-Coded Digital Subtraction Angiography in Pediatric Moyamoya Disease.

PubMed

Cho, H-H; Cheon, J-E; Kim, S-K; Choi, Y H; Kim, I-O; Kim, W S; Lee, S-M; You, S K; Shin, S-M

2016-05-01

For the postoperative follow-up in pediatric patients with Moyamoya disease, it is essential to evaluate the degree of neovascularization status. Our aim was to quantitatively assess the neovascularization status after bypass surgery in pediatric Moyamoya disease by using color-coded digital subtraction angiography. Time-attenuation intensity curves were generated at ROIs corresponding to surgical flap sites from color-coded DSA images of the common carotid artery, internal carotid artery, and external carotid artery angiograms obtained pre- and postoperatively in 32 children with Moyamoya disease. Time-to-peak and area under the curve values were obtained. Postoperative changes in adjusted time-to-peak (ΔTTP) and ratios of adjusted area under the curve changes (ΔAUC ratio) of common carotid artery, ICA, and external carotid artery angiograms were compared across clinical and angiographic outcome groups. To analyze diagnostic performance, we categorized clinical outcomes into favorable and unfavorable groups. The ΔTTP at the common carotid artery increased among clinical and angiographic outcomes, in that order, with significant differences (P = .003 and .005, respectively). The ΔAUC ratio at the common carotid artery and external carotid artery also increased, in that order, among clinical and angiographic outcomes with a significant difference (all, P = .000). The ΔAUC ratio of ICA showed no significant difference among clinical and angiographic outcomes (P = .418 and .424, respectively). The ΔTTP for the common carotid artery of >1.27 seconds and the ΔAUC ratio of >33.5% for the common carotid artery and 504% for the external carotid artery are revealed as optimal cutoff values between favorable and unfavorable groups. Postoperative changes in quantitative values obtained with color-coded DSA software showed a significant correlation with outcome scores and can be used as objective parameters for predicting the outcome in pediatric Moyamoya disease, with an additional cutoff value calculated through the receiver operating characteristic curve. © 2016 by American Journal of Neuroradiology.

Glucose and insulin do not decrease in a dose-dependent manner after increasing doses of mixed fibers that are consumed in muffins for breakfast.

PubMed

Willis, Holly J; Thomas, William; Eldridge, Alison L; Harkness, Laura; Green, Hilary; Slavin, Joanne L

2011-01-01

Conventional wisdom suggests that fiber consumption leads to lower postprandial glucose and insulin response. We hypothesized that increasing doses of mixed, viscous fiber would lower glucose and insulin levels in a dose-dependent manner. Healthy men (n = 10) and women (n = 10) with a body mass index of 24 ± 2 (mean ± SEM) participated in this double-blind, crossover study. On 4 separate visits, fasting subjects consumed an approximately 2093 kJ (500 calorie) muffin with 0, 4, 8, or 12 g of mixed fibers. Blood was drawn to measure glucose and insulin at regular intervals throughout a 3-hour test period. Area under the curve (AUC) glucose was significantly lower after 0 g of fiber than after 4, 8, or 12 g of fiber (arbitrary AUC units ± SEM: 25.3 ± 5.2 vs 44.6 ± 7.7, 49.7 ± 7.9, 51.5 ± 6.6, respectively; P < .006). Area under the curve glucose increased with increasing fiber doses (P for trend = .0003). Area under the curve insulin was higher after the 4-g dose than after the 0-, 8-, and 12-g doses (arbitrary AUC units ± SEM: 84.4 ± 8.0 vs 60.1 ± 6.5, 69.4 ± 8.7, 69.7 ± 8.5, respectively; P < .05); it did not change in a dose-dependent manner. Area under the curve glucose and AUC insulin did not correlate with each other. Glucose and insulin did not decrease in a dose-dependent manner after 0, 4, 8, and 12 g of mixed fibers were consumed in muffins for breakfast. The lack of differences was largely based on the individual variation in glucose response. Caution should be used when making general claims about the expected impact of fiber on glucose and insulin levels. Copyright © 2011 Elsevier Inc. All rights reserved.

Serum biomarkers as predictors of long-term outcome in severe traumatic brain injury: analysis from a randomized placebo-controlled Phase II clinical trial.

PubMed

Raheja, Amol; Sinha, Sumit; Samson, Neha; Bhoi, Sanjeev; Subramanian, Arulselvi; Sharma, Pushpa; Sharma, Bhawani Shankar

2016-09-01

OBJECTIVE There has been increased interest in the potential importance of biochemical parameters as predictors of outcome in severe traumatic brain injury (sTBI). METHODS Of 107 patients with sTBI (age 18-65 years with a Glasgow Coma Scale score of 4-8 presenting within 8 hours after injury) who were randomized for a placebo-controlled Phase II trial of progesterone with or without hypothermia, the authors serially analyzed serum biomarkers (S100-B, glial fibrillary acidic protein [GFAP], neuron-specific enolase [NSE], tumor necrosis factor-α, interleukin-6 [IL-6], estrogen [Eg], and progesterone [Pg]). This analysis was performed using the sandwich enzyme-linked immunosorbent assay technique at admission and 7 days later for 86 patients, irrespective of assigned group. The long-term predictive values of serum biomarkers for dichotomized Glasgow Outcome Scale (GOS) score, functional independence measure, and survival status at 6 and 12 months were analyzed using an adjusted binary logistic regression model and receiver operating characteristic curve. RESULTS A favorable GOS score (4-5) at 1 year was predicted by higher admission IL-6 (above 108.36 pg/ml; area under the curve [AUC] 0.69, sensitivity 52%, and specificity 78.6%) and Day 7 Pg levels (above 3.15 ng/ml; AUC 0.79, sensitivity 70%, and specificity 92.9%). An unfavorable GOS score (1-3) at 1 year was predicted by higher Day 7 GFAP levels (above 9.50 ng/ml; AUC 0.82, sensitivity 78.6%, and specificity 82.4%). Survivors at 1 year had significantly higher Day 7 Pg levels (above 3.15 ng/ml; AUC 0.78, sensitivity 66.7%, and specificity 90.9%). Nonsurvivors at 1 year had significantly higher Day 7 GFAP serum levels (above 11.14 ng/ml; AUC 0.81, sensitivity 81.8%, and specificity 88.9%) and Day 7 IL-6 serum levels (above 71.26 pg/ml; AUC 0.87, sensitivity 81.8%, and specificity 87%). In multivariate logistic regression analysis, independent predictors of outcome at 1 year were serum levels of Day 7 Pg (favorable GOS-OR 3.24, CI 1.5-7, p = 0.003; and favorable survival-OR 2, CI 1.2-3.5, p = 0.01); admission IL-6 (favorable GOS-OR 1.04, CI 1.00-1.08, p = 0.04); and Day 7 GFAP (unfavorable GOS-OR 0.79, CI 0.65-0.95, p = 0.01; and unfavorable survival-OR 0.80, CI 0.66-0.96, p = 0.01). CONCLUSIONS Serial Pg, GFAP, and IL-6 monitoring could aid in prognosticating outcomes in patients with acute sTBI. A cause and effect relationship or a mere association of these biomarkers to outcome needs to be further studied for better understanding of the pathophysiology of sTBI and for choosing potential therapeutic targets. Clinical trial registration no.: CTRI/2009/091/000893 ( http://www.ctri.nic.in ).

Serum Irisin Predicts Mortality Risk in Acute Heart Failure Patients.

PubMed

Shen, Shutong; Gao, Rongrong; Bei, Yihua; Li, Jin; Zhang, Haifeng; Zhou, Yanli; Yao, Wenming; Xu, Dongjie; Zhou, Fang; Jin, Mengchao; Wei, Siqi; Wang, Kai; Xu, Xuejuan; Li, Yongqin; Xiao, Junjie; Li, Xinli

2017-01-01

Irisin is a peptide hormone cleaved from a plasma membrane protein fibronectin type III domain containing protein 5 (FNDC5). Emerging studies have indicated association between serum irisin and many major chronic diseases including cardiovascular diseases. However, the role of serum irisin as a predictor for mortality risk in acute heart failure (AHF) patients is not clear. AHF patients were enrolled and serum was collected at the admission and all patients were followed up for 1 year. Enzyme-linked immunosorbent assay was used to measure serum irisin levels. To explore predictors for AHF mortality, the univariate and multivariate logistic regression analysis, and receiver-operator characteristic (ROC) curve analysis were used. To determine the role of serum irisin levels in predicting survival, Kaplan-Meier survival analysis was used. In this study, 161 AHF patients were enrolled and serum irisin level was found to be significantly higher in patients deceased in 1-year follow-up. The univariate logistic regression analysis identified 18 variables associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 2 variables namely blood urea nitrogen and serum irisin. ROC curve analysis indicated that blood urea nitrogen and the most commonly used biomarker, NT-pro-BNP, displayed poor prognostic value for AHF (AUCs ≤ 0.700) compared to serum irisin (AUC = 0.753). Kaplan-Meier survival analysis demonstrated that AHF patients with higher serum irisin had significantly higher mortality (P<0.001). Collectively, our study identified serum irisin as a predictive biomarker for 1-year all-cause mortality in AHF patients though large multicenter studies are highly needed. © 2017 The Author(s). Published by S. Karger AG, Basel.

Altered serum microRNAs as biomarkers for the early diagnosis of pulmonary tuberculosis infection

PubMed Central

2012-01-01

Background Pulmonary tuberculosis (TB) is a highly lethal infectious disease and early diagnosis of TB is critical for the control of disease progression. The objective of this study was to profile a panel of serum microRNAs (miRNAs) as potential biomarkers for the early diagnosis of pulmonary TB infection. Methods Using TaqMan Low-Density Array (TLDA) analysis followed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) validation, expression levels of miRNAs in serum samples from 30 patients with active tuberculosis and 60 patients with Bordetella pertussis (BP), varicella-zoster virus (VZV) and enterovirus (EV) were analyzed. Results The Low-Density Array data showed that 97 miRNAs were differentially expressed in pulmonary TB patient sera compared with healthy controls (90 up-regulated and 7 down-regulated). Following qRT-PCR confirmation and receiver operational curve (ROC) analysis, three miRNAs (miR-361-5p, miR-889 and miR-576-3p) were shown to distinguish TB infected patients from healthy controls and other microbial infections with moderate sensitivity and specificity (area under curve (AUC) value range, 0.711-0.848). Multiple logistic regression analysis of a combination of these three miRNAs showed an enhanced ability to discriminate between these two groups with an AUC value of 0.863. Conclusions Our study suggests that altered levels of serum miRNAs have great potential to serve as non-invasive biomarkers for early detection of pulmonary TB infection. PMID:23272999

Hypoglycemia and blood glucose fluctuations in the application of a sensor-augmented insulin pump.

PubMed

Luo, Pei; Cheng, Qianpeng; Chen, Bin; Li, Yang; Wu, Jinxiao; Zhang, Xingguang; Jiao, Xiumin; Zhao, Jing; Lv, Xiaofeng

2013-12-01

The purpose of this study was to understand the effect of sensor-augmented insulin pump (SAP) use on hypoglycemia and blood glucose (BG) fluctuations. Sixty patients with type 2 diabetes mellitus were randomly assigned to three groups of treatment with SAP, continuous subcutaneous insulin infusion (CSII), or multiple daily injection (MDI) therapy for 6 days. Parameters of glycemic control that were determined included mean BG concentration (MBG), SD of BG (SDBG), mean amplitude of glycemic excursions (MAGE), absolute means of daily differences (MODD), 24-h area under the curve at 10 h (AUC10), 24-h area under the curve at 3.9 h (AUC3.9), and Low Blood Glucose Index (LBGI). No significant differences were observed among the three groups in terms of MBG, SDBG, MAGE, or MODD at the beginning of treatment. The MBG, SDBG, MAGE, MODD, and total AUC10 of the SAP group improved over the 4 days of the intervention compared with the CSII and MDI groups; however, no significant differences were observed among the three groups in terms of total AUC3.9 and LBGI. Compared with CSII and MDI therapy, SAP therapy was able to rapidly lower mean BG and reduce BG level fluctuations with no increased risks of hypoglycemia.

Low haemoglobin density for detecting iron deficiency across a large population, including pregnancy.

PubMed

Crispin, P; Sinclair, F; Andriolo, K

2016-08-01

Low haemoglobin density (LHD%) from Coulter counters has been suggested as a means to detect iron deficiency. Its performance in a broad population group, including pregnancy, has not been evaluated. A retrospective study of adult and paediatric (under 12 years old) patient samples referred for blood counts and iron studies between October 2013 and March 2015. Receiver operator characteristic (ROC) curves were constructed to evaluate the performance of LHD% adults, children, and in the antenatal subgroup. Using a strict definition for iron deficiency, compared with a selected normal cohort, LHD% had a ROC area under the curve (AUC) of 0.90 (0.89-0.91), but in an unselected cohort, the AUC fell to 0.74 (0.73-0.75) with a sensitivity of 74% and specificity of 60% at a cut-off value of 5.9%. In the paediatric cohort, the AUC was 0.79(0.73-0.85), giving a sensitivity and specificity of 75% and 68%, respectively. LHD% did not effectively identify iron deficiency in pregnancy with an AUC of 0.60 (0.54-0.65) and was no better than MCV at detecting iron deficiency. LHD% detects iron deficiency in adult and paediatric populations, but not in the antenatal setting, and does not appear superior to MCV. © 2016 John Wiley & Sons Ltd.

Diagnostic ability of macular ganglion cell asymmetry for glaucoma.

PubMed

Hwang, Young Hoon; Ahn, Sang Il; Ko, Sung Ju

2015-11-01

Using spectral-domain optical coherence tomography (OCT), this study aims to investigate the glaucoma diagnostic ability of macular ganglion cell asymmetry analysis. A cross-sectional study was conducted. This study was performed to investigate glaucoma diagnostic ability of macular ganglion cell asymmetry analysis in eyes with various degrees of glaucoma. We enrolled 181 healthy eyes and 265 glaucomatous eyes. Glaucomatous eyes were subdivided into pre-perimetric, early, moderate and advanced-to-severe glaucoma based on visual field test results. For each eye, macular ganglion cell-inner plexiform layer (GCIPL) thickness was measured using OCT. Average GCIPL thickness, GCIPL thicknesses in superior and inferior hemispheres, absolute difference in GCIPL thickness between superior and inferior hemispheres and GCIPL asymmetry index calculated as the absolute value of log10 (inferior hemisphere thickness/superior hemisphere thickness) were analysed. Areas under the receiver operating characteristics curves (AUCs) of GCIPL parameter were calculated and compared. All of the GCIPL parameters showed good glaucoma diagnostic ability (AUCs ≥ 0.817, P < 0.01). AUCs of average, superior and inferior GCIPL thickness increased as the severity of glaucoma increased. GCIPL thickness difference and asymmetry index showed the highest AUCs in early and moderate glaucoma and lower AUCs in pre-perimetric and advanced-to-severe glaucoma. GCIPL thickness difference and asymmetry index showed better glaucoma diagnostic ability than other GCIPL parameters only in early stage of glaucoma (P < 0.05); in other stages, these parameters had similar to or worse glaucoma diagnostic ability than other GCIPL parameters. Macular ganglion cell asymmetry analysis showed good glaucoma diagnostic ability, especially in early-stage glaucoma. However, it has limited usefulness in other stages of glaucoma. © 2015 Royal Australian and New Zealand College of Ophthalmologists.

Evaluation of MIh Scoring System in Diagnosis of Obstructive Sleep Apnea Syndrome.

PubMed

Xu, Qinxing; Du, Junwei; Ling, Xiaobo; Lu, Yangfei

2017-10-02

BACKGROUND The objective of the present study was to investigate whether the analysis of magnesium (Mg), high-sensitivity C-reactive protein (hsCRP), and ischemia-modified albumin (IMA) concentrations can be used as a non-invasive and convenient method for diagnosing obstructive sleep apnea syndrome (OSAS). MATERIAL AND METHODS After polysomnography, venous blood was collected from 33 patients with OSAS and 30 control individuals. Serum levels of Mg, hsCRP, and IMA were investigated. The relationship between these factors and apnea-hypopnea index (AHI) was analyzed using the Pearson correlation coefficient. The role of the factors was determined using a receiver operating characteristic (ROC) curve and multivariate logistic regression analysis. RESULTS The levels of hsCRP and IMA were significantly higher in patients with OSAS than in control subjects, while the levels of Mg were lower (P<0.05 for all). A significant correlation was noted between serum IMA (r=0.614; P<0.001) and hsCRP (r=0.453; P<0.001) levels and the AHI. The ROC showed that serum Mg (AUC=0.74(0.62-0.85)), hsCRP (AUC=0.77(0.65-0.87)), and IMA (AUC=0.78(0.66-0.87)) levels could be used as markers to diagnose OSAS. Moreover, our new model, MIh, which is obtained by multivariate analysis, yielded an AUC value of 0.93 (0.83-0.98). Continuous positive airway pressure (CPAP) treatment reversed the changes in the serum levels of Mg, hsCRP, and IMA. CONCLUSIONS Patients with OSAS show reduced serum Mg levels and elevated serum hsCRP and IMA levels. These observed alterations can be reversed by CPAP treatment. A novel model, named MIh, may be a promising tool for OSAS diagnosis.

Diagnostic Accuracy of APRI, AAR, FIB-4, FI, and King Scores for Diagnosis of Esophageal Varices in Liver Cirrhosis: A Retrospective Study.

PubMed

Deng, Han; Qi, Xingshun; Peng, Ying; Li, Jing; Li, Hongyu; Zhang, Yongguo; Liu, Xu; Sun, Xiaolin; Guo, Xiaozhong

2015-12-20

BACKGROUND Aspartate aminotransferase-to-platelet ratio index (APRI), aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), FIB-4, fibrosis index (FI), and King scores might be alternatives to the use of upper gastrointestinal endoscopy for the diagnosis of esophageal varices (EVs) in liver cirrhosis. This study aimed to evaluate their diagnostic accuracy in predicting the presence and severity of EVs in liver cirrhosis. MATERIAL AND METHODS All patients who were consecutively admitted to our hospital and underwent upper gastrointestinal endoscopy between January 2012 and June 2014 were eligible for this retrospective study. Areas under curve (AUCs) were calculated. Subgroup analyses were performed according to the history of upper gastrointestinal bleeding (UGIB) and splenectomy. RESULTS A total of 650 patients with liver cirrhosis were included, and 81.4% of them had moderate-severe EVs. In the overall analysis, the AUCs of these non-invasive scores for predicting moderate-severe EVs and presence of any EVs were 0.506-0.6 and 0.539-0.612, respectively. In the subgroup analysis of patients without UGIB, their AUCs for predicting moderate-severe varices and presence of any EVs were 0.601-0.664 and 0.596-0.662, respectively. In the subgroup analysis of patients without UGIB or splenectomy, their AUCs for predicting moderate-severe varices and presence of any EVs were 0.627-0.69 and 0.607-0.692, respectively. CONCLUSIONS APRI, AAR, FIB-4, FI, and King scores had modest diagnostic accuracy of EVs in liver cirrhosis. They might not be able to replace the utility of upper gastrointestinal endoscopy for the diagnosis of EVs in liver cirrhosis.

Diagnostic Accuracy of APRI, AAR, FIB-4, FI, and King Scores for Diagnosis of Esophageal Varices in Liver Cirrhosis: A Retrospective Study

PubMed Central

Deng, Han; Qi, Xingshun; Peng, Ying; Li, Jing; Li, Hongyu; Zhang, Yongguo; Liu, Xu; Sun, Xiaolin; Guo, Xiaozhong

2015-01-01

Background Aspartate aminotransferase-to-platelet ratio index (APRI), aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), FIB-4, fibrosis index (FI), and King scores might be alternatives to the use of upper gastrointestinal endoscopy for the diagnosis of esophageal varices (EVs) in liver cirrhosis. This study aimed to evaluate their diagnostic accuracy in predicting the presence and severity of EVs in liver cirrhosis. Material/Methods All patients who were consecutively admitted to our hospital and underwent upper gastrointestinal endoscopy between January 2012 and June 2014 were eligible for this retrospective study. Areas under curve (AUCs) were calculated. Subgroup analyses were performed according to the history of upper gastrointestinal bleeding (UGIB) and splenectomy. Results A total of 650 patients with liver cirrhosis were included, and 81.4% of them had moderate-severe EVs. In the overall analysis, the AUCs of these non-invasive scores for predicting moderate-severe EVs and presence of any EVs were 0.506–0.6 and 0.539–0.612, respectively. In the subgroup analysis of patients without UGIB, their AUCs for predicting moderate-severe varices and presence of any EVs were 0.601–0.664 and 0.596–0.662, respectively. In the subgroup analysis of patients without UGIB or splenectomy, their AUCs for predicting moderate-severe varices and presence of any EVs were 0.627–0.69 and 0.607–0.692, respectively. Conclusions APRI, AAR, FIB-4, FI, and King scores had modest diagnostic accuracy of EVs in liver cirrhosis. They might not be able to replace the utility of upper gastrointestinal endoscopy for the diagnosis of EVs in liver cirrhosis. PMID:26687574

Application of the piecewise rational quadratic interpolant to the AUC calculation in the bioavailability study.

PubMed

Akhter, Khalid P; Ahmad, Mahmood; Khan, Shujaat Ali; Ramzan, Munazza; Shafi, Ishrat; Muryam, Burhana; Javed, Zafar; Murtaza, Ghulam

2012-01-01

This study presents an application of the piecewise rational quadratic interpolant to the AUC calculation in the bioavailability study. The objective of this work is to find an area under the plasma concentration-time curve (AUC) for multiple doses of salbutamol sulfate sustained release tablets (Ventolin oral tablets SR 8 mg, GSK, Pakistan) in the group of 24 healthy adults by using computational mathematics techniques. Following the administration of 4 doses of Ventolin tablets 12 hourly to 24 healthy human subjects and bioanalysis of obtained plasma samples, plasma drug concentration-time profile was constructed. The approximated AUC was computed by using computational mathematics techniques such as extended rectangular, extended trapezium and extended Simpson's rule and compared with exact value of AUC calculated by using software - Kinetica to find best computational mathematics method that gives AUC values closest to exact. The exact values of AUC for four consecutive doses of Ventolin oral tablets were 150.58, 157.81, 164.41 and 162.78 ngxh/mL while the closest approximated AUC values were 149.24, 157.33, 164.25 and 162.28 ngxh/mL, respectively, as found by extended rectangular rule. The errors in the approximated values of AUC were negligible. It is concluded that all computational tools approximated values of AUC accurately but the extended rectangular rule gives slightly better approximated values of AUC as compared to extended trapezium and extended Simpson's rules.

Evaluation of Modified Retinopathy of Prematurity Screening Guidelines Using Birth Weight as the Sole Inclusion Criterion

PubMed Central

Chalam, Kakarla V.; Lin, Selina; Murthy, Ravi K.; Brar, Vikram S.; Gupta, Shailesh K.; Radhakrishnan, Ravi

2011-01-01

Purpose: The purpose was to determine if birth weight (BW) alone can be the sole criterion for screening infants at risk for retinopathy of prematurity (ROP). Materials and Methods: In this retrospective, observational case series, 208 infants were screened for ROP using the American Association for Pediatric Ophthalmology and Strabismus (AAPOS) Guidelines (1997). Variables examined included gestational age (GA), birth weight (BW), and a composite variable BWGA Index [(grams × weeks)/1000], which takes into consideration both the birth weight and gestational age of the infant. Infants were divided into two groups: Group 1, BW ≤1250 g, and Group 2, BW >1250 g. Multivariate analysis was performed to detect factors predictive of ROP. Receiver operator characteristic (ROC) curves were generated to determine the efficacy of screening using the BW, GA, and BWGA Index. Statistical analyses were performed with logistic regression with a P-value of 0.05 or less indicating statistical significance. Results: Varying stages of ROP were present in 116 of 416 eyes. Of the 105 eyes in Group 2, only 1 eye developed stage 1 ROP. Only Group 1 eyes developed stage 3 or higher ROP. The ROC curve for BW alone gave an area under the curve (AUC) of 0.797 (standard error [SE] = 0.0329, P < 0.0001); for GA, AUC was 0.801 (SE = 0.0340, P < 0.0001) and for the BWGA Index, the AUC was 0.808 (SE = 0.0324, P < 0.0001). Using 1250-g BW as a criterion for ROP screening would have decreased the number of screenings by 24%, and did not exclude any ROP higher than stage 1. Conclusion: Data from our neonatal intensive care unit suggest that birth weight ≤ 1250 g alone is an adequate parameter to identify premature infants at risk for ROP. PMID:21887076

Predictive capacity of a multimarker strategy to determine short-term mortality in patients attending a hospital emergency Department for acute heart failure. BIO-EAHFE study.

PubMed

Herrero-Puente, Pablo; Prieto-García, Belén; García-García, María; Jacob, Javier; Martín-Sánchez, F Javier; Pascual-Figal, Domingo; Bueno, Héctor; Gil, Victor; Llorens, Pere; Vázquez-Alvarez, Joaquin; Romero-Pareja, Rodolfo; Sanchez-Gonzalez, Marta; Miró, Òscar

2017-03-01

A multimarker strategy may help determine the prognosis of patients with acute heart failure (AHF). The aim of this study was to evaluate the capacity of mid-regional pro-adrenomedullin (MRproADM), copeptin and interleukin-6 (IL-6) combined with conventional clinical and biochemical markers to predict the 30-day mortality of patients with AHF. We performed an observational, multicenter, prospective study of patients attended in the emergency department (ED) for AHF. We collected clinical and biochemical data as well as comorbidities and biomarker values. The endpoint variable was mortality at 7, 14, 30, 90 and 180days. The clinical model included: gender, age, blood pressure values, hemoglobin, sodium <135mmol/L and estimated glomerular filtration <60mL/min/1.73m2. We made receiver operating curves (ROC) curves, and areas under the curve (AUC) and survival analysis for each model and calculated the hazard ratio (HR) and its 95% confidence interval. A total of 547 individuals were included: 55.6% were women with a mean age of 79.9 (9.5) years. Copeptin alone showed greater discriminatory power for 30-mortality [AUC 0.70 (0.62-0.78)]. The AUC for 30-day mortality of the clinical model plus copeptin and NTproBNP was 0.75 (0.67-0.83), being better than the clinical model alone with 0.67 (0.58-0.76; p=0.19). The discriminatory power of the different biomarkers alone, in combination or together with the clinical model decreased over time. The combination of a clinical model with copeptin and NTproBNP, which are available in the ED, is able to prognose early mortality in patients with an episode of AHF. Copyright © 2017 Elsevier B.V. All rights reserved.

Are Vancomycin Trough Concentrations of 15 to 20 mg/L Associated With Increased Attainment of an AUC/MIC ≥ 400 in Patients With Presumed MRSA Infection?

PubMed

Hale, Cory M; Seabury, Robert W; Steele, Jeffrey M; Darko, William; Miller, Christopher D

2017-06-01

To determine whether there is an association between higher vancomycin trough concentrations and attainment of a calculated area under the concentration-time curve (AUC)/minimum inhibitory concentration (MIC) ≥400. A retrospective analysis was conducted among vancomycin-treated adult patients with a positive methicillin-resistant Staphylococcus aureus (MRSA) culture. Attainment of a calculated AUC/MIC ≥400 was compared between patients with troughs in the reference range of 15 to 20 mg/L and those with troughs in the following ranges: <10, 10 to 14.9, and >20 mg/L. Nephrotoxicity was assessed as a secondary outcome based on corrected average vancomycin troughs over 10 days of treatment. Overall, 226 patients were reviewed and 100 included. Relative to troughs ≥10, patients with vancomycin troughs <10 mg/L were 73% less likely to attain an AUC/MIC ≥400 (odds ratio [OR] 0.27, 95% confidence interval [CI]: 0.01-0.75). No difference was found in the attainment of an AUC/MIC ≥400 in patients with troughs of 10 to 14.9 mg/L and >20 mg/L when compared to patients with troughs of 15 to 20 mg/L. The mean corrected average vancomycin trough was higher in patients developing nephrotoxicity compared to those who did not (19.5 vs 14.5 mg/L, P < .001). Achieving vancomycin serum trough concentrations of 15 to 20 mg/L did not result in an increased attainment of the AUC/MIC target relative to troughs of 10 to 14.9 mg/L but may increase nephrotoxicity risk.

Periostin and CA242 as potential diagnostic serum biomarkers complementing CA19.9 in detecting pancreatic cancer.

PubMed

Dong, Dong; Jia, Li; Zhang, Lufang; Ma, Na; Zhang, Aimin; Zhou, Yunli; Ren, Li

2018-06-26

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with few biomarkers to guide treatment options. Carbohydrate antigen 19.9 (CA19.9), the mainly used biomarker for PDAC, is not sensitive and specific enough for the detection of the disease. This study was aimed to evaluate serum periostin (POSTN) and CA242 as potential diagnostic biomarkers complementing CA19.9 in detecting pancreatic cancer. Blood samples were from 362 participants, including 213 patients with different stages of PDAC, 75 patients with benign pancreatic disease and 74 healthy individuals. All samples were randomly divided into training set and validation set. CA19.9, CA242, POSTN, as well as carcinoembryonic antigen (CEA), were measured by ELISA or automated immunoassay. The receiver operating curve (ROC) analysis revealed that the performances of CA19.9 in the validation group were improved by the marker panel composed of CA19.9, POSTN and CA242, to discriminate early-stage PDAC not only from healthy controls (AUC CA 19.9 = 0.94 vs. AUC CA 19.9 + POSTN + CA 242 = 0.98, P < 0.05) but also from benign conditions (AUC CA 19.9 = 0.87 vs. AUC CA 19.9 + POSTN + CA 242 = 0.90, P < 0.05). In addition, POSTN retained significant diagnostic capabilities to distinguish PDAC CA19.9-negative from healthy controls (AUC POSTN = 0.87) as well as from benign conditions (AUC POSTN = 0.84) in the whole set. This study suggested that POSTN and CA242 are potential diagnostic serum biomarkers complementing CA19.9 in detecting early pancreatic cancer. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Predictive value of preoperative inflammatory response biomarkers for metabolic syndrome and post-PCNL systemic inflammatory response syndrome in patients with nephrolithiasis.

PubMed

Tang, Kun; Liu, Haoran; Jiang, Kehua; Ye, Tao; Yan, Libin; Liu, Peijun; Xia, Ding; Chen, Zhiqiang; Xu, Hua; Ye, Zhangqun

2017-10-17

Neutrophil to lymphocyte ratio (NLR), derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR) were promising biomarkers used to predict diagnosis and prognosis in various inflammatory responses diseases and cancers. However, there have been no reports regarding these biomarkers in kidney stone patients. This study aimed to evaluate the predictive value of inflammatory biomarkers for metabolic syndrome (MetS) and post-PCNL SIRS in nephrolithiasis patients. We retrospectively enrolled 513 patients with nephrolithiasis and 204 healthy controls. NLR, dNLR, LMR and PLR in nephrolithiasis patients were significantly higher than control group. Patients with renal stone have higher NLR, dNLR, LMR and PLR than those without. ROC curve analysis indicated NLR, dNLR, LMR and PLR for predicting patients with nephrolithiasis and MetS, displayed AUC of 0.730, 0.717, 0.627 and 0.606. Additionally, ROC curves, using post-PCNL SIRS as the end-point for NLR, dNLR, LMR and PLR with AUC of 0.831, 0.813, 0.723 and 0.685. Multivariate analysis revealed that NLR, dNLR represented independent factors for predicting post-PCNL SIRS. While LMR independently associated with MetS. These resluts demonstrate preoperative NLR, dNLR and LMR appears to be effective predictors of post-PCNL SIRS and LMR of MetS in nephrolithiasis patients.

