P09.62 Towards individualized survival prediction in glioblastoma patients using machine learning methods

PubMed Central

Vera, L.; Pérez-Beteta, J.; Molina, D.; Borrás, J. M.; Benavides, M.; Barcia, J. A.; Velásquez, C.; Albillo, D.; Lara, P.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Machine learning methods are integrated in clinical research studies due to their strong capability to discover parameters having a high information content and their predictive combined potential. Several studies have been developed using glioblastoma patient’s imaging data. Many of them have focused on including large numbers of variables, mostly two-dimensional textural features and/or genomic data, regardless of their meaning or potential clinical relevance. Materials and methods: 193 glioblastoma patients were included in the study. Preoperative 3D magnetic resonance images were collected and semi-automatically segmented using an in-house software. After segmentation, a database of 90 parameters including geometrical and textural image-based measures together with patients’ clinical data (including age, survival, type of treatment, etc.) was constructed. The criterion for including variables in the study was that they had either shown individual impact on survival in single or multivariate analyses or have a precise clinical or geometrical meaning. These variables were used to perform several machine learning experiments. In a first set of computational cross-validation experiments based on regression trees, those attributes showing the highest information measures were extracted. In the second phase, more sophisticated learning methods were employed in order to validate the potential of the previous variables predicting survival. Concretely support vector machines, neural networks and sparse grid methods were used. Results: Variables showing high information measure in the first phase provided the best prediction results in the second phase. Specifically, patient age, Stupp regimen and a geometrical measure related with the irregularity of contrast-enhancing areas were the variables showing the highest information measure in the first stage. For the second phase, the combinations of patient age and Stupp regimen together with one tumor geometrical measure and one tumor heterogeneity feature reached the best quality prediction. Conclusions: Advanced machine learning methods identified the parameters with the highest information measure and survival predictive potential. The uninformed machine learning methods identified a novel feature measure with direct impact on survival. Used in combination with other previously known variables multi-indexes can be defined that can help in tumor characterization and prognosis prediction. Recent advances on the definition of those multi-indexes will be reported in the conference. Funding: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

Functionality of empirical model-based predictive analytics for the early detection of hemodynamic instabilty.

PubMed

Summers, Richard L; Pipke, Matt; Wegerich, Stephan; Conkright, Gary; Isom, Kristen C

2014-01-01

Background. Monitoring cardiovascular hemodynamics in the modern clinical setting is a major challenge. Increasing amounts of physiologic data must be analyzed and interpreted in the context of the individual patient’s pathology and inherent biologic variability. Certain data-driven analytical methods are currently being explored for smart monitoring of data streams from patients as a first tier automated detection system for clinical deterioration. As a prelude to human clinical trials, an empirical multivariate machine learning method called Similarity-Based Modeling (“SBM”), was tested in an In Silico experiment using data generated with the aid of a detailed computer simulator of human physiology (Quantitative Circulatory Physiology or “QCP”) which contains complex control systems with realistic integrated feedback loops. Methods. SBM is a kernel-based, multivariate machine learning method that that uses monitored clinical information to generate an empirical model of a patient’s physiologic state. This platform allows for the use of predictive analytic techniques to identify early changes in a patient’s condition that are indicative of a state of deterioration or instability. The integrity of the technique was tested through an In Silico experiment using QCP in which the output of computer simulations of a slowly evolving cardiac tamponade resulted in progressive state of cardiovascular decompensation. Simulator outputs for the variables under consideration were generated at a 2-min data rate (0.083Hz) with the tamponade introduced at a point 420 minutes into the simulation sequence. The functionality of the SBM predictive analytics methodology to identify clinical deterioration was compared to the thresholds used by conventional monitoring methods. Results. The SBM modeling method was found to closely track the normal physiologic variation as simulated by QCP. With the slow development of the tamponade, the SBM model are seen to disagree while the simulated biosignals in the early stages of physiologic deterioration and while the variables are still within normal ranges. Thus, the SBM system was found to identify pathophysiologic conditions in a timeframe that would not have been detected in a usual clinical monitoring scenario. Conclusion. In this study the functionality of a multivariate machine learning predictive methodology that that incorporates commonly monitored clinical information was tested using a computer model of human physiology. SBM and predictive analytics were able to differentiate a state of decompensation while the monitored variables were still within normal clinical ranges. This finding suggests that the SBM could provide for early identification of a clinical deterioration using predictive analytic techniques. predictive analytics, hemodynamic, monitoring.

Longitudinal Reliability of Self-Reported Age at Menarche in Adolescent Girls: Variability across Time and Setting

ERIC Educational Resources Information Center

Dorn, Lorah D.; Sontag-Padilla, Lisa M.; Pabst, Stephanie; Tissot, Abbigail; Susman, Elizabeth J.

2013-01-01

Age at menarche is critical in research and clinical settings, yet there is a dearth of studies examining its reliability in adolescents. We examined age at menarche during adolescence, specifically, (a) average method reliability across 3 years, (b) test-retest reliability between time points and methods, (c) intraindividual variability of…

Mandibular bone structure, bone mineral density, and clinical variables as fracture predictors: a 15-year follow-up of female patients in a dental clinic.

PubMed

Jonasson, Grethe; Billhult, Annika

2013-09-01

To compare three mandibular trabeculation evaluation methods, clinical variables, and osteoporosis as fracture predictors in women. One hundred and thirty-six female dental patients (35-94 years) answered a questionnaire in 1996 and 2011. Using intra-oral radiographs from 1996, five methods were compared as fracture predictors: (1) mandibular bone structure evaluated with a visual radiographic index, (2) bone texture, (3) size and number of intertrabecular spaces calculated with Jaw-X software, (4) fracture probability calculated with a fracture risk assessment tool (FRAX), and (5) osteoporosis diagnosis based on dual-energy-X-ray absorptiometry. Differences were assessed with the Mann-Whitney test and relative risk calculated. Previous fracture, gluco-corticoid medication, and bone texture were significant indicators of future and total (previous plus future) fracture. Osteoporosis diagnosis, sparse trabeculation, Jaw-X, and FRAX were significant predictors of total but not future fracture. Clinical and oral bone variables may identify individuals at greatest risk of fracture. Copyright © 2013 Elsevier Inc. All rights reserved.

Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models.

PubMed

Geeleher, Paul; Cox, Nancy J; Huang, R Stephanie

2016-09-21

We show that variability in general levels of drug sensitivity in pre-clinical cancer models confounds biomarker discovery. However, using a very large panel of cell lines, each treated with many drugs, we could estimate a general level of sensitivity to all drugs in each cell line. By conditioning on this variable, biomarkers were identified that were more likely to be effective in clinical trials than those identified using a conventional uncorrected approach. We find that differences in general levels of drug sensitivity are driven by biologically relevant processes. We developed a gene expression based method that can be used to correct for this confounder in future studies.

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

PubMed

Chen, Tian; Wu, Pan; Tang, Wan; Zhang, Hui; Feng, Changyong; Kowalski, Jeanne; Tu, Xin M

2016-07-20

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

EDUCORE project: a clinical trial, randomised by clusters, to assess the effect of a visual learning method on blood pressure control in the primary healthcare setting

PubMed Central

2010-01-01

Background High blood pressure (HBP) is a major risk factor for cardiovascular disease (CVD). European hypertension and cardiology societies as well as expert committees on CVD prevention recommend stratifying cardiovascular risk using the SCORE method, the modification of lifestyles to prevent CVD, and achieving good control over risk factors. The EDUCORE (Education and Coronary Risk Evaluation) project aims to determine whether the use of a cardiovascular risk visual learning method - the EDUCORE method - is more effective than normal clinical practice in improving the control of blood pressure within one year in patients with poorly controlled hypertension but no background of CVD; Methods/Design This work describes a protocol for a clinical trial, randomised by clusters and involving 22 primary healthcare clinics, to test the effectiveness of the EDUCORE method. The number of patients required was 736, all between 40 and 65 years of age (n = 368 in the EDUCORE and control groups), all of whom had been diagnosed with HBP at least one year ago, and all of whom had poorly controlled hypertension (systolic blood pressure ≥ 140 mmHg and/or diastolic ≥ 90 mmHg). All personnel taking part were explained the trial and trained in its methodology. The EDUCORE method contemplates the visualisation of low risk SCORE scores using images embodying different stages of a high risk action, plus the receipt of a pamphlet explaining how to better maintain cardiac health. The main outcome variable was the control of blood pressure; secondary outcome variables included the SCORE score, therapeutic compliance, quality of life, and total cholesterol level. All outcome variables were measured at the beginning of the experimental period and again at 6 and 12 months. Information on sex, age, educational level, physical activity, body mass index, consumption of medications, change of treatment and blood analysis results was also recorded; Discussion The EDUCORE method could provide a simple, inexpensive means of improving blood pressure control, and perhaps other health problems, in the primary healthcare setting; Trial registration The trial was registered with ClinicalTrials.gov, number NCT01155973 [http://ClinicalTrials.gov]. PMID:20673325

Datamining approaches for modeling tumor control probability.

PubMed

Naqa, Issam El; Deasy, Joseph O; Mu, Yi; Huang, Ellen; Hope, Andrew J; Lindsay, Patricia E; Apte, Aditya; Alaly, James; Bradley, Jeffrey D

2010-11-01

Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.

Comparison of a clinical gait analysis method using videography and temporal-distance measures with 16-mm cinematography.

PubMed

Stuberg, W A; Colerick, V L; Blanke, D J; Bruce, W

1988-08-01

The purpose of this study was to compare a clinical gait analysis method using videography and temporal-distance measures with 16-mm cinematography in a gait analysis laboratory. Ten children with a diagnosis of cerebral palsy (means age = 8.8 +/- 2.7 years) and 9 healthy children (means age = 8.9 +/- 2.4 years) participated in the study. Stride length, walking velocity, and goniometric measurements of the hip, knee, and ankle were recorded using the two gait analysis methods. A multivariate analysis of variance was used to determine significant differences between the data collected using the two methods. Pearson product-moment correlation coefficients were determined to examine the relationship between the measurements recorded by the two methods. The consistency of performance of the subjects during walking was examined by intraclass correlation coefficients. No significant differences were found between the methods for the variables studied. Pearson product-moment correlation coefficients ranged from .79 to .95, and intraclass coefficients ranged from .89 to .97. The clinical gait analysis method was found to be a valid tool in comparison with 16-mm cinematography for the variables that were studied.

Blood pressure (BP) assessment-from BP level to BP variability.

PubMed

Feber, Janusz; Litwin, Mieczyslaw

2016-07-01

The assessment of blood pressure (BP) can be challenging in children, especially in very young individuals, due to their variable body size and lack of cooperation. In the absence of data relating BP with cardiovascular outcomes in children, there is a need to convert absolute BP values (in mmHg) into age-, gender- and height appropriate BP percentiles or Z-scores in order to compare a patient's BP with the BP of healthy children of the same age, but also of children of different ages. Traditionally, the interpretation of BP has been based mainly on the assessment of the BP level obtained by office, home or 24-h BP monitoring. Recent studies suggest that it is not only BP level (i.e. average BP) but also BP variability that is clinically important for the development of target organ damage, including the progression of chronic kidney disease. In this review we describe current methods to evaluate of BP level, outline available methods for BP variability assessment and discuss the clinical consequences of BP variability, including its potential role in the management of hypertension.

Use of Telehealth for Research and Clinical Measures in Cochlear Implant Recipients: A Validation Study

ERIC Educational Resources Information Center

Hughes, Michelle L.; Goehring, Jenny L.; Baudhuin, Jacquelyn L.; Diaz, Gina R.; Sanford, Todd; Harpster, Roger; Valente, Daniel L.

2012-01-01

Purpose: The goal of this study was to compare clinical and research-based cochlear implant (CI) measures using telehealth versus traditional methods. Method: This prospective study used an ABA design (A = laboratory, B = remote site). All measures were made twice per visit for the purpose of assessing within-session variability. Twenty-nine adult…

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

PubMed

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

Appending Limited Clinical Data to an Administrative Database for Acute Myocardial Infarction Patients: The Impact on the Assessment of Hospital Quality.

PubMed

Hannan, Edward L; Samadashvili, Zaza; Cozzens, Kimberly; Jacobs, Alice K; Venditti, Ferdinand J; Holmes, David R; Berger, Peter B; Stamato, Nicholas J; Hughes, Suzanne; Walford, Gary

2016-05-01

Hospitals' risk-standardized mortality rates and outlier status (significantly higher/lower rates) are reported by the Centers for Medicare and Medicaid Services (CMS) for acute myocardial infarction (AMI) patients using Medicare claims data. New York now has AMI claims data with blood pressure and heart rate added. The objective of this study was to see whether the appended database yields different hospital assessments than standard claims data. New York State clinically appended claims data for AMI were used to create 2 different risk models based on CMS methods: 1 with and 1 without the added clinical data. Model discrimination was compared, and differences between the models in hospital outlier status and tertile status were examined. Mean arterial pressure and heart rate were both significant predictors of mortality in the clinically appended model. The C statistic for the model with the clinical variables added was significantly higher (0.803 vs. 0.773, P<0.001). The model without clinical variables identified 10 low outliers and all of them were percutaneous coronary intervention hospitals. When clinical variables were included in the model, only 6 of those 10 hospitals were low outliers, but there were 2 new low outliers. The model without clinical variables had only 3 high outliers, and the model with clinical variables included identified 2 new high outliers. Appending even a small number of clinical data elements to administrative data resulted in a difference in the assessment of hospital mortality outliers for AMI. The strategy of adding limited but important clinical data elements to administrative datasets should be considered when evaluating hospital quality for procedures and other medical conditions.

Modeling Predictors of Duties Not Including Flying Status.

PubMed

Tvaryanas, Anthony P; Griffith, Converse

2018-01-01

The purpose of this study was to reuse available datasets to conduct an analysis of potential predictors of U.S. Air Force aircrew nonavailability in terms of being in "duties not to include flying" (DNIF) status. This study was a retrospective cohort analysis of U.S. Air Force aircrew on active duty during the period from 2003-2012. Predictor variables included age, Air Force Specialty Code (AFSC), clinic location, diagnosis, gender, pay grade, and service component. The response variable was DNIF duration. Nonparametric methods were used for the exploratory analysis and parametric methods were used for model building and statistical inference. Out of a set of 783 potential predictor variables, 339 variables were identified from the nonparametric exploratory analysis for inclusion in the parametric analysis. Of these, 54 variables had significant associations with DNIF duration in the final model fitted to the validation data set. The predicted results of this model for DNIF duration had a correlation of 0.45 with the actual number of DNIF days. Predictor variables included age, 6 AFSCs, 7 clinic locations, and 40 primary diagnosis categories. Specific demographic (i.e., age), occupational (i.e., AFSC), and health (i.e., clinic location and primary diagnosis category) DNIF drivers were identified. Subsequent research should focus on the application of primary, secondary, and tertiary prevention measures to ameliorate the potential impact of these DNIF drivers where possible.Tvaryanas AP, Griffith C Jr. Modeling predictors of duties not including flying status. Aerosp Med Hum Perform. 2018; 89(1):52-57.

The effects of medical group practice and physician payment methods on costs of care.

PubMed Central

Kralewski, J E; Rich, E C; Feldman, R; Dowd, B E; Bernhardt, T; Johnson, C; Gold, W

2000-01-01

OBJECTIVE: To assess the effects of payment methods on the costs of care in medical group practices. DATA SOURCES: Eighty-six clinics providing services for a Blue Cross managed care program during 1995. The clinics were analyzed to determine the relationship between payment methods and cost of care. Cost and patient data were obtained from Blue Cross records, and medical group practice clinic data were obtained by a survey of those organizations. STUDY DESIGN: The effects of clinic and physician payment methods on per member per year (PMPY) adjusted patient costs are evaluated using a two-stage regression model. Patient costs are adjusted for differences in payment schedules; patient age, gender, and ACG; clinic organizational variables are included as explanatory variables. DATA COLLECTION: Patient cost data were extracted from Blue Cross claims files, and patient and physician data from their enrollee and provider data banks. Medical group practice data were obtained by a mailed survey with telephone follow-up. PRINCIPAL FINDINGS: Capitation payment is correlated with lower patient care costs. When combined with fee-for-service with withhold provisions, this effect is smaller indicating that these two clinic payment methods are not interchangeable. Clinics with more physician compensation based on measures of resource use or based on some share of the net revenue of the clinic have lower patient care costs than those with more compensation related to productivity or based on salary. Salary compensation is strongly associated with higher costs. The use of physician profiles and clinical guidelines is associated with lower costs, but referral management systems have no such effect. The lower cost clinics are the smaller, multispecialty clinics. CONCLUSIONS: This study indicates that payment methods at both the medical group practice and physician levels influence the cost of care. However, the methods by which that influence is manifest is not clear. Although the organizational structure of clinics and their use of managed care programs appear to play a role, this influence is less than expected. PMID:10966087

Neuropsychological Test Selection for Cognitive Impairment Classification: A Machine Learning Approach

PubMed Central

Williams, Jennifer A.; Schmitter-Edgecombe, Maureen; Cook, Diane J.

2016-01-01

Introduction Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI) or dementia using a suite of classification techniques. Methods Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis, clinical dementia rating; CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. Twenty-seven demographic, psychological, and neuropsychological variables were available for variable selection. Results No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0 – 99.1%), geometric mean (60.9 – 98.1%), sensitivity (44.2 – 100%), and specificity (52.7 – 100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2 – 9 variables were required for classification and varied between datasets in a clinically meaningful way. Conclusions The current study results reveal that machine learning techniques can accurately classifying cognitive impairment and reduce the number of measures required for diagnosis. PMID:26332171

Falsification Testing of Instrumental Variables Methods for Comparative Effectiveness Research.

PubMed

Pizer, Steven D

2016-04-01

To demonstrate how falsification tests can be used to evaluate instrumental variables methods applicable to a wide variety of comparative effectiveness research questions. Brief conceptual review of instrumental variables and falsification testing principles and techniques accompanied by an empirical application. Sample STATA code related to the empirical application is provided in the Appendix. Comparative long-term risks of sulfonylureas and thiazolidinediones for management of type 2 diabetes. Outcomes include mortality and hospitalization for an ambulatory care-sensitive condition. Prescribing pattern variations are used as instrumental variables. Falsification testing is an easily computed and powerful way to evaluate the validity of the key assumption underlying instrumental variables analysis. If falsification tests are used, instrumental variables techniques can help answer a multitude of important clinical questions. © Health Research and Educational Trust.

Self-Calibrating Wave-Encoded Variable-Density Single-Shot Fast Spin Echo Imaging.

PubMed

Chen, Feiyu; Taviani, Valentina; Tamir, Jonathan I; Cheng, Joseph Y; Zhang, Tao; Song, Qiong; Hargreaves, Brian A; Pauly, John M; Vasanawala, Shreyas S

2018-04-01

It is highly desirable in clinical abdominal MR scans to accelerate single-shot fast spin echo (SSFSE) imaging and reduce blurring due to T 2 decay and partial-Fourier acquisition. To develop and investigate the clinical feasibility of wave-encoded variable-density SSFSE imaging for improved image quality and scan time reduction. Prospective controlled clinical trial. With Institutional Review Board approval and informed consent, the proposed method was assessed on 20 consecutive adult patients (10 male, 10 female, range, 24-84 years). A wave-encoded variable-density SSFSE sequence was developed for clinical 3.0T abdominal scans to enable high acceleration (3.5×) with full-Fourier acquisitions by: 1) introducing wave encoding with self-refocusing gradient waveforms to improve acquisition efficiency; 2) developing self-calibrated estimation of wave-encoding point-spread function and coil sensitivity to improve motion robustness; and 3) incorporating a parallel imaging and compressed sensing reconstruction to reconstruct highly accelerated datasets. Image quality was compared pairwise with standard Cartesian acquisition independently and blindly by two radiologists on a scale from -2 to 2 for noise, contrast, confidence, sharpness, and artifacts. The average ratio of scan time between these two approaches was also compared. A Wilcoxon signed-rank tests with a P value under 0.05 considered statistically significant. Wave-encoded variable-density SSFSE significantly reduced the perceived noise level and improved the sharpness of the abdominal wall and the kidneys compared with standard acquisition (mean scores 0.8, 1.2, and 0.8, respectively, P < 0.003). No significant difference was observed in relation to other features (P = 0.11). An average of 21% decrease in scan time was achieved using the proposed method. Wave-encoded variable-density sampling SSFSE achieves improved image quality with clinically relevant echo time and reduced scan time, thus providing a fast and robust approach for clinical SSFSE imaging. 1 Technical Efficacy: Stage 6 J. Magn. Reson. Imaging 2018;47:954-966. © 2017 International Society for Magnetic Resonance in Medicine.

Missing Data in Clinical Studies: Issues and Methods

PubMed Central

Ibrahim, Joseph G.; Chu, Haitao; Chen, Ming-Hui

2012-01-01

Missing data are a prevailing problem in any type of data analyses. A participant variable is considered missing if the value of the variable (outcome or covariate) for the participant is not observed. In this article, various issues in analyzing studies with missing data are discussed. Particularly, we focus on missing response and/or covariate data for studies with discrete, continuous, or time-to-event end points in which generalized linear models, models for longitudinal data such as generalized linear mixed effects models, or Cox regression models are used. We discuss various classifications of missing data that may arise in a study and demonstrate in several situations that the commonly used method of throwing out all participants with any missing data may lead to incorrect results and conclusions. The methods described are applied to data from an Eastern Cooperative Oncology Group phase II clinical trial of liver cancer and a phase III clinical trial of advanced non–small-cell lung cancer. Although the main area of application discussed here is cancer, the issues and methods we discuss apply to any type of study. PMID:22649133

How novice, skilled and advanced clinical researchers include variables in a case report form for clinical research: a qualitative study

PubMed Central

Chu, Hongling; Zeng, Lin; Fetters, Micheal D; Li, Nan; Tao, Liyuan; Shi, Yanyan; Zhang, Hua; Wang, Xiaoxiao; Li, Fengwei; Zhao, Yiming

2017-01-01

Objectives Despite varying degrees in research training, most academic clinicians are expected to conduct clinical research. The objective of this research was to understand how clinical researchers of different skill levels include variables in a case report form for their clinical research. Setting The setting for this research was a major academic institution in Beijing, China. Participants The target population was clinical researchers with three levels of experience, namely, limited clinical research experience, clinicians with rich clinical research experience and clinical research experts. Methods Using a qualitative approach, we conducted 13 individual interviews (face to face) and one group interview (n=4) with clinical researchers from June to September 2016. Based on maximum variation sampling to identify researchers with three levels of research experience: eight clinicians with limited clinical research experience, five clinicians with rich clinical research experience and four clinical research experts. These 17 researchers had diverse hospital-based medical specialties and or specialisation in clinical research. Results Our analysis yields a typology of three processes developing a case report form that varies according to research experience level. Novice clinician researchers often have an incomplete protocol or none at all, and conduct data collection and publication based on a general framework. Experienced clinician researchers include variables in the case report form based on previous experience with attention to including domains or items at risk for omission and by eliminating unnecessary variables. Expert researchers consider comprehensively in advance data collection and implementation needs and plan accordingly. Conclusion These results illustrate increasing levels of sophistication in research planning that increase sophistication in selection for variables in the case report form. These findings suggest that novice and intermediate-level researchers could benefit by emulating the comprehensive planning procedures such as those used by expert clinical researchers. PMID:28928184

Selection Practices of Group Leaders: A National Survey.

ERIC Educational Resources Information Center

Riva, Maria T.; Lippert, Laurel; Tackett, M. Jan

2000-01-01

Study surveys the selection practices of group leaders. Explores methods of selection, variables used to make selection decisions, and the types of selection errors that leaders have experienced. Results suggest that group leaders use clinical judgment to make selection decisions and endorse using some specific variables in selection. (Contains 22…

Variables selection methods in near-infrared spectroscopy.

PubMed

Xiaobo, Zou; Jiewen, Zhao; Povey, Malcolm J W; Holmes, Mel; Hanpin, Mao

2010-05-14

Near-infrared (NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields, such as the petrochemical, pharmaceutical, environmental, clinical, agricultural, food and biomedical sectors during the past 15 years. A NIR spectrum of a sample is typically measured by modern scanning instruments at hundreds of equally spaced wavelengths. The large number of spectral variables in most data sets encountered in NIR spectral chemometrics often renders the prediction of a dependent variable unreliable. Recently, considerable effort has been directed towards developing and evaluating different procedures that objectively identify variables which contribute useful information and/or eliminate variables containing mostly noise. This review focuses on the variable selection methods in NIR spectroscopy. Selection methods include some classical approaches, such as manual approach (knowledge based selection), "Univariate" and "Sequential" selection methods; sophisticated methods such as successive projections algorithm (SPA) and uninformative variable elimination (UVE), elaborate search-based strategies such as simulated annealing (SA), artificial neural networks (ANN) and genetic algorithms (GAs) and interval base algorithms such as interval partial least squares (iPLS), windows PLS and iterative PLS. Wavelength selection with B-spline, Kalman filtering, Fisher's weights and Bayesian are also mentioned. Finally, the websites of some variable selection software and toolboxes for non-commercial use are given. Copyright 2010 Elsevier B.V. All rights reserved.

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

Quantification of myocardium at risk in ST- elevation myocardial infarction: a comparison of contrast-enhanced steady-state free precession cine cardiovascular magnetic resonance with coronary angiographic jeopardy scores.

PubMed

De Palma, Rodney; Sörensson, Peder; Verouhis, Dinos; Pernow, John; Saleh, Nawzad

2017-07-27

Clinical outcome following acute myocardial infarction is predicted by final infarct size evaluated in relation to left ventricular myocardium at risk (MaR). Contrast-enhanced steady-state free precession (CE-SSFP) cardiovascular magnetic resonance imaging (CMR) is not widely used for assessing MaR. Evidence of its utility compared to traditional assessment methods and as a surrogate for clinical outcome is needed. Retrospective analysis within a study evaluating post-conditioning during ST elevation myocardial infarction (STEMI) treated with coronary intervention (n = 78). CE-SSFP post-infarction was compared with angiographic jeopardy methods. Differences and variability between CMR and angiographic methods using Bland-Altman analyses were evaluated. Clinical outcomes were compared to MaR and extent of infarction. MaR showed correlation between CE-SSFP, and both BARI and APPROACH scores of 0.83 (p < 0.0001) and 0.84 (p < 0.0001) respectively. Bias between CE-SSFP and BARI was 1.1% (agreement limits -11.4 to +9.1). Bias between CE-SSFP and APPROACH was 1.2% (agreement limits -13 to +10.5). Inter-observer variability for the BARI score was 0.56 ± 2.9; 0.42 ± 2.1 for the APPROACH score; -1.4 ± 3.1% for CE-SSFP. Intra-observer variability was 0.15 ± 1.85 for the BARI score; for the APPROACH score 0.19 ± 1.6; and for CE-SSFP -0.58 ± 2.9%. Quantification of MaR with CE-SSFP imaging following STEMI shows high correlation and low bias compared with angiographic scoring and supports its use as a reliable and practical method to determine myocardial salvage in this patient population. Clinical trial registration information for the parent clinical trial: Karolinska Clinical Trial Registration (2008) Unique identifier: CT20080014. Registered 04 th January 2008.

PRIM versus CART in subgroup discovery: when patience is harmful.

PubMed

Abu-Hanna, Ameen; Nannings, Barry; Dongelmans, Dave; Hasman, Arie

2010-10-01

We systematically compare the established algorithms CART (Classification and Regression Trees) and PRIM (Patient Rule Induction Method) in a subgroup discovery task on a large real-world high-dimensional clinical database. Contrary to current conjectures, PRIM's performance was generally inferior to CART's. PRIM often considered "peeling of" a large chunk of data at a value of a relevant discrete ordinal variable unattractive, ultimately missing an important subgroup. This finding has considerable significance in clinical medicine where ordinal scores are ubiquitous. PRIM's utility in clinical databases would increase when global information about (ordinal) variables is better put to use and when the search algorithm keeps track of alternative solutions.

Molecular method for the characterization of Coxiella burnetii from clinical and environmental samples: variability of genotypes in Spain

PubMed Central

2012-01-01

Background Coxiella burnetii is a highly clonal microorganism which is difficult to culture, requiring BSL3 conditions for its propagation. This leads to a scarce availability of isolates worldwide. On the other hand, published methods of characterization have delineated up to 8 different genomic groups and 36 genotypes. However, all these methodologies, with the exception of one that exhibited limited discriminatory power (3 genotypes), rely on performing between 10 and 20 PCR amplifications or sequencing long fragments of DNA, which make their direct application to clinical samples impracticable and leads to a scarce accessibility of data on the circulation of C. burnetii genotypes. Results To assess the variability of this organism in Spain, we have developed a novel method that consists of a multiplex (8 targets) PCR and hybridization with specific probes that reproduce the previous classification of this organism into 8 genomic groups, and up to 16 genotypes. It allows for a direct characterization from clinical and environmental samples in a single run, which will help in the study of the different genotypes circulating in wild and domestic cycles as well as from sporadic human cases and outbreaks. The method has been validated with reference isolates. A high variability of C. burnetii has been found in Spain among 90 samples tested, detecting 10 different genotypes, being those adaA negative associated with acute Q fever cases presenting as fever of intermediate duration with liver involvement and with chronic cases. Genotypes infecting humans are also found in sheep, goats, rats, wild boar and ticks, and the only genotype found in cattle has never been found among our clinical samples. Conclusions This newly developed methodology has permitted to demonstrate that C. burnetii is highly variable in Spain. With the data presented here, cattle seem not to participate in the transmission of C. burnetii to humans in the samples studied, while sheep, goats, wild boar, rats and ticks share genotypes with the human population. PMID:22656068

Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

PubMed Central

Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

2013-01-01

Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

Big data in sleep medicine: prospects and pitfalls in phenotyping

PubMed Central

Bianchi, Matt T; Russo, Kathryn; Gabbidon, Harriett; Smith, Tiaundra; Goparaju, Balaji; Westover, M Brandon

2017-01-01

Clinical polysomnography (PSG) databases are a rich resource in the era of “big data” analytics. We explore the uses and potential pitfalls of clinical data mining of PSG using statistical principles and analysis of clinical data from our sleep center. We performed retrospective analysis of self-reported and objective PSG data from adults who underwent overnight PSG (diagnostic tests, n=1835). Self-reported symptoms overlapped markedly between the two most common categories, insomnia and sleep apnea, with the majority reporting symptoms of both disorders. Standard clinical metrics routinely reported on objective data were analyzed for basic properties (missing values, distributions), pairwise correlations, and descriptive phenotyping. Of 41 continuous variables, including clinical and PSG derived, none passed testing for normality. Objective findings of sleep apnea and periodic limb movements were common, with 51% having an apnea–hypopnea index (AHI) >5 per hour and 25% having a leg movement index >15 per hour. Different visualization methods are shown for common variables to explore population distributions. Phenotyping methods based on clinical databases are discussed for sleep architecture, sleep apnea, and insomnia. Inferential pitfalls are discussed using the current dataset and case examples from the literature. The increasing availability of clinical databases for large-scale analytics holds important promise in sleep medicine, especially as it becomes increasingly important to demonstrate the utility of clinical testing methods in management of sleep disorders. Awareness of the strengths, as well as caution regarding the limitations, will maximize the productive use of big data analytics in sleep medicine. PMID:28243157

A simple, rapid and validated high-performance liquid chromatography method suitable for clinical measurements of human mercaptalbumin and non-mercaptalbumin.

PubMed

Yasukawa, Keiko; Shimosawa, Tatsuo; Okubo, Shigeo; Yatomi, Yutaka

2018-01-01

Background Human mercaptalbumin and human non-mercaptalbumin have been reported as markers for various pathological conditions, such as kidney and liver diseases. These markers play important roles in redox regulations throughout the body. Despite the recognition of these markers in various pathophysiologic conditions, the measurements of human mercaptalbumin and non-mercaptalbumin have not been popular because of the technical complexity and long measurement time of conventional methods. Methods Based on previous reports, we explored the optimal analytical conditions for a high-performance liquid chromatography method using an anion-exchange column packed with a hydrophilic polyvinyl alcohol gel. The method was then validated using performance tests as well as measurements of various patients' serum samples. Results We successfully established a reliable high-performance liquid chromatography method with an analytical time of only 12 min per test. The repeatability (within-day variability) and reproducibility (day-to-day variability) were 0.30% and 0.27% (CV), respectively. A very good correlation was obtained with the results of the conventional method. Conclusions A practical method for the clinical measurement of human mercaptalbumin and non-mercaptalbumin was established. This high-performance liquid chromatography method is expected to be a powerful tool enabling the expansion of clinical usefulness and ensuring the elucidation of the roles of albumin in redox reactions throughout the human body.

Time series analysis as input for clinical predictive modeling: Modeling cardiac arrest in a pediatric ICU

PubMed Central

2011-01-01

Background Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. Methods We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Results Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1) selecting candidate variables; 2) specifying measurement parameters; 3) defining data format; 4) defining time window duration and resolution; 5) calculating latent variables for candidate variables not directly measured; 6) calculating time series features as latent variables; 7) creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8) reducing the number of candidate features; 9) training models for various data subsets; and 10) measuring model performance characteristics in unseen data to estimate their external validity. Conclusions We have proposed a ten step process that results in data sets that contain time series features and are suitable for predictive modeling by a number of methods. We illustrated the process through an example of cardiac arrest prediction in a pediatric intensive care setting. PMID:22023778

[Clinical research XXIII. From clinical judgment to meta-analyses].

PubMed

Rivas-Ruiz, Rodolfo; Castelán-Martínez, Osvaldo D; Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Noyola-Castillo, Maura E; Talavera, Juan O

2014-01-01

Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index -BMI-) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and chi-squared. To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations.

Intra- and Interobserver Variability of Cochlear Length Measurements in Clinical CT.

PubMed

Iyaniwura, John E; Elfarnawany, Mai; Riyahi-Alam, Sadegh; Sharma, Manas; Kassam, Zahra; Bureau, Yves; Parnes, Lorne S; Ladak, Hanif M; Agrawal, Sumit K

2017-07-01

The cochlear A-value measurement exhibits significant inter- and intraobserver variability, and its accuracy is dependent on the visualization method in clinical computed tomography (CT) images of the cochlea. An accurate estimate of the cochlear duct length (CDL) can be used to determine electrode choice, and frequency map the cochlea based on the Greenwood equation. Studies have described estimating the CDL using a single A-value measurement, however the observer variability has not been assessed. Clinical and micro-CT images of 20 cadaveric cochleae were acquired. Four specialists measured A-values on clinical CT images using both standard views and multiplanar reconstructed (MPR) views. Measurements were repeated to assess for intraobserver variability. Observer variabilities were evaluated using intra-class correlation and absolute differences. Accuracy was evaluated by comparison to the gold standard micro-CT images of the same specimens. Interobserver variability was good (average absolute difference: 0.77 ± 0.42 mm) using standard views and fair (average absolute difference: 0.90 ± 0.31 mm) using MPR views. Intraobserver variability had an average absolute difference of 0.31 ± 0.09 mm for the standard views and 0.38 ± 0.17 mm for the MPR views. MPR view measurements were more accurate than standard views, with average relative errors of 9.5 and 14.5%, respectively. There was significant observer variability in A-value measurements using both the standard and MPR views. Creating the MPR views increased variability between experts, however MPR views yielded more accurate results. Automated A-value measurement algorithms may help to reduce variability and increase accuracy in the future.

Effects of Talker Variability on Vowel Recognition in Cochlear Implants

ERIC Educational Resources Information Center

Chang, Yi-ping; Fu, Qian-Jie

2006-01-01

Purpose: To investigate the effects of talker variability on vowel recognition by cochlear implant (CI) users and by normal-hearing (NH) participants listening to 4-channel acoustic CI simulations. Method: CI users were tested with their clinically assigned speech processors. For NH participants, 3 CI processors were simulated, using different…

Error Variability and the Differentiation between Apraxia of Speech and Aphasia with Phonemic Paraphasia

ERIC Educational Resources Information Center

Haley, Katarina L.; Jacks, Adam; Cunningham, Kevin T.

2013-01-01

Purpose: This study was conducted to evaluate the clinical utility of error variability for differentiating between apraxia of speech (AOS) and aphasia with phonemic paraphasia. Method: Participants were 32 individuals with aphasia after left cerebral injury. Diagnostic groups were formed on the basis of operationalized measures of recognized…

Examination of Individual Differences in Outcomes from a Randomized Controlled Clinical Trial Comparing Formal and Informal Individual Auditory Training Programs

ERIC Educational Resources Information Center

Smith, Sherri L.; Saunders, Gabrielle H.; Chisolm, Theresa H.; Frederick, Melissa; Bailey, Beth A.

2016-01-01

Purpose: The purpose of this study was to determine if patient characteristics or clinical variables could predict who benefits from individual auditory training. Method: A retrospective series of analyses were performed using a data set from a large, multisite, randomized controlled clinical trial that compared the treatment effects of at-home…

Towards a new standardized method for circulating miRNAs profiling in clinical studies: Interest of the exogenous normalization to improve miRNA signature accuracy.

PubMed

Vigneron, Nicolas; Meryet-Figuière, Matthieu; Guttin, Audrey; Issartel, Jean-Paul; Lambert, Bernard; Briand, Mélanie; Louis, Marie-Hélène; Vernon, Mégane; Lebailly, Pierre; Lecluse, Yannick; Joly, Florence; Krieger, Sophie; Lheureux, Stéphanie; Clarisse, Bénédicte; Leconte, Alexandra; Gauduchon, Pascal; Poulain, Laurent; Denoyelle, Christophe

2016-08-01

Circulating miRNAs are promising biomarkers in oncology but have not yet been implemented in the clinic given the lack of concordance across studies. In order to increase the cross-studies reliability, we attempted to reduce and to control the circulating miRNA expression variability between patients. First, to maximize profiling signals and to reduce miRNA expression variability, three isolation kits were compared and the NucleoSpin(®) kit provided higher miRNA concentrations than the other widely used kits. Second, to control inter-sample variability during the profiling step, the exogenous miRNAs normalization method commonly used for RT-qPCR validation step was adapted to microarray experiments. Importantly, exogenous miRNAs presented two-fold lower inter-sample variability than the widely used endogenous miR-16-5p reflecting that the latter is subject to both biological and technical variability. Although Caenorhabditis elegans miRNAs isolation yields were heterogeneous, they correlated to each other and to their geometrical mean across samples. The normalization based on the geometrical mean of three exogenous miRNAs increased the correlation up-to 0.97 between the microarrays and individual RT-qPCR steps of circulating miRNAs expression. Overall, this new strategy open new avenue to identify reliable circulating miRNA signatures for translation into clinical practice. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Incorporating microbiota data into epidemiologic models: examples from vaginal microbiota research.

PubMed

van de Wijgert, Janneke H; Jespers, Vicky

2016-05-01

Next generation sequencing and quantitative polymerase chain reaction technologies are now widely available, and research incorporating these methods is growing exponentially. In the vaginal microbiota (VMB) field, most research to date has been descriptive. The purpose of this article is to provide an overview of different ways in which next generation sequencing and quantitative polymerase chain reaction data can be used to answer clinical epidemiologic research questions using examples from VMB research. We reviewed relevant methodological literature and VMB articles (published between 2008 and 2015) that incorporated these methodologies. VMB data have been analyzed using ecologic methods, methods that compare the presence or relative abundance of individual taxa or community compositions between different groups of women or sampling time points, and methods that first reduce the complexity of the data into a few variables followed by the incorporation of these variables into traditional biostatistical models. To make future VMB research more clinically relevant (such as studying associations between VMB compositions and clinical outcomes and the effects of interventions on the VMB), it is important that these methods are integrated with rigorous epidemiologic methods (such as appropriate study designs, sampling strategies, and adjustment for confounding). Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

An automated A-value measurement tool for accurate cochlear duct length estimation.

PubMed

Iyaniwura, John E; Elfarnawany, Mai; Ladak, Hanif M; Agrawal, Sumit K

2018-01-22

There has been renewed interest in the cochlear duct length (CDL) for preoperative cochlear implant electrode selection and postoperative generation of patient-specific frequency maps. The CDL can be estimated by measuring the A-value, which is defined as the length between the round window and the furthest point on the basal turn. Unfortunately, there is significant intra- and inter-observer variability when these measurements are made clinically. The objective of this study was to develop an automated A-value measurement algorithm to improve accuracy and eliminate observer variability. Clinical and micro-CT images of 20 cadaveric cochleae specimens were acquired. The micro-CT of one sample was chosen as the atlas, and A-value fiducials were placed onto that image. Image registration (rigid affine and non-rigid B-spline) was applied between the atlas and the 19 remaining clinical CT images. The registration transform was applied to the A-value fiducials, and the A-value was then automatically calculated for each specimen. High resolution micro-CT images of the same 19 specimens were used to measure the gold standard A-values for comparison against the manual and automated methods. The registration algorithm had excellent qualitative overlap between the atlas and target images. The automated method eliminated the observer variability and the systematic underestimation by experts. Manual measurement of the A-value on clinical CT had a mean error of 9.5 ± 4.3% compared to micro-CT, and this improved to an error of 2.7 ± 2.1% using the automated algorithm. Both the automated and manual methods correlated significantly with the gold standard micro-CT A-values (r = 0.70, p < 0.01 and r = 0.69, p < 0.01, respectively). An automated A-value measurement tool using atlas-based registration methods was successfully developed and validated. The automated method eliminated the observer variability and improved accuracy as compared to manual measurements by experts. This open-source tool has the potential to benefit cochlear implant recipients in the future.

Determination of the anaerobic threshold in the pre-operative assessment clinic: inter-observer measurement error.

PubMed

Sinclair, R C F; Danjoux, G R; Goodridge, V; Batterham, A M

2009-11-01

The variability between observers in the interpretation of cardiopulmonary exercise tests may impact upon clinical decision making and affect the risk stratification and peri-operative management of a patient. The purpose of this study was to quantify the inter-reader variability in the determination of the anaerobic threshold (V-slope method). A series of 21 cardiopulmonary exercise tests from patients attending a surgical pre-operative assessment clinic were read independently by nine experienced clinicians regularly involved in clinical decision making. The grand mean for the anaerobic threshold was 10.5 ml O(2).kg body mass(-1).min(-1). The technical error of measurement was 8.1% (circa 0.9 ml.kg(-1).min(-1); 90% confidence interval, 7.4-8.9%). The mean absolute difference between readers was 4.5% with a typical random error of 6.5% (6.0-7.2%). We conclude that the inter-observer variability for experienced clinicians determining the anaerobic threshold from cardiopulmonary exercise tests is acceptable.

Strategies and methods to study female-specific cardiovascular health and disease: a guide for clinical scientists.

PubMed

Ouyang, Pamela; Wenger, Nanette K; Taylor, Doris; Rich-Edwards, Janet W; Steiner, Meir; Shaw, Leslee J; Berga, Sarah L; Miller, Virginia M; Merz, Noel Bairey

2016-01-01

In 2001, the Institute of Medicine's (IOM) report, "Exploring the Biological Contributions to Human Health: Does Sex Matter?" advocated for better understanding of the differences in human diseases between the sexes, with translation of these differences into clinical practice. Sex differences are well documented in the prevalence of cardiovascular (CV) risk factors, the clinical manifestation and incidence of cardiovascular disease (CVD), and the impact of risk factors on outcomes. There are also physiologic and psychosocial factors unique to women that may affect CVD risk, such as issues related to reproduction. The Society for Women's Health Research (SWHR) CV Network compiled an inventory of sex-specific strategies and methods for the study of women and CV health and disease across the lifespan. References for methods and strategy details are provided to gather and evaluate this information. Some items comprise robust measures; others are in development. To address female-specific CV health and disease in population, physiology, and clinical trial research, data should be collected on reproductive history, psychosocial variables, and other factors that disproportionately affect CVD in women. Variables related to reproductive health include the following: age of menarche, menstrual cycle regularity, hormone levels, oral contraceptive use, pregnancy history/complications, polycystic ovary syndrome (PCOS) components, menopause age, and use and type of menopausal hormone therapy. Other factors that differentially affect women's CV risk include diabetes mellitus, autoimmune inflammatory disease, and autonomic vasomotor control. Sex differences in aging as well as psychosocial variables such as depression and stress should also be considered. Women are frequently not included/enrolled in mixed-sex CVD studies; when they are included, information on these variables is generally not collected. These omissions limit the ability to determine the role of sex-specific contributors to CV health and disease. Lack of sex-specific knowledge contributes to the CVD health disparities that women face. The purpose of this review is to encourage investigators to consider ways to increase the usefulness of physiological and psychosocial data obtained from clinical populations, in an effort to improve the understanding of sex differences in clinical CVD research and health-care delivery for women and men.

Is the common cold a clinical entity or a cultural concept?

PubMed

Eccles, R

2013-03-01

Common cold is the most common infectious disease of mankind and the term is widely used in the clinical literature as though it were a defined clinical syndrome. Clinical studies on this syndrome often use elaborate symptom scoring systems to diagnose a common cold. The symptom scores are based on a study conducted over 50 years ago to retrospectively diagnose experimental cold and this method cannot be applied to diagnosis of common cold in the community. Diagnosis of the common cold by virology is not feasible because of the number of viruses and the variability in the disease states caused by the viruses. Because of the familiarity of subjects with common cold and the variability in symptomatology it seems a more reasonable approach to use self-diagnosis of common cold for clinical research studies and accept that the common cold is a cultural concept and not a clinical entity.

Group Variable Selection Via Convex Log-Exp-Sum Penalty with Application to a Breast Cancer Survivor Study

PubMed Central

Geng, Zhigeng; Wang, Sijian; Yu, Menggang; Monahan, Patrick O.; Champion, Victoria; Wahba, Grace

2017-01-01

Summary In many scientific and engineering applications, covariates are naturally grouped. When the group structures are available among covariates, people are usually interested in identifying both important groups and important variables within the selected groups. Among existing successful group variable selection methods, some methods fail to conduct the within group selection. Some methods are able to conduct both group and within group selection, but the corresponding objective functions are non-convex. Such a non-convexity may require extra numerical effort. In this article, we propose a novel Log-Exp-Sum(LES) penalty for group variable selection. The LES penalty is strictly convex. It can identify important groups as well as select important variables within the group. We develop an efficient group-level coordinate descent algorithm to fit the model. We also derive non-asymptotic error bounds and asymptotic group selection consistency for our method in the high-dimensional setting where the number of covariates can be much larger than the sample size. Numerical results demonstrate the good performance of our method in both variable selection and prediction. We applied the proposed method to an American Cancer Society breast cancer survivor dataset. The findings are clinically meaningful and may help design intervention programs to improve the qualify of life for breast cancer survivors. PMID:25257196

Agreement between clinical estimation and a new quantitative analysis by Photoshop software in fundus and angiographic image variables.

PubMed

Ramezani, Alireza; Ahmadieh, Hamid; Azarmina, Mohsen; Soheilian, Masoud; Dehghan, Mohammad H; Mohebbi, Mohammad R

2009-12-01

To evaluate the validity of a new method for the quantitative analysis of fundus or angiographic images using Photoshop 7.0 (Adobe, USA) software by comparing with clinical evaluation. Four hundred and eighteen fundus and angiographic images of diabetic patients were evaluated by three retina specialists and then by computing using Photoshop 7.0 software. Four variables were selected for comparison: amount of hard exudates (HE) on color pictures, amount of HE on red-free pictures, severity of leakage, and the size of the foveal avascular zone (FAZ). The coefficient of agreement (Kappa) between the two methods in the amount of HE on color and red-free photographs were 85% (0.69) and 79% (0.59), respectively. The agreement for severity of leakage was 72% (0.46). In the two methods for the evaluation of the FAZ size using the magic and lasso software tools, the agreement was 54% (0.09) and 89% (0.77), respectively. Agreement in the estimation of the FAZ size by the lasso magnetic tool was excellent and was almost as good in the quantification of HE on color and on red-free images. Considering the agreement of this new technique for the measurement of variables in fundus images using Photoshop software with the clinical evaluation, this method seems to have sufficient validity to be used for the quantitative analysis of HE, leakage, and FAZ size on the angiograms of diabetic patients.