Measuring Psychological Trauma in the Workplace: Psychometric Properties of the Italian Version of the Psychological Injury Risk Indicator—A Cross-Sectional Study

PubMed Central

Garbarino, Sergio; Winwood, Peter C.

2015-01-01

Background. The aim of this study was to cross-culturally adapt the Psychological Injury Risk Indicator (PIRI) and to validate its psychometric properties. Methods. Workers from 24 small companies were invited to self-complete the PIRI before undergoing their routine medical examination at the workplace. All participants (841 out of 845, 99.6%) were also asked to report occupational injuries and episodes of violence that had occurred at the workplace in the previous 12 months and were given the General Health Questionnaire (GHQ12) to complete. Results. Exploratory factor analysis revealed a 4-factor structure, “sleep problems,” “recovery failure,” “posttraumatic stress symptoms,” and “chronic fatigue,” which were the same subscales observed in the original version. The internal consistency was excellent (alpha = 0.932). ROC curve analysis revealed that the PIRI was much more efficient than GHQ12 in diagnosing workers who had suffered trauma (workplace violence or injury) in the previous year, as it revealed an area under the curve (AUC) of 0.679 (95% CI: 0.625–0.734) for the PIRI, while for the GHQ12 the AUC was 0.551 (not significant). Conclusions. This study, performed on a large population of workers, provides evidence of the validity of the Italian version of the PIRI. PMID:25839055

Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System.

PubMed

Chai, Rifai; Naik, Ganesh R; Nguyen, Tuan Nghia; Ling, Sai Ho; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-05-01

This paper presents a two-class electroencephal-ography-based classification for classifying of driver fatigue (fatigue state versus alert state) from 43 healthy participants. The system uses independent component by entropy rate bound minimization analysis (ERBM-ICA) for the source separation, autoregressive (AR) modeling for the features extraction, and Bayesian neural network for the classification algorithm. The classification results demonstrate a sensitivity of 89.7%, a specificity of 86.8%, and an accuracy of 88.2%. The combination of ERBM-ICA (source separator), AR (feature extractor), and Bayesian neural network (classifier) provides the best outcome with a p-value < 0.05 with the highest value of area under the receiver operating curve (AUC-ROC = 0.93) against other methods such as power spectral density as feature extractor (AUC-ROC = 0.81). The results of this study suggest the method could be utilized effectively for a countermeasure device for driver fatigue identification and other adverse event applications.

Evaluation of computer-aided detection of lesions in mammograms obtained with a digital phase-contrast mammography system.

PubMed

Tanaka, Toyohiko; Nitta, Norihisa; Ohta, Shinichi; Kobayashi, Tsuyoshi; Kano, Akiko; Tsuchiya, Keiko; Murakami, Yoko; Kitahara, Sawako; Wakamiya, Makoto; Furukawa, Akira; Takahashi, Masashi; Murata, Kiyoshi

2009-12-01

A computer-aided detection (CAD) system was evaluated for its ability to detect microcalcifications and masses on images obtained with a digital phase-contrast mammography (PCM) system, a system characterised by the sharp images provided by phase contrast and by the high resolution of 25-μm-pixel mammograms. Fifty abnormal and 50 normal mammograms were collected from about 3,500 mammograms and printed on film for reading on a light box. Seven qualified radiologists participated in an observer study based on receiver operating characteristic (ROC) analysis. The average of the areas under ROC curve (AUC) values for the ROC analysis with and without CAD were 0.927 and 0.897 respectively (P = 0.015). The AUC values improved from 0.840 to 0.888 for microcalcifications (P = 0.034) and from 0.947 to 0.962 for masses (P = 0.025) respectively. The application of CAD to the PCM system is a promising approach for the detection of breast cancer in its early stages.

Performance of Two Bioelectrical Impedance Analyses in the Diagnosis of Overweight and Obesity in Children and Adolescents: The FUPRECOL Study

PubMed Central

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge Enrique; Martínez-Torres, Javier; González-Ruíz, Katherine; González-Jiménez, Emilio; Schmidt-RioValle, Jacqueline; Garcia-Hermoso, Antonio

2016-01-01

This study aimed to determine thresholds for percentage of body fat (BF%) corresponding to the cut-off values for overweight/obesity as recommended by the International Obesity Task Force (IOTF), using two bioelectrical impedance analyzers (BIA), and described the likelihood of increased cardiometabolic risk in our cohort defined by the IOTF and BF% status. Participants included 1165 children and adolescents (54.9% girls) from Bogotá (Colombia). Body mass index (BMI) was calculated from height and weight. BF% of each youth was assessed first using the Tanita BC-418® followed by a Tanita BF-689®. The sensitivity and specificity of both devices and their ability to correctly classify children as overweight/obesity (≥2 standard deviation), as defined by IOTF, was investigated using receiver operating characteristic (ROC) by sex and age groups (9–11, 12–14, and 13–17 years old); Area under curve (AUC) values were also reported. For girls, the optimal BF% threshold for classifying into overweight/obesity was found to be between 25.2 and 28.5 (AUC = 0.91–0.97) and 23.9 to 26.6 (AUC = 0.90–0.99) for Tanita BC-418® and Tanita BF-689®, respectively. For boys, the optimal threshold was between 16.5 and 21.1 (AUC = 0.93–0.96) and 15.8 to 20.6 (AUC = 0.92–0.94) by Tanita BC-418® and Tanita BF-689®, respectively. All AUC values for ROC curves were statistically significant and there were no differences between AUC values measured by both BIA devices. The BF% values associated with the IOTF-recommended BMI cut-off for overweight/obesity may require age- and sex-specific threshold values in Colombian children and adolescents aged 9–17 years and could be used as a surrogate method to identify individuals at risk of excess adiposity. PMID:27782039

Performance of Two Bioelectrical Impedance Analyses in the Diagnosis of Overweight and Obesity in Children and Adolescents: The FUPRECOL Study.

PubMed

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge Enrique; Martínez-Torres, Javier; González-Ruíz, Katherine; González-Jiménez, Emilio; Schmidt-RioValle, Jacqueline; Garcia-Hermoso, Antonio

2016-10-04

This study aimed to determine thresholds for percentage of body fat (BF%) corresponding to the cut-off values for overweight/obesity as recommended by the International Obesity Task Force (IOTF), using two bioelectrical impedance analyzers (BIA), and described the likelihood of increased cardiometabolic risk in our cohort defined by the IOTF and BF% status. Participants included 1165 children and adolescents (54.9% girls) from Bogotá (Colombia). Body mass index (BMI) was calculated from height and weight. BF% of each youth was assessed first using the Tanita BC-418® followed by a Tanita BF-689®. The sensitivity and specificity of both devices and their ability to correctly classify children as overweight/obesity (≥2 standard deviation), as defined by IOTF, was investigated using receiver operating characteristic (ROC) by sex and age groups (9-11, 12-14, and 13-17 years old); Area under curve (AUC) values were also reported. For girls, the optimal BF% threshold for classifying into overweight/obesity was found to be between 25.2 and 28.5 (AUC = 0.91-0.97) and 23.9 to 26.6 (AUC = 0.90-0.99) for Tanita BC-418® and Tanita BF-689®, respectively. For boys, the optimal threshold was between 16.5 and 21.1 (AUC = 0.93-0.96) and 15.8 to 20.6 (AUC = 0.92-0.94) by Tanita BC-418® and Tanita BF-689®, respectively. All AUC values for ROC curves were statistically significant and there were no differences between AUC values measured by both BIA devices. The BF% values associated with the IOTF-recommended BMI cut-off for overweight/obesity may require age- and sex-specific threshold values in Colombian children and adolescents aged 9-17 years and could be used as a surrogate method to identify individuals at risk of excess adiposity.

Accuracy of Four Imaging Techniques for Diagnosis of Posterior Pelvic Floor Disorders.

PubMed

van Gruting, Isabelle M A; Stankiewicz, Aleksandra; Kluivers, Kirsten; De Bin, Riccardo; Blake, Helena; Sultan, Abdul H; Thakar, Ranee

2017-11-01

To establish the diagnostic test accuracy of evacuation proctography, magnetic resonance imaging (MRI), transperineal ultrasonography, and endovaginal ultrasonography for detecting posterior pelvic floor disorders (rectocele, enterocele, intussusception, and anismus) in women with obstructed defecation syndrome and secondarily to identify the most patient-friendly imaging technique. In this prospective cohort study, 131 women with symptoms of obstructed defecation syndrome underwent evacuation proctogram, MRI, and transperineal and endovaginal ultrasonography. Images were analyzed by two blinded observers. In the absence of a reference standard, latent class analysis was used to assess diagnostic test accuracy of multiple tests with area under the curve (AUC) as the primary outcome measure. Secondary outcome measures were interobserver agreement calculated as Cohen's κ and patient acceptability using a visual analog scale. No significant differences in diagnostic accuracy were found among the imaging techniques for all the target conditions. Estimates of diagnostic test accuracy were highest for rectocele using MRI (AUC 0.79) or transperineal ultrasonography (AUC 0.85), for enterocele using transperineal (AUC 0.73) or endovaginal ultrasonography (AUC 0.87), for intussusception using evacuation proctography (AUC 0.76) or endovaginal ultrasonography (AUC 0.77), and for anismus using endovaginal (AUC 0.95) or transperineal ultrasonography (AUC 0.78). Interobserver agreement for the diagnosis of rectocele (κ 0.53-0.72), enterocele (κ 0.54-0.94) and anismus (κ 0.43-0.81) was moderate to excellent, but poor to fair for intussusception (κ -0.03 to 0.37) with all techniques. Patient acceptability was better for transperineal and endovaginal ultrasonography as compared with MRI and evacuation proctography (P<.001). Evacuation proctography, MRI, and transperineal and endovaginal ultrasonography were shown to have similar diagnostic test accuracy. Evacuation proctography is not the best available imaging technique. There is no one optimal test for the diagnosis of all posterior pelvic floor disorders. Because transperineal and endovaginal ultrasonography have good test accuracy and patient acceptability, we suggest these could be used for initial assessment of obstructed defecation syndrome. ClinicalTrials.gov, NCT02239302.

Improved Early Detection of Sepsis in the ED With a Novel Monocyte Distribution Width Biomarker.

PubMed

Crouser, Elliott D; Parrillo, Joseph E; Seymour, Christopher; Angus, Derek C; Bicking, Keri; Tejidor, Liliana; Magari, Robert; Careaga, Diana; Williams, JoAnna; Closser, Douglas R; Samoszuk, Michael; Herren, Luke; Robart, Emily; Chaves, Fernando

2017-09-01

Sepsis most often presents to the ED, and delayed detection is harmful. WBC count is often used to detect sepsis, but changes in WBC count size also correspond to sepsis. We sought to determine if volume increases of circulating immune cells add value to the WBC count for early sepsis detection in the ED. A blinded, prospective cohort study was conducted in two different ED populations within a large academic hospital. Neutrophil and monocyte volume parameters were measured in conjunction with routine CBC testing on a UniCel DxH 800 analyzer at the time of ED admission and were evaluated for the detection of sepsis. There were 1,320 subjects in the ED consecutively enrolled and categorized as control subjects (n = 879) and those with systemic inflammatory response syndrome (SIRS) (n = 203), infection (n = 140), or sepsis (n = 98). Compared with other parameters, monocyte distribution width (MDW) best discriminated sepsis from all other conditions (area under the curve [AUC], 0.79; 95% CI, 0.73-0.84; sensitivity, 0.77; specificity, 0.73; MDW threshold, 20.50), sepsis from SIRS (AUC, 0.74; 95% CI, 0.67-0.84), and severe sepsis from noninfected patients in the ED (AUC, 0.88; 95% CI, 0.75-0.99; negative predictive value, 99%). The added value of MDW to WBC count was statistically significant (AUC, 0.89 for MDW + WBC vs 0.81 for WBC alone; P < .01); a decision curve analysis also showed improved performance compared with WBC count alone. The incorporation of MDW with WBC count is shown in this prospective cohort study to improve detection of sepsis compared with WBC count alone at the time of admission in the ED. ClinicalTrials.gov; No.: NCT02232750; URL: www.clinicaltrials.gov. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Cystatin C is Better than Serum Creatinine for Estimating Glomerular Filtration Rate to Detect Osteopenia in Chronic Kidney Disease Patients.

PubMed

Kwon, Young Eun; Lee, Mi Jung; Park, Kyoung Sook; Han, Seung Hyeok; Yoo, Tae Hyun; Oh, Kook Hwan; Lee, Joongyub; Lee, Kyu Beck; Chung, Wookyung; Kim, Yeong Hoon; Ahn, Curie; Choi, Kyu Hun

2017-03-01

Recent studies have reported that loss of bone mass is associated with renal function decline and increased fracture risks in chronic kidney disease (CKD) patients. The aim of this study was to investigate the best estimated glomerular filtration rate (eGFR) equation to detect osteopenia in CKD patients. This was a cross-sectional study, and 780 patients aged 50 years or above were classified into normal bone mass or osteopenia groups according to the -1.0 of T-scores at total hip and femur neck. Comparisons of area under the receiver operating characteristic (ROC) curves (AUC) were performed to investigate significant differences among three eGFR formulas: Modification of Diet in Renal Disease, CKD-Epidemiology Collaboration (EPI) creatinine, and CKD-EPI cystatin C (CKD-EPI-Cys). The mean age was 61 years old and the proportion of females was 37.3%. The total hip osteopenia group showed lower CKD-EPI-Cys eGFR levels (osteopenia group, 33.3±19.0 mL/min/1.73 m²; normal group, 48.1±26.2 mL/min/1.73 m², p<0.001). In multiple logistic regression analysis, CKD-EPI-Cys eGFR was independently associated with osteopenia at the total hip (per 1 mL/min/1.73 m² increase, odds ratio 0.98, 95% confidence interval 0.97-0.99, p=0.004) after adjusting for confounding variables. ROC curve analyses indicated that CKD-EPI-Cys shows the largest AUC for osteopenia at the total hip (AUC=0.678, all p<0.01) and the femur neck (AUC=0.665, all p<0.05). Decreased renal function assessed by CKD-EPI-Cys equation correlates with osteopenia better than creatinine-based methods in CKD patients, and the CKD-EPI-Cys formula might be a useful tool to assess skeletal-related event risks.

Differences in the associations of anthropometric measures with insulin resistance and type 2 diabetes mellitus between Korean and US populations: Comparisons of representative nationwide sample data.

PubMed

Yoon, Yeong Sook; Choi, Han Seok; Kim, Jin Kuk; Kim, Yu Il; Oh, Sang Woo

Variation among ethnic groups in the association between obesity and insulin resistance (IR)/diabetes has been suggested, but studies reported inconsistent results. We evaluated ethnic differences in the association between obesity and insulin resistance (IR)/diabetes. We conducted a cross-sectional analysis using Korea (n=18,845) and the USA (n=4657) National Health and Nutrition Examination Survey(NHANES) 2007-2010. We performed statistical comparisons of AUC-ROC (area under the curve in a receiver operating characteristic curve) values for body mass index (BMI), waist circumference (WC) and homeostasis model assessment of insulin resistance (HOMA-IR) to predict IR or diabetes among different ethnic groups. AUC-ROC values for BMI and WC for predicting IR were highest in Whites (0.8324 and 0.8468) and lowest in Koreans (0.7422 and 0.7367). Whites showed the highest AUC-ROC values for BMI (0.6869) and WC (0.7421) for predicting diabetes, while the AUC-ROC for HOMA-IR was highest in Koreans (0.8861). Linear regression showed significant interactions between ethnicity and the main effects (all P<0.0001). Increases in BMI were associated with a larger increase in HOMA-IR in Whites (β=0.0719) and WC in Hispanics (β=0.0324), while BMI was associated with a larger increase in fasting glucose in Koreans (β=0.8279) and WC in Blacks (β=0.4037). In addition, the slope for fasting glucose with increasing HOMA-IR was steeper in Koreans (β=16.5952, P<0.001) than in other groups. The ability of BMI and WC to predict IR and diabetes was highest in Whites, while the ability of HOMA-IR to predict diabetes was highest in Koreans. Copyright © 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Second- to Third-Trimester Longitudinal Growth Assessment for the Prediction of Largeness for Gestational Age and Macrosomia in an Unselected Population.

PubMed

Caradeux, Javier; Eixarch, Elisenda; Mazarico, Edurne; Basuki, Tri Rahmat; Gratacós, Eduard; Figueras, Francesc

2018-01-01

Prenatal detection of excessive growth remains inaccurate. Most strategies rely on a single cross-sectional evaluation of fetal size during the third trimester. To compare second- to third-trimester longitudinal growth assessment with cross-sectional evaluation at the third trimester in the prediction of largeness for gestational age (LGA) and macrosomia. A cohort of 2,696 unselected singleton pregnancies scanned at 21 ± 2 and 32 ± 2 weeks was created. Abdominal circumference (AC) measurements were transformed to z values according to the INTERGROWTH-21st standards. Longitudinal growth assessment was performed by calculation of z velocity and conditional growth. Both methods were compared to cross-sectional assessment at 32 ± 2 weeks. Predictive performance for LGA and macrosomia was determined by receiver operating characteristic curve analysis. A total of 188 (7%) newborns qualified for LGA and 182 (6.8%) for macrosomia. The areas under the curve (AUCs) for 32-week AC z score, AC z velocity, and conditional AC were 0.78, 0.61, and 0.55, respectively, for the prediction of LGA, and 0.75, 0.61, and 0.55, respectively, for the prediction of macrosomia. Both AUCs of AC z velocity and conditional AC were significantly lower (p < 0.001) than the AUC of cross-sectional AC z scores. In the general population, second- to third-trimester longitudinal assessment of fetal growth is inferior to third-trimester cross-sectional evaluation of size in the prediction of LGA and macrosomia. © 2017 S. Karger AG, Basel.

Innovative haematological parameters for early diagnosis of sepsis in adult patients admitted in intensive care unit.

PubMed

Buoro, Sabrina; Manenti, Barbara; Seghezzi, Michela; Dominoni, Paola; Barbui, Tiziano; Ghirardi, Arianna; Carobbio, Alessandra; Marchesi, Gianmariano; Riva, Ivano; Nasi, Alessandra; Ottomano, Cosimo; Lippi, Giuseppe

2018-04-01

This study was aimed to investigate the role of erythrocyte, platelet and reticulocyte (RET) parameters, measured by new haematological analyser Sysmex XN and C reactive protein (CRP), for early diagnosis of sepsis during intensive care unit (ICU) stay. The study population consisted of 62 ICU patients, 21 of whom developed sepsis during ICU stay and 41 who did not. The performance for early diagnosing of sepsis was calculated as area under the curve (AUC) of receiver operating characteristics curves analysis. Compared with CRP (AUC 0.81), immature platelet fraction (IPF) (AUC 0.82) showed comparable efficiency for identifying the onset of sepsis. The association with the risk of developing sepsis during ICU stay was also assessed. One day before the onset of sepsis, a decreased of RET% was significantly associated with the risk of developing sepsis (OR=0.35, 95% CI 0.14 to 0.87), whereas an increased of IPF absolute value (IPF#) was significantly associated with the risk of developing sepsis (OR=1.13, 95% CI 1.03 to 1.24) 2 days before the onset of sepsis. The value of CRP was not predictive of sepsis at either time points. IPF# and RET% may provide valuable clinical information for predicting the risk of developing sepsis, thus allowing early management of patients before the onset of clinically evident systemic infections. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Predictive Factors for Nonsentinel Lymph Node Metastasis in Patients With Positive Sentinel Lymph Nodes After Neoadjuvant Chemotherapy: Nomogram for Predicting Nonsentinel Lymph Node Metastasis.

PubMed

Ryu, Jai Min; Lee, Se Kyung; Kim, Ji Young; Yu, Jonghan; Kim, Seok Won; Lee, Jeong Eon; Han, Se Hwan; Jung, Yong Sik; Nam, Seok Jin

2017-11-01

Axillary lymph node (ALN) status is an important prognostic factor for breast cancer patients. With increasing numbers of patients undergoing neoadjuvant chemotherapy (NAC), issues concerning sentinel lymph node biopsy (SLNB) after NAC have emerged. We analyzed the clinicopathologic features and developed a nomogram to predict the possibility of nonsentinel lymph node (NSLN) metastases in patients with positive SLNs after NAC. A retrospective medical record review was performed of 140 patients who had had clinically positive ALNs at presentation, had a positive SLN after NAC on subsequent SLNB, and undergone axillary lymph node dissection (ALND) from 2008 to 2014. On multivariate stepwise logistic regression analysis, pathologic T stage, lymphovascular invasion, SLN metastasis size, and number of positive SLN metastases were independent predictors for NSLN metastases (P < .05). The NAC nomogram was based on these 4 variables. A receiver operating characteristic curve was plotted, and the area under the curve (AUC) was 0.791 for the NAC nomogram. In the internal validation of performance, the AUCs for the training and test sets were 0.801 and 0.760, respectively. The nomogram was validated in an external patient cohort, with an AUC of 0.705. The Samsung Medical Center NAC nomogram was developed to predict the likelihood of additional positive NSLNs. The Samsung Medical Center NAC nomogram could provide information to surgeons regarding whether to perform additional ALND when the permanent biopsy revealed positive findings, although the intraoperative SLNB findings were negative. Copyright © 2017 Elsevier Inc. All rights reserved.

Optical coherence tomography detects characteristic retinal nerve fiber layer thickness corresponding to band atrophy of the optic discs.

PubMed

Kanamori, Akiyasu; Nakamura, Makoto; Matsui, Noriko; Nagai, Azusa; Nakanishi, Yoriko; Kusuhara, Sentaro; Yamada, Yuko; Negi, Akira

2004-12-01

To analyze retinal nerve fiber layer (RNFL) thickness in eyes with band atrophy by use of optical coherence tomography (OCT) and to evaluate the ability of OCT to detect this characteristic pattern of RNFL loss. Cross-sectional, retrospective study. Thirty-four eyes of 18 patients with bitemporal hemianopia caused by optic chiasm compression by chiasmal tumors were studied. All eyes were divided into 3 groups according to visual field loss grading after Goldmann perimetry. Retinal nerve fiber layer thickness measurements with OCT. Retinal nerve fiber layer thickness around the optic disc was measured by OCT (3.4-mm diameter circle). Calculation of the changes in OCT parameters, including the horizontal (nasal + temporal quadrant RNFL thickness) and vertical values (superior + inferior quadrant RNFL thickness) was based on data from 160 normal eyes. Comparison between the 3 visual field grading groups was done with the analysis of variance test. The receiver operating characteristic (ROC) curve for the horizontal and vertical value were calculated, and the areas under the curve (AUC) were compared. Retinal nerve fiber layer thickness in eyes with band atrophy decreased in all OCT parameters. The reduction rate in average and temporal RNFL thickness and horizontal value was correlated with visual field grading. The AUC of horizontal value was 0.970+/-0.011, which was significantly different from AUC of vertical value (0.903+/-0.022). The degree of RNFL thickness reduction correlated with that of visual field defects. Optical coherence tomography was able to identify the characteristic pattern of RNFL loss in these eyes.

The New Injury Severity Score Versus the Injury Severity Score in Predicting Patient Outcome: A Comparative Evaluation on Trauma Service Patients of the Auckland Hospital

PubMed Central

Samin, Oliver A.; Civil, Ian D.

1999-01-01

Retrospectively calculated NISS was compared with the prospectively calculated ISS from data derived from the trauma registry of the Trauma Services of the Auckland Hospital as to which test is a better predictor of patient outcome, which is defined as the likelihood of death. The area under the curve (AUC) for ISS and NISS were computed using the non-parametric approach. AUC for ISS = 0.95835, and AUC for NISS = 0.97350, p <0.012. Misclassification rate for ISS was 2.77% and the value for NISS was 2.43%.

Enantioselective analysis of ibuprofen in human plasma by anionic cyclodextrin-modified electrokinetic chromatography.

PubMed

Jabor, Valquíria A P; Lanchote, Vera L; Bonato, Pierina S

2002-09-01

This paper reports the development of a rapid method for the enantioselective analysis of the nonsteroidal anti-inflammatory drug ibuprofen in human plasma by capillary electrophoresis employing the anionic cyclodextrin-modified electrokinetic chromatography mode. Sample cleanup was carried out by acidification with HCl followed by liquid-liquid extraction with hexane:isopropanol (99:1 v/v). The complete enantioselective analysis was performed within 10 min, using 100 mmol L(-1) phosphoric acid/triethanolamine buffer, pH 2.6, containing 2.0% w/v sulfated beta-cyclodextrin as chiral selector; fenoprofen, another nonsteroidal anti-inflammatory drug, was used as internal standard. The calibration curves were linear over the concentration range of 0.25-125.0 microg mL(-1) for each enantiomer of ibuprofen. The mean recoveries for ibuprofen enantiomers were up to 85%. The enantiomers studied could be quantified at three different concentrations (0.5, 5.0 and 50.0 microg mL(-1)) with a coefficient of variation and relative error not higher than 15%. The quantitation limit was 0.2 microg mL(-1) for (+)-(S)- and (-)-(R)-ibuprofen using 1 mL of human plasma. The plasma endogenous compounds and other drugs did not interfere with the present assay. The analysis of real plasma samples obtained from a healthy volunteer after administration of 600 mg of racemic ibuprofen showed a maximum plasma level of 29.6 and 39.9 microg mL(-1) of (-)-(R)- and (+)-(S)-ibuprofen, respectively, and the area under plasma concentration-time curve AUC(0-infinity) (+)-(S)/AUC(0-infinity) (-)-(R) ratio was 1.87.

Effect on Insulin-Stimulated Release of D-Chiro-Inositol-Containing Inositolphosphoglycan Mediator during Weight Loss in Obese Women with and without Polycystic Ovary Syndrome.

PubMed

Cheang, Kai I; Sistrun, Sakita N; Morel, Kelley S; Nestler, John E

2016-01-01

Background. A deficiency of D-chiro-inositol-inositolphosphoglycan mediator (DCI-IPG) may contribute to insulin resistance in polycystic ovary syndrome (PCOS). Whether the relationship between impaired DCI-IPG release and insulin resistance is specific to PCOS rather than obesity is unknown. We assessed insulin-released DCI-IPG and its relationship to insulin sensitivity at baseline and after weight loss in obese women with and without PCOS. Methods. Obese PCOS ( n = 16) and normal ( n = 15) women underwent 8 weeks of a hypocaloric diet. The Matsuda index, area under the curve DCI-IPG (AUC DCI-IPG ), AUC insulin , and AUC DCI-IPG /AUC insulin were measured during a 2 hr OGTT at baseline and 8 weeks. Results. PCOS women had lower AUC DCI-IPG /AUC insulin at baseline and a significant relationship between AUC DCI-IPG /AUC insulin and Matsuda index ( p = 0.0003), which was not present in controls. Weight loss was similar between PCOS (-4.08 kg) and normal women (-4.29 kg, p = 0.6281). Weight loss in PCOS women did not change the relationship between AUC DCI-IPG /AUC insulin and Matsuda index ( p = 0.0100), and this relationship remained absent in control women. Conclusion. The association between AUC DCI-IPG /AUC insulin and insulin sensitivity was only found in PCOS but not in normal women, and this relationship was unaffected by weight loss. DCI and its messenger may contribute to insulin resistance in PCOS independent of obesity.

[Meta-analysis of diagnostic capability of frequency-doubling technology (FDT) for primary glaucoma].

PubMed

Liu, Ting; He, Xiang-ge

2006-05-01

To evaluate the overall diagnostic capabilities of frequency-doubling technology (FDT) in patients of primary glaucoma, with standard automated perimetry (SAP) and/or optic disc appearance as the gold standard. A comprehensive electric search in MEDLINE, EMBASE, Cochrane Library, BIOSIS, Previews, HMIC, IPA, OVID, CNKI, CBMdisc, VIP information, CMCC, CCPD, SSreader and 21dmedia and a manual search in related textbooks, journals, congress articles and their references were performed to identify relevant English and Chinese language articles. Criteria for adaptability were established according to validity criteria for diagnostic research published by the Cochrane Methods Group on Screening and Diagnostic Tests. Quality of the included articles was assessed and relevant materials were extracted for studying. Statistical analysis was performed with Meta Test version 0.6 software. Heterogeneity of the included articles was tested, which was used to select appropriate effect model to calculate pooled weighted sensitivity and specificity. Summary Receiver Operating Characteristic (SROC) curve was established and the area under the curve (AUC) was calculated. Finally, sensitivity analysis was performed. Fifteen English articles (21 studies) of 206 retrieved articles were included in the present study, with a total of 3172 patients. The reported sensitivity of FDT ranged from 0.51 to 1.00, and specificity from 0.58 to 1.00. The pooled weighted sensitivity and specificity for FDT with 95% confidence intervals (95% CI) after correction for standard error were 0.86 (0.80 - 0.90), 0.87 (0.81 - 0.91), respectively. The AUC of SROC was 93.01%. Sensitivity analysis demonstrated no disproportionate influences of individual study. The included articles are of good quality and FDT can be a highly efficient diagnostic test for primary glaucoma based on Meta-analysis. However, a high quality perspective study is still required for further analysis.

Predicting stroke through genetic risk functions: The CHARGE risk score project

PubMed Central

Ibrahim-Verbaas, Carla A; Fornage, Myriam; Bis, Joshua C; Choi, Seung Hoan; Psaty, Bruce M; Meigs, James B; Rao, Madhu; Nalls, Mike; Fontes, Joao D; O’Donnell, Christopher J.; Kathiresan, Sekar; Ehret, Georg B.; Fox, Caroline S; Malik, Rainer; Dichgans, Martin; Schmidt, Helena; Lahti, Jari; Heckbert, Susan R; Lumley, Thomas; Rice, Kenneth; Rotter, Jerome I; Taylor, Kent D; Folsom, Aaron R; Boerwinkle, Eric; Rosamond, Wayne D; Shahar, Eyal; Gottesman, Rebecca F.; Koudstaal, Peter J; Amin, Najaf; Wieberdink, Renske G.; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G; DeStefano, Anita L.; Debette, Stephanie; Xue, Luting; Beiser, Alexa; Wolf, Philip A.; DeCarli, Charles; Ikram, M. Arfan; Seshadri, Sudha; Mosley, Thomas H; Longstreth, WT; van Duijn, Cornelia M; Launer, Lenore J

2014-01-01

Background and Purpose Beyond the Framingham Stroke Risk Score (FSRS), prediction of future stroke may improve with a genetic risk score (GRS) based on Single nucleotide polymorphisms (SNPs) associated with stroke and its risk factors. Methods The study includes four population-based cohorts with 2,047 first incident strokes from 22,720 initially stroke-free European origin participants aged 55 years and older, who were followed for up to 20 years. GRS were constructed with 324 SNPs implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with Area under the curve (AUC) statistics comparing the GRS to age sex, and FSRS models, and with reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke (IS). Results In the meta-analysis, adding the GRS to the FSRS, age and sex model resulted in a significant improvement in discrimination (All stroke: Δjoint AUC =0.016, p-value=2.3*10-6; IS: Δ joint AUC =0.021, p-value=3.7*10−7), although the overall AUC remained low. In all studies there was a highly significantly improved net reclassification index (p-values <10−4). Conclusions The SNPs associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared to the classical epidemiological risk factors for stroke. PMID:24436238

Cost-effectiveness analysis of an early-initiated, continuous chain of rehabilitation after severe traumatic brain injury.