Harmonization of blood-based indicators of iron status: making the hard work matter.

PubMed

Hoofnagle, Andrew N

2017-12-01

Blood-based indicators that are used in the assessment of iron status are assumed to be accurate. In practice, inaccuracies in these measurements exist and stem from bias and variability. For example, the analytic variability of serum ferritin measurements across laboratories is very high (>15%), which increases the rate of misclassification in clinical and epidemiologic studies. The procedures that are used in laboratory medicine to minimize bias and variability could be used effectively in clinical research studies, particularly in the evaluation of iron deficiency and its associated anemia in pregnancy and early childhood and in characterizing states of iron repletion and excess. The harmonization and standardization of traditional and novel bioindicators of iron status will allow results from clinical studies to be more meaningfully translated into clinical practice by providing a firm foundation for clinical laboratories to set appropriate cutoffs. In addition, proficiency testing monitors the performance of the methods over time. It is important that measures of iron status be evaluated, validated, and performed in a manner that is consistent with standard procedures in laboratory medicine. © 2017 American Society for Nutrition.

Management of rheumatoid arthritis in Spain (emAR II). Clinical characteristics of the patients.

PubMed

Maese, Jesús; García De Yébenes, María Jesús; Carmona, Loreto; Hernández-García, Cesar

2012-01-01

There is a wide variability in the diagnostic and therapeutic methods in rheumatoid arthritis (AR) in Spain, according to prior studies. The quality of care could benefit from the application of appropriate clinical practice standards; we present a study on the variability of clinical practice. Descriptive review of clinical records (CR) of patients aged 16 or older diagnosed with RA, selected by stratified sampling of the Autonomous Communities in two stages per Hospital Center and patient. Collected analysis of sociodemographic data, evolution, follow-up, joint count, reactants, function, job history, Visual Analogue Scales (VAS) and other. We obtained valid information of 1,272 RA patients. The ESR, CRP and rheumatoid factor (RF) were regularly used parameters. The percentages of missing data in tender (TJN) and swollen (SJN) joint counts were 8.2% and 9.6% respectively; regarding the VAS we found 53.6% (patient), 59.1% (pain), and 72% in the physician VAS. Despite having clinical practice guidelines on RA, there still exists a significant variability in RA management in our country. Copyright © 2011 Elsevier España, S.L. All rights reserved.

Financial Management of a Large Multi-site Randomized Clinical Trial

PubMed Central

Sheffet, Alice J.; Flaxman, Linda; Tom, MeeLee; Hughes, Susan E.; Longbottom, Mary E.; Howard, Virginia J.; Marler, John R.; Brott, Thomas G.

2014-01-01

Background The Carotid Revascularization Endarterectomy versus Stenting Trial (CREST) received five years’ funding ($21,112,866) from the National Institutes of Health to compare carotid stenting to surgery for stroke prevention in 2,500 randomized participants at 40 sites. Aims Herein we evaluate the change in the CREST budget from a fixed to variable-cost model and recommend strategies for the financial management of large-scale clinical trials. Methods Projections of the original grant’s fixed-cost model were compared to the actual costs of the revised variable-cost model. The original grant’s fixed-cost budget included salaries, fringe benefits, and other direct and indirect costs. For the variable-cost model, the costs were actual payments to the clinical sites and core centers based upon actual trial enrollment. We compared annual direct and indirect costs and per-patient cost for both the fixed and variable models. Differences between clinical site and core center expenditures were also calculated. Results Using a variable-cost budget for clinical sites, funding was extended by no-cost extension from five to eight years. Randomizing sites tripled from 34 to 109. Of the 2,500 targeted sample size, 138 (5.5%) were randomized during the first five years and 1,387 (55.5%) during the no-cost extension. The actual per-patient costs of the variable model were 9% ($13,845) of the projected per-patient costs ($152,992) of the fixed model. Conclusions Performance-based budgets conserve funding, promote compliance, and allow for additional sites at modest additional cost. Costs of large-scale clinical trials can thus be reduced through effective management without compromising scientific integrity. PMID:24661748

Beat to beat variability in cardiovascular variables: noise or music?

NASA Technical Reports Server (NTRS)

Appel, M. L.; Berger, R. D.; Saul, J. P.; Smith, J. M.; Cohen, R. J.

1989-01-01

Cardiovascular variables such as heart rate, arterial blood pressure, stroke volume and the shape of electrocardiographic complexes all fluctuate on a beat to beat basis. These fluctuations have traditionally been ignored or, at best, treated as noise to be averaged out. The variability in cardiovascular signals reflects the homeodynamic interplay between perturbations to cardiovascular function and the dynamic response of the cardiovascular regulatory systems. Modern signal processing techniques provide a means of analyzing beat to beat fluctuations in cardiovascular signals, so as to permit a quantitative, noninvasive or minimally invasive method of assessing closed loop hemodynamic regulation and cardiac electrical stability. This method promises to provide a new approach to the clinical diagnosis and management of alterations in cardiovascular regulation and stability.

Considerations of multiple imputation approaches for handling missing data in clinical trials.

PubMed

Quan, Hui; Qi, Li; Luo, Xiaodong; Darchy, Loic

2018-07-01

Missing data exist in all clinical trials and missing data issue is a very serious issue in terms of the interpretability of the trial results. There is no universally applicable solution for all missing data problems. Methods used for handling missing data issue depend on the circumstances particularly the assumptions on missing data mechanisms. In recent years, if the missing at random mechanism cannot be assumed, conservative approaches such as the control-based and returning to baseline multiple imputation approaches are applied for dealing with the missing data issues. In this paper, we focus on the variability in data analysis of these approaches. As demonstrated by examples, the choice of the variability can impact the conclusion of the analysis. Besides the methods for continuous endpoints, we also discuss methods for binary and time to event endpoints as well as consideration for non-inferiority assessment. Copyright © 2018. Published by Elsevier Inc.

Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society.

PubMed

Sassi, Roberto; Cerutti, Sergio; Lombardi, Federico; Malik, Marek; Huikuri, Heikki V; Peng, Chung-Kang; Schmidt, Georg; Yamamoto, Yoshiharu

2015-09-01

Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a number of articles have been published to describe new HRV methodologies and their application in different physiological and clinical studies. This document presents a critical review of the new methods. A particular attention has been paid to methodologies that have not been reported in the 1996 standardization document but have been more recently tested in sufficiently sized populations. The following methods were considered: Long-range correlation and fractal analysis; Short-term complexity; Entropy and regularity; and Nonlinear dynamical systems and chaotic behaviour. For each of these methods, technical aspects, clinical achievements, and suggestions for clinical application were reviewed. While the novel approaches have contributed in the technical understanding of the signal character of HRV, their success in developing new clinical tools, such as those for the identification of high-risk patients, has been rather limited. Available results obtained in selected populations of patients by specialized laboratories are nevertheless of interest but new prospective studies are needed. The investigation of new parameters, descriptive of the complex regulation mechanisms of heart rate, has to be encouraged because not all information in the HRV signal is captured by traditional methods. The new technologies thus could provide after proper validation, additional physiological, and clinical meaning. Multidisciplinary dialogue and specialized courses in the combination of clinical cardiology and complex signal processing methods seem warranted for further advances in studies of cardiac oscillations and in the understanding normal and abnormal cardiac control processes. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

Recent developments in tissue-type imaging (TTI) for planning and monitoring treatment of prostate cancer.

PubMed

Feleppa, Ernest J; Porter, Christopher R; Ketterling, Jeffrey; Lee, Paul; Dasgupta, Shreedevi; Urban, Stella; Kalisz, Andrew

2004-07-01

Because current methods of imaging prostate cancer are inadequate, biopsies cannot be effectively guided and treatment cannot be effectively planned and targeted. Therefore, our research is aimed at ultrasonically characterizing cancerous prostate tissue so that we can image it more effectively and thereby provide improved means of detecting, treating and monitoring prostate cancer. We base our characterization methods on spectrum analysis of radiofrequency (rf) echo signals combined with clinical variables such as prostate-specific antigen (PSA). Tissue typing using these parameters is performed by artificial neural networks. We employed and evaluated different approaches to data partitioning into training, validation, and test sets and different neural network configuration options. In this manner, we sought to determine what neural network configuration is optimal for these data and also to assess possible bias that might exist due to correlations among different data entries among the data for a given patient. The classification efficacy of each neural network configuration and data-partitioning method was measured using relative-operating-characteristic (ROC) methods. Neural network classification based on spectral parameters combined with clinical data generally produced ROC-curve areas of 0.80 compared to curve areas of 0.64 for conventional transrectal ultrasound imaging combined with clinical data. We then used the optimal neural network configuration to generate lookup tables that translate local spectral parameter values and global clinical-variable values into pixel values in tissue-type images (TTIs). TTIs continue to show cancerous regions successfully, and may prove to be particularly useful clinically in combination with other ultrasonic and nonultrasonic methods, e.g., magnetic-resonance spectroscopy.

Recent Developments in Tissue-type Imaging(TTI) for Planning and Monitoring Treatment of Prostate Cancer

PubMed Central

Feleppa, Ernest J.; Porter, Christopher R.; Ketterling, Jeffrey; Lee, Paul; Dasgupta, Shreedevi; Urban, Stella; Kalisz, Andrew

2006-01-01

Because current methods of imaging prostate cancer are inadequate, biopsies cannot be effectively guided and treatment cannot be effectively planned and targeted. Therefore, our research is aimed at ultrasonically characterizing cancerous prostate tissue so that we can image it more effectively and thereby provide improved means of detecting, treating and monitoring prostate cancer. We base our characterization methods on spectrum analysis of radio frequency (rf) echo signals combined with clinical variables such as prostate-specific antigen (PSA). Tissue typing using these parameters is performed by artificial neural networks. We employedand evaluated different approaches to data partitioning into training, validation, and test sets and different neural network configuration options. In this manner, we sought to determine what neural network configuration is optimal for these data and also to assess possible bias that might exist due to correlations among different data entries among the data for a given patient. The classification efficacy of each neural network configuration and data-partitioning method was measured using relative-operating-characteristic (ROC) methods. Neural network classification based on spectral parameters combined with clinical data generally produced ROC-curve areas of 0.80 compared to curve areas of 0.64 for conventional transrectal ultrasound imaging combined with clinical data. We then used the optimal neural network configuration to generate lookup tables that translate local spectral parameter values and global clinical-variable values into pixel values in tissue-type images (TTIs). TTIs continue to show can cerous regions successfully, and may prove to be particularly useful clinically in combination with other ultrasonic and nonultrasonic methods, e.g., magnetic-resonance spectroscopy. PMID:15754797

Graphic tracings of condylar paths and measurements of condylar angles.

PubMed

el-Gheriani, A S; Winstanley, R B

1989-01-01

A study was carried out to determine the accuracy of different methods of measuring condylar inclination from graphical recordings of condylar paths. Thirty subjects made protrusive mandibular movements while condylar inclination was recorded on a graph paper card. A mandibular facebow and intraoral central bearing plate facilitated the procedure. The first method proved to be too variable to be of value in measuring condylar angles. The spline curve fitting technique was shown to be accurate, but its use clinically may prove complex. The mathematical method was more practical and overcame the variability of the tangent method. Other conclusions regarding condylar inclination are outlined.

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data

PubMed Central

Guinney, Justin; Wang, Tao; Laajala, Teemu D; Winner, Kimberly Kanigel; Bare, J Christopher; Neto, Elias Chaibub; Khan, Suleiman A; Peddinti, Gopal; Airola, Antti; Pahikkala, Tapio; Mirtti, Tuomas; Yu, Thomas; Bot, Brian M; Shen, Liji; Abdallah, Kald; Norman, Thea; Friend, Stephen; Stolovitzky, Gustavo; Soule, Howard; Sweeney, Christopher J; Ryan, Charles J; Scher, Howard I; Sartor, Oliver; Xie, Yang; Aittokallio, Tero; Zhou, Fang Liz; Costello, James C

2016-01-01

Summary Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest—namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial—ENTHUSE M1—in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39–4·62, p<0·0001; reference model: 2·56, 1·85–3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified predictive clinical variables and revealed aspartate aminotransferase as an important, albeit previously under-reported, prognostic biomarker. Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer. Funding Sanofi US Services, Project Data Sphere. PMID:27864015

Identifying a clinical signature of suicidality among patients with mood disorders: a pilot study using a machine learning approach

PubMed Central

Passos, Ives Cavalcante; Mwangi, Benson; Cao, Bo; Hamilton, Jane E; Wu, Mon-Ju; Zhang, Xiang Yang; Zunta-Soares, Giovana B.; Quevedo, Joao; Kauer-Sant'Anna, Marcia; Kapczinski, Flávio; Soares, Jair C.

2016-01-01

Objective A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to estimate the probability of an individual patient attempting suicide. Method A total of 144 patients with mood disorders were included. Clinical variables associated with suicide attempts among patients with mood disorders and demographic variables were used to ‘train’ a machine learning algorithm. The resulting algorithm was utilized in identifying novel or ‘unseen’ individual subjects as either suicide attempters or non-attempters. Three machine learning algorithms were implemented and evaluated. Results All algorithms distinguished individual suicide attempters from non-attempters with prediction accuracy ranging between 65%-72% (p<0.05). In particular, the relevance vector machine (RVM) algorithm correctly predicted 103 out of 144 subjects translating into 72% accuracy (72.1% sensitivity and 71.3% specificity) and an area under the curve of 0.77 (p<0.0001). The most relevant predictor variables in distinguishing attempters from non-attempters included previous hospitalizations for depression, a history of psychosis, cocaine dependence and post-traumatic stress disorder (PTSD) comorbidity. Conclusion Risk for suicide attempt among patients with mood disorders can be estimated at an individual subject level by incorporating both demographic and clinical variables. Future studies should examine the performance of this model in other populations and its subsequent utility in facilitating selection of interventions to prevent suicide. PMID:26773901

Comparison of Digital 12-Lead ECG and Digital 12-Lead Holter ECG Recordings in Healthy Male Subjects: Results from a Randomized, Double-Blinded, Placebo-Controlled Clinical Trial.

PubMed

Wang, Duolao; Bakhai, Ameet; Arezina, Radivoj; Täubel, Jörg

2016-11-01

Electrocardiogram (ECG) variability is greatly affected by the ECG recording method. This study aims to compare Holter and standard ECG recording methods in terms of central locations and variations of ECG data. We used the ECG data from a double-blinded, placebo-controlled, randomized clinical trial and used a mixed model approach to assess the agreement between two methods in central locations and variations of eight ECG parameters (Heart Rate, PR, QRS, QT, RR, QTcB, QTcF, and QTcI intervals). A total of 34 heathy male subjects with mean age of 25.7 ± 4.78 years were randomized to receive either active drug or placebo. Digital 12-lead ECG and digital 12-lead Holter ECG recordings were performed to assess ECG variability. There are no significant differences in least square mean between the Holter and the standard method for all ECG parameters. The total variance is consistently higher for the Holter method than the standard method for all ECG parameters except for QRS. The intraclass correlation coefficient (ICC) values for the Holter method are consistently lower than those for the standard method for all ECG parameters except for QRS, in particular, the ICC for QTcF is reduced from 0.86 for the standard method to 0.67 for the Holter method. This study suggests that Holter ECGs recorded in a controlled environment are not significantly different but more variable than those from the standard method. © 2016 Wiley Periodicals, Inc.

Missing data and multiple imputation in clinical epidemiological research.

PubMed

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data.

Missing data and multiple imputation in clinical epidemiological research

PubMed Central

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data. PMID:28352203

Evaluation of direct-to-consumer low-volume lab tests in healthy adults

PubMed Central

Kidd, Brian A.; Hoffman, Gabriel; Zimmerman, Noah; Li, Li; Morgan, Joseph W.; Glowe, Patricia K.; Botwin, Gregory J.; Parekh, Samir; Babic, Nikolina; Doust, Matthew W.; Stock, Gregory B.; Schadt, Eric E.; Dudley, Joel T.

2016-01-01

BACKGROUND. Clinical laboratory tests are now being prescribed and made directly available to consumers through retail outlets in the USA. Concerns with these test have been raised regarding the uncertainty of testing methods used in these venues and a lack of open, scientific validation of the technical accuracy and clinical equivalency of results obtained through these services. METHODS. We conducted a cohort study of 60 healthy adults to compare the uncertainty and accuracy in 22 common clinical lab tests between one company offering blood tests obtained from finger prick (Theranos) and 2 major clinical testing services that require standard venipuncture draws (Quest and LabCorp). Samples were collected in Phoenix, Arizona, at an ambulatory clinic and at retail outlets with point-of-care services. RESULTS. Theranos flagged tests outside their normal range 1.6× more often than other testing services (P < 0.0001). Of the 22 lab measurements evaluated, 15 (68%) showed significant interservice variability (P < 0.002). We found nonequivalent lipid panel test results between Theranos and other clinical services. Variability in testing services, sample collection times, and subjects markedly influenced lab results. CONCLUSION. While laboratory practice standards exist to control this variability, the disparities between testing services we observed could potentially alter clinical interpretation and health care utilization. Greater transparency and evaluation of testing technologies would increase their utility in personalized health management. FUNDING. This work was supported by the Icahn Institute for Genomics and Multiscale Biology, a gift from the Harris Family Charitable Foundation (to J.T. Dudley), and grants from the NIH (R01 DK098242 and U54 CA189201, to J.T. Dudley, and R01 AG046170 and U01 AI111598, to E.E. Schadt). PMID:27018593

Clustering of samples and variables with mixed-type data

PubMed Central

Edelmann, Dominic; Kopp-Schneider, Annette

2017-01-01

Analysis of data measured on different scales is a relevant challenge. Biomedical studies often focus on high-throughput datasets of, e.g., quantitative measurements. However, the need for integration of other features possibly measured on different scales, e.g. clinical or cytogenetic factors, becomes increasingly important. The analysis results (e.g. a selection of relevant genes) are then visualized, while adding further information, like clinical factors, on top. However, a more integrative approach is desirable, where all available data are analyzed jointly, and where also in the visualization different data sources are combined in a more natural way. Here we specifically target integrative visualization and present a heatmap-style graphic display. To this end, we develop and explore methods for clustering mixed-type data, with special focus on clustering variables. Clustering of variables does not receive as much attention in the literature as does clustering of samples. We extend the variables clustering methodology by two new approaches, one based on the combination of different association measures and the other on distance correlation. With simulation studies we evaluate and compare different clustering strategies. Applying specific methods for mixed-type data proves to be comparable and in many cases beneficial as compared to standard approaches applied to corresponding quantitative or binarized data. Our two novel approaches for mixed-type variables show similar or better performance than the existing methods ClustOfVar and bias-corrected mutual information. Further, in contrast to ClustOfVar, our methods provide dissimilarity matrices, which is an advantage, especially for the purpose of visualization. Real data examples aim to give an impression of various kinds of potential applications for the integrative heatmap and other graphical displays based on dissimilarity matrices. We demonstrate that the presented integrative heatmap provides more information than common data displays about the relationship among variables and samples. The described clustering and visualization methods are implemented in our R package CluMix available from https://cran.r-project.org/web/packages/CluMix. PMID:29182671

[Predictive ability of clinical parameters of bacteremia in hemodialysed patients].

PubMed

Egea, Ana L; Vilaró, Mario; De la Fuente, Jorge; Cuestas, Eduardo; Bongiovanni, María E

2012-01-01

No clinical events to differentiate bacteteremia from other pathologies in hemodialysis patients therefore the physicians makes diagnosis and treatment decisions based on clinical evidence an local epidemiology. the aim of this work was to study the frequency of microorganism isolated from blood culture of hemodialysis patients with suspected bacteraemia and evaluate Sensitivity (S) and Specificity (E) of medical diagnostic orientation in this cases of suspected Materials and methods: we performed an observational and prospective study for one year in hemodialysis patient with suspected bacteremia. We evaluated blood pressure, temperature (Tº), altered conscious state (AEC), respiratory frequency (FR), chills (ESC),diarrhea (DIARR), blood culture results and microbiological identification. We work with the mean ± standar desviation for continuous variables and frequencies for categorical variables We analyzed S, E, negative predictive value (VPN), positive predictive value (VPP) RESULTADOS: a total of 87 events with suspected bacteremia 34 (39%) were confirmed with positive blood culture the most common microorganisms were cocci Gram positive (CGP) 65%, Most relevant clinical variables were PCP ≥ 2 (VPN 81%), Tº ≥ 38 (VPN 76%) and AEC (E 98% y VPP 80%). CGP were the most prevalent microorganisms None of the clinical variables shows high S and E indicating low usefulness as a predictive tool of bacteremia Excepting AEC with E98% and VPP 80% but it would be necessary to evaluate this variable with a more number patient. Results justify to routine HC use like diagnostic tool.

Virology, Immunology, and Clinical Course of HIV Infection.

ERIC Educational Resources Information Center

McCutchan, J. Allen

1990-01-01

Presents overview of medical aspects of human immunodeficiency virus Type 1 (HIV-1) disease. Addresses structure and replication of virus, current methods for detecting HIV-1 in infected persons, effects of the virus on immune system, and clinical course of HIV-1 disease. Emphasizes variable causes of progression through HIV-1 infection stages;…

Application of lean methods improves surgical clinic experience.

PubMed

Waldhausen, John H T; Avansino, Jeffrey R; Libby, Arlene; Sawin, Robert S

2010-07-01

A quality visit in high volume surgery clinics is challenging. There is variability in numbers of patients seen and care provider behavior. Documentation, regulatory and compliance issues and computerization of patient care systems may decrease clinic efficiency and throughput. We tried to reduce variability and improve patient experience. Baseline data included: patients seen, time in exam rooms, and spent with providers, and patient satisfaction surveys. Two Rapid Process Improvement Workshops (RPIWs) were conducted to apply lean methods. 5S techniques helped standardize exam rooms. Similar data were collected at 30 days, 60 days, and 1 year. Satisfaction surveys were followed at 6 months and 1 year. Median pre-RPIW room time was 49 minutes. Post-RPIW times were 33 minutes at 30 days, 41 minutes at 60 days, and 42 minutes at 1 year. Face to face provider-patient time increased 30% to 61% at 30 days, 58% at 60 days, and 59% at 1 year. The median number of patients in a 4-hour clinic increased from 10 to 12. Satisfaction survey Problem Scores improved and were sustained. Lean methodology may be used to improve clinic efficiency as well as patient and staff's experience. Copyright 2010. Published by Elsevier Inc.

Time series analysis as input for clinical predictive modeling: modeling cardiac arrest in a pediatric ICU.

PubMed

Kennedy, Curtis E; Turley, James P

2011-10-24

Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1) selecting candidate variables; 2) specifying measurement parameters; 3) defining data format; 4) defining time window duration and resolution; 5) calculating latent variables for candidate variables not directly measured; 6) calculating time series features as latent variables; 7) creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8) reducing the number of candidate features; 9) training models for various data subsets; and 10) measuring model performance characteristics in unseen data to estimate their external validity. We have proposed a ten step process that results in data sets that contain time series features and are suitable for predictive modeling by a number of methods. We illustrated the process through an example of cardiac arrest prediction in a pediatric intensive care setting.

Prediction of Methotrexate Clinical Response in Portuguese Rheumatoid Arthritis Patients: Implication of MTHFR rs1801133 and ATIC rs4673993 Polymorphisms

PubMed Central

Lima, Aurea; Monteiro, Joaquim; Bernardes, Miguel; Sousa, Hugo; Azevedo, Rita; Seabra, Vitor; Medeiros, Rui

2014-01-01

Objective. Methotrexate (MTX), the most used drug in rheumatoid arthritis (RA) treatment, showing variability in clinical response, is often associated with genetic polymorphisms. This study aimed to elucidate the role of methylenetetrahydrofolate reductase (MTHFR) C677T and aminoimidazole carboxamide adenosine ribonucleotide transformylase (ATIC) T675C polymorphisms and clinicopathological variables in clinical response to MTX in Portuguese RA patients. Methods. Study included 233 RA patients treated with MTX for at least six months. MTHFR C677T and ATIC T675C polymorphisms were genotyped and clinicopathological variables were collected. Statistical analyses were performed and binary logistic regression method adjusted to possible confounding variables. Results. Multivariate analyses demonstrated that MTHFR 677TT (OR = 4.63; P = 0.013) and ATIC 675T carriers (OR = 5.16; P = 0.013) were associated with over 4-fold increased risk for nonresponse. For clinicopathological variables, noncurrent smokers (OR = 7.98; P = 0.001), patients positive to anti-cyclic citrullinated peptide (OR = 3.53; P = 0.004) and antinuclear antibodies (OR = 2.28; P = 0.045), with higher health assessment questionnaire score (OR = 2.42; P = 0.007), and nonsteroidal anti-inflammatory drug users (OR = 2.77; P = 0.018) were also associated with nonresponse. Contrarily, subcutaneous administration route (OR = 0.11; P < 0.001) was associated with response. Conclusion. Our study suggests that MTHFR C677T and ATIC T675C genotyping combined with clinicopathological data may help to identify patients whom will not benefit from MTX treatment and, therefore, assist clinicians in personalizing RA treatment. PMID:24967362

Episiotomy and its relationship to various clinical variables that influence its performance

PubMed Central

Ballesteros-Meseguer, Carmen; Carrillo-García, César; Meseguer-de-Pedro, Mariano; Canteras-Jordana, Manuel; Martínez-Roche, Mª Emilia

2016-01-01

Objective: to understand the episiotomy rate and its relationship with various clinical variables. Method: a descriptive, cross-sectional, analytic study of 12,093 births in a tertiary hospital. Variables: Parity, gestational age, start of labor, use of epidural analgesia, oxytocin usage, position during fetal explusion, weight of neonate, and completion of birth. The analysis was performed with SPSS 19.0. Results: the global percentage of episiotomies was 50%. The clinical variables that presented a significant association were primiparity (RR=2.98), gestational age >41 weeks (RR=1.2), augmented or induced labor (RR=1.33), epidural analgesia use (RR=1,95), oxytocin use (RR=1.58), lithotomy position during fetal expulsion (RR=6.4), and instrumentation (RR=1.84). Furthermore, maternal age ≥35 years (RR=0.85) and neonatal weight <2500 g (RR=0.8) were associated with a lower incidence of episiotomy. Conclusions: episiotomy is dependent on obstetric interventions performed during labor. If we wish to reduce the episiotomy rate, it will be necessary to bear in mind these risk factors when establishing policies for reducing this procedure. PMID:27224064

Meaning and challenges in the practice of multiple therapeutic massage modalities: a combined methods study.

PubMed

Porcino, Antony J; Boon, Heather S; Page, Stacey A; Verhoef, Marja J

2011-09-20

Therapeutic massage and bodywork (TMB) practitioners are predominantly trained in programs that are not uniformly standardized, and in variable combinations of therapies. To date no studies have explored this variability in training and how this affects clinical practice. Combined methods, consisting of a quantitative, population-based survey and qualitative interviews with practitioners trained in multiple therapies, were used to explore the training and practice of TMB practitioners in Alberta, Canada. Of the 5242 distributed surveys, 791 were returned (15.1%). Practitioners were predominantly female (91.7%), worked in a range of environments, primarily private (44.4%) and home clinics (35.4%), and were not significantly different from other surveyed massage therapist populations. Seventy-seven distinct TMB therapies were identified. Most practitioners were trained in two or more therapies (94.4%), with a median of 8 and range of 40 therapies. Training programs varied widely in number and type of TMB components, training length, or both. Nineteen interviews were conducted. Participants described highly variable training backgrounds, resulting in practitioners learning unique combinations of therapy techniques. All practitioners reported providing individualized patient treatment based on a responsive feedback process throughout practice that they described as being critical to appropriately address the needs of patients. They also felt that research treatment protocols were different from clinical practice because researchers do not usually sufficiently acknowledge the individualized nature of TMB care provision. The training received, the number of therapies trained in, and the practice descriptors of TMB practitioners are all highly variable. In addition, clinical experience and continuing education may further alter or enhance treatment techniques. Practitioners individualize each patient's treatment through a highly adaptive process. Therefore, treatment provision is likely unique to each practitioner. These results may be of interest to researchers considering similar practice issues in other professions. The use of a combined-methods design effectively captured this complexity of TMB practice. TMB research needs to consider research approaches that can capture or adapt to the individualized nature of practice.

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

PubMed

Guinney, Justin; Wang, Tao; Laajala, Teemu D; Winner, Kimberly Kanigel; Bare, J Christopher; Neto, Elias Chaibub; Khan, Suleiman A; Peddinti, Gopal; Airola, Antti; Pahikkala, Tapio; Mirtti, Tuomas; Yu, Thomas; Bot, Brian M; Shen, Liji; Abdallah, Kald; Norman, Thea; Friend, Stephen; Stolovitzky, Gustavo; Soule, Howard; Sweeney, Christopher J; Ryan, Charles J; Scher, Howard I; Sartor, Oliver; Xie, Yang; Aittokallio, Tero; Zhou, Fang Liz; Costello, James C

2017-01-01

Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39-4·62, p<0·0001; reference model: 2·56, 1·85-3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified predictive clinical variables and revealed aspartate aminotransferase as an important, albeit previously under-reported, prognostic biomarker. Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer. Sanofi US Services, Project Data Sphere. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Clinical reasoning in undergraduate nursing education: a scoping review].

PubMed

Menezes, Sáskia Sampaio Cipriano de; Corrêa, Consuelo Garcia; Silva, Rita de Cássia Gengo E; Cruz, Diná de Almeida Monteiro Lopes da

2015-12-01

This study aimed at analyzing the current state of knowledge on clinical reasoning in undergraduate nursing education. A systematic scoping review through a search strategy applied to the MEDLINE database, and an analysis of the material recovered by extracting data done by two independent reviewers. The extracted data were analyzed and synthesized in a narrative manner. From the 1380 citations retrieved in the search, 23 were kept for review and their contents were summarized into five categories: 1) the experience of developing critical thinking/clinical reasoning/decision-making process; 2) teaching strategies related to the development of critical thinking/clinical reasoning/decision-making process; 3) measurement of variables related to the critical thinking/clinical reasoning/decision-making process; 4) relationship of variables involved in the critical thinking/clinical reasoning/decision-making process; and 5) theoretical development models of critical thinking/clinical reasoning/decision-making process for students. The biggest challenge for developing knowledge on teaching clinical reasoning seems to be finding consistency between theoretical perspectives on the development of clinical reasoning and methodologies, methods, and procedures in research initiatives in this field.

Using a handbook to improve nurses' continence care.

PubMed

Williams, K; Roe, B; Sindhu, F

Nursing care should be based on sound research evidence with demonstrated clinical effectiveness. Dissemination of this research evidence is, therefore, of paramount importance. A study using focus groups was undertaken during 1993-1994 to evaluate the dissemination of a clinical handbook for continence care to qualified nurses, in relation to reported nursing practice in care of the elderly wards/units in one health authority. A total of 124 nurses participated in the study and 98 variables were included. Improvements were recorded in nurses' responses between the pre-test and post-test for 84 (86 per cent) variables in the experimental group and 58 (59 per cent) in the control group. This demonstrates the positive value of the clinical handbook as a method of disseminating research evidence.

Bayesian imperfect information analysis for clinical recurrent data

PubMed Central

Chang, Chih-Kuang; Chang, Chi-Chang

2015-01-01

In medical research, clinical practice must often be undertaken with imperfect information from limited resources. This study applied Bayesian imperfect information-value analysis to realistic situations to produce likelihood functions and posterior distributions, to a clinical decision-making problem for recurrent events. In this study, three kinds of failure models are considered, and our methods illustrated with an analysis of imperfect information from a trial of immunotherapy in the treatment of chronic granulomatous disease. In addition, we present evidence toward a better understanding of the differing behaviors along with concomitant variables. Based on the results of simulations, the imperfect information value of the concomitant variables was evaluated and different realistic situations were compared to see which could yield more accurate results for medical decision-making. PMID:25565853

Gender Differences in Treatment-Seeking British Pathological Gamblers

PubMed Central

Ronzitti, Silvia; Lutri, Vittorio; Smith, Neil; Clerici, Massimo; Bowden-Jones, Henrietta

2016-01-01

Background and aim Gambling is a widespread recreational activity in the UK. A significant percentage of gamblers develop subclinical or clinically relevant problem gambling issues, but only a low percentage of them seek treatment. Although characteristics of pathological gamblers from treatment-seeking population have been examined in some research, only a few studies have explored the differences between females and males. This study aimed to examine the gender-related differences in demographics, gambling measures, and clinical variables in an outpatient sample of pathological gamblers seeking treatment. Methods A total of 1,178 treatment-seeking individuals with gambling disorder were assessed at the National Problem Gambling Clinic in London. Sociodemographic characteristics, clinical variables, and gambling behavior habits were obtained during the assessment evaluation. Of the total sample, 92.5% were males and 7.5% were females. Results Males were more likely to be younger, white, and employed than females. In addition, compared to women, men showed a lower PGSI score, an earlier age of onset of gambling behavior, a higher gambling involvement, and preferred specific forms gambling. Female gamblers were more anxious and depressed, while men were more likely to use alcohol and illicit drugs. Conclusions Our findings support the importance of gender differences in a treatment-seeking population of pathological gamblers both in sociodemographic characteristics, gambling behavior variables, and clinical variables. Males and females might benefit from group-specific treatment. PMID:27348561

A nomograph method for assessing body weight.

PubMed

Thomas, A E; McKay, D A; Cutlip, M B

1976-03-01

The ratio of weight/height emerges from varied epidemiological studies as the most generally useful index of relative body mass in adults. The authors present a nomograph to facilitate use of this relationship in clinical situations. While showing the range of weight given as desirable in life insurance studies, the scale expresses relative weight as a continuous variable. This method encourages use of clinical judgment in interpreting "overweight" and "underweight" and in accounting for muscular and skeletal contributions to measured mass.

Nursing Home Spending Patterns in the 1990s: The Role of Nursing Home Competition and Excess Demand

PubMed Central

Mukamel, Dana B; Spector, William D; Bajorska, Alina

2005-01-01

Objective To examine nursing home expenditures on clinical, hotel, and administrative activities during the 1990s and to determine the association between nursing home competition and excess demand on expenditures. Data Sources/Study Setting Secondary data sources for 1991, 1996, and 1999 for 500 free-standing nursing homes in New York State. Study Design A retrospective statistical analysis of nursing homes' expenditures. The dependent variables were clinical, hotel, and administrative costs in each year. Independent variables included outputs (inpatient and outpatient), wages, ownership, New York City location, and measures of competition and excess demand. Data Collection/Extraction Method Variables were constructed from annual financial reports submitted by the nursing homes, the Patient Review Instrument and Medicare enrollment data. Principal Findings Clinical and administrative costs have increased over the decade, while hotel expenditures have declined. Increased competition was associated with higher clinical and administrative costs while excess demand was associated with lower clinical and hotel expenditures. Conclusions Nursing home expenditures are sensitive to competition and excess demand conditions. Policies that influence competition in nursing home markets are therefore likely to have an impact on expenditures as well. PMID:16033491

A Tutorial on Multiblock Discriminant Correspondence Analysis (MUDICA): A New Method for Analyzing Discourse Data from Clinical Populations

ERIC Educational Resources Information Center

Williams, Lynne J.; Abdi, Herve; French, Rebecca; Orange, Joseph B.

2010-01-01

Purpose: In communication disorders research, clinical groups are frequently described based on patterns of performance, but researchers often study only a few participants described by many quantitative and qualitative variables. These data are difficult to handle with standard inferential tools (e.g., analysis of variance or factor analysis)…

Delayed Auditory Feedback in the Treatment of Stuttering: Clients as Consumers

ERIC Educational Resources Information Center

Van Borsel, John; Reunes, Gert; Van den Bergh, Nathalie

2003-01-01

Purpose: To investigate the effect of repeated exposure to delayed auditory feedback (DAF) during a 3-month period outside a clinical environment and with only minimal clinical guidance on speech fluency in people who stutter. Method: A pretest-post-test design was used with repeated exposure to DAF during 3 months as the independent variable.…

Communication of mechanically ventilated patients in intensive care units

PubMed Central

Martinho, Carina Isabel Ferreira; Rodrigues, Inês Tello Rato Milheiras

2016-01-01

Objective The aim of this study was to translate and culturally and linguistically adapt the Ease of Communication Scale and to assess the level of communication difficulties for patients undergoing mechanical ventilation with orotracheal intubation, relating these difficulties to clinical and sociodemographic variables. Methods This study had three stages: (1) cultural and linguistic adaptation of the Ease of Communication Scale; (2) preliminary assessment of its psychometric properties; and (3) observational, descriptive-correlational and cross-sectional study, conducted from March to August 2015, based on the Ease of Communication Scale - after extubation answers and clinical and sociodemographic variables of 31 adult patients who were extubated, clinically stable and admitted to five Portuguese intensive care units. Results Expert analysis showed high agreement on content (100%) and relevance (75%). The pretest scores showed a high acceptability regarding the completion of the instrument and its usefulness. The Ease of Communication Scale showed excellent internal consistency (0.951 Cronbach's alpha). The factor analysis explained approximately 81% of the total variance with two scale components. On average, the patients considered the communication experiences during intubation to be "quite hard" (2.99). No significant correlation was observed between the communication difficulties reported and the studied sociodemographic and clinical variables, except for the clinical variable "number of hours after extubation" (p < 0.05). Conclusion This study translated and adapted the first assessment instrument of communication difficulties for mechanically ventilated patients in intensive care units into European Portuguese. The preliminary scale validation suggested high reliability. Patients undergoing mechanical ventilation reported that communication during intubation was "quite hard", and these communication difficulties apparently existed regardless of the presence of other clinical and/or sociodemographic variables. PMID:27410408

PROGNOSTIC SIGNIFICANCE OF CLINICAL, HISTOPATHOLOGICAL, AND MOLECULAR CHARACTERISTICS OF MEDULLOBLASTOMAS IN THE PROSPECTIVE HIT2000 MULTICENTER CLINICAL TRIAL COHORT

PubMed Central

Pietsch, Torsten; Schmidt, Rene; Remke, Marc; Korshunov, Andrey; Hovestadt, Volker; Jones, David TW; Felsberg, Jörg; Kaulich, Kerstin; Goschzik, Tobias; Kool, Marcel; Northcott, Paul A.; von Hoff, Katja; von Bueren, André O.; Friedrich, Carsten; Skladny, Heyko; Fleischhack, Gudrun; Taylor, Michael D.; Cremer, Friedrich; Lichter, Peter; Faldum, Andreas; Reifenberger, Guido; Rutkowski, Stefan; Pfister, Stefan M.

2014-01-01

BACKGROUND: This study aimed to prospectively evaluate clinical, histopathological and molecular variables for outcome prediction in medulloblastoma patients. METHODS: Patients from the HIT2000 cooperative clinical trial were prospectively enrolled based on the availability of sufficient tumor material and complete clinical information. This revealed a cohort of 184 patients (median age 7.6 years), which was randomly split at a 2:1 ratio into a training (n = 127), and a validation (n = 57) dataset. All samples were subjected to thorough histopathological investigation, CTNNB1 mutation analysis, quantitative PCR, MLPA and FISH analyses for cytogenetic variables, and methylome analysis. RESULTS: By univariable analysis, clinical factors (M-stage), histopathological variables (large cell component, endothelial proliferation, synaptophysin pattern), and molecular features (chromosome 6q status, MYC amplification, TOP2A copy-number, subgrouping) were found to be prognostic. Molecular consensus subgrouping (WNT, SHH, Group 3, Group 4) was validated as an independent feature to stratify patients into different risk groups. When comparing methods for the identification of WNT-driven medulloblastoma, this study identified CTNNB1 sequencing and methylation profiling to most reliably identify these patients. After removing patients with particularly favorable (CTNNB1 mutation, extensive nodularity) or unfavorable (MYC amplification) markers, a risk score for the remaining “intermediate molecular risk” population dependent on age, M-stage, pattern of synaptophysin expression, and MYCN copy-number status was identified and validated, with speckled synaptophysin expression indicating worse outcome. CONCLUSIONS: Methylation subgrouping and CTNNB1 mutation status represent robust tools for the risk-stratification of medulloblastoma. A simple clinico-pathological risk score for “intermediate molecular risk” patients was identified, which deserves further validation. SECONDARY CATEGORY: Pediatrics.

Epidemiologic research using probabilistic outcome definitions.

PubMed

Cai, Bing; Hennessy, Sean; Lo Re, Vincent; Small, Dylan S

2015-01-01

Epidemiologic studies using electronic healthcare data often define the presence or absence of binary clinical outcomes by using algorithms with imperfect specificity, sensitivity, and positive predictive value. This results in misclassification and bias in study results. We describe and evaluate a new method called probabilistic outcome definition (POD) that uses logistic regression to estimate the probability of a clinical outcome using multiple potential algorithms and then uses multiple imputation to make valid inferences about the risk ratio or other epidemiologic parameters of interest. We conducted a simulation to evaluate the performance of the POD method with two variables that can predict the true outcome and compared the POD method with the conventional method. The simulation results showed that when the true risk ratio is equal to 1.0 (null), the conventional method based on a binary outcome provides unbiased estimates. However, when the risk ratio is not equal to 1.0, the traditional method, either using one predictive variable or both predictive variables to define the outcome, is biased when the positive predictive value is <100%, and the bias is very severe when the sensitivity or positive predictive value is poor (less than 0.75 in our simulation). In contrast, the POD method provides unbiased estimates of the risk ratio both when this measure of effect is equal to 1.0 and not equal to 1.0. Even when the sensitivity and positive predictive value are low, the POD method continues to provide unbiased estimates of the risk ratio. The POD method provides an improved way to define outcomes in database research. This method has a major advantage over the conventional method in that it provided unbiased estimates of risk ratios and it is easy to use. Copyright © 2014 John Wiley & Sons, Ltd.

Development of a computerized assessment of clinician adherence to a treatment guideline for patients with bipolar disorder.

PubMed

Dennehy, Ellen B; Suppes, Trisha; John Rush, A; Lynn Crismon, M; Witte, B; Webster, J

2004-01-01

The adoption of treatment guidelines for complex psychiatric illness is increasing. Treatment decisions in psychiatry depend on a number of variables, including severity of symptoms, past treatment history, patient preferences, medication tolerability, and clinical response. While patient outcomes may be improved by the use of treatment guidelines, there is no agreed upon standard by which to assess the degree to which clinician behavior corresponds to those recommendations. This report presents a method to assess clinician adherence to the complex multidimensional treatment guideline for bipolar disorder utilized in the Texas Medication Algorithm Project. The steps involved in the development of this system are presented, including the reliance on standardized documentation, defining core variables of interest, selecting criteria for operationalization of those variables, and computerization of the assessment of adherence. The computerized assessment represents an improvement over other assessment methods, which have relied on laborious and costly chart reviews to extract clinical information and to analyze provider behavior. However, it is limited by the specificity of decisions that guided the adherence scoring process. Preliminary findings using this system with 2035 clinical visits conducted for the bipolar disorder module of TMAP Phase 3 are presented. These data indicate that this system of guideline adherence monitoring is feasible.

Dynamic TIMI Risk Score for STEMI

PubMed Central

Amin, Sameer T.; Morrow, David A.; Braunwald, Eugene; Sloan, Sarah; Contant, Charles; Murphy, Sabina; Antman, Elliott M.

2013-01-01

Background Although there are multiple methods of risk stratification for ST‐elevation myocardial infarction (STEMI), this study presents a prospectively validated method for reclassification of patients based on in‐hospital events. A dynamic risk score provides an initial risk stratification and reassessment at discharge. Methods and Results The dynamic TIMI risk score for STEMI was derived in ExTRACT‐TIMI 25 and validated in TRITON‐TIMI 38. Baseline variables were from the original TIMI risk score for STEMI. New variables were major clinical events occurring during the index hospitalization. Each variable was tested individually in a univariate Cox proportional hazards regression. Variables with P<0.05 were incorporated into a full multivariable Cox model to assess the risk of death at 1 year. Each variable was assigned an integer value based on the odds ratio, and the final score was the sum of these values. The dynamic score included the development of in‐hospital MI, arrhythmia, major bleed, stroke, congestive heart failure, recurrent ischemia, and renal failure. The C‐statistic produced by the dynamic score in the derivation database was 0.76, with a net reclassification improvement (NRI) of 0.33 (P<0.0001) from the inclusion of dynamic events to the original TIMI risk score. In the validation database, the C‐statistic was 0.81, with a NRI of 0.35 (P=0.01). Conclusions This score is a prospectively derived, validated means of estimating 1‐year mortality of STEMI at hospital discharge and can serve as a clinically useful tool. By incorporating events during the index hospitalization, it can better define risk and help to guide treatment decisions. PMID:23525425

Assessment of published models and prognostic variables in epithelial ovarian cancer at Mayo Clinic

PubMed Central

Hendrickson, Andrea Wahner; Hawthorne, Kieran M.; Goode, Ellen L.; Kalli, Kimberly R.; Goergen, Krista M.; Bakkum-Gamez, Jamie N.; Cliby, William A.; Keeney, Gary L.; Visscher, Dan W.; Tarabishy, Yaman; Oberg, Ann L.; Hartmann, Lynn C.; Maurer, Matthew J.

2015-01-01

Objectives Epithelial ovarian cancer (EOC) is an aggressive disease in which first line therapy consists of a surgical staging/debulking procedure and platinum based chemotherapy. There is significant interest in clinically applicable, easy to use prognostic tools to estimate risk of recurrence and overall survival. In this study we used a large prospectively collected cohort of women with EOC to validate currently published models and assess prognostic variables. Methods Women with invasive ovarian, peritoneal, or fallopian tube cancer diagnosed between 2000-2011 and prospectively enrolled into the Mayo Clinic Ovarian Cancer registry were identified. Demographics and known prognostic markers as well as epidemiologic exposure variables were abstracted from the medical record and collected via questionnaire. Six previously published models of overall and recurrence-free survival were assessed for external validity. In addition, predictors of outcome were assessed in our dataset. Results Previously published models validated with a range of c-statistics (0.587-0.827), though application of models containing variables not part of routine practice were somewhat limited by missing data; utilization of all applicable models and comparison of results is suggested. Examination of prognostic variables identified only the presence of ascites and ASA score to be independent predictors of prognosis in our dataset, albeit with marginal gain in prognostic information, after accounting for stage and debulking. Conclusions Existing prognostic models for newly diagnosed EOC showed acceptable calibration in our cohort for clinical application. However, modeling of prospective variables in our dataset reiterates that stage and debulking remain the most important predictors of prognosis in this setting. PMID:25620544

Mass Spectrometry and Multiplex Antigen Assays to Assess Microbial Quality and Toxin Production of Staphylococcus aureus Strains Isolated from Clinical and Food Samples

PubMed Central

Attien, Paul; Sina, Haziz; Moussaoui, Wardi; Zimmermann-Meisse, Gaëlle; Dadié, Thomas; Keller, Daniel; Riegel, Philippe; Edoh, Vincent; Kotchoni, Simeon O.; Djè, Marcellin; Prévost, Gilles

2014-01-01

The aim of our study was to investigate the microbial quality of meat products and on some clinical samples in Abidjan focused on Staphylococcus genus and the toxin production profile of Staphylococcus aureus (S. aureus) isolated. Bacteria were collected from 240 samples of three meat products sold in Abidjan and 180 samples issued from clinical infections. The strains were identified by both microbiological and MALDI-TOF-MS methods. The susceptibility to antibiotics was determined by the disc diffusion method. The production of Panton-Valentine Leukocidin, LukE/D, and epidermolysins was screened using radial gel immunodiffusion. The production of staphylococcal enterotoxins and TSST-1 was screened by a Bio-Plex Assay. We observed that 96/240 of meat samples and 32/180 of clinical samples were contaminated by Staphylococcus. Eleven species were isolated from meats and 4 from clinical samples. Forty-two S. aureus strains were isolated from ours samples. Variability of resistance was observed for most of the tested antibiotics but none of the strains displays a resistance to imipenem and quinolones. We observed that 89% of clinical S. aureus were resistant to methicillin against 58% for those issued from meat products. All S. aureus isolates issued from meat products produce epidermolysins whereas none of the clinical strains produced these toxins. The enterotoxins were variably produced by both clinical and meat product samples. PMID:24987686

Patient-Centered Research

PubMed Central

Wicki, J; Perneger, TV; Junod, AF; Bounameaux, H; Perrier, A

2000-01-01

PURPOSE We aimed to develop a simple standardized clinical score to stratify emergency ward patients with clinically suspected PE into groups with a high, intermediate, or low probability of PE, in order to improve and simplify the diagnostic approach. METHODS Analysis of a database of 1090 consecutive patients admitted to the emergency ward for suspected PE, in whom diagnosis of PE was ruled in or out by a standard diagnostic algorithm. Logistic regression was used to predict clinical parameters associated with PE. RESULTS 296 out of 1090 patients (27%) were found to have PE. The optimal estimate of clinical probability was based on eight variables: recent surgery, previous thromboembolic event, older age, hypocapnia, hypoxemia, tachycardia, band atelectasis or elevation of a hemidiaphragm on chest X-ray. A probability score was calculated by adding points assigned to these variables. A cut-off score of 4 best identified patients with low probability of PE. 486 patients (49%) had a low clinical probability of PE (score < 4), of which 50 (10.3%) had a proven PE. The prevalence of PE was 38% in the 437 patients with an intermediate probability (score 5–8, n = 437) and 81% in the 63 patients with a high probability (score>9). CONCLUSION This clinical score, based on easily available and objective variables, provides a standardized assessment of the clinical probability of PE. Applying this score to emergency ward patients suspected of PE could allow a more efficient diagnostic process.

Phase II cancer clinical trials for biomarker-guided treatments.

PubMed

Jung, Sin-Ho

2018-01-01

The design and analysis of cancer clinical trials with biomarker depend on various factors, such as the phase of trials, the type of biomarker, whether the used biomarker is validated or not, and the study objectives. In this article, we demonstrate the design and analysis of two Phase II cancer clinical trials, one with a predictive biomarker and the other with an imaging prognostic biomarker. Statistical testing methods and their sample size calculation methods are presented for each trial. We assume that the primary endpoint of these trials is a time to event variable, but this concept can be used for any type of endpoint.

Objective Evaluation of Vergence Disorders and a Research-Based Novel Method for Vergence Rehabilitation

PubMed Central

Kapoula, Zoï; Morize, Aurélien; Daniel, François; Jonqua, Fabienne; Orssaud, Christophe; Brémond-Gignac, Dominique

2016-01-01

Purpose We performed video-oculography to evaluate vergence eye movement abnormalities in students diagnosed clinically with vergence disorders. We tested the efficiency of a novel rehabilitation method and evaluated its benefits with video-oculography cross-correlated with clinical tests and symptomatology. Methods A total of 19 students (20–27 years old) underwent ophthalmologic, orthoptic examination, and a vergence test coupled with video-oculography. Eight patients were diagnosed with vergence disorders with a high symptomatology score (CISS) and performed a 5-week session of vergence rehabilitation. Vergence and rehabilitation tasks were performed with a trapezoid surface of light emitting diodes (LEDs) and adjacent buzzers (US 8851669). We used a novel Vergence double-step (Vd-s) protocol: the target stepped to a second position before the vergence movement completion. Afterward the vergence test was repeated 1 week and 1 month later. Results Abnormally increased intertrial variability was observed for many vergence parameters (gain, duration, and speed) for the subjects with vergence disorders. High CISS scores were correlated with variability and increased latency. After the Vd-s, variability of all parameters dropped to normal or better levels. Moreover, the convergence and divergence latency diminished significantly to levels better than normal; benefits were maintained 1 month after completion of Vd-s. CISS scores dropped to normal level, which was maintained up to 1 year. Conclusions and Translational Relevance: Intertrial variability is the major marker of vergence disorders. The Vd-s research-based method leads to normalization of vergence properties and lasting removal of symptoms. The efficiency of the method is due to the spatiotemporal parameters of repetitive trials that stimulate neural plasticity. PMID:26981330

Interpretation of correlations in clinical research.

PubMed

Hung, Man; Bounsanga, Jerry; Voss, Maren Wright

2017-11-01

Critically analyzing research is a key skill in evidence-based practice and requires knowledge of research methods, results interpretation, and applications, all of which rely on a foundation based in statistics. Evidence-based practice makes high demands on trained medical professionals to interpret an ever-expanding array of research evidence. As clinical training emphasizes medical care rather than statistics, it is useful to review the basics of statistical methods and what they mean for interpreting clinical studies. We reviewed the basic concepts of correlational associations, violations of normality, unobserved variable bias, sample size, and alpha inflation. The foundations of causal inference were discussed and sound statistical analyses were examined. We discuss four ways in which correlational analysis is misused, including causal inference overreach, over-reliance on significance, alpha inflation, and sample size bias. Recent published studies in the medical field provide evidence of causal assertion overreach drawn from correlational findings. The findings present a primer on the assumptions and nature of correlational methods of analysis and urge clinicians to exercise appropriate caution as they critically analyze the evidence before them and evaluate evidence that supports practice. Critically analyzing new evidence requires statistical knowledge in addition to clinical knowledge. Studies can overstate relationships, expressing causal assertions when only correlational evidence is available. Failure to account for the effect of sample size in the analyses tends to overstate the importance of predictive variables. It is important not to overemphasize the statistical significance without consideration of effect size and whether differences could be considered clinically meaningful.

Primary outcome indices in illicit drug dependence treatment research: systematic approach to selection and measurement of drug use end-points in clinical trials

PubMed Central

Donovan, Dennis M.; Bigelow, George E.; Brigham, Gregory S.; Carroll, Kathleen M.; Cohen, Allan J.; Gardin, John G.; Hamilton, John A.; Huestis, Marilyn A.; Hughes, John R.; Lindblad, Robert; Marlatt, G. Alan; Preston, Kenzie L.; Selzer, Jeffrey A.; Somoza, Eugene C.; Wakim, Paul G.; Wells, Elizabeth A.

2012-01-01

Aims Clinical trials test the safety and efficacy of behavioral and pharmacological interventions in drug-dependent individuals. However, there is no consensus about the most appropriate outcome(s) to consider in determining treatment efficacy or on the most appropriate methods for assessing selected outcome(s). We summarize the discussion and recommendations of treatment and research experts, convened by the US National Institute on Drug Abuse, to select appropriate primary outcomes for drug dependence treatment clinical trials, and in particular the feasibility of selecting a common outcome to be included in all or most trials. Methods A brief history of outcomes employed in prior drug dependence treatment research, incorporating perspectives from tobacco and alcohol research, is included. The relative merits and limitations of focusing on drug-taking behavior, as measured by self-report and qualitative or quantitative biological markers, are evaluated. Results Drug-taking behavior, measured ideally by a combination of self-report and biological indicators, is seen as the most appropriate proximal primary outcome in drug dependence treatment clinical trials. Conclusions We conclude that the most appropriate outcome will vary as a function of salient variables inherent in the clinical trial, such as the type of intervention, its target, treatment goals (e.g. abstinence or reduction of use) and the perspective being taken (e.g. researcher, clinical program, patient, society). It is recommended that a decision process, based on such trial variables, be developed to guide the selection of primary and secondary outcomes as well as the methods to assess them. PMID:21781202

Success Rate of Microimplants in a University Orthodontic Clinic

PubMed Central

Sharma, P.; Valiathan, A.; Sivakumar, A.

2011-01-01

Introduction. The purpose of this study was to examine the success rate and find factors affecting the clinical success of microimplants used as orthodontic anchorage. Methods. Seventy-three consecutive patients (25 male, 48 female; mean age, 22.45 years) with a total of 139 screw implants of 2 types were examined. Success rate was determined according to 18 clinical variables. Results. The overall success rate was 87.8%. The clinical variables of microimplant factors (type), patient factors (sex, skeletal and dental relationships, overbite, jaw involved, side involved and site involved), and treatment factors (type of insertion, time of loading, purpose of microimplant insertion, mode of loading, type of anchorage used, direction of forces applied) did not show any statistical difference in success rates. Mandibular angle, vertical position of implant placement, oral hygiene status, and inflammation showed significant difference in success rates. Conclusions. Proper case selection and following the recommended protocol are extremely essential to minimise failures. PMID:22084789

Variable selection in semiparametric cure models based on penalized likelihood, with application to breast cancer clinical trials.

PubMed

Liu, Xiang; Peng, Yingwei; Tu, Dongsheng; Liang, Hua

2012-10-30

Survival data with a sizable cure fraction are commonly encountered in cancer research. The semiparametric proportional hazards cure model has been recently used to analyze such data. As seen in the analysis of data from a breast cancer study, a variable selection approach is needed to identify important factors in predicting the cure status and risk of breast cancer recurrence. However, no specific variable selection method for the cure model is available. In this paper, we present a variable selection approach with penalized likelihood for the cure model. The estimation can be implemented easily by combining the computational methods for penalized logistic regression and the penalized Cox proportional hazards models with the expectation-maximization algorithm. We illustrate the proposed approach on data from a breast cancer study. We conducted Monte Carlo simulations to evaluate the performance of the proposed method. We used and compared different penalty functions in the simulation studies. Copyright © 2012 John Wiley & Sons, Ltd.

Variable selection in subdistribution hazard frailty models with competing risks data

PubMed Central

Do Ha, Il; Lee, Minjung; Oh, Seungyoung; Jeong, Jong-Hyeon; Sylvester, Richard; Lee, Youngjo

2014-01-01

The proportional subdistribution hazards model (i.e. Fine-Gray model) has been widely used for analyzing univariate competing risks data. Recently, this model has been extended to clustered competing risks data via frailty. To the best of our knowledge, however, there has been no literature on variable selection method for such competing risks frailty models. In this paper, we propose a simple but unified procedure via a penalized h-likelihood (HL) for variable selection of fixed effects in a general class of subdistribution hazard frailty models, in which random effects may be shared or correlated. We consider three penalty functions (LASSO, SCAD and HL) in our variable selection procedure. We show that the proposed method can be easily implemented using a slight modification to existing h-likelihood estimation approaches. Numerical studies demonstrate that the proposed procedure using the HL penalty performs well, providing a higher probability of choosing the true model than LASSO and SCAD methods without losing prediction accuracy. The usefulness of the new method is illustrated using two actual data sets from multi-center clinical trials. PMID:25042872

A multi-segment foot model based on anatomically registered technical coordinate systems: method repeatability in pediatric feet.

PubMed

Saraswat, Prabhav; MacWilliams, Bruce A; Davis, Roy B

2012-04-01

Several multi-segment foot models to measure the motion of intrinsic joints of the foot have been reported. Use of these models in clinical decision making is limited due to lack of rigorous validation including inter-clinician, and inter-lab variability measures. A model with thoroughly quantified variability may significantly improve the confidence in the results of such foot models. This study proposes a new clinical foot model with the underlying strategy of using separate anatomic and technical marker configurations and coordinate systems. Anatomical landmark and coordinate system identification is determined during a static subject calibration. Technical markers are located at optimal sites for dynamic motion tracking. The model is comprised of the tibia and three foot segments (hindfoot, forefoot and hallux) and inter-segmental joint angles are computed in three planes. Data collection was carried out on pediatric subjects at two sites (Site 1: n=10 subjects by two clinicians and Site 2: five subjects by one clinician). A plaster mold method was used to quantify static intra-clinician and inter-clinician marker placement variability by allowing direct comparisons of marker data between sessions for each subject. Intra-clinician and inter-clinician joint angle variability were less than 4°. For dynamic walking kinematics, intra-clinician, inter-clinician and inter-laboratory variability were less than 6° for the ankle and forefoot, but slightly higher for the hallux. Inter-trial variability accounted for 2-4° of the total dynamic variability. Results indicate the proposed foot model reduces the effects of marker placement variability on computed foot kinematics during walking compared to similar measures in previous models. Copyright © 2011 Elsevier B.V. All rights reserved.

Evaluation of the analytical variability of dipstick protein pads in canine urine.

PubMed

Giraldi, Marco; Paltrinieri, Saverio; Zatelli, Andrea

2018-06-01

The dipstick is a first-line and inexpensive test that can exclude the presence of proteinuria in dogs. However, no information is available about the analytical variability of canine urine dipstick analysis. The aim of this study was to assess the analytical variability in 2 dipsticks and the inter-operator variability in dipstick interpretation. Canine urine supernatants (n = 174) were analyzed with 2 commercially available dipsticks. Two observers evaluated each result blinded to the other observer and to the results of the other dipstick. Intra- and inter-assay variability was assessed in 5 samples (corresponding to the 5 different semi-quantitative results) tested 10 consecutive times over 5 consecutive days. The agreement between observers and between dipsticks was evaluated with Cohen's k test. Intra-assay repeatability was good (≤3/10 errors), whereas inter-assay variability was higher (from 1/5 to 4/5 discordant results). The concordance between the operators (k = 0.68 and 0.79 for the 2 dipsticks) and that of the dipsticks (k = 0.66 and 0.74 for the 2 operators) was good. However, 1 observer and 1 dipstick overestimated the results compared with the second observer or dipstick. In any case, discordant results accounted for a single unit of the semi-quantitative scale. As for any other method, analytic variability may affect the semi-quantitation of urinary proteins when using the dipstick method. Subjective interpretation of the pad and, to a lesser extent, intrinsic staining properties of the pads could affect the results. Further studies are warranted to evaluate the effect of this variability on clinical decisions. © 2018 American Society for Veterinary Clinical Pathology.

Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods.

PubMed

Young, Stefano; Kim, Hyun J Grace; Ko, Moe Moe; Ko, War War; Flores, Carlos; McNitt-Gray, Michael F

2015-05-01

Measuring the size of nodules on chest CT is important for lung cancer staging and measuring therapy response. 3D volumetry has been proposed as a more robust alternative to 1D and 2D sizing methods. There have also been substantial advances in methods to reduce radiation dose in CT. The purpose of this work was to investigate the effect of dose reduction and reconstruction methods on variability in 3D lung-nodule volumetry. Reduced-dose CT scans were simulated by applying a noise-addition tool to the raw (sinogram) data from clinically indicated patient scans acquired on a multidetector-row CT scanner (Definition Flash, Siemens Healthcare). Scans were simulated at 25%, 10%, and 3% of the dose of their clinical protocol (CTDIvol of 20.9 mGy), corresponding to CTDIvol values of 5.2, 2.1, and 0.6 mGy. Simulated reduced-dose data were reconstructed with both conventional filtered backprojection (B45 kernel) and iterative reconstruction methods (SAFIRE: I44 strength 3 and I50 strength 3). Three lab technologist readers contoured "measurable" nodules in 33 patients under each of the different acquisition/reconstruction conditions in a blinded study design. Of the 33 measurable nodules, 17 were used to estimate repeatability with their clinical reference protocol, as well as interdose and inter-reconstruction-method reproducibilities. The authors compared the resulting distributions of proportional differences across dose and reconstruction methods by analyzing their means, standard deviations (SDs), and t-test and F-test results. The clinical-dose repeatability experiment yielded a mean proportional difference of 1.1% and SD of 5.5%. The interdose reproducibility experiments gave mean differences ranging from -5.6% to -1.7% and SDs ranging from 6.3% to 9.9%. The inter-reconstruction-method reproducibility experiments gave mean differences of 2.0% (I44 strength 3) and -0.3% (I50 strength 3), and SDs were identical at 7.3%. For the subset of repeatability cases, inter-reconstruction-method mean/SD pairs were (1.4%, 6.3%) and (-0.7%, 7.2%) for I44 strength 3 and I50 strength 3, respectively. Analysis of representative nodules confirmed that reader variability appeared unaffected by dose or reconstruction method. Lung-nodule volumetry was extremely robust to the radiation-dose level, down to the minimum scanner-supported dose settings. In addition, volumetry was robust to the reconstruction methods used in this study, which included both conventional filtered backprojection and iterative methods.

Quality requirements for veterinary hematology analyzers in small animals-a survey about veterinary experts' requirements and objective evaluation of analyzer performance based on a meta-analysis of method validation studies: bench top hematology analyzer.

PubMed

Cook, Andrea M; Moritz, Andreas; Freeman, Kathleen P; Bauer, Natali

2016-09-01

Scarce information exists about quality requirements and objective evaluation of performance of large veterinary bench top hematology analyzers. The study was aimed at comparing the observed total error (TEobs ) derived from meta-analysis of published method validation data to the total allowable error (TEa ) for veterinary hematology variables in small animals based on experts' opinions. Ideally, TEobs should be < TEa . An online survey was sent to veterinary experts in clinical pathology and small animal internal medicine for providing the maximal allowable deviation from a given result for each variable. Percent of TEa = (allowable median deviation/clinical threshold) * 100%. Second, TEobs for 3 laser-based bench top hematology analyzers (ADVIA 2120; Sysmex XT2000iV, and CellDyn 3500) was calculated based on method validation studies published between 2005 and 2013 (n = 4). The percent TEobs = 2 * CV (%) + bias (%). The CV was derived from published studies except for the ADVIA 2120 (internal data), and bias was estimated from the regression equation. A total of 41 veterinary experts (19 diplomates, 8 residents, 10 postgraduate students, 4 anonymous specialists) responded. The proposed range of TEa was wide, but generally ≤ 20%. The TEobs was < TEa for all variables and analyzers except for canine and feline HGB (high bias, low CV) and platelet counts (high bias, high CV). Overall, veterinary bench top analyzers fulfilled experts' requirements except for HGB due to method-related bias, and platelet counts due to known preanalytic/analytic issues. © 2016 American Society for Veterinary Clinical Pathology.

Evaluating predictive modeling’s potential to improve teleretinal screening participation in urban safety net clinics

PubMed Central

Ogunyemi, Omolola; Teklehaimanot, Senait; Patty, Lauren; Moran, Erin; George, Sheba

2013-01-01

Introduction Screening guidelines for diabetic patients recommend yearly eye examinations to detect diabetic retinopathy and other forms of diabetic eye disease. However, annual screening rates for retinopathy in US urban safety net settings remain low. Methods Using data gathered from a study of teleretinal screening in six urban safety net clinics, we assessed whether predictive modeling could be of value in identifying patients at risk of developing retinopathy. We developed and examined the accuracy of two predictive modeling approaches for diabetic retinopathy in a sample of 513 diabetic individuals, using routinely available clinical variables from retrospective medical record reviews. Bayesian networks and radial basis function (neural) networks were learned using ten-fold cross-validation. Results The predictive models were modestly predictive with the best model having an AUC of 0.71. Discussion Using routinely available clinical variables to predict patients at risk of developing retinopathy and to target them for annual eye screenings may be of some usefulness to safety net clinics. PMID:23920536

Number needed to treat (NNT) in clinical literature: an appraisal.

PubMed

Mendes, Diogo; Alves, Carlos; Batel-Marques, Francisco

2017-06-01

The number needed to treat (NNT) is an absolute effect measure that has been used to assess beneficial and harmful effects of medical interventions. Several methods can be used to calculate NNTs, and they should be applied depending on the different study characteristics, such as the design and type of variable used to measure outcomes. Whether or not the most recommended methods have been applied to calculate NNTs in studies published in the medical literature is yet to be determined. The aim of this study is to assess whether the methods used to calculate NNTs in studies published in medical journals are in line with basic methodological recommendations. The top 25 high-impact factor journals in the "General and/or Internal Medicine" category were screened to identify studies assessing pharmacological interventions and reporting NNTs. Studies were categorized according to their design and the type of variables. NNTs were assessed for completeness (baseline risk, time horizon, and confidence intervals [CIs]). The methods used for calculating NNTs in selected studies were compared to basic methodological recommendations published in the literature. Data were analyzed using descriptive statistics. The search returned 138 citations, of which 51 were selected. Most were meta-analyses (n = 23, 45.1%), followed by clinical trials (n = 17, 33.3%), cohort (n = 9, 17.6%), and case-control studies (n = 2, 3.9%). Binary variables were more common (n = 41, 80.4%) than time-to-event (n = 10, 19.6%) outcomes. Twenty-six studies (51.0%) reported only NNT to benefit (NNTB), 14 (27.5%) reported both NNTB and NNT to harm (NNTH), and 11 (21.6%) reported only NNTH. Baseline risk (n = 37, 72.5%), time horizon (n = 38, 74.5%), and CI (n = 32, 62.7%) for NNTs were not always reported. Basic methodological recommendations to calculate NNTs were not followed in 15 studies (29.4%). The proportion of studies applying non-recommended methods was particularly high for meta-analyses (n = 13, 56.5%). A considerable proportion of studies, particularly meta-analyses, applied methods that are not in line with basic methodological recommendations. Despite their usefulness in assisting clinical decisions, NNTs are uninterpretable if incompletely reported, and they may be misleading if calculating methods are inadequate to study designs and variables under evaluation. Further research is needed to confirm the present findings.

The Relationship Between Executive Functions and Language Abilities in Children: A Latent Variables Approach

PubMed Central

Park, Ji Sook; Gangopadhyay, Ishanti; Davidson, Meghan M.; Weismer, Susan Ellis

2017-01-01

Purpose We aimed to outline the latent variables approach for measuring nonverbal executive function (EF) skills in school-age children, and to examine the relationship between nonverbal EF skills and language performance in this age group. Method Seventy-one typically developing children, ages 8 through 11, participated in the study. Three EF components, inhibition, updating, and task-shifting, were each indexed using 2 nonverbal tasks. A latent variables approach was used to extract latent scores that represented each EF construct. Children were also administered common standardized language measures. Multiple regression analyses were conducted to examine the relationship between EF and language skills. Results Nonverbal updating was associated with the Receptive Language Index on the Clinical Evaluation of Language Fundamentals–Fourth Edition (CELF-4). When composites denoting lexical–semantic and syntactic abilities were derived, nonverbal inhibition (but not shifting or updating) was found to predict children's syntactic abilities. These relationships held when the effects of age, IQ, and socioeconomic status were controlled. Conclusions The study makes a methodological contribution by explicating a method by which researchers can use the latent variables approach when measuring EF performance in school-age children. The study makes a theoretical and a clinical contribution by suggesting that language performance may be related to domain-general EFs. PMID:28306755

Latent class instrumental variables: A clinical and biostatistical perspective

PubMed Central

Baker, Stuart G.; Kramer, Barnett S.; Lindeman, Karen S.

2015-01-01

In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research. PMID:26239275

A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.

PubMed

Schmid, Matthias; Küchenhoff, Helmut; Hoerauf, Achim; Tutz, Gerhard

2016-02-28

Survival trees are a popular alternative to parametric survival modeling when there are interactions between the predictor variables or when the aim is to stratify patients into prognostic subgroups. A limitation of classical survival tree methodology is that most algorithms for tree construction are designed for continuous outcome variables. Hence, classical methods might not be appropriate if failure time data are measured on a discrete time scale (as is often the case in longitudinal studies where data are collected, e.g., quarterly or yearly). To address this issue, we develop a method for discrete survival tree construction. The proposed technique is based on the result that the likelihood of a discrete survival model is equivalent to the likelihood of a regression model for binary outcome data. Hence, we modify tree construction methods for binary outcomes such that they result in optimized partitions for the estimation of discrete hazard functions. By applying the proposed method to data from a randomized trial in patients with filarial lymphedema, we demonstrate how discrete survival trees can be used to identify clinically relevant patient groups with similar survival behavior. Copyright © 2015 John Wiley & Sons, Ltd.

Beyond total treatment effects in randomised controlled trials: Baseline measurement of intermediate outcomes needed to reduce confounding in mediation investigations.

PubMed

Landau, Sabine; Emsley, Richard; Dunn, Graham

2018-06-01

Random allocation avoids confounding bias when estimating the average treatment effect. For continuous outcomes measured at post-treatment as well as prior to randomisation (baseline), analyses based on (A) post-treatment outcome alone, (B) change scores over the treatment phase or (C) conditioning on baseline values (analysis of covariance) provide unbiased estimators of the average treatment effect. The decision to include baseline values of the clinical outcome in the analysis is based on precision arguments, with analysis of covariance known to be most precise. Investigators increasingly carry out explanatory analyses to decompose total treatment effects into components that are mediated by an intermediate continuous outcome and a non-mediated part. Traditional mediation analysis might be performed based on (A) post-treatment values of the intermediate and clinical outcomes alone, (B) respective change scores or (C) conditioning on baseline measures of both intermediate and clinical outcomes. Using causal diagrams and Monte Carlo simulation, we investigated the performance of the three competing mediation approaches. We considered a data generating model that included three possible confounding processes involving baseline variables: The first two processes modelled baseline measures of the clinical variable or the intermediate variable as common causes of post-treatment measures of these two variables. The third process allowed the two baseline variables themselves to be correlated due to past common causes. We compared the analysis models implied by the competing mediation approaches with this data generating model to hypothesise likely biases in estimators, and tested these in a simulation study. We applied the methods to a randomised trial of pragmatic rehabilitation in patients with chronic fatigue syndrome, which examined the role of limiting activities as a mediator. Estimates of causal mediation effects derived by approach (A) will be biased if one of the three processes involving baseline measures of intermediate or clinical outcomes is operating. Necessary assumptions for the change score approach (B) to provide unbiased estimates under either process include the independence of baseline measures and change scores of the intermediate variable. Finally, estimates provided by the analysis of covariance approach (C) were found to be unbiased under all the three processes considered here. When applied to the example, there was evidence of mediation under all methods but the estimate of the indirect effect depended on the approach used with the proportion mediated varying from 57% to 86%. Trialists planning mediation analyses should measure baseline values of putative mediators as well as of continuous clinical outcomes. An analysis of covariance approach is recommended to avoid potential biases due to confounding processes involving baseline measures of intermediate or clinical outcomes, and not simply for increased precision.

Evaluation of a Serum Lung Cancer Biomarker Panel

PubMed Central

Mazzone, Peter J; Wang, Xiao-Feng; Han, Xiaozhen; Choi, Humberto; Seeley, Meredith; Scherer, Richard; Doseeva, Victoria

2018-01-01

Background: A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. Methods: The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. Results: The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. Conclusions: This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results. PMID:29371783

Kinematic evaluation of the finger's interphalangeal joints coupling mechanism--variability, flexion-extension differences, triggers, locking swanneck deformities, anthropometric correlations.

PubMed

Leijnse, J N A L; Quesada, P M; Spoor, C W

2010-08-26

The human finger contains tendon/ligament mechanisms essential for proper control. One mechanism couples the movements of the interphalangeal joints when the (unloaded) finger is flexed with active deep flexor. This study's aim was to accurately determine in a large finger sample the kinematics and variability of the coupled interphalangeal joint motions, for potential clinical and finger model validation applications. The data could also be applied to humanoid robotic hands. Sixty-eight fingers were measured in seventeen hands in nine subjects. Fingers exhibited great joint mobility variability, with passive proximal interphalangeal hyperextension ranging from zero to almost fifty degrees. Increased measurement accuracy was obtained by using marker frames to amplify finger segment motions. Gravitational forces on the marker frames were not found to invalidate measurements. The recorded interphalangeal joint trajectories were highly consistent, demonstrating the underlying coupling mechanism. The increased accuracy and large sample size allowed for evaluation of detailed trajectory variability, systematic differences between flexion and extension trajectories, and three trigger types, distinct from flexor tendon triggers, involving initial flexion deficits in either proximal or distal interphalangeal joint. The experimental methods, data and analysis should advance insight into normal and pathological finger biomechanics (e.g., swanneck deformities), and could help improve clinical differential diagnostics of trigger finger causes. The marker frame measuring method may be useful to quantify interphalangeal joints trajectories in surgical/rehabilitative outcome studies. The data as a whole provide the most comprehensive collection of interphalangeal joint trajectories for clinical reference and model validation known to us to date. 2010 Elsevier Ltd. All rights reserved.

VARIABLE SELECTION FOR QUALITATIVE INTERACTIONS IN PERSONALIZED MEDICINE WHILE CONTROLLING THE FAMILY-WISE ERROR RATE

PubMed Central

Gunter, Lacey; Zhu, Ji; Murphy, Susan

2012-01-01

For many years, subset analysis has been a popular topic for the biostatistics and clinical trials literature. In more recent years, the discussion has focused on finding subsets of genomes which play a role in the effect of treatment, often referred to as stratified or personalized medicine. Though highly sought after, methods for detecting subsets with altering treatment effects are limited and lacking in power. In this article we discuss variable selection for qualitative interactions with the aim to discover these critical patient subsets. We propose a new technique designed specifically to find these interaction variables among a large set of variables while still controlling for the number of false discoveries. We compare this new method against standard qualitative interaction tests using simulations and give an example of its use on data from a randomized controlled trial for the treatment of depression. PMID:22023676

Valx: A system for extracting and structuring numeric lab test comparison statements from text

PubMed Central

Hao, Tianyong; Liu, Hongfang; Weng, Chunhua

2017-01-01

Objectives To develop an automated method for extracting and structuring numeric lab test comparison statements from text and evaluate the method using clinical trial eligibility criteria text. Methods Leveraging semantic knowledge from the Unified Medical Language System (UMLS) and domain knowledge acquired from the Internet, Valx takes 7 steps to extract and normalize numeric lab test expressions: 1) text preprocessing, 2) numeric, unit, and comparison operator extraction, 3) variable identification using hybrid knowledge, 4) variable - numeric association, 5) context-based association filtering, 6) measurement unit normalization, and 7) heuristic rule-based comparison statements verification. Our reference standard was the consensus-based annotation among three raters for all comparison statements for two variables, i.e., HbA1c and glucose, identified from all of Type 1 and Type 2 diabetes trials in ClinicalTrials.gov. Results The precision, recall, and F-measure for structuring HbA1c comparison statements were 99.6%, 98.1%, 98.8% for Type 1 diabetes trials, and 98.8%, 96.9%, 97.8% for Type 2 Diabetes trials, respectively. The precision, recall, and F-measure for structuring glucose comparison statements were 97.3%, 94.8%, 96.1% for Type 1 diabetes trials, and 92.3%, 92.3%, 92.3% for Type 2 diabetes trials, respectively. Conclusions Valx is effective at extracting and structuring free-text lab test comparison statements in clinical trial summaries. Future studies are warranted to test its generalizability beyond eligibility criteria text. The open-source Valx enables its further evaluation and continued improvement among the collaborative scientific community. PMID:26940748

HIV-1 Genetic Variability in Cuba and Implications for Transmission and Clinical Progression.

PubMed

Blanco, Madeline; Machado, Liuber Y; Díaz, Héctor; Ruiz, Nancy; Romay, Dania; Silva, Eladio

2015-10-01

INTRODUCTION Serological and molecular HIV-1 studies in Cuba have shown very low prevalence of seropositivity, but an increasing genetic diversity attributable to introduction of many HIV-1 variants from different areas, exchange of such variants among HIV-positive people with several coinciding routes of infection and other epidemiologic risk factors in the seropositive population. The high HIV-1 genetic variability observed in Cuba has possible implications for transmission and clinical progression. OBJECTIVE Study genetic variability for the HIV-1 env, gag and pol structural genes in Cuba; determine the prevalence of B and non-B subtypes according to epidemiologic and behavioral variables and determine whether a relationship exists between genetic variability and transmissibility, and between genetic variability and clinical disease progression in people living with HIV/AIDS. METHODS Using two molecular assays (heteroduplex mobility assay and nucleic acid sequencing), structural genes were characterized in 590 people with HIV-1 (480 men and 110 women), accounting for 3.4% of seropositive individuals in Cuba as of December 31, 2013. Nonrandom sampling, proportional to HIV prevalence by province, was conducted. Relationships between molecular results and viral factors, host characteristics, and patients' clinical, epidemiologic and behavioral variables were studied for molecular epidemiology, transmission, and progression analyses. RESULTS Molecular analysis of the three HIV-1 structural genes classified 297 samples as subtype B (50.3%), 269 as non-B subtypes (45.6%) and 24 were not typeable. Subtype B prevailed overall and in men, mainly in those who have sex with men. Non-B subtypes were prevalent in women and heterosexual men, showing multiple circulating variants and recombinant forms. Sexual transmission was the predominant form of infection for all. B and non-B subtypes were encountered throughout Cuba. No association was found between subtypes and transmission or clinical progression, although the proportion of deaths was higher for subtype B. Among those who died during the study period, there were no differences between subtypes in the mean time from HIV or AIDS diagnosis to death. CONCLUSIONS Our results suggest that B and non-B HIV-1 subtypes found in Cuba do not differ in transmissibility and in clinical disease progression. KEYWORDS HIV-1, AIDS, molecular epidemiology, transmissibility, clinical progression, subtypes, circulating recombinant forms, pathogenesis, Cuba.

Link between immunoexpression of hMLH1 and hMSH2 proteins and clinical-epidemiological aspects of actinic cheilitis*

PubMed Central

Sarmento, Dmitry José de Santana; Godoy, Gustavo Pina; Miguel, Márcia Cristina da Costa; da Silveira, Éricka Janine Dantas

2016-01-01

Background The studies found in the literature associate the immunoexpression of hMLH1 and hMSH2 proteins with histologic aspects, but do not correlate it with clinical and epidemiological data. Objective To evaluate the immunoexpression of hMLH1 and hMSH2 in actinic cheilitis, correlating it with clinical characteristics. Methods We analyzed 40 cases. Histological and immunohistochemical analyses were performed. The following clinical variables were evaluated: gender, age range, ethnicity, clinical aspect and occupational sunlight exposure. Statistical evaluation included the Student t-test, while the significance level was set at 5%. Results Greater immunoexpression of hMLH1 and hMSH2 was observed in females, individuals aged over 40, and mixed-race/black patients. Furthermore, the immunoexpression of these proteins was greater in actinic cheilitis with a white-colored appearance and in patients without occupational sunlight exposure. No statistical differences were observed for the variables studied. Conclusion This study uncovered variations of hMLH1 and hMSH2 protein expression upon evaluation of clinical aspects in actinic cheilitis. PMID:27579741

Quantifier variables of the back surface deformity obtained with a noninvasive structured light method: evaluation of their usefulness in idiopathic scoliosis diagnosis

PubMed Central

Buendía, Mateo; Cibrián, Rosa M.; Salvador, Rosario; Laguía, Manuel; Martín, Antonio; Gomar, Francisco

2006-01-01

New noninvasive techniques, amongst them structured light methods, have been applied to study rachis deformities, providing a way to evaluate external back deformities in the three planes of space. These methods are aimed at reducing the number of radiographic examinations necessary to diagnose and follow-up patients with scoliosis. By projecting a grid over the patient’s back, the corresponding software for image treatment provides a topography of the back in a color or gray scale. Visual inspection of back topographic images using this method immediately provides information about back deformity, but it is important to determine quantifier variables of the deformity to establish diagnostic criteria. In this paper, two topographic variables [deformity in the axial plane index (DAPI) and posterior trunk symmetry index (POTSI)] that quantify deformity in two different planes are analyzed. Although other authors have reported the POTSI variable, the DAPI variable proposed in this paper is innovative. The upper normality limit of these variables in a nonpathological group was determined. These two variables have different and complementary diagnostic characteristics, therefore we devised a combined diagnostic criterion: cases with normal DAPI and POTSI (DAPI ≤ 3.9% and POTSI ≤ 27.5%) were diagnosed as nonpathologic, but cases with high DAPI or POTSI were diagnosed as pathologic. When we used this criterion to analyze all the cases in the sample (56 nonpathologic and 30 with idiopathic scoliosis), we obtained 76.6% sensitivity, 91% specificity, and a positive predictive value of 82%. The interobserver, intraobserver, and interassay variability were studied by determining the variation coefficient. There was good correlation between topographic variables (DAPI and POTSI) and clinical variables (Cobb’s angle and vertebral rotation angle). PMID:16609858

Is Abdominal Fetal Electrocardiography an Alternative to Doppler Ultrasound for FHR Variability Evaluation?

PubMed Central

Jezewski, Janusz; Wrobel, Janusz; Matonia, Adam; Horoba, Krzysztof; Martinek, Radek; Kupka, Tomasz; Jezewski, Michal

2017-01-01

Great expectations are connected with application of indirect fetal electrocardiography (FECG), especially for home telemonitoring of pregnancy. Evaluation of fetal heart rate (FHR) variability, when determined from FECG, uses the same criteria as for FHR signal acquired classically—through ultrasound Doppler method (US). Therefore, the equivalence of those two methods has to be confirmed, both in terms of recognizing classical FHR patterns: baseline, accelerations/decelerations (A/D), long-term variability (LTV), as well as evaluating the FHR variability with beat-to-beat accuracy—short-term variability (STV). The research material consisted of recordings collected from 60 patients in physiological and complicated pregnancy. The FHR signals of at least 30 min duration were acquired dually, using two systems for fetal and maternal monitoring, based on US and FECG methods. Recordings were retrospectively divided into normal (41) and abnormal (19) fetal outcome. The complex process of data synchronization and validation was performed. Obtained low level of the signal loss (4.5% for US and 1.8% for FECG method) enabled to perform both direct comparison of FHR signals, as well as indirect one—by using clinically relevant parameters. Direct comparison showed that there is no measurement bias between the acquisition methods, whereas the mean absolute difference, important for both visual and computer-aided signal analysis, was equal to 1.2 bpm. Such low differences do not affect the visual assessment of the FHR signal. However, in the indirect comparison the inconsistencies of several percent were noted. This mainly affects the acceleration (7.8%) and particularly deceleration (54%) patterns. In the signals acquired using the electrocardiography the obtained STV and LTV indices have shown significant overestimation by 10 and 50% respectively. It also turned out, that ability of clinical parameters to distinguish between normal and abnormal groups do not depend on the acquisition method. The obtained results prove that the abdominal FECG, considered as an alternative to the ultrasound approach, does not change the interpretation of the FHR signal, which was confirmed during both visual assessment and automated analysis. PMID:28559852

Atlas based brain volumetry: How to distinguish regional volume changes due to biological or physiological effects from inherent noise of the methodology.

PubMed

Opfer, Roland; Suppa, Per; Kepp, Timo; Spies, Lothar; Schippling, Sven; Huppertz, Hans-Jürgen

2016-05-01

Fully-automated regional brain volumetry based on structural magnetic resonance imaging (MRI) plays an important role in quantitative neuroimaging. In clinical trials as well as in clinical routine multiple MRIs of individual patients at different time points need to be assessed longitudinally. Measures of inter- and intrascanner variability are crucial to understand the intrinsic variability of the method and to distinguish volume changes due to biological or physiological effects from inherent noise of the methodology. To measure regional brain volumes an atlas based volumetry (ABV) approach was deployed using a highly elastic registration framework and an anatomical atlas in a well-defined template space. We assessed inter- and intrascanner variability of the method in 51 cognitively normal subjects and 27 Alzheimer dementia (AD) patients from the Alzheimer's Disease Neuroimaging Initiative by studying volumetric results of repeated scans for 17 compartments and brain regions. Median percentage volume differences of scan-rescans from the same scanner ranged from 0.24% (whole brain parenchyma in healthy subjects) to 1.73% (occipital lobe white matter in AD), with generally higher differences in AD patients as compared to normal subjects (e.g., 1.01% vs. 0.78% for the hippocampus). Minimum percentage volume differences detectable with an error probability of 5% were in the one-digit percentage range for almost all structures investigated, with most of them being below 5%. Intrascanner variability was independent of magnetic field strength. The median interscanner variability was up to ten times higher than the intrascanner variability. Copyright © 2016 Elsevier Inc. All rights reserved.

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers

PubMed Central

Clementz, Brett A.; Sweeney, John A.; Hamm, Jordan P.; Ivleva, Elena I.; Ethridge, Lauren E.; Pearlson, Godfrey D.; Keshavan, Matcheri S.; Tamminga, Carol A.

2017-01-01

Objective Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. Method A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. Results Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. Conclusions These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold standard. PMID:26651391

Obstructive Sleep Apnea in Women: Study of Speech and Craniofacial Characteristics

PubMed Central

Tyan, Marina; Fernández Pozo, Rubén; Toledano, Doroteo; Lopez Gonzalo, Eduardo; Alcazar Ramirez, Jose Daniel; Hernandez Gomez, Luis Alfonso

2017-01-01

Background Obstructive sleep apnea (OSA) is a common sleep disorder characterized by frequent cessation of breathing lasting 10 seconds or longer. The diagnosis of OSA is performed through an expensive procedure, which requires an overnight stay at the hospital. This has led to several proposals based on the analysis of patients’ facial images and speech recordings as an attempt to develop simpler and cheaper methods to diagnose OSA. Objective The objective of this study was to analyze possible relationships between OSA and speech and facial features on a female population and whether these possible connections may be affected by the specific clinical characteristics in OSA population and, more specifically, to explore how the connection between OSA and speech and facial features can be affected by gender. Methods All the subjects are Spanish subjects suspected to suffer from OSA and referred to a sleep disorders unit. Voice recordings and photographs were collected in a supervised but not highly controlled way, trying to test a scenario close to a realistic clinical practice scenario where OSA is assessed using an app running on a mobile device. Furthermore, clinical variables such as weight, height, age, and cervical perimeter, which are usually reported as predictors of OSA, were also gathered. Acoustic analysis is centered in sustained vowels. Facial analysis consists of a set of local craniofacial features related to OSA, which were extracted from images after detecting facial landmarks by using the active appearance models. To study the probable OSA connection with speech and craniofacial features, correlations among apnea-hypopnea index (AHI), clinical variables, and acoustic and facial measurements were analyzed. Results The results obtained for female population indicate mainly weak correlations (r values between .20 and .39). Correlations between AHI, clinical variables, and speech features show the prevalence of formant frequencies over bandwidths, with F2/i/ being the most appropriate formant frequency for OSA prediction in women. Results obtained for male population indicate mainly very weak correlations (r values between .01 and .19). In this case, bandwidths prevail over formant frequencies. Correlations between AHI, clinical variables, and craniofacial measurements are very weak. Conclusions In accordance with previous studies, some clinical variables are found to be good predictors of OSA. Besides, strong correlations are found between AHI and some clinical variables with speech and facial features. Regarding speech feature, the results show the prevalence of formant frequency F2/i/ over the rest of features for the female population as OSA predictive feature. Although the correlation reported is weak, this study aims to find some traces that could explain the possible connection between OSA and speech in women. In the case of craniofacial measurements, results evidence that some features that can be used for predicting OSA in male patients are not suitable for testing female population. PMID:29109068

Gingival Retraction Methods: A Systematic Review.

PubMed

Tabassum, Sadia; Adnan, Samira; Khan, Farhan Raza

2017-12-01

The aim of this systematic review was to assess the gingival retraction methods in terms of the amount of gingival retraction achieved and changes observed in various clinical parameters: gingival index (GI), plaque index (PI), probing depth (PD), and attachment loss (AL). Data sources included three major databases, PubMed, CINAHL plus (Ebsco), and Cochrane, along with hand search. Search was made using the key terms in different permutations of gingival retraction* AND displacement method* OR technique* OR agents OR material* OR medicament*. The initial search results yielded 145 articles which were narrowed down to 10 articles using a strict eligibility criteria of including clinical trials or experimental studies on gingival retraction methods with the amount of tooth structure gained and assessment of clinical parameters as the outcomes conducted on human permanent teeth only. Gingival retraction was measured in 6/10 studies whereas the clinical parameters were assessed in 5/10 studies. The total number of teeth assessed in the 10 included studies was 400. The most common method used for gingival retraction was chemomechanical. The results were heterogeneous with regards to the outcome variables. No method seemed to be significantly superior to the other in terms of gingival retraction achieved. Clinical parameters were not significantly affected by the gingival retraction method. © 2016 by the American College of Prosthodontists.

[Prediction of histological liver damage in asymptomatic alcoholic patients by means of clinical and laboratory data].

PubMed

Iturriaga, H; Hirsch, S; Bunout, D; Díaz, M; Kelly, M; Silva, G; de la Maza, M P; Petermann, M; Ugarte, G

1993-04-01

Looking for a noninvasive method to predict liver histologic alterations in alcoholic patients without clinical signs of liver failure, we studied 187 chronic alcoholics recently abstinent, divided in 2 series. In the model series (n = 94) several clinical variables and results of common laboratory tests were confronted to the findings of liver biopsies. These were classified in 3 groups: 1. Normal liver; 2. Moderate alterations; 3. Marked alterations, including alcoholic hepatitis and cirrhosis. Multivariate methods used were logistic regression analysis and a classification and regression tree (CART). Both methods entered gamma-glutamyltransferase (GGT), aspartate-aminotransferase (AST), weight and age as significant and independent variables. Univariate analysis with GGT and AST at different cutoffs were also performed. To predict the presence of any kind of damage (Groups 2 and 3), CART and AST > 30 IU showed the higher sensitivity, specificity and correct prediction, both in the model and validation series. For prediction of marked liver damage, a score based on logistic regression and GGT > 110 IU had the higher efficiencies. It is concluded that GGT and AST are good markers of alcoholic liver damage and that, using sample cutoffs, histologic diagnosis can be correctly predicted in 80% of recently abstinent asymptomatic alcoholics.

Baseline OCT Measurements in the Idiopathic Intracranial Hypertension Treatment Trial, Part I: Quality Control, Comparisons, and Variability

PubMed Central

2014-01-01

Purpose. Optical coherence tomography (OCT) has been used to investigate papilledema in single-site, mostly retrospective studies. We investigated whether spectral-domain OCT (SD-OCT), which provides thickness and volume measurements of the optic nerve head and retina, could reliably demonstrate structural changes due to papilledema in a prospective multisite clinical trial setting. Methods. At entry, 126 subjects in the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT) with mild visual field loss had optic disc and macular scans, using the Cirrus SD-OCT. Images were analyzed by using the proprietary commercial and custom 3D-segmentation algorithms to calculate retinal nerve fiber layer (RNFL), total retinal thickness (TRT), optic nerve head volume (ONHV), and retinal ganglion cell layer (GCL) thickness. We evaluated variability, with interocular comparison and correlation between results for both methods. Results. The average RNFL thickness > 95% of normal controls in 90% of eyes and the RNFL, TRT, ONH height, and ONHV showed strong (r > 0.8) correlations for interocular comparisons. Variability for repeated testing of OCT parameters was low for both methods and intraclass correlations > 0.9 except for the proprietary GCL thickness. The proprietary algorithm–derived RNFL, TRT, and GCL thickness measurements had failure rates of 10%, 16%, and 20% for all eyes respectively, which were uncommon with 3D-segmentation–derived measurements. Only 7% of eyes had GCL thinning that was less than fifth percentile of normal age-matched control eyes by both methods. Conclusions. Spectral-domain OCT provides reliable continuous variables and quantified assessment of structural alterations due to papilledema. (ClinicalTrials.gov number, NCT01003639.) PMID:25370510

The clinical evaluation of International Normalized Ratio variability and control in conventional oral anticoagulant administration by use of the variance growth rate.

PubMed

Ibrahim, S; Jespersen, J; Poller, L

2013-08-01

The time in target International Normalized Ratio (INR) range (TIR) is used to assess the control and intensity of oral anticoagulation, but it does not measure variation in the INR. The value of assessing INR variability by use of the variance growth rate (VGR) as a predictor of events was investigated in patients treated with warfarin. Three different methods of VGR determination (A, B1, and B2) together with the TIR were studied. Method A measures both INR variability and control, but methods B1 and B2 measure variability only. The VGR and TIR were determined over three time periods: overall follow-up to an event, and 6 months and 3 months before an event. Six hundred and sixty-one control patients were matched to 158 cases (bleeding, thromboembolism, or death). With all VGR methods, the risk of an event was greater in unstable patients at 6 months before an event than in stable patients. Method A demonstrated the greatest risk 3 months before an event in the unstable VGR group as compared with the stable group (odds ratio 3.3, 95% confidence interval 1.9-5.7, P < 0.005). The risk of an event was 1.9 times greater in patients with a low TIR (< 39%) than in those with a high TIR (> 80%) in the 3-month period (P = 0.02). Risk of bleeding was significantly greater in the 3-month period in patients with unstable VGR, with the greatest risk found with method B2 (P < 0.01). Patients with unstable anticoagulation have a significantly increased risk of 'clinical events' at 3 and 6 months before an event. The VGR can be incorporated into computer-dosage programs, and may offer additional safety when oral anticoagulation is monitored. © 2013 International Society on Thrombosis and Haemostasis.