PubMed

Andelic, Nada; Ye, Jiajia; Tornas, Sveinung; Roe, Cecilie; Lu, Juan; Bautz-Holter, Erik; Moger, Tron; Sigurdardottir, Solrun; Schanke, Anne-Kristine; Aas, Eline

2014-07-15

The aim of this study is to estimate the long-term cost-effectiveness of two different rehabilitation trajectories after severe traumatic brain injury (sTBI). A decision tree model compared hospitalization costs, health effects, and incremental cost-effectiveness ratios (ICER) of a continuous chain versus a broken chain of rehabilitation. The expected costs were estimated by the reimbursement system using diagnosis-related group and based on point estimates of the Disability Rating Scale (DRS); the health effects were measured by means of area under the curve (AUC). The incremental health benefit was estimated as the difference in the AUCs between the chains. Lower values on the DRS scale indicate better health; thus, smaller AUCs were preferred. The modeled population was a cohort of 59 patients with sTBI (30 in continuous chain; 29 in broken chain) with 6-weeks, 1-year, and 5-year post-injury follow-ups. Regarding the DRS estimates, 5-year AUCs were 19.40 (continuous chain) and 23.46 (broken chain). Across 5 years, the continuous chain of rehabilitation had lower costs and better health effects. By replacing the broken chain with the continuous chain, NOK 37.000 could be saved and 4.06 DRS points gained. By means of probabilistic sensitivity analysis, the majority of ICER estimates (67% of the Monte Carlo simulations) indicated that a continuous chain of rehabilitation was less costly and more effective. These findings indicate that the trajectory of continuous rehabilitation represents a dominant strategy in that it reduces costs and improves outcomes after sTBI under reasonable assumptions.

Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

PubMed

Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

2016-11-01

Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

FRAX®: Prediction of Major Osteoporotic Fractures in Women from the General Population: The OPUS Study

PubMed Central

Briot, Karine; Paternotte, Simon; Kolta, Sami; Eastell, Richard; Felsenberg, Dieter; Reid, David M.; Glüer, Claus-C.; Roux, Christian

2013-01-01

Purposes The aim of this study was to analyse how well FRAX® predicts the risk of major osteoporotic and vertebral fractures over 6 years in postmenopausal women from general population. Patients and methods The OPUS study was conducted in European women aged above 55 years, recruited in 5 centers from random population samples and followed over 6 years. The population for this study consisted of 1748 women (mean age 74.2 years) with information on incident fractures. 742 (43.1%) had a prevalent fracture; 769 (44%) and 155 (8.9%) of them received an antiosteoporotic treatment before and during the study respectively. We compared FRAX® performance with and without bone mineral density (BMD) using receiver operator characteristic (ROC) c-statistical analysis with ORs and areas under receiver operating characteristics curves (AUCs) and net reclassification improvement (NRI). Results 85 (4.9%) patients had incident major fractures over 6 years. FRAX® with and without BMD predicted these fractures with an AUC of 0.66 and 0.62 respectively. The AUC were 0.60, 0.66, 0.69 for history of low trauma fracture alone, age and femoral neck (FN) BMD and combination of the 3 clinical risk factors, respectively. FRAX® with and without BMD predicted incident radiographic vertebral fracture (n = 65) with an AUC of 0.67 and 0.65 respectively. NRI analysis showed a significant improvement in risk assignment when BMD is added to FRAX®. Conclusions This study shows that FRAX® with BMD and to a lesser extent also without FN BMD predict major osteoporotic and vertebral fractures in the general population. PMID:24386199

14-3-3η Autoantibodies: Diagnostic Use in Early Rheumatoid Arthritis.

PubMed

Maksymowych, Walter P; Boire, Gilles; van Schaardenburg, Dirkjan; Wichuk, Stephanie; Turk, Samina; Boers, Maarten; Siminovitch, Katherine A; Bykerk, Vivian; Keystone, Ed; Tak, Paul Peter; van Kuijk, Arno W; Landewé, Robert; van der Heijde, Desiree; Murphy, Mairead; Marotta, Anthony

2015-09-01

To describe the expression and diagnostic use of 14-3-3η autoantibodies in early rheumatoid arthritis (RA). 14-3-3η autoantibody levels were measured using an electrochemiluminescent multiplexed assay in 500 subjects (114 disease-modifying antirheumatic drug-naive patients with early RA, 135 with established RA, 55 healthy, 70 autoimmune, and 126 other non-RA arthropathy controls). 14-3-3η protein levels were determined in an earlier analysis. Two-tailed Student t tests and Mann-Whitney U tests compared differences among groups. Receiver-operator characteristic (ROC) curves were generated and diagnostic performance was estimated by area under the curve (AUC), as well as specificity, sensitivity, and likelihood ratios (LR) for optimal cutoffs. Median serum 14-3-3η autoantibody concentrations were significantly higher (p < 0.0001) in patients with early RA (525 U/ml) when compared with healthy controls (235 U/ml), disease controls (274 U/ml), autoimmune disease controls (274 U/ml), patients with osteoarthritis (259 U/ml), and all controls (265 U/ml). ROC curve analysis comparing early RA with healthy controls demonstrated a significant (p < 0.0001) AUC of 0.90 (95% CI 0.85-0.95). At an optimal cutoff of ≥ 380 U/ml, the ROC curve yielded a sensitivity of 73%, a specificity of 91%, and a positive LR of 8.0. Adding 14-3-3η autoantibodies to 14-3-3η protein positivity enhanced the identification of patients with early RA from 59% to 90%; addition of 14-3-3η autoantibodies to anticitrullinated protein antibodies (ACPA) and/or rheumatoid factor (RF) increased identification from 72% to 92%. Seventy-two percent of RF- and ACPA-seronegative patients were positive for 14-3-3η autoantibodies. 14-3-3η autoantibodies, alone and in combination with the 14-3-3η protein, RF, and/or ACPA identified most patients with early RA.

Dual Incorporation of the in vitro Data (IC50) and in vivo (Cmax) Data for the Prediction of Area Under the Curve (AUC) for Statins using Regression Models Developed for Either Pravastatin or Simvastatin.

PubMed

Srinivas, N R

2016-08-01

Linear regression models utilizing a single time point (Cmax) has been reported for pravastatin and simvastatin. A new model was developed for the prediction of AUC of statins that utilized the slopes of the above 2 models, with pharmacokinetic (Cmax) and a pharmacodynamic (IC50 value) components for the statins. The prediction of AUCs for various statins (pravastatin, atorvastatin, simvastatin and rosuvastatin) was carried out using the newly developed dual pharmacokinetic and pharmacodynamic model. Generally, the AUC predictions were contained within 0.5 to 2-fold difference of the observed AUC suggesting utility of the new models. The root mean square error predictions were<45% for the 2 models. On the basis of the present work, it is feasible to utilize both pharmacokinetic (Cmax) and pharmacodynamic (IC50) data for effectively predicting the AUC for statins. Such a new concept as described in the work may have utility in both drug discovery and development stages. © Georg Thieme Verlag KG Stuttgart · New York.

Two meals with different carbohydrate, fat and protein contents render equivalent postprandial plasma levels of calprotectin, cortisol, triglycerides and zonulin.

PubMed

Ohlsson, Bodil; Darwiche, Gassan; Roth, Bodil; Höglund, Peter

2016-11-01

The aim was to compare postprandial plasma levels of calprotectin, cortisol, triglycerides and zonulin between a control breakfast and a moderately low-carbohydrate test breakfast, given randomly after 10-h fast. Blood samples were collected before and repeatedly after the meal. Plasma calprotectin, cortisol, triglycerides and zonulin were analyzed. The total area under the curve (tAUC) and change in AUC from baseline (dAUC) were calculated. Ratios between the test and control values were calculated to investigate equivalence. Healthy volunteers (8 men and 12 women; 46.0 ± 14.5 years) were included. tAUCs of cortisol and triglycerides did not differ between the breakfasts (p = 0.158 versus p = 0.579). Cortisol dAUCs were decreased and triglyceride dAUCs were increased after both breakfasts, with no differences between the breakfasts (p = 0.933 versus p = 0.277). Calprotectin and zonulin levels were unaffected. The meals were bioequivalent for cortisol, triglycerides and zonulin, but not for calprotectin.

Predicting severe motor impairment in preterm children at age 5 years.

PubMed

Synnes, Anne; Anderson, Peter J; Grunau, Ruth E; Dewey, Deborah; Moddemann, Diane; Tin, Win; Davis, Peter G; Doyle, Lex W; Foster, Gary; Khairy, May; Nwaesei, Chukwuma; Schmidt, Barbara

2015-08-01

To determine whether the ability to predict severe motor impairment at age 5 years improves between birth and 18 months. Ancillary study of the Caffeine for Apnea of Prematurity Trial. International cohort of very low birth weight children who were assessed sequentially from birth to 5 years. Severe motor impairment was defined as a score <5th percentile on the Movement Assessment Battery of Children (MABC), or inability to complete the MABC because of cerebral palsy. Multivariable logistic regression cumulative risk models used four sets of predictor variables: early neonatal risk factors, risk factors at 36 weeks' postmenstrual age, risk factors at a corrected age of 18 months, and sociodemographic variables. A receiver operating characteristic curve (ROC) was generated for each model, and the four ROC curves were compared to determine if the addition of the new set of predictors significantly increased the area under the curve (AUC). Of 1469 children, 291 (19.8%) had a severe motor impairment at 5 years. The AUC increased from 0.650 soon after birth, to 0.718 (p<0.001) at 36 weeks' postmenstrual age, and to 0.797 at 18 months (p<0.001). Sociodemographic variables did not significantly improve the AUC (AUC=0.806; p=0.07). Prediction of severe motor impairment at 5 years of age using a cumulative risk model improves significantly from birth to 18 months of age in children with birth weights between 500 g and 1250 g. ClinicalTrials.gov number NCT00182312. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Semi-quantitative analysis of salivary gland scintigraphy in Sjögren's syndrome diagnosis: a first-line tool.

PubMed

Angusti, Tiziana; Pilati, Emanuela; Parente, Antonella; Carignola, Renato; Manfredi, Matteo; Cauda, Simona; Pizzigati, Elena; Dubreuil, Julien; Giammarile, Francesco; Podio, Valerio; Skanjeti, Andrea

2017-09-01

The aim of this study was the assessment of semi-quantified salivary gland dynamic scintigraphy (SGdS) parameters independently and in an integrated way in order to predict primary Sjögren's syndrome (pSS). Forty-six consecutive patients (41 females; age 61 ± 11 years) with sicca syndrome were studied by SGdS after injection of 200 MBq of pertechnetate. In sixteen patients, pSS was diagnosed, according to American-European Consensus Group criteria (AECGc). Semi-quantitative parameters (uptake (UP) and excretion fraction (EF)) were obtained for each gland. ROC curves were used to determine the best cut-off value. The area under the curve (AUC) was used to estimate the accuracy of each semi-quantitative analysis. To assess the correlation between scintigraphic results and disease severity, semi-quantitative parameters were plotted versus Sjögren's syndrome disease activity index (ESSDAI). A nomogram was built to perform an integrated evaluation of all the scintigraphic semi-quantitative data. Both UP and EF of salivary glands were significantly lower in pSS patients compared to those in non-pSS (p < 0.001). ROC curve showed significantly large AUC for both the parameters (p < 0.05). Parotid UP and submandibular EF, assessed by univariated and multivariate logistic regression, showed a significant and independent correlation with pSS diagnosis (p value <0.05). No correlation was found between SGdS semi-quantitative parameters and ESSDAI. The proposed nomogram accuracy was 87%. SGdS is an accurate and reproducible tool for the diagnosis of pSS. ESSDAI was not shown to be correlated with SGdS data. SGdS should be the first-line imaging technique in patients with suspected pSS.

Utility of 18F-fluorodeoxyglucose-positron emission tomography in the differential diagnosis of benign and malignant gynaecological tumours.

PubMed

Takagi, Hiroaki; Sakamoto, Jinichi; Osaka, Yasuhiro; Shibata, Takeo; Fujita, Satoko; Sasagawa, Toshiyuki

2018-02-05

Positron emission tomography/computed tomography (PET/CT) involving 18F-fluorodeoxyglucose (FDG) is widely used for systemic cancer and recurrence diagnosis. However, the differential diagnosis of benign and malignant gynaecological tumours according to FDG accumulation is unclear. This study aimed to investigate the intensity of FDG uptake/metabolic activity for the differential diagnosis of benign and malignant gynaecological tumours. This study included seven patients with physiological phenomena, 34 with benign tumours, 13 with borderline malignant tumours and 119 with malignant tumours who underwent 18F-FDG PET/CT. We assessed the maximum standardized uptake value (SUVmax) and determined its utility in the diagnosis of benign and malignant tumours using a receiver operating characteristic (ROC) curve analysis. Among the 63 patients with ovarian tumours, the mean SUVmax of 22 patients with benign ovarian tumours was 2.48 and the mean SUVmax of 41 patients with malignant ovarian tumours was 10.98 (P < 0.001). In the ROC curve analysis, the area under the curve (AUC) was 0.977, with a 95% confidence interval of 0.947-1.000. With a cut-off value of 3.97 for the optimal SUVmax, the sensitivity and specificity were 95.1% and 86.4%, respectively. In addition, the AUC was 0.911 (95% CI: 0.768-1.000) for the assessment of uterine myomas and sarcomas. With a cut-off value of 10.62 for the optimal SUVmax, the sensitivity and specificity were 91.7% and 86.7% respectively. The SUVmax value helps differentiate benign and malignant ovarian tumours, as well as uterine myomas and uterine sarcomas. © 2018 The Royal Australian and New Zealand College of Radiologists.

Pressure injuries in elderly with acute myocardial infarction.

PubMed

Komici, Klara; Vitale, Dino F; Leosco, Dario; Mancini, Angela; Corbi, Graziamaria; Bencivenga, Leonardo; Mezzani, Alessandro; Trimarco, Bruno; Morisco, Carmine; Ferrara, Nicola; Rengo, Giuseppe

2017-01-01

To assess pressure injury (PI) incidence among patients hospitalized for acute myocardial infarction (AMI) in an intensive coronary care unit (ICCU) and to detect the impact of specific risk factors on the development of PI in this clinical setting. Prospective cohort study in ICCU setting. Patients admitted for AMI: patients mean age 67.5±11.5 years (n=165). Norton Scale, Mini Nutritional Assessment (MNA), demographic, clinical and biochemical data collected at the time of ICCU admission have been tested in a logistic model to assess the odds ratios (ORs) of PI risk development. The jackknifed area under the receiver operating characteristic curve (AUC) and the decision curve analysis have been employed to assess the additive predictive value of a factor. Twenty-seven (16.3%) patients developed PIs. An increased PI risk was associated with advanced age (OR =2.5 every 10-year increase; 95% CI =1.1-5.7), while probability of PI development was reduced in patients with higher left ventricular ejection fraction (LVEF) (OR =0.4 every 5% increase; 95% CI =0.24-0.66), MNA score (OR =0.65 every unit change; 95% CI =0.44-0.95) and Norton Scale score (OR =0.7 every unit change; 95% CI =0.57-0.88). The AUC and the decision curve analysis showed that LVEF inclusion improved the discrimination power and the clinical net benefit of the final model. Age, LVEF, Norton Scale and MNA scores have a strong and independent clinical value as predictors of in-hospital PI development in patients with AMI. This finding has the potential to improve the clinical management of patients admitted in ICCU.

A receiver operated curve-based evaluation of change in sensitivity and specificity of cotinine urinalysis for detecting active tobacco use.

PubMed

Balhara, Yatan Pal Singh; Jain, Raka

2013-01-01

Tobacco use has been associated with various carcinomas including lung, esophagus, larynx, mouth, throat, kidney, bladder, pancreas, stomach, and cervix. Biomarkers such as concentration of cotinine in the blood, urine, or saliva have been used as objective measures to distinguish nonusers and users of tobacco products. A change in the cut-off value of urinary cotinine to detect active tobacco use is associated with a change in sensitivity and sensitivity of detection. The current study aimed at assessing the impact of using different cut-off thresholds of urinary cotinine on sensitivity and specificity of detection of smoking and smokeless tobacco product use among psychiatric patients. All the male subjects attending the psychiatry out-patient department of the tertiary care multispecialty teaching hospital constituted the sample frame for the current study in a cross-sectionally. Quantitative urinary cotinine assay was done by using ELISA kits of Calbiotech. Inc., USA. We used the receiver operating characteristic (ROC) curve to assess the sensitivity and specificity of various cut-off values of urinary cotinine to identify active smokers and users of smokeless tobacco products. ROC analysis of urinary cotinine levels in detection of self-reported smoking provided the area under curve (AUC) of 0.434. Similarly, the ROC analysis of urinary cotinine levels in detection of self-reported smoking revealed AUC of 0.44. The highest sensitivity and specificity of 100% for smoking were detected at the urinary cut-off value greater than or equal to 2.47 ng/ml. The choice of cut-off value of urinary cotinine used to distinguish nonusers form active users of tobacco products impacts the sensitivity as well as specificity of detection.

Role of specific IgE and skin-prick testing in predicting food challenge results to baked egg.

PubMed

Cortot, Catherine F; Sheehan, William J; Permaul, Perdita; Friedlander, James L; Baxi, Sachin N; Gaffin, Jonathan M; Dioun, Anahita F; Hoffman, Elaine B; Schneider, Lynda C; Phipatanakul, Wanda

2012-01-01

Previous studies suggest that children with egg allergy may be able to tolerate baked egg. Reliable predictors of a successful baked egg challenge are not well established. We examined egg white-specific IgE levels, skin-prick test (SPT) results, and age as predictors of baked egg oral food challenge (OFC) outcomes. We conducted a retrospective chart review of children, aged 2-18 years, receiving an egg white-specific IgE level, SPT, and OFC to baked egg from 2008 to 2010. Fifty-two oral baked egg challenges were conducted. Of the 52 challenges, 83% (n = 43) passed and 17% (n = 9) failed, including 2 having anaphylaxis. Median SPT wheal size was 12 mm (range, 0-35 mm) for passed challenges and 17 mm (range, 10-30 mm) for failed challenges (p = 0.091). The negative predictive value for passing the OFC was 100% (9 of 9) if SPT wheal size was <10 mm. Median egg white-specific IgE was 2.02 kU/L (range, <0.35-13.00 kU/L) for passed challenges and 1.52 kU/L (range, 0.51-6.10 kU/L) for failed challenges (p = 0.660). Receiver operating characteristic (ROC) curve analysis for SPT revealed an area under the curve (AUC) of 0.64. ROC curve analysis for egg white-specific IgE revealed an AUC of 0.63. There was no significant difference in age between patients who failed and those who passed (median = 8.8 years versus 7.0 years; p = 0.721). Based on our sample, SPT, egg white-specific IgE and age are not good predictors of passing a baked egg challenge. However, there was a trend for more predictability with SPT wheal size.

Sesame allergy: role of specific IgE and skin-prick testing in predicting food challenge results.

PubMed

Permaul, Perdita; Stutius, Lisa M; Sheehan, William J; Rangsithienchai, Pitud; Walter, Jolan E; Twarog, Frank J; Young, Michael C; Scott, Jordan E; Schneider, Lynda C; Phipatanakul, Wanda

2009-01-01

There are conflicting data regarding the diagnostic value of sesame-specific IgE and sesame skin test. Currently, there are no established thresholds that predict clinical reactivity. We examined the correlation of sesame ImmunoCAP and skin-prick test (SPT) results with oral challenge outcomes in children suspected of having a sesame food allergy. We conducted a retrospective chart review of children, aged 2-12 years, receiving a sesame ImmunoCAP level, SPT, and food challenge from January 2004 to August 2008 at Children's Hospital Boston and affiliated allergy clinics. Food challenges were conducted in cases of questionable clinical history or a negative ImmunoCAP and/or negative SPT despite a convincing history. Thirty-three oral sesame challenges were conducted. Of the 33 challenges performed, 21% (n = 7) failed and 79% (n = 26) passed. A sesame-specific IgE level of > or = 7 kU(A)/L showed specificity of >90%. An SPT wheal size of > or = 6 mm showed specificity of >90%. Receiver operator characteristic (ROC) curve analysis for sesame-specific IgE revealed an area under the curve (AUC) of 0.56. ROC curve analysis for SPT wheal size revealed an AUC of 0.67. To our knowledge, this study represents the largest number of sesame challenges performed to evaluate the diagnostic value of both sesame-specific IgE and SPT. Based on our sample, both tests are not good predictors of true sesame allergy as determined by an oral challenge. We were unable to establish a threshold with a 95% positive predictive value for both sesame-specific IgE and SPT.

Comparative analysis of anthropometric indices of obesity as correlates and potential predictors of risk for hypertension and prehypertension in a population in Nigeria.

PubMed

Ononamadu, Chimaobi James; Ezekwesili, Chinwe Nonyelum; Onyeukwu, Onyemaechi Faith; Umeoguaju, Uchenna Francis; Ezeigwe, Obiajulu Christian; Ihegboro, Godwin Okwudiri

Obesity is a well-established independent risk factor for hypertension and other cardiometabolic disorders. However, the best anthropometric index of obesity that predicts or associates strongly with hypertension and related conditions remains controversial and inconclusive. This study compared the performance of eight anthropometric indices of obesity: body mass index (BMI), ponderal index (PI), waist circumference (WC), hip circumference (HC), waist-hip ratio (WHR), waist-height ratio (WHtR), body adiposity index (BAI) and conicity index (CI) as correlates and potential predictors of risk of hypertension and prehypertension in a Nigerian population, and also the possible effect of combining two or more indices in that regard. This church-based, cross-sectional study was conducted in Anambra state, south-eastern Nigeria from 2012 to 2013. A total of 912 persons (436 male and 476 female) drawn randomly from three major cities (Awka, Onitsha and Nnewi) in the state participated in the study. Information on demography, medical history and lifestyle were obtained using a well-structured and validated questionnaire. The systolic/diastolic blood pressure and anthropometric measurements were taken by well-trained personnel. The resulting data were analysed using descriptive statistics, logistic regression, Poisson regression and receiver operating characteristic curve analysis. The mean values of all the anthropometric indices studied increased from normotension, through prehypertension to hypertension in both genders. BMI, WC, HC and CI were significantly higher (p < 0.05) in females than males. All the anthropometric indices studied were significantly (p < 0.001 except for CI) correlated with systolic and diastolic blood pressure. BMI, WHtR, WC and PI (with higher correlation coefficients for blood pressure) showed the best potential to predict hypertension and prehypertension in the study: BMI (cut-off = 24.49, AUC = 0.698; cut-off = 23.62, AUC = 0.659), WHtR (cut-off = 0.55, AUC = 0.682; cut-off = 0.5, AUC = 0.636), WC (cut-off = 91.44, AUC = 0.692; cut-off = 82.55, AUC = 0.645), PI (cut-off = 14.45, AUC = 0.670; cut-off = 13.69, AUC = 0.639), in males; and BMI (cut-off = 24.44, AUC = 0.622; cut-off = 28.01, AUC = 0.609), WHtR (cut-off = 0.51, AUC = 0.624; cut-off = 0.6, AUC = 0.572), WC ( cut-off = 96.62, AUC = 0.616; cut-off = 96.52, AUC = 0.584), PI ( cut-off = 16.38, AUC = 0.619; cut-off = 17.65, AUC = 0.599), in females for hypertension and prehypertension, respectively. In predicting hypertension risk, WC and WHtR did not significantly improve the performance of BMI in the models when included using our decision rule. Overall, CI had a very poor discriminatory power for both conditions in this study. BMI, WHtR, WC and PI emerged the best predictors of hypertension risk, and BMI, WC and PI of prehypertension risk in this study. The combination of high-performing anthropometric indices in a model did not improve their performance. Therefore we recommend the simultaneous but independent use of BMI and either WC or WHtR for predicting hypertension, and BMI and WC for prehypertension risk, bearing in mind that both types of index (abdominal and general obesity) account for different forms of obesity.

Comparative analysis of anthropometric indices of obesity as correlates and potential predictors of risk for hypertension and prehypertension in a population in Nigeria

PubMed Central

Ononamadu, Chimaobi James; Ihegboro, Godwin Okwudiri; Ezekwesili, Chinwe Nonyelum; Onyeukwu, Onyemaechi Faith; Umeoguaju,, Uchenna Francis; Ezeigwe, Obiajulu Christian

2017-01-01

Summary Background: Obesity is a well-established independent risk factor for hypertension and other cardiometabolic disorders. However, the best anthropometric index of obesity that predicts or associates strongly with hypertension and related conditions remains controversial and inconclusive. Objective: This study compared the performance of eight anthropometric indices of obesity: body mass index (BMI), ponderal index (PI), waist circumference (WC), hip circumference (HC), waist–hip ratio (WHR), waist–height ratio (WHtR), body adiposity index (BAI) and conicity index (CI) as correlates and potential predictors of risk of hypertension and prehypertension in a Nigerian population, and also the possible effect of combining two or more indices in that regard. Methods: This church-based, cross-sectional study was conducted in Anambra state, south-eastern Nigeria from 2012 to 2013. A total of 912 persons (436 male and 476 female) drawn randomly from three major cities (Awka, Onitsha and Nnewi) in the state participated in the study. Information on demography, medical history and lifestyle were obtained using a well-structured and validated questionnaire. The systolic/diastolic blood pressure and anthropometric measurements were taken by well-trained personnel. The resulting data were analysed using descriptive statistics, logistic regression, Poisson regression and receiver operating characteristic curve analysis. Results: The mean values of all the anthropometric indices studied increased from normotension, through prehypertension to hypertension in both genders. BMI, WC, HC and CI were significantly higher (p < 0.05) in females than males. All the anthropometric indices studied were significantly (p < 0.001 except for CI) correlated with systolic and diastolic blood pressure. BMI, WHtR, WC and PI (with higher correlation coefficients for blood pressure) showed the best potential potential to predict hypertension and prehypertension in the study: BMI (cut-off = 24.49, AUC = 0.698; cut-off = 23.62, AUC = 0.659), WHtR (cut-off = 0.55, AUC = 0.682; cut-off = 0.5, AUC = 0.636), WC (cut-off = 91.44, AUC = 0.692; cut-off = 82.55, AUC = 0.645), PI (cut-off = 14.45, AUC = 0.670; cut-off = 13.69, AUC = 0.639), in males; and BMI (cut-off = 24.44, AUC = 0.622; cut-off = 28.01, AUC = 0.609), WHtR (cut-off = 0.51, AUC = 0.624; cut-off = 0.6, AUC = 0.572), WC (cut-off = 96.62, AUC = 0.616; cut-off = 96.52, AUC = 0.584), PI (cut-off = 16.38, AUC = 0.619; cut-off = 17.65, AUC = 0.599), in females for hypertension and prehypertension, respectively. In predicting hypertension risk, WC and WHtR did not significantly improve the performance of BMI in the models when included using our decision rule. Overall, CI had a very poor discriminatory power for both conditions in this study. Conclusion: BMI, WHtR, WC and PI emerged the best predictors of hypertension risk, and BMI, WC and PI of prehypertension risk in this study. The combination of high-performing anthropometric indices in a model did not improve their performance. Therefore we recommend the simultaneous but independent use of BMI and either WC or WHtR for predicting hypertension, and BMI and WC for prehypertension risk, bearing in mind that both types of index (abdominal and general obesity) account for different forms of obesity. PMID:27701484

Diurnal salivary cortisol, glycemia and insulin resistance: The multi-ethnic study of atherosclerosis.

PubMed

Joseph, Joshua J; Wang, Xu; Spanakis, Elias; Seeman, Teresa; Wand, Gary; Needham, Belinda; Golden, Sherita Hill

2015-12-01

Hypercortisolism is associated with insulin resistance (IR) and diabetes mellitus (DM); however, to our knowledge prior studies have not examined the association of diurnal cortisol curve features with measures of glycemia or IR in a population-based setting. Using log-transformed salivary cortisol data on 850 ethnically diverse men and women from the Multi-Ethnic Study of Atherosclerosis, we investigated the cross-sectional association of cortisol curve features with (1) glycemia in those with and without DM and (2) IR, in non-diabetic subjects. The log-transformed salivary cortisol curve features included wake-up cortisol, cortisol awakening response (CAR), early decline slope (30min to 2h post-awakening), late decline slope (2h post-awakening to bedtime), overall decline slope (0min to bedtime, excluding 30min cortisol), bedtime cortisol and total area under the curve (AUC). Overall, following multivariable adjustment, among those with diabetes mellitus (DM), early decline slope, overall decline slope, bedtime cortisol, and AUC were significantly and positively associated with a 5.4% (95% CI: 1.3, 9.7), 54.7% (95% CI: 12.4, 112.9), 4.0% (95% CI: 1.6,6.4), and 6.8% (95% CI: 3.3,10.4) higher HbA1c per 1 unit increase in log cortisol feature, respectively. Cortisol curve features were not associated with HbA1c among non-diabetic participants; however, wake-up cortisol and AUC were associated with a 8.2% lower (95% CI: -13.3,-2.7) and 7.9% lower (95% CI: -14.6, -0.6) log HOMA-IR, respectively. This was attenuated by adjustment for waist circumference. Among participants with DM, cortisol curve parameters suggestive of higher hypothalamic-pituitary-adrenal (HPA) axis activity and dysfunction were associated with higher HbA1c. In non-diabetic participants, greater HPA activity was paradoxically associated with lower insulin resistance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Diurnal Salivary Cortisol, Glycemia and Insulin Resistance: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Joseph, Joshua J.; Wang, Xu; Spanakis, Elias; Seeman, Teresa; Wand, Gary; Needham, Belinda; Golden, Sherita Hill

2015-01-01

Summary Hypercortisolism is associated with insulin resistance (IR) and diabetes mellitus (DM); however, to our knowledge prior studies have not examined the association of diurnal cortisol curve features with measures of glycemia or IR in a population-based setting. Using log-transformed salivary cortisol data on 850 ethnically diverse men and women from the Multi-Ethnic Study of Atherosclerosis, we investigated the cross-sectional association of cortisol curve features with (1) glycemia in those with and without DM and (2) IR, in non-diabetic subjects. The log-transformed salivary cortisol curve features included wake-up cortisol, cortisol awakening response (CAR), early decline slope (30 minutes to 2 hours post-awakening), late decline slope (2 hours post-awakening to bedtime), overall decline slope (0 minutes to bedtime, excluding 30 minute cortisol), bedtime cortisol and total area under the curve (AUC). Overall, following multivariable adjustment, among those with diabetes mellitus (DM), early decline slope, overall decline slope, bedtime cortisol, and AUC were significantly and positively associated with a 5.4% (95% CI: 1.3, 9.7), 54.7% (95% CI: 12.4, 112.9), 4.0% (95% CI: 1.6, 6.4), and 6.8% (95% CI: 3.3, 10.4) higher HbA1c per 1 unit increase in log cortisol feature, respectively. Cortisol curve features were not associated with HbA1c among non-diabetic participants; however, wake-up cortisol and AUC were associated with a 8.2% lower (95% CI: −13.3, −2.7) and 7.9% lower (95% CI: −14.6, −0.6) log HOMA-IR, respectively. This was attenuated by adjustment for waist circumference. Among participants with DM, cortisol curve parameters suggestive of higher hypothalamic-pituitary-adrenal (HPA) axis activity and dysfunction were associated with higher HbA1c. In non-diabetic participants, greater HPA activity was paradoxically associated with lower insulin resistance. PMID:26356041

Bladder cancer treatment response assessment in CT urography using two-channel deep-learning network

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Samala, Ravi K.; Cohan, Richard H.; Caoili, Elaine M.; Weizer, Alon Z.; Alva, Ajjai

2018-02-01

We are developing a CAD system for bladder cancer treatment response assessment in CT. We trained a 2- Channel Deep-learning Convolution Neural Network (2Ch-DCNN) to identify responders (T0 disease) and nonresponders to chemotherapy. The 87 lesions from 82 cases generated 18,600 training paired ROIs that were extracted from segmented bladder lesions in the pre- and post-treatment CT scans and partitioned for 2-fold cross validation. The paired ROIs were input to two parallel channels of the 2Ch-DCNN. We compared the 2Ch-DCNN with our hybrid prepost- treatment ROI DCNN method and the assessments by 2 experienced abdominal radiologists. The radiologist estimated the likelihood of stage T0 after viewing each pre-post-treatment CT pair. Receiver operating characteristic analysis was performed and the area under the curve (AUC) and the partial AUC at sensitivity <90% (AUC0.9) were compared. The test AUCs were 0.76+/-0.07 and 0.75+/-0.07 for the 2 partitions, respectively, for the 2Ch-DCNN, and were 0.75+/-0.08 and 0.75+/-0.07 for the hybrid ROI method. The AUCs for Radiologist 1 were 0.67+/-0.09 and 0.75+/-0.07 for the 2 partitions, respectively, and were 0.79+/-0.07 and 0.70+/-0.09 for Radiologist 2. For the 2Ch-DCNN, the AUC0.9s were 0.43 and 0.39 for the 2 partitions, respectively, and were 0.19 and 0.28 for the hybrid ROI method. For Radiologist 1, the AUC0.9s were 0.14 and 0.34 for partition 1 and 2, respectively, and were 0.33 and 0.23 for Radiologist 2. Our study demonstrated the feasibility of using a 2Ch-DCNN for the estimation of bladder cancer treatment response in CT.

AUC-based biomarker ensemble with an application on gene scores predicting low bone mineral density.

PubMed

Zhao, X G; Dai, W; Li, Y; Tian, L

2011-11-01

The area under the receiver operating characteristic (ROC) curve (AUC), long regarded as a 'golden' measure for the predictiveness of a continuous score, has propelled the need to develop AUC-based predictors. However, the AUC-based ensemble methods are rather scant, largely due to the fact that the associated objective function is neither continuous nor concave. Indeed, there is no reliable numerical algorithm identifying optimal combination of a set of biomarkers to maximize the AUC, especially when the number of biomarkers is large. We have proposed a novel AUC-based statistical ensemble methods for combining multiple biomarkers to differentiate a binary response of interest. Specifically, we propose to replace the non-continuous and non-convex AUC objective function by a convex surrogate loss function, whose minimizer can be efficiently identified. With the established framework, the lasso and other regularization techniques enable feature selections. Extensive simulations have demonstrated the superiority of the new methods to the existing methods. The proposal has been applied to a gene expression dataset to construct gene expression scores to differentiate elderly women with low bone mineral density (BMD) and those with normal BMD. The AUCs of the resulting scores in the independent test dataset has been satisfactory. Aiming for directly maximizing AUC, the proposed AUC-based ensemble method provides an efficient means of generating a stable combination of multiple biomarkers, which is especially useful under the high-dimensional settings. lutian@stanford.edu. Supplementary data are available at Bioinformatics online.

Enhanced cued recall has a high utility as a screening test in the diagnosis of Alzheimer's disease and mild cognitive impairment in Turkish people.

PubMed

Saka, Esen; Mihci, Ebru; Topcuoglu, M Akif; Balkan, Sevin

2006-10-01

Enhanced cued recall (ECR) is highly sensitive and specific in discrimination of demented from non-demented elderly persons. The nature of the test promises that it can be applicable to subjects in different cultures and education level. We studied the utility of the test in a Turkish population. Eighty consecutive cases with dementia or mild cognitive impairment (MCI) and 33 elderly controls were studied. The utility of ECR was high in discriminating dementia from controls (area under curve (AUC)) of the ROC curve: 0.907 (95% confidence interval (CI): 0.830-0.953 for total recall), Alzheimer's disease from controls (AUC: 0.990 (95%CI: 0.934-0.998 for total recall)) and moderate (AUC: 0.625 (95%CI: 0.545-0.812 for third free recall)) in discriminating MCI from controls. Education did not affect the utility of the test. We conclude that ECR is a valuable test in assessment of elderly Turkish patients with a complaint of memory impairment.

External validation of the Cairns Prediction Model (CPM) to predict conversion from laparoscopic to open cholecystectomy.

PubMed

Hu, Alan Shiun Yew; Donohue, Peter O'; Gunnarsson, Ronny K; de Costa, Alan

2018-03-14

Valid and user-friendly prediction models for conversion to open cholecystectomy allow for proper planning prior to surgery. The Cairns Prediction Model (CPM) has been in use clinically in the original study site for the past three years, but has not been tested at other sites. A retrospective, single-centred study collected ultrasonic measurements and clinical variables alongside with conversion status from consecutive patients who underwent laparoscopic cholecystectomy from 2013 to 2016 in The Townsville Hospital, North Queensland, Australia. An area under the curve (AUC) was calculated to externally validate of the CPM. Conversion was necessary in 43 (4.2%) out of 1035 patients. External validation showed an area under the curve of 0.87 (95% CI 0.82-0.93, p = 1.1 × 10 -14 ). In comparison with most previously published models, which have an AUC of approximately 0.80 or less, the CPM has the highest AUC of all published prediction models both for internal and external validation. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

Discrepancy in Vancomycin AUC/MIC Ratio Targeted Attainment Based upon the Susceptibility Testing in Staphylococcus aureus.

PubMed

Eum, Seenae; Bergsbaken, Robert L; Harvey, Craig L; Warren, J Bryan; Rotschafer, John C

2016-09-27

This study demonstrated a statistically significant difference in vancomycin minimum inhibitory concentration (MIC) for Staphylococcus aureus between a common automated system (Vitek 2) and the E-test method in patients with S. aureus bloodstream infections. At an area under the serum concentration time curve (AUC) threshold of 400 mg∙h/L, we would have reached the current Infectious Diseases Society of America (IDSA)/American Society of Health System Pharmacists (ASHP)/Society of Infectious Diseases Pharmacists (SIDP) guideline suggested AUC/MIC target in almost 100% of patients while using the Vitek 2 MIC data; however, we could only generate 40% target attainment while using E-test MIC data ( p < 0.0001). An AUC of 450 mg∙h/L or greater was required to achieve 100% target attainment using either Vitek 2 or E-test MIC results.

Comparison between the story recall test and the word-list learning test in Korean patients with mild cognitive impairment and early stage of Alzheimer's disease.

PubMed

Baek, Min Jae; Kim, Hyun Jung; Kim, Sangyun

2012-01-01

Among verbal memory tests, two that are commonly used to measure the ability of verbal memory function in cognitive impairment are story recall tests and word-list learning tests. However, research is limited regarding which test might be more sensitive in discriminating between normal cognitive aging and patients with Alzheimer's disease (AD) in the Korean population. The purpose of the current study was to compare the word-list learning test (Seoul Verbal Learning Test; SVLT) and the story recall test (Korean Story Recall Test; KSRT) to determine which test is more sensitive in discriminating between individuals with normal cognitive aging and patients with mild cognitive impairment (MCI) and early stage of AD in Korea. A total of 53 healthy adults, 127 patients with MCI, and 72 patients with early stage of AD participated in this study. The receiver-operating characteristic (ROC) curve and area under the curve (AUC) were evaluated to compare these two tests. The results showed that the AUC of the SVLT was significantly larger than the AUC of the KSRT in all three groups (healthy adults vs. MCI and early stage of AD; healthy adults vs. MCI; healthy adults vs. early stage of AD). However, in comparison of patients with MCI and early stage of AD, the AUC of SVLT and the AUC of KSRT were not significant. The word-list learning test is a more useful tool for examining verbal memory function for older adults in Korea than the story recall test.

Measurement of glucose area under the curve using minimally invasive interstitial fluid extraction technology: evaluation of glucose monitoring concepts without blood sampling.

PubMed

Sato, Toshiyuki; Okada, Seiki; Hagino, Kei; Asakura, Yoshihiro; Kikkawa, Yasuo; Kojima, Junko; Watanabe, Toshihiro; Maekawa, Yasunori; Isobe, Kazuki; Koike, Reona; Nakajima, Hiromu; Asano, Kaoru

2011-12-01

Monitoring postprandial hyperglycemia is crucial in treating diabetes, although its dynamics make accurate monitoring difficult. We developed a new technology for monitoring postprandial hyperglycemia using interstitial fluid (ISF) extraction technology without blood sampling. The glucose area under the curve (AUC) using this system was measured as accumulated ISF glucose (IG) with simultaneous calibration with sodium ions. The objective of this study was to evaluate this technological concept in healthy individuals. Minimally invasive ISF extraction technology (MIET) comprises two steps: pretreatment with microneedles and ISF accumulation over a specific time by contact with a solvent. The correlation between glucose and sodium ion levels using MIET was evaluated in 12 subjects with stable blood glucose (BG) levels during fasting. BG and IG time courses were evaluated in three subjects to confirm their relationship while BG was fluctuating. Furthermore, the accuracy of glucose AUC measurements by MIET was evaluated several hours after a meal in 30 subjects. A high correlation was observed between glucose and sodium ion levels when BG levels were stable (R=0.87), indicating that sodium ion is a good internal standard for calibration. The variation in IG and BG with MIET was similar, indicating that IG is an adequate substitute for BG. Finally, we showed a strong correlation (R=0.92) between IG-AUC and BG-AUC after a meal. These findings validate the adequacy of glucose AUC measurements using MIET. Monitoring glucose using MIET without blood sampling may be beneficial to patients with diabetes.

Pharmacokinetics and bioavailability of single dose ibuprofen and pseudoephedrine alone or in combination: a randomized three-period, cross-over trial in healthy Indian volunteers

PubMed Central

Kale, Prashant

2014-01-01

Objective: To compare the bioavailability of single dose ibuprofen 200 mg and pseudoephedrine hydrochloride 30 mg administered alone or in combination as an oral suspension. Methods: This was a single-center, randomized, single-dose, open-label, 3-period, crossover study. After an overnight fast (≥10 h), 18 healthy male subjects received either ibuprofen 200 mg (reference-A), pseudoephedrine 30 mg (reference-B) or the combination (test-C) as a suspension, on 3 separate visits, with blood sampling up to 36-h post-dose. The primary pharmacokinetic parameters, maximum plasma concentration (Cmax) and area under the plasma concentration–time curve (AUC) from time zero to last measurable concentration (AUC0−t) and extrapolated to infinity (AUC0−∞) were compared by an analysis of variance using log-transformed data. Bioequivalence was concluded if the 90% confidence intervals (CIs) of the adjusted geometric mean (gMean) ratios for Cmax and AUC were within the predetermined range of 80–125%, in accordance with regulatory requirements. Results: For the test formulation, the ibuprofen gMean Cmax was 17.0 μg/mL (vs. 18.1 μg/mL for reference-A), AUC0−t was 57.1 (vs. 60.0 μg·h/mL), and AUC0−∞ was 59.9 μg·h/mL (vs. 63.1 μg·h/mL). The 90% CIs for the ratio (test/reference-A) were 81.0–108.1% for Cmax, 91.5–98.4% for AUC0−t and 91.6–97.9% for AUC0−∞. For pseudoephedrine, the gMean Cmax for the test formulation was 97.2 ng/mL (vs. 98.5 ng/mL for reference-B), AUC0−t was 878.4 (vs. 842.8 ng·h/mL) and AUC0−∞ was 907.8 ng·h/mL (vs. 868.3 ng·h/mL). The 90% CIs for the ratio (test/reference-B) were 92.4–106.9% for Cmax, 97.7–111.0% for AUC0−t and 97.9–111.3% for AUC0−∞. All treatments were well tolerated. Conclusion: This oral suspension containing ibuprofen and pseudoephedrine combined in a new formulation met the regulatory criterion for bioequivalence compared with oral suspensions containing the individual components. PMID:24847268

Advances in SCA and RF-DNA Fingerprinting Through Enhanced Linear Regression Attacks and Application of Random Forest Classifiers

DTIC Science & Technology

2014-09-18

Converter AES Advance Encryption Standard ANN Artificial Neural Network APS Application Support AUC Area Under the Curve CPA Correlation Power Analysis ...Importance WGN White Gaussian Noise WPAN Wireless Personal Area Networks XEnv Cross-Environment XRx Cross-Receiver xxi ADVANCES IN SCA AND RF-DNA...based tool called KillerBee was released in 2009 that increases the exposure of ZigBee and other IEEE 802.15.4-based Wireless Personal Area Networks

Applying an Evidence-Based Assessment Model to Identify Students at Risk for Perceived Academic Problems following Concussion.

PubMed

Ransom, Danielle M; Burns, Alison R; Youngstrom, Eric A; Vaughan, Christopher G; Sady, Maegan D; Gioia, Gerard A

2016-11-01

The aim of this study was to demonstrate the utility of an evidence-based assessment (EBA) model to establish a multimodal set of tools for identifying students at risk for perceived post-injury academic problems. Participants included 142 students diagnosed with concussion (age: M=14.95; SD=1.80; 59% male), evaluated within 4 weeks of injury (median=16 days). Demographics, pre-injury history, self- and parent-report measures assessing symptom severity and executive functions, and cognitive test performance were examined as predictors of self-reported post-injury academic problems. Latent class analysis categorized participants into "high" (44%) and "low" (56%) levels of self-reported academic problems. Receiver operating characteristic analyses revealed significant discriminative validity for self- and parent-reported symptom severity and executive dysfunction and self-reported exertional response for identifying students reporting low versus high academic problems. Parent-reported symptom ratings [area under the receiver operating characteristic curve (AUC)=.79] and executive dysfunction (AUC=.74), and self-reported ratings of executive dysfunction (AUC=.84), symptoms (AUC=.80), and exertional response (AUC=.70) each classified students significantly better than chance (ps<.001). Hierarchical logistic regression indicated that, of the above, self-reported symptoms and executive dysfunction accounted for the most variance in the prediction of self-reported academic problems. Post-concussion symptom severity and executive dysfunction significantly predict perceived post-injury academic problems. EBA modeling identified the strongest set of predictors of academic challenges, offering an important perspective in the management of concussion by applying traditional strengths of neuropsychological assessment to clinical decision making. (JINS, 2016, 22, 1038-1049).

The development and validation of a novel model for predicting surgical complications in colorectal cancer of elderly patients: Results from 1008 cases.

PubMed

Shen, Zhanlong; Lin, Yuanpei; Ye, Yingjiang; Jiang, Kewei; Xie, Qiwei; Gao, Zhidong; Wang, Shan

2018-04-01

To establish predicting models of surgical complications in elderly colorectal cancer patients. Surgical complications are usually critical and lethal in the elderly patients. However, none of the current models are specifically designed to predict surgical complications in elderly colorectal cancer patients. Details of 1008 cases of elderly colorectal cancer patients (age ≥ 65) were collected retrospectively from January 1998 to December 2013. Seventy-six clinicopathological variables which might affect postoperative complications in elderly patients were recorded. Multivariate stepwise logistic regression analysis was used to develop the risk model equations. The performance of the developed model was evaluated by measures of calibration (Hosmer-Lemeshow test) and discrimination (the area under the receiver-operator characteristic curve, AUC). The AUC of our established Surgical Complication Score for Elderly Colorectal Cancer patients (SCSECC) model was 0.743 (sensitivity, 82.1%; specificity, 78.3%). There was no significant discrepancy between observed and predicted incidence rates of surgical complications (AUC, 0.820; P = .812). The Surgical Site Infection Score for Elderly Colorectal Cancer patients (SSISECC) model showed significantly better prediction power compared to the National Nosocomial Infections Surveillance index (NNIS) (AUC, 0.732; P ˂ 0.001) and Efficacy of Nosocomial Infection Control index (SENIC) (AUC; 0.686; P˂0.001) models. The SCSECC and SSISECC models show good prediction power for postoperative surgical complication morbidity and surgical site infection in elderly colorectal cancer patients. Copyright © 2018 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Reliability of blood color and blood gases in discriminating arterial from venous puncture during cardiopulmonary resuscitation.

PubMed

Park, Je Sung; Lee, Byung Kook; Jeung, Kyung Woon; Choi, Sung Soo; Park, Sang Wook; Song, Kyung Hwan; Lee, Sung Min; Heo, Tag; Min, Yong Il

2015-04-01

We investigated the use of blood color brightness and blood gas variables for discriminating arterial from venous puncture during cardiopulmonary resuscitation (CPR). The study's aims were to determine if discrimination using Po2 is superior to using blood color brightness, and if blood color brightness, Po2, and acid-base variables derived from blood gas analysis accurately discriminate arterial from venous blood during CPR. Fifteen pigs underwent ventricular fibrillation followed by CPR. During CPR, paired femoral arterial and venous blood samples were obtained, and 2 blinded observers were asked to identify the blood's origin. Blood color brightness was measured using a blood brightness scale (BBS). The discriminatory performances of the BBS and blood gas variables were evaluated by calculating the area under receiver operating characteristic curves (AUC). The observers accurately discriminated arterial from venous blood with a sensitivity of 97.0% (84.7%-99.5%) and specificity of 84.9% (69.1%-93.4%). The BBS (AUC = 0.983) and Po2 (AUC = 0.981) methods both showed comparable and excellent discriminatory performances. pH, Pco2, and HCO3(-) all discriminated arterial from venous blood (AUC = 0.831, 0.971, and 0.652, respectively). The AUC for Pco2 was comparable to that for Po2 but significantly larger than that for pH (P = .002) or HCO3(-) (P < .001). The BBS and Po2 methods showed comparable and excellent discrimination performances. Using pH, Pco2, and HCO3(-) levels also discriminated arterial from venous blood during CPR with statistical significance. Copyright © 2015 Elsevier Inc. All rights reserved.

Three-dimensional shear wave elastography for differentiation of breast lesions: An initial study with quantitative analysis using three orthogonal planes.

PubMed

Wang, Qiao

2018-05-25

To prospectively evaluate the diagnostic performance of three-dimensional (3D) shear wave elastography (SWE) for breast lesions with quantitative stiffness information from transverse, sagittal and coronal planes. Conventional ultrasound (US), two-dimensional (2D)-SWE and 3D-SWE were performed for 122 consecutive patients with 122 breast lesions before biopsy or surgical excision. Maximum elasticity values of Young's modulus (Emax) were recorded on 2D-SWE and three planes of 3D-SWE. Area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, 2D-SWE and 3D-SWE were evaluated. Two combined sets (i.e., BI-RADS and 2D-SWE; BI-RADS and 3D-SWE) were compared in AUC. Observer consistency was also evaluated. On 3D-SWE, the AUC and sensitivity of sagittal plane were significantly higher than those of transverse and coronal planes (both P < 0.05). Compared with BI-RADS alone, both combined sets had significantly (P < 0.05) higher AUCs and specificities, whereas, the two combined sets showed no significant difference in AUC (P > 0.05). However, the combined set of BI-RADS and sagittal plane of 3D-SWE had significantly higher sensitivity than the combined set of BI-RADS and 2D-SWE. The sagittal plane shows the best diagnostic performance among 3D-SWE. The combination of BI-RADS and 3D-SWE is a useful tool for predicting breast malignant lesions in comparison with BI-RADS alone.

Limited diagnostic value of Dual-Time-Point (18)F-FDG PET/CT imaging for classifying solitary pulmonary nodules in granuloma-endemic regions both at visual and quantitative analyses.

PubMed

Chen, Song; Li, Xuena; Chen, Meijie; Yin, Yafu; Li, Na; Li, Yaming

2016-10-01

This study is aimed to compare the diagnostic power of using quantitative analysis or visual analysis with single time point imaging (STPI) PET/CT and dual time point imaging (DTPI) PET/CT for the classification of solitary pulmonary nodules (SPN) lesions in granuloma-endemic regions. SPN patients who received early and delayed (18)F-FDG PET/CT at 60min and 180min post-injection were retrospectively reviewed. Diagnoses are confirmed by pathological results or follow-ups. Three quantitative metrics, early SUVmax, delayed SUVmax and retention index(the percentage changes between the early SUVmax and delayed SUVmax), were measured for each lesion. Three 5-point scale score was given by blinded interpretations performed by physicians based on STPI PET/CT images, DTPI PET/CT images and CT images, respectively. ROC analysis was performed on three quantitative metrics and three visual interpretation scores. One-hundred-forty-nine patients were retrospectively included. The areas under curve (AUC) of the ROC curves of early SUVmax, delayed SUVmax, RI, STPI PET/CT score, DTPI PET/CT score and CT score are 0.73, 0.74, 0.61, 0.77 0.75 and 0.76, respectively. There were no significant differences between the AUCs in visual interpretation of STPI PET/CT images and DTPI PET/CT images, nor in early SUVmax and delayed SUVmax. The differences of sensitivity, specificity and accuracy between STPI PET/CT and DTPI PET/CT were not significantly different in either quantitative analysis or visual interpretation. In granuloma-endemic regions, DTPI PET/CT did not offer significant improvement over STPI PET/CT in differentiating malignant SPNs in both quantitative analysis and visual interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Diurnal Salivary Cortisol and Urinary Catecholamines Are Associated With Diabetes Mellitus: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Champaneri, Shivam; Xu, Xiaoqiang; Carnethon, Mercedes R.; Bertoni, Alain G.; Seeman, Teresa; Roux, Ana Diez; Golden, Sherita Hill

2011-01-01

Objective To examine the cross-sectional association of diurnal salivary cortisol curve components and urinary catecholamines with diabetes status. Methods Up to 18 salivary cortisol samples over 3 days and overnight urinary catecholamines were collected from 1,002 participants in the Multi-Ethnic Study of Atherosclerosis. Diabetes was defined as a fasting blood glucose ≥126 mg/dL or medication use. Cortisol curve measures included awakening cortisol, cortisol awakening response (CAR), early decline, late decline, and cortisol area under the curve (AUC). Urinary catecholamines included epinephrine, norepinephrine, and dopamine. Results Participants with diabetes had significantly lower CAR (β=−0.19; 95% CI: −0.34 to −0.04) than those without diabetes in multivariable models. While men with diabetes had a non-significant trend toward lower total AUC (β=−1.56; 95% CI: −3.93 to 0.80), women with diabetes had significantly higher total AUC (β=2.62; 95% CI: 0.72 to 4.51) (p=0.02 for interaction) compared to those without diabetes. Men but not women with diabetes had significantly lower urinary catecholamines, compared to those without diabetes (p<0.05). Conclusions Diabetes is associated with neuroendocrine dysregulation, which may differ by sex. Further studies are needed to determine the role of the neuroendocrine system in the pathophysiology of diabetes. PMID:22209664

Digital tomosynthesis for evaluating metastatic lung nodules: nodule visibility, learning curves, and reading times.

PubMed

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyungjin; Song, Yong Sub; Hwang, Eui Jin

2015-01-01

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, ≤ 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Prostate-specific antigen velocity is not better than total prostate-specific antigen in predicting prostate biopsy diagnosis.

PubMed

Gorday, William; Sadrzadeh, Hossein; de Koning, Lawrence; Naugler, Christopher T

2015-12-01

1.) Identify whether prostate-specific antigen velocity improves the ability to predict prostate biopsy diagnosis. 2.) Test whether there is an increase in the predictive capability of models when Gleason 7 prostate cancers are separated into a 3+4 and a 4+3 group. Calgary Laboratory Services' Clinical Laboratory Information System was searched for prostate biopsies reported between January 1, 2009 and December 31, 2013. Total prostate-specific antigen tests were recorded for each patient from January 1, 2007 to the most recent test before their recorded prostate biopsy. The data set was divided into the following three groups for comparison; benign, all prostate cancer and Gleason 7-10. The Gleason grade 7-10 group was further divided into 4+3 and 3+4 Gleason 7 prostate cancers. Prostate-specific antigen velocity was calculated using four different methods found in the literature. Receiver operator curves were used to assess operational characteristics of the tests. 4622 men between the ages of 40-89 with a prostate biopsy were included for analysis. Combining prostate-specific antigen velocity with total prostate-specific antigen (AUC=0.570-0.712) resulted in small non-statistically significant changes to the area under the curve compared to the area under the curve of total prostate-specific antigen alone (AUC=0.572-0.699). There were marked increases in the area under curves when 3+4 and 4+3 Gleason 7 cancers were separated. Prostate-specific antigen velocity does not add predictive value for prostate biopsy diagnosis. The clinical significance of the prostate specific antigen test can be improved by separating Gleason 7 prostate cancers into a 3+4 and 4+3 group. Copyright © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia

PubMed Central

Omura, Nobuo; Tsuboi, Kazuto; Hoshino, Masato; Yamamoto, Seryung; Akimoto, Shunsuke; Masuda, Takahiro; Kashiwagi, Hideyuki; Yanaga, Katsuhiko

2017-01-01

Purpose Although laparoscopic Heller myotomy and Dor fundoplication (LHD) is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD. Methods Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC) curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve. Results We defined the completion of the learning curve when the following 3 conditions were satisfied. 1) The operation time was less than 165 minutes. 2) There was no blood loss. 3) There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001). Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646). Conclusion Learning curve seems to complete after performing 16 cases. PMID:28686640

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia.

PubMed

Yano, Fumiaki; Omura, Nobuo; Tsuboi, Kazuto; Hoshino, Masato; Yamamoto, Seryung; Akimoto, Shunsuke; Masuda, Takahiro; Kashiwagi, Hideyuki; Yanaga, Katsuhiko

2017-01-01

Although laparoscopic Heller myotomy and Dor fundoplication (LHD) is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD. Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC) curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve. We defined the completion of the learning curve when the following 3 conditions were satisfied. 1) The operation time was less than 165 minutes. 2) There was no blood loss. 3) There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001). Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646). Learning curve seems to complete after performing 16 cases.

Raman Spectroscopic Analysis of Fingernail Clippings Can Help Differentiate Between Postmenopausal Women Who Have and Have Not Suffered a Fracture

PubMed Central

Beattie, James R.; Cummins, Niamh M.; Caraher, Clare; O’Driscoll, Olive M.; Bansal, Aruna T.; Eastell, Richard; Ralston, Stuart H.; Stone, Michael D.; Pearson, Gill; Towler, Mark R.

2016-01-01

Raman spectroscopy was applied to nail clippings from 633 postmenopausal British and Irish women, from six clinical sites, of whom 42% had experienced a fragility fracture. The objective was to build a prediction algorithm for fracture using data from four sites (known as the calibration set) and test its performance using data from the other two sites (known as the validation set). Results from the validation set showed that a novel algorithm, combining spectroscopy data with clinical data, provided area under the curve (AUC) of 74% compared to an AUC of 60% from a reduced QFracture score (a clinically accepted risk calculator) and 61% from the dual-energy X-ray absorptiometry T-score, which is in current use for the diagnosis of osteoporosis. Raman spectroscopy should be investigated further as a noninvasive tool for the early detection of enhanced risk of fragility fracture. PMID:27429561

Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

PubMed

Song, Yang; Zhang, Yu-Dong; Yan, Xu; Liu, Hui; Zhou, Minxiong; Hu, Bingwen; Yang, Guang

2018-04-16

Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI). To develop an automatic approach based on deep convolutional neural network (DCNN) to classify PCa and noncancerous tissues (NC) with mp-MRI. Retrospective. In all, 195 patients with localized PCa were collected from a PROSTATEx database. In total, 159/17/19 patients with 444/48/55 observations (215/23/23 PCas and 229/25/32 NCs) were randomly selected for training/validation/testing, respectively. T 2 -weighted, diffusion-weighted, and apparent diffusion coefficient images. A radiologist manually labeled the regions of interest of PCas and NCs and estimated the Prostate Imaging Reporting and Data System (PI-RADS) scores for each region. Inspired by VGG-Net, we designed a patch-based DCNN model to distinguish between PCa and NCs based on a combination of mp-MRI data. Additionally, an enhanced prediction method was used to improve the prediction accuracy. The performance of DCNN prediction was tested using a receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Moreover, the predicted result was compared with the PI-RADS score to evaluate its clinical value using decision curve analysis. Two-sided Wilcoxon signed-rank test with statistical significance set at 0.05. The DCNN produced excellent diagnostic performance in distinguishing between PCa and NC for testing datasets with an AUC of 0.944 (95% confidence interval: 0.876-0.994), sensitivity of 87.0%, specificity of 90.6%, PPV of 87.0%, and NPV of 90.6%. The decision curve analysis revealed that the joint model of PI-RADS and DCNN provided additional net benefits compared with the DCNN model and the PI-RADS scheme. The proposed DCNN-based model with enhanced prediction yielded high performance in statistical analysis, suggesting that DCNN could be used in computer-aided diagnosis (CAD) for PCa classification. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Diagnostic Value of Methylated Septin9 for Colorectal Cancer Screening: A Meta-Analysis

PubMed Central

Yan, Shirong; Liu, Zijing; Yu, Shuang; Bao, Yixi

2016-01-01

Background Septin9 is a member of GTP-binding protein family, and is used as a predictive diagnostic index. However, it has not been widely adopted due to inconsistent results reported in the literature. The present study was performed to determine the diagnostic accuracy of methylated Septin9 (mSEPT9) for colorectal cancer (CRC) and to evaluate its utility in CRC screening. Material/Methods After reviewing relevant studies, accuracy measures (pooled sensitivity and specificity, positive/negative likelihood ratio [PLR/NLR], and diagnostic odds ratio [DOR]) were calculated for mSEPT9 in the diagnosis of CRC. Overall test performance was summarized using summary receiver operating characteristic curve analysis. Potential between-study heterogeneity was explored by use of a meta-regression model. We divided included studies into Epi proColon test and non-Epi proColon test subgroups. We compared the effects of mSEPT9 and fecal occult blood test (FOBT) for CRC screening. Results A total of 9870 subjects in 14 studies were recruited. Pooled sensitivity and specificity, PLR, NLR, DOR, and corresponding 95% confidence intervals (CI) of mSEPT9 for CRC diagnosis were 0.66 (95% CI: 0.64–0.69), 0.91 (95% CI: 0.90–0.91), 5.59 (95% CI: 4.03–7.74), 0.37 (95% CI: 0.29–0.48), and 16.79 (95% CI: 10.54–26.76), respectively. The area under the summary ROC curve (AUC) was 0.8563. The AUCs in the Epi proColon test and non-Epi proColon test for CRC diagnosis were 0.8709 and 0.7968, respectively. In head-to-head comparison, AUC of mSEPT9 and FOBT for CRC diagnosis were 0.7857 and 0.6571, respectively. Conclusions The present study demonstrates that mSEPT9 can be a good diagnostic biomarker complementary to FOBT as a screening tool for CRC. PMID:27665580

Diagnostic Value of Methylated Septin9 for Colorectal Cancer Screening: A Meta-Analysis.