Teaching a Machine to Feel Postoperative Pain: Combining High-Dimensional Clinical Data with Machine Learning Algorithms to Forecast Acute Postoperative Pain

PubMed Central

Tighe, Patrick J.; Harle, Christopher A.; Hurley, Robert W.; Aytug, Haldun; Boezaart, Andre P.; Fillingim, Roger B.

2015-01-01

Background Given their ability to process highly dimensional datasets with hundreds of variables, machine learning algorithms may offer one solution to the vexing challenge of predicting postoperative pain. Methods Here, we report on the application of machine learning algorithms to predict postoperative pain outcomes in a retrospective cohort of 8071 surgical patients using 796 clinical variables. Five algorithms were compared in terms of their ability to forecast moderate to severe postoperative pain: Least Absolute Shrinkage and Selection Operator (LASSO), gradient-boosted decision tree, support vector machine, neural network, and k-nearest neighbor, with logistic regression included for baseline comparison. Results In forecasting moderate to severe postoperative pain for postoperative day (POD) 1, the LASSO algorithm, using all 796 variables, had the highest accuracy with an area under the receiver-operating curve (ROC) of 0.704. Next, the gradient-boosted decision tree had an ROC of 0.665 and the k-nearest neighbor algorithm had an ROC of 0.643. For POD 3, the LASSO algorithm, using all variables, again had the highest accuracy, with an ROC of 0.727. Logistic regression had a lower ROC of 0.5 for predicting pain outcomes on POD 1 and 3. Conclusions Machine learning algorithms, when combined with complex and heterogeneous data from electronic medical record systems, can forecast acute postoperative pain outcomes with accuracies similar to methods that rely only on variables specifically collected for pain outcome prediction. PMID:26031220

Principal components analysis in clinical studies.

PubMed

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

The inter-rater reliability of estimating the size of burns from various burn area chart drawings.

PubMed

Wachtel, T L; Berry, C C; Wachtel, E E; Frank, H A

2000-03-01

The accuracy and variability of burn size calculations using four Lund and Browder charts currently in clinical use and two Rule of Nine's diagrams were evaluated. The study showed that variability in estimation increased with burn size initially, plateaued in large burns and then decreased slightly in extensive burns. The Rule of Nine's technique often overestimates the burn size and is more variable, but can be performed somewhat faster than the Lund and Browder method. More burn experience leads to less variability in burn area chart drawing estimates. Irregularly shaped burns and burns on the trunk and thighs had greater variability than less irregularly shaped burns or burns on more defined anatomical parts of the body.

Use of generalised additive models to categorise continuous variables in clinical prediction

PubMed Central

2013-01-01

Background In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. Methods We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high- and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. Results The three-category proposal for the respiratory rate was ≤ 20;(20,24];> 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically significant differences being found between the two AUCs (p =0.079). The four-category proposal for PCO2 was ≤ 43;(43,52];(52,65];> 65, for which the following values were obtained: AIC=258.1 and AUC=0.81. No statistically significant differences were found between the AUC of the four-category option and that of the continuous predictor, which yielded an AIC of 250.3 and an AUC of 0.825 (p =0.115). Conclusions Our proposed method provides clinicians with the number and location of cut points for categorising variables, and performs as successfully as the original continuous predictor when it comes to developing clinical prediction rules. PMID:23802742

Monosomy 3 by FISH in uveal melanoma: variability in techniques and results.

PubMed

Aronow, Mary; Sun, Yang; Saunthararajah, Yogen; Biscotti, Charles; Tubbs, Raymond; Triozzi, Pierre; Singh, Arun D

2012-09-01

Tumor monosomy 3 confers a poor prognosis in patients with uveal melanoma. We critically review the techniques used for fluorescence in situ hybridization (FISH) detection of monosomy 3 in order to assess variability in practice patterns and to explain differences in results. Significant variability that has likely affected reported results was found in tissue sampling methods, selection of FISH probes, number of cells counted, and the cut-off point used to determine monosomy 3 status. Clinical parameters and specific techniques employed to report FISH results should be specified so as to allow meta-analysis of published studies. FISH-based detection of monosomy 3 in uveal melanoma has not been performed in a standardized manner, which limits conclusions regarding its clinical utility. FISH is a widely available, versatile technology, and when performed optimally has the potential to be a valuable tool for determining the prognosis of uveal melanoma. Copyright © 2012 Elsevier Inc. All rights reserved.

Night-to-Night Sleep Variability in Older Adults With Chronic Insomnia: Mediators and Moderators in a Randomized Controlled Trial of Brief Behavioral Therapy (BBT-I)

PubMed Central

Chan, Wai Sze; Williams, Jacob; Dautovich, Natalie D.; McNamara, Joseph P.H.; Stripling, Ashley; Dzierzewski, Joseph M.; Berry, Richard B.; McCoy, Karin J.M.; McCrae, Christina S.

2017-01-01

Study Objectives: Sleep variability is a clinically significant variable in understanding and treating insomnia in older adults. The current study examined changes in sleep variability in the course of brief behavioral therapy for insomnia (BBT-I) in older adults who had chronic insomnia. Additionally, the current study examined the mediating mechanisms underlying reductions of sleep variability and the moderating effects of baseline sleep variability on treatment responsiveness. Methods: Sixty-two elderly participants were randomly assigned to either BBT-I or self-monitoring and attention control (SMAC). Sleep was assessed by sleep diaries and actigraphy from baseline to posttreatment and at 3-month follow-up. Mixed models were used to examine changes in sleep variability (within-person standard deviations of weekly sleep parameters) and the hypothesized mediation and moderation effects. Results: Variabilities in sleep diary-assessed sleep onset latency (SOL) and actigraphy-assessed total sleep time (TST) significantly decreased in BBT-I compared to SMAC (Pseudo R2 = .12, .27; P = .018, .008). These effects were mediated by reductions in bedtime and wake time variability and time in bed. Significant time × group × baseline sleep variability interactions on sleep outcomes indicated that participants who had higher baseline sleep variability were more responsive to BBT-I; their actigraphy-assessed TST, SOL, and sleep efficiency improved to a greater degree (Pseudo R2 = .15 to .66; P < .001 to .044). Conclusions: BBT-I is effective in reducing sleep variability in older adults who have chronic insomnia. Increased consistency in bedtime and wake time and decreased time in bed mediate reductions of sleep variability. Baseline sleep variability may serve as a marker of high treatment responsiveness to BBT-I. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT02967185 Citation: Chan WS, Williams J, Dautovich ND, McNamara JP, Stripling A, Dzierzewski JM, Berry RB, McCoy KJ, McCrae CS. Night-to-night sleep variability in older adults with chronic insomnia: mediators and moderators in a randomized controlled trial of brief behavioral therapy (BBT-I). J Clin Sleep Med. 2017;13(11):1243–1254. PMID:28992829

SU-D-BRC-05: Effects of Motion and Variable RBE in a Lung Patient Treated with Passively Scattered Protons

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

Mirkovic, D; Titt, U; Mohan, R

2016-06-15

Purpose: To evaluate effects of motion and variable relative biological effectiveness (RBE) in a lung cancer patient treated with passively scattered proton therapy using dose volume histograms associated with patient dose computed using three different methods. Methods: A proton treatment plan of a lung cancer patient optimized using clinical treatment planning system (TPS) was used to construct a detailed Monte Carlo (MC) model of the beam delivery system and the patient specific aperture and compensator. A phase space file containing all particles transported through the beam line was collected at the distal surface of the range compensator and subsequently transportedmore » through two different patient models. The first model was based on the average CT used by the TPS and the second model included all 10 phases of the corresponding 4DCT. The physical dose and proton linear energy transfer (LET) were computed in each voxel of two models and used to compute constant and variable RBE MC dose on average CT and 4D CT. The MC computed doses were compared to the TPS dose using dose volume histograms for relevant structures. Results: The results show significant differences in doses to the target and critical structures suggesting the need for more accurate proton dose computation methods. In particular, the 4D dose shows reduced coverage of the target and higher dose to the spinal cord, while variable RBE dose shows higher lung dose. Conclusion: The methodology developed in this pilot study is currently used for the analysis of a cohort of ∼90 lung patients from a clinical trial comparing proton and photon therapy for lung cancer. The results from this study will help us in determining the clinical significance of more accurate dose computation models in proton therapy.« less

Autosomal Dominant Cataract: Intrafamilial Phenotypic Variability, Interocular Asymmetry, and Variable Progression in Four Chilean Families

PubMed Central

Shafie, Suraiya M.; Barria von-Bischhoffshausen, Fernando R.; Bateman, J. Bronwyn

2006-01-01

PURPOSE To document intrafamilial and interocular phenotypic variability of autosomal dominant cataract (ADC). DESIGN Prospective observational case series. METHODS We performed ophthalmologic examination in four Chilean ADC families. RESULTS The families exhibited variability with respect to morphology, location with the lens, color and density of cataracts among affected members. We documented asymmetry between eyes in the morphology, location within the lens, color and density of cataracts, and a variable rate of progression. CONCLUSIONS The cataracts in these families exhibit wide intrafamilial and interocular phenotypic variability, supporting the premise that the mutated genes are expressed differentially in individuals and between eyes; other genes or environmental factors may be the bases for this variability. Marked progression among some family members underscores the variable clinical course of a common mutation within a family. Like retinitis pigmentosa, classification of ADC will be most useful if based on the gene and specific mutation. PMID:16564818

The use of digital PCR to improve the application of quantitative molecular diagnostic methods for tuberculosis.

PubMed

Devonshire, Alison S; O'Sullivan, Denise M; Honeyborne, Isobella; Jones, Gerwyn; Karczmarczyk, Maria; Pavšič, Jernej; Gutteridge, Alice; Milavec, Mojca; Mendoza, Pablo; Schimmel, Heinz; Van Heuverswyn, Fran; Gorton, Rebecca; Cirillo, Daniela Maria; Borroni, Emanuele; Harris, Kathryn; Barnard, Marinus; Heydenrych, Anthenette; Ndusilo, Norah; Wallis, Carole L; Pillay, Keshree; Barry, Thomas; Reddington, Kate; Richter, Elvira; Mozioğlu, Erkan; Akyürek, Sema; Yalçınkaya, Burhanettin; Akgoz, Muslum; Žel, Jana; Foy, Carole A; McHugh, Timothy D; Huggett, Jim F

2016-08-03

Real-time PCR (qPCR) based methods, such as the Xpert MTB/RIF, are increasingly being used to diagnose tuberculosis (TB). While qualitative methods are adequate for diagnosis, the therapeutic monitoring of TB patients requires quantitative methods currently performed using smear microscopy. The potential use of quantitative molecular measurements for therapeutic monitoring has been investigated but findings have been variable and inconclusive. The lack of an adequate reference method and reference materials is a barrier to understanding the source of such disagreement. Digital PCR (dPCR) offers the potential for an accurate method for quantification of specific DNA sequences in reference materials which can be used to evaluate quantitative molecular methods for TB treatment monitoring. To assess a novel approach for the development of quality assurance materials we used dPCR to quantify specific DNA sequences in a range of prototype reference materials and evaluated accuracy between different laboratories and instruments. The materials were then also used to evaluate the quantitative performance of qPCR and Xpert MTB/RIF in eight clinical testing laboratories. dPCR was found to provide results in good agreement with the other methods tested and to be highly reproducible between laboratories without calibration even when using different instruments. When the reference materials were analysed with qPCR and Xpert MTB/RIF by clinical laboratories, all laboratories were able to correctly rank the reference materials according to concentration, however there was a marked difference in the measured magnitude. TB is a disease where the quantification of the pathogen could lead to better patient management and qPCR methods offer the potential to rapidly perform such analysis. However, our findings suggest that when precisely characterised materials are used to evaluate qPCR methods, the measurement result variation is too high to determine whether molecular quantification of Mycobacterium tuberculosis would provide a clinically useful readout. The methods described in this study provide a means by which the technical performance of quantitative molecular methods can be evaluated independently of clinical variability to improve accuracy of measurement results. These will assist in ultimately increasing the likelihood that such approaches could be used to improve patient management of TB.

A Non-Invasive Method for Estimating Cardiopulmonary Variables Using Breath-by-Breath Injection of Two Tracer Gases.

PubMed

Clifton, Lei; Clifton, David A; Hahn, Clive E W; Farmeryy, Andrew D

2013-01-01

Conventional methods for estimating cardiopulmonary variables usually require complex gas analyzers and the active co-operation of the patient. Therefore, they are not compatible with the crowded environment of the intensive care unit (ICU) or operating theatre, where patient co-operation is typically impossible. However, it is these patients that would benefit the most from accurate estimation of cardiopulmonary variables, because of their critical condition. This paper describes the results of a collaborative development between an anesthesiologists and biomedical engineers to create a compact and non-invasive system for the measurement of cardiopulmonary variables such as lung volume, airway dead space volume, and pulmonary blood flow. In contrast with conventional methods, the compact apparatus and non-invasive nature of the proposed method allow it to be used in the ICU, as well as in general clinical settings. We propose the use of a non-invasive method, in which tracer gases are injected into the patient's inspired breath, and the concentration of the tracer gases is subsequently measured. A novel breath-by-breath tidal ventilation model is then used to estimate the value of a patient's cardiopulmonary variables. Experimental results from an artificial lung demonstrate minimal error in the estimation of known parameters using the proposed method. Results from analysis of a cohort of 20 healthy volunteers (within the Oxford University Hospitals NHS Trust) show that the values of estimated cardiopulmonary variables from these subjects lies within the expected ranges. Advantages of this method are that it is non-invasive, compact, portable, and can perform analysis in real time with less than 1 min of acquired respiratory data.

Do team processes really have an effect on clinical performance? A systematic literature review.

PubMed

Schmutz, J; Manser, T

2013-04-01

There is a growing literature on the relationship between team processes and clinical performance. The purpose of this review is to summarize these articles and examine the impact of team process behaviours on clinical performance. We conducted a literature search in five major databases. Inclusion criteria were: English peer-reviewed papers published between January 2001 and May 2012, which showed or tried to show (i) a statistical relationship of a team process variable and clinical performance or (ii) an improvement of a performance variable through a team process intervention. Study quality was assessed using predefined quality indicators. For every study, we calculated the relevant effect sizes. We included 28 studies in the review, seven of which were intervention studies. Every study reported at least one significant relationship between team processes or an intervention and performance. Also, some non-significant effects were reported. Most of the reported effect sizes were large or medium. The study quality ranged from medium to high. The studies are highly diverse regarding the specific team process behaviours investigated and also regarding the methods used. However, they suggest that team process behaviours do influence clinical performance and that training results in increased performance. Future research should rely on existing theoretical frameworks, valid, and reliable methods to assess processes such as teamwork or coordination and focus on the development of adequate tools to assess process performance, linking them with outcomes in the clinical setting.

Fatigue as a Driver of Overall Quality of Life in Cancer Patients

PubMed Central

McCabe, Ryan M.; Grutsch, James F.; Braun, Donald P.; Nutakki, Swetha B.

2015-01-01

Background This manuscript describes an approach for analyzing large amounts of disparate clinical data to elucidate the most impactful factor(s) that relate to a meaningful clinical outcome, in this case, the quality of life of cancer patients. The relationships between clinical and quality of life variables were evaluated using the EORTC QLQ-C30 global health domain—a validated surrogate variable for overall cancer patient well-being. Methods A cross-sectional study design was used to evaluate the determinants of global health in cancer patients who initiated treatment at two regional medical centers between January 2001 and December 2009. Variables analyzed included 15 EORTC QLQ-C30 scales, age at diagnosis, gender, newly diagnosed/ recurrent disease status, and stage. The decision tree algorithm, perhaps unfamiliar to practicing clinicians, evaluates the relative contribution of individual parameters in classifying a clinically meaningful functional endpoint, such as the global health of a patient. Findings Multiple patient characteristics were identified as important contributors. Fatigue, in particular, emerged as the most prevalent indicator of cancer patients’ quality of life in 16/23 clinically relevant subsets. This analysis allowed results to be stated in a clinically-intuitive, rule set format using the language and quantities of the Quality of Life (QoL) tool itself. Interpretation By applying the classification algorithms to a large data set, identification of fatigue as a root factor in driving global health and overall QoL was revealed. The ability to practice mining of clinical data sets to uncover critical clinical insights that are immediately applicable to patient care practices is illustrated. PMID:26070133

Motivation factors for suicidal behavior and their clinical relevance in admitted psychiatric patients.

PubMed

Hayashi, Naoki; Igarashi, Miyabi; Imai, Atsushi; Yoshizawa, Yuka; Asamura, Kaori; Ishikawa, Yoichi; Tokunaga, Taro; Ishimoto, Kayo; Tatebayashi, Yoshitaka; Harima, Hirohiko; Kumagai, Naoki; Ishii, Hidetoki; Okazaki, Yuji

2017-01-01

Suicidal behavior (SB) is a major, worldwide health concern. To date there is limited understanding of the associated motivational aspects which accompany this self-initiated conduct. To develop a method for identifying motivational features associated with SB by studying admitted psychiatric patients, and to examine their clinical relevance. By performing a factor analytic study using data obtained from a patient sample exhibiting high suicidality and a variety of SB methods, Motivations for SB Scale (MSBS) was constructed to measure the features. Data included assessments of DSM-IV psychiatric and personality disorders, suicide intent, depressive symptomatology, overt aggression, recent life events (RLEs) and methods of SB, collated from structured interviews. Association of identified features with clinical variables was examined by correlation analyses and MANCOVA. Factor analyses elicited a 4-factor solution composed of Interpersonal-testing (IT), Interpersonal-change (IC), Self-renunciation (SR) and Self-sustenance (SS). These factors were classified according to two distinctions, namely interpersonal vs. intra-personal directedness, and the level of assumed influence by SB or the relationship to prevailing emotions. Analyses revealed meaningful links between patient features and clinical variables. Interpersonal-motivations (IT and IC) were associated with overt aggression, low suicidality and RLE discord or conflict, while SR was associated with depression, high suicidality and RLE separation or death. Borderline personality disorder showed association with IC and SS. When self-strangulation was set as a reference SB method, self-cutting and overdose-taking were linked to IT and SS, respectively. The factors extracted in this study largely corresponded to factors from previous studies, implying that they may be useful in a wider clinical context. The association of these features with SB-related factors suggests that they constitute an integral part of the process leading to SB. These results provide a base for further research into clinical strategies for patient management and therapy.

Quality controls in cellular immunotherapies: rapid assessment of clinical grade dendritic cells by gene expression profiling.

PubMed

Castiello, Luciano; Sabatino, Marianna; Zhao, Yingdong; Tumaini, Barbara; Ren, Jiaqiang; Ping, Jin; Wang, Ena; Wood, Lauren V; Marincola, Francesco M; Puri, Raj K; Stroncek, David F

2013-02-01

Cell-based immunotherapies are among the most promising approaches for developing effective and targeted immune response. However, their clinical usefulness and the evaluation of their efficacy rely heavily on complex quality control assessment. Therefore, rapid systematic methods are urgently needed for the in-depth characterization of relevant factors affecting newly developed cell product consistency and the identification of reliable markers for quality control. Using dendritic cells (DCs) as a model, we present a strategy to comprehensively characterize manufactured cellular products in order to define factors affecting their variability, quality and function. After generating clinical grade human monocyte-derived mature DCs (mDCs), we tested by gene expression profiling the degrees of product consistency related to the manufacturing process and variability due to intra- and interdonor factors, and how each factor affects single gene variation. Then, by calculating for each gene an index of variation we selected candidate markers for identity testing, and defined a set of genes that may be useful comparability and potency markers. Subsequently, we confirmed the observed gene index of variation in a larger clinical data set. In conclusion, using high-throughput technology we developed a method for the characterization of cellular therapies and the discovery of novel candidate quality assurance markers.

Quantifying temporal glucose variability in diabetes via continuous glucose monitoring: mathematical methods and clinical application.

PubMed

Kovatchev, Boris P; Clarke, William L; Breton, Marc; Brayman, Kenneth; McCall, Anthony

2005-12-01

Continuous glucose monitors (CGMs) collect detailed blood glucose (BG) time series, which carry significant information about the dynamics of BG fluctuations. In contrast, the methods for analysis of CGM data remain those developed for infrequent BG self-monitoring. As a result, important information about the temporal structure of the data is lost during the translation of raw sensor readings into clinically interpretable statistics and images. The following mathematical methods are introduced into the field of CGM data interpretation: (1) analysis of BG rate of change; (2) risk analysis using previously reported Low/High BG Indices and Poincare (lag) plot of risk associated with temporal BG variability; and (3) spatial aggregation of the process of BG fluctuations and its Markov chain visualization. The clinical application of these methods is illustrated by analysis of data of a patient with Type 1 diabetes mellitus who underwent islet transplantation and with data from clinical trials. Normative data [12,025 reference (YSI device, Yellow Springs Instruments, Yellow Springs, OH) BG determinations] in patients with Type 1 diabetes mellitus who underwent insulin and glucose challenges suggest that the 90%, 95%, and 99% confidence intervals of BG rate of change that could be maximally sustained over 15-30 min are [-2,2], [-3,3], and [-4,4] mg/dL/min, respectively. BG dynamics and risk parameters clearly differentiated the stages of transplantation and the effects of medication. Aspects of treatment were clearly visualized by graphs of BG rate of change and Low/High BG Indices, by a Poincare plot of risk for rapid BG fluctuations, and by a plot of the aggregated Markov process. Advanced analysis and visualization of CGM data allow for evaluation of dynamical characteristics of diabetes and reveal clinical information that is inaccessible via standard statistics, which do not take into account the temporal structure of the data. The use of such methods improves the assessment of patients' glycemic control.

[Comparison of three methods for measuring multiple morbidity according to the use of health resources in primary healthcare].

PubMed

Sicras-Mainar, Antoni; Velasco-Velasco, Soledad; Navarro-Artieda, Ruth; Blanca Tamayo, Milagrosa; Aguado Jodar, Alba; Ruíz Torrejón, Amador; Prados-Torres, Alexandra; Violan-Fors, Concepción

2012-06-01

To compare three methods of measuring multiple morbidity according to the use of health resources (cost of care) in primary healthcare (PHC). Retrospective study using computerized medical records. Thirteen PHC teams in Catalonia (Spain). Assigned patients requiring care in 2008. The socio-demographic variables were co-morbidity and costs. Methods of comparison were: a) Combined Comorbidity Index (CCI): an index itself was developed from the scores of acute and chronic episodes, b) Charlson Index (ChI), and c) Adjusted Clinical Groups case-mix: resource use bands (RUB). The cost model was constructed by differentiating between fixed (operational) and variable costs. 3 multiple lineal regression models were developed to assess the explanatory power of each measurement of co-morbidity which were compared from the determination coefficient (R(2)), p< .05. The study included 227,235 patients. The mean unit of cost was €654.2. The CCI explained an R(2)=50.4%, the ChI an R(2)=29.2% and BUR an R(2)=39.7% of the variability of the cost. The behaviour of the ICC is acceptable, albeit with low scores (1 to 3 points), showing inconclusive results. The CCI may be a simple method of predicting PHC costs in routine clinical practice. If confirmed, these results will allow improvements in the comparison of the case-mix. Copyright © 2011 Elsevier España, S.L. All rights reserved.

Determinants of successful clinical networks: the conceptual framework and study protocol.

PubMed

Haines, Mary; Brown, Bernadette; Craig, Jonathan; D'Este, Catherine; Elliott, Elizabeth; Klineberg, Emily; McInnes, Elizabeth; Middleton, Sandy; Paul, Christine; Redman, Sally; Yano, Elizabeth M

2012-03-13

Clinical networks are increasingly being viewed as an important strategy for increasing evidence-based practice and improving models of care, but success is variable and characteristics of networks with high impact are uncertain. This study takes advantage of the variability in the functioning and outcomes of networks supported by the Australian New South Wales (NSW) Agency for Clinical Innovation's non-mandatory model of clinical networks to investigate the factors that contribute to the success of clinical networks. The objective of this retrospective study is to examine the association between external support, organisational and program factors, and indicators of success among 19 clinical networks over a three-year period (2006-2008). The outcomes (health impact, system impact, programs implemented, engagement, user perception, and financial leverage) and explanatory factors will be collected using a web-based survey, interviews, and record review. An independent expert panel will provide judgements about the impact or extent of each network's initiatives on health and system impacts. The ratings of the expert panel will be the outcome used in multivariable analyses. Following the rating of network success, a qualitative study will be conducted to provide a more in-depth examination of the most successful networks. This is the first study to combine quantitative and qualitative methods to examine the factors that contribute to the success of clinical networks and, more generally, is the largest study of clinical networks undertaken. The adaptation of expert panel methods to rate the impacts of networks is the methodological innovation of this study. The proposed project will identify the conditions that should be established or encouraged by agencies developing clinical networks and will be of immediate use in forming strategies and programs to maximise the effectiveness of such networks.

Clinical validity of prototype personality disorder ratings in adolescents.

PubMed

Defife, Jared A; Haggerty, Greg; Smith, Scott W; Betancourt, Luis; Ahmed, Zain; Ditkowsky, Keith

2015-01-01

A growing body of research shows that personality pathology in adolescents is clinically distinctive and frequently stable into adulthood. A reliable and useful method for rating personality pathology in adolescent patients has the potential to enhance conceptualization, dissemination, and treatment effectiveness. The aim of this study is to examine the clinical validity of a prototype matching approach (derived from the Shedler Westen Assessment Procedure-Adolescent Version) for quantifying personality pathology in an adolescent inpatient sample. Sixty-six adolescent inpatients and their parents or legal guardians completed forms of the Child Behavior Checklist (CBCL) assessing emotional and behavioral problems. Clinical criterion variables including suicide history, substance use, and fights with peers were also assessed. Patients' individual and group therapists on the inpatient unit completed personality prototype ratings. Prototype diagnoses demonstrated substantial reliability (median intraclass correlation coefficient =.75) across independent ratings from individual and group therapists. Personality prototype ratings correlated with the CBCL scales and clinical criterion variables in anticipated and meaningful ways. As seen in prior research with adult samples, prototype personality ratings show clinical validity across independent clinician raters previously unfamiliar with the approach, and they are meaningfully related to clinical symptoms, behavioral problems, and adaptive functioning.

Clinical Validity of Prototype Personality Disorder Ratings in Adolescents

PubMed Central

DeFife, Jared A.; Haggerty, Greg; Smith, Scott W.; Betancourt, Luis; Ahmed, Zain; Ditkowsky, Keith

2015-01-01

A growing body of research shows that personality pathology in adolescents is clinically distinctive and frequently stable into adulthood. A reliable and useful method for rating personality pathology in adolescent patients has the potential to enhance conceptualization, dissemination, and treatment effectiveness. The aim of this study is to examine the clinical validity of a prototype matching approach (derived from the Shedler Westen Assessment Procedure – Adolescent Version) for quantifying personality pathology in an adolescent inpatient sample. Sixty-six adolescent inpatients and their parents or legal guardians completed forms of the Child Behavior Checklist (CBCL) assessing emotional and behavioral problems. Clinical criterion variables including suicide history, substance use, and fights with peers were also assessed. Patients’ individual and group therapists on the inpatient unit completed personality prototype ratings. Prototype diagnoses demonstrated substantial reliability (median ICC = .75) across independent ratings from individual and group therapists. Personality prototype ratings correlated with the CBCL scales and clinical criterion variables in anticipated and meaningful ways. As seen in prior research with adult samples, prototype personality ratings show clinical validity across independent clinician raters previously unfamiliar with the approach, and they are meaningfully related to clinical symptoms, behavioral problems, and adaptive functioning. PMID:25457971

Quantification of topographic changes in the surface of back of young patients monitored for idiopathic scoliosis: correlation with radiographic variables

NASA Astrophysics Data System (ADS)

Pino-Almero, Laura; Mínguez-Rey, María Fe; Sentamans-Segarra, Salvador; Salvador-Palmer, María Rosario; Anda, Rosa María Cibrián-Ortiz de; La O, Javier López-de

2016-11-01

Idiopathic scoliosis requires a close follow-up while the patient is skeletally immature to detect early progression. Patients who are monitored by radiographs are exposed to high doses of ionizing radiation. The purpose of this study is to evaluate if an optic noninvasive method of back surface topography based on structured light would be clinically useful in the follow-up of young patients with idiopathic scoliosis. This could reduce the number of radiographs made on these children. Thirty-one patients with idiopathic scoliosis were submitted twice to radiograph and our topographic method at intervals of 6 months to 1 year. Three topographical variables were applied horizontal plane deformity index (DHOPI), posterior trunk symmetry index (POTSI), and columnar profile (PC). A statistically significant correlation was found between variations of Cobb angle with DHOPI (r=0.720, p<0.01) and POTSI (r=0.753, p<0.01) during the monitoring period. Hence, this topographic method could be useful in clinical practice as an objective adjuvant tool in routine follow-up of scoliosis.

Optimization of Answer Keys for Script Concordance Testing: Should We Exclude Deviant Panelists, Deviant Responses, or Neither?

ERIC Educational Resources Information Center

Gagnon, Robert; Lubarsky, Stuart; Lambert, Carole; Charlin, Bernard

2011-01-01

The Script Concordance Test (SCT) uses a panel-based, aggregate scoring method that aims to capture the variability of responses of experienced practitioners to particular clinical situations. The use of this type of scoring method is a key determinant of the tool's discriminatory power, but deviant answers could potentially diminish the…

A three-dimensional comparison of a morphometric and conventional cephalometric midsagittal planes for craniofacial asymmetry.

PubMed

Damstra, Janalt; Fourie, Zacharias; De Wit, Marnix; Ren, Yijin

2012-02-01

Morphometric methods are used in biology to study object symmetry in living organisms and to determine the true plane of symmetry. The aim of this study was to determine if there are clinical differences between three-dimensional (3D) cephalometric midsagittal planes used to describe craniofacial asymmetry and a true symmetry plane derived from a morphometric method based on visible facial features. The sample consisted of 14 dry skulls (9 symmetric and 5 asymmetric) with metallic markers which were imaged with cone-beam computed tomography. An error study and statistical analysis were performed to validate the morphometric method. The morphometric and conventional cephalometric planes were constructed and compared. The 3D cephalometric planes constructed as perpendiculars to the Frankfort horizontal plane resembled the morphometric plane the most in both the symmetric and asymmetric groups with mean differences of less than 1.00 mm for most variables. However, the standard deviations were often large and clinically significant for these variables. There were clinically relevant differences (>1.00 mm) between the different 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features. The difference between 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features were clinically relevant. Care has to be taken using cephalometric midsagittal planes for diagnosis and treatment planning of craniofacial asymmetry as they might differ from the true plane of symmetry as determined by morphometrics.

Variability in objective and subjective measures affects baseline values in studies of patients with COPD

PubMed Central

Ha, Jae Wook; Couper, David J.; O’Neal, Wanda K.; Barr, R. Graham; Bleecker, Eugene R.; Carretta, Elizabeth E.; Cooper, Christopher B.; Doerschuk, Claire M.; Drummond, M Bradley; Han, MeiLan K.; Hansel, Nadia N.; Kim, Victor; Kleerup, Eric C.; Martinez, Fernando J.; Rennard, Stephen I.; Tashkin, Donald; Woodruff, Prescott G.; Paine, Robert; Curtis, Jeffrey L.; Kanner, Richard E.

2017-01-01

Rationale Understanding the reliability and repeatability of clinical measurements used in the diagnosis, treatment and monitoring of disease progression is of critical importance across all disciplines of clinical practice and in clinical trials to assess therapeutic efficacy and safety. Objectives Our goal is to understand normal variability for assessing true changes in health status and to more accurately utilize this data to differentiate disease characteristics and outcomes. Methods Our study is the first study designed entirely to establish the repeatability of a large number of instruments utilized for the clinical assessment of COPD in the same subjects over the same period. We utilized SPIROMICS participants (n = 98) that returned to their clinical center within 6 weeks of their baseline visit to repeat complete baseline assessments. Demographics, spirometry, questionnaires, complete blood cell counts (CBC), medical history, and emphysema status by computerized tomography (CT) imaging were obtained. Results Pulmonary function tests (PFTs) were highly repeatable (ICC’s >0.9) but the 6 minute walk (6MW) was less so (ICC = 0.79). Among questionnaires, the Saint George’s Respiratory Questionnaire (SGRQ) was most repeatable. Self-reported clinical features, such as exacerbation history, and features of chronic bronchitis, often produced kappa values <0.6. Reported age at starting smoking and average number of cigarettes smoked were modestly repeatable (kappa = 0.76 and 0.79). Complete blood counts (CBC) variables produced intraclass correlation coefficients (ICC) values between 0.6 and 0.8. Conclusions PFTs were highly repeatable, while subjective measures and subject recall were more variable. Analyses using features with poor repeatability could lead to misclassification and outcome errors. Hence, care should be taken when interpreting change in clinical features based on measures with low repeatability. Efforts to improve repeatability of key clinical features such as exacerbation history and chronic bronchitis are warranted. PMID:28934249

Mediators and moderators in early intervention research

PubMed Central

Breitborde, Nicholas J. K.; Srihari, Vinod H.; Pollard, Jessica M.; Addington, Donald N.; Woods, Scott W.

2015-01-01

Aim The goal of this paper is to provide clarification with regard to the nature of mediator and moderator variables and the statistical methods used to test for the existence of these variables. Particular attention will be devoted to discussing the ways in which the identification of mediator and moderator variables may help to advance the field of early intervention in psychiatry. Methods We completed a literature review of the methodological strategies used to test for mediator and moderator variables. Results Although several tests for mediator variables are currently available, recent evaluations suggest that tests which directly evaluate the indirect effect are superior. With regard to moderator variables, two approaches (‘pick-a-point’ and regions of significance) are available, and we provide guidelines with regard to how researchers can determine which approach may be most appropriate to use for their specific study. Finally, we discuss how to evaluate the clinical importance of mediator and moderator relationships as well as the methodology to calculate statistical power for tests of mediation and moderation. Conclusion Further exploration of mediator and moderator variables may provide valuable information with regard to interventions provided early in the course of a psychiatric illness. PMID:20536970

Motivational journey of Iranian bachelor of nursing students during clinical education: a grounded theory study.

PubMed

Hanifi, Nasrin; Parvizy, Soroor; Joolaee, Soodabeh

2013-09-01

This study explored how nursing students can be kept motivated throughout their clinical education. Motivation is a key issue in nursing clinical education for student retention. The study was conducted using grounded theory methods, which are appropriate when studying process in a social context. Sixteen students and four instructors, who were purposefully selected, participated in semistructured interviews. Data were analyzed using the constant comparative method. Students' motivational journey occurred in three steps: (i) social condition; (ii) encountering the clinical education challenges; and (iii) looking for an escape from nursing, or simply tolerating nursing. Struggling with professional identity emerged as the core variable. Iran's social context and many other conditions in the clinical education setting affect students' motivation. Identifying motivational process might assist educational authorities in offering solutions to promote motivation among students. © 2013 Wiley Publishing Asia Pty Ltd.

Electronic Cigarettes for Smoking Cessation.

PubMed

Orellana-Barrios, Menfil A; Payne, Drew; Medrano-Juarez, Rita M; Yang, Shengping; Nugent, Kenneth

2016-10-01

The use of electronic cigarettes (e-cigarettes) is increasing, but their use as a smoking-cessation aid is controversial. The reporting of e-cigarette studies on cessation is variable and inconsistent. To date, only 1 randomized clinical trial has included an arm with other cessation methods (nicotine patches). The cessation rates for available clinical trials are difficult to compare given differing follow-up periods and broad ranges (4% at 12 months with non-nicotine e-cigarettes to 68% at 4 weeks with concomitant nicotine e-cigarettes and other cessation methods). The average combined abstinence rate for included prospective studies was 29.1% (combination of 6-18 months׳ rates). There are few comparable clinical trials and prospective studies related to e-cigarettes use for smoking cessation, despite an increasing number of citations. Larger randomized clinical trials are essential to determine whether e-cigarettes are effective smoking-cessation devices. Copyright © 2016 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

Validation of a Nutrition Screening Tool for Pediatric Patients with Cystic Fibrosis.

PubMed

Souza Dos Santos Simon, Miriam Isabel; Forte, Gabriele Carra; da Silva Pereira, Juliane; da Fonseca Andrade Procianoy, Elenara; Drehmer, Michele

2016-05-01

In cystic fibrosis (CF), nutrition diagnosis is of critical relevance because the early identification of nutrition-related compromise enables early, adequate intervention and, consequently, influences patient prognosis. Up to now, there has not been a validated nutrition screening tool that takes into consideration clinical variables. To validate a specific nutritional risk screening tool for patients with CF based on clinical variables, anthropometric parameters, and dietary intake. Cross-sectional study. The nutrition screening tool was compared with a risk screening tool proposed by McDonald and the Cystic Fibrosis Foundation criteria. Patients aged 6 to 18 years, with a diagnosis of CF confirmed by two determinations of elevated chloride level in sweat (sweat test) and/or by identification of two CF-associated genetic mutations who were receiving follow-up care through the outpatient clinic of a Cystic Fibrosis Treatment Center. Earlier identification of nutritional risk in CF patients aged 6 to 18 years when a new screening tool was applied. Agreement among the tested methods was assessed by means of the kappa coefficient for categorical variables. Sensitivity, specificity, and accuracy values were calculated. The significance level was set at 5% (P<0.05). Statistical analyses were carried out in PASW Statistics for Windows version 18.0 (2009, SPSS Inc). Eighty-two patients (49% men, aged 6 to 18 years) were enrolled in the study. The agreement between the proposed screening tool and the tool for screening nutritional risk for CF by the McDonald method was good (κ=0.804; P<0.001) and the sensitivity and specificity was 85% and 95%, respectively. Agreement with the Cystic Fibrosis Foundation criteria was lower (κ=0.418; P<0.001), and the sensitivity and specificity were both 72%. The proposed screening tool with defined clinical variables promotes earlier identification of nutritional risk in pediatric patients with CF. Copyright © 2016 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy Ageing.

PubMed

Costa, Patrício Soares; Santos, Nadine Correia; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno

2013-01-01

The main focus of this study was to illustrate the applicability of multiple correspondence analysis (MCA) in detecting and representing underlying structures in large datasets used to investigate cognitive ageing. Principal component analysis (PCA) was used to obtain main cognitive dimensions, and MCA was used to detect and explore relationships between cognitive, clinical, physical, and lifestyle variables. Two PCA dimensions were identified (general cognition/executive function and memory), and two MCA dimensions were retained. Poorer cognitive performance was associated with older age, less school years, unhealthier lifestyle indicators, and presence of pathology. The first MCA dimension indicated the clustering of general/executive function and lifestyle indicators and education, while the second association was between memory and clinical parameters and age. The clustering analysis with object scores method was used to identify groups sharing similar characteristics. The weaker cognitive clusters in terms of memory and executive function comprised individuals with characteristics contributing to a higher MCA dimensional mean score (age, less education, and presence of indicators of unhealthier lifestyle habits and/or clinical pathologies). MCA provided a powerful tool to explore complex ageing data, covering multiple and diverse variables, showing if a relationship exists and how variables are related, and offering statistical results that can be seen both analytically and visually.

Anxiety, Depression and Hopelessness in Adolescents: A Structural Equation Model

PubMed Central

Cunningham, Shaylyn; Gunn, Thelma; Alladin, Assen; Cawthorpe, David

2008-01-01

Objective This study tested a structural model, examining the relationship between a latent variable termed demoralization and measured variables (anxiety, depression and hopelessness) in a community sample of Canadian youth. Methods The combined sample consisted of data collected from four independent studies from 2001 to 2005. Nine hundred and seventy one (n=971) participants were high school students (grades 10–12) from three geographic locations: Calgary, Saskatchewan and Lethbridge. Participants completed the Beck Anxiety Inventory (BAI), Beck Depression Inventory-Revised (BDI-II), Beck Hopelessness Scale (BHS), and demographic survey. Structural equation modeling was used for statistical analysis. Results The analysis revealed that the final model, including depression, anxiety and hopelessness and one latent variable demoralization, fit the data (chi-square value, X2 (2) = 7.25, p< .001, goodness of fit indices (CFI=0.99, NFI=0.98) and standardized error (0.05). Overall, the findings suggest that close relationships exist among depression, anxiety, hopelessness and demoralization that is stable across demographic variables. Further, the model explains the relationship between sub-clinical anxiety, depression and hopelessness. Conclusion These findings contribute to a theoretical framework, which has implications for educational and clinical intervention. The present findings will help guide further preventative research on examining demoralization as a precursor to sub-clinical anxiety and depression. PMID:18769644

ZAP-70 staining in chronic lymphocytic leukemia.

PubMed

Villamor, Neus

2005-05-01

Chronic lymphocytic leukemia (CLL) is the most common chronic leukemia in Western countries. The disease has an extremely variable clinical course, and several prognostic features have been identified to assess individual risk. The configuration of the immunoglobulin variable heavy-chain gene (IgV(H)) is a strong predictor of the outcome. CLL patients with unmutated IgV(H) status have an aggressive clinical course and a short survival. Unfortunately, analysis of IgV(H) gene configuration is not available in most clinical laboratories. A small number of genes are differentially expressed between unmutated IgV(H) and mutated IgV(H) clinical forms of CLL. One of these genes is ZAP-70, which is detected in leukemic cells from patients with the unmutated IgV(H) form of CLL. Flow cytometry presents advantages over other methods to detect ZAP-70, and its quantification by flow cytometry has proved its predictive value. This unit focuses on protocols to quantify ZAP-70 by flow cytometry in CLL.

Latent class instrumental variables: a clinical and biostatistical perspective.

PubMed

Baker, Stuart G; Kramer, Barnett S; Lindeman, Karen S

2016-01-15

In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research. Copyright © 2015 John Wiley & Sons, Ltd.

Correcting for Optimistic Prediction in Small Data Sets

PubMed Central

Smith, Gordon C. S.; Seaman, Shaun R.; Wood, Angela M.; Royston, Patrick; White, Ian R.

2014-01-01

The C statistic is a commonly reported measure of screening test performance. Optimistic estimation of the C statistic is a frequent problem because of overfitting of statistical models in small data sets, and methods exist to correct for this issue. However, many studies do not use such methods, and those that do correct for optimism use diverse methods, some of which are known to be biased. We used clinical data sets (United Kingdom Down syndrome screening data from Glasgow (1991–2003), Edinburgh (1999–2003), and Cambridge (1990–2006), as well as Scottish national pregnancy discharge data (2004–2007)) to evaluate different approaches to adjustment for optimism. We found that sample splitting, cross-validation without replication, and leave-1-out cross-validation produced optimism-adjusted estimates of the C statistic that were biased and/or associated with greater absolute error than other available methods. Cross-validation with replication, bootstrapping, and a new method (leave-pair-out cross-validation) all generated unbiased optimism-adjusted estimates of the C statistic and had similar absolute errors in the clinical data set. Larger simulation studies confirmed that all 3 methods performed similarly with 10 or more events per variable, or when the C statistic was 0.9 or greater. However, with lower events per variable or lower C statistics, bootstrapping tended to be optimistic but with lower absolute and mean squared errors than both methods of cross-validation. PMID:24966219

Predictors and Moderators of Response to Cognitive Behavioral Therapy and Medication for the Treatment of Binge Eating Disorder

PubMed Central

Grilo, Carlos. M.; Masheb, Robin M.; Crosby, Ross D.

2012-01-01

Objective To examine predictors and moderators of response to cognitive-behavioral therapy (CBT) and medication treatments for binge-eating disorder (BED). Method 108 BED patients in a randomized double-blind placebo-controlled trial testing CBT and fluoxetine treatments were assessed prior, throughout-, and post-treatment. Demographic factors, psychiatric and personality-disorder co-morbidity, eating-disorder psychopathology, psychological features, and two sub-typing methods (negative-affect, overvaluation of shape/weight) were tested as predictors and moderators for the primary outcome of remission from binge-eating and four secondary dimensional outcomes (binge-eating frequency, eating-disorder psychopathology, depression, and body mass index). Mixed-effects-models analyzed all available data for each outcome variable. In each model, effects for baseline value and treatment were included with tests of both prediction and moderator effects. Results Several demographic and clinical variables significantly predicted and/or moderated outcomes. One demographic variable signaled a statistical advantage for medication-only (younger participants had greater binge-eating reductions) whereas several demographic and clinical variables (lower self-esteem, negative-affect, and overvaluation of shape/weight) signaled better improvements if receiving CBT. Overvaluation was the most salient predictor/moderator of outcomes. Overvaluation significantly predicted binge-eating remission (29% of participants with versus 57% of participants without overvaluation remitted). Overvaluation was especially associated with lower remission rates if receiving medication-only (10% versus 42% for participants without overvaluation). Overvaluation moderated dimensional outcomes: participants with overvaluation had significantly greater reductions in eating-disorder psychopathology and depression levels if receiving CBT. Overvaluation predictor/moderator findings persisted after controlling for negative-affect. Conclusions Our findings have clinical utility for prescription of CBT and medication and implications for refinement of the BED diagnosis. PMID:22289130

Fasting Insulin Levels and Metabolic Risk Factors in Type 2 Diabetic Patients at the First Visit in Japan

PubMed Central

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-01-01

OBJECTIVE To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. RESEARCH DESIGN AND METHODS In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. RESULTS Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. CONCLUSIONS During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs. PMID:22665215

The Complexity of Clinical Huntington's Disease: Developments in Molecular Genetics, Neuropathology and Neuroimaging Biomarkers.

PubMed

Tippett, Lynette J; Waldvogel, Henry J; Snell, Russell G; Vonsattel, Jean-Paul; Young, Anne B; Faull, Richard L M

2017-01-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder characterised by extensive neuronal loss in the striatum and cerebral cortex, and a triad of clinical symptoms affecting motor, cognitive/behavioural and mood functioning. The mutation causing HD is an expansion of a CAG tract in exon 1 of the HTT gene. This chapter provides a multifaceted overview of the clinical complexity of HD. We explore recent directions in molecular genetics including the identification of loci that are genetic modifiers of HD that could potentially reveal therapeutic targets beyond the HTT gene transcript and protein. The variability of clinical symptomatology in HD is considered alongside recent findings of variability in cellular and neurochemical changes in the striatum and cerebral cortex in human brain. We review evidence from structural neuroimaging methods of progressive changes of striatum, cerebral cortex and white matter in pre-symptomatic and symptomatic HD, with a particular focus on the potential identification of neuroimaging biomarkers that could be used to test promising disease-specific and modifying treatments. Finally we provide an overview of completed clinical trials in HD and future therapeutic developments.

A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals.

PubMed

Gold, Nathan; Frasch, Martin G; Herry, Christophe L; Richardson, Bryan S; Wang, Xiaogang

2017-01-01

Experimentally and clinically collected time series data are often contaminated with significant confounding noise, creating short, noisy time series. This noise, due to natural variability and measurement error, poses a challenge to conventional change point detection methods. We propose a novel and robust statistical method for change point detection for noisy biological time sequences. Our method is a significant improvement over traditional change point detection methods, which only examine a potential anomaly at a single time point. In contrast, our method considers all suspected anomaly points and considers the joint probability distribution of the number of change points and the elapsed time between two consecutive anomalies. We validate our method with three simulated time series, a widely accepted benchmark data set, two geological time series, a data set of ECG recordings, and a physiological data set of heart rate variability measurements of fetal sheep model of human labor, comparing it to three existing methods. Our method demonstrates significantly improved performance over the existing point-wise detection methods.

Combined Dynamic Contrast Enhanced Liver MRI and MRA Using Interleaved Variable Density Sampling

PubMed Central

Rahimi, Mahdi Salmani; Korosec, Frank R.; Wang, Kang; Holmes, James H.; Motosugi, Utaroh; Bannas, Peter; Reeder, Scott B.

2014-01-01

Purpose To develop and evaluate a method for volumetric contrast-enhanced MR imaging of the liver, with high spatial and temporal resolutions, for combined dynamic imaging and MR angiography using a single injection of contrast. Methods An interleaved variable density (IVD) undersampling pattern was implemented in combination with a real-time-triggered, time-resolved, dual-echo 3D spoiled gradient echo sequence. Parallel imaging autocalibration lines were acquired only once during the first time-frame. Imaging was performed in ten subjects with focal nodular hyperplasia (FNH) and compared with their clinical MRI. The angiographic phase of the proposed method was compared to a dedicated MR angiogram acquired during a second injection of contrast. Results A total of 21 FNH, 3 cavernous hemangiomas, and 109 arterial segments were visualized in 10 subjects. The temporally-resolved images depicted the characteristic arterial enhancement pattern of the lesions with a 4 s update rate. Images were graded as having significantly higher quality compared to the clinical MRI. Angiograms produced from the IVD method provided non-inferior diagnostic assessment compared to the dedicated MRA. Conclusion Using an undersampled IVD imaging method, we have demonstrated the feasibility of obtaining high spatial and temporal resolution dynamic contrast-enhanced imaging and simultaneous MRA of the liver. PMID:24639130

Variables associated with work performance in multidisciplinary mental health teams

PubMed Central

Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie; Chiocchio, François

2017-01-01

Objectives: This study investigates work performance among 79 mental health teams in Quebec (Canada). We hypothesized that work performance was positively associated with the use of standardized clinical tools and clinical approaches, integration strategies, “clan culture,” and mental health funding per capita. Methods: Work performance was measured using an adapted version of the Work Role Questionnaire. Variables were organized into four key areas: (1) team attributes, (2) organizational culture, (3) inter-organizational interactions, and (4) external environment. Results: Work performance was associated with two types of organizational culture (clan and hierarchy) and with two team attributes (use of standardized clinical tools and approaches). Discussion and conclusion: This study was innovative in identifying associations between work performance and best practices, justifying their implementation. Recommendations are provided to develop organizational cultures promoting a greater focus on the external environment and integration strategies that strengthen external focus, service effectiveness, and innovation. PMID:28839935

Culture as a variable in neuroscience and clinical neuropsychology: A comprehensive review

PubMed Central

Wajman, José Roberto; Bertolucci, Paulo Henrique Ferreira; Mansur, Letícia Lessa; Gauthier, Serge

2015-01-01

Culture is a dynamic system of bidirectional influences among individuals and their environment, including psychological and biological processes, which facilitate adaptation and social interaction. One of the main challenges in clinical neuropsychology involves cognitive, behavioral and functional assessment of people with different sociocultural backgrounds. In this review essay, examining culture from a historical perspective to ethical issues in cross-cultural research, including the latest significant and publications, the authors sought to explore the main features related to cultural variables in neuropsychological practice and to debate the challenges found regarding the operational methods currently in use. Literature findings suggest a more comprehensive approach in cognitive and behavioral neuroscience, including an interface between elementary disciplines and applied neuropsychology. Thus, as a basis for discussion on this issue, the authors analyzed key-topics related to the study of new trends in sociocultural neuroscience and the application of their concepts from a clinical perspective. PMID:29213964

Clinical and Biological Relevance of Genomic Heterogeneity in Chronic Lymphocytic Leukemia

PubMed Central

Friedman, Daphne R.; Lucas, Joseph E.; Weinberg, J. Brice

2013-01-01

Background Chronic lymphocytic leukemia (CLL) is typically regarded as an indolent B-cell malignancy. However, there is wide variability with regards to need for therapy, time to progressive disease, and treatment response. This clinical variability is due, in part, to biological heterogeneity between individual patients’ leukemias. While much has been learned about this biological variation using genomic approaches, it is unclear whether such efforts have sufficiently evaluated biological and clinical heterogeneity in CLL. Methods To study the extent of genomic variability in CLL and the biological and clinical attributes of genomic classification in CLL, we evaluated 893 unique CLL samples from fifteen publicly available gene expression profiling datasets. We used unsupervised approaches to divide the data into subgroups, evaluated the biological pathways and genetic aberrations that were associated with the subgroups, and compared prognostic and clinical outcome data between the subgroups. Results Using an unsupervised approach, we determined that approximately 600 CLL samples are needed to define the spectrum of diversity in CLL genomic expression. We identified seven genomically-defined CLL subgroups that have distinct biological properties, are associated with specific chromosomal deletions and amplifications, and have marked differences in molecular prognostic markers and clinical outcomes. Conclusions Our results indicate that investigations focusing on small numbers of patient samples likely provide a biased outlook on CLL biology. These findings may have important implications in identifying patients who should be treated with specific targeted therapies, which could have efficacy against CLL cells that rely on specific biological pathways. PMID:23468975

Evaluation of the Environmental Bias on Accelerometer-Measured Total Daily Activity Counts and Owner Survey Responses in Dogs with Osteoarthritis.

PubMed

Katz, Erin M; Scott, Ruth M; Thomson, Christopher B; Mesa, Eileen; Evans, Richard; Conzemius, Michael G

2017-11-01

Objective  To determine if environmental variables affect the average daily activity counts (AC) of dogs with osteoarthritis (OA) and/or owners' perception of their dog's clinical signs or quality of life. Methods  The AC and Canine Brief Pain Inventory (CBPI) owner questionnaires of 62 dogs with OA were compared with daily environmental variables including the following: average temperature (°C), high temperature (°C), low temperature (°C), relative humidity (%), total precipitation (mm), average barometric pressure (hPa) and total daylight hours. Results  Daily AC significantly correlated with average temperature and total daylight hours, but average temperature and total daylight hours accounted for less than 1% of variation in AC. No other significant relationships were found between daily AC and daily high temperature, low temperature, relative humidity, total precipitation or average barometric pressure. No statistical relationship was found between daily AC and the CBPI, nor between environmental variables and the CBPI. Canine Brief Pain Inventory scores for pain severity and pain interference decreased significantly over the test period. Clinical Significance  The relationship between daily AC and average temperature and total daylight hours was significant, but unlikely to be clinically significant. Thus, environmental variables do not appear to have a clinically relevant bias on AC or owner CBPI questionnaires. The decrease over time in CBPI pain severity and pain interference values suggests owners completing the CBPI in this study were influenced by a caregiver placebo effect. Schattauer GmbH Stuttgart.

Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

PubMed

Rakha, E A; Soria, D; Green, A R; Lemetre, C; Powe, D G; Nolan, C C; Garibaldi, J M; Ball, G; Ellis, I O

2014-04-02

Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. In this study, we hypothesised that molecular features of BC are a key driver of tumour behaviour and when coupled with a novel and bespoke application of established clinicopathologic prognostic variables can predict both clinical outcome and relevant therapeutic options more accurately than existing methods. In the current study, a comprehensive panel of biomarkers with relevance to BC was applied to a large and well-characterised series of BC, using immunohistochemistry and different multivariate clustering techniques, to identify the key molecular classes. Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). The NPI+ was then used to predict outcome in the different molecular classes. Seven core molecular classes were identified using a selective panel of 10 biomarkers. Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Outcome analysis showed that using the bespoke NPI formulae for each biological BC class provides improved patient outcome stratification superior to the traditional NPI. This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.

Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke

PubMed Central

Banks, Caitlin L.; Pai, Mihir M.; McGuirk, Theresa E.; Fregly, Benjamin J.; Patten, Carolynn

2017-01-01

Muscle synergy analysis (MSA) is a mathematical technique that reduces the dimensionality of electromyographic (EMG) data. Used increasingly in biomechanics research, MSA requires methodological choices at each stage of the analysis. Differences in methodological steps affect the overall outcome, making it difficult to compare results across studies. We applied MSA to EMG data collected from individuals post-stroke identified as either responders (RES) or non-responders (nRES) on the basis of a critical post-treatment increase in walking speed. Importantly, no clinical or functional indicators identified differences between the cohort of RES and nRES at baseline. For this exploratory study, we selected the five highest RES and five lowest nRES available from a larger sample. Our goal was to assess how the methodological choices made before, during, and after MSA affect the ability to differentiate two groups with intrinsic physiologic differences based on MSA results. We investigated 30 variations in MSA methodology to determine which choices allowed differentiation of RES from nRES at baseline. Trial-to-trial variability in time-independent synergy vectors (SVs) and time-varying neural commands (NCs) were measured as a function of: (1) number of synergies computed; (2) EMG normalization method before MSA; (3) whether SVs were held constant across trials or allowed to vary during MSA; and (4) synergy analysis output normalization method after MSA. MSA methodology had a strong effect on our ability to differentiate RES from nRES at baseline. Across all 10 individuals and MSA variations, two synergies were needed to reach an average of 90% variance accounted for (VAF). Based on effect sizes, differences in SV and NC variability between groups were greatest using two synergies with SVs that varied from trial-to-trial. Differences in SV variability were clearest using unit magnitude per trial EMG normalization, while NC variability was less sensitive to EMG normalization method. No outcomes were greatly impacted by output normalization method. MSA variability for some, but not all, methods successfully differentiated intrinsic physiological differences inaccessible to traditional clinical or biomechanical assessments. Our results were sensitive to methodological choices, highlighting the need for disclosure of all aspects of MSA methodology in future studies. PMID:28912707

Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke.

PubMed

Banks, Caitlin L; Pai, Mihir M; McGuirk, Theresa E; Fregly, Benjamin J; Patten, Carolynn

2017-01-01

Muscle synergy analysis (MSA) is a mathematical technique that reduces the dimensionality of electromyographic (EMG) data. Used increasingly in biomechanics research, MSA requires methodological choices at each stage of the analysis. Differences in methodological steps affect the overall outcome, making it difficult to compare results across studies. We applied MSA to EMG data collected from individuals post-stroke identified as either responders (RES) or non-responders (nRES) on the basis of a critical post-treatment increase in walking speed. Importantly, no clinical or functional indicators identified differences between the cohort of RES and nRES at baseline. For this exploratory study, we selected the five highest RES and five lowest nRES available from a larger sample. Our goal was to assess how the methodological choices made before, during, and after MSA affect the ability to differentiate two groups with intrinsic physiologic differences based on MSA results. We investigated 30 variations in MSA methodology to determine which choices allowed differentiation of RES from nRES at baseline. Trial-to-trial variability in time-independent synergy vectors (SVs) and time-varying neural commands (NCs) were measured as a function of: (1) number of synergies computed; (2) EMG normalization method before MSA; (3) whether SVs were held constant across trials or allowed to vary during MSA; and (4) synergy analysis output normalization method after MSA. MSA methodology had a strong effect on our ability to differentiate RES from nRES at baseline. Across all 10 individuals and MSA variations, two synergies were needed to reach an average of 90% variance accounted for (VAF). Based on effect sizes, differences in SV and NC variability between groups were greatest using two synergies with SVs that varied from trial-to-trial. Differences in SV variability were clearest using unit magnitude per trial EMG normalization, while NC variability was less sensitive to EMG normalization method. No outcomes were greatly impacted by output normalization method. MSA variability for some, but not all, methods successfully differentiated intrinsic physiological differences inaccessible to traditional clinical or biomechanical assessments. Our results were sensitive to methodological choices, highlighting the need for disclosure of all aspects of MSA methodology in future studies.

The relationship between effectiveness and costs measured by a risk-adjusted case-mix system: multicentre study of Catalonian population data bases.

PubMed

Sicras-Mainar, Antoni; Navarro-Artieda, Ruth; Blanca-Tamayo, Milagrosa; Velasco-Velasco, Soledad; Escribano-Herranz, Esperanza; Llopart-López, Josep Ramon; Violan-Fors, Concepción; Vilaseca-Llobet, Josep Maria; Sánchez-Fontcuberta, Encarna; Benavent-Areu, Jaume; Flor-Serra, Ferran; Aguado-Jodar, Alba; Rodríguez-López, Daniel; Prados-Torres, Alejandra; Estelrich-Bennasar, Jose

2009-06-25

The main objective of this study is to measure the relationship between morbidity, direct health care costs and the degree of clinical effectiveness (resolution) of health centres and health professionals by the retrospective application of Adjusted Clinical Groups in a Spanish population setting. The secondary objectives are to determine the factors determining inadequate correlations and the opinion of health professionals on these instruments. We will carry out a multi-centre, retrospective study using patient records from 15 primary health care centres and population data bases. The main measurements will be: general variables (age and sex, centre, service [family medicine, paediatrics], and medical unit), dependent variables (mean number of visits, episodes and direct costs), co-morbidity (Johns Hopkins University Adjusted Clinical Groups Case-Mix System) and effectiveness.The totality of centres/patients will be considered as the standard for comparison. The efficiency index for visits, tests (laboratory, radiology, others), referrals, pharmaceutical prescriptions and total will be calculated as the ratio: observed variables/variables expected by indirect standardization.The model of cost/patient/year will differentiate fixed/semi-fixed (visits) costs of the variables for each patient attended/year (N = 350,000 inhabitants). The mean relative weights of the cost of care will be obtained. The effectiveness will be measured using a set of 50 indicators of process, efficiency and/or health results, and an adjusted synthetic index will be constructed (method: percentile 50).The correlation between the efficiency (relative-weights) and synthetic (by centre and physician) indices will be established using the coefficient of determination. The opinion/degree of acceptance of physicians (N = 1,000) will be measured using a structured questionnaire including various dimensions. multiple regression analysis (procedure: enter), ANCOVA (method: Bonferroni's adjustment) and multilevel analysis will be carried out to correct models. The level of statistical significance will be p < 0.05.

Heart rate variability measure in breast cancer patients and survivors: A systematic review.

PubMed

Arab, Claudia; Dias, Daniel Penteado Martins; Barbosa, Renata Thaís de Almeida; Carvalho, Tatiana Dias de; Valenti, Vitor Engrácia; Crocetta, Tânia Brusque; Ferreira, Marcelo; Abreu, Luiz Carlos de; Ferreira, Celso

2016-06-01

In the current study, we aimed to review literature findings showing the clinical importance of cardiac autonomic modulation assessed by heart rate variability analysis in breast cancer (BC) patients and survivors. We conducted a systematic review according to The PRISMA Statement in Medline, Scopus and Web of Science (_-2015) databases. The search was limited to articles in English language, published in peer-reviewed journals, and with adult age samples only (e.g., women, patients, or survivors, diagnosed with BC in any stage). We included observational studies and randomized trials. Detailed heart rate variability analysis (instruments, data collection protocol, and analysis methods) was required. Search terms included autonomic nervous system, heart rate variability, sympathetic and parasympathetic nervous system, autonomic dysfunction, vagal nervous and breast neoplasms, breast cancer and breast tumor. Twelve studies were included in this review. The clinical importance of cardiac autonomic modulation assessed by heart rate variability analysis in BC patients and survivors is demonstrated by association with effects of BC surgery, and treatments, and the adverse effects of surgery and treatments on survivors (e.g., cardiotoxicity, fatigue, and stress). The strength of evidence of included studies is low: small samples size and heterogeneity, presence of confounders, and observational studies design. The heart rate variability analysis could be used as a complementary non-invasive tool for the early diagnosis and better prognosis of autonomic dysfunction, and survival in BC patients. There are many potential clinical applications of heart rate variability analysis in BC patients, and the employment of such approaches could lead to lower impairment of autonomic function in this individuals. Copyright © 2016 Elsevier Ltd. All rights reserved.

Endoscopic ultrasound as an adjunctive evaluation in patients with esophageal motor disorders subtyped by high-resolution manometry

PubMed Central

Krishnan, Kumar; Lin, Chen-Yuan; Keswani, Rajesh; Pandolfino, John E; Kahrilas, Peter J; Komanduri, Srinadh

2015-01-01

Background and aims Esophageal motor disorders are a heterogenous group of conditions identified by esophageal manometry that lead to esophageal dysfunction. The aim of this study was to assess the clinical utility of endoscopic ultrasound in the further evaluation of patients with esophageal motor disorders categorized using the updated Chicago Classification. Methods We performed a retrospective, single center study of 62 patients with esophageal motor disorders categorized according to the Chicago Classification. All patients underwent standard radial endosonography to assess for extra esophageal findings or alternative explanations for esophageal outflow obstruction. Secondary outcomes included esophageal wall thickness among the different patient subsets within the Chicago Classification Key Results EUS identified 9/62 (15%) clinically relevant findings that altered patient management and explained the etiology of esophageal outflow obstruction. We further identified substantial variability in esophageal wall thickness in a proportion of patients including some with a significantly thickened non-muscular layer. Conclusions EUS findings are clinically relevant in a significant number of patients with motor disorders and can alter clinical management. Variability in esophageal wall thickness of the muscularis propria and non-muscular layers identified by EUS may also explain the observed variability in response to standard therapies for achalasia. PMID:25041229

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Preferential Cyclooxygenase 2 Inhibitors as a Nonhormonal Method of Emergency Contraception: A Look at the Evidence.

PubMed

Weiss, Erich A; Gandhi, Mona

2016-04-01

To review the literature surrounding the use of preferential cyclooxygenase 2 (COX-2) inhibitors as an alternative form of emergency contraception. MEDLINE (1950 to February 2014) was searched using the key words cyclooxygenase or COX-2 combined with contraception, emergency contraception, or ovulation. Results were limited to randomized control trials, controlled clinical trials, and clinical trials. Human trials that measured the effects of COX inhibition on female reproductive potential were included for review. The effects of the COX-2 inhibitors rofecoxib, celecoxib, and meloxicam were evaluated in 6 trials. Each of which was small in scope, enrolled women of variable fertility status, used different dosing regimens, included multiple end points, and had variable results. Insufficient evidence exists to fully support the use of preferential COX-2 inhibitors as a form of emergency contraception. Although all trials resulted in a decrease in ovulatory cycles, outcomes varied between dosing strategies and agents used. A lack of homogeneity in these studies makes comparisons difficult. However, success of meloxicam in multiple trials warrants further study. Larger human trials are necessary before the clinical utility of this method of emergency contraception can be fully appreciated. © The Author(s) 2014.

VFS interjudge reliability using a free and directed search.

PubMed

Bryant, Karen N; Finnegan, Eileen; Berbaum, Kevin

2012-03-01

Reports in the literature suggest that clinicians demonstrate poor reliability in rating videofluoroscopic swallow (VFS) variables. Contemporary perception theories suggest that the methods used in VFS reliability studies constrain subjects to make judgments in an abnormal way. The purpose of this study was to determine whether a directed search or a free search approach to rating swallow studies results in better interjudge reliability. Ten speech pathologists served as judges. Five clinical judges were assigned to the directed search group (use checklist) and five to the free search group (unguided observations). Clinical judges interpreted 20 VFS examinations of swallowing. Interjudge reliability of ratings of dysphagia severity, affected stage of swallow, dysphagia symptoms, and attributes identified by clinical judges using a directed search was compared with that using a free search approach. Interjudge reliability for rating the presence of aspiration and penetration was significantly better using a free search ("substantial" to "almost perfect" agreement) compared to a directed search ("moderate" agreement). Reliability of dysphagia severity ratings ranged from "moderate" to "almost perfect" agreement for both methods of search. Reliability for reporting all other symptoms and attributes of dysphagia was variable and was not significantly different between the groups.

Purposeful Variable Selection and Stratification to Impute Missing FAST Data in Trauma Research

PubMed Central

Fuchs, Paul A.; del Junco, Deborah J.; Fox, Erin E.; Holcomb, John B.; Rahbar, Mohammad H.; Wade, Charles A.; Alarcon, Louis H.; Brasel, Karen J.; Bulger, Eileen M.; Cohen, Mitchell J.; Myers, John G.; Muskat, Peter; Phelan, Herb A.; Schreiber, Martin A.; Cotton, Bryan A.

2013-01-01

Background The Focused Assessment with Sonography for Trauma (FAST) exam is an important variable in many retrospective trauma studies. The purpose of this study was to devise an imputation method to overcome missing data for the FAST exam. Due to variability in patients’ injuries and trauma care, these data are unlikely to be missing completely at random (MCAR), raising concern for validity when analyses exclude patients with missing values. Methods Imputation was conducted under a less restrictive, more plausible missing at random (MAR) assumption. Patients with missing FAST exams had available data on alternate, clinically relevant elements that were strongly associated with FAST results in complete cases, especially when considered jointly. Subjects with missing data (32.7%) were divided into eight mutually exclusive groups based on selected variables that both described the injury and were associated with missing FAST values. Additional variables were selected within each group to classify missing FAST values as positive or negative, and correct FAST exam classification based on these variables was determined for patients with non-missing FAST values. Results Severe head/neck injury (odds ratio, OR=2.04), severe extremity injury (OR=4.03), severe abdominal injury (OR=1.94), no injury (OR=1.94), other abdominal injury (OR=0.47), other head/neck injury (OR=0.57) and other extremity injury (OR=0.45) groups had significant ORs for missing data; the other group odds ratio was not significant (OR=0.84). All 407 missing FAST values were imputed, with 109 classified as positive. Correct classification of non-missing FAST results using the alternate variables was 87.2%. Conclusions Purposeful imputation for missing FAST exams based on interactions among selected variables assessed by simple stratification may be a useful adjunct to sensitivity analysis in the evaluation of imputation strategies under different missing data mechanisms. This approach has the potential for widespread application in clinical and translational research and validation is warranted. Level of Evidence Level II Prognostic or Epidemiological PMID:23778515

Parent-child communication and psychological adjustment in children with a brain tumor.

PubMed

Adduci, Annarita; Jankovic, Momcilo; Strazzer, Sandra; Massimino, Maura; Clerici, Carlo; Poggi, Geraldina

2012-08-01

Internalizing problems, anxiety, depression, withdrawal, and consequent social problems are frequently observed in children with brain tumors. The objective of this work is to describe the relationship between these psychological problems and the type of parent-child communication established about the disease. A group of 64 children surviving a brain tumor (aged 4-18 years) underwent psychological assessment by means of parent reports on the Child Behavior Checklist (CBCL) and the Vineland Adaptive Behavior Scales (VABS). A semi-structured interview with each child and their parents enabled us to classify the method of communication regarding the disease as "avoidance," "ineffective," and "effective." Demographic, clinical, and functional data relating to the disease were also collected. A significant relationship between the onset of Internalizing problems, withdrawal, anxiety-depression, and social problems and the presence of avoidance or ineffective communication about the disease was observed (P = 0.001, P = 0.001, P = 0.001, and P = 0.01, respectively). These psychological problems did not prove to be associated to demographic or clinical variables; however, they were found to be related to the children's residual functional problems. By contrast, the method of communication proved to be unrelated to clinical or functional variables, but it was associated to demographic variables such as sex and age at assessment. Effective (complete, truthful, consistent, comprehensible, gradual and continuous, and tailored) communication to the child about his/her condition proved to be associated with a better psychological outcome. Copyright © 2012 Wiley Periodicals, Inc.

Evaluation of machine learning algorithms for improved risk assessment for Down's syndrome.

PubMed

Koivu, Aki; Korpimäki, Teemu; Kivelä, Petri; Pahikkala, Tapio; Sairanen, Mikko

2018-05-04

Prenatal screening generates a great amount of data that is used for predicting risk of various disorders. Prenatal risk assessment is based on multiple clinical variables and overall performance is defined by how well the risk algorithm is optimized for the population in question. This article evaluates machine learning algorithms to improve performance of first trimester screening of Down syndrome. Machine learning algorithms pose an adaptive alternative to develop better risk assessment models using the existing clinical variables. Two real-world data sets were used to experiment with multiple classification algorithms. Implemented models were tested with a third, real-world, data set and performance was compared to a predicate method, a commercial risk assessment software. Best performing deep neural network model gave an area under the curve of 0.96 and detection rate of 78% with 1% false positive rate with the test data. Support vector machine model gave area under the curve of 0.95 and detection rate of 61% with 1% false positive rate with the same test data. When compared with the predicate method, the best support vector machine model was slightly inferior, but an optimized deep neural network model was able to give higher detection rates with same false positive rate or similar detection rate but with markedly lower false positive rate. This finding could further improve the first trimester screening for Down syndrome, by using existing clinical variables and a large training data derived from a specific population. Copyright © 2018 Elsevier Ltd. All rights reserved.

Towards standardization of 18F-FET PET imaging: do we need a consistent method of background activity assessment?

PubMed

Unterrainer, Marcus; Vettermann, Franziska; Brendel, Matthias; Holzgreve, Adrien; Lifschitz, Michael; Zähringer, Matthias; Suchorska, Bogdana; Wenter, Vera; Illigens, Ben M; Bartenstein, Peter; Albert, Nathalie L

2017-12-01

PET with O-(2- 18 F-fluoroethyl)-L-tyrosine ( 18 F-FET) has reached increasing clinical significance for patients with brain neoplasms. For quantification of standard PET-derived parameters such as the tumor-to-background ratio, the background activity is assessed using a region of interest (ROI) or volume of interest (VOI) in unaffected brain tissue. However, there is no standardized approach regarding the assessment of the background reference. Therefore, we evaluated the intra- and inter-reader variability of commonly applied approaches for clinical 18 F-FET PET reading. The background activity of 20 18 F-FET PET scans was independently evaluated by 6 readers using a (i) simple 2D-ROI, (ii) spherical VOI with 3.0 cm diameter, and (iii) VOI consisting of crescent-shaped ROIs; each in the contralateral, non-affected hemisphere including white and gray matter in line with the European Association of Nuclear Medicine (EANM) and German guidelines. To assess intra-reader variability, each scan was evaluated 10 times by each reader. The coefficient of variation (CoV) was assessed for determination of intra- and inter-reader variability. In a second step, the best method was refined by instructions for a guided background activity assessment and validated by 10 further scans. Compared to the other approaches, the crescent-shaped VOIs revealed most stable results with the lowest intra-reader variabilities (median CoV 1.52%, spherical VOI 4.20%, 2D-ROI 3.69%; p < 0.001) and inter-reader variabilities (median CoV 2.14%, spherical VOI 4.02%, 2D-ROI 3.83%; p = 0.001). Using the guided background assessment, both intra-reader variabilities (median CoV 1.10%) and inter-reader variabilities (median CoV 1.19%) could be reduced even more. The commonly applied methods for background activity assessment show different variability which might hamper 18 F-FET PET quantification and comparability in multicenter settings. The proposed background activity assessment using a (guided) crescent-shaped VOI allows minimization of both intra- and inter-reader variability and might facilitate comprehensive methodological standardization of amino acid PET which is of interest in the light of the anticipated EANM technical guidelines.

Variability of exhaled breath condensate pH in lung transplant recipients.

PubMed

Czebe, Krisztina; Kullmann, Tamas; Csiszer, Eszter; Barat, Erzsebet; Horvath, Ildiko; Antus, Balazs

2008-01-01

Measurement of pH in exhaled breath condensate (EBC) may represent a novel method for investigating airway pathology. The aim of this longitudinal study was to assess the variability of EBC pH in stable lung transplant recipients (LTR). During routine clinical visits 74 EBC pH measurements were performed in 17 LTR. EBC pH was also measured in 19 healthy volunteers on four separate occasions. EBC pH was determined at standard CO2 partial pressure by a blood gas analyzer. Mean EBC pH in clinically stable LTR and in controls was similar (6.38 +/- 0.09 vs. 6.44 +/- 0.16; p = nonsignificant). Coefficient of variation for pH in LTR and controls was 2.1 and 2.3%, respectively. The limits of agreement for between-visit variability determined by the Bland-Altman test in LTR and healthy volunteers were also comparable (-0.29 and 0.46 vs. -0.53 and 0.44). Our data suggest that the variability of EBC pH in stable LTR is relatively small, and it is similar to that in healthy nontransplant subjects.

What is the perception of biological risk by undergraduate nursing students?

PubMed Central

Moreno-Arroyo, Mª Carmen; Puig-Llobet, Montserrat; Falco-Pegueroles, Anna; Lluch-Canut, Maria Teresa; García, Irma Casas; Roldán-Merino, Juan

2016-01-01

Abstract Objective: to analyze undergraduate nursing students' perception of biological risk and its relationship with their prior practical training. Method: a descriptive cross-sectional study was conducted among undergraduate nursing students enrolled in clinical practice courses in the academic year 2013-2014 at the School of Nursing at the University of Barcelona. Variables: sociodemographic variables, employment, training, clinical experience and other variables related to the assessment of perceived biological risk were collected. Both a newly developed tool and the Dimensional Assessment of Risk Perception at the worker level scale (Escala de Evaluación Dimensional del Riesgo Percibido por el Trabajador, EDRP-T) were used. Statistical analysis: descriptive and univariate analysis were used to identify differences between the perception of biological risk of the EDRP-T scale items and sociodemographic variables. Results: students without prior practical training had weaker perceptions of biological risk compared to students with prior practical training (p=0.05 and p=0.04, respectively). Weaker perceptions of biological risk were found among students with prior work experience. Conclusion: practical training and work experience influence the perception of biological risk among nursing students. PMID:27384468

A preliminary score for the assessment of disease activity in hereditary recurrent fevers: results from the AIDAI (Auto-Inflammatory Diseases Activity Index) Consensus Conference

PubMed Central

Piram, Maryam; Frenkel, Joost; Gattorno, Marco; Ozen, Seza; Lachmann, Helen J; Goldbach-Mansky, Raphaela; Hentgen, Véronique; Neven, Bénédicte; Stankovic Stojanovic, Katia; Simon, Anna; Kuemmerle-Deschner, Jasmin; Hoffman, Hal; Stojanov, Silvia; Duquesne, Agnès; Pillet, Pascal; Martini, Alberto; Pouchot, Jacques; Koné-Paut, Isabelle

2012-01-01

Background The systemic autoinflammatory disorders (SAID) share many clinical manifestations, albeit with variable patterns, intensity and frequency. A common definition of disease activity would be rational and useful in the management of these lifelong diseases. Moreover, standardised disease activity scores are required for the assessment of new therapies in constant development. The aim of this study was to develop preliminary activity scores for familial Mediterranean fever, mevalonate kinase deficiency, tumour necrosis factor receptor-1-associated periodic syndrome and cryopyrin-associated periodic syndromes (CAPS). Methods The study was conducted using two well-recognised consensus formation methods: the Delphi technique and the nominal group technique. The results from a two-step survey and data from parent/patient interviews were used as preliminary data to develop the agenda for a consensus conference to build a provisional scoring system. Results 24 of 65 experts in SAID from 20 countries answered the web questionnaire and 16 attended the consensus conference. There was consensus agreement to develop separate activity scores for each disease but with a common format based on patient diaries. Fever and disease-specific clinical variables were scored according to their severity. A final score was generated by summing the score of all the variables divided by the number of days over which the diary was completed. Scores varied from 0 to 16 (0–13 in CAPS). These scores were developed for the purpose of clinical studies but could be used in clinical practice. Conclusion Using widely recognised consensus formation techniques, preliminary scores were obtained to measure disease activity in four main SAID. Further prospective validation study of this instrument will follow. PMID:21081528

[Pheochromocytoma in 8-year observation at a single endocrinological center in Wroclaw].

PubMed

Bednarek-Tupikowska, Grazyna; Bucyk, Barbara; Daroszewski, Jacek; Bidzińska-Speichert, Bozena; Bohdanowicz-Pawlak, Anna; Szymczak, Jadwiga; Bednorz, Włodzimierz; Podgórski, Franciszek; Zareba-Bogdał, Elzbieta; Kuliczkowska-Płaksej, Justyna; Lenarcik, Agnieszka; Filus, Alicja; Kałuzny, Marcin; Kubicka, Eliza; Syrycka, Joanna; Tupikowska, Małgorzata; Lizurej, Oskar; Bolanowski, Marek; Milewicz, Andrzej

2009-01-01

Pheochromocytoma is rare tumor with a highly variable clinical presentation. This report provides clinical picture, efficiency of diagnostics and treatment of pheochromocytoma in 8-years in the endocrinological center in Wroclaw. The records of 37 patients with pheochromocytoma were identified, who were treated in 2000-2007 in the Department of Endocrinology, Diabetology and Isotope Treatment in Wroclaw. There were 23 women (age 23-75 year) and 14 men (age 17-74). We studied frequency of clinical signs, usefulness of diagnostic methods and efficacy of treatment. The duration of the clinical history ranged from 2 months to 16 years. The most frequent symptoms were: hypertension paroxysmal and constant, palpitations, headache, sweating and anxiety. The most sensitive diagnostic method was increased concentration of urinary metanephrine in 24-hour urine. Computed tomography was the most widely used method for tumor localization. Adrenal pheochromocytoma was detecting by CT in all patients, predominated in right adrenal, in 1 case in urinary bladder. Surgery caused remission of hypertension in 59%, improvement in 26.8%, and no changes in 13.9% of patients. Malignancy was reported in 2 cases, 1 woman died after surgery. MEN 2A occur in 21.6%. The diagnosis of pheochromocytma is usually made after long duration of the disease. The study confirms that clinical presentation of pheochromocytoma is variable and nonspecific, this finding makes the diagnosis very difficult. The most typical symptom is paroxysmal hypertension, which is present only in 40%, other symptoms are nonspecific. The measurement of 24-hour urinary metanephrines was the best indicator. CT was almost always successful in localizing the tumor. Patients with pheochromocytoma should be consider for other endocrine diseases especially medullary carcinoma, primary hyperparathyroidism and other component of MEN 2A.

Critical discussion of evaluation parameters for inter-observer variability in target definition for radiation therapy.

PubMed

Fotina, I; Lütgendorf-Caucig, C; Stock, M; Pötter, R; Georg, D

2012-02-01

Inter-observer studies represent a valid method for the evaluation of target definition uncertainties and contouring guidelines. However, data from the literature do not yet give clear guidelines for reporting contouring variability. Thus, the purpose of this work was to compare and discuss various methods to determine variability on the basis of clinical cases and a literature review. In this study, 7 prostate and 8 lung cases were contoured on CT images by 8 experienced observers. Analysis of variability included descriptive statistics, calculation of overlap measures, and statistical measures of agreement. Cross tables with ratios and correlations were established for overlap parameters. It was shown that the minimal set of parameters to be reported should include at least one of three volume overlap measures (i.e., generalized conformity index, Jaccard coefficient, or conformation number). High correlation between these parameters and scatter of the results was observed. A combination of descriptive statistics, overlap measure, and statistical measure of agreement or reliability analysis is required to fully report the interrater variability in delineation.

cp-R, an interface the R programming language for clinical laboratory method comparisons.

PubMed

Holmes, Daniel T

2015-02-01

Clinical scientists frequently need to compare two different bioanalytical methods as part of assay validation/monitoring. As a matter necessity, regression methods for quantitative comparison in clinical chemistry, hematology and other clinical laboratory disciplines must allow for error in both the x and y variables. Traditionally the methods popularized by 1) Deming and 2) Passing and Bablok have been recommended. While commercial tools exist, no simple open source tool is available. The purpose of this work was to develop and entirely open-source GUI-driven program for bioanalytical method comparisons capable of performing these regression methods and able to produce highly customized graphical output. The GUI is written in python and PyQt4 with R scripts performing regression and graphical functions. The program can be run from source code or as a pre-compiled binary executable. The software performs three forms of regression and offers weighting where applicable. Confidence bands of the regression are calculated using bootstrapping for Deming and Passing Bablok methods. Users can customize regression plots according to the tools available in R and can produced output in any of: jpg, png, tiff, bmp at any desired resolution or ps and pdf vector formats. Bland Altman plots and some regression diagnostic plots are also generated. Correctness of regression parameter estimates was confirmed against existing R packages. The program allows for rapid and highly customizable graphical output capable of conforming to the publication requirements of any clinical chemistry journal. Quick method comparisons can also be performed and cut and paste into spreadsheet or word processing applications. We present a simple and intuitive open source tool for quantitative method comparison in a clinical laboratory environment. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Linear data mining the Wichita clinical matrix suggests sleep and allostatic load involvement in chronic fatigue syndrome.

PubMed

Gurbaxani, Brian M; Jones, James F; Goertzel, Benjamin N; Maloney, Elizabeth M

2006-04-01

To provide a mathematical introduction to the Wichita (KS, USA) clinical dataset, which is all of the nongenetic data (no microarray or single nucleotide polymorphism data) from the 2-day clinical evaluation, and show the preliminary findings and limitations, of popular, matrix algebra-based data mining techniques. An initial matrix of 440 variables by 227 human subjects was reduced to 183 variables by 164 subjects. Variables were excluded that strongly correlated with chronic fatigue syndrome (CFS) case classification by design (for example, the multidimensional fatigue inventory [MFI] data), that were otherwise self reporting in nature and also tended to correlate strongly with CFS classification, or were sparse or nonvarying between case and control. Subjects were excluded if they did not clearly fall into well-defined CFS classifications, had comorbid depression with melancholic features, or other medical or psychiatric exclusions. The popular data mining techniques, principle components analysis (PCA) and linear discriminant analysis (LDA), were used to determine how well the data separated into groups. Two different feature selection methods helped identify the most discriminating parameters. Although purely biological features (variables) were found to separate CFS cases from controls, including many allostatic load and sleep-related variables, most parameters were not statistically significant individually. However, biological correlates of CFS, such as heart rate and heart rate variability, require further investigation. Feature selection of a limited number of variables from the purely biological dataset produced better separation between groups than a PCA of the entire dataset. Feature selection highlighted the importance of many of the allostatic load variables studied in more detail by Maloney and colleagues in this issue [1] , as well as some sleep-related variables. Nonetheless, matrix linear algebra-based data mining approaches appeared to be of limited utility when compared with more sophisticated nonlinear analyses on richer data types, such as those found in Maloney and colleagues [1] and Goertzel and colleagues [2] in this issue.

Variability of gastrointestinal transit in healthy women and men.

PubMed Central

Degen, L P; Phillips, S F

1996-01-01

BACKGROUND AND AIMS: Measurements of gastrointestinal transit are made in clinical and research gastroenterology, yet their intrinsic variability is not well characterised. In particular, an influence of hormones on transit has been proposed as the basis for gastrointestinal symptoms that vary with the menstrual cycle. Our aims were to quantify individual differences in transit during the menstrual cycle in healthy women and to compare these with the intrinsic variability in healthy men. METHODS: On two occasions, whole gut transit was assessed scintigraphically and colonic transit quantified by radio-opaque markers. Thirty two healthy volunteers (12 women, 20 men) were studied, women during the follicular and luteal phases, men twice within a similar four week period. Diets and exercise were standardised prior to and during both studies. RESULTS: Colonic transit was significantly faster in men, and postlag gastric emptying was also more rapid; other indices of regional transit were not different between the sexes. Total colonic transit time was equally well reflected by the scintigraphic and radio-opaque marker methods. Important intraindividual differences were noted in both sexes. The variances in our samples predicted an 80% chance of detecting (with 95% confidence) a mean effect of menstrual hormones on transit that was in the same range as the intrinsic variation in men. CONCLUSIONS: Colonic transit was faster in men than in women. Although group means in the two studies were almost identical, single assessments of transit in subjects sometimes exhibited considerable variability, implying broad biological variations. Given this intrinsic variability, the influence of menstrual hormones on gastrointestinal transit must be small and of doubtful clinical significance. PMID:8977347

Dynamic TIMI risk score for STEMI.

PubMed

Amin, Sameer T; Morrow, David A; Braunwald, Eugene; Sloan, Sarah; Contant, Charles; Murphy, Sabina; Antman, Elliott M

2013-01-29

Although there are multiple methods of risk stratification for ST-elevation myocardial infarction (STEMI), this study presents a prospectively validated method for reclassification of patients based on in-hospital events. A dynamic risk score provides an initial risk stratification and reassessment at discharge. The dynamic TIMI risk score for STEMI was derived in ExTRACT-TIMI 25 and validated in TRITON-TIMI 38. Baseline variables were from the original TIMI risk score for STEMI. New variables were major clinical events occurring during the index hospitalization. Each variable was tested individually in a univariate Cox proportional hazards regression. Variables with P<0.05 were incorporated into a full multivariable Cox model to assess the risk of death at 1 year. Each variable was assigned an integer value based on the odds ratio, and the final score was the sum of these values. The dynamic score included the development of in-hospital MI, arrhythmia, major bleed, stroke, congestive heart failure, recurrent ischemia, and renal failure. The C-statistic produced by the dynamic score in the derivation database was 0.76, with a net reclassification improvement (NRI) of 0.33 (P<0.0001) from the inclusion of dynamic events to the original TIMI risk score. In the validation database, the C-statistic was 0.81, with a NRI of 0.35 (P=0.01). This score is a prospectively derived, validated means of estimating 1-year mortality of STEMI at hospital discharge and can serve as a clinically useful tool. By incorporating events during the index hospitalization, it can better define risk and help to guide treatment decisions.

Method and apparatus for assessing cardiovascular risk

NASA Technical Reports Server (NTRS)

Albrecht, Paul (Inventor); Bigger, J. Thomas (Inventor); Cohen, Richard J. (Inventor)

1998-01-01

The method for assessing risk of an adverse clinical event includes detecting a physiologic signal in the subject and determining from the physiologic signal a sequence of intervals corresponding to time intervals between heart beats. The long-time structure of fluctuations in the intervals over a time period of more than fifteen minutes is analyzed to assess risk of an adverse clinical event. In a preferred embodiment, the physiologic signal is an electrocardiogram and the time period is at least fifteen minutes. A preferred method for analyzing the long-time structure variability in the intervals includes computing the power spectrum and fitting the power spectrum to a power law dependence on frequency over a selected frequency range such as 10.sup.-4 to 10.sup.-2 Hz. Characteristics of the long-time structure fluctuations in the intervals is used to assess risk of an adverse clinical event.

Heart rate variability in patients with systemic lupus erythematosus: a systematic review and methodological considerations.

PubMed

Matusik, P S; Matusik, P T; Stein, P K

2018-07-01

Aim The aim of this review was to summarize current knowledge about the scientific findings and potential clinical utility of heart rate variability measures in patients with systemic lupus erythematosus. Methods PubMed, Embase and Scopus databases were searched for the terms associated with systemic lupus erythematosus and heart rate variability, including controlled vocabulary, when appropriate. Articles published in English and available in full text were considered. Finally, 11 publications were selected, according to the systematic review protocol and were analyzed. Results In general, heart rate variability, measured in the time and frequency domains, was reported to be decreased in patients with systemic lupus erythematosus compared with controls. In some systemic lupus erythematosus studies, heart rate variability was found to correlate with inflammatory markers and albumin levels. A novel heart rate variability measure, heart rate turbulence onset, was shown to be increased, while heart rate turbulence slope was decreased in systemic lupus erythematosus patients. Reports of associations of changes in heart rate variability parameters with increasing systemic lupus erythematosus activity were inconsistent, showing decreasing heart rate variability or no relationship. However, the low/high frequency ratio was, in some studies, reported to increase with increasing disease activity or to be inversely correlated with albumin levels. Conclusions Patients with systemic lupus erythematosus have abnormal heart rate variability, which reflects cardiac autonomic dysfunction and may be related to inflammatory cytokines but not necessarily to disease activity. Thus measurement of heart rate variability could be a useful clinical tool for monitoring autonomic dysfunction in systemic lupus erythematosus, and may potentially provide prognostic information.

Methodological requirements for valid tissue-based biomarker studies that can be used in clinical practice.

PubMed

True, Lawrence D

2014-03-01

Paralleling the growth of ever more cost efficient methods to sequence the whole genome in minute fragments of tissue has been the identification of increasingly numerous molecular abnormalities in cancers--mutations, amplifications, insertions and deletions of genes, and patterns of differential gene expression, i.e., overexpression of growth factors and underexpression of tumor suppressor genes. These abnormalities can be translated into assays to be used in clinical decision making. In general terms, the result of such an assay is subject to a large number of variables regarding the characteristics of the available sample, particularities of the used assay, and the interpretation of the results. This review discusses the effects of these variables on assays of tissue-based biomarkers, classified by macromolecule--DNA, RNA (including micro RNA, messenger RNA, long noncoding RNA, protein, and phosphoprotein). Since the majority of clinically applicable biomarkers are immunohistochemically detectable proteins this review focuses on protein biomarkers. However, the principles outlined are mostly applicable to any other analyte. A variety of preanalytical variables impacts on the results obtained, including analyte stability (which is different for different analytes, i.e., DNA, RNA, or protein), period of warm and of cold ischemia, fixation time, tissue processing, sample storage time, and storage conditions. In addition, assay variables play an important role, including reagent specificity (notably but not uniquely an issue concerning antibodies used in immunohistochemistry), technical components of the assay, quantitation, and assay interpretation. Finally, appropriateness of an assay for clinical application is an important issue. Reference is made to publicly available guidelines to improve on biomarker development in general and requirements for clinical use in particular. Strategic goals are formulated in order to improve on the quality of biomarker reporting, including issues of analyte quality, experimental detail, assay efficiency and precision, and assay appropriateness.

Clinical and Pharmacogenetic Predictors of Circulating Atorvastatin and Rosuvastatin Concentration in Routine Clinical Care

PubMed Central

DeGorter, Marianne K.; Tirona, Rommel G.; Schwarz, Ute I.; Choi, Yun-Hee; Dresser, George K.; Suskin, Neville; Myers, Kathryn; Zou, GuangYong; Iwuchukwu, Otito; Wei, Wei-Qi; Wilke, Russell A.; Hegele, Robert A.; Kim, Richard B.

2014-01-01

Background A barrier to statin therapy is myopathy associated with elevated systemic drug exposure. Our objective was to examine the association between clinical and pharmacogenetic variables and statin concentrations in patients. Methods and Results In total, 299 patients taking atorvastatin or rosuvastatin were prospectively recruited at an outpatient referral center. The contribution of clinical variables and transporter gene polymorphisms to statin concentration was assessed using multiple linear regression. We observed 45-fold variation in statin concentration among patients taking the same dose. After adjustment for gender, age, body mass index, ethnicity, dose, and time from last dose, SLCO1B1 c.521T>C (p < 0.001) and ABCG2 c.421C>A (p < 0.01) were important to rosuvastatin concentration (adjusted R2 = 0.56 for the final model). Atorvastatin concentration was associated with SLCO1B1 c.388A>G (p < 0.01) and c.521T>C (p < 0.05), and 4β-hydroxycholesterol, a CYP3A activity marker (adjusted R2 = 0.47). A second cohort of 579 patients from primary and specialty care databases were retrospectively genotyped. In this cohort, genotypes associated with statin concentration were not differently distributed among dosing groups, implying providers had not yet optimized each patient's risk-benefit ratio. Nearly 50% of patients in routine practice taking the highest doses were predicted to have statin concentrations greater than the 90th percentile. Conclusions Interindividual variability in statin exposure in patients is associated with uptake and efflux transporter polymorphisms. An algorithm incorporating genomic and clinical variables to avoid high atorvastatin and rosuvastatin levels is described; further study will determine if this approach reduces incidence of statin-myopathy. PMID:23876492

Post-use assay of vaginal rings (VRs) as a potential measure of clinical trial adherence.

PubMed

Spence, Patrick; Nel, Annalene; van Niekerk, Neliëtte; Derrick, Tiffany; Wilder, Susan; Devlin, Bríd

2016-06-05

Adherence measurement for microbicide use within the clinical trial setting remains a challenge for the HIV prevention field. This paper describes an assay method used for determining residual dapivirine levels in post-use vaginal rings from clinical trials conducted with the Dapivirine Vaginal Matrix Ring-004 developed by the International Partnership for Microbicides to prevent male to female HIV transmission. Post-use assay results from three Ring-004 clinical trials showed that of the 25mg drug load, approximately 4mg of dapivirine is released from the matrix ring over a 28-day use period. Data obtained by both in vitro and in vivo studies indicate that dapivirine is released according to a diffusion mechanism, as determined by conformance of both data sets to the Higuchi equation. This, coupled with the low variability associated with batch production over two manufacturing sites and 20 batches of material, provides evidence that post-use ring analysis can contribute to the assessment of adherence to ring use. Limitations of this method include the potential of intra-participant and inter-participant variability and uncertainty associated with measuring the low amount of dapivirine actually released relative to the drug load. Therefore, residual drug levels should not serve as the only direct measurement for microbicide adherence in vaginal ring clinical trials but should preferably be used as part of a multi-pronged approach towards understanding and assessing adherence to vaginal ring use. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Effect of clothing weight on body weight

USDA-ARS?s Scientific Manuscript database

Background: In clinical settings, it is common to measure weight of clothed patients and estimate a correction for the weight of clothing, but we can find no papers in the medical literature regarding the variability in clothing weight with weather, season, and gender. Methods: Fifty adults (35 wom...