PubMed

Yan, Shirong; Liu, Zijing; Yu, Shuang; Bao, Yixi

2016-09-25

BACKGROUND Septin9 is a member of GTP-binding protein family, and is used as a predictive diagnostic index. However, it has not been widely adopted due to inconsistent results reported in the literature. The present study was performed to determine the diagnostic accuracy of methylated Septin9 (mSEPT9) for colorectal cancer (CRC) and to evaluate its utility in CRC screening. MATERIAL AND METHODS After reviewing relevant studies, accuracy measures (pooled sensitivity and specificity, positive/negative likelihood ratio [PLR/NLR], and diagnostic odds ratio [DOR]) were calculated for mSEPT9 in the diagnosis of CRC. Overall test performance was summarized using summary receiver operating characteristic curve analysis. Potential between-study heterogeneity was explored by use of a meta-regression model. We divided included studies into Epi proColon test and non-Epi proColon test subgroups. We compared the effects of mSEPT9 and fecal occult blood test (FOBT) for CRC screening. RESULTS A total of 9870 subjects in 14 studies were recruited. Pooled sensitivity and specificity, PLR, NLR, DOR, and corresponding 95% confidence intervals (CI) of mSEPT9 for CRC diagnosis were 0.66 (95% CI: 0.64-0.69), 0.91 (95% CI: 0.90-0.91), 5.59 (95% CI: 4.03-7.74), 0.37 (95% CI: 0.29-0.48), and 16.79 (95% CI: 10.54-26.76), respectively. The area under the summary ROC curve (AUC) was 0.8563. The AUCs in the Epi proColon test and non-Epi proColon test for CRC diagnosis were 0.8709 and 0.7968, respectively. In head-to-head comparison, AUC of mSEPT9 and FOBT for CRC diagnosis were 0.7857 and 0.6571, respectively. CONCLUSIONS The present study demonstrates that mSEPT9 can be a good diagnostic biomarker complementary to FOBT as a screening tool for CRC.

Prognostic implications of surrogate markers of atherosclerosis in low to intermediate risk patients with Type 2 Diabetes

PubMed Central

2012-01-01

Background Type 2 diabetes mellitus (T2DM) patients are at increased risk of developing cardiovascular events. Unfortunately traditional risk assessment scores, including the Framingham Risk Score (FRS), have only modest accuracy in cardiovascular risk prediction in these patients. Methods We sought to determine the prognostic values of different non-invasive markers of atherosclerosis, including brachial artery endothelial function, carotid artery atheroma burden, ankle-brachial index, arterial stiffness and computed tomography coronary artery calcium score (CACS) in 151 T2DM Chinese patients that were identified low-intermediate risk from the FRS recalibrated for Chinese (<20% risk in 10 years). Patients were prospectively followed-up and presence of atherosclerotic events documented for a mean duration of 61 ± 16 months. Results A total of 17 atherosclerotic events in 16 patients (11%) occurred during the follow-up period. The mean FRS of the study population was 5.0 ± 4.6% and area under curve (AUC) from receiver operating characteristic curve analysis for prediction of atherosclerotic events was 0.59 ± 0.07 (P = 0.21). Among different vascular assessments, CACS > 40 had the best prognostic value (AUC 0.81 ± 0.06, P < 0.01) and offered significantly better accuracy in prediction compared with FRS (P = 0.038 for AUC comparisons). Combination of FRS with CACS or other surrogate vascular markers did not further improve the prognostic values over CACS alone. Multivariate Cox regression analysis identified CACS > 40 as an independent predictor of atherosclerotic events in T2DM patients (Hazards Ratio 27.11, 95% Confidence Interval 3.36-218.81, P = 0.002). Conclusions In T2DM patients identified as low-intermediate risk by the FRS, a raised CACS > 40 was an independent predictor for atherosclerotic events. PMID:22900680

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

The effect of weight, body mass index, age, sex, and race on plasma concentrations of subcutaneous sumatriptan: a pooled analysis.

PubMed

Munjal, Sagar; Gautam, Anirudh; Rapoport, Alan M; Fisher, Dennis M

2016-01-01

Factors such as body size (weight and body mass index [BMI]), age, sex, and race might influence the clinical response to sumatriptan. We evaluated the impact of these covariates on the plasma concentration (Cp) profile of sumatriptan administered subcutaneously. We conducted three pharmacokinetic studies of subcutaneous sumatriptan in 98 healthy adults. Sumatriptan was administered subcutaneously (236 administrations) as either DFN-11 3 mg, a novel 0.5 mL autoinjector being developed by Dr. Reddy's Laboratories; Imitrex(®) (Sumatriptan) injection 3 mg or 6 mg (6 mg/0.5 mL); or Imitrex STATdose 4 mg or 6 mg (0.5 mL). Blood was sampled for 12 hours to determine sumatriptan Cp. Maximum Cp (Cmax), area under the curve during the first 2 hours (AUC0-2), and total area under the curve (AUC0-∞) were determined using noncompartmental methods. Post hoc analyses were conducted to determine the relationship between these exposure metrics and each of body weight, BMI, age, sex, and race (categorized as white, black, or others). Both weight and BMI correlated negatively with each exposure metric for each treatment group. Across all treatment groups, AUC0-2 for subjects with BMI less than or equal to median value was 1.03-1.12 times the value for subjects with BMI more than median value. For subjects with BMI less than or equal to median value receiving DFN-11, median AUC0-2 was slightly less than that for subjects with BMI more than median value receiving Imitrex 4 mg and larger than that for subjects with BMI more than median value receiving Imitrex 3 mg. Results were similar for the other exposure metrics and for weight. Exposure was higher in women than in men, which can be attributed in part to differences in weight. There was no relationship between exposure and age. For DFN-11, AUC0-2 and AUC0-∞ were lower in nonwhites compared with whites; the ratio of median values was 0.84 and 0.89, respectively. A similar, nonstatistically significant, trend was observed in the other products (ratio of median values ranging from 0.84 to 0.89). Weight and BMI appear to be important covariates for sumatriptan exposure: subjects with lower values for either metric of body size have higher systemic exposure compared with subjects with higher values. Additional studies are required to determine if doses of subcutaneous sumatriptan may be adjusted based on BMI for comparable efficacy and a potentially improved tolerability profile.

Usefulness of the Waist Circumference-to-Height Ratio in Screening for Obesity and Metabolic Syndrome among Korean Children and Adolescents: Korea National Health and Nutrition Examination Survey, 2010-2014.

PubMed

Choi, Dong-Hyun; Hur, Yang-Im; Kang, Jae-Heon; Kim, Kyoungwoo; Cho, Young Gyu; Hong, Soo-Min; Cho, Eun Byul

2017-03-10

The aims of this study were to assess the diagnostic value of the weight-to-height ratio (WHtR) for the detection of obesity and metabolic syndrome (MS) in Korean children and adolescents, and to determine the advantages of WHtR as a population-based screening tool in comparison with other obesity indicators, such as body mass index (BMI) and waist circumference (WC). We performed a cross-sectional analysis of data from 3057 children and adolescents (1625 boys, 1332 girls) aged 10-19 years who were included in the fifth Korean National Health and Nutrition Examination Survey (KNHANES, 2010-2012) up to the second year of the sixth KNHANES (2013-2014). Receiver operation characteristic (ROC) curves were generated to determine the optimal cutoff value and accuracy of WHtR for predicting individual obesity indicators or more than two non-WC components of MS. The area under the ROC curve (AUC) is a measure of the diagnostic power of a test. A perfect test will have an AUC of 1.0, and an AUC equal to 0.5 means that the test performs no better than chance. The optimal WHtR cutoff for the evaluation of general obesity and central obesity was 0.50 in boys and 0.47-0.48 in girls, and the AUC was 0.9. Regarding the assessment of each MS risk factor, the optimal WHtR cutoff was 0.43-0.50 in boys and 0.43-0.49 in girls, and these cutoffs were statistically significant only for the detection of high triglyceride and low High-density lipoprotein (HDL) cholesterol levels. When a pairwise comparison of the AUCs was conducted between WHtR and BMI/WC percentiles to quantify the differences in power for MS screening, the WHtR AUC values (boys, 0.691; girls, 0.684) were higher than those of other indices; however, these differences were not statistically significant (boys, p = 0.467; girls, p = 0.51). The WHtR cutoff value was 0.44 (sensitivity, 67.7%; specificity, 64.6%) for boys and 0.43 (sensitivity, 66.4%; specificity, 66.9%) for girls. There was no significant difference between the diagnostic power of WHtR and that of BMI/WC when screening for MS. Although the use of WHtR was not superior, WHtR is still useful as a screening tool for metabolic problems related to obesity because of its convenience.

Predictive Accuracy of Calf Circumference Measurements to Detect Decreased Skeletal Muscle Mass and European Society for Clinical Nutrition and Metabolism-Defined Malnutrition in Hospitalized Older Patients.

PubMed

Maeda, Keisuke; Koga, Takayuki; Nasu, Tomomi; Takaki, Miki; Akagi, Junji

2017-01-01

The ability to readily diagnose sarcopenia and malnutrition in a clinical setting is essential. This study is aimed at clarifying the calf circumference (CC) cut-off values for decreased skeletal muscle mass (SMM), according to the Asian Work Group for Sarcopenia's criteria definition of sarcopenia, and those for European Society for Clinical Nutrition and Metabolism-defined malnutrition, in hospitalized Japanese patients. The study involved 1,164 patients aged ≥65 years. Predictive CC cut-off values were determined using receiver operating curve (ROC) analyses. The predictive validity of the cut-off values was confirmed against in-hospital mortality. There were 654 females and 510 males (mean age, 83.5 ± 8.2 years). Decreased SMM and malnutrition were observed in 80.4 and 32.8% of all patients, respectively. ROC analyses identified CCs of ≤29 cm (female, area under the curve [AUC] 0.791) and ≤30 cm (male, AUC 0.832) as cut-off values for decreased SMM, and CCs of ≤26 cm (female, AUC 0.798) and ≤28 cm (male, AUC 0.837) for malnutrition. CC cut-off values for SMM and malnutrition were independently correlated with in-hospital mortality. The study determined appropriate cut-off values for CC to identify decreased SMM and malnutrition according to the relevant guidelines. © 2017 S. Karger AG, Basel.

Short-Term Effects of Lupin vs. Whey Supplementation on Glucose and Insulin Responses to a Standardized Meal in a Randomized Cross-Over Trial

PubMed Central

Schopen, Kathrin; Ewald, Ann C.; Johannes, Bernd W.; Bloch, Wilhelm; Rittweger, Jörn; Frings-Meuthen, Petra

2017-01-01

Background: Whey protein is known to reduce postprandial glycaemia in people with type 2 diabetes mellitus. Lupin as a vegetable source of protein could be considered as an alternative, as the percentage of vegetarian and vegan consumers is raising. The present study compares the acute glycemic effects of whey and lupin in healthy volunteers following a carbohydrate-rich reference meal. Methods In cross-over design, three standardized meals (reference meal; reference meal + whey; reference meal + lupin) were provided to 12 healthy male and female volunteers, aged between 23 and 33, in a balanced, randomized order. Volunteers' blood glucose and insulin concentrations were analyzed at baseline and at seven time points following the ingestion of the meals. Results: The supplementation of whey or lupin significantly blunted the postprandial increase in blood glucose concentrations compared to the reference meal (p < 0.001). In the overall statistical analysis, this effect was comparable for whey and lupin [Δ AUC whey-lupin = 8%, 0–60 min area under the curve (0–60 min AUC), p = 0.937], with a blunting effect of −46% by whey (p = 0.005, 0–60 min AUC) and of −54% by lupin (p < 0.001, 0–60 min AUC). When comparing whey and lupin data only, the insulin increase was found to be more pronounced for whey protein than for lupin supplementation (Δ AUC whey-lupin = 39%, 0–60 min AUC, p = 0.022). However, when comparing the insulin response of each supplementation to the one of the reference meal, no differences could be detected (whey p = 0.259, 0–60 min AUC; lupin p = 0.275, 0–60 min AUC). Conclusions: Results suggest that lupin and whey can both lower the increase of postprandial blood glucose concentrations to a comparable extent, implying the usability of lupin to reduce postprandial glycaemia. However, the insulin response following the supplementations to a carbohydrate-rich meal seems to differ for these two protein sources. PMID:28443026

Short-Term Effects of Lupin vs. Whey Supplementation on Glucose and Insulin Responses to a Standardized Meal in a Randomized Cross-Over Trial.

PubMed

Schopen, Kathrin; Ewald, Ann C; Johannes, Bernd W; Bloch, Wilhelm; Rittweger, Jörn; Frings-Meuthen, Petra

2017-01-01

Background: Whey protein is known to reduce postprandial glycaemia in people with type 2 diabetes mellitus. Lupin as a vegetable source of protein could be considered as an alternative, as the percentage of vegetarian and vegan consumers is raising. The present study compares the acute glycemic effects of whey and lupin in healthy volunteers following a carbohydrate-rich reference meal. Methods In cross-over design, three standardized meals (reference meal; reference meal + whey; reference meal + lupin) were provided to 12 healthy male and female volunteers, aged between 23 and 33, in a balanced, randomized order. Volunteers' blood glucose and insulin concentrations were analyzed at baseline and at seven time points following the ingestion of the meals. Results: The supplementation of whey or lupin significantly blunted the postprandial increase in blood glucose concentrations compared to the reference meal ( p < 0.001). In the overall statistical analysis, this effect was comparable for whey and lupin [Δ AUC whey-lupin = 8%, 0-60 min area under the curve (0-60 min AUC), p = 0.937], with a blunting effect of -46% by whey ( p = 0.005, 0-60 min AUC) and of -54% by lupin ( p < 0.001, 0-60 min AUC). When comparing whey and lupin data only, the insulin increase was found to be more pronounced for whey protein than for lupin supplementation (Δ AUC whey-lupin = 39%, 0-60 min AUC, p = 0.022). However, when comparing the insulin response of each supplementation to the one of the reference meal, no differences could be detected (whey p = 0.259, 0-60 min AUC; lupin p = 0.275, 0-60 min AUC). Conclusions: Results suggest that lupin and whey can both lower the increase of postprandial blood glucose concentrations to a comparable extent, implying the usability of lupin to reduce postprandial glycaemia. However, the insulin response following the supplementations to a carbohydrate-rich meal seems to differ for these two protein sources.

Fatty liver index vs waist circumference for predicting non-alcoholic fatty liver disease.

PubMed

Motamed, Nima; Sohrabi, Masoudreza; Ajdarkosh, Hossein; Hemmasi, Gholamreza; Maadi, Mansooreh; Sayeedian, Fatemeh Sima; Pirzad, Reza; Abedi, Khadijeh; Aghapour, Sivil; Fallahnezhad, Mojtaba; Zamani, Farhad

2016-03-14

To determine the discriminatory performance of fatty liver index (FLI) for non-alcoholic fatty liver disease (NAFLD). The data of 5052 subjects aged over 18 years were analyzed. FLI was calculated from body mass index, waist circumference (WC), triglyceride, and gamma glutamyl transferase data. Logistic regression analysis was conducted to determine the association between FLI and NAFLD. The discriminatory performance of FLI in the diagnosis of NAFLD was evaluated by receiver operating characteristic analysis. Area under the curves (AUCs) and related confidence intervals were estimated. Optimal cutoff points of FLI in the diagnosis of NAFLD were determined based on the maximum values of Youden's index. The mean age of men and women in the study population were 44.8 ± 16.8 and 43.78 ± 15.43, respectively (P = 0.0216). The prevalence of NAFLD was 40.1% in men and 44.2% in women (P < 0.0017). FLI was strongly associated with NAFLD, so that even a one unit increase in FLI increased the chance of developing NAFLD by 5.8% (OR = 1.058, 95%CI: 1.054-1.063, P < 0.0001). Although FLI showed good performance in the diagnosis of NAFLD (AUC = 0.8656 (95%CI: 0.8548-0.8764), there was no significant difference with regards to WC (AUC = 0.8533, 95%CI: 0.8419-0.8646). The performance of FLI was not significantly different between men (AUC = 0.8648, 95%CI: 0.8505-0.8791) and women (AUC = 0.8682, 95%CI: 0.8513-0.8851). The highest performance with regards to age was related to the 18-39 age group (AUC = 0.8930, 95%CI: 0.8766-0.9093). The optimal cutoff points of FLI were 46.9 in men (sensitivity = 0.8242, specificity = 0.7687, Youden's index = 0.5929) and 53.8 in women (sensitivity = 0.8233, specificity = 0.7655, Youden's index = 0.5888). Although FLI had acceptable discriminatory power in the diagnosis of NAFLD, WC was a simpler and more accessible index with a similar performance.

References of anthropometric indices of central obesity and metabolic syndrome in Jordanian men and women.

PubMed

Al-Odat, Areej Zaal; Ahmad, Mousa Numan; Haddad, Fares Halim

2012-01-01

To set references and evaluate the associations between the predictive powers of the anthropometric indices of obesity, particularly central obesity, including body mass index (BMI), waist circumference (WC), waist to hip ratio (WHpR) and waist to height ratio (WHtR), and the risk factor accumulations of ≥ 2 of the components of the metabolic syndrome (MS) in a group of Jordanian men and women. Five hundreds subjects were randomly selected from among the visitors attending several family clinics in Amman. Obesity was assessed using BMI, WC, WHpR and WHtR anthropometric indices. MS risk factors as defined by the International Diabetes Federation were determined. Receiver operating characteristic curve (ROC) analysis was used to determine the predictive powers and the cut off points of each index associated with increased MS risk. There were 212 men and 288 women with age ranged 20-85 years. Optimal cut off points of BMI, WC, WHpR for MS diagnosis in men were 28.4 kg/m(2), 97.8 cm and 0.89, respectively. In women, these were 30.3 kg/m(2), 95.6 cm and 0.84, respectively. WHtR was 0.61 in both genders. Area under the curve (AUC) of ROC analysis for identifying of MS (≥ 2 risk factors) was the highest for WHpR (AUC=0.71), followed by WHtR (AUC=0.67), WC (AUC=0.64) and BMI (AUC=0.59) in men; whereas in women WHpR, WHtR and WC were almost equal (AUC=0.76, 0.75 and 0.74, respectively), followed by BMI (AUC=0.67). Correlation coefficients (r) between WHpR and MS risk factors were the strongest among the other obesity indices, followed by WC and WHtR. WHpR correlated significantly with FBG (r=0.27, p<0.01), systolic blood pressure (r=0.20, p<0.01), TGs (r=0.24, p<0.01) and HDL-C (r=-0.39, p<0.01). The respective r-values between WC and WHtR and each MS risk factors were: FBG (r=0.15, p<0.001 or r=0.13, p<0.01), systolic blood pressure (r=0.16, p<0.01 or r=0.11, p<0.05), TGs (r=0.20, p<0.01 or r=0.14, p<0.01) and HDL-C (r=-0.25, p<0.01 or r=-0.11, p<0.01). This study showed that BMI tended to be the weakest index for identifying MS risk factors in both sexes. WHpR exhibited the best predictive index for MS, particularly in men. Almost similar predictive powers of WHtR, WHpR and WC for identifying MS risk factors were seen in women. WHtR had the highest sensitivity for MS diagnosis among obesity indices in men and its boundary value was the same for both men and women. These cut off values of obesity particularly waist circumference should be advocated and used in Arab Jordanians until larger cross sectional studies shows different results. Copyright © 2012 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Analysis of DCE-MRI features in tumor and the surrounding stroma for prediction of Ki-67 proliferation status in breast cancer

NASA Astrophysics Data System (ADS)

Li, Hui; Fan, Ming; Zhang, Peng; Li, Yuanzhe; Cheng, Hu; Zhang, Juan; Shao, Guoliang; Li, Lihua

2018-03-01

Breast cancer, with its high heterogeneity, is the most common malignancies in women. In addition to the entire tumor itself, tumor microenvironment could also play a fundamental role on the occurrence and development of tumors. The aim of this study is to investigate the role of heterogeneity within a tumor and the surrounding stromal tissue in predicting the Ki-67 proliferation status of oestrogen receptor (ER)-positive breast cancer patients. To this end, we collected 62 patients imaged with preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for analysis. The tumor and the peritumoral stromal tissue were segmented into 8 shells with 5 mm width outside of tumor. The mean enhancement rate in the stromal shells showed a decreasing order if their distances to the tumor increase. Statistical and texture features were extracted from the tumor and the surrounding stromal bands, and multivariate logistic regression classifiers were trained and tested based on these features. An area under the receiver operating characteristic curve (AUC) were calculated to evaluate performance of the classifiers. Furthermore, the statistical model using features extracted from boundary shell next to the tumor produced AUC of 0.796+/-0.076, which is better than that using features from the other subregions. Furthermore, the prediction model using 7 features from the entire tumor produced an AUC value of 0.855+/-0.065. The classifier based on 9 selected features extracted from peritumoral stromal region showed an AUC value of 0.870+/-0.050. Finally, after fusion of the predictive model obtained from entire tumor and the peritumoral stromal regions, the classifier performance was significantly improved with AUC of 0.920. The results indicated that heterogeneity in tumor boundary and peritumoral stromal region could be valuable in predicting the indicator associated with prognosis.

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, R; Aguilera, T; Shultz, D

2014-06-15

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayesmore » (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in identifying patients who might benefit from adjuvant therapy.« less

On a fractional order calculus model in diffusion weighted breast imaging to differentiate between malignant and benign breast lesions detected on X-ray screening mammography

PubMed Central

Steudle, Franziska; Paech, Daniel; Mlynarska, Anna; Kuder, Tristan Anselm; Lederer, Wolfgang; Daniel, Heidi; Freitag, Martin; Delorme, Stefan; Schlemmer, Heinz-Peter; Laun, Frederik Bernd

2017-01-01

Objective To evaluate a fractional order calculus (FROC) model in diffusion weighted imaging to differentiate between malignant and benign breast lesions in breast cancer screening work-up using recently introduced parameters (βFROC, DFROC and μFROC). Materials and methods This retrospective analysis within a prospective IRB-approved study included 51 participants (mean 58.4 years) after written informed consent. All patients had suspicious screening mammograms and indication for biopsy. Prior to biopsy, full diagnostic contrast-enhanced MRI examination was acquired including diffusion-weighted-imaging (DWI, b = 0,100,750,1500 s/mm2). Conventional apparent diffusion coefficient Dapp and FROC parameters (βFROC, DFROC and μFROC) as suggested further indicators of diffusivity components were measured in benign and malignant lesions. Receiver operating characteristics (ROC) were calculated to evaluate the diagnostic performance of the parameters. Results 29/51 patients histopathologically revealed malignant lesions. The analysis revealed an AUC for Dapp of 0.89 (95% CI 0.80–0.98). For FROC derived parameters, AUC was 0.75 (0.60–0.89) for DFROC, 0.59 (0.43–0.75) for βFROC and 0.59 (0.42–0.77) for μFROC. Comparison of the AUC curves revealed a significantly higher AUC of Dapp compared to the FROC parameters DFROC (p = 0.009), βFROC (p = 0.003) and μFROC (p = 0.001). Conclusion In contrast to recent description in brain tumors, the apparent diffusion coefficient Dapp showed a significantly higher AUC than the recently proposed FROC parameters βFROC, DFROC and μFROC for differentiating between malignant and benign breast lesions. This might be related to the intrinsic high heterogeneity within breast tissue or to the lower maximal b-value used in our study. PMID:28453516

Prognostic models for complete recovery in ischemic stroke: a systematic review and meta-analysis.

PubMed

Jampathong, Nampet; Laopaiboon, Malinee; Rattanakanokchai, Siwanon; Pattanittum, Porjai

2018-03-09

Prognostic models have been increasingly developed to predict complete recovery in ischemic stroke. However, questions arise about the performance characteristics of these models. The aim of this study was to systematically review and synthesize performance of existing prognostic models for complete recovery in ischemic stroke. We searched journal publications indexed in PUBMED, SCOPUS, CENTRAL, ISI Web of Science and OVID MEDLINE from inception until 4 December, 2017, for studies designed to develop and/or validate prognostic models for predicting complete recovery in ischemic stroke patients. Two reviewers independently examined titles and abstracts, and assessed whether each study met the pre-defined inclusion criteria and also independently extracted information about model development and performance. We evaluated validation of the models by medians of the area under the receiver operating characteristic curve (AUC) or c-statistic and calibration performance. We used a random-effects meta-analysis to pool AUC values. We included 10 studies with 23 models developed from elderly patients with a moderately severe ischemic stroke, mainly in three high income countries. Sample sizes for each study ranged from 75 to 4441. Logistic regression was the only analytical strategy used to develop the models. The number of various predictors varied from one to 11. Internal validation was performed in 12 models with a median AUC of 0.80 (95% CI 0.73 to 0.84). One model reported good calibration. Nine models reported external validation with a median AUC of 0.80 (95% CI 0.76 to 0.82). Four models showed good discrimination and calibration on external validation. The pooled AUC of the two validation models of the same developed model was 0.78 (95% CI 0.71 to 0.85). The performance of the 23 models found in the systematic review varied from fair to good in terms of internal and external validation. Further models should be developed with internal and external validation in low and middle income countries.

Antimüllerian hormone as predictor of implantation and clinical pregnancy after assisted conception: a systematic review and meta-analysis.

PubMed

Tal, Reshef; Tal, Oded; Seifer, Benjamin J; Seifer, David B

2015-01-01

To assess whether antimüllerian hormone (AMH) is a predictor of implantation and/or clinical pregnancy in women undergoing assisted reproductive technology. Systematic review and meta-analysis. Not applicable. Women undergoing IVF/intracytoplasmic sperm injection in nondonor cycles. Measurement of serum AMH level. Diagnostic odds ratio (OR) and summary receiver operating characteristic curve (AUC) for AMH as a predictor of implantation and/or clinical pregnancy. A total of 525 observational studies were identified, of which 19 were selected (comprising 5,373 women). Studies reporting clinical pregnancy rates in women with unspecified ovarian reserve (n = 11), diminished ovarian reserve (DOR) (n = 4), and polycystic ovary syndrome (n = 4) were included, together with studies reporting implantation rates (n = 4). The OR for AMH as a predictor of implantation in women with unspecified ovarian reserve (n = 1,591) was 1.83 (95% confidence interval [CI] 1.49-2.25), whereas the AUC was 0.591 (95% CI 0.563-0.618). The OR for AMH as a predictor of clinical pregnancy in these women (n = 4,324) was 2.10 (95% CI 1.82-2.41), whereas the AUC was 0.634 (95% CI 0.618-0.650). The predictive ability of AMH for pregnancy was greatest in women with DOR (n = 615), with OR and AUC of 3.96 (95% CI 2.57-6.10) and 0.696 (95% CI 0.641-0.751), respectively. In contrast, AMH had no significant predictive ability in women with PCOS (n = 414), with OR and AUC of 1.18 (95% CI 0.53-2.62) and 0.600 (95% CI 0.547-0.653), respectively. Antimüllerian hormone has weak association with implantation and clinical pregnancy rates in assisted reproductive technology but may still have some clinical utility in counseling women undergoing fertility treatment regarding pregnancy rates, particularly those with DOR. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

Volumetric characterization of human patellar cartilage matrix on phase contrast x-ray computed tomography

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Nagarajan, Mahesh B.; Checefsky, Walter A.; Coan, Paola; Diemoz, Paul C.; Hobbs, Susan K.; Huber, Markus B.; Wismüller, Axel

2015-03-01

Phase contrast X-ray computed tomography (PCI-CT) has recently emerged as a novel imaging technique that allows visualization of cartilage soft tissue, subsequent examination of chondrocyte patterns, and their correlation to osteoarthritis. Previous studies have shown that 2D texture features are effective at distinguishing between healthy and osteoarthritic regions of interest annotated in the radial zone of cartilage matrix on PCI-CT images. In this study, we further extend the texture analysis to 3D and investigate the ability of volumetric texture features at characterizing chondrocyte patterns in the cartilage matrix for purposes of classification. Here, we extracted volumetric texture features derived from Minkowski Functionals and gray-level co-occurrence matrices (GLCM) from 496 volumes of interest (VOI) annotated on PCI-CT images of human patellar cartilage specimens. The extracted features were then used in a machine-learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with GLCM features correlation (AUC = 0.83 +/- 0.06) and homogeneity (AUC = 0.82 +/- 0.07), which significantly outperformed all Minkowski Functionals (p < 0.05). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving GLCM-derived statistical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Diagnostic accuracy of presepsin (sCD14-ST) as a biomarker of infection and sepsis in the emergency department.

PubMed

de Guadiana Romualdo, Luis García; Torrella, Patricia Esteban; Acebes, Sergio Rebollo; Otón, María Dolores Albaladejo; Sánchez, Roberto Jiménez; Holgado, Ana Hernando; Santos, Enrique Jiménez; Freire, Alejandro Ortín

2017-01-01

Presepsin is a promising biomarker for the diagnosis and prognosis of sepsis. However, results reported about its value to diagnose sepsis in an emergency department (ED) are controversial, probably due to differences in the design of the studies. We have evaluated the diagnostic accuracy of presepsin for infection and sepsis, compared with procalcitonin (PCT) and C-reactive protein (CRP), in patients presenting to the emergency department (ED) with suspected infection. 223 patients with suspected infection were enrolled for the study. Blood samples were collected on admission for measurement of biomarkers. Definitive diagnosis was obtained afterwards by analysis of digital medical records. Receiver operating characteristic (ROC) curve analysis was conducted to determine the diagnostic accuracy. Infection was confirmed in 200 patients, including 130 with non-complicated infection and 70 with sepsis. Median CRP, PCT and presepsin levels were significantly higher in patients with infection and sepsis. PCT was the biomarker with the highest performance for infection (ROC AUC: 0.910); for sepsis, PCT (ROC AUC: 0.815) and presepsin (ROC AUC: 0.775) shown a similar performance. Although presepsin is a valuable biomarker for diagnosis of infection and sepsis, its diagnostic accuracy in our study does not improve that of PCT. Its introduction in clinical practice is not justified. Copyright © 2016 Elsevier B.V. All rights reserved.

An exposure-response analysis based on rifampin suggests CYP3A4 induction is driven by AUC: an in vitro investigation.

PubMed

Chang, Cheng; Yang, Xin; Fahmi, Odette A; Riccardi, Keith A; Di, Li; Obach, R Scott

2017-08-01

1. Induction is an important mechanism contributing to drug-drug interactions. It is most commonly evaluated in the human hepatocyte assay over 48-h or 72-h incubation period. However, whether the overall exposure (i.e. Area Under the Curve (AUC) or C ave ) or maximum exposure (i.e. C max ) of the inducer is responsible for the magnitude of subsequent induction has not been thoroughly investigated. Additionally, in vitro induction assays are typically treated as static systems, which could lead to inaccurate induction potency estimation. Hence, European Medicines Agency (EMA) guidance now specifies quantitation of drug levels in the incubation. 2. This work treated the typical in vitro evaluation of rifampin induction as an in vivo system by generating various target engagement profiles, measuring free rifampin concentration over 3 d of incubation and evaluating the impact of these factors on final induction response. 3. This rifampin-based analysis demonstrates that the induction process is driven by time-averaged target engagement (i.e. AUC-driven). Additionally, depletion of rifampin in the incubation medium over 3 d as well as non-specific/specific binding were observed. 4. These findings should help aid the discovery of clinical candidates with minimal induction liability and further expand our knowledge in the quantitative translatability of in vitro induction assays.