Subtyping of a Large Collection of Historical Listeria monocytogenes Strains from Ontario, Canada, by an Improved Multilocus Variable-Number Tandem-Repeat Analysis (MLVA)

PubMed Central

Saleh-Lakha, S.; Allen, V. G.; Li, J.; Pagotto, F.; Odumeru, J.; Taboada, E.; Lombos, M.; Tabing, K. C.; Blais, B.; Ogunremi, D.; Downing, G.; Lee, S.; Gao, A.; Nadon, C.

2013-01-01

Listeria monocytogenes is responsible for severe and often fatal food-borne infections in humans. A collection of 2,421 L. monocytogenes isolates originating from Ontario's food chain between 1993 and 2010, along with Ontario clinical isolates collected from 2004 to 2010, was characterized using an improved multilocus variable-number tandem-repeat analysis (MLVA). The MLVA method was established based on eight primer pairs targeting seven variable-number tandem-repeat (VNTR) loci in two 4-plex fluorescent PCRs. Diversity indices and amplification rates of the individual VNTR loci ranged from 0.38 to 0.92 and from 0.64 to 0.99, respectively. MLVA types and pulsed-field gel electrophoresis (PFGE) patterns were compared using Comparative Partitions analysis involving 336 clinical and 99 food and environmental isolates. The analysis yielded Simpson's diversity index values of 0.998 and 0.992 for MLVA and PFGE, respectively, and adjusted Wallace coefficients of 0.318 when MLVA was used as a primary subtyping method and 0.088 when PFGE was a primary typing method. Statistical data analysis using BioNumerics allowed for identification of at least 8 predominant and persistent L. monocytogenes MLVA types in Ontario's food chain. The MLVA method correctly clustered epidemiologically related outbreak strains and separated unrelated strains in a subset analysis. An MLVA database was established for the 2,421 L. monocytogenes isolates, which allows for comparison of data among historical and new isolates of different sources. The subtyping method coupled with the MLVA database will help in effective monitoring/prevention approaches to identify environmental contamination by pathogenic strains of L. monocytogenes and investigation of outbreaks. PMID:23956391

Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials.

PubMed

Yan, Zhennan; Zhang, Shaoting; Tan, Chaowei; Qin, Hongxing; Belaroussi, Boubakeur; Yu, Hui Jing; Miller, Colin; Metaxas, Dimitris N

2015-04-01

Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to obtain fine segmentation. Fat-fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with two other atlas-based methods. Experimental results demonstrate the promises of our assessment framework. Copyright © 2014 Elsevier Ltd. All rights reserved.

Methods of assessment of the post-exercise cardiac autonomic recovery: A methodological review.

PubMed

Peçanha, Tiago; Bartels, Rhenan; Brito, Leandro C; Paula-Ribeiro, Marcelle; Oliveira, Ricardo S; Goldberger, Jeffrey J

2017-01-15

The analysis of post-exercise cardiac autonomic recovery is a practical clinical tool for the assessment of cardiovascular health. A reduced heart rate recovery - an indicator of autonomic dysfunction - has been found in a broad range of cardiovascular diseases and has been associated with increased risks of both cardiac and all-cause mortality. For this reason, over the last several years, non-invasive methods for the assessment of cardiac autonomic recovery after exercise - either based on heart rate recovery or heart rate variability indices - have been proposed. However, for the proper implementation of such methods in daily clinical practice, the discussion of their clinical validity, physiologic meaning, mathematical formulation and reproducibility should be better addressed. Therefore, the aim of this methodological review is to present some of the most employed methods of post-exercise cardiac autonomic recovery in the literature and comprehensively discuss their strengths and weaknesses. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Implementing clinical guidelines for chronic obstructive pulmonary disease: barriers and solutions

PubMed Central

Overington, Jeff D.; Huang, Yao C.; Abramson, Michael J.; Brown, Juliet L.; Goddard, John R.; Bowman, Rayleen V.; Fong, Kwun M.

2014-01-01

Chronic obstructive pulmonary disease (COPD) is a complex chronic lung disease characterised by progressive fixed airflow limitation and acute exacerbations that frequently require hospitalisation. Evidence-based clinical guidelines for the diagnosis and management of COPD are now widely available. However, the uptake of these COPD guidelines in clinical practice is highly variable, as is the case for many other chronic disease guidelines. Studies have identified many barriers to implementation of COPD and other guidelines, including factors such as lack of familiarity with guidelines amongst clinicians and inadequate implementation programs. Several methods for enhancing adherence to clinical practice guidelines have been evaluated, including distribution methods, professional education sessions, electronic health records (EHR), point of care reminders and computer decision support systems (CDSS). Results of these studies are mixed to date, and the most effective ways to implement clinical practice guidelines remain unclear. Given the significant resources dedicated to evidence-based medicine, effective dissemination and implementation of best practice at the patient level is an important final step in the process of guideline development. Future efforts should focus on identifying optimal methods for translating the evidence into everyday clinical practice to ensure that patients receive the best care. PMID:25478199

Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods

PubMed Central

Stukel, Thérèse A.; Fisher, Elliott S; Wennberg, David E.; Alter, David A.; Gottlieb, Daniel J.; Vermeulen, Marian J.

2007-01-01

Context Comparisons of outcomes between patients treated and untreated in observational studies may be biased due to differences in patient prognosis between groups, often because of unobserved treatment selection biases. Objective To compare 4 analytic methods for removing the effects of selection bias in observational studies: multivariable model risk adjustment, propensity score risk adjustment, propensity-based matching, and instrumental variable analysis. Design, Setting, and Patients A national cohort of 122 124 patients who were elderly (aged 65–84 years), receiving Medicare, and hospitalized with acute myocardial infarction (AMI) in 1994–1995, and who were eligible for cardiac catheterization. Baseline chart reviews were taken from the Cooperative Cardiovascular Project and linked to Medicare health administrative data to provide a rich set of prognostic variables. Patients were followed up for 7 years through December 31, 2001, to assess the association between long-term survival and cardiac catheterization within 30 days of hospital admission. Main Outcome Measure Risk-adjusted relative mortality rate using each of the analytic methods. Results Patients who received cardiac catheterization (n=73 238) were younger and had lower AMI severity than those who did not. After adjustment for prognostic factors by using standard statistical risk-adjustment methods, cardiac catheterization was associated with a 50% relative decrease in mortality (for multivariable model risk adjustment: adjusted relative risk [RR], 0.51; 95% confidence interval [CI], 0.50–0.52; for propensity score risk adjustment: adjusted RR, 0.54; 95% CI, 0.53–0.55; and for propensity-based matching: adjusted RR, 0.54; 95% CI, 0.52–0.56). Using regional catheterization rate as an instrument, instrumental variable analysis showed a 16% relative decrease in mortality (adjusted RR, 0.84; 95% CI, 0.79–0.90). The survival benefits of routine invasive care from randomized clinical trials are between 8% and 21 %. Conclusions Estimates of the observational association of cardiac catheterization with long-term AMI mortality are highly sensitive to analytic method. All standard risk-adjustment methods have the same limitations regarding removal of unmeasured treatment selection biases. Compared with standard modeling, instrumental variable analysis may produce less biased estimates of treatment effects, but is more suited to answering policy questions than specific clinical questions. PMID:17227979

Gene expression variability in human hepatic drug metabolizing enzymes and transporters.

PubMed

Yang, Lun; Price, Elvin T; Chang, Ching-Wei; Li, Yan; Huang, Ying; Guo, Li-Wu; Guo, Yongli; Kaput, Jim; Shi, Leming; Ning, Baitang

2013-01-01

Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs) in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

Operationalizing hippocampal volume as an enrichment biomarker for amnestic MCI trials: effect of algorithm, test-retest variability and cut-point on trial cost, duration and sample size

PubMed Central

Yu, P.; Sun, J.; Wolz, R.; Stephenson, D.; Brewer, J.; Fox, N.C.; Cole, P.E.; Jack, C.R.; Hill, D.L.G.; Schwarz, A.J.

2014-01-01

Objective To evaluate the effect of computational algorithm, measurement variability and cut-point on hippocampal volume (HCV)-based patient selection for clinical trials in mild cognitive impairment (MCI). Methods We used normal control and amnestic MCI subjects from ADNI-1 as normative reference and screening cohorts. We evaluated the enrichment performance of four widely-used hippocampal segmentation algorithms (FreeSurfer, HMAPS, LEAP and NeuroQuant) in terms of two-year changes in MMSE, ADAS-Cog and CDR-SB. We modeled the effect of algorithm, test-retest variability and cut-point on sample size, screen fail rates and trial cost and duration. Results HCV-based patient selection yielded not only reduced sample sizes (by ~40–60%) but also lower trial costs (by ~30–40%) across a wide range of cut-points. Overall, the dependence on the cut-point value was similar for the three clinical instruments considered. Conclusion These results provide a guide to the choice of HCV cut-point for aMCI clinical trials, allowing an informed trade-off between statistical and practical considerations. PMID:24211008

[Does the Youth Psychopathic Traits Inventory (YPI) identify a clinically relevant subgroup among young offenders?].

PubMed

Mingers, Daniel; Köhler, Denis; Huchzermeier, Christian; Hinrichs, Günter

2017-01-01

Does the Youth Psychopathic Traits Inventory identify one or more high-risk subgroups among young offenders? Which recommendations for possible courses of action can be derived for individual clinical or forensic cases? Method: Model-based cluster analysis (Raftery, 1995) was conducted on a sample of young offenders (N = 445, age 14–22 years, M = 18.5, SD = 1.65). The resulting model was then tested for differences between clusters with relevant context variables of psychopathy. The variables included measures of intelligence, social competence, drug use, and antisocial behavior. Results: Three clusters were found (Low Trait, Impulsive/Irresponsible, Psychopathy) that differ highly significantly concerning YPI scores and the variables mentioned above. The YPI Scores Δ Low = 4.28 (Low Trait – Impulsive/Irresponsible) and Δ High = 6.86 (Impulsive/Irresponsible – Psychopathy) were determined to be thresholds between the clusters. The allocation of a person to be assessed within the calculated clusters allows for an orientation of consequent tests beyond the diagnosis of psychopathy. We conclude that the YPI is a valuable instrument for the assessment of young offenders, as it yields clinically and forensically relevant information concerning the cause and expected development of psychopathological behavior.

How are patient populations characterized in studies investigating depression in advanced cancer? Results from a systematic literature review.

PubMed

Janberidze, Elene; Hjermstad, Marianne Jensen; Haugen, Dagny Faksvåg; Sigurdardottir, Katrin Ruth; Løhre, Erik Torbjørn; Lie, Hanne Cathrine; Loge, Jon Håvard; Kaasa, Stein; Knudsen, Anne Kari

2014-10-01

Prevalence rates of depression in patients with advanced cancer vary considerably. This may be because of heterogeneous samples and use of different assessment methods. Adequate sample descriptions and consistent use of measures are needed to be able to generalize research findings and apply them to clinical practice. Our objective was twofold: First, to investigate which clinically important variables were used to describe the samples in studies of depression in patients with advanced cancer; and second, to examine the methods used for assessing and classifying depression in these studies. PubMed, PsycINFO, Embase, and CINAHL were searched combining search term groups representing "depression," "palliative care," and "advanced cancer" covering 2007-2011. Titles and abstracts were screened, and relevant full-text articles were evaluated independently by two authors. Information on 32 predefined variables on cancer disease, treatment, sociodemographics, depression-related factors, and assessment methods was extracted from the articles. After removing duplicates, 916 citations were screened of which 59 articles were retained. Age, gender, and stage of the cancer disease were the most frequently reported variables. Depression-related variables were rarely reported, for example, antidepressant use (17%) and previous depressive episodes (12%). Only 25% of the studies assessed and classified depression according to a validated diagnostic system. Current practice for describing sample characteristics and assessing depression varies greatly between studies. A more standardized practice is recommended to enhance the generalizability and utility of findings. Stakeholders are encouraged to work toward a common standard for sample descriptions. Copyright © 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

PubMed Central

2018-01-01

Objective To study the performance of multifocal-visual-evoked-potential (mfVEP) signals filtered using empirical mode decomposition (EMD) in discriminating, based on amplitude, between control and multiple sclerosis (MS) patient groups, and to reduce variability in interocular latency in control subjects. Methods MfVEP signals were obtained from controls, clinically definitive MS and MS-risk progression patients (radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS)). The conventional method of processing mfVEPs consists of using a 1–35 Hz bandpass frequency filter (XDFT). The EMD algorithm was used to decompose the XDFT signals into several intrinsic mode functions (IMFs). This signal processing was assessed by computing the amplitudes and latencies of the XDFT and IMF signals (XEMD). The amplitudes from the full visual field and from ring 5 (9.8–15° eccentricity) were studied. The discrimination index was calculated between controls and patients. Interocular latency values were computed from the XDFT and XEMD signals in a control database to study variability. Results Using the amplitude of the mfVEP signals filtered with EMD (XEMD) obtains higher discrimination index values than the conventional method when control, MS-risk progression (RIS and CIS) and MS subjects are studied. The lowest variability in interocular latency computations from the control patient database was obtained by comparing the XEMD signals with the XDFT signals. Even better results (amplitude discrimination and latency variability) were obtained in ring 5 (9.8–15° eccentricity of the visual field). Conclusions Filtering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies. This could be applied to assess visual cortex activity in MS diagnosis and evolution studies. PMID:29677200

Deciphering Sources of Variability in Clinical Pathology.

PubMed

Tripathi, Niraj K; Everds, Nancy E; Schultze, A Eric; Irizarry, Armando R; Hall, Robert L; Provencher, Anne; Aulbach, Adam

2017-01-01

The objectives of this session were to explore causes of variability in clinical pathology data due to preanalytical and analytical variables as well as study design and other procedures that occur in toxicity testing studies. The presenters highlighted challenges associated with such variability in differentiating test article-related effects from the effects of experimental procedures and its impact on overall data interpretation. These presentations focused on preanalytical and analytical variables and study design-related factors and their influence on clinical pathology data, and the importance of various factors that influence data interpretation including statistical analysis and reference intervals. Overall, these presentations touched upon potential effect of many variables on clinical pathology parameters, including animal physiology, sample collection process, specimen handling and analysis, study design, and some discussion points on how to manage those variables to ensure accurate interpretation of clinical pathology data in toxicity studies. This article is a brief synopsis of presentations given in a session entitled "Deciphering Sources of Variability in Clinical Pathology-It's Not Just about the Numbers" that occurred at the 35th Annual Symposium of the Society of Toxicologic Pathology in San Diego, California.

Biopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score

NASA Astrophysics Data System (ADS)

Khan, Adnan Mujahid; Yuan, Yinyin

2016-11-01

The number of tumour biopsies required for a good representation of tumours has been controversial. An important factor to consider is intra-tumour heterogeneity, which can vary among cancer types and subtypes. Immune cells in particular often display complex infiltrative patterns, however, there is a lack of quantitative understanding of the spatial heterogeneity of immune cells and how this fundamental biological nature of human tumours influences biopsy variability and treatment resistance. We systematically investigate biopsy variability for the lymphocytic infiltrate in 998 breast tumours using a novel virtual biopsy method. Across all breast cancers, we observe a nonlinear increase in concordance between the biopsy and whole-tumour score of lymphocytic infiltrate with increasing number of biopsies, yet little improvement is gained with more than four biopsies. Interestingly, biopsy variability of lymphocytic infiltrate differs considerably among breast cancer subtypes, with the human epidermal growth factor receptor 2-positive (HER2+) subtype having the highest variability. We subsequently identify a quantitative measure of spatial variability that predicts disease-specific survival in HER2+ subtype independent of standard clinical variables (node status, tumour size and grade). Our study demonstrates how systematic methods provide new insights that can influence future study design based on a quantitative knowledge of tumour heterogeneity.

The Novel Quantitative Technique for Assessment of Gait Symmetry Using Advanced Statistical Learning Algorithm

PubMed Central

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis. PMID:25705672

The novel quantitative technique for assessment of gait symmetry using advanced statistical learning algorithm.

PubMed

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.

A Low-Effort, Clinic-Wide Intervention Improves Attendance for HIV Primary Care

PubMed Central

Gardner, Lytt I.; Marks, Gary; Craw, Jason A.; Wilson, Tracey E.; Drainoni, Mari-Lynn; Moore, Richard D.; Mugavero, Michael J.; Rodriguez, Allan E.; Bradley-Springer, Lucy A.; Holman, Susan; Keruly, Jeanne C.; Sullivan, Meg; Skolnik, Paul R.; Malitz, Faye; Metsch, Lisa R.; Raper, James L.; Giordano, Thomas P.

2012-01-01

Background. Retention in care for human immunodeficiency virus (HIV)–infected patients is a National HIV/AIDS Strategy priority. We hypothesized that retention could be improved with coordinated messages to encourage patients' clinic attendance. We report here the results of the first phase of the Centers for Disease Control and Prevention/Health Resources and Services Administration Retention in Care project. Methods. Six HIV-specialty clinics participated in a cross-sectionally sampled pretest-posttest evaluation of brochures, posters, and messages that conveyed the importance of regular clinic attendance. 10 018 patients in 2008–2009 (preintervention period) and 11 039 patients in 2009–2010 (intervention period) were followed up for clinic attendance. Outcome variables were the percentage of patients who kept 2 consecutive primary care visits and the mean proportion of all primary care visits kept. Stratification variables were: new, reengaging, and active patients, HIV RNA viral load, CD4 cell count, age, sex, race or ethnicity, risk group, number of scheduled visits, and clinic site. Data were analyzed by multivariable log-binomial and linear models using generalized estimation equation methods. Results. Clinic attendance for primary care was significantly higher in the intervention versus preintervention year. Overall relative improvement was 7.0% for keeping 2 consecutive visits and 3.0% for the mean proportion of all visits kept (P < .0001). Larger relative improvement for both outcomes was observed for new or reengaging patients, young patients and patients with elevated viral loads. Improved attendance among the new or reengaging patients was consistent across the 6 clinics, and less consistent across clinics for active patients. Conclusion. Targeted messages on staying in care, which were delivered at minimal effort and cost, improved clinic attendance, especially for new or reengaging patients, young patients, and those with elevated viral loads. PMID:22828593

Combining biological and psychosocial baseline variables did not improve prediction of outcome of a very-low-energy diet in a clinic referral population.

PubMed

Sumithran, P; Purcell, K; Kuyruk, S; Proietto, J; Prendergast, L A

2018-02-01

Consistent, strong predictors of obesity treatment outcomes have not been identified. It has been suggested that broadening the range of predictor variables examined may be valuable. We explored methods to predict outcomes of a very-low-energy diet (VLED)-based programme in a clinically comparable setting, using a wide array of pre-intervention biological and psychosocial participant data. A total of 61 women and 39 men (mean ± standard deviation [SD] body mass index: 39.8 ± 7.3 kg/m 2 ) underwent an 8-week VLED and 12-month follow-up. At baseline, participants underwent a blood test and assessment of psychological, social and behavioural factors previously associated with treatment outcomes. Logistic regression, linear discriminant analysis, decision trees and random forests were used to model outcomes from baseline variables. Of the 100 participants, 88 completed the VLED and 42 attended the Week 60 visit. Overall prediction rates for weight loss of ≥10% at weeks 8 and 60, and attrition at Week 60, using combined data were between 77.8 and 87.6% for logistic regression, and lower for other methods. When logistic regression analyses included only baseline demographic and anthropometric variables, prediction rates were 76.2-86.1%. In this population, considering a wide range of biological and psychosocial data did not improve outcome prediction compared to simply-obtained baseline characteristics. © 2017 World Obesity Federation.

Estimation of Hidden State Variables of the Intracranial System Using Constrained Nonlinear Kalman Filters

PubMed Central

Nenov, Valeriy; Bergsneider, Marvin; Glenn, Thomas C.; Vespa, Paul; Martin, Neil

2007-01-01

Impeded by the rigid skull, assessment of physiological variables of the intracranial system is difficult. A hidden state estimation approach is used in the present work to facilitate the estimation of unobserved variables from available clinical measurements including intracranial pressure (ICP) and cerebral blood flow velocity (CBFV). The estimation algorithm is based on a modified nonlinear intracranial mathematical model, whose parameters are first identified in an offline stage using a nonlinear optimization paradigm. Following the offline stage, an online filtering process is performed using a nonlinear Kalman filter (KF)-like state estimator that is equipped with a new way of deriving the Kalman gain satisfying the physiological constraints on the state variables. The proposed method is then validated by comparing different state estimation methods and input/output (I/O) configurations using simulated data. It is also applied to a set of CBFV, ICP and arterial blood pressure (ABP) signal segments from brain injury patients. The results indicated that the proposed constrained nonlinear KF achieved the best performance among the evaluated state estimators and that the state estimator combined with the I/O configuration that has ICP as the measured output can potentially be used to estimate CBFV continuously. Finally, the state estimator combined with the I/O configuration that has both ICP and CBFV as outputs can potentially estimate the lumped cerebral arterial radii, which are not measurable in a typical clinical environment. PMID:17281533

DIAGNOSIS AND TREATMENT OF POSTERIOR INTEROSSEOUS NERVE ENTRAPMENT: SYSTEMATIC REVIEW

PubMed Central

MORAES, MARCO AURÉLIO DE; GONÇALVES, RUBENS GUILHERME; SANTOS, JOÃO BAPTISTA GOMES DOS; BELLOTI, JOÃO CARLOS; FALOPPA, FLÁVIO; MORAES, VINÍCIUS YNOE DE

2017-01-01

ABSTRACT Compressive syndromes of the radial nerve have different presentations. There is no consensus on diagnostic and therapeutic methods. The aim of this review is to summarize such methods. Eletronic searches related terms, held in databases (1980-2016): Pubmed (via Medline), Lilacs (via Scielo) and Google Scholar. Through pre-defined protocol, we identified relevant studies. We excluded case reports. Aspects of diagnosis and treatment were synthesized for analysis and tables. Quantitative analyzes were followed by their dispersion variables. Fourteen studies were included. All studies were considered as level IV evidence. Most studies consider aspects of clinical history and provocative maneuvers. There is no consensus on the use of electromyography, and methods are heterogeneous. Studies have shown that surgical treatment (muscle release and neurolysis) has variable success rate, ranging from 20 to 96.5%. Some studies applied self reported scores, though the heterogeneity of the population does not allow inferential analyzes on the subject. few complications reported. Most studies consider the diagnosis of compressive radial nerve syndromes essentially clinical. The most common treatment was combined muscle release and neurolysis, with heterogeneous results. There is a need for comparative studies. Level of Evidence III, Systematic Review. PMID:28642652

Exploration of a variation of the bottle buoyancy technique for the assessment of body composition.

PubMed

Gulick, Dawn T; Geigle, Paula Richley

2003-05-01

Hydrostatic weighing has long been recognized as a reliable and valid method for the assessment of body composition. An alternative method known as bottle buoyancy (BB) was introduced by Katch, Hortobagyi, and Denahan in 1989. The purpose of this clinical investigation was to determine the accuracy of the BB technique using an 11-L container. Sixteen individuals (8 men, 8 women) were weighed hydrostatically using a chair/scale and the BB technique. The overall intraclass correlation coefficient for the two techniques was 0.9537. A 2-variable ANOVA was significant for gender but not for technique, and there was no interaction between variables. Thus, the BB technique appears to be an accurate substitute for the chair/scale technique for hydrostatic weighing. The BB method does not involve elaborate equipment and is portable. It could be improved with the use of multiple bottles of various volumes or a calibrated bottle to minimize the number of trials needed for accurate measurements. BB is a valuable, simple clinical tool for assessing body composition based on the principles of hydrostatic weighing and can be performed in any high school, college, or community swimming pool.

Network Analysis to Risk Stratify Patients With Exercise Intolerance.

PubMed

Oldham, William M; Oliveira, Rudolf K F; Wang, Rui-Sheng; Opotowsky, Alexander R; Rubins, David M; Hainer, Jon; Wertheim, Bradley M; Alba, George A; Choudhary, Gaurav; Tornyos, Adrienn; MacRae, Calum A; Loscalzo, Joseph; Leopold, Jane A; Waxman, Aaron B; Olschewski, Horst; Kovacs, Gabor; Systrom, David M; Maron, Bradley A

2018-03-16

Current methods assessing clinical risk because of exercise intolerance in patients with cardiopulmonary disease rely on a small subset of traditional variables. Alternative strategies incorporating the spectrum of factors underlying prognosis in at-risk patients may be useful clinically, but are lacking. Use unbiased analyses to identify variables that correspond to clinical risk in patients with exercise intolerance. Data from 738 consecutive patients referred for invasive cardiopulmonary exercise testing at a single center (2011-2015) were analyzed retrospectively (derivation cohort). A correlation network of invasive cardiopulmonary exercise testing parameters was assembled using |r|>0.5. From an exercise network of 39 variables (ie, nodes) and 98 correlations (ie, edges) corresponding to P <9.5e -46 for each correlation, we focused on a subnetwork containing peak volume of oxygen consumption (pVo 2 ) and 9 linked nodes. K-mean clustering based on these 10 variables identified 4 novel patient clusters characterized by significant differences in 44 of 45 exercise measurements ( P <0.01). Compared with a probabilistic model, including 23 independent predictors of pVo 2 and pVo 2 itself, the network model was less redundant and identified clusters that were more distinct. Cluster assignment from the network model was predictive of subsequent clinical events. For example, a 4.3-fold ( P <0.0001; 95% CI, 2.2-8.1) and 2.8-fold ( P =0.0018; 95% CI, 1.5-5.2) increase in hazard for age- and pVo 2 -adjusted all-cause 3-year hospitalization, respectively, were observed between the highest versus lowest risk clusters. Using these data, we developed the first risk-stratification calculator for patients with exercise intolerance. When applying the risk calculator to patients in 2 independent invasive cardiopulmonary exercise testing cohorts (Boston and Graz, Austria), we observed a clinical risk profile that paralleled the derivation cohort. Network analyses were used to identify novel exercise groups and develop a point-of-care risk calculator. These data expand the range of useful clinical variables beyond pVo 2 that predict hospitalization in patients with exercise intolerance. © 2018 American Heart Association, Inc.

Maternal and neonatal epidemiological features in clinical subtypes of preterm-birth

PubMed Central

Gimenez, Lucas G.; Krupitzki, Hugo B.; Momany, Allison M.; Gili, Juan A.; Poletta, Fernando A.; Campaña, Hebe; Cosentino, Viviana R.; Saleme, César; Pawluk, Mariela; Murray, Jeffrey C.; Castilla, Eduardo E.; Gadow, Enrique C.; Lopez-Camelo, Jorge S.

2016-01-01

Objective This study was designed to characterize and compare the maternal and newborn epidemiological characteristics through analysis of environmental factors, socio-demographic characteristics, and clinical characteristics between the different clinical subtypes of preterm birth (PTB): Idiopathic (PTB-I), premature rupture of the membranes (PTB-PPROM) and medically indicated (PTB-M). The two subtypes PTB-I and PTB-PPROM grouped are called spontaneous preterm births (PTB-S). Methods A retrospective, observational study was conducted in 1.291 preterm non-malformed singleton live-born children to nulliparous and multiparous mother’s in Tucumán-Argentina between 2005 and 2010. Over 50 maternal variables and ten newborn variables were compared between the different clinical subtypes. The comparisons were done to identify heterogeneity between subtypes of preterm birth: (PTB-S) vs. (PTB-M), and within spontaneous subtype: (PTB-I) vs. (PTB-PPROM). In the same way, two conditional logistic multivariate regressions were used to compare the odds ratio (OR) between PTB-S and PTB-M, as well as PTB-I and PTB-PPROM. We matched for maternal age when comparing maternal variables and gestational age when comparing infant variables. Results The PTB-I subtype was characterized by younger mothers of lower socioeconomic status, PTB-PPROM was characterized by environmental factors resulting from inflammatory processes, and PTB-M was characterized by increased maternal or fetal risk pregnancies. Conclusions The main risk factor for PTB-I and PTB-M was having had a prior preterm delivery, however previous spontaneous abortion was not a risk factor, suggesting a reproductive selection mechanism. PMID:26701680

External Validation of the HERNIAscore: An Observational Study.

PubMed

Cherla, Deepa V; Moses, Maya L; Mueck, Krislynn M; Hannon, Craig; Ko, Tien C; Kao, Lillian S; Liang, Mike K

2017-09-01

The HERNIAscore is a ventral incisional hernia (VIH) risk assessment tool that uses only preoperative variables and predictable intraoperative variables. The aim of this study was to validate and modify, if needed, the HERNIAscore in an external dataset. This was a retrospective observational study of all patients undergoing resection for gastrointestinal malignancy from 2011 through 2015 at a safety-net hospital. The primary end point was clinical postoperative VIH. Patients were stratified into low-risk, medium-risk, and high-risk groups based on HERNIAscore. A revised HERNIAscore was calculated with the addition of earlier abdominal operation as a categorical variable. Cox regression of incisional hernia with stratification by risk class was performed. Incidence rates of clinical VIH formation within each risk class were also calculated. Two hundred and forty-seven patents were enrolled. On Cox regression, in addition to the 3 variables of the HERNIAscore (BMI, COPD, and incision length), earlier abdominal operation was also predictive of VIH. The revised HERNIAscore demonstrated improved predictive accuracy for clinical VIH. Although the original HERNIAscore effectively stratified the risk of an incisional radiographic VIH developing, the revised HERNIAscore provided a statistically significant stratification for both clinical and radiographic VIHs in this patient cohort. We have externally validated and improved the HERNIAscore. The revised HERNIAscore uses BMI, incision length, COPD, and earlier abdominal operation to predict risk of postoperative incisional hernia. Future research should assess methods to prevent incisional hernias in moderate-to-high risk patients. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Clinical Assessment of Cognitive Function in Patients with Head and Neck Cancer: Prevalence and Correlates.

PubMed

Williams, Amy M; Lindholm, Jamie; Siddiqui, Farzan; Ghanem, Tamer A; Chang, Steven S

2017-11-01

Objective Identify the prevalence and clinical correlates of cognitive impairment in patients presenting for treatment of head and neck cancer (HNC) using brief screening within a multidisciplinary care team. Study Design A case series with planned data collection of cognitive function, quality of life (QoL), and psychosocial variables. Setting Urban Midwest academic medical center. Subjects and Methods In total, 209 consecutive patients with a diagnosis of HNC between August 2015 and September 2016 who had a pretreatment assessment with a clinical health psychologist. At pretreatment assessment, the Montreal Cognitive Assessment (MoCA), a brief screening tool for cognitive function, was administered along with a semistructured interview to gather information on psychiatric symptoms, social support, and substance use. Patient information, including demographics, clinical variables, and psychosocial variables, was extracted via chart review. A subset of patients with HNC completed the Functional Assessment of Cancer Therapy-Head and Neck Cancer at pretreatment assessment and was included in the QoL analyses. Results Cognitive impairment was associated with current alcohol use, past tobacco use and number of pack years, time in radiotherapy, and adherence to treatment recommendations. Social, emotional, and functional QoL scales were associated with cognitive impairment, including executive function, language, and memory. Conclusion Cognitive impairment is common in patients with HNC, and there are important associations between cognitive impairment and psychosocial, QoL, and treatment adherence variables. The results argue for the incorporation of cognitive screening as part of pretreatment assessment for patients, as well as further research into more direct, causal relationships via longitudinal, prospective studies.

Variability in Cortical Representations of Speech Sound Perception

ERIC Educational Resources Information Center

Boatman, Dana F.

2007-01-01

Recent brain mapping studies have provided new insights into the cortical systems that mediate human speech perception. Electrocortical stimulation mapping (ESM) is a brain mapping method that is used clinically to localize cortical functions in neurosurgical patients. Recent ESM studies have yielded new insights into the cortical systems that…

Effects of Phonetic Context on Relative Fundamental Frequency

ERIC Educational Resources Information Center

Lien, Yu-An S.; Gattuccio, Caitlin I.; Stepp, Cara E.

2014-01-01

Purpose: The effect of phonetic context on relative fundamental frequency (RFF) was examined, in order to develop stimuli sets with minimal within-speaker variability that can be implemented in future clinical protocols. Method: Sixteen speakers with healthy voices produced RFF stimuli. Uniform utterances consisted of 3 repetitions of the same…

Connecting clinical and actuarial prediction with rule-based methods.

PubMed

Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

2015-06-01

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

Comparability of clinical wear measurements by optical 3D laser scanning in two different centers.

PubMed

Stober, Thomas; Heuschmid, Navina; Zellweger, Gaby; Rousson, Valentin; Rues, Stefan; Heintze, Siegward D

2014-05-01

The purpose of this study was to compare the use of different variables to measure the clinical wear of two denture tooth materials in two analysis centers. Twelve edentulous patients were provided with full dentures. Two different denture tooth materials (experimental material and control) were placed randomly in accordance with the split-mouth design. For wear measurements, impressions were made after an adjustment phase of 1-2 weeks and after 6, 12, 18, and 24 months. The occlusal wear of the posterior denture teeth of 11 subjects was assessed in two study centers by use of plaster replicas and 3D laser-scanning methods. In both centers sequential scans of the occlusal surfaces were digitized and superimposed. Wear was described by use of four different variables. Statistical analysis was performed after log-transformation of the wear data by use of the Pearson and Lin correlation and by use of a mixed linear model. Mean occlusal vertical wear of the denture teeth after 24 months was between 120μm and 212μm, depending on wear variable and material. For three of the four variables, wear of the experimental material was statistically significantly less than that of the control. Comparison of the two study centers, however, revealed correlation of the wear variables was only moderate whereas strong correlation was observed among the different wear variables evaluated by each center. Moderate correlation was observed for clinical wear measurements by optical 3D laser scanning in two different study centers. For the two denture tooth materials, wear measurements limited to the attrition zones led to the same qualitative assessment. Copyright © 2014 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

In vivo short-term precision of hip structure analysis variables in comparison with bone mineral density using paired dual-energy X-ray absorptiometry scans from multi-center clinical trials.

PubMed

Khoo, Benjamin C C; Beck, Thomas J; Qiao, Qi-Hong; Parakh, Pallav; Semanick, Lisa; Prince, Richard L; Singer, Kevin P; Price, Roger I

2005-07-01

Hip structural analysis (HSA) is a technique for extracting strength-related structural dimensions of bone cross-sections from two-dimensional hip scan images acquired by dual energy X-ray absorptiometry (DXA) scanners. Heretofore the precision of the method has not been thoroughly tested in the clinical setting. Using paired scans from two large clinical trials involving a range of different DXA machines, this study reports the first precision analysis of HSA variables, in comparison with that of conventional bone mineral density (BMD) on the same scans. A key HSA variable, section modulus (Z), biomechanically indicative of bone strength during bending, had a short-term precision percentage coefficient of variation (CV%) in the femoral neck of 3.4-10.1%, depending on the manufacturer or model of the DXA equipment. Cross-sectional area (CSA), a determinant of bone strength during axial loading and closely aligned with conventional DXA bone mineral content, had a range of CV% from 2.8% to 7.9%. Poorer precision was associated with inadequate inclusion of the femoral shaft or femoral head in the DXA-scanned hip region. Precision of HSA-derived BMD varied between 2.4% and 6.4%. Precision of DXA manufacturer-derived BMD varied between 1.9% and 3.4%, arising from the larger analysis region of interest (ROI). The precision of HSA variables was not generally dependent on magnitude, subject height, weight, or conventional femoral neck densitometric variables. The generally poorer precision of key HSA variables in comparison with conventional DXA-derived BMD highlights the critical roles played by correct limb repositioning and choice of an adequate and appropriately positioned ROI.

Factors influencing the perceived quality of clinical supervision of occupational therapists in a large Australian state.

PubMed

Martin, Priya; Kumar, Saravana; Lizarondo, Lucylynn; Tyack, Zephanie

2016-10-01

Clinical supervision is important for effective health service delivery, professional development and practice. Despite its importance there is a lack of evidence regarding the factors that improve its quality. This study aimed to investigate the factors that influence the quality of clinical supervision of occupational therapists employed in a large public sector health service covering mental health, paediatrics, adult physical and other practice areas. A mixed method, sequential explanatory study design was used consisting of two phases. This article reports the quantitative phase (Phase One) which involved administration of the Manchester Clinical Supervision Scale (MCSS-26) to 207 occupational therapists. Frequency of supervision sessions, choice of supervisor and the type of supervision were found to be the predictor variables with a positive and significant influence on the quality of clinical supervision. Factors such as age, length of supervision and the area of practice were found to be the predictor variables with a negative and significant influence on the quality of clinical supervision. Factors that influence the perceived quality of clinical supervision among occupational therapists have been identified. High quality clinical supervision is an important component of clinical governance and has been shown to be beneficial to practitioners, patients and the organisation. Information on factors that make clinical supervision effective identified in this study can be added to existing supervision training and practices to improve the quality of clinical supervision. © 2016 Occupational Therapy Australia.

A peer learning intervention for nursing students in clinical practice education: A quasi-experimental study.

PubMed

Pålsson, Ylva; Mårtensson, Gunilla; Swenne, Christine Leo; Ädel, Eva; Engström, Maria

2017-04-01

Studies of peer learning indicate that the model enables students to practice skills useful in their future profession, such as communication, cooperation, reflection and independence. However, so far most studies have used a qualitative approach and none have used a quasi-experimental design to study effects of nursing students' peer learning in clinical practice. To investigate the effects of peer learning in clinical practice education on nursing students' self-rated performance. Quasi-experimental. The study was conducted during nursing students' clinical practice. All undergraduate nursing students (n=87) attending their first clinical practice were approached. Seventy students out of 87 answered the questionnaires at both baseline and follow-up (42 of 46 in the intervention group and 28 of 39 in the comparison group). During the first two weeks of the clinical practice period, all students were supervised traditionally. Thereafter, the intervention group received peer learning the last two weeks, and the comparison group received traditional supervision. Questionnaire data were collected on nursing students' self-rated performance during the second (baseline) and last (follow-up) week of their clinical practice. Self-efficacy was improved in the intervention group and a significant interaction effect was found for changes over time between the two groups. For the other self-rated variables/tests, there were no differences in changes over time between the groups. Studying each group separately, the intervention group significantly improved on thirteen of the twenty variables/tests over time and the comparison group improved on four. The results indicate that peer learning is a useful method which improves nursing students' self-efficacy to a greater degree than traditional supervision does. Regarding the other self-rated performance variables, no interaction effects were found. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model

PubMed Central

Orini, Michele; Mincholé, Ana; Monasterio, Violeta; Cygankiewicz, Iwona; Bayés de Luna, Antonio; Martínez, Juan Pablo

2017-01-01

Background Sudden cardiac death (SCD) and pump failure death (PFD) are common endpoints in chronic heart failure (CHF) patients, but prevention strategies are different. Currently used tools to specifically predict these endpoints are limited. We developed risk models to specifically assess SCD and PFD risk in CHF by combining ECG markers and clinical variables. Methods The relation of clinical and ECG markers with SCD and PFD risk was assessed in 597 patients enrolled in the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study. ECG indices included: turbulence slope (TS), reflecting autonomic dysfunction; T-wave alternans (TWA), reflecting ventricular repolarization instability; and T-peak-to-end restitution (ΔαTpe) and T-wave morphology restitution (TMR), both reflecting changes in dispersion of repolarization due to heart rate changes. Standard clinical indices were also included. Results The indices with the greatest SCD prognostic impact were gender, New York Heart Association (NYHA) class, left ventricular ejection fraction, TWA, ΔαTpe and TMR. For PFD, the indices were diabetes, NYHA class, ΔαTpe and TS. Using a model with only clinical variables, the hazard ratios (HRs) for SCD and PFD for patients in the high-risk group (fifth quintile of risk score) with respect to patients in the low-risk group (first and second quintiles of risk score) were both greater than 4. HRs for SCD and PFD increased to 9 and 11 when using a model including only ECG markers, and to 14 and 13, when combining clinical and ECG markers. Conclusion The inclusion of ECG markers capturing complementary pro-arrhythmic and pump failure mechanisms into risk models based only on standard clinical variables substantially improves prediction of SCD and PFD in CHF patients. PMID:29020031

Evaluation of direct-to-consumer low-volume lab tests in healthy adults.

PubMed

Kidd, Brian A; Hoffman, Gabriel; Zimmerman, Noah; Li, Li; Morgan, Joseph W; Glowe, Patricia K; Botwin, Gregory J; Parekh, Samir; Babic, Nikolina; Doust, Matthew W; Stock, Gregory B; Schadt, Eric E; Dudley, Joel T

2016-05-02

Clinical laboratory tests are now being prescribed and made directly available to consumers through retail outlets in the USA. Concerns with these test have been raised regarding the uncertainty of testing methods used in these venues and a lack of open, scientific validation of the technical accuracy and clinical equivalency of results obtained through these services. We conducted a cohort study of 60 healthy adults to compare the uncertainty and accuracy in 22 common clinical lab tests between one company offering blood tests obtained from finger prick (Theranos) and 2 major clinical testing services that require standard venipuncture draws (Quest and LabCorp). Samples were collected in Phoenix, Arizona, at an ambulatory clinic and at retail outlets with point-of-care services. Theranos flagged tests outside their normal range 1.6× more often than other testing services (P < 0.0001). Of the 22 lab measurements evaluated, 15 (68%) showed significant interservice variability (P < 0.002). We found nonequivalent lipid panel test results between Theranos and other clinical services. Variability in testing services, sample collection times, and subjects markedly influenced lab results. While laboratory practice standards exist to control this variability, the disparities between testing services we observed could potentially alter clinical interpretation and health care utilization. Greater transparency and evaluation of testing technologies would increase their utility in personalized health management. This work was supported by the Icahn Institute for Genomics and Multiscale Biology, a gift from the Harris Family Charitable Foundation (to J.T. Dudley), and grants from the NIH (R01 DK098242 and U54 CA189201, to J.T. Dudley, and R01 AG046170 and U01 AI111598, to E.E. Schadt).

Evaluation of Automated and Semi-Automated Scoring of Polysomnographic Recordings from a Clinical Trial Using Zolpidem in the Treatment of Insomnia

PubMed Central

Svetnik, Vladimir; Ma, Junshui; Soper, Keith A.; Doran, Scott; Renger, John J.; Deacon, Steve; Koblan, Ken S.

2007-01-01

Objective: To evaluate the performance of 2 automated systems, Morpheus and Somnolyzer24X7, with various levels of human review/editing, in scoring polysomnographic (PSG) recordings from a clinical trial using zolpidem in a model of transient insomnia. Methods: 164 all-night PSG recordings from 82 subjects collected during 2 nights of sleep, one under placebo and one under zolpidem (10 mg) treatment were used. For each recording, 6 different methods were used to provide sleep stage scores based on Rechtschaffen & Kales criteria: 1) full manual scoring, 2) automated scoring by Morpheus 3) automated scoring by Somnolyzer24X7, 4) automated scoring by Morpheus with full manual review, 5) automated scoring by Morpheus with partial manual review, 6) automated scoring by Somnolyzer24X7 with partial manual review. Ten traditional clinical efficacy measures of sleep initiation, maintenance, and architecture were calculated. Results: Pair-wise epoch-by-epoch agreements between fully automated and manual scores were in the range of intersite manual scoring agreements reported in the literature (70%-72%). Pair-wise epoch-by-epoch agreements between automated scores manually reviewed were higher (73%-76%). The direction and statistical significance of treatment effect sizes using traditional efficacy endpoints were essentially the same whichever method was used. As the degree of manual review increased, the magnitude of the effect size approached those estimated with fully manual scoring. Conclusion: Automated or semi-automated sleep PSG scoring offers valuable alternatives to costly, time consuming, and intrasite and intersite variable manual scoring, especially in large multicenter clinical trials. Reduction in scoring variability may also reduce the sample size of a clinical trial. Citation: Svetnik V; Ma J; Soper KA; Doran S; Renger JJ; Deacon S; Koblan KS. Evaluation of automated and semi-automated scoring of polysomnographic recordings from a clinical trial using zolpidem in the treatment of insomnia. SLEEP 2007;30(11):1562-1574. PMID:18041489

A practical approach to Sasang constitutional diagnosis using vocal features

PubMed Central

2013-01-01

Background Sasang constitutional medicine (SCM) is a type of tailored medicine that divides human beings into four Sasang constitutional (SC) types. Diagnosis of SC types is crucial to proper treatment in SCM. Voice characteristics have been used as an essential clue for diagnosing SC types. In the past, many studies tried to extract quantitative vocal features to make diagnosis models; however, these studies were flawed by limited data collected from one or a few sites, long recording time, and low accuracy. We propose a practical diagnosis model having only a few variables, which decreases model complexity. This in turn, makes our model appropriate for clinical applications. Methods A total of 2,341 participants’ voice recordings were used in making a SC classification model and to test the generalization ability of the model. Although the voice data consisted of five vowels and two repeated sentences per participant, we used only the sentence part for our study. A total of 21 features were extracted, and an advanced feature selection method—the least absolute shrinkage and selection operator (LASSO)—was applied to reduce the number of variables for classifier learning. A SC classification model was developed using multinomial logistic regression via LASSO. Results We compared the proposed classification model to the previous study, which used both sentences and five vowels from the same patient’s group. The classification accuracies for the test set were 47.9% and 40.4% for male and female, respectively. Our result showed that the proposed method was superior to the previous study in that it required shorter voice recordings, is more applicable to practical use, and had better generalization performance. Conclusions We proposed a practical SC classification method and showed that our model having fewer variables outperformed the model having many variables in the generalization test. We attempted to reduce the number of variables in two ways: 1) the initial number of candidate features was decreased by considering shorter voice recording, and 2) LASSO was introduced for reducing model complexity. The proposed method is suitable for an actual clinical environment. Moreover, we expect it to yield more stable results because of the model’s simplicity. PMID:24200041

The time has come for new models in febrile neutropenia: a practical demonstration of the inadequacy of the MASCC score.

PubMed

Carmona-Bayonas, A; Jiménez-Fonseca, P; Virizuela Echaburu, J; Sánchez Cánovas, M; Ayala de la Peña, F

2017-09-01

Since its publication more than 15 years ago, the MASCC score has been internationally validated any number of times and recommended by most clinical practice guidelines for the management of febrile neutropenia (FN) around the world. We have used an empirical data-supported simulated scenario to demonstrate that, despite everything, the MASCC score is impractical as a basis for decision-making. A detailed analysis of reasons supporting the clinical irrelevance of this model is performed. First, seven of its eight variables are "innocent bystanders" that contribute little to selecting low-risk candidates for ambulatory management. Secondly, the training series was hardly representative of outpatients with solid tumors and low-risk FN. Finally, the simultaneous inclusion of key variables both in the model and in the outcome explains its successful validation in various series of patients. Alternative methods of prognostic classification, such as the Clinical Index of Stable Febrile Neutropenia, have been specifically validated for patients with solid tumors and should replace the MASCC model in situations of clinical uncertainty.

Quantitative methods for evaluating the efficacy of thalamic deep brain stimulation in patients with essential tremor.

PubMed

Wastensson, Gunilla; Holmberg, Björn; Johnels, Bo; Barregard, Lars

2013-01-01

Deep brain stimulation (DBS) of the thalamus is a safe and efficient method for treatment of disabling tremor in patient with essential tremor (ET). However, successful tremor suppression after surgery requires careful selection of stimulus parameters. Our aim was to examine the possible use of certain quantitative methods for evaluating the efficacy of thalamic DBS in ET patients in clinical practice, and to compare these methods with traditional clinical tests. We examined 22 patients using the Essential Tremor Rating Scale (ETRS) and quantitative assessment of tremor with the stimulator both activated and deactivated. We used an accelerometer (CATSYS tremor Pen) for quantitative measurement of postural tremor, and a eurythmokinesimeter (EKM) to evaluate kinetic tremor in a rapid pointing task. The efficacy of DBS on tremor suppression was prominent irrespective of the method used. The agreement between clinical rating of postural tremor and tremor intensity as measured by the CATSYS tremor pen was relatively high (rs = 0.74). The agreement between kinetic tremor as assessed by the ETRS and the main outcome variable from the EKM test was low (rs = 0.34). The lack of agreement indicates that the EKM test is not comparable with the clinical test. Quantitative methods, such as the CATSYS tremor pen, could be a useful complement to clinical tremor assessment in evaluating the efficacy of DBS in clinical practice. Future studies should evaluate the precision of these methods and long-term impact on tremor suppression, activities of daily living (ADL) function and quality of life.

Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.

PubMed

Liu, Cong; Wang, Xujun; Genchev, Georgi Z; Lu, Hui

2017-07-15

New developments in high-throughput genomic technologies have enabled the measurement of diverse types of omics biomarkers in a cost-efficient and clinically-feasible manner. Developing computational methods and tools for analysis and translation of such genomic data into clinically-relevant information is an ongoing and active area of investigation. For example, several studies have utilized an unsupervised learning framework to cluster patients by integrating omics data. Despite such recent advances, predicting cancer prognosis using integrated omics biomarkers remains a challenge. There is also a shortage of computational tools for predicting cancer prognosis by using supervised learning methods. The current standard approach is to fit a Cox regression model by concatenating the different types of omics data in a linear manner, while penalty could be added for feature selection. A more powerful approach, however, would be to incorporate data by considering relationships among omics datatypes. Here we developed two methods: a SKI-Cox method and a wLASSO-Cox method to incorporate the association among different types of omics data. Both methods fit the Cox proportional hazards model and predict a risk score based on mRNA expression profiles. SKI-Cox borrows the information generated by these additional types of omics data to guide variable selection, while wLASSO-Cox incorporates this information as a penalty factor during model fitting. We show that SKI-Cox and wLASSO-Cox models select more true variables than a LASSO-Cox model in simulation studies. We assess the performance of SKI-Cox and wLASSO-Cox using TCGA glioblastoma multiforme and lung adenocarcinoma data. In each case, mRNA expression, methylation, and copy number variation data are integrated to predict the overall survival time of cancer patients. Our methods achieve better performance in predicting patients' survival in glioblastoma and lung adenocarcinoma. Copyright © 2017. Published by Elsevier Inc.

Multilevel Predictors of Clinic Adoption of State-Supported Trainings in Children’s Services

PubMed Central

Olin, Su-chin Serene; Chor, Ka Ho Brian; Weaver, James; Duan, Naihua; Kerker, Bonnie D.; Clark, Lisa J.; Cleek, Andrew F.; Hoagwood, Kimberly Eaton; Horwitz, Sarah McCue

2015-01-01

Objective Characteristics associated with participation in training in evidence-informed business and clinical practices by 346 outpatient mental health clinics licensed to treat youths in New York State were examined. Methods Clinic characteristics extracted from state administrative data were used as proxies for variables that have been linked with adoption of innovation (extraorganizational factors, agency factors, clinic provider-level profiles, and clinic client-level profiles). Multiple logistic regression models were used to assess the independent effects of theoretical variables on the clinics’ participation in state-supported business and clinical trainings between September 2011 and August 2013 and on the intensity of participation (low or high). Interaction effects between clinic characteristics and outcomes were explored. Results Clinic characteristics were predictive of any participation in trainings but were less useful in predicting intensity of participation. Clinics affiliated with larger (adjusted odds ratio [AOR]=.65, p<.01), more efficient agencies (AOR=.62, p<.05) and clinics that outsourced more clinical services (AOR=.60, p<.001) had lower odds of participating in any business-practice trainings. Participation in business trainings was associated with interaction effects between agency affiliation (hospital or community) and clinical staff capacity. Clinics with more full-time-equivalent clinical staff (AOR=1.52, p<.01) and a higher proportion of clients under age 18 (AOR=1.90, p<.001) had higher odds of participating in any clinical trainings. Participating clinics with larger proportions of youth clients had greater odds of being high adopters of clinical trainings (odds ratio=1.54, p<.01). Conclusions Clinic characteristics associated with uptake of business and clinical training could be used to target state technical assistance efforts. PMID:25686815

Medicine Based Evidence for Individualized Decision Making: Case Study of Systemic Lupus Erythematosus.

PubMed

Wivel, Ashley E; Lapane, Kate; Kleoudis, Christi; Singer, Burton H; Horwitz, Ralph I

2017-11-01

To guide management decisions for an index patient, evidence is required from comparisons between approximate matches to the profile of the index case, where some matches contain responses to treatment and others act as controls. We describe a method for constructing clinically relevant histories/profiles using data collected but unreported from 2 recent phase 3 randomized controlled trials assessing belimumab in subjects with clinically active and serologically positive systemic lupus erythematosus. Outcome was the Systemic lupus erythematosus Responder Index (SRI) measured at 52 weeks. Among 1175 subjects, we constructed an algorithm utilizing 11 trajectory variables including 4 biological, 2 clinical, and 5 social/behavioral. Across all biological and social/behavioral variables, the proportion of responders based on the SRI whose value indicated clinical worsening or no improvement ranged from 27.5% to 42.3%. Kappa values suggested poor agreement, indicating that each biological and patient-reported outcome provides different information than gleaned from the SRI. The richly detailed patient profiles needed to guide decision-making in clinical practice are sharply at odds with the limited information utilized in conventional randomized controlled trial analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

Investigating the Implications of a Variable RBE on Proton Dose Fractionation Across a Clinical Pencil Beam Scanned Spread-Out Bragg Peak

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

Marshall, Thomas I.; Chaudhary, Pankaj; Michaelidesová, Anna

2016-05-01

Purpose: To investigate the clinical implications of a variable relative biological effectiveness (RBE) on proton dose fractionation. Using acute exposures, the current clinical adoption of a generic, constant cell killing RBE has been shown to underestimate the effect of the sharp increase in linear energy transfer (LET) in the distal regions of the spread-out Bragg peak (SOBP). However, experimental data for the impact of dose fractionation in such scenarios are still limited. Methods and Materials: Human fibroblasts (AG01522) at 4 key depth positions on a clinical SOBP of maximum energy 219.65 MeV were subjected to various fractionation regimens with an interfractionmore » period of 24 hours at Proton Therapy Center in Prague, Czech Republic. Cell killing RBE variations were measured using standard clonogenic assays and were further validated using Monte Carlo simulations and parameterized using a linear quadratic formalism. Results: Significant variations in the cell killing RBE for fractionated exposures along the proton dose profile were observed. RBE increased sharply toward the distal position, corresponding to a reduction in cell sparing effectiveness of fractionated proton exposures at higher LET. The effect was more pronounced at smaller doses per fraction. Experimental survival fractions were adequately predicted using a linear quadratic formalism assuming full repair between fractions. Data were also used to validate a parameterized variable RBE model based on linear α parameter response with LET that showed considerable deviations from clinically predicted isoeffective fractionation regimens. Conclusions: The RBE-weighted absorbed dose calculated using the clinically adopted generic RBE of 1.1 significantly underestimates the biological effective dose from variable RBE, particularly in fractionation regimens with low doses per fraction. Coupled with an increase in effective range in fractionated exposures, our study provides an RBE dataset that can be used by the modeling community for the optimization of fractionated proton therapy.« less

Development of a novel diagnostic algorithm to predict NASH in HCV-positive patients.

PubMed

Gallotta, Andrea; Paneghetti, Laura; Mrázová, Viera; Bednárová, Adriana; Kružlicová, Dáša; Frecer, Vladimir; Miertus, Stanislav; Biasiolo, Alessandra; Martini, Andrea; Pontisso, Patrizia; Fassina, Giorgio

2018-05-01

Non-alcoholic steato-hepatitis (NASH) is a severe disease characterised by liver inflammation and progressive hepatic fibrosis, which may progress to cirrhosis and hepatocellular carcinoma. Clinical evidence suggests that in hepatitis C virus patients steatosis and NASH are associated with faster fibrosis progression and hepatocellular carcinoma. A safe and reliable non-invasive diagnostic method to detect NASH at its early stages is still needed to prevent progression of the disease. We prospectively enrolled 91 hepatitis C virus-positive patients with histologically proven chronic liver disease: 77 patients were included in our study; of these, 10 had NASH. For each patient, various clinical and serological variables were collected. Different algorithms combining squamous cell carcinoma antigen-immunoglobulin-M (SCCA-IgM) levels with other common clinical data were created to provide the probability of having NASH. Our analysis revealed a statistically significant correlation between the histological presence of NASH and SCCA-IgM, insulin, homeostasis model assessment, haemoglobin, high-density lipoprotein and ferritin levels, and smoke. Compared to the use of a single marker, algorithms that combined four, six or seven variables identified NASH with higher accuracy. The best diagnostic performance was obtained with the logistic regression combination, which included all seven variables correlated with NASH. The combination of SCCA-IgM with common clinical data shows promising diagnostic performance for the detection of NASH in hepatitis C virus patients.

Incidence of temonera, sulphuhydryl variables and cefotaximase genes associated with β-lactamase producing escherichia coli in clinical isolates

PubMed Central

Isaiah, Ibeh Nnana; Nche, Bikwe Thomas; Nwagu, Ibeh Georgina; Nwagu, Ibeh Isaiah

2011-01-01

Background: the occurrence of the different types of Extended spectrum beta Lactamase producing Escherichia coli with the, Sulphurhydryl variable, Temonera and the Cefotaximase have been on the rise Aim: The study was to determine the prevalence of extended spectrum beta lactamase gene resistance across the clinical isolates of hospitalized patients. Materials and Method: Three hundred and fifty isolates of Escherichia coli were received from different clinical specimens. The susceptibility profile of the isolates against 10 different antibiotics was examined, the MICs (Minimum Inhibitory Concentration) for ceftazidime were also determined using micro-broth dilution assay. Isolates showing MIC ≥ 6 μg/ml for ceftazidime were screened for ESBL (PCT)phenotypic confirmatory test and subjected to PCR (polymerase chain reaction) to further. Results: By disk diffusion test, there was resistance to ceftazidime and cefotaxime were 180(51.4%) and 120 (34.2%) respectively. However, all strains were susceptible to imipenem. 250 isolates showed MICs≥ 6 μg/ml for ceftazidime of which 180 (72%) were positive for extended spectrum beta lactamase. The prevalence of Sulphurhydryl variable, Temonera and the Cefotaximase among these isolates were 17.1%, 6.6% and 17%, respectively. Conclusion: For the identification of extended spectrum beta lactamase producing isolates it is recommended that clinical laboratories adopt simple test based on Cinical laboratory standard institute recommendation for confirming extended spectrum beta lactamase production in enterobacteriacea species. PMID:22363078

The current deconstruction of paradoxes: one sign of the ongoing methodological "revolution".

PubMed

Porta, Miquel; Vineis, Paolo; Bolúmar, Francisco

2015-10-01

The current deconstruction of paradoxes is one among several signs that a profound renewal of methods for clinical and epidemiological research is taking place; perhaps for some basic life sciences as well. The new methodological approaches have already deconstructed and explained long puzzling apparent paradoxes, including the (non-existent) benefits of obesity in diabetics, or of smoking in low birth weight. Achievements of the new methods also comprise the elucidation of the causal structure of long-disputed and highly complex questions, as Berkson's bias and Simpson's paradox, and clarifying reasons for deep controversies, as those on estrogens and endometrial cancer, or on adverse effects of hormone replacement therapy. These are signs that the new methods can go deeper and beyond the methods in current use. A major example of a highly relevant idea is: when we condition on a common effect of a pair of variables, then a spurious association between such pair is likely. The implications of these ideas are potentially vast. A substantial number of apparent paradoxes may simply be the result of collider biases, a source of selection bias that is common not just in epidemiologic research, but in many types of research in the health, life, and social sciences. The new approaches develop a new framework of concepts and methods, as collider, instrumental variables, d-separation, backdoor path and, notably, Directed Acyclic Graphs (DAGs). The current theoretical and methodological renewal-or, perhaps, "revolution"-may be changing deeply how clinical and epidemiological research is conceived and performed, how we assess the validity and relevance of findings, and how causal inferences are made. Clinical and basic researchers, among others, should get acquainted with DAGs and related concepts.

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting

PubMed Central

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-01-01

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.

PubMed

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-02-17

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes.

Predictors and Moderators of Treatment Response in Childhood Anxiety Disorders: Results from the CAMS Trial

PubMed Central

Compton, Scott N.; Peris, Tara S.; Almirall, Daniel; Birmaher, Boris; Sherrill, Joel; Kendall, Phillip C.; March, John S.; Gosch, Elizabeth A.; Ginsburg, Golda S.; Rynn, Moira A.; Piacentini, John C.; McCracken, James T.; Keeton, Courtney P.; Suveg, Cynthia M.; Aschenbrand, Sasha G.; Sakolsky, Dara; Iyengar, Satish; Walkup, John T.; Albano, Anne Marie

2014-01-01

Objective To examine predictors and moderators of treatment outcomes among 488 youth ages 7-17 years (50% female; 74% ≤ 12 years) with DSM-IV diagnoses of separation anxiety disorder, social phobia, or generalized anxiety disorder who were randomly assigned to receive either cognitive behavior therapy (CBT), sertraline (SRT), their combination (COMB), or medication management with pill placebo (PBO) in the Child/Adolescent Anxiety Multimodal Study (CAMS). Method Six classes of predictor and moderator variables (22 variables) were identified from the literature and examined using continuous (Pediatric Anxiety Ratings Scale; PARS) and categorical (Clinical Global Impression Scale-Improvement; CGI-I) outcome measures. Results Three baseline variables predicted better outcomes (independent of treatment condition) on the PARS, including low anxiety severity (as measured by parents and independent evaluators) and caregiver strain. No baseline variables were found to predict week 12 responder status (CGI-I). Participant's principal diagnosis moderated treatment outcomes, but only on the PARS. No baseline variables were found to moderate treatment outcomes on week 12 responder status (CGI-I). Discussion Overall, anxious children responded favorably to CAMS treatments. However, having more severe and impairing anxiety, greater caregiver strain, and a principal diagnosis of social phobia were associated with less favorable outcomes. Clinical implications of these findings are discussed. PMID:24417601

The impact of targeting repetitive BamHI-W sequences on the sensitivity and precision of EBV DNA quantification

PubMed Central

Fayd’herbe de Maudave, Alexis; Bollore, Karine; Zimmermann, Valérie; Foulongne, Vincent; Van de Perre, Philippe; Tuaillon, Edouard

2017-01-01

Background Viral load monitoring and early Epstein-Barr virus (EBV) DNA detection are essential in routine laboratory testing, especially in preemptive management of Post-transplant Lymphoproliferative Disorder. Targeting the repetitive BamHI-W sequence was shown to increase the sensitivity of EBV DNA quantification, but the variability of BamHI-W reiterations was suggested to be a source of quantification bias. We aimed to assess the extent of variability associated with BamHI-W PCR and its impact on the sensitivity of EBV DNA quantification using the 1st WHO international standard, EBV strains and clinical samples. Methods Repetitive BamHI-W- and LMP2 single- sequences were amplified by in-house qPCRs and BXLF-1 sequence by a commercial assay (EBV R-gene™, BioMerieux). Linearity and limits of detection of in-house methods were assessed. The impact of repeated versus single target sequences on EBV DNA quantification precision was tested on B95.8 and Raji cell lines, possessing 11 and 7 copies of the BamHI-W sequence, respectively, and on clinical samples. Results BamHI-W qPCR demonstrated a lower limit of detection compared to LMP2 qPCR (2.33 log10 versus 3.08 log10 IU/mL; P = 0.0002). BamHI-W qPCR underestimated the EBV DNA load on Raji strain which contained fewer BamHI-W copies than the WHO standard derived from the B95.8 EBV strain (mean bias: - 0.21 log10; 95% CI, -0.54 to 0.12). Comparison of BamHI-W qPCR versus LMP2 and BXLF-1 qPCR showed an acceptable variability between EBV DNA levels in clinical samples with the mean bias being within 0.5 log10 IU/mL EBV DNA, whereas a better quantitative concordance was observed between LMP2 and BXLF-1 assays. Conclusions Targeting BamHI-W resulted to a higher sensitivity compared to LMP2 but the variable reiterations of BamHI-W segment are associated with higher quantification variability. BamHI-W can be considered for clinical and therapeutic monitoring to detect an early EBV DNA and a dynamic change in viral load. PMID:28850597

Meningitis With a Negative Cerebrospinal Fluid Gram Stain in Adults: Risk Classification for an Adverse Clinical Outcome

PubMed Central

Khoury, Nabil T.; Hossain, Md Monir; Wootton, Susan H.; Salazar, Lucrecia; Hasbun, Rodrigo

2012-01-01

Objective To derive and validate a risk score for an adverse clinical outcome in adults with meningitis and a negative cerebrospinal fluid (CSF) Gram stain. Patients and Methods We conducted a retrospective study of 567 adults from Houston, Texas, with meningitis evaluated between January 1, 2005, and January 1, 2010. The patients were divided into derivation (N=292) and validation (N=275) cohorts. An adverse clinical outcome was defined as a Glasgow Outcome Scale score of 4 or less. Results Of the 567 patients, 62 (11%) had an adverse clinical outcome. A predictive model was created using 3 baseline variables that were independently associated with an adverse clinical outcome (P<.05): age greater than 60 years, abnormal findings on neurologic examination (altered mental status, focal neurologic deficits, or seizures), and CSF glucose level of less than 2.4975 mmol/L (to convert CSF glucose to mmol/L, multiply by 0.05551). The model classified patients into 2 categories of risk for an adverse clinical outcome—derivation sample: low risk, 0.6% and high risk, 32.8%; P<.001; and validation sample: low risk, 0.5% and high risk, 21.1%; P<.001. Conclusion Adults with meningitis and a negative CSF Gram stain can be accurately stratified for the risk of an adverse clinical outcome using clinical variables available at presentation. PMID:23218086

Valx: A System for Extracting and Structuring Numeric Lab Test Comparison Statements from Text.

PubMed

Hao, Tianyong; Liu, Hongfang; Weng, Chunhua

2016-05-17

To develop an automated method for extracting and structuring numeric lab test comparison statements from text and evaluate the method using clinical trial eligibility criteria text. Leveraging semantic knowledge from the Unified Medical Language System (UMLS) and domain knowledge acquired from the Internet, Valx takes seven steps to extract and normalize numeric lab test expressions: 1) text preprocessing, 2) numeric, unit, and comparison operator extraction, 3) variable identification using hybrid knowledge, 4) variable - numeric association, 5) context-based association filtering, 6) measurement unit normalization, and 7) heuristic rule-based comparison statements verification. Our reference standard was the consensus-based annotation among three raters for all comparison statements for two variables, i.e., HbA1c and glucose, identified from all of Type 1 and Type 2 diabetes trials in ClinicalTrials.gov. The precision, recall, and F-measure for structuring HbA1c comparison statements were 99.6%, 98.1%, 98.8% for Type 1 diabetes trials, and 98.8%, 96.9%, 97.8% for Type 2 diabetes trials, respectively. The precision, recall, and F-measure for structuring glucose comparison statements were 97.3%, 94.8%, 96.1% for Type 1 diabetes trials, and 92.3%, 92.3%, 92.3% for Type 2 diabetes trials, respectively. Valx is effective at extracting and structuring free-text lab test comparison statements in clinical trial summaries. Future studies are warranted to test its generalizability beyond eligibility criteria text. The open-source Valx enables its further evaluation and continued improvement among the collaborative scientific community.

Analysis of intraosseous samples using point of care technology--an experimental study in the anaesthetised pig.

PubMed

Strandberg, Gunnar; Eriksson, Mats; Gustafsson, Mats G; Lipcsey, Miklós; Larsson, Anders

2012-11-01

Intraosseous access is an essential method in emergency medicine when other forms of vascular access are unavailable and there is an urgent need for fluid or drug therapy. A number of publications have discussed the suitability of using intraosseous access for laboratory testing. We aimed to further evaluate this issue and to study the accuracy and precision of intraosseous measurements. Five healthy, anaesthetised pigs were instrumented with bilateral tibial intraosseous cannulae and an arterial catheter. Samples were collected hourly for 6h and analysed for blood gases, acid base status, haemoglobin and electrolytes using an I-Stat point of care analyser. There was no clinically relevant difference between results from left and right intraosseous sites. The variability of the intraosseous sample values, measured as the coefficient of variance (CV), was maximally 11%, and smaller than for the arterial sample values for all variables except SO2. For most variables, there seems to be some degree of systematic difference between intraosseous and arterial results. However, the direction of this difference seems to be predictable. Based on our findings in this animal model, cartridge based point of care instruments appear suitable for the analysis of intraosseous samples. The agreement between intraosseous and arterial analysis seems to be good enough for the method to be clinically useful. The precision, quantified in terms of CV, is at least as good for intraosseous as for arterial analysis. There is no clinically important difference between samples from left and right tibia, indicating a good reproducibility. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

99mTc-sestamibi scintigraphy used to evaluate tumor response to neoadjuvant chemotherapy in locally advanced breast cancer: A quantitative analysis

PubMed Central

KOGA, KATIA HIROMOTO; MORIGUCHI, SONIA MARTA; NETO, JORGE NAHÁS; PERES, STELA VERZINHASSE; SILVA, EDUARDO TINÓIS DA; SARRI, ALMIR JOSÉ; MICHELIN, ODAIR CARLITO; MARQUES, MARIANGELA ESTHER ALENCAR; GRIVA, BEATRIZ LOTUFO

2010-01-01

To evaluate the tumor response to neoadjuvant chemotherapy, 99mTc-sestamibi breast scintigraphy was proposed as a quantitative method. Fifty-five patients with ductal carcinoma were studied. They underwent breast scintigraphy before and after neoadjuvant chemotherapy, along with clinical assessment and surgical specimen analysis. The regions of interest on the lesion and contralateral breast were identified, and the pixel counts were used to evaluate lesion uptake in relation to background radiation. The ratio of these counts before to after neoadjuvant chemotherapy was assessed. The decrease in uptake rate due to chemotherapy characterized the scintigraphy tumor response. The Kruskal-Wallis test was used to compare the mean scintigraphic tumor response and histological type. Dunn’s multiple comparison test was used to detect differences between histological types. The Mann-Whitney test was used to compare means between quantitative and qualitative variables: scintigraphic tumor response vs. clinical response and uptake before chemotherapy vs. scintigraphic tumor response. The Spearman’s test was used to correlate the quantitative variables of clinical reduction in tumor size and scintigraphic tumor response. All of the variables compared presented significant differences. The change in 99mTc-sestamibi uptake noted on breast scintigraphy, before to after neoadjuvant chemotherapy, may be used as an effective method for evaluating the response to neoadjuvant chemotherapy, since this quantification reflects the biological behavior of the tumor towards the chemotherapy regimen. Furthermore, additional analysis on the uptake rate before chemotherapy may accurately predict treatment response. PMID:22966312

Predictors of Very Low Adherence with Medications for Osteoporosis: Towards Development of a Clinical Prediction Rule

PubMed Central

Solomon, Daniel H.; Brookhart, M. Alan; Tsao, Peter; Sundaresan, Devi; Andrade, Susan E.; Mazor, Kathleen; Yood, Robert

2016-01-01

Background Medication non-adherence is extremely common for osteoporosis, however no clear methods exist for identifying patients at-risk of this behavior. We developed a clinical prediction rule to predict medication non-adherence for women prescribed osteoporosis treatment. Methods Women undergoing bone mineral density testing and fulfilling WHO criteria for osteoporosis were invited to complete a questionnaire and then followed for one year. Adjusted logistic regression models were examined to identify variables associated with very low adherence (medication possession ratio < 20%). The weighted variables, based on the logistic regression, were summed and the score compared with the proportion of subjects with very low adherence. Results 142 women participated in the questionnaire and were prescribed an osteoporosis medication. After one year, 36% (n = 50) had very low adherence. Variables associated with very low adherence included: prior non-adherence with chronic medications, agreement that side effects are concerning, agreement that she is taking too many medications, lack of agreement that osteoporosis is a worry, lack of agreement that a fracture will cause disability, lack of agreement that medications help her stay active, and frequent use of alcohol. When combined into a summative score, 36 of the 58 subjects (62%) with 7 or more points on the score demonstrated very low adherence. This compares with 14 of the 84 (17%) subjects with fewer than 7 points (c-statistic = 0.74). Conclusions We developed a brief clinical prediction rule that was able to discriminate between women likely (and unlikely) to experience very low adherence with osteoporosis medications. PMID:20878392

Big data and computational biology strategy for personalized prognosis.

PubMed

Ow, Ghim Siong; Tang, Zhiqun; Kuznetsov, Vladimir A

2016-06-28

The era of big data and precision medicine has led to accumulation of massive datasets of gene expression data and clinical information of patients. For a new patient, we propose that identification of a highly similar reference patient from an existing patient database via similarity matching of both clinical and expression data could be useful for predicting the prognostic risk or therapeutic efficacy.Here, we propose a novel methodology to predict disease/treatment outcome via analysis of the similarity between any pair of patients who are each characterized by a certain set of pre-defined biological variables (biomarkers or clinical features) represented initially as a prognostic binary variable vector (PBVV) and subsequently transformed to a prognostic signature vector (PSV). Our analyses revealed that Euclidean distance rather correlation distance measure was effective in defining an unbiased similarity measure calculated between two PSVs.We implemented our methods to high-grade serous ovarian cancer (HGSC) based on a 36-mRNA predictor that was previously shown to stratify patients into 3 distinct prognostic subgroups. We studied and revealed that patient's age, when converted into binary variable, was positively correlated with the overall risk of succumbing to the disease. When applied to an independent testing dataset, the inclusion of age into the molecular predictor provided more robust personalized prognosis of overall survival correlated with the therapeutic response of HGSC and provided benefit for treatment targeting of the tumors in HGSC patients.Finally, our method can be generalized and implemented in many other diseases to accurately predict personalized patients' outcomes.

Influence of ROI definition on the heart-to-mediastinum ratio in planar 123I-MIBG imaging.

PubMed

Klene, Christiane; Jungen, Christiane; Okuda, Koichi; Kobayashi, Yuske; Helberg, Annabelle; Mester, Janos; Meyer, Christian; Nakajima, Kenichi

2018-02-01

Iodine-123-metaiodobenzylguanidine ( 123 I-MIBG) imaging with estimation of the heart-to-mediastinum ratio (HMR) has been established for risk assessment in patients with chronic heart failure. Our aim was to evaluate the effect of different methods of ROI definition on the renderability of HMR to normal or decreased sympathetic innervation. The results of three different methods of ROI definition (clinical routine (CLI), simple standardization (STA), and semi-automated (AUT) were compared. Ranges of 95% limits of agreement (LoA) of inter-observer variabilities were 0.28 and 0.13 for STA and AUT, respectively. Considering a HMR of 1.60 as the lower limit of normal, 13 of 32 (41%) for method STA and 5 of 32 (16%) for method AUT of all HMR measurements could not be classified to normal or pathologic. Ranges of 95% LoA of inter-method variabilities were 0.72 for CLI vs AUT, 0.65 for CLI vs STA, and 0.31 for STA vs AUT. Different methods of ROI definition result in different ranges of the LoA of the measured HMR with relevance for rendering the results to normal or pathological innervation. We could demonstrate that standardized protocols can help keep methodological variabilities limited, narrowing the gray zone of renderability.

Automation of Classical QEEG Trending Methods for Early Detection of Delayed Cerebral Ischemia: More Work to Do.

PubMed

Wickering, Ellis; Gaspard, Nicolas; Zafar, Sahar; Moura, Valdery J; Biswal, Siddharth; Bechek, Sophia; OʼConnor, Kathryn; Rosenthal, Eric S; Westover, M Brandon

2016-06-01

The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and underwent continuous EEG monitoring. We implemented several variations of two classical algorithms for automated detection of delayed cerebral ischemia based on decreases in alpha-delta ratio and relative alpha variability. Of 95 patients, 43 (45%) developed delayed cerebral ischemia. Our automated implementation of the classical alpha-delta ratio-based trending method resulted in a sensitivity and specificity (Se,Sp) of (80,27)%, compared with the values of (100,76)% reported in the classic study using similar methods in a nonautomated fashion. Our automated implementation of the classical relative alpha variability-based trending method yielded (Se,Sp) values of (65,43)%, compared with (100,46)% reported in the classic study using nonautomated analysis. Our findings suggest that improved methods to detect decreases in alpha-delta ratio and relative alpha variability are needed before an automated EEG-based early delayed cerebral ischemia detection system is ready for clinical use.

Endodontic and Clinical Considerations in the Management of Variable Anatomy in Mandibular Premolars: A Literature Review

PubMed Central

Hammo, Mohammad

2014-01-01

Mandibular premolars are known to have numerous anatomic variations of their roots and root canals, which are a challenge to treat endodontically. The paper reviews literature to detail the various clinically relevant anatomic considerations with detailed techniques and methods to successfully manage these anomalies. An emphasis and detailed description of every step of treatment including preoperative diagnosis, intraoperative identification and management, and surgical endodontic considerations for the successful management of these complex cases have been included. PMID:24895584

Electromagnetic fields in medicine - The state of art.

PubMed

Pasek, Jarosław; Pasek, Tomasz; Sieroń-Stołtny, Karolina; Cieślar, Grzegorz; Sieroń, Aleksander

2016-01-01

Intense development of methods belonging to physical medicine has been noted recently. There are treatment methods, which in many cases lead to reduction treatment time and positively influence on quality of life treatment patients. The present physical medicine systematically extends their therapeutic possibilities. This above applies to illnesses and injuries of locomotor system, diseases affecting of soft tissues, as well as chronic wounds. The evidence on this are the results of basic and clinical examinations relating the practical use of electromagnetic fields in medicine. In this work the authors introduced the procedure using the current knowledge relating to physical characteristic and biological effects of the magnetic fields. In the work the following methods were used: static magnetic fields, spatial magnetic fields, the variable magnetic fields both with laser therapy (magnetolaserotherapy) and variable magnetic fields both with light optical non-laser (magnetoledtherapy) talked.

Salivary Parameters (Salivary Flow, pH and Buffering Capacity) in Stimulated Saliva of Mexican Elders 60 Years Old and Older

PubMed Central

Islas-Granillo, H; Borges-Yañez, SA; Medina-Solís, CE; Galan-Vidal, CA; Navarrete-Hernández, JJ; Escoffié-Ramirez, M; Maupomé, G

2014-01-01

ABSTRACT Objective: To compare a limited array of chewing-stimulated saliva features (salivary flow, pH and buffer capacity) in a sample of elderly Mexicans with clinical, sociodemographic and socio-economic variables. Subjects and Methods: A cross-sectional study was carried out in 139 adults, 60 years old and older, from two retirement homes and a senior day care centre in the city of Pachuca, Mexico. Socio-demographic, socio-economic and behavioural variables were collected through a questionnaire. A trained and standardized examiner obtained the oral clinical variables. Chewing-stimulated saliva (paraffin method) was collected and the salivary flow rate, pH and buffer capacity were measured. The analysis was performed using non-parametric tests in Stata 9.0. Results: Mean age was 79.1 ± 9.8 years. Most of the subjects included were women (69.1%). Mean chewing-stimulated salivary flow was 0.75 ± 0.80 mL/minute, and the pH and buffer capacity were 7.88 ± 0.83 and 4.20 ± 1.24, respectively. Mean chewing-stimulated salivary flow varied (p < 0.05) across type of retirement home, tooth brushing frequency, number of missing teeth and use of dental prostheses. pH varied across the type of retirement home (p < 0.05) and marginally by age (p = 0.087); buffer capacity (p < 0.05) varied across type of retirement home, tobacco consumption and the number of missing teeth. Conclusions: These exploratory data add to the body of knowledge with regard to chewing-stimulated salivary features (salivary flow rate, pH and buffer capacity) and outline the variability of those features across selected sociodemographic, socio-economic and behavioural variables in a group of Mexican elders. PMID:25867562

[Instruments for quantitative methods of nursing research].

PubMed

Vellone, E

2000-01-01

Instruments for quantitative nursing research are a mean to objectify and measure a variable or a phenomenon in the scientific research. There are direct instruments to measure concrete variables and indirect instruments to measure abstract concepts (Burns, Grove, 1997). Indirect instruments measure the attributes by which a concept is made of. Furthermore, there are instruments for physiologic variables (e.g. for the weight), observational instruments (Check-lists e Rating Scales), interviews, questionnaires, diaries and the scales (Check-lists, Rating Scales, Likert Scales, Semantic Differential Scales e Visual Anologue Scales). The choice to select an instrument or another one depends on the research question and design. Instruments research are very useful in research both to describe the variables and to see statistical significant relationships. Very carefully should be their use in the clinical practice for diagnostic assessment.

Methodological aspects of multicenter studies with quantitative PET.

PubMed

Boellaard, Ronald

2011-01-01

Quantification of whole-body FDG PET studies is affected by many physiological and physical factors. Much of the variability in reported standardized uptake value (SUV) data seen in the literature results from the variability in methodology applied among these studies, i.e., due to the use of different scanners, acquisition and reconstruction settings, region of interest strategies, SUV normalization, and/or corrections methods. To date, the variability in applied methodology prohibits a proper comparison and exchange of quantitative FDG PET data. Consequently, the promising role of quantitative PET has been demonstrated in several monocentric studies, but these published results cannot be used directly as a guideline for clinical (multicenter) trials performed elsewhere. In this chapter, the main causes affecting whole-body FDG PET quantification and strategies to minimize its inter-institute variability are addressed.

Surrogacy Assessment Using Principal Stratification and a Gaussian Copula Model

PubMed Central

Taylor, J.M.G.; Elliott, M.R.

2014-01-01

In clinical trials, a surrogate outcome (S) can be measured before the outcome of interest (T) and may provide early information regarding the treatment (Z) effect on T. Many methods of surrogacy validation rely on models for the conditional distribution of T given Z and S. However, S is a post-randomization variable, and unobserved, simultaneous predictors of S and T may exist, resulting in a non-causal interpretation. Frangakis and Rubin1 developed the concept of principal surrogacy, stratifying on the joint distribution of the surrogate marker under treatment and control to assess the association between the causal effects of treatment on the marker and the causal effects of treatment on the clinical outcome. Working within the principal surrogacy framework, we address the scenario of an ordinal categorical variable as a surrogate for a censored failure time true endpoint. A Gaussian copula model is used to model the joint distribution of the potential outcomes of T, given the potential outcomes of S. Because the proposed model cannot be fully identified from the data, we use a Bayesian estimation approach with prior distributions consistent with reasonable assumptions in the surrogacy assessment setting. The method is applied to data from a colorectal cancer clinical trial, previously analyzed by Burzykowski et al..2 PMID:24947559

Patellar denervation with electrocautery in total knee arthroplasty without patellar resurfacing: a meta-analysis.

PubMed

Cheng, Tao; Zhu, Chen; Guo, Yongyuan; Shi, Sifeng; Chen, Desheng; Zhang, Xianlong

2014-11-01

The impact of patellar denervation with electrocautery in total knee arthroplasty (TKA) on post-operative outcomes has been under debate. This study aims to conduct a meta-analysis and systematic review to compare the benefits and risks of circumpatellar electrocautery with those of non-electrocautery in primary TKAs. Comparative and randomized clinical studies were identified by conducting an electronic search of articles dated up to September 2012 in PubMed, EMBASE, Scopus, and the Cochrane databases. Six studies that focus on a total of 849 knees were analysed. A random-effects model was conducted using the inverse-variance method for continuous variables and the Mantel-Haenszel method for dichotomous variables. There was no significant difference in the incidence of anterior knee pain between the electrocautery and non-electrocautery groups. In term of patellar score and Knee Society Score, circumpatellar electrocautery improved clinical outcomes compared with non-electrocautery in TKAs. The statistical differences were in favour of the electrocautery group but have minimal clinical significance. In addition, the overall complications indicate no statistical significance between the two groups. This study shows no strong evidence either for or against electrocautery compared with non-electrocautery in TKAs. Therapeutic study (systematic review and meta-analysis), Level III.

Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

PubMed

Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

2012-01-01

The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

Surrogacy assessment using principal stratification and a Gaussian copula model.

PubMed

Conlon, Asc; Taylor, Jmg; Elliott, M R

2017-02-01

In clinical trials, a surrogate outcome ( S) can be measured before the outcome of interest ( T) and may provide early information regarding the treatment ( Z) effect on T. Many methods of surrogacy validation rely on models for the conditional distribution of T given Z and S. However, S is a post-randomization variable, and unobserved, simultaneous predictors of S and T may exist, resulting in a non-causal interpretation. Frangakis and Rubin developed the concept of principal surrogacy, stratifying on the joint distribution of the surrogate marker under treatment and control to assess the association between the causal effects of treatment on the marker and the causal effects of treatment on the clinical outcome. Working within the principal surrogacy framework, we address the scenario of an ordinal categorical variable as a surrogate for a censored failure time true endpoint. A Gaussian copula model is used to model the joint distribution of the potential outcomes of T, given the potential outcomes of S. Because the proposed model cannot be fully identified from the data, we use a Bayesian estimation approach with prior distributions consistent with reasonable assumptions in the surrogacy assessment setting. The method is applied to data from a colorectal cancer clinical trial, previously analyzed by Burzykowski et al.

Clinical factors predicting risk for aspiration and respiratory aspiration among patients with Stroke1

PubMed Central

Oliveira, Ana Railka de Souza; Costa, Alice Gabrielle de Sousa; Morais, Huana Carolina Cândido; Cavalcante, Tahissa Frota; Lopes, Marcos Venícios de Oliveira; de Araujo, Thelma Leite

2015-01-01

Objective: to investigate the association of risk factors with the Risk for aspiration nursing diagnosis and respiratory aspiration. Method: cross-sectional study assessing 105 patients with stroke. The instrument used to collect data addressing sociodemographic information, clinical variables and risk factors for Risk for aspiration. The clinical judgments of three expert RNs were used to establish the diagnosis. The relationship between variables and strength of association using Odds Ratio (OR) was verified both in regard to Risk for aspiration and respiratory aspiration. Results: risk for aspiration was present in 34.3% of the patients and aspiration in 30.5%. The following stood out among the risk factors: Dysphagia, Impaired or absent gag reflex, Neurological disorders, and Impaired physical mobility, all of which were statistically associated with Risk for aspiration. Note that patients who develop such a diagnosis were seven times more likely to develop respiratory aspiration. Conclusion: dysphagia, Impaired or absent gag reflex were the best predictors both for Risk for aspiration and respiratory aspiration. PMID:26039291

Plasma chemistry references values in psittaciformes.

PubMed

Lumeij, J T; Overduin, L M

1990-04-01

Reference values for 17 plasma chemical variables in African greys. Amazons, cockatoos and macaws were established for use in avian clinical practice. The inner limits are given for the percentiles P(2.5) and P(97.5) with a probability of 90%. The following variables were studied: urea, creatinine, uric acid, urea/uric acid ratio, osmolality, sodium, potassium, calcium, glucose, aspartate aminotransferase, alanine aminotransferase, gamma glutamyltransferase, lactate dehydrogenase, creatine kinase, bile acids, total protein, albumin/globulin ratio. Differences between methods used and values found in this study and those reported previously are discussed.

Effect of mixed mutans streptococci colonization on caries development.

PubMed

Seki, M; Yamashita, Y; Shibata, Y; Torigoe, H; Tsuda, H; Maeno, M

2006-02-01

To evaluate the clinical importance of mixed mutans streptococci colonization in predicting caries in preschool children. Caries prevalence was examined twice, with a 6-month interval, in 410 preschool children aged 3-4 years at baseline. A commercial strip method was used to evaluate the mutans streptococci score in plaque collected from eight selected interdental spaces and in saliva. Mutans streptococci typing polymerase chain reaction (PCR) assays (Streptococcus sobrinus and Streptococcus mutans, including serotypes c, e, and f) were performed using colonies on the strips as template. Twenty variables were examined in a univariate analysis to predict caries development: questionnaire variables, results of clinical examination, mutans streptococci scores, and PCR detection of S. sobrinus and S. mutans (including serotypes c, e, and f). Sixteen variables showed statistically significant associations (P < 0.04) in the univariate analysis. However, when entered into a logistic regression, only five variables remained significant (P < 0.05): caries experience at baseline; mixed colonization of S. sobrinus and S. mutans including S. mutans serotypes; high plaque mutans streptococci score; habitual use of sweet drinks; and nonuse of fluoride toothpaste. 'Mixed mutans streptococci colonization' is a novel measure correlated with caries development in their primary dentition.

Inference of median difference based on the Box-Cox model in randomized clinical trials.

PubMed

Maruo, K; Isogawa, N; Gosho, M

2015-05-10

In randomized clinical trials, many medical and biological measurements are not normally distributed and are often skewed. The Box-Cox transformation is a powerful procedure for comparing two treatment groups for skewed continuous variables in terms of a statistical test. However, it is difficult to directly estimate and interpret the location difference between the two groups on the original scale of the measurement. We propose a helpful method that infers the difference of the treatment effect on the original scale in a more easily interpretable form. We also provide statistical analysis packages that consistently include an estimate of the treatment effect, covariance adjustments, standard errors, and statistical hypothesis tests. The simulation study that focuses on randomized parallel group clinical trials with two treatment groups indicates that the performance of the proposed method is equivalent to or better than that of the existing non-parametric approaches in terms of the type-I error rate and power. We illustrate our method with cluster of differentiation 4 data in an acquired immune deficiency syndrome clinical trial. Copyright © 2015 John Wiley & Sons, Ltd.

The influence of RBE variations in a clinical proton treatment plan for a hypopharynx cancer

NASA Astrophysics Data System (ADS)

Tilly, N.; Johansson, J.; Isacsson, U.; Medin, J.; Blomquist, E.; Grusell, E.; Glimelius, B.

2005-06-01

Currently, most clinical range-modulated proton beams are assumed to have a fixed overall relative biological effectiveness (RBE) of 1.1. However, it is well known that the RBE increases with depth in the spread-out Bragg peak (SOBP) and becomes about 10% higher than mid-SOBP RBE at 2 mm from the distal edge (Paganetti 2003 Technol. Cancer Res. Treat. 2 413-26) and can reach values of 1.3-1.4 in vitro at the distal edge (Robertson et al 1975 Cancer 35 1664-77, Courdi et al 1994 Br. J. Radiol. 67 800-4). We present a fast method for applying a variable RBE correction with linear energy transfer (LET) dependent tissue-specific parameters based on the αref/βref ratios suitable for implementation in a treatment planning system. The influence of applying this variable RBE correction on a clinical multiple beam proton dose plan is presented here. The treatment plan is evaluated by RBE weighted dose volume histograms (DVHs) and the calculation of tumour control probability (TCP) and normal tissue complication probability (NTCP) values. The variable RBE correction yields DVHs for the clinical target volumes (CTVs), a primary advanced hypopharynx cancer and subclinical disease in the lymph nodes, that are slightly higher than those achieved by multiplying the absorbed dose with RBE = 1.1. Although, more importantly, the RBE weighted DVH for an organ at risk, the spinal cord is considerably increased for the variable RBE. As the spinal cord in this particular case is located 8 mm behind the planning target volume (PTV) and hence receives only low total doses, the NTCP values are zero in spite of the significant increase in the RBE weighted DVHs for the variable RBE. However, high NTCP values for the non-target normal tissue were obtained when applying the variable RBE correction. As RBE variations tend to be smaller for in vivo systems, this study—based on in vitro data since human tissue RBE values are scarce and have large uncertainties—can be interpreted as showing the upper limits of the possible effects of utilizing a variable RBE correction. In conclusion, the results obtained here still indicate a significant difference in introducing a variable RBE compared to applying a generic RBE of 1.1, suggesting it is worth considering such a correction in clinical proton therapy planning, especially when risk organs are located immediately behind the target volume.

Dendritic cell and histiocytic neoplasms: biology, diagnosis, and treatment.

PubMed

Dalia, Samir; Shao, Haipeng; Sagatys, Elizabeth; Cualing, Hernani; Sokol, Lubomir

2014-10-01

Dendritic and histiocytic cell neoplasms are rare malignancies that make up less than 1% of all neoplasms arising in lymph nodes or soft tissues. These disorders have distinctive disease biology, clinical presentations, pathology, and unique treatment options. Morphology and immunohistochemistry evaluation by a hematopathologist remains key for differentiating between these neoplasms. In this review, we describe tumor biology, clinical features, pathology, and treatment of follicular dendritic cell sarcoma, interdigitating dendritic cell sarcoma, indeterminate dendritic cell sarcoma, histiocytic sarcoma, fibroblastic reticular cell tumors, and disseminated juvenile xanthogranuloma. A literature search for articles published between 1990 and 2013 was undertaken. Articles are reviewed and salient findings are systematically described. Patients with dendritic cell and histiocytic neoplasms have distinct but variable clinical presentations; however, because many tumors have recently been recognized, their true incidence is uncertain. Although the clinical features can present in many organs, most occur in the lymph nodes or skin. Most cases are unifocal and solitary presentations have good prognoses with surgical resection. The role of adjuvant therapy in these disorders remains unclear. In cases with disseminated disease, prognosis is poor and data on treatment options are limited, although chemotherapy and referral to a tertiary care center should be considered. Excisional biopsy is the preferred method of specimen collection for tissue diagnosis, and immunohistochemistry is the most important diagnostic method for differentiating these disorders from other entities. Dendritic cell and histiocytic cell neoplasms are rare hematological disorders with variable clinical presentations and prognoses. Immunohistochemistry remains important for diagnosis. Larger pooled analyses or clinical trials are needed to better understand optimal treatment options in these rare disorders. Whenever possible, patients should be referred to a tertiary care center for disease management.

Invited review: study design considerations for clinical research in veterinary radiology and radiation oncology.

PubMed

Scrivani, Peter V; Erb, Hollis N

2013-01-01

High quality clinical research is essential for advancing knowledge in the areas of veterinary radiology and radiation oncology. Types of clinical research studies may include experimental studies, method-comparison studies, and patient-based studies. Experimental studies explore issues relative to pathophysiology, patient safety, and treatment efficacy. Method-comparison studies evaluate agreement between techniques or between observers. Patient-based studies investigate naturally acquired disease and focus on questions asked in clinical practice that relate to individuals or populations (e.g., risk, accuracy, or prognosis). Careful preplanning and study design are essential in order to achieve valid results. A key point to planning studies is ensuring that the design is tailored to the study objectives. Good design includes a comprehensive literature review, asking suitable questions, selecting the proper sample population, collecting the appropriate data, performing the correct statistical analyses, and drawing conclusions supported by the available evidence. Most study designs are classified by whether they are experimental or observational, longitudinal or cross-sectional, and prospective or retrospective. Additional features (e.g., controlled, randomized, or blinded) may be described that address bias. Two related challenging aspects of study design are defining an important research question and selecting an appropriate sample population. The sample population should represent the target population as much as possible. Furthermore, when comparing groups, it is important that the groups are as alike to each other as possible except for the variables of interest. Medical images are well suited for clinical research because imaging signs are categorical or numerical variables that might be predictors or outcomes of diseases or treatments. © 2013 Veterinary Radiology & Ultrasound.