Assessment of endothelial dysfunction: the role of symmetrical dimethylarginine and proinflammatory markers in chronic kidney disease and renal transplant recipients.

PubMed

Memon, Lidija; Spasojevic-Kalimanovska, Vesna; Bogavac-Stanojevic, Natasa; Kotur-Stevuljevic, Jelena; Simic-Ogrizovic, Sanja; Giga, Vojislav; Dopsaj, Violeta; Jelic-Ivanovic, Zorana; Spasic, Slavica

2013-01-01

The study was designed to evaluate associations between symmetric dimethylarginine (SDMA), inflammation, and superoxide anion (O2∙-) with endothelial function and to determine their potential for screening of endothelial dysfunction in patients with chronic kidney disease (CKD) and renal transplant (RT) recipients. We included 64 CKD and 52 RT patients. Patients were stratified according to brachial artery flow-mediated dilation (FMD). Logistic regression analysis showed that high SDMA and high sensitive C-reactive protein (hs-CRP) were associated with impaired FMD in CKD and RT patients, after adjustment for glomerular filtration rate. The ability of inflammation, SDMA, and O2∙- to detect impaired FMD was investigated by receiving operative characteristic analysis. Hs-CRP (area under the curves (AUC) = 0.754, P < 0.001), IL-6 (AUC = 0.699, P = 0.002), and SDMA (AUC = 0.689, P = 0.007) had the highest ability to detect impaired FMD. SDMA in combination with inflammatory parameters and/or O2∙- had better screening performance than SDMA alone. Our results indicate a strong predictable association between hs-CRP, SDMA, and endothelial dysfunction in CKD patients and RT recipients. The individual marker that showed the strongest discriminative ability for endothelial dysfunction is hs-CRP, but its usefulness as a discriminatory marker for efficient diagnosis of endothelial dysfunction should be examined in prospective studies.

Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

NASA Astrophysics Data System (ADS)

Oustimov, Andrew; Gastounioti, Aimilia; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

2017-03-01

We assess the feasibility of a parenchymal texture feature fusion approach, utilizing a convolutional neural network (ConvNet) architecture, to benefit breast cancer risk assessment. Hypothesizing that by capturing sparse, subtle interactions between localized motifs present in two-dimensional texture feature maps derived from mammographic images, a multitude of texture feature descriptors can be optimally reduced to five meta-features capable of serving as a basis on which a linear classifier, such as logistic regression, can efficiently assess breast cancer risk. We combine this methodology with our previously validated lattice-based strategy for parenchymal texture analysis and we evaluate the feasibility of this approach in a case-control study with 424 digital mammograms. In a randomized split-sample setting, we optimize our framework in training/validation sets (N=300) and evaluate its descriminatory performance in an independent test set (N=124). The discriminatory capacity is assessed in terms of the the area under the curve (AUC) of the receiver operator characteristic (ROC). The resulting meta-features exhibited strong classification capability in the test dataset (AUC = 0.90), outperforming conventional, non-fused, texture analysis which previously resulted in an AUC=0.85 on the same case-control dataset. Our results suggest that informative interactions between localized motifs exist and can be extracted and summarized via a fairly simple ConvNet architecture.

Investigation of bioequivalence of a new fixed-dose combination of acarbose and metformin with the corresponding loose combination as well as the drug-drug interaction potential between both drugs in healthy adult male subjects.

PubMed

Kim, S; Jang, I-J; Shin, D; Shin, D S; Yoon, S; Lim, K S; Yu, K-S; Li, J; Zhang, H; Liu, Y; Brendel, E; Blode, H; Wang, Y

2014-08-01

Both metformin and acarbose are recommended monotherapy and add-on therapy in type 2 diabetes mellitus (T2DM). A fixed-dose combination (FDC) of acarbose and metformin has been developed to reduce pill burden and potentially improve compliance. The current study investigated the bioequivalence of the acarbose/metformin FDC compared with the individual agents administered simultaneously (loose combination). Secondary endpoints were the safety and tolerability of the FDC and the potential for drug-drug interactions between acarbose and metformin. A single-centre, randomized, open-label, four-period crossover study was conducted in healthy male Korean subjects aged 18-45 years. Following one-period balanced Williams design, participants were randomized to receive four single oral treatments on different study days separated by ≥7 days' washout. Treatments were as follows: (i) acarbose/metformin 50/500 mg FDC (test); (ii) acarbose 50 mg and metformin 500 mg as loose combination (reference); (iii) acarbose 50 mg; and (iv) metformin 500 mg. Serial blood samples were taken for glucose and insulin levels for 4 h after a sucrose load on the day before and day of study drug administration. Additionally, serial blood samples were taken for analysis of metformin levels for 24 h after each drug containing metformin. The area under the curve for 4 h post-test (AUC0-4 h ) and the maximal serum concentration (Cmax ) of plasma glucose and serum insulin were primary pharmacodynamic (PD) parameters, and Cmax , AUC0-last and AUC for metformin levels were primary pharmacokinetic (PK) parameters. The bioequivalence of the FDC to the loose combination was considered established if the 90% confidence intervals (CIs) of the baseline-adjusted PD parameter ratios (test vs. reference) for plasma glucose and the PK parameter ratios for metformin fell completely within current acceptance limits (0·8-1·25). Thirty-three of 40 randomized subjects completed the study; five withdrew consent and two discontinued because of adverse events (AEs). The 24-h plasma concentration-time curves of metformin and the 4-h plasma glucose-time curves after acarbose/metformin FDC (test) and acarbose + metformin loose combination (reference) were almost superimposable. The geometric least squares (LS) mean of the RatioAUC and RatioCmax for plasma glucose after the FDC vs. loose combination, and the LS mean of the ratios in metformin AUC, AUC0-last and Cmax were close to unity, and the 90% CI of all these parameters fell within the predefined equivalence range of 0·8-1·25, confirming bioequivalence. The metformin AUC was reduced by 26% and Cmax by 34% after acarbose + metformin compared with metformin alone. Eight subjects (20·0%) reported AEs, but all were mild, and most were gastrointestinal, as expected for these agents. The incidence of AEs was not higher with the combinations vs. monotherapy. These data demonstrate that the acarbose/metformin FDC is bioequivalent to the loose combination of these agents. Although acarbose slightly reduced the bioavailability of metformin, the accumulated evidence of the efficacy of this combination implies that this is clinically irrelevant. The observed AE profile was consistent with the established knowledge on the safety of the two drugs. © 2014 John Wiley & Sons Ltd.

Intact protein analysis of ubiquitin in cerebrospinal fluid by multiple reaction monitoring reveals differences in Alzheimer's disease and frontotemporal lobar degeneration.

PubMed

Oeckl, Patrick; Steinacker, Petra; von Arnim, Christine A F; Straub, Sarah; Nagl, Magdalena; Feneberg, Emily; Weishaupt, Jochen H; Ludolph, Albert C; Otto, Markus

2014-11-07

The impairment of the ubiquitin-proteasome system (UPS) is thought to be an early event in neurodegeneration, and monitoring UPS alterations might serve as a disease biomarker. Our aim was to establish an alternate method to antibody-based assays for the selective measurement of free monoubiquitin in cerebrospinal fluid (CSF). Free monoubiquitin was measured with liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MS/MS) in CSF of patients with Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), behavioral variant of frontotemporal dementia (bvFTD), Creutzfeldt-Jakob disease (CJD), Parkinson's disease (PD), primary progressive aphasia (PPA), and progressive supranuclear palsy (PSP). The LC-MS/MS method showed excellent intra- and interassay precision (4.4-7.4% and 4.9-10.3%) and accuracy (100-107% and 100-106%). CSF ubiquitin concentration was increased compared with that of controls (33.0 ± 9.7 ng/mL) in AD (47.5 ± 13.1 ng/mL, p < 0.05) and CJD patients (171.5 ± 103.5 ng/mL, p < 0.001) but not in other neurodegenerative diseases. Receiver operating characteristic curve (ROC) analysis of AD vs control patients revealed an area under the curve (AUC) of 0.832, and the specificity and sensitivity were 75 and 75%, respectively. ROC analysis of AD and FTLD patients yielded an AUC of 0.776, and the specificity and sensitivity were 53 and 100%, respectively. In conclusion, our LC-MS/MS method may facilitate ubiquitin determination to a broader community and might help to discriminate AD, CJD, and FTLD patients.

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis to differentiate benign peripheral neurogenic tumors from soft tissue sarcomas.

PubMed

Nakajo, Masanori; Fukukura, Yoshihiko; Hakamada, Hiroto; Yoneyama, Tomohide; Kamimura, Kiyohisa; Nagano, Satoshi; Nakajo, Masayuki; Yoshiura, Takashi

2018-02-22

Apparent diffusion coefficient (ADC) histogram analyses have been used to differentiate tumor grades and predict therapeutic responses in various anatomic sites with moderate success. To determine the ability of diffusion-weighted imaging (DWI) with a whole-tumor ADC histogram analysis to differentiate benign peripheral neurogenic tumors (BPNTs) from soft tissue sarcomas (STSs). Retrospective study, single institution. In all, 25 BPNTs and 31 STSs. Two-b value DWI (b-values = 0, 1000s/mm 2 ) was at 3.0T. The histogram parameters of whole-tumor for ADC were calculated by two radiologists and compared between BPNTs and STSs. Nonparametric tests were performed for comparisons between BPNTs and STSs. P < 0.05 was considered statistically significant. The ability of each parameter to differentiate STSs from BPNTs was evaluated using area under the curve (AUC) values derived from a receiver operating characteristic curve analysis. The mean ADC and all percentile parameters were significantly lower in STSs than in BPNTs (P < 0.001-0.009), with AUCs of 0.703-0.773. However, the coefficient of variation (P = 0.020 and AUC = 0.682) and skewness (P = 0.012 and AUC = 0.697) were significantly higher in STSs than in BPNTs. Kurtosis (P = 0.295) and entropy (P = 0.604) did not differ significantly between BPNTs and STSs. Whole-tumor ADC histogram parameters except kurtosis and entropy differed significantly between BPNTs and STSs. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Tumour xenograft detection through quantitative analysis of the metabolic profile of urine in mice

NASA Astrophysics Data System (ADS)

Moroz, Jennifer; Turner, Joan; Slupsky, Carolyn; Fallone, Gino; Syme, Alasdair

2011-02-01

The metabolic content of urine from NIH III nude mice (n = 22) was analysed before and after inoculation with human glioblastoma multiforme (GBM) cancer cells. An age- and gender-matched control population (n = 14) was also studied to identify non-tumour-related changes. Urine samples were collected daily for 6 weeks, beginning 1 week before cell injection. Metabolite concentrations were obtained via targeted profiling with Chenomx Suite 5.1, based on nuclear magnetic resonance (NMR) spectra acquired on an Oxford 800 MHz cold probe NMR spectrometer. The Wilcoxon rank sum test was used to evaluate the significance of the change in metabolite concentration between the two time points. Both the metabolite concentrations and the ratios of pairs of metabolites were studied. The complicated inter-relationships between metabolites were assessed through partial least-squares discriminant analysis (PLS-DA). Receiver operating characteristic (ROC) curves were generated for all variables and the area under the curve (AUC) calculated. The data indicate that the number of statistically significant changes in metabolite concentrations was more pronounced in the tumour-bearing population than in the control animals. This was also true of the ratios of pairs of metabolites. ROC analysis suggests that the ratios were better able to differentiate between the pre- and post-injection samples compared to the metabolite concentrations. PLS-DA models produced good separation between the populations and had the best AUC results (all models exceeded 0.937). These results demonstrate that metabolomics may be used as a screening tool for GBM cells grown in xenograft models in mice.

Braden scale (ALB) for assessing pressure ulcer risk in hospital patients: A validity and reliability study.

PubMed

Chen, Hong-Lin; Cao, Ying-Juan; Zhang, Wei; Wang, Jing; Huai, Bao-Sha

2017-02-01

The inter-rater reliability of Braden Scale is not so good. We modified the Braden(ALB) scale by defining nutrition subscale based on serum albumin, then assessed it's the validity and reliability in hospital patients. We designed a retrospective study for validity analysis, and a prospective study for reliability analysis. Receiver operating curve (ROC) and area under the curve (AUC) were used to evaluate the predictive validity. Intra-class correlation coefficient (ICC) was used to investigate the inter-rater reliability. Two thousand five hundred twenty-five patients were included for validity analysis, 76 patients (3.0%) developed pressure ulcer. Positive correlation was found between serum albumin and nutrition score in Braden scale (Spearman's coefficient 0.2203, P<0.0001). The AUCs for Braden scale and Braden(ALB) scale predicting pressure ulcer risk were 0.813 (95% CI 0.797-0.828; P<0.0001), and 0.859 (95% CI 0.845-0.872; P<0.0001), respectively. The Braden(ALB) scale was even more valid than the Braden scale (z=1.860, P=0.0628). In different age subgroups, the Braden(ALB) scale seems also more valid than the original Braden scale, but no statistically significant differences were found (P>0.05). The inter-rater reliability study showed the ICC-value for nutrition increased 45.9%, and increased 4.3% for total score. The Braden(ALB) scale has similar validity compared with the original Braden scale for in hospital patients. However, the inter-rater reliability was significantly increased. Copyright © 2016 Elsevier Inc. All rights reserved.

Value of circulating cell-free DNA analysis as a diagnostic tool for breast cancer: a meta-analysis

PubMed Central

Ma, Xuelei; Zhang, Jing; Hu, Xiuying

2017-01-01

Objectives The aim of this study was to systematically evaluate the diagnostic value of cell free DNA (cfDNA) for breast cancer. Results Among 308 candidate articles, 25 with relevant diagnostic screening qualified for final analysis. The mean sensitivity, specificity and area under the curve (AUC) of SROC plots for 24 studies that distinguished breast cancer patients from healthy controls were 0.70, 0.87, and 0.9314, yielding a DOR of 32.31. When analyzed in subgroups, the 14 quantitative studies produced sensitivity, specificity, AUC, and a DOR of 0.78, 0.83, 0.9116, and 24.40. The 10 qualitative studies produced 0.50, 0.98, 0.9919, and 68.45. For 8 studies that distinguished malignant breast cancer from benign diseases, the specificity, sensitivity, AUC and DOR were 0.75, 0.79, 0.8213, and 9.49. No covariate factors had a significant correlation with relative DOR. Deek's funnel plots indicated an absence of publication bias. Materials and Methods Databases were searched for studies involving the use of cfDNA to diagnose breast cancer. The studies were analyzed to determine sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC). Covariates were evaluated for effect on relative DOR. Deek's Funnel plots were generated to measure publication bias. Conclusions Our analysis suggests a promising diagnostic potential of using cfDNA for breast cancer screening, but this diagnostic method is not yet independently sufficient. Further work refining qualitative cfDNA assays will improve the correct diagnosis of breast cancers. PMID:28460452

Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

2017-02-01

We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

Novel application of multi dynamic trend analysis as a sensitive tool for detecting the effects of aging and congestive heart failure on heart rate variability

NASA Astrophysics Data System (ADS)

Lin, Yu-Cheng; Lin, Yu-Hsuan; Lo, Men-Tzung; Peng, Chung-Kang; Huang, Norden E.; Yang, Cheryl C. H.; Kuo, Terry B. J.

2016-02-01

The complex fluctuations in heart rate variability (HRV) reflect cardiac autonomic modulation and are an indicator of congestive heart failure (CHF). This paper proposes a novel nonlinear approach to HRV investigation, the multi dynamic trend analysis (MDTA) method, based on the empirical mode decomposition algorithm of the Hilbert-Huang transform combined with a variable-sized sliding-window method. Electrocardiographic signal data obtained from the PhysioNet database were used. These data were from subjects with CHF (mean age = 59.4 ± 8.4), an age-matched elderly healthy control group (59.3 ± 10.6), and a healthy young group (30.3 ± 4.8); the HRVs of these subjects were processed using the MDTA method, time domain analysis, and frequency domain analysis. Among all HRV parameters, the MDTA absolute value slope (MDTS) and MDTA deviation (MDTD) exhibited the greatest area under the curve (AUC) of the receiver operating characteristics in distinguishing between the CHF group and the healthy controls (AUC = 1.000) and between the healthy elderly subject group and the young subject group (AUC = 0.834 ± 0.067 for MDTS; 0.837 ± 0.066 for MDTD). The CHF subjects presented with lower MDTA indices than those of the healthy elderly subject group. Furthermore, the healthy elderly subjects exhibited lower MDTA indices than those of the young controls. The MDTA method can adaptively and automatically identify the intrinsic fluctuation on variable temporal and spatial scales when investigating complex fluctuations in the cardiac autonomic regulation effects of aging and CHF.

Objective Dysphonia Quantification in Vocal Fold Paralysis: Comparing Nonlinear with Classical Measures

PubMed Central

Little, Max A.; Costello, Declan A. E.; Harries, Meredydd L.

2010-01-01

Summary Clinical acoustic voice-recording analysis is usually performed using classical perturbation measures, including jitter, shimmer, and noise-to-harmonic ratios (NHRs). However, restrictive mathematical limitations of these measures prevent analysis for severely dysphonic voices. Previous studies of alternative nonlinear random measures addressed wide varieties of vocal pathologies. Here, we analyze a single vocal pathology cohort, testing the performance of these alternative measures alongside classical measures. We present voice analysis pre- and postoperatively in 17 patients with unilateral vocal fold paralysis (UVFP). The patients underwent standard medialization thyroplasty surgery, and the voices were analyzed using jitter, shimmer, NHR, nonlinear recurrence period density entropy (RPDE), detrended fluctuation analysis (DFA), and correlation dimension. In addition, we similarly analyzed 11 healthy controls. Systematizing the preanalysis editing of the recordings, we found that the novel measures were more stable and, hence, reliable than the classical measures on healthy controls. RPDE and jitter are sensitive to improvements pre- to postoperation. Shimmer, NHR, and DFA showed no significant change (P > 0.05). All measures detect statistically significant and clinically important differences between controls and patients, both treated and untreated (P < 0.001, area under curve [AUC] > 0.7). Pre- to postoperation grade, roughness, breathiness, asthenia, and strain (GRBAS) ratings show statistically significant and clinically important improvement in overall dysphonia grade (G) (AUC = 0.946, P < 0.001). Recalculating AUCs from other study data, we compare these results in terms of clinical importance. We conclude that, when preanalysis editing is systematized, nonlinear random measures may be useful for monitoring UVFP-treatment effectiveness, and there may be applications to other forms of dysphonia. PMID:19900790

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling

PubMed Central

Wang, Sheng; Sun, Siqi

2017-01-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC. PMID:28884168

Development and validation of a nomogram to estimate the pretest probability of cancer in Chinese patients with solid solitary pulmonary nodules: A multi-institutional study.

PubMed

She, Yunlang; Zhao, Lilan; Dai, Chenyang; Ren, Yijiu; Jiang, Gening; Xie, Huikang; Zhu, Huiyuan; Sun, Xiwen; Yang, Ping; Chen, Yongbing; Shi, Shunbin; Shi, Weirong; Yu, Bing; Xie, Dong; Chen, Chang

2017-11-01

To develop and validate a nomogram to estimate the pretest probability of malignancy in Chinese patients with solid solitary pulmonary nodule (SPN). A primary cohort of 1798 patients with pathologically confirmed solid SPNs after surgery was retrospectively studied at five institutions from January 2014 to December 2015. A nomogram based on independent prediction factors of malignant solid SPN was developed. Predictive performance also was evaluated using the calibration curve and the area under the receiver operating characteristic curve (AUC). The mean age of the cohort was 58.9 ± 10.7 years. In univariate and multivariate analysis, age; history of cancer; the log base 10 transformations of serum carcinoembryonic antigen value; nodule diameter; the presence of spiculation, pleural indentation, and calcification remained the predictive factors of malignancy. A nomogram was developed, and the AUC value (0.85; 95%CI, 0.83-0.88) was significantly higher than other three models. The calibration cure showed optimal agreement between the malignant probability as predicted by nomogram and the actual probability. We developed and validated a nomogram that can estimate the pretest probability of malignant solid SPNs, which can assist clinical physicians to select and interpret the results of subsequent diagnostic tests. © 2017 Wiley Periodicals, Inc.

Diagnostic Tools for Acute Anterior Cruciate Ligament Injury: GNRB, Lachman Test, and Telos.

PubMed

Ryu, Seung Min; Na, Ho Dong; Shon, Oog Jin

2018-06-01

The purpose of this study is to compare the accuracy of the GNRB arthrometer (Genourob), Lachman test, and Telos device (GmbH) in acute anterior cruciate ligament (ACL) injuries and to evaluate the accuracy of each diagnostic tool according to the length of time from injury to examination. From September 2015 to September 2016, 40 cases of complete ACL rupture were reviewed. We divided the time from injury to examination into three periods of 10 days each and analyzed the diagnostic tools according to the time frame. An analysis of the area under the curve (AUC) of a receiver operating characteristic curve showed that all diagnostic tools were fairly informative. The GNRB showed a higher AUC than other diagnostic tools. In 10 cases assessed within 10 days after injury, the GNRB showed statistically significant side-to-side difference in laxity (p＜0.001), whereas the Telos test and Lachman test did not show significantly different laxity (p=0.541 and p=0.413, respectively). All diagnostic values of the GNRB were better than other diagnostic tools in acute ACL injuries. The GNRB was more effective in acute ACL injuries examined within 10 days of injury. The GNRB arthrometer can be a useful diagnostic tool for acute ACL injuries.

Metabolomic profile of systemic sclerosis patients.

PubMed

Murgia, Federica; Svegliati, Silvia; Poddighe, Simone; Lussu, Milena; Manzin, Aldo; Spadoni, Tatiana; Fischetti, Colomba; Gabrielli, Armando; Atzori, Luigi

2018-05-16

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by 1 H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726-0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7-0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.

The influence of secondary reconstruction slice thickness on NewTom 3G cone beam computed tomography-based radiological interpretation of sheep mandibular condyle fractures.

PubMed

Sirin, Yigit; Guven, Koray; Horasan, Sinan; Sencan, Sabri; Bakir, Baris; Barut, Oya; Tanyel, Cem; Aral, Ali; Firat, Deniz

2010-11-01

The objective of this study was to examine the diagnostic accuracy of the different secondary reconstruction slice thicknesses of cone beam computed tomography (CBCT) on artificially created mandibular condyle fractures. A total of 63 sheep heads with or without condylar fractures were scanned with a NewTom 3G CBCT scanner. Multiplanar reformatted (MPR) views in 0.2-mm, 1-mm, 2-mm, and 3-mm secondary reconstruction slice thicknesses were evaluated by 7 observers. Inter- and intraobserver agreements were calculated with weighted kappa statistics. The receiver operating characteristic (ROC) curve analysis was used to statistically compare the area under the curve (AUC) of each slice thickness. The kappa coefficients varied from fair and to excellent. The AUCs of 0.2-mm and 1-mm slice thicknesses were found to be significantly higher than those of 2 mm and 3 mm for some type of fractures. CBCT was found to be accurate in detecting all variants of fractures at 0.2 mm and 1 mm. However, 2-mm and 3-mm slices were not suitable to detect fissure, complete, and comminuted types of mandibular condyle fractures. Copyright © 2010 Mosby, Inc. All rights reserved.

Interaction of Citrus Juices with Cyclosporine: Systematic Review and Meta-Analysis.

PubMed

Sridharan, Kannan; Sivaramakrishnan, Gowri

2016-12-01

Cyclosporine is an immunosuppressant with narrow therapeutic window, metabolized mainly by cytochrome P450 3A4 (CYP3A4) and minimally by cytochrome P450 3A5 (CYP3A5). Citrus juices such as grapefruit juice (GFJ), orange, lemon, pomelo and lime were known to interact with cyclosporine in several randomized controlled trials. The present review is a systematic compilation and quantitative synthesis on the changes of cyclosporine pharmacokinetics with concomitant citrus juice administration. Electronic databases were searched for randomized controlled trials evaluating the effect of any citrus juice on the pharmacokinetics of cyclosporine comparing with water or placebo in healthy volunteers using appropriate search strategies. Percent mean difference with standard error was used to assess the magnitude of difference in the following outcome measures: area under curve from time of drug administration to 24 h (AUC 0-24 ), area under curve from time of drug administration to infinity (AUC 0-∞ ), maximum concentration (C max ), time to achieve C max (T max ), elimination half-life (T 1/2 ), clearance (CL), volume of distribution and frequency for adverse drug reactions following administration of cyclosporine. RevMan 5.3 software was used to assess heterogeneity (by I 2 statistics), use random-effects model and generate pooled results and Forest plot. A total of 57 studies were obtained with the search strategy, of which seven were found eligible to be included in the present review. The pooled percent mean difference [95 % CI] for GFJ in comparison to controls for AUC 0-24 , AUC 0-∞ , C max and T max of cyclosporine was observed to be 53 [43, 64], 53 [45, 62], 24 [12, 36] and 19 [12, 26], respectively. Similarly, pomelo juice was found to significantly increase both AUC 0-∞ and C max with the pooled percent mean difference [95 % CI] as 23 [13, 32] and 25 [1, 50], respectively but decrease T 1/2 {-8 [-15, -1]} of cyclosporine. Orange juice did not alter any of the pharmacokinetic parameter of cyclosporine significantly. Citrus juices especially GFJ and pomelo juice were found to significantly increase the plasma exposure of cyclosporine while orange juice did not exhibit any significant interaction with cyclosporine.

CA-125 AUC as a predictor for epithelial ovarian cancer relapse.

PubMed

Mano, António; Falcão, Amílcar; Godinho, Isabel; Santos, Jorge; Leitão, Fátima; de Oliveira, Carlos; Caramona, Margarida

2008-01-01

The aim of the present work was to evaluate the usefulness of CA-125 normalized in time area under the curve (CA-125 AUC) to signalise epithelial ovarian cancer relapse. Data from a hundred and eleven patients were submitted to two different approaches based on CA-125 AUC increase values to predict patient relapse. In Criterion A total CA-125 AUC normalized in time value (AUC(i)) was compared with the immediately previous one (AUC(i-1)) using the formulae AUC(i) > or = F * AUC(i-1) (several F values were tested) to find the appropriate close related increment associated to patient relapse. In Criterion B total CA-125 AUC normalised in time was calculated and several cut-off values were correlated with patient relapse prediction capacity. In Criterion A the best accuracy was achieved with a factor (F) of 1.25 (increment of 25% from the previous status), while in Criterion B the best accuracies were achieved with cut-offs of 25, 50, 75 and 100 IU/mL. The mean lead time to relapse achieved with Criterion A was 181 days, while with Criterion B they were, respectively, 131, 111, 63 and 11 days. Based on our results we believe that conjugation and sequential application of both criteria in patient relapse detection should be highly advisable. CA-125 AUC rapid burst in asymptomatic patients should be firstly evaluated using Criterion A with a high accuracy (0.85) and with a substantial mean lead time to relapse (181 days). If a negative answer was obtained then Criterion B should performed to confirm the absence of relapse.

A new mathematical approach for the estimation of the AUC and its variability under different experimental designs in preclinical studies.

PubMed

Navarro-Fontestad, Carmen; González-Álvarez, Isabel; Fernández-Teruel, Carlos; Bermejo, Marival; Casabó, Vicente Germán

2012-01-01

The aim of the present work was to develop a new mathematical method for estimating the area under the curve (AUC) and its variability that could be applied in different preclinical experimental designs and amenable to be implemented in standard calculation worksheets. In order to assess the usefulness of the new approach, different experimental scenarios were studied and the results were compared with those obtained with commonly used software: WinNonlin® and Phoenix WinNonlin®. The results do not show statistical differences among the AUC values obtained by both procedures, but the new method appears to be a better estimator of the AUC standard error, measured as the coverage of 95% confidence interval. In this way, the new proposed method demonstrates to be as useful as WinNonlin® software when it was applicable. Copyright © 2011 John Wiley & Sons, Ltd.

Proposing the Use of Partial AUC as an Adjunctive Measure in Establishing Bioequivalence Between Deltoid and Gluteal Administration of Long-Acting Injectable Antipsychotics.

PubMed

Lee, Lik Hang N; Choi, Charles; Gershkovich, Pavel; Barr, Alasdair M; Honer, William G; Procyshyn, Ric M

2016-12-01

The maximum plasma concentration (C max ) and the area under the plasma concentration-time curve (AUC) are commonly used to establish bioequivalence between two formulations of the same oral medication. Similarly, these pharmacokinetic parameters have also been used to establish bioequivalence between two sites of administration for the same injectable formulation. However, these conventional methods of establishing bioequivalence are of limited use when comparing modified-release formulations of a drug, particularly those with rates of absorption that are amenable to change with the site of injection. Inherent differences in the rate of absorption can result in clinically significant differences in early exposure and drug response. Here, we propose the use of the partial AUC (pAUC) as a measure of early exposure to aid in the assessment of bioequivalence between the gluteal and the deltoid site of administration for long-acting injectable antipsychotics.

Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

PubMed

Sun, Wenqing; Zheng, Bin; Qian, Wei

2017-10-01

This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists' markings, and 13,668 samples were generated by rotating every slice of nodule images. Three multichannel ROI based deep structured algorithms were designed and implemented in this study: convolutional neural network (CNN), deep belief network (DBN), and stacked denoising autoencoder (SDAE). For the comparison purpose, we also implemented a CADx system using hand-crafted features including density features, texture features and morphological features. The performance of every scheme was evaluated by using a 10-fold cross-validation method and an assessment index of the area under the receiver operating characteristic curve (AUC). The observed highest area under the curve (AUC) was 0.899±0.018 achieved by CNN, which was significantly higher than traditional CADx with the AUC=0.848±0.026. The results from DBN was also slightly higher than CADx, while SDAE was slightly lower. By visualizing the automatic generated features, we found some meaningful detectors like curvy stroke detectors from deep structured schemes. The study results showed the deep structured algorithms with automatically generated features can achieve desirable performance in lung nodule diagnosis. With well-tuned parameters and large enough dataset, the deep learning algorithms can have better performance than current popular CADx. We believe the deep learning algorithms with similar data preprocessing procedure can be used in other medical image analysis areas as well. Copyright © 2017. Published by Elsevier Ltd.

Evaluation of waist-to-height ratio as a predictor of insulin resistance in non-diabetic obese individuals. A cross-sectional study.

PubMed

Jamar, Giovana; Almeida, Flávio Rossi de; Gagliardi, Antonio; Sobral, Marianna Ribeiro; Ping, Chao Tsai; Sperandio, Evandro; Romiti, Marcelo; Arantes, Rodolfo; Dourado, Victor Zuniga

2017-01-01

Insulin resistance (IR) and progressive pancreatic β-cell dysfunction have been identified as the two fundamental features in the pathogenesis of obesity and non-insulin-dependent diabetes mellitus. We aimed to investigate correlations between anthropometric indices of obesity and IR in non-diabetic obese individuals, and the cutoff value from receiver operating characteristic (ROC) curve analysis. Cross-sectional study conducted in a private clinic. We included obese individuals (body mass index, BMI ≥ 30 kg/m2) with no diabetes mellitus (fasting glucose levels ≤ 126 mg/dl). The participants were evaluated for the presence of cardiovascular risk factors and through anthropometric measurements and biochemical tests. Furthermore, IR was assessed indirectly using the homeostatic model assessment (HOMA)-IR and HOMA-β indexes. The area underthe curve (AUC) of the variables was compared.The sensitivity, specificity and cutoff of each variable for diagnosing IR were calculated. The most promising anthropometric parameters for indicating IR in non-diabetic obese individuals were waist-to-height ratio (WHtR), waist circumference (WC) and BMI. WHtR proved to be an independent predictor of IR, with risk increased by 0.53% in HOMA-IR, 5.3% in HOMA-β and 1.14% in insulin. For HOMA-IR, WHtR had the highest AUC value (0.98), followed by WC (0.93) and BMI (0.81). For HOMA-β, WHtR also had the highest AUC value (0.83), followed by WC (0.75) and BMI (0.73).The optimal WHtR cutoff was 0.65 for HOMA-IR and 0.67 for HOMA-β. Among anthropometric obesity indicators, WHtR was most closely associated with occurrences of IR and predicted the onset of diabetes in obese individuals.

Gaze Stabilization Test Asymmetry Score as an Indicator of Previous Concussion in a Cohort of Collegiate Football Players.

PubMed

Honaker, Julie A; Criter, Robin E; Patterson, Jessie N; Jones, Sherri M

2015-07-01

Vestibular dysfunction may lead to decreased visual acuity with head movements, which may impede athletic performance and result in injury. The purpose of this study was to test the hypothesis that athletes with history of concussion would have differences in gaze stabilization test (GST) as compared with those without a history of concussion. Cross-sectional, descriptive. University Athletic Medicine Facility. Fifteen collegiate football players with a history of concussion, 25 collegiate football players without a history of concussion. Participants completed the dizziness handicap inventory (DHI), static visual acuity, perception time test, active yaw plane GST, stability evaluation test (SET), and a bedside oculomotor examination. Independent samples t test was used to compare GST, SET, and DHI scores per group, with Bonferroni-adjusted alpha at P < 0.01. Receiver operating characteristic curve analysis and area under the curve (AUC) were used to assess the clinical performance of the GST and SET. Athletes with previous concussion had a larger GST asymmetry score [mean (M) = 12.40, SD = 9.09] than those without concussion (M = 4.92, SD = 4.67; t (18.70) = -2.955, P = 0.008, 95% CI, -12.79 to -2.18, d = -1.37). Clinical performance of the GST (AUC = 0.77) was better than the SET (AUC = 0.61). Results suggest peripheral vestibular or vestibular-visual interaction deficits in collegiate athletes with a history of concussion. The results support further research on the use of GST for sport-related concussion evaluation and monitoring. Inclusion of objective vestibular tests in the concussion protocol may reveal the presence of peripheral vestibular or visual-vestibular deficits. Therefore, the GST may add an important perspective on the effects of concussion.

Subcategorization of Suspicious Breast Lesions (BI-RADS Category 4) According to MRI Criteria: Role of Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging.

PubMed

Maltez de Almeida, João Ricardo; Gomes, André Boechat; Barros, Thomas Pitangueira; Fahel, Paulo Eduardo; de Seixas Rocha, Mário

2015-07-01

The purposes of this study were to investigate whether dynamic contrast-enhanced MRI is adequate for subcategorization of suspicious lesions (BI-RADS category 4) and to evaluate whether use of DWI improves diagnostic performance. The study group was composed of 103 suspicious lesions found in 83 subjects. Patient ages and lesion sizes were compiled, and two radiologists reanalyzed the images; subcategorized the findings as BI-RADS 4A, 4B, or 4C; and calculated apparent diffusion coefficient (ADC) values. The stratified variables were tested by univariate analysis and inserted in two multivariate predictive models, which were used to generate ROC curves and compare AUCs. Positive predictive values (PPVs) for each subcategory and ADC level were calculated, and interobserver agreement was tested. Forty-four (42.7%) suspicious findings proved malignant. Except for age (p = 0.08), all stratified predictor variables were significant in univariate analyses (p < 0.01). Logistic regression models did not differ substantially after comparison of the ROC curves (p = 0.09), but the one including ADC values was slightly better: AUC of 0.89 (95% CI, 0.82-0.95) against AUC of 0.85 (95% CI, 0.78-0.93). PPV increased progressively in each BI-RADS 4 subcategory (4A, 0.15; 4B, 0.37; 4C, 0.84). ADC values of 1.10 × 10(-3) mm(2)/s or less had the second highest PPV (0.77). Interobserver agreement was substantial at a kappa value of 0.80 (95% CI, 0.70-0.90; p < 0.01). Risk stratification of suspicious lesions (BI-RADS category 4) can be satisfactorily performed with DCE-MRI and slightly improved when DWI is introduced.

Analytical and clinical performance of thyroglobulin autoantibody assays in thyroid cancer follow-up.

PubMed

Katrangi, Waddah; Grebe, Stephan K G; Algeciras-Schimnich, Alicia

2017-10-26

While thyroglobulin autoantibodies (TgAb) can result in false low serum thyroglobulin (Tg) immunoassay (IA) measurements, they might also be indicators of disease persistence/recurrence. Hence, accurate TgAb measurement, in addition to Tg quantification, is crucial for thyroid cancer monitoring. We compared the analytical and clinical performance of four commonly used TgAb IAs. We measured Tg by mass spectrometry (Tg-MS) and by four pairs of Tg and TgAb IAs (Beckman, Roche, Siemens, Thermo) in 576 samples. Limit of quantitation (LOQ) and manufacturers' upper reference interval cut-off (URI) were used for comparisons. Clinical performance was assessed by receiving operator characteristics (ROC) curve analysis. Quantitative and qualitative agreement between TgAb-IAs was moderate with R2 of 0.20-0.70 and κ from 0.41-0.66 using LOQ and 0.47-0.71 using URI. In samples with TgAb interference, detection rates of TgAb were similar using LOQ and URI for Beckman, Siemens, and Thermo, but much lower for the Roche TgAb-IA when the URI was used. In TgAb positive cases, the ROC areas under the curve (AUC) for the TgAb-IAs were 0.59 (Beckman), 0.62 (Siemens), 0.59 (Roche), and 0.59 (Thermo), similar to ROC AUCs achieved with Tg. Combining Tg and TgAb measurements improved the ROC AUCs compared to Tg or TgAb alone. TgAb-IAs show significant qualitative and quantitative differences. For 2 of the 4 TgAb-IAs, using the LOQ improves the detection of interfering TgAbs. All assays showed suboptimal clinical performance when used as surrogate markers of disease, with modest improvements when Tg and TgAb were combined.

Fluorine-18-fluorodeoxyglucose positron emission tomography as an objective substitute for CT morphologic response criteria in patients undergoing chemotherapy for colorectal liver metastases.

PubMed

Nishioka, Yujiro; Yoshioka, Ryuji; Gonoi, Wataru; Sugawara, Toshitaka; Yoshida, Shuntaro; Hashimoto, Masaji; Shindoh, Junichi

2018-05-01

The computed tomography (CT) morphologic response of colorectal liver metastases (CLM) after chemotherapy is reportedly correlated with pathologic response and survival outcomes of patients undergoing surgery. However, they are rather subjective criteria and not evaluable without adequate quality of contrast-enhanced CT images. This study sought the potential use of fluorine-18-fluorodeoxyglucose (FDG) positron emission tomography (PET) as an objective substitute for predicting pathological viability of CLM after chemotherapy. Predictive ability of tumor viability of ≤10% was compared between FDG-PET/CT and contrast-enhanced CT in 34 patients who underwent curative surgical resection for CLM after chemotherapy. The CT morphology and response were defined according to the reported criteria (Chun YS, JAMA 2009). The mean standard uptake value (SUV-mean) in CLM was significantly lower in patients with group 1 and group 2 CT morphology (median, 2.53 and 3.00, respectively) than in group 3 (median, 3.32). The tumor SUV-mean showed moderate correlation with the tumor pathologic viability (r = 0.660, P < 0.0001). A receiver operating characteristic curve analysis revealed that both the tumor SUV-mean (area under the curve [AUC], 0.916; the cut-off value, 3.00) and the CT morphology (AUC, 0.882) have excellent predictive power for ≤10% of tumor viability, while degree of tumor shrinkage showed lower predictive power (AUC, 0.692). FDG-PET shows significant correlation with pathologic viability of CLM after chemotherapy and may offer additional objective information for estimating tumor viability when the CT morphologic response is not evaluable.

Additional value of anaerobic threshold in a general mortality prediction model in a urban patient cohort with Chagas cardiomyopathy.

PubMed

Silva, Roberto Ribeiro da; Reis, Michel Silva; Pereira, Basílio de Bragança; Nascimento, Emilia Matos do; Pedrosa, Roberto Coury

2017-12-01

Anaerobic threshold (AT) is recognized as objective and direct measurement that reflects variations in metabolism of skeletal muscles during exercise. Its prognostic value in heart diseases of non-chagasic etiology is well established. However, the assessment of risk of death in Chagas heart disease is relatively well established by Rassi score. But, the added value that AT can bring to Rassi score has not been studied yet. To assess whether AT presents additional effect to Rassi score in patients with chronic Chagas' heart disease. Prospective research of dynamic cohort by review of 150 medical records of patients. Were selected for cohort 45 medical records of patients who underwent cardiopulmonary exercise testing between 1996-1997 and followed until September 2015. Data analysis to detect association between studied variables can be seen using a logistic regression model. The suitability of the models was verified using ROC curves and the coefficient of determination R 2 . 8 patients (17.78%) died by September 2015, with 7 of them (87.5%) from cardiovascular causes, of which 4 (57.14%) were considered on high risk by Rassi score. With Rassi score as independent variable, and death being the outcome, we obtained an area under the curve (AUC)=0.711, with R 2 =0.214. Instituting AT as independent variable, we found AUC=0.706, with R 2 =0.078. When we define Rassi score and AT as independent variables, it was obtained AUC=0.800 and R 2 =0.263. when AT is included in logistic regression, it increases by 5% the explanation (R 2 ) to the death estimation. Copyright © 2017 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.

Screening older cancer patients for a Comprehensive Geriatric Assessment: A comparison of three instruments

PubMed Central

Owusu, Cynthia; Koroukian, Siran M.; Schluchter, Mark; Bakaki, Paul; Berger, Nathan A.

2011-01-01

Background The Vulnerable Elders Survey (VES-13) has been validated for screening older cancer patients for a Comprehensive Geriatric Assessment (CGA). To identify a widely acceptable approach that encourages oncologists to screen older cancer patients for a CGA, we examined the Eastern Cooperative Oncology Group Performance Status (ECOG-PS) and Karnofsky Index of Performance Status (KPS) scales’ ability to identify abnormalities on a CGA and compared the performance of the two instruments with the VES-13. Methods We enrolled 117 participants, ≥65 years with stage I–IV cancer into this cross-sectional study. Our primary outcome variable was ≥two abnormalities on the CGA, (Yes or No). We employed receiver operating characteristic curve analysis to compare the discriminatory abilities of the three instruments to identify ≥two abnormalities on the CGA. Results Of the 117 participants, 43% had ≥two abnormalities on the CGA. The VES-13 was predictive of ≥two abnormalities on the CGA, area under the curve (AUC)=0.85 [(95% CI: 0.78–0.92); sensitivity=88%, specificity=69%, at cut-off ≥3]. The ECOG-PS and KPS showed similar discriminatory powers, AUC=0.88 [(95% CI: 0.83–0.94); sensitivity=94%, specificity=55%, at cut-off ≥1]; and AUC=0.90 [(95% CI: 0.84–0.96); sensitivity=78%, specificity=91%, at cut-off ≤80%], respectively. Conclusion The ECOG-PS and KPS were equivalent to the VES-13 in identifying older cancer patients with at least two abnormalities on the CGA. Given that oncologists are already conversant with the KPS and ECOG-PS, these two instruments offer medical oncologists a widely acceptable approach for screening older patients for a CGA. PMID:21927633

Using Machine-Learned Bayesian Belief Networks to Predict Perioperative Risk of Clostridium Difficile Infection Following Colon Surgery

PubMed Central

Bilchik, Anton; Eberhardt, John; Kalina, Philip; Nissan, Aviram; Johnson, Eric; Avital, Itzhak; Stojadinovic, Alexander

2012-01-01

Background Clostridium difficile (C-Diff) infection following colorectal resection is an increasing source of morbidity and mortality. Objective We sought to determine if machine-learned Bayesian belief networks (ml-BBNs) could preoperatively provide clinicians with postoperative estimates of C-Diff risk. Methods We performed a retrospective modeling of the Nationwide Inpatient Sample (NIS) national registry dataset with independent set validation. The NIS registries for 2005 and 2006 were used for initial model training, and the data from 2007 were used for testing and validation. International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes were used to identify subjects undergoing colon resection and postoperative C-Diff development. The ml-BBNs were trained using a stepwise process. Receiver operating characteristic (ROC) curve analysis was conducted and area under the curve (AUC), positive predictive value (PPV), and negative predictive value (NPV) were calculated. Results From over 24 million admissions, 170,363 undergoing colon resection met the inclusion criteria. Overall, 1.7% developed postoperative C-Diff. Using the ml-BBN to estimate C-Diff risk, model AUC is 0.75. Using only known a priori features, AUC is 0.74. The model has two configurations: a high sensitivity and a high specificity configuration. Sensitivity, specificity, PPV, and NPV are 81.0%, 50.1%, 2.6%, and 99.4% for high sensitivity and 55.4%, 81.3%, 3.5%, and 99.1% for high specificity. C-Diff has 4 first-degree associates that influence the probability of C-Diff development: weight loss, tumor metastases, inflammation/infections, and disease severity. Conclusions Machine-learned BBNs can produce robust estimates of postoperative C-Diff infection, allowing clinicians to identify high-risk patients and potentially implement measures to reduce its incidence or morbidity. PMID:23611947

Comparison of neutrophil-to-lymphocyte ratio and mean platelet volume in the prediction of adverse events after primary percutaneous coronary intervention in patients with ST-elevation myocardial infarction.

PubMed

Machado, Guilherme Pinheiro; Araujo, Gustavo Neves de; Carpes, Christian Kunde; Lech, Mateus; Mariani, Stefani; Valle, Felipe Homem; Bergoli, Luiz Carlos Corsetti; Gonçalves, Sandro Cadaval; Wainstein, Rodrigo V; Wainstein, Marco V

2018-07-01

Elevated neutrophil-to-lymphocyte ratio (NLR) and mean platelet volume (MPV) are indirect inflammatory markers. There is some evidence that both are associated with worse outcomes in ST-segment elevation myocardial infarction (STEMI) after primary percutaneous coronary intervention (PCI). The aim of the present study was to compare the capacity of NLR and MPV to predict adverse events after primary PCI. In a prospective cohort study, 625 consecutive patients with STEMI, who underwent primary PCI, were followed. Receiver operating characteristic (ROC) curve analysis was performed to calculate the area under the curve (AUC) for the occurrence of procedural complications, mortality and major adverse cardiovascular events (MACE). Mean age was 60.7 (±12.1) years, 67.5% were male. The median of NLR was 6.17 (3.8-9.4) and MPV was 10.7 (10.0-11.3). In multivariate analysis, both NLR and MPV remained independent predictors of no-reflow (relative risk [RR] = 2.26; 95%confidence interval [95%CI] = 1.16-4.32; p = 0.01 and RR = 2.68; 95%CI = 1.40-5.10; p < 0.01, respectively), but only NLR remained an independent predictor of in-hospital MACE (RR = 1.01; 95%CI = 1.00-1.06; p = 0.02). The AUC for in-hospital MACE was 0.57 for NLR (95%CI = 0.53-0.60; p = 0.03) and 0.56 for MPV (95%CI = 0.52-0.60; p = 0.07). However, when AUC were compared with DeLong test, there was no statistically significant difference for these outcomes (p > 0.05). NLR had an excellent negative predictive value (NPV) of 96.7 for no-reflow and 89.0 for in-hospital MACE. Despite no difference in the ROC curve comparison with MPV, only NLR remained an independent predictor for in-hospital MACE. A low NLR has an excellent NPV for no-reflow and in-hospital MACE, and this could be of clinical relevance in the management of low-risk patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction models for the risk of spontaneous preterm birth based on maternal characteristics: a systematic review and independent external validation.

PubMed

Meertens, Linda J E; van Montfort, Pim; Scheepers, Hubertina C J; van Kuijk, Sander M J; Aardenburg, Robert; Langenveld, Josje; van Dooren, Ivo M A; Zwaan, Iris M; Spaanderman, Marc E A; Smits, Luc J M

2018-04-17

Prediction models may contribute to personalized risk-based management of women at high risk of spontaneous preterm delivery. Although prediction models are published frequently, often with promising results, external validation generally is lacking. We performed a systematic review of prediction models for the risk of spontaneous preterm birth based on routine clinical parameters. Additionally, we externally validated and evaluated the clinical potential of the models. Prediction models based on routinely collected maternal parameters obtainable during first 16 weeks of gestation were eligible for selection. Risk of bias was assessed according to the CHARMS guidelines. We validated the selected models in a Dutch multicenter prospective cohort study comprising 2614 unselected pregnant women. Information on predictors was obtained by a web-based questionnaire. Predictive performance of the models was quantified by the area under the receiver operating characteristic curve (AUC) and calibration plots for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation. Clinical value was evaluated by means of decision curve analysis and calculating classification accuracy for different risk thresholds. Four studies describing five prediction models fulfilled the eligibility criteria. Risk of bias assessment revealed a moderate to high risk of bias in three studies. The AUC of the models ranged from 0.54 to 0.67 and from 0.56 to 0.70 for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation, respectively. A subanalysis showed that the models discriminated poorly (AUC 0.51-0.56) for nulliparous women. Although we recalibrated the models, two models retained evidence of overfitting. The decision curve analysis showed low clinical benefit for the best performing models. This review revealed several reporting and methodological shortcomings of published prediction models for spontaneous preterm birth. Our external validation study indicated that none of the models had the ability to predict spontaneous preterm birth adequately in our population. Further improvement of prediction models, using recent knowledge about both model development and potential risk factors, is necessary to provide an added value in personalized risk assessment of spontaneous preterm birth. © 2018 The Authors Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Model free approach to kinetic analysis of real-time hyperpolarized 13C magnetic resonance spectroscopy data.

PubMed

Hill, Deborah K; Orton, Matthew R; Mariotti, Erika; Boult, Jessica K R; Panek, Rafal; Jafar, Maysam; Parkes, Harold G; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M S; Beloueche-Babari, Mounia; Robinson, Simon P; Leach, Martin O; Chung, Yuen-Li; Eykyn, Thomas R

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized (13)C metabolic imaging in humans, where measurement of the input function can be problematic.

Model Free Approach to Kinetic Analysis of Real-Time Hyperpolarized 13C Magnetic Resonance Spectroscopy Data

PubMed Central

Mariotti, Erika; Boult, Jessica K. R.; Panek, Rafal; Jafar, Maysam; Parkes, Harold G.; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M. S.; Beloueche-Babari, Mounia; Robinson, Simon P.; Leach, Martin O.; Chung, Yuen-Li; Eykyn, Thomas R.

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized 13C metabolic imaging in humans, where measurement of the input function can be problematic. PMID:24023724

Screening instruments for a population of older adults: The 10-item Kessler Psychological Distress Scale (K10) and the 7-item Generalized Anxiety Disorder Scale (GAD-7).

PubMed

Vasiliadis, Helen-Maria; Chudzinski, Veronica; Gontijo-Guerra, Samantha; Préville, Michel

2015-07-30

Screening tools that appropriately detect older adults' mental disorders are of great public health importance. The present study aimed to establish cutoff scores for the 10-item Kessler Psychological Distress (K10) and the 7-item Generalized Anxiety Disorder (GAD-7) scales when screening for depression and anxiety. We used data from participants (n = 1811) in the Enquête sur la Santé des Aînés-Service study. Depression and anxiety were measured using DSM-V and DSM-IV criteria. Receiver operating characteristic (ROC) curve analysis provided an area under the curve (AUC) of 0.767 and 0.833 for minor and for major depression when using K10. A cutoff of 19 was found to balance sensitivity (0.794) and specificity (0.664) for minor depression, whereas a cutoff of 23 was found to balance sensitivity (0.692) and specificity (0.811) for major depression. When screening for an anxiety with GAD-7, ROC analysis yielded an AUC of 0.695; a cutoff of 5 was found to balance sensitivity (0.709) and specificity (0.568). No significant differences were found between subgroups of age and gender. Both K10 and GAD-7 were able to discriminate between cases and non-cases when screening for depression and anxiety in an older adult population of primary care service users. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Relationship Between Vancomycin Trough Concentrations and AUC/MIC Ratios in Pediatric Patients: A Qualitative Systematic Review.

PubMed

Tkachuk, Stacey; Collins, Kyle; Ensom, Mary H H

2018-04-01

In adults, the area under the concentration-time curve (AUC) divided by the minimum inhibitory concentration (MIC) is associated with better clinical and bacteriological response to vancomycin in patients with methicillin-resistant Staphylococcus aureus who achieve target AUC/MIC ≥ 400. This target is often extrapolated to pediatric patients despite the lack of similar evidence. The impracticalities of calculating the AUC in practice means vancomycin trough concentrations are used to predict the AUC/MIC. This review aimed to determine the relationship between vancomycin trough concentrations and AUC/MIC in pediatric patients. We searched the MEDLINE and Embase databases, the Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials using the medical subject heading (MeSH) terms vancomycin and AUC and pediatric* or paediatric*. Articles were included if they were published in English and reported a relationship between vancomycin trough concentrations and AUC/MIC. Of 122 articles retrieved, 11 met the inclusion criteria. One trial reported a relationship between vancomycin trough concentrations, AUC/MIC, and clinical outcomes but was likely underpowered. Five studies found troughs 6-10 mg/l were sufficient to attain an AUC/MIC > 400 in most general hospitalized pediatric patients. One study in patients undergoing cardiothoracic surgery found a trough of 18.4 mg/l achieved an AUC/MIC > 400. Two oncology studies reported troughs ≥ 15 mg/l likely attained an AUC/MIC ≥ 400. In critical care patients: one study found a trough of 9 mg/l did not attain the AUC/MIC target; another found 7 mg/l corresponded to an AUC/MIC of 400. Potential vancomycin targets varied based on the population studied but, for general hospitalized pediatric patients, troughs of 6-10 mg/l are likely sufficient to achieve AUC/MIC ≥ 400. For MIC ≥ 2 mg/l, higher troughs are likely necessary to achieve an AUC/MIC ≥ 400. More research is needed to determine the relationships between vancomycin trough concentrations, AUC/MIC, and clinical outcomes.

Large-scale external validation and comparison of prognostic models: an application to chronic obstructive pulmonary disease.

PubMed

Guerra, Beniamino; Haile, Sarah R; Lamprecht, Bernd; Ramírez, Ana S; Martinez-Camblor, Pablo; Kaiser, Bernhard; Alfageme, Inmaculada; Almagro, Pere; Casanova, Ciro; Esteban-González, Cristóbal; Soler-Cataluña, Juan J; de-Torres, Juan P; Miravitlles, Marc; Celli, Bartolome R; Marin, Jose M; Ter Riet, Gerben; Sobradillo, Patricia; Lange, Peter; Garcia-Aymerich, Judith; Antó, Josep M; Turner, Alice M; Han, Meilan K; Langhammer, Arnulf; Leivseth, Linda; Bakke, Per; Johannessen, Ane; Oga, Toru; Cosio, Borja; Ancochea-Bermúdez, Julio; Echazarreta, Andres; Roche, Nicolas; Burgel, Pierre-Régis; Sin, Don D; Soriano, Joan B; Puhan, Milo A

2018-03-02

External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores for 3-year all-cause mortality in mostly multimorbid patients with COPD. We relied on 24 cohort studies of the COPD Cohorts Collaborative International Assessment consortium, corresponding to primary, secondary, and tertiary care in Europe, the Americas, and Japan. These studies include globally 15,762 patients with COPD (1871 deaths and 42,203 person years of follow-up). We used network meta-analysis adapted to multiple score comparison (MSC), following a frequentist two-stage approach; thus, we were able to compare all scores in a single analytical framework accounting for correlations among scores within cohorts. We assessed transitivity, heterogeneity, and inconsistency and provided a performance ranking of the prognostic scores. Depending on data availability, between two and nine prognostic scores could be calculated for each cohort. The BODE score (body mass index, airflow obstruction, dyspnea, and exercise capacity) had a median area under the curve (AUC) of 0.679 [1st quartile-3rd quartile = 0.655-0.733] across cohorts. The ADO score (age, dyspnea, and airflow obstruction) showed the best performance for predicting mortality (difference AUC ADO - AUC BODE = 0.015 [95% confidence interval (CI) = -0.002 to 0.032]; p = 0.08) followed by the updated BODE (AUC BODE updated - AUC BODE = 0.008 [95% CI = -0.005 to +0.022]; p = 0.23). The assumption of transitivity was not violated. Heterogeneity across direct comparisons was small, and we did not identify any local or global inconsistency. Our analyses showed best discriminatory performance for the ADO and updated BODE scores in patients with COPD. A limitation to be addressed in future studies is the extension of MSC network meta-analysis to measures of calibration. MSC network meta-analysis can be applied to prognostic scores in any medical field to identify the best scores, possibly paving the way for stratified medicine, public health, and research.

WE-G-207-05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, J; Nishikawa, R; Reiser, I

Purpose: Segmentation quality can affect quantitative image feature analysis. The objective of this study is to examine the relationship between computed tomography (CT) image quality, segmentation performance, and quantitative image feature analysis. Methods: A total of 90 pathology proven breast lesions in 87 dedicated breast CT images were considered. An iterative image reconstruction (IIR) algorithm was used to obtain CT images with different quality. With different combinations of 4 variables in the algorithm, this study obtained a total of 28 different qualities of CT images. Two imaging tasks/objectives were considered: 1) segmentation and 2) classification of the lesion as benignmore » or malignant. Twenty-three image features were extracted after segmentation using a semi-automated algorithm and 5 of them were selected via a feature selection technique. Logistic regression was trained and tested using leave-one-out-cross-validation and its area under the ROC curve (AUC) was recorded. The standard deviation of a homogeneous portion and the gradient of a parenchymal portion of an example breast were used as an estimate of image noise and sharpness. The DICE coefficient was computed using a radiologist’s drawing on the lesion. Mean DICE and AUC were used as performance metrics for each of the 28 reconstructions. The relationship between segmentation and classification performance under different reconstructions were compared. Distributions (median, 95% confidence interval) of DICE and AUC for each reconstruction were also compared. Results: Moderate correlation (Pearson’s rho = 0.43, p-value = 0.02) between DICE and AUC values was found. However, the variation between DICE and AUC values for each reconstruction increased as the image sharpness increased. There was a combination of IIR parameters that resulted in the best segmentation with the worst classification performance. Conclusion: There are certain images that yield better segmentation or classification performance. The best segmentation Result does not necessarily lead to the best classification Result. This work has been supported in part by grants from the NIH R21-EB015053. R Nishikawa is receives royalties form Hologic, Inc.« less

Relationship between Grooming Performance and Motor and Cognitive Functions in Stroke Patients with Receiver Operating Characteristic Analysis.

PubMed

Fujita, Takaaki; Sato, Atsushi; Tsuchiya, Kenji; Ohashi, Takuro; Yamane, Kazuhiro; Yamamoto, Yuichi; Iokawa, Kazuaki; Ohira, Yoko; Otsuki, Koji; Tozato, Fusae

2017-12-01

This study aimed to elucidate the relationship between grooming performance of stroke patients and various motor and cognitive functions and to examine the cognitive and physical functional standards required for grooming independence. We retrospectively analyzed the data of 96 hospitalized patients with first stroke in a rehabilitation hospital ward. Logistic regression analysis and receiver operating characteristic curves were used to investigate the related cognitive and motor functions with grooming performance and to calculate the cutoff values for independence and supervision levels in grooming. For analysis between the independent and supervision-dependent groups, the only item with an area under the curve (AUC) of .9 or higher was the Berg Balance Scale, and the calculated cutoff value was 41/40 (sensitivity, 83.6%; specificity, 87.8%). For analysis between the independent-supervision and dependent groups, the items with an AUC of .9 or higher were the Simple Test for Evaluating Hand Function (STEF) on the nonaffected side, Vitality Index (VI), and FIM ® cognition. The cutoff values were 68/67 for the STEF (sensitivity, 100%; specificity, 72.2%), 9/8 points for the VI (sensitivity, 92.3%; specificity, 88.9%), and 23/22 points for FIM ® cognition (sensitivity, 91.0%; specificity, 88.9%). Our results suggest that upper-extremity functions on the nonaffected side, motivation, and cognitive functions are particularly important to achieve the supervision level and that balance is important to reach the independence level. The effective improvement of grooming performance is possible by performing therapeutic or compensatory intervention on functions that have not achieved these cutoff values. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Value of lower respiratory tract surveillance cultures to predict bacterial pathogens in ventilator-associated pneumonia: systematic review and diagnostic test accuracy meta-analysis.

PubMed

Brusselaers, Nele; Labeau, Sonia; Vogelaers, Dirk; Blot, Stijn

2013-03-01

In ventilator-associated pneumonia (VAP), early appropriate antimicrobial therapy may be hampered by involvement of multidrug-resistant (MDR) pathogens. A systematic review and diagnostic test accuracy meta-analysis were performed to analyse whether lower respiratory tract surveillance cultures accurately predict the causative pathogens of subsequent VAP in adult patients. Selection and assessment of eligibility were performed by three investigators by mutual consideration. Of the 525 studies retrieved, 14 were eligible for inclusion (all in English; published since 1994), accounting for 791 VAP episodes. The following data were collected: study and population characteristics; in- and exclusion criteria; diagnostic criteria for VAP; microbiological workup of surveillance and diagnostic VAP cultures. Sub-analyses were conducted for VAP caused by Staphylococcus aureus, Pseudomonas spp., and Acinetobacter spp., MDR microorganisms, frequency of sampling, and consideration of all versus the most recent surveillance cultures. The meta-analysis showed a high accuracy of surveillance cultures, with pooled sensitivities up to 0.75 and specificities up to 0.92 in culture-positive VAP. The area under the curve (AUC) of the hierarchical summary receiver-operating characteristic curve demonstrates moderate accuracy (AUC: 0.90) in predicting multidrug resistance. A sampling frequency of >2/week (sensitivity 0.79; specificity 0.96) and consideration of only the most recent surveillance culture (sensitivity 0.78; specificity 0.96) are associated with a higher accuracy of prediction. This study provides evidence for the benefit of surveillance cultures in predicting MDR bacterial pathogens in VAP. However, clinical and statistical heterogeneity, limited samples sizes, and bias remain important limitations of this meta-analysis.

Clinical implications of six inflammatory biomarkers as prognostic indicators in Ewing sarcoma

PubMed Central

Li, Yong-Jiang; Yang, Xi; Zhang, Wen-Biao; Yi, Cheng; Wang, Feng; Li, Ping

2017-01-01

Cancer-related systemic inflammation responses have been correlated with cancer development and progression. The prognostic significance of several inflammatory indicators, including neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), Glasgow Prognostic Score (GPS), C-reactive protein to albumin ratio (CRP/Alb ratio), lymphocyte–monocyte ratio (LMR), and neutrophil–platelet score (NPS), were found to be correlated with prognosis in several cancers. However, the prognostic role of these inflammatory biomarkers in Ewing sarcoma has not been evaluated. This study enrolled 122 Ewing patients. Receiver operating characteristic (ROC) analysis was generated to determine optimal cutoff values; areas under the curves (AUCs) were assessed to show the discriminatory ability of the biomarkers; Kaplan–Meier analysis was conducted to plot the survival curves; and Cox multivariate survival analysis was performed to identify independent prognostic factors. The optimal cutoff values of CRP/Alb ratio, NLR, PLR, and LMR were 0.225, 2.38, 131, and 4.41, respectively. CRP/Alb ratio had a significantly larger AUC than NLR, PLR, LMR, and NPS. Higher levels of CRP/Alb ratio (hazard ratio [HR] 2.41, P=0.005), GPS (HR 2.27, P=0.006), NLR (HR 2.07, P=0.013), and PLR (HR 1.85, P=0.032) were significantly correlated with poor prognosis. As the biomarkers had internal correlations, only the CRP/Alb ratio was involved in the multivariate Cox analysis and remained an independent prognostic indicator. The study demonstrated that CRP/Alb ratio, GPS, and NLR were effective prognostic indicators for patients with Ewing sarcoma, and the CRP/Alb ratio was the most robust prognostic indicator with a discriminatory ability superior to that of the other indicators; however, PLR, LMR, and NPS may not be suitable as prognostic indicators in Ewing sarcoma. PMID:29033609

The accuracy of presepsin for the diagnosis of sepsis from SIRS: a systematic review and meta-analysis.

PubMed

Zheng, Zhongjun; Jiang, Libing; Ye, Ligang; Gao, Yuzhi; Tang, Luping; Zhang, Mao

2015-12-01

Sepsis is a common condition that has a high mortality and morbidity that need prompt diagnosis and treatment. Biomarkers like Soluble CD14 subtype (sCD14-ST, presepsin) may be useful in identifying patients with sepsis and its diagnostic superiority has been confirmed by several preliminary studies. The aim of this study was systematically and quantitatively to evaluate the value of presepsin for the diagnosis of sepsis through the method of meta-analysis. Four major databases, including MEDLINE, EMBASE, ISI Web of Knowledge, and the Cochrane Library were systematically searched from inception to March 2015. Two investigators conducted the processes of literature search, study selection, data extraction, and quality evaluation independently. And the original data were extracted from all eligible individual studies to construct two-by-two tables. A total of eight studies comprising 1757 patients were included in this meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratio were 0.77 (95 % confidence interval [CI]: 0.75-0.80), 0.73 (95 % CI 0.69-0.77), and 14.25 (95 % CI 8.66-23.42), respectively. The summary receiver operating characteristic curve (SROC) area under the curve (AUC) was 0.8598. The subgroup analysis based on excluding the outliers showed that the pooled sensitivity and specificity were 0.85 (95 % CI 0.81-0.89) and 0.65 (95 % CI 0.59-0.70), respectively. The AUC was 0.8213 with no significant heterogeneity. Presepsin has moderate diagnostic capacity for the detection of sepsis. Further research of presepsin is needed before widespread use in emergency department. And presepsin in combination with other laboratory biomarkers in diagnosing sepsis may be the focus of future studies.

Salivary Cortisol and Cortisone do not Appear to be Useful Biomarkers for Monitoring Hydrocortisone Replacement in Addison's Disease.

PubMed

Ross, I L; Lacerda, M; Pillay, T S; Blom, D J; Johannsson, G; Dave, J A; Levitt, N S; Haarburger, D; van der Walt, J-S

2016-12-01

Salivary cortisol has been used to monitor hydrocortisone replacement in patients with Addison's disease (AD). Since salivary cortisol is metabolised to salivary cortisone, it may be an adjunctive analyte to assess adequacy of hydrocortisone replacement in patients with AD. We aimed to characterise the exposure of salivary cortisol and cortisone in patients and healthy controls. We measured salivary cortisol and cortisone by liquid chromatography-tandem mass spectrometry and constructed a day curve (08:00 until 24:00 h) with 16 time points in 25 AD patients taking their usual hydrocortisone dose and in 26 healthy controls. The median (interquartile range) area under the curve (AUC) for cortisol was not different for patients, compared with controls [55.63 (32.91-151.07) nmol*min*l -1 vs. 37.49 (27.41-52.00) nmol*min*l -1 ; p=0.098, respectively], whereas the peak cortisol C max was higher in patients [32.61 (5.75-146.19) nmol/l vs. 8.96 (6.96-12.23) nmol/l; p=0.013], compared with controls. The AUC for cortisone [23.65 (6.10-54.76) nmol*min*l -1 vs. 227.73 (200.10-280.52) nmol*min*l -1 ; p≤ 0.001, respectively], and peak cortisone C max was lower in patients than in controls [11.11 (2.91-35.85) nmol/l vs. 33.12 (25.97-39.95) nmol/l; p=0.002]. The AUC for salivary cortisol and salivary cortisone were not correlated with any measures of hydrocortisone dose. The time-course and AUC of salivary cortisol were similar between Addison's patients and healthy controls. Patients had substantially lower salivary cortisone AUC, compared to healthy controls. Salivary cortisol AUC and pharmacokinetics were not related to hydrocortisone dose and thus are not likely useful markers for the adequacy of hydrocortisone replacement. © Georg Thieme Verlag KG Stuttgart · New York.

Emtricitabine Seminal Plasma and Blood Plasma Population Pharmacokinetics in HIV-Infected Men in the EVARIST ANRS-EP 49 Study

PubMed Central

Tréluyer, Jean-Marc; Illamola, Silvia M.; Bouazza, Naïm; Foissac, Frantz; De Sousa Mendes, Maïlys; Lui, Gabrielle; Chenevier-Gobeaux, Camille; Suzan-Monti, Marie; Rouzioux, Christine; Assoumou, Lambert; Viard, Jean-Paul; Hirt, Déborah; Urien, Saïk; Ghosn, Jade

2015-01-01

We aimed to describe blood plasma (BP) and seminal plasma (SP) pharmacokinetics of emtricitabine (FTC) in HIV-1-infected men, assess its penetration in the male genital tract, and evaluate its impact on seminal plasma HIV load (spVL) detection. Men from the EVARIST ANRS EP49 study receiving combined antiretroviral therapy with FTC and with suppressed BP viral load were included in the study. A total of 236 and 209 FTC BP and SP concentrations, respectively, were available. A population pharmacokinetic model was developed with Monolix 4.1.4. The impact of FTC seminal exposure on spVL detection was explored by receiver operating characteristic (ROC) curves and mixed-effects logistic regressions. FTC BP pharmacokinetics was described by a two-compartment model. The addition of an effect compartment with different input and output constants best described FTC SP pharmacokinetics. No covariates were found to explain the variability in SP. FTC exposures (area under the concentration-time curve from 0 to 24 h [AUC0–24]) were higher in SP than in BP (median AUC0–24, 38.04 and 12.95 mg · liter−1 · h, respectively). The median (range) SP-to-BP AUC0–24 ratio was 2.91 (0.84 to 10.08). Less than 1% of FTC AUC0–24 ratios were lower than 1. The impact of FTC SP AUC0–24 or FTC SP-to-BP AUC0–24 ratio on spVL detection was not significant (P = 0.943 or 0.893, respectively). This is the first population model describing FTC pharmacokinetics simultaneously in both BP and SP. FTC distributes well in the male genital tract with higher FTC concentrations in SP than in BP. FTC seminal plasma exposures were considered efficient in the majority of men. PMID:26282407

ROC analysis of the accuracy of Noncycloplegic retinoscopy, Retinomax Autorefractor, and SureSight Vision Screener for preschool vision screening.

PubMed

Ying, Gui-shuang; Maguire, Maureen; Quinn, Graham; Kulp, Marjean Taylor; Cyert, Lynn

2011-12-28

To evaluate, by receiver operating characteristic (ROC) analysis, the accuracy of three instruments of refractive error in detecting eye conditions among 3- to 5-year-old Head Start preschoolers and to evaluate differences in accuracy between instruments and screeners and by age of the child. Children participating in the Vision In Preschoolers (VIP) Study (n = 4040), had screening tests administered by pediatric eye care providers (phase I) or by both nurse and lay screeners (phase II). Noncycloplegic retinoscopy (NCR), the Retinomax Autorefractor (Nikon, Tokyo, Japan), and the SureSight Vision Screener (SureSight, Alpharetta, GA) were used in phase I, and Retinomax and SureSight were used in phase II. Pediatric eye care providers performed a standardized eye examination to identify amblyopia, strabismus, significant refractive error, and reduced visual acuity. The accuracy of the screening tests was summarized by the area under the ROC curve (AUC) and compared between instruments and screeners and by age group. The three screening tests had a high AUC for all categories of screening personnel. The AUC for detecting any VIP-targeted condition was 0.83 for NCR, 0.83 (phase I) to 0.88 (phase II) for Retinomax, and 0.86 (phase I) to 0.87 (phase II) for SureSight. The AUC was 0.93 to 0.95 for detecting group 1 (most severe) conditions and did not differ between instruments or screeners or by age of the child. NCR, Retinomax, and SureSight had similar and high accuracy in detecting vision disorders in preschoolers across all types of screeners and age of child, consistent with previously reported results at specificity levels of 90% and 94%.

Classifying post-stroke fatigue: Optimal cut-off on the Fatigue Assessment Scale.

PubMed

Cumming, Toby B; Mead, Gillian

2017-12-01

Post-stroke fatigue is common and has debilitating effects on independence and quality of life. The Fatigue Assessment Scale (FAS) is a valid screening tool for fatigue after stroke, but there is no established cut-off. We sought to identify the optimal cut-off for classifying post-stroke fatigue on the FAS. In retrospective analysis of two independent datasets (the '2015' and '2007' studies), we evaluated the predictive validity of FAS score against a case definition of fatigue (the criterion standard). Area under the curve (AUC) and sensitivity and specificity at the optimal cut-off were established in the larger 2015 dataset (n=126), and then independently validated in the 2007 dataset (n=52). In the 2015 dataset, AUC was 0.78 (95% CI 0.70-0.86), with the optimal ≥24 cut-off giving a sensitivity of 0.82 and specificity of 0.66. The 2007 dataset had an AUC of 0.83 (95% CI 0.71-0.94), and applying the ≥24 cut-off gave a sensitivity of 0.84 and specificity of 0.67. Post-hoc analysis of the 2015 dataset revealed that using only the 3 most predictive FAS items together ('FAS-3') also yielded good validity: AUC 0.81 (95% CI 0.73-0.89), with sensitivity of 0.83 and specificity of 0.75 at the optimal ≥8 cut-off. We propose ≥24 as a cut-off for classifying post-stroke fatigue on the FAS. While further validation work is needed, this is a positive step towards a coherent approach to reporting fatigue prevalence using the FAS. Copyright © 2017 Elsevier Inc. All rights reserved.

Leptin secretory dynamics and associated disordered eating psychopathology across the weight spectrum

PubMed Central

Baskaran, Charumathi; Eddy, Kamryn T.; Miller, Karen K.; Meenaghan, Erinne; Misra, Madhusmita; Lawson, Elizabeth A.

2016-01-01

Leptin secretory dynamics across the weight spectrum and their relationship with disordered eating psychopathology have not been studied. Our objective was to compare leptin secretory dynamics in 13 anorexia nervosa (AN), 12 overweight/obese (OB) and 12 normal-weight women using deconvolution analysis. Methods In this cross-sectional study conducted at a tertiary referral center, serum leptin levels were obtained every 20 minutes from 2000-0800h. Dual energy X-ray absorptiometry was used to measure %body fat. Disordered eating psychopathology was assessed by the Eating Disorders Examination-Questionnaire (EDE-Q) and Eating Disorders Inventory-2 (EDI-2). Results The groups differed for basal leptin secretion (BASAL) (p=0.02). Mean leptin pulse amplitude, pulse mass, total pulsatile secretion (TPS) and area under the curve (AUC) were significantly different between groups before and after adjustment for BASAL (p<0.0001 for all). Leptin AUC correlated strongly with TPS (r=0.97, p<0.0001) and less with BASAL (r=0.35, p=0.03). On multivariate analysis, only TPS was a significant predictor of leptin AUC (p<0.0001). TPS was inversely associated with most EDE-Q and EDI-2 parameters and the associations remained significant for EDE-Q eating concern (p=0.01), and EDI-2 asceticism, ineffectiveness and social insecurity (p<0.05) after adjusting for BASAL. These relationships were not significant when controlled for %body fat. Conclusion Secretory dynamics of leptin differ across weight spectrum, with mean pulse amplitude, mean pulse mass and TPS being low in AN and high in OB. Pulsatile, rather than basal secretion, is the major contributor to leptin AUC. Decreased pulsatile leptin is associated with disordered eating psychopathology, possibly reflecting low %body fat in AN. PMID:26903591

Gender differences in GH response to GHRH+ARG in lipodystrophic patients with HIV: a key role for body fat distribution.

PubMed

Brigante, Giulia; Diazzi, Chiara; Ansaloni, Anna; Zirilli, Lucia; Orlando, Gabriella; Guaraldi, Giovanni; Rochira, Vincenzo

2014-05-01

Gender influence on GH secretion in human immunodeficiency virus (HIV)-infected patients is poorly known. To determine the effect of gender, we compared GH response to GH-releasing hormone plus arginine (GHRH+Arg), and body composition in 103 men and 97 women with HIV and lipodystrophy. The main outcomes were IGF1, basal GH, GH peak and area under the curve (AUC) after GHRH+Arg, body composition, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). Men had lower GH peak and AUC than women (P<0.001). Of the study population, 21% of women and 37% of men had biochemical GH deficiency (GHD; GH peak <7.5 μg/l). VAT-to-SAT ratio was higher in men than in women with GHD (P<0.05). Unlike women, VAT, SAT, and trunk fat were greater in men with GHD than in men without GHD. IGF1 was significantly lower in women with GHD than in women without GHD, but not in men. At univariate analysis, BMI, trunk fat mass, VAT, and total adipose tissue were associated with GH peak and AUC in both sexes (P<0.05). BMI was the most significant predictive factor of GH peak, and AUC at multiregression analysis. Overall, abdominal fat had a less pronounced effect on GH in females than in males. These data demonstrate that GH response to GHRH+Arg is significantly lower in HIV-infected males than females, resulting in a higher percentage of GHD in men. Adipose tissue distribution more than fat mass per se seems to account for GH gender differences and for the alteration of GH-IGF1 status in these patients.

Uterine electromyography during active phase compared with latent phase of labor at term.

PubMed

Trojner Bregar, Andreja; Lucovnik, Miha; Verdenik, Ivan; Jager, Franc; Gersak, Ksenija; Garfield, Robert E

2016-02-01

In a prospective study in a tertiary university hospital we wanted to determine whether uterine electromyography (EMG) can differentiate between the active and latent phase of labor. Thirty women presenting at ≥37(0/7) weeks of gestation with regular uterine contractions, intact membranes, and a Bishop score <6. EMG was recorded from the abdominal surface for 30 min. Latent phase was defined as no cervical change within at least 4 h. Student's t-test was used for statistical analysis (p ≤ 0.05 significant). Diagnostic accuracy of EMG was determined by receiver operator characteristics (ROC) analysis. The integral of the amplitudes of the power density spectrum (PDS) corresponding to the PDS energy within the "bursts" of uterine EMG activity was compared between the active and latent labor groups. Seventeen (57%) women were found to be in the active phase of labor and 13 (43%) were in the latent phase. The EMG PDS integral was significantly higher (p = 0.02) in the active (mean 3.40 ± 0.82 μV) compared with the latent (mean 1.17 ± 0.33 μV) phase of labor. The PDS integral had an area under the ROC curve (AUC) of 0.80 to distinguish between active and latent phases of labor, compared with number of contractions on tocodynamometry (AUC = 0.79), and Bishop score (AUC = 0.78). The combination (sum) of PDS integral, tocodynamometry, and Bishop score predicted active phase of labor with an AUC of 0.90. Adding uterine EMG measurements to the methods currently used in the clinics could improve the accuracy of diagnosing active labor. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

Diagnostic Accuracy of CT Coronary Angiography According to Pretest Probability of Coronary Artery Disease and Severity of Coronary Arterial Calcification: The CorE-64 International, Multicenter Study

PubMed Central

Arbab-Zadeh, Armin; Miller, Julie M; Rochitte, Carlos E; Dewey, Marc; Niinuma, Hiroyuki; Gottlieb, Ilan; Paul, Narinder; Clouse, Melvin E.; Shapiro, Edward P.; Hoe, John; Lardo, Albert C.; Bush, David E.; de Roos, Albert; Cox, Christopher; Brinker, Jeffrey; Lima, Joăo A. C.

2012-01-01

Objectives Assess the impact of patient population characteristics on accuracy by CT angiography (CTA) to detect obstructive coronary artery disease (CAD). Background The ability of CTA to exclude obstructive CAD in patients of different pretest probabilities and in presence of coronary calcification remains uncertain. Methods For the CorE-64 study 371 patients underwent CTA and cardiac catheterization for the detection of obstructive CAD defined as 50% or greater luminal stenosis by quantitative coronary angiography (QCA). This analysis includes 80 initially excluded patients with a calcium score ≥ 600. Area under the receiver-operating-characteristics curve (AUC) was used to evaluate CTA diagnostic accuracy compared to QCA in patients according to calcium score and pretest probability of CAD. Results Analysis of patient-based quantitative CTA accuracy revealed an AUC of 0.93 (95% confidence interval [CI] 0.90-0.95). AUC remained 0.93 (0.90-0.96) after excluding patients with known CAD but decreased to 0.81 (0.71-0.89) in patients with calcium score ≥ 600 (p=0.077). While AUC were similar (0.93, 0.92, and 0.93, respectively) for patients with intermediate, high pretest probability for CAD, and known CAD, negative predictive values were different: 0.90, 0.83, and 0.50, respectively. Negative predictive values decreased from 0.93 to 0.75 for patients with calcium score < or ≥ 100, respectively (p= 0.053). Conclusions Both pretest probability for CAD and coronary calcium scoring should be considered before using CTA for excluding obstructive CAD. CTA is less effective for this purpose in patients with calcium score ≥ 600 and in patients with a high pretest probability for obstructive CAD. PMID:22261160

Dose-Volume Analysis of Predictors for Gastrointestinal Toxicity After Concurrent Full-Dose Gemcitabine and Radiotherapy for Locally Advanced Pancreatic Adenocarcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang Jiayi; Robertson, John M., E-mail: jrobertson@beaumont.edu; Ye Hong

2012-07-15

Purpose: To identify dosimetric predictors for the development of gastrointestinal (GI) toxicity in patients with locally advanced pancreatic adenocarcinoma (LAPC) treated with concurrent full-dose gemcitabine and radiotherapy (GemRT). Methods and Materials: From June 2002 to June 2009, 46 LAPC patients treated with definitive GemRT were retrospectively analyzed. The stomach and duodenum were retrospectively contoured separately to determine their dose-volume histogram (DVH) parameters. GI toxicity was defined as Grade 3 or higher GI toxicity. The follow-up time was calculated from the start of RT to the date of death or last contact. Univariate analysis (UVA) and multivariate analysis (MVA) using Kaplan-Meiermore » and Cox regression models were performed to identify risk factors associated with GI toxicity. The receiver operating characteristic curve and the area under the receiver operating characteristic curve (AUC) were used to determine the best DVH parameter to predict for GI toxicity. Results: Of the patients, 28 (61%) received concurrent gemcitabine alone, and 18 (39%) had concurrent gemcitabine with daily erlotinib. On UVA, only the V{sub 20Gy} to V{sub 35Gy} of duodenum were significantly associated with GI toxicity (all p {<=} 0.05). On MVA, the V{sub 25Gy} of duodenum and the use of erlotinib were independent risk factors for GI toxicity (p = 0.006 and 0.02, respectively). For the entire cohort, the V{sub 25Gy} of duodenum is the best predictor for GI toxicity (AUC = 0.717), and the 12-month GI toxicity rate was 8% vs. 48% for V{sub 25Gy} {<=} 45% and V{sub 25Gy} > 45%, respectively (p = 0.03). However, excluding the erlotinib group, the V{sub 35Gy} is the best predictor (AUC = 0.725), and the 12-month GI toxicity rate was 0% vs. 41% for V{sub 35Gy} {<=} 20% and V{sub 35Gy} > 20%, respectively (p = 0.04). Conclusions: DVH parameters of duodenum may predict Grade 3 GI toxicity after GemRT for LAPC. Concurrent use of erlotinib during GemRT may increase GI toxicity.« less

Global quantitative indices reflecting provider process-of-care: data-base derivation.

PubMed

Moran, John L; Solomon, Patricia J

2010-04-19

Controversy has attended the relationship between risk-adjusted mortality and process-of-care. There would be advantage in the establishment, at the data-base level, of global quantitative indices subsuming the diversity of process-of-care. A retrospective, cohort study of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 1993-2003, at the level of geographic and ICU-level descriptors (n = 35), for both hospital survivors and non-survivors. Process-of-care indices were established by analysis of: (i) the smoothed time-hazard curve of individual patient discharge and determined by pharmaco-kinetic methods as area under the hazard-curve (AUC), reflecting the integrated experience of the discharge process, and time-to-peak-hazard (TMAX, in days), reflecting the time to maximum rate of hospital discharge; and (ii) individual patient ability to optimize output (as length-of-stay) for recorded data-base physiological inputs; estimated as a technical production-efficiency (TE, scaled [0,(maximum)1]), via the econometric technique of stochastic frontier analysis. For each descriptor, multivariate correlation-relationships between indices and summed mortality probability were determined. The data-set consisted of 223129 patients from 99 ICUs with mean (SD) age and APACHE III score of 59.2(18.9) years and 52.7(30.6) respectively; 41.7% were female and 45.7% were mechanically ventilated within the first 24 hours post-admission. For survivors, AUC was maximal in rural and for-profit ICUs, whereas TMAX (>or= 7.8 days) and TE (>or= 0.74) were maximal in tertiary-ICUs. For non-survivors, AUC was maximal in tertiary-ICUs, but TMAX (>or= 4.2 days) and TE (>or= 0.69) were maximal in for-profit ICUs. Across descriptors, significant differences in indices were demonstrated (analysis-of-variance, P

Assessing Hemorrhage Severity with Continuous Automatic Heart-Rate-Complexity Monitoring in Swine

DTIC Science & Technology

2014-12-02

resuscitative interven- tions, HRC metrics individually were associated with death: SampEn p=0.0002, area under the curve ( AUC ) =.88; MSE p=0.002, AUC =.83...Spontaneously breathing consciously sedated swine were shed 65% of blood volume over 1 hour, then were randomized to 3 groups: control (C, n=7...transfusion of shed blood (TSB, n=7); or endovascular balloon occlusion of the aorta (REBOA) (Pryor Medical, Arvada, CO) for up to 60 minutes followed

Fructose acute effects on glucose, insulin, and triglyceride after a solid meal compared with sucralose and sucrose in a randomized crossover study.

PubMed

Gallagher, Clare; Keogh, Jennifer B; Pedersen, Eva; Clifton, Peter M

2016-06-01

Fructose, which is a sweetener with a low glycemic index, has been shown to elevate postprandial triglyceride compared with glucose. There are limited data on the effect of fructose in a solid mixed meal containing starch and protein. We determined the effects of sucrose, fructose, and sucralose on triglyceride, glucose, and insulin in an acute study in healthy, overweight, and obese individuals. The study had a randomized crossover design. Twenty-seven participants with a mean age of 44 y and a mean body mass index (in kg/m(2)) of 26 completed the study. Fructose (52 g), sucrose (65 g), and sucralose (0.1 g) were delivered as sweet-taste-balanced muffins with a total fat load (66 g). Blood samples were taken at baseline and every 30 min for 4-h glucose, triglyceride, and insulin concentrations, and the area under the curve (AUC) and the incremental area under the curve (iAUC) were analyzed. No significant difference was shown between the 3 sweeteners for triglyceride and glucose concentrations and the AUC. The glucose iAUC was lower for fructose than for sucrose and sucralose (P < 0.05). Insulin concentrations differed significantly by the type of muffin (P = 0.001), the interaction of time by type of muffin (P = 0.035), the AUC (P < 0.001), and the iAUC (P < 0.001). Fructose had a significantly lower insulin response than that of either sucrose (P-treatment = 0.006) or sucralose (P-treatment = 0.041). Fructose, at a moderate dose, did not significantly elevate triglyceride compared with sucrose or sucralose and lowered the glucose iAUC. These results indicate that these sweeteners, at an equivalent sweetness, can be used in normal solid meals. Fructose showed a lower insulin response, which may be beneficial in the long term in individuals at risk of type 2 diabetes. This trial was registered at the Australian New Zealand Clinical Trials Registry as ACTRN12615000279527. © 2016 American Society for Nutrition.

Direct comparison of serial B-type natriuretic peptide and NT-proBNP levels for prediction of short- and long-term outcome in acute decompensated heart failure

PubMed Central

2011-01-01

Introduction Monitoring treatment efficacy and assessing outcome by serial measurements of natriuretic peptides in acute decompensated heart failure (ADHF) patients may help to improve outcome. Methods This was a prospective multi-center study of 171 consecutive patients (mean age 80 73-85 years) presenting to the emergency department with ADHF. Measurement of BNP and NT-proBNP was performed at presentation, 24 hours, 48 hours and at discharge. The primary endpoint was one-year all-cause mortality; secondary endpoints were 30-days all-cause mortality and one-year heart failure (HF) readmission. Results During one-year follow-up, a total of 60 (35%) patients died. BNP and NT-proBNP levels were higher in non-survivors at all time points (all P < 0.001). In survivors, treatment reduced BNP and NT-proBNP levels by more than 50% (P < 0.001), while in non-survivors treatment did not lower BNP and NT-proBNP levels. The area under the ROC curve (AUC) for the prediction of one-year mortality increased during the course of hospitalization for BNP (AUC presentation: 0.67; AUC 24 h: 0.77; AUC 48 h: 0.78; AUC discharge: 0.78) and NT-proBNP (AUC presentation: 0.67; AUC 24 h: 0.73; AUC 48 h: 0.75; AUC discharge: 0.77). In multivariate analysis, BNP at 24 h (1.02 [1.01-1.04], P = 0.003), 48 h (1.04 [1.02-1.06], P < 0.001) and discharge (1.02 [1.01-1.03], P < 0.001) independently predicted one-year mortality, while only pre-discharge NT-proBNP was predictive (1.07 [1.01-1.13], P = 0.016). Comparable results could be obtained for the secondary endpoint 30-days mortality but not for one-year HF readmissions. Conclusions BNP and NT-proBNP reliably predict one-year mortality in patients with ADHF. Prognostic accuracy of both biomarker increases during the course of hospitalization. In survivors BNP levels decline more rapidly than NT-proBNP levels and thus seem to allow earlier assessment of treatment efficacy. Ability to predict one-year HF readmission was poor for BNP and NT-proBNP. Trial registration ClinicalTrials.gov identifier: NCT00514384. PMID:21208408

Multiparametric Analysis of Sniff Nasal Inspiratory Pressure Test in Middle Stage Amyotrophic Lateral Sclerosis.

PubMed

Sarmento, Antonio; Aliverti, Andrea; Marques, Layana; Pennati, Francesca; Dourado-Júnior, Mario Emílio; Fregonezi, Guilherme; Resqueti, Vanessa

2018-01-01

The relaxation rates and contractile properties of inspiratory muscles are altered with inspiratory muscle weakness and fatigue. This fact plays an important role in neuromuscular disorders patients and had never been extensively studied in amyotrophic lateral sclerosis (ALS). In this cross-sectional study, these parameters were investigated non-invasively through nasal inspiratory sniff pressure test (SNIP) in 39 middle stage spinal onset ALS subjects and compared with 39 healthy controls. ALS patients were also divided into three subgroups according to a decline in their percentage of predicted forced vital capacity (FVC %pred ) as well as a decline in the ALS functional rating scale score and its respiratory subscore (R-subscore) in order to determine the best parameter linked to early respiratory muscle weakness. When compared with healthy subjects, middle stage ALS subjects exhibited a significantly lower ( p  < 0.0001) maximum relaxation rate and maximum rate of pressure development (MRPD), as well as a significantly higher ( p  < 0.0001) tau (τ), contraction time, and half-relaxation time. The results from receiver operating characteristic curves showed that MRPD (AUC 0.735, p  < 0.001) and FVC %pred (AUC 0.749, p  = 0.009) were the best discriminator parameters between ALS patients with ≤30 and >30 points in the ALS functional rating scale. In addition, 1/2RT (AUC 0.720, p  = 0.01), FVC %pred (AUC 0.700, p  = 0.03), τ (AUC 0.824, p  < 0.0001), and MRPD (AUC 0.721, p  = 0.01) were the parameters more sensitive in detecting a fall of three points in the R-subscore. On the other hand, MRPD (AUC 0.781, p  < 0.001), τ (AUC 0.794, p  = 0.0001), and percentage of predicted of SNIP (AUC 0.769, p  = 0.002) were the parameters able to detect a fall in 30% of the FVC %pred in middle stage ALS patients. The contractile properties and relaxation rates of the diaphragm are altered in middle stage spinal onset ALS when compared with healthy subjects. These parameters are able to discriminate between those middle stage ALS subjects with early decline in inspiratory muscle function and those who not.

Evaluation of salivary fluoride retention from a new high fluoride mouthrinse.

PubMed

Mason, Stephen C; Shirodaria, Soha; Sufi, Farzana; Rees, Gareth D; Birkhed, Dowen

2010-11-01

To evaluate salivary fluoride retention from a new high fluoride daily use mouthrinse over a 120 min period. Sixteen subjects completed a randomised single-blind, four-treatment cross-over trial. Sensodyne® Pronamel® mouthrinse (A) contained 450 ppm fluoride; reference products were Colgate® Fluorigard® (B), Listerine® Total Care (C) and Listerine Softmint Sensation (D) containing 225, 100 and 0 ppm fluoride respectively. Salivary fluoride retention was monitored ex vivo after a single supervised use of test product (10 mL, 60 s). Samples were collected at 0, 1, 3, 5, 15, 30, 60 and 120 min post-rinse, generating fluoride clearance curves from which the area under the curve (AUC) was calculated. Differences in salivary fluoride concentrations for each product were analysed using ANCOVA at each time point using a 5% significance level, as well as lnAUC for the periods 0-120, 0-1, 1-15, 15-60 and 60-120 min. Pairwise comparisons between all treatment groups were performed. Salivary fluoride levels for A-C peaked immediately following use. Fluoride levels were statistically significantly higher for A versus B-D (p≤ 0.004), linear dose responses were apparent. AUC(0-120) was statistically significantly greater for A than for B (p = 0.035), C (p< 0.0001) and D (p< 0.0001). Post-hoc comparisons of lnAUC for the remaining time domains showed fluoride retention from A was statistically significantly greater versus B-D (p< 0.0001). Single-use treatment with the new mouthrinse containing 450 ppm fluoride resulted in statistically significantly higher salivary fluoride levels throughout the 120 min test period. Total fluoride retention (AUC(0-120)) was also statistically significantly greater versus comparator rinse treatments. Copyright © 2010 Elsevier Ltd. All rights reserved.