A descriptive study of culture media in Brazilian assisted reproduction clinics

PubMed Central

Bartmann, Ana; do Amaral, Amanda Turato Barbosa; Gonçalves, Letícia

2016-01-01

Objective The present study aimed to draw a profile of the most commonly used media and protocol characteristics from assisted reproduction technology (ART) facilities in Brazil. Methods To obtain an overview of ART methods and culture media, a questionnaire was given to embryologists from ART clinics in Brazil. Further research in scientific papers and journals was carried out for describing the processes around Brazil, USA and Europe. Results From the questionnaire, we found that the embryo medium mostly used is CSCMTM from Irvine Scientific, represented 37.04% in Brazilian ART clinics; interestingly, 70.37% of clinics exchange the embryo media bath; however, 70.37% do not change the media type. Transfers in Brazilian clinics were variable, but day 3 transfer was a procedure seen in 37.04%. The remaining embryos are habitually maintained in prolonged cultivation in 51.85% of the clinics interviewed. Conclusion Although there are numerous studies trying to better understand embryo culture media influences, there is a lack of evidence for choosing one as the most appropriate. In short, it is a random decision for such an essential stage of In Vitro Fertilization. PMID:27584601

Cocaine and metabolite concentrations in DBS and venous blood after controlled intravenous cocaine administration

PubMed Central

Ellefsen, Kayla N; da Costa, Jose Luiz; Concheiro, Marta; Anizan, Sebastien; Barnes, Allan J; Pirard, Sandrine; Gorelick, David A; Huestis, Marilyn A

2015-01-01

Background: DBS are an increasingly common clinical matrix. Methods & results: Sensitive and specific methods for DBS and venous blood cocaine and metabolite detection by LC–HRMS and 2D GC–MS, respectively, were validated to examine correlation between concentrations following controlled intravenous cocaine administration. Linear ranges from 1 to 200 µg/l were achieved, with acceptable bias and imprecision. Authentic matched specimens’ (392 DBS, 97 venous blood) cocaine and benzoylecgonine concentrations were qualitatively similar, but DBS had much greater variability (21.4–105.9 %CV) and were lower than in blood. Conclusion: DBS offer advantages for monitoring cocaine intake; however, differences between capillary and venous blood and DBS concentration variability must be addressed. PMID:26327184

[Visit-to-visit blood pressure variability: clinical and prognostic significance].

PubMed

Kotovskaia, Iu V; Troitskaia, E A; Kobalava, Zh D

2014-01-01

The phenomenon of variability of blood pressure (BP) was studied for a long time, but recently it has received increased attention, with the focus shifted from short-term BP variability, estimated at daily monitoring for clinical blood pressure variability from visit to visit, which can be regarded as one of the indicators quality control of blood pressure with prolonged treatment. In light of the recent years of clinical data from visit to visit BP variability seems a promising new target for antihypertensive therapy.

Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.

PubMed

Jordan, Pascal; Shedden-Mora, Meike C; Löwe, Bernd

To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classifier for SI based on variables of the Patient Health Questionnaire (PHQ) and sociodemographic variables, and to obtain an upper bound on the best possible performance of a predictor based on those variables. From a consecutive sample of 9025 primary care patients, 6805 eligible patients (60% female; mean age = 51.5 years) participated. Advanced methods of machine learning were used to derive the prediction equation. Various classifiers were applied and the area under the curve (AUC) was computed as a performance measure. Classifiers based on methods of machine learning outperformed ordinary regression methods and achieved AUCs around 0.87. The key variables in the prediction equation comprised four items - namely feelings of depression/hopelessness, low self-esteem, worrying, and severe sleep disturbances. The generalized anxiety disorder scale (GAD-7) and the somatic symptom subscale (PHQ-15) did not enhance prediction substantially. In predicting suicidal ideation researchers should refrain from using ordinary regression tools. The relevant information is primarily captured by the depression subscale and should be incorporated in a nonlinear model. For clinical practice, a classification tree using only four items of the whole PHQ may be advocated. Copyright © 2018 Elsevier Inc. All rights reserved.

Automated Detection of Actinic Keratoses in Clinical Photographs

PubMed Central

Hames, Samuel C.; Sinnya, Sudipta; Tan, Jean-Marie; Morze, Conrad; Sahebian, Azadeh; Soyer, H. Peter; Prow, Tarl W.

2015-01-01

Background Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. Objective The aim of this pilot study was to determine if automatically detecting and circumscribing actinic keratoses in clinical photographs is feasible. Methods Photographs of the face and dorsal forearms were acquired in 20 volunteers from two groups: the first with at least on actinic keratosis present on the face and each arm, the second with no actinic keratoses. The photographs were automatically analysed using colour space transforms and morphological features to detect erythema. The automated output was compared with a senior consultant dermatologist’s assessment of the photographs, including the intra-observer variability. Performance was assessed by the correlation between total lesions detected by automated method and dermatologist, and whether the individual lesions detected were in the same location as the dermatologist identified lesions. Additionally, the ability to limit false positives was assessed by automatic assessment of the photographs from the no actinic keratosis group in comparison to the high actinic keratosis group. Results The correlation between the automatic and dermatologist counts was 0.62 on the face and 0.51 on the arms, compared to the dermatologist’s intra-observer variation of 0.83 and 0.93 for the same. Sensitivity of automatic detection was 39.5% on the face, 53.1% on the arms. Positive predictive values were 13.9% on the face and 39.8% on the arms. Significantly more lesions (p<0.0001) were detected in the high actinic keratosis group compared to the no actinic keratosis group. Conclusions The proposed method was inferior to assessment by the dermatologist in terms of sensitivity and positive predictive value. However, this pilot study used only a single simple feature and was still able to achieve sensitivity of detection of 53.1% on the arms.This suggests that image analysis is a feasible avenue of investigation for overcoming variability in clinical assessment. Future studies should focus on more sophisticated features to improve sensitivity for actinic keratoses without erythema and limit false positives associated with the anatomical structures on the face. PMID:25615930

Reporting the accuracy of biochemical measurements for epidemiologic and nutrition studies.

PubMed

McShane, L M; Clark, L C; Combs, G F; Turnbull, B W

1991-06-01

Procedures for reporting and monitoring the accuracy of biochemical measurements are presented. They are proposed as standard reporting procedures for laboratory assays for epidemiologic and clinical-nutrition studies. The recommended procedures require identification and estimation of all major sources of variability and explanations of laboratory quality control procedures employed. Variance-components techniques are used to model the total variability and calculate a maximum percent error that provides an easily understandable measure of laboratory precision accounting for all sources of variability. This avoids ambiguities encountered when reporting an SD that may taken into account only a few of the potential sources of variability. Other proposed uses of the total-variability model include estimating precision of laboratory methods for various replication schemes and developing effective quality control-checking schemes. These procedures are demonstrated with an example of the analysis of alpha-tocopherol in human plasma by using high-performance liquid chromatography.

Medical school clinical placements - the optimal method for assessing the clinical educational environment from a graduate entry perspective.

PubMed

Hyde, Sarah; Hannigan, Ailish; Dornan, Tim; McGrath, Deirdre

2018-01-05

Educational environment is a strong determinant of student satisfaction and achievement. The learning environments of medical students on clinical placements are busy workplaces, composed of many variables. There is no universally accepted method of evaluating the clinical learning environment, nor is there consensus on what concepts or aspects should be measured. The aims of this study were to compare the Dundee ready educational environment measure (DREEM - the current de facto standard) and the more recently developed Manchester clinical placement index (MCPI) for the assessment of the clinical learning environment in a graduate entry medical student cohort by correlating the scores of each and analysing free text comments. This study also explored student perceptionof how the clinical educational environment is assessed. An online, anonymous survey comprising of both the DREEM and MCPI instruments was delivered to students on clinical placement in a graduate entry medical school. Additional questions explored students' perceptions of instruments for giving feedback. Numeric variables (DREEM score, MCPI score, ratings) were tested for normality and summarised. Pearson's correlation coefficient was used to measure the strength of the association between total DREEM score and total MCPI scores. Thematic analysis was used to analyse the free text comments. The overall response rate to the questionnaire was 67% (n = 180), with a completed response rate for the MCPI of 60% (n = 161) and for the DREEM of 58% (n = 154). There was a strong, positive correlation between total DREEM and MCPI scores (r = 0.71, p < 0.001). On a scale of 0 to 7, the mean rating for how worthwhile students found completing the DREEM was 3.27 (SD 1.41) and for the MCPI was 3.49 (SD 1.57). 'Finding balance' and 'learning at work' were among the themes to emerge from analysis of free text comments. The present study confirms that DREEM and MCPI total scores are strongly correlated. Graduate entry students tended to favour this method of evaluation over the DREEM with the MCPI prompting rich description of the clinical learning environment. Further study is warranted to determine if this finding is transferable to all clinical medical student cohorts.

Visually estimated ejection fraction by two dimensional and triplane echocardiography is closely correlated with quantitative ejection fraction by real-time three dimensional echocardiography

PubMed Central

Shahgaldi, Kambiz; Gudmundsson, Petri; Manouras, Aristomenis; Brodin, Lars-Åke; Winter, Reidar

2009-01-01

Background Visual assessment of left ventricular ejection fraction (LVEF) is often used in clinical routine despite general recommendations to use quantitative biplane Simpsons (BPS) measurements. Even thou quantitative methods are well validated and from many reasons preferable, the feasibility of visual assessment (eyeballing) is superior. There is to date only sparse data comparing visual EF assessment in comparison to quantitative methods available. The aim of this study was to compare visual EF assessment by two-dimensional echocardiography (2DE) and triplane echocardiography (TPE) using quantitative real-time three-dimensional echocardiography (RT3DE) as the reference method. Methods Thirty patients were enrolled in the study. Eyeballing EF was assessed using apical 4-and 2 chamber views and TP mode by two experienced readers blinded to all clinical data. The measurements were compared to quantitative RT3DE. Results There were an excellent correlation between eyeballing EF by 2D and TP vs 3DE (r = 0.91 and 0.95 respectively) without any significant bias (-0.5 ± 3.7% and -0.2 ± 2.9% respectively). Intraobserver variability was 3.8% for eyeballing 2DE, 3.2% for eyeballing TP and 2.3% for quantitative 3D-EF. Interobserver variability was 7.5% for eyeballing 2D and 8.4% for eyeballing TP. Conclusion Visual estimation of LVEF both using 2D and TP by an experienced reader correlates well with quantitative EF determined by RT3DE. There is an apparent trend towards a smaller variability using TP in comparison to 2D, this was however not statistically significant. PMID:19706183

Multiple-locus variable-number tandem repeat analysis for strain discrimination of non-O157 Shiga toxin-producing Escherichia coli.

PubMed

Timmons, Chris; Trees, Eija; Ribot, Efrain M; Gerner-Smidt, Peter; LaFon, Patti; Im, Sung; Ma, Li Maria

2016-06-01

Non-O157 Shiga toxin-producing Escherichia coli (STEC) are foodborne pathogens of growing concern worldwide that have been associated with several recent multistate and multinational outbreaks of foodborne illness. Rapid and sensitive molecular-based bacterial strain discrimination methods are critical for timely outbreak identification and contaminated food source traceback. One such method, multiple-locus variable-number tandem repeat analysis (MLVA), is being used with increasing frequency in foodborne illness outbreak investigations to augment the current gold standard bacterial subtyping technique, pulsed-field gel electrophoresis (PFGE). The objective of this study was to develop a MLVA assay for intra- and inter-serogroup discrimination of six major non-O157 STEC serogroups-O26, O111, O103, O121, O45, and O145-and perform a preliminary internal validation of the method on a limited number of clinical isolates. The resultant MLVA scheme consists of ten variable number tandem repeat (VNTR) loci amplified in three multiplex PCR reactions. Sixty-five unique MLVA types were obtained among 84 clinical non-O157 STEC strains comprised of geographically diverse sporadic and outbreak related isolates. Compared to PFGE, the developed MLVA scheme allowed similar discrimination among serogroups O26, O111, O103, and O121 but not among O145 and O45. To more fully compare the discriminatory power of this preliminary MLVA method to PFGE and to determine its epidemiological congruence, a thorough internal and external validation needs to be performed on a carefully selected large panel of strains, including multiple isolates from single outbreaks. Copyright © 2016. Published by Elsevier B.V.

Neurological Soft Signs in Indian Children with Specific Developmental Disorders of Scholastic Skills

ERIC Educational Resources Information Center

Sadhu, Raja; Mehta, Manju; Kalra, Veena; Sagar, Rajesh; Mongia, Monica

2008-01-01

Aim: To compare the occurrence of neurological soft signs (NSS) in children with specific developmental disorders of scholastic skills (SDDSS) and normal children. Methods: 36 cases of SDDSS were compared with 30 control children regarding sociodemographic and clinical variables and neurological soft signs. Results: Children with SDDSS had…

Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study.

PubMed

Kellogg, Joshua J; Graf, Tyler N; Paine, Mary F; McCune, Jeannine S; Kvalheim, Olav M; Oberlies, Nicholas H; Cech, Nadja B

2017-05-26

A challenge that must be addressed when conducting studies with complex natural products is how to evaluate their complexity and variability. Traditional methods of quantifying a single or a small range of metabolites may not capture the full chemical complexity of multiple samples. Different metabolomics approaches were evaluated to discern how they facilitated comparison of the chemical composition of commercial green tea [Camellia sinensis (L.) Kuntze] products, with the goal of capturing the variability of commercially used products and selecting representative products for in vitro or clinical evaluation. Three metabolomic-related methods-untargeted ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), targeted UPLC-MS, and untargeted, quantitative 1 HNMR-were employed to characterize 34 commercially available green tea samples. Of these methods, untargeted UPLC-MS was most effective at discriminating between green tea, green tea supplement, and non-green-tea products. A method using reproduced correlation coefficients calculated from principal component analysis models was developed to quantitatively compare differences among samples. The obtained results demonstrated the utility of metabolomics employing UPLC-MS data for evaluating similarities and differences between complex botanical products.

Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization

PubMed Central

Budczies, Jan; Klauschen, Frederick; Sinn, Bruno V.; Győrffy, Balázs; Schmitt, Wolfgang D.; Darb-Esfahani, Silvia; Denkert, Carsten

2012-01-01

Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff. PMID:23251644

Sjögren SER: National registry of the Spanish Society of Rheumatology of patients with primary Sjögren syndrome: Objectives and methodology.

PubMed

Fernández Castro, Mónica; Andreu, Jose Luis; Sánchez-Piedra, Carlos; Martínez Taboada, Víctor; Olivé, Alejandro; Rosas, José; Sánchez-Alonso, Fernando

2016-01-01

To describe the objectives and methods of the Spanish Society of Rheumatology primary Sjögren syndrome (pSS) registry (SJOGREN-SER) METHODS: This is a multicenter descriptive transversal study of a cohort of pSS patients fulfilling European/American consensus criteria collected from Rheumatology clinics all over Spain. Patients were included by randomisation from an anonymised list provided by every department. Data were collected by reviewing clinical records and an interviewing the patients. Two hundred and ninety eight variables were investigated: epidemiological, clinical, serological characteristics, treatments and complications. Informed consent was obtained and local ethics committees approved the study. Variables were analysed by descriptive statistical methods, using means, medians, and rates, with their deviations and interquartile ranges (p25-p75). A total of 3 rheumatology departments participated in the registry. A total of 437 patients were included. And 95% of them were women, with a median age of 58. Median age at pSS 's diagnosis was 50 years. Dryness symptoms (95%) were the most frequent complaint and anti-Ro/SS-A were present in 94% of the cases. Only 27% of the patients fulfilled the new 2012 SICCA-ACR classification criteria. SJOGREN-SER has been designed in order to characterize a representative pSS Spanish cohort, in clinical daily practice, to analyze the magnitude and distribution of its manifestations, activity, accumulated damage and therapeutic management of the disease. This will allow broadening the knowledge of this disease and plan strategies of action in pSS. Copyright © 2015 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Differences in quantitative methods for measuring subjective cognitive decline - results from a prospective memory clinic study.

PubMed

Vogel, Asmus; Salem, Lise Cronberg; Andersen, Birgitte Bo; Waldemar, Gunhild

2016-09-01

Cognitive complaints occur frequently in elderly people and may be a risk factor for dementia and cognitive decline. Results from studies on subjective cognitive decline are difficult to compare due to variability in assessment methods, and little is known about how different methods influence reports of cognitive decline. The Subjective Memory Complaints Scale (SMC) and The Memory Complaint Questionnaire (MAC-Q) were applied in 121 mixed memory clinic patients with mild cognitive symptoms (mean MMSE = 26.8, SD 2.7). The scales were applied independently and raters were blinded to results from the other scale. Scales were not used for diagnostic classification. Cognitive performances and depressive symptoms were also rated. We studied the association between the two measures and investigated the scales' relation to depressive symptoms, age, and cognitive status. SMC and MAC-Q were significantly associated (r = 0.44, N = 121, p = 0.015) and both scales had a wide range of scores. In this mixed cohort of patients, younger age was associated with higher SMC scores. There were no significant correlations between cognitive test performances and scales measuring subjective decline. Depression scores were significantly correlated to both scales measuring subjective decline. Linear regression models showed that age did not have a significant contribution to the variance in subjective memory beyond that of depressive symptoms. Measures for subjective cognitive decline are not interchangeable when used in memory clinics and the application of different scales in previous studies is an important factor as to why studies show variability in the association between subjective cognitive decline and background data and/or clinical results. Careful consideration should be taken as to which questions are relevant and have validity when operationalizing subjective cognitive decline.

Methods to control for unmeasured confounding in pharmacoepidemiology: an overview.

PubMed

Uddin, Md Jamal; Groenwold, Rolf H H; Ali, Mohammed Sanni; de Boer, Anthonius; Roes, Kit C B; Chowdhury, Muhammad A B; Klungel, Olaf H

2016-06-01

Background Unmeasured confounding is one of the principal problems in pharmacoepidemiologic studies. Several methods have been proposed to detect or control for unmeasured confounding either at the study design phase or the data analysis phase. Aim of the Review To provide an overview of commonly used methods to detect or control for unmeasured confounding and to provide recommendations for proper application in pharmacoepidemiology. Methods/Results Methods to control for unmeasured confounding in the design phase of a study are case only designs (e.g., case-crossover, case-time control, self-controlled case series) and the prior event rate ratio adjustment method. Methods that can be applied in the data analysis phase include, negative control method, perturbation variable method, instrumental variable methods, sensitivity analysis, and ecological analysis. A separate group of methods are those in which additional information on confounders is collected from a substudy. The latter group includes external adjustment, propensity score calibration, two-stage sampling, and multiple imputation. Conclusion As the performance and application of the methods to handle unmeasured confounding may differ across studies and across databases, we stress the importance of using both statistical evidence and substantial clinical knowledge for interpretation of the study results.

Combining Fourier and lagged k-nearest neighbor imputation for biomedical time series data.

PubMed

Rahman, Shah Atiqur; Huang, Yuxiao; Claassen, Jan; Heintzman, Nathaniel; Kleinberg, Samantha

2015-12-01

Most clinical and biomedical data contain missing values. A patient's record may be split across multiple institutions, devices may fail, and sensors may not be worn at all times. While these missing values are often ignored, this can lead to bias and error when the data are mined. Further, the data are not simply missing at random. Instead the measurement of a variable such as blood glucose may depend on its prior values as well as that of other variables. These dependencies exist across time as well, but current methods have yet to incorporate these temporal relationships as well as multiple types of missingness. To address this, we propose an imputation method (FLk-NN) that incorporates time lagged correlations both within and across variables by combining two imputation methods, based on an extension to k-NN and the Fourier transform. This enables imputation of missing values even when all data at a time point is missing and when there are different types of missingness both within and across variables. In comparison to other approaches on three biological datasets (simulated and actual Type 1 diabetes datasets, and multi-modality neurological ICU monitoring) the proposed method has the highest imputation accuracy. This was true for up to half the data being missing and when consecutive missing values are a significant fraction of the overall time series length. Copyright © 2015 Elsevier Inc. All rights reserved.

How well are journal and clinical article characteristics associated with the journal impact factor? a retrospective cohort study

PubMed Central

Lokker, Cynthia; Haynes, R. Brian; Chu, Rong; McKibbon, K. Ann; Wilczynski, Nancy L; Walter, Stephen D

2012-01-01

Objective: Journal impact factor (JIF) is often used as a measure of journal quality. A retrospective cohort study determined the ability of clinical article and journal characteristics, including appraisal measures collected at the time of publication, to predict subsequent JIFs. Methods: Clinical research articles that passed methods quality criteria were included. Each article was rated for relevance and newsworthiness by 3 to 24 physicians from a panel of more than 4,000 practicing clinicians. The 1,267 articles (from 103 journals) were divided 60∶40 into derivation (760 articles) and validation sets (507 articles), representing 99 and 88 journals, respectively. A multiple regression model was produced determining the association of 10 journal and article measures with the 2007 JIF. Results: Four of the 10 measures were significant in the regression model: number of authors, number of databases indexing the journal, proportion of articles passing methods criteria, and mean clinical newsworthiness scores. With the number of disciplines rating the article, the 5 variables accounted for 61% of the variation in JIF (R2 = 0.607, 95% CI 0.444 to 0.706, P<0.001). Conclusion: For the clinical literature, measures of scientific quality and clinical newsworthiness available at the time of publication can predict JIFs with 60% accuracy. PMID:22272156

24-Hour Blood Pressure Variability Assessed by Average Real Variability: A Systematic Review and Meta-Analysis.

PubMed

Mena, Luis J; Felix, Vanessa G; Melgarejo, Jesus D; Maestre, Gladys E

2017-10-19

Although 24-hour blood pressure (BP) variability (BPV) is predictive of cardiovascular outcomes independent of absolute BP levels, it is not regularly assessed in clinical practice. One possible limitation to routine BPV assessment is the lack of standardized methods for accurately estimating 24-hour BPV. We conducted a systematic review to assess the predictive power of reported BPV indexes to address appropriate quantification of 24-hour BPV, including the average real variability (ARV) index. Studies chosen for review were those that presented data for 24-hour BPV in adults from meta-analysis, longitudinal or cross-sectional design, and examined BPV in terms of the following issues: (1) methods used to calculate and evaluate ARV; (2) assessment of 24-hour BPV determined using noninvasive ambulatory BP monitoring; (3) multivariate analysis adjusted for covariates, including some measure of BP; (4) association of 24-hour BPV with subclinical organ damage; and (5) the predictive value of 24-hour BPV on target organ damage and rate of cardiovascular events. Of the 19 assessed studies, 17 reported significant associations between high ARV and the presence and progression of subclinical organ damage, as well as the incidence of hard end points, such as cardiovascular events. In all these cases, ARV remained a significant independent predictor ( P <0.05) after adjustment for BP and other clinical factors. In addition, increased ARV in systolic BP was associated with risk of all cardiovascular events (hazard ratio, 1.18; 95% confidence interval, 1.09-1.27). Only 2 cross-sectional studies did not find that high ARV was a significant risk factor. Current evidence suggests that ARV index adds significant prognostic information to 24-hour ambulatory BP monitoring and is a useful approach for studying the clinical value of BPV. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Birth Control in Clinical Trials

PubMed Central

Stewart, J.; Beyer, B. K.; Chadwick, K.; De Schaepdrijver, L.; Desai, M.; Enright, B.; Foster, W.; Hui, J. Y.; Moffat, G. J.; Tornesi, B.; Van Malderen, K.; Wiesner, L.; Chen, C. L.

2015-01-01

The Health and Environmental Sciences Institute (HESI) Developmental and Reproductive Toxicology Technical Committee sponsored a pharmaceutical industry survey on current industry practices for contraception use during clinical trials. The objectives of the survey were to improve our understanding of the current industry practices for contraception requirements in clinical trials, the governance processes set up to promote consistency and/or compliance with contraception requirements, and the effectiveness of current contraception practices in preventing pregnancies during clinical trials. Opportunities for improvements in current practices were also considered. The survey results from 12 pharmaceutical companies identified significant variability among companies with regard to contraception practices and governance during clinical trials. This variability was due primarily to differences in definitions, areas of scientific uncertainty or misunderstanding, and differences in company approaches to enrollment in clinical trials. The survey also revealed that few companies collected data in a manner that would allow a retrospective understanding of the reasons for failure of birth control during clinical trials. In this article, suggestions are made for topics where regulatory guidance or scientific publications could facilitate best practice. These include provisions for a pragmatic definition of women of childbearing potential, guidance on how animal data can influence the requirements for male and female birth control, evidence-based guidance on birth control and pregnancy testing regimes suitable for low- and high-risk situations, plus practical methods to ascertain the risk of drug-drug interactions with hormonal contraceptives. PMID:27042398

Applicable or non-applicable: investigations of clinical heterogeneity in systematic reviews.

PubMed

Chess, Laura E; Gagnier, Joel J

2016-02-17

Clinical heterogeneity can be defined as differences in participant characteristics, types or timing of outcome measurements and intervention characteristics. Clinical heterogeneity in systematic reviews has the possibility to significantly affect statistical heterogeneity leading to inaccurate conclusions and misled decision making. The aim of this study is to identify to what extent investigators are assessing clinical heterogeneity in both Cochrane and non-Cochrane systematic reviews. The most recent 100 systematic reviews from the top five journals in medicine-JAMA, Archives of Internal Medicine, British Medical Journal, The Lancet, and PLOS Medicine-and the 100 most recently published and/or updated systematic reviews from Cochrane were collected. Various defined items of clinical heterogeneity were extracted from the included reviews. Investigators used chi-squared tests, logarithmic modeling and linear regressions to determine if the presence of such items served as a predictor for clinical heterogeneity when comparing Cochrane to non-Cochrane reviews. Extracted variables include number of studies, number of participants, presence of quantitative synthesis, exploration of clinical heterogeneity, heterogeneous characteristics explored, basis and methods used for investigating clinical heterogeneity, plotting/visual aids, author contact, inferences from clinical heterogeneity investigation, reporting assessment, and the presence of a priori or post-hoc analysis. A total of 317 systematic reviews were considered, of which 199 were in the final analysis. A total of 81% of Cochrane reviews and 90% of non-Cochrane reviews explored characteristics that are considered aspects of clinical heterogeneity and also described the methods they planned to use to investigate the influence of those characteristics. Only 1% of non-Cochrane reviews and 8% of Cochrane reviews explored the clinical characteristics they initially chose as potential for clinical heterogeneity. Very few studies mentioned clinician training, compliance, brand, co-interventions, dose route, ethnicity, prognostic markers and psychosocial variables as covariates to investigate as potentially clinically heterogeneous. Addressing aspects of clinical heterogeneity was not different between Cochrane and non-Cochrane reviews. The ability to quantify and compare the clinical differences of trials within a meta-analysis is crucial to determining its applicability and use in clinical practice. Despite Cochrane Collaboration emphasis on methodology, the proportion of reviews that assess clinical heterogeneity is less than those of non-Cochrane reviews. Our assessment reveals that there is room for improvement in assessing clinical heterogeneity in both Cochrane and non-Cochrane reviews.

Analysis of causality from observational studies and its application in clinical research in Intensive Care Medicine.

PubMed

Coscia Requena, C; Muriel, A; Peñuelas, O

2018-02-28

Random allocation of treatment or intervention is the key feature of clinical trials and divides patients into treatment groups that are approximately balanced for baseline, and therefore comparable covariates except for the variable treatment of the study. However, in observational studies, where treatment allocation is not random, patients in the treatment and control groups often differ in covariates that are related to intervention variables. These imbalances in covariates can lead to biased estimates of the treatment effect. However, randomized clinical trials are sometimes not feasible for ethical, logistical, economic or other reasons. To resolve these situations, interest in the field of clinical research has grown in designing studies that are most similar to randomized experiments using observational (i.e. non-random) data. Observational studies using propensity score analysis methods have been increasing in the scientific papers of Intensive Care. Propensity score analyses attempt to control for confounding in non-experimental studies by adjusting for the likelihood that a given patient is exposed. However, studies with propensity indexes may be confusing, and intensivists are not familiar with this methodology and may not fully understand the importance of this technique. The objectives of this review are: to describe the fundamentals of propensity index methods; to present the techniques to adequately evaluate propensity index models; to discuss the advantages and disadvantages of these techniques. Copyright © 2018 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

Individualized prediction of lung-function decline in chronic obstructive pulmonary disease

PubMed Central

Zafari, Zafar; Sin, Don D.; Postma, Dirkje S.; Löfdahl, Claes-Göran; Vonk, Judith; Bryan, Stirling; Lam, Stephen; Tammemagi, C. Martin; Khakban, Rahman; Man, S.F. Paul; Tashkin, Donald; Wise, Robert A.; Connett, John E.; McManus, Bruce; Ng, Raymond; Hollander, Zsuszanna; Sadatsafavi, Mohsen

2016-01-01

Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD. Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being −124 to −15 mL/yr for smokers and −83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets. Interpretation: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD. Trial registration: Lung Health Study — ClinicalTrials.gov, no. NCT00000568; Pan-Canadian Early Detection of Lung Cancer Study — ClinicalTrials.gov, no. NCT00751660 PMID:27486205

Personalized treatment planning with a model of radiation therapy outcomes for use in multiobjective optimization of IMRT plans for prostate cancer.

PubMed

Smith, Wade P; Kim, Minsun; Holdsworth, Clay; Liao, Jay; Phillips, Mark H

2016-03-11

To build a new treatment planning approach that extends beyond radiation transport and IMRT optimization by modeling the radiation therapy process and prognostic indicators for more outcome-focused decision making. An in-house treatment planning system was modified to include multiobjective inverse planning, a probabilistic outcome model, and a multi-attribute decision aid. A genetic algorithm generated a set of plans embodying trade-offs between the separate objectives. An influence diagram network modeled the radiation therapy process of prostate cancer using expert opinion, results of clinical trials, and published research. A Markov model calculated a quality adjusted life expectancy (QALE), which was the endpoint for ranking plans. The Multiobjective Evolutionary Algorithm (MOEA) was designed to produce an approximation of the Pareto Front representing optimal tradeoffs for IMRT plans. Prognostic information from the dosimetrics of the plans, and from patient-specific clinical variables were combined by the influence diagram. QALEs were calculated for each plan for each set of patient characteristics. Sensitivity analyses were conducted to explore changes in outcomes for variations in patient characteristics and dosimetric variables. The model calculated life expectancies that were in agreement with an independent clinical study. The radiation therapy model proposed has integrated a number of different physical, biological and clinical models into a more comprehensive model. It illustrates a number of the critical aspects of treatment planning that can be improved and represents a more detailed description of the therapy process. A Markov model was implemented to provide a stronger connection between dosimetric variables and clinical outcomes and could provide a practical, quantitative method for making difficult clinical decisions.

Phenotypic variability of the kyphoscoliotic type of Ehlers-Danlos syndrome (EDS VIA): clinical, molecular and biochemical delineation

PubMed Central

2011-01-01

Background The kyphoscoliotic type of Ehlers-Danlos syndrome (EDS VIA) (OMIM 225400) is a rare inheritable connective tissue disorder characterized by a deficiency of collagen lysyl hydroxylase 1 (LH1; EC 1.14.11.4) due to mutations in PLOD1. Biochemically this results in underhydroxylation of collagen lysyl residues and, hence, an abnormal pattern of lysyl pyridinoline (LP) and hydroxylysyl pyridinoline (HP) crosslinks excreted in the urine. Clinically the disorder is characterized by hypotonia and kyphoscoliosis at birth, joint hypermobility, and skin hyperelasticity and fragility. Severe hypotonia usually leads to delay in gross motor development, whereas cognitive development is reported to be normal. Methods We describe the clinical, biochemical and molecular characterisation, as well as electron microscopy findings of skin, in 15 patients newly diagnosed with this rare type of Ehlers-Danlos syndrome. Results Age at diagnosis ranged from 5 months to 27 years, with only 1/3 of the patients been diagnosed correctly in the first year of life. A similar disease frequency was found in females and males, however a broad disease severity spectrum (intra- and interfamilial), independent of molecular background or biochemical phenotype, was observed. Kyphoscoliosis, one of the main clinical features was not present at birth in 4 patients. Importantly we also noted the occurrence of vascular rupture antenatally and postnatally, as well as developmental delay in 5 patients. Conclusion In view of these findings we propose that EDS VIA is a highly variable clinical entity, presenting with a broad clinical spectrum, which may also be associated with cognitive delay and an increased risk for vascular events. Genotype/phenotype association studies and additional molecular investigations in more extended EDS VIA populations will be necessary to further elucidate the cause of the variability of the disease severity. PMID:21699693

Dolichoectatic aneurysms of the vertebrobasilar system: clinical and radiographic factors that predict poor outcomes.

PubMed

Xu, David S; Levitt, Michael R; Kalani, M Yashar S; Rangel-Castilla, Leonardo; Mulholland, Celene B; Abecassis, Isaac J; Morton, Ryan P; Nerva, John D; Siddiqui, Adnan H; Levy, Elad I; Spetzler, Robert F; Albuquerque, Felipe C; McDougall, Cameron G

2018-02-01

OBJECTIVE Fusiform dolichoectatic vertebrobasilar aneurysms are rare, challenging lesions. The natural history of these lesions and medium- and long-term patient outcomes are poorly understood. The authors sought to evaluate patient prognosis after diagnosis of fusiform dolichoectatic vertebrobasilar aneurysms and to identify clinical and radiographic predictors of neurological deterioration. METHODS The authors reviewed multiple, prospectively maintained, single-provider databases at 3 large-volume cerebrovascular centers to obtain data on patients with unruptured, fusiform, basilar artery dolichoectatic aneurysms diagnosed between January 1, 2000, and January 1, 2015. RESULTS A total of 50 patients (33 men, 17 women) were identified; mean clinical follow-up was 50.1 months and mean radiographic follow-up was 32.4 months. At last follow-up, 42% (n = 21) of aneurysms had progressed and 44% (n = 22) of patients had deterioration of their modified Rankin Scale scores. When patients were dichotomized into 2 groups- those who worsened and those who did not-univariate analysis showed 5 variables to be statistically significantly different: sex (p = 0.007), radiographic brainstem compression (p = 0.03), clinical posterior fossa compression (p < 0.001), aneurysmal growth on subsequent imaging (p = 0.001), and surgical therapy (p = 0.006). A binary logistic regression was then created to evaluate these variables. The only variable found to be a statistically significant predictor of clinical worsening was clinical symptoms of posterior fossa compression at presentation (p = 0.01). CONCLUSIONS Fusiform dolichoectatic vertebrobasilar aneurysms carry a poor prognosis, with approximately one-half of the patients deteriorating or experiencing progression of their aneurysm within 5 years. Despite being high risk, intervention-when carefully timed (before neurological decline)-may be beneficial in select patients.

Intercenter Differences in Bronchopulmonary Dysplasia or Death Among Very Low Birth Weight Infants

PubMed Central

Walsh, Michele; Bobashev, Georgiy; Das, Abhik; Levine, Burton; Carlo, Waldemar A.; Higgins, Rosemary D.

2011-01-01

OBJECTIVES: To determine (1) the magnitude of clustering of bronchopulmonary dysplasia (36 weeks) or death (the outcome) across centers of the Eunice Kennedy Shriver National Institute of Child and Human Development National Research Network, (2) the infant-level variables associated with the outcome and estimate their clustering, and (3) the center-specific practices associated with the differences and build predictive models. METHODS: Data on neonates with a birth weight of <1250 g from the cluster-randomized benchmarking trial were used to determine the magnitude of clustering of the outcome according to alternating logistic regression by using pairwise odds ratio and predictive modeling. Clinical variables associated with the outcome were identified by using multivariate analysis. The magnitude of clustering was then evaluated after correction for infant-level variables. Predictive models were developed by using center-specific and infant-level variables for data from 2001 2004 and projected to 2006. RESULTS: In 2001–2004, clustering of bronchopulmonary dysplasia/death was significant (pairwise odds ratio: 1.3; P < .001) and increased in 2006 (pairwise odds ratio: 1.6; overall incidence: 52%; range across centers: 32%–74%); center rates were relatively stable over time. Variables that varied according to center and were associated with increased risk of outcome included lower body temperature at NICU admission, use of prophylactic indomethacin, specific drug therapy on day 1, and lack of endotracheal intubation. Center differences remained significant even after correction for clustered variables. CONCLUSION: Bronchopulmonary dysplasia/death rates demonstrated moderate clustering according to center. Clinical variables associated with the outcome were also clustered. Center differences after correction of clustered variables indicate presence of as-yet unmeasured center variables. PMID:21149431

Assessing national provision of care: variability in bariatric clinical care pathways.

PubMed

Telem, Dana A; Majid, Saniea F; Powers, Kinga; DeMaria, Eric; Morton, John; Jones, Daniel B

2017-02-01

The American Society for Metabolic and Bariatric Surgery (ASMBS) Quality Improvement and Patient Safety (QIPS) Committee hypothesized that collecting and sharing clinical pathways could provide a valuable resource to new and existing bariatric programs. To shed light on the variability in practice patterns across the country by analyzing pathways. United States Centers of Excellence METHODS: From June 2014 to April 2015, clinical pathways pertaining to preoperative, intraoperative, and postoperative management of bariatric patients were solicited from the ASMBS executive council (EC), QIPS committee members, and state chapter presidents. Pathways were de-identified and then analyzed based on predetermined metrics pertaining to preoperative, intraoperative, and postoperative care. Concordance and discordance were then analyzed. In total, 31 pathways were collected; response rate was 80% from the EC, 77% from the QIPS committee, and 21% from state chapter presidents. The number of pathways sent in ranged from 1 to 10 with a median of 3 pathways per individual or institution. The majority of pathways centered on perioperative care (80%). Binary assessment (presence or absence) of variables found a high concordance (defined by greater than 65% of pathways accounting for that parameter) in only 6 variables: nutritional evaluation, psychological evaluation, intraoperative venous thromboembolism (VTE) prophylaxis, utilization of antiemetics in the postoperative period, a dedicated pain pathway, and postoperative laboratory evaluation. There is considerable national variation in clinical pathways among practicing bariatric surgeons. Most pathways center on Metabolic and Bariatric Surgery Accredited Quality Improvement Program (MBSAQIP) accreditation parameters, patient satisfaction, or Surgical Care Improvement Protocol (SCIP) measures. These pathways provide a path toward standardization of improved care. Copyright © 2016. Published by Elsevier Inc.

EULAR/ACR classification criteria for adult and juvenile idiopathic inflammatory myopathies and their major subgroups: a methodology report

PubMed Central

Bottai, Matteo; Tjärnlund, Anna; Santoni, Giola; Werth, Victoria P; Pilkington, Clarissa; de Visser, Marianne; Alfredsson, Lars; Amato, Anthony A; Barohn, Richard J; Liang, Matthew H; Aggarwal, Rohit; Arnardottir, Snjolaug; Chinoy, Hector; Cooper, Robert G; Danko, Katalin; Dimachkie, Mazen M; Feldman, Brian M; García-De La Torre, Ignacio; Gordon, Patrick; Hayashi, Taichi; Katz, James D; Kohsaka, Hitoshi; Lachenbruch, Peter A; Lang, Bianca A; Li, Yuhui; Oddis, Chester V; Olesinka, Marzena; Reed, Ann M; Rutkowska-Sak, Lidia; Sanner, Helga; Selva-O’Callaghan, Albert; Wook Song, Yeong; Ytterberg, Steven R; Miller, Frederick W; Rider, Lisa G; Lundberg, Ingrid E; Amoruso, Maria

2017-01-01

Objective To describe the methodology used to develop new classification criteria for adult and juvenile idiopathic inflammatory myopathies (IIMs) and their major subgroups. Methods An international, multidisciplinary group of myositis experts produced a set of 93 potentially relevant variables to be tested for inclusion in the criteria. Rheumatology, dermatology, neurology and paediatric clinics worldwide collected data on 976 IIM cases (74% adults, 26% children) and 624 non-IIM comparator cases with mimicking conditions (82% adults, 18% children). The participating clinicians classified each case as IIM or non-IIM. Generally, the classification of any given patient was based on few variables, leaving remaining variables unmeasured. We investigated the strength of the association between all variables and between these and the disease status as determined by the physician. We considered three approaches: (1) a probability-score approach, (2) a sum-of-items approach criteria and (3) a classification-tree approach. Results The approaches yielded several candidate models that were scrutinised with respect to statistical performance and clinical relevance. The probability-score approach showed superior statistical performance and clinical practicability and was therefore preferred over the others. We developed a classification tree for subclassification of patients with IIM. A calculator for electronic devices, such as computers and smartphones, facilitates the use of the European League Against Rheumatism/American College of Rheumatology (EULAR/ACR) classification criteria. Conclusions The new EULAR/ACR classification criteria provide a patient’s probability of having IIM for use in clinical and research settings. The probability is based on a score obtained by summing the weights associated with a set of criteria items. PMID:29177080

Evaluation of clinical, laboratory and morphologic prognostic factors in colon cancer

PubMed Central

Grande, Michele; Milito, Giovanni; Attinà, Grazia Maria; Cadeddu, Federica; Muzi, Marco Gallinella; Nigro, Casimiro; Rulli, Francesco; Farinon, Attilio Maria

2008-01-01

Background The long-term prognosis of patients with colon cancer is dependent on many factors. To investigate the influence of a series of clinical, laboratory and morphological variables on prognosis of colon carcinoma we conducted a retrospective analysis of our data. Methods Ninety-two patients with colon cancer, who underwent surgical resection between January 1999 and December 2001, were analyzed. On survival analysis, demographics, clinical, laboratory and pathomorphological parameters were tested for their potential prognostic value. Furthermore, univariate and multivariate analysis of the above mentioned data were performed considering the depth of tumour invasion into the bowel wall as independent variable. Results On survival analysis we found that depth of tumour invasion (P < 0.001; F-ratio 2.11), type of operation (P < 0.001; F-ratio 3.51) and CT scanning (P < 0.001; F-ratio 5.21) were predictors of survival. Considering the degree of mural invasion as independent variable, on univariate analysis, we observed that mucorrhea, anismus, hematocrit, WBC count, fibrinogen value and CT scanning were significantly related to the degree of mural invasion of the cancer. On the multivariate analysis, fibrinogen value was the most statistically significant variable (P < 0.001) with the highest F-ratio (F-ratio 5.86). Finally, in the present study, the tumour site was significantly related neither to the survival nor to the mural invasion of the tumour. Conclusion The various clinical, laboratory and patho-morphological parameters showed different prognostic value for colon carcinoma. In the future, preoperative prognostic markers will probably gain relevance in order to make a proper choice between surgery, chemotherapy and radiotherapy. Nevertheless, current data do not provide sufficient evidence for preoperative stratification of high and low risk patients. Further assessments in prospective large studies are warranted. PMID:18778464

Who will have Sustainable Employment After a Back Injury? The Development of a Clinical Prediction Model in a Cohort of Injured Workers.

PubMed

Shearer, Heather M; Côté, Pierre; Boyle, Eleanor; Hayden, Jill A; Frank, John; Johnson, William G

2017-09-01

Purpose Our objective was to develop a clinical prediction model to identify workers with sustainable employment following an episode of work-related low back pain (LBP). Methods We used data from a cohort study of injured workers with incident LBP claims in the USA to predict employment patterns 1 and 6 months following a workers' compensation claim. We developed three sequential models to determine the contribution of three domains of variables: (1) basic demographic/clinical variables; (2) health-related variables; and (3) work-related factors. Multivariable logistic regression was used to develop the predictive models. We constructed receiver operator curves and used the c-index to measure predictive accuracy. Results Seventy-nine percent and 77 % of workers had sustainable employment at 1 and 6 months, respectively. Sustainable employment at 1 month was predicted by initial back pain intensity, mental health-related quality of life, claim litigation and employer type (c-index = 0.77). At 6 months, sustainable employment was predicted by physical and mental health-related quality of life, claim litigation and employer type (c-index = 0.77). Adding health-related and work-related variables to models improved predictive accuracy by 8.5 and 10 % at 1 and 6 months respectively. Conclusion We developed clinically-relevant models to predict sustainable employment in injured workers who made a workers' compensation claim for LBP. Inquiring about back pain intensity, physical and mental health-related quality of life, claim litigation and employer type may be beneficial in developing programs of care. Our models need to be validated in other populations.

The Analytic Information Warehouse (AIW): a Platform for Analytics using Electronic Health Record Data

PubMed Central

Post, Andrew R.; Kurc, Tahsin; Cholleti, Sharath; Gao, Jingjing; Lin, Xia; Bornstein, William; Cantrell, Dedra; Levine, David; Hohmann, Sam; Saltz, Joel H.

2013-01-01

Objective To create an analytics platform for specifying and detecting clinical phenotypes and other derived variables in electronic health record (EHR) data for quality improvement investigations. Materials and Methods We have developed an architecture for an Analytic Information Warehouse (AIW). It supports transforming data represented in different physical schemas into a common data model, specifying derived variables in terms of the common model to enable their reuse, computing derived variables while enforcing invariants and ensuring correctness and consistency of data transformations, long-term curation of derived data, and export of derived data into standard analysis tools. It includes software that implements these features and a computing environment that enables secure high-performance access to and processing of large datasets extracted from EHRs. Results We have implemented and deployed the architecture in production locally. The software is available as open source. We have used it as part of hospital operations in a project to reduce rates of hospital readmission within 30 days. The project examined the association of over 100 derived variables representing disease and co-morbidity phenotypes with readmissions in five years of data from our institution’s clinical data warehouse and the UHC Clinical Database (CDB). The CDB contains administrative data from over 200 hospitals that are in academic medical centers or affiliated with such centers. Discussion and Conclusion A widely available platform for managing and detecting phenotypes in EHR data could accelerate the use of such data in quality improvement and comparative effectiveness studies. PMID:23402960

Prediction of remission of depression with clinical variables, neuropsychological performance, and serotonergic/dopaminergic gene polymorphisms.

PubMed

Gudayol-Ferré, Esteve; Herrera-Guzmán, Ixchel; Camarena, Beatriz; Cortés-Penagos, Carlos; Herrera-Abarca, Jorge E; Martínez-Medina, Patricia; Asbun-Bojalil, Juan; Lira-Islas, Yuridia; Reyes-Ponce, Celia; Guàrdia-Olmos, Joan

2012-11-01

The aim of our work is to study the possible role of clinical variables, neuropsychological performance, and the 5HTTLPR, rs25531, and val108/58Met COMT polymorphisms on the prediction of depression remission after 12 weeks' treatment with fluoxetine. These variables have been studied as potential predictors of depression remission, but they present poor prognostic sensitivity and specificity by themselves. Seventy-two depressed patients were genotyped according to the aforementioned polymorphisms and were clinically and neuropsychologically assessed before a 12-week fluxetine treatment. Only the La allele of rs25531 polymorphism and the GG and AA forms of the val 108/158 Met polymorphism predict major depressive disorder remission after 12 weeks' treatment with fluoxetine. None of the clinical and neuropsychological variables studied predicted remission. Our results suggest that clinical and neuropsychological variables can initially predict early response to fluoxetine and mask the predictive role of genetic variables; but in remission, where clinical and neuropsychological symptoms associated with depression tend to disappear thanks to the treatment administered, the polymorphisms studied are the only variables in our model capable of predicting remission. However, placebo effects that are difficult to control require cautious interpretation of the results.

Clinical and Biological Predictors of Plasma Levels of Soluble RAGE in Critically Ill Patients: Secondary Analysis of a Prospective Multicenter Observational Study

PubMed Central

Pranal, Thibaut; Pereira, Bruno; Berthelin, Pauline; Roszyk, Laurence; Chabanne, Russell; Eisenmann, Nathanael; Lautrette, Alexandre; Belville, Corinne; Blondonnet, Raiko; Gillart, Thierry; Skrzypczak, Yvan; Souweine, Bertrand; Bouvier, Damien; Constantin, Jean-Michel

2018-01-01

Rationale Although soluble forms of the receptor for advanced glycation end products (RAGE) have been recently proposed as biomarkers in multiple acute or chronic diseases, few studies evaluated the influence of usual clinical and biological parameters, or of patient characteristics and comorbidities, on circulating levels of soluble RAGE in the intensive care unit (ICU) setting. Objectives To determine, among clinical and biological parameters that are usually recorded upon ICU admission, which variables, if any, could be associated with plasma levels of soluble RAGE. Methods Data for this ancillary study were prospectively obtained from adult patients with at least one ARDS risk factor upon ICU admission enrolled in a large multicenter observational study. At ICU admission, plasma levels of total soluble RAGE (sRAGE) and endogenous secretory (es)RAGE were measured by duplicate ELISA and baseline patient characteristics, comorbidities, and usual clinical and biological indices were recorded. After univariate analyses, significant variables were used in multivariate, multidimensional analyses. Measurements and Main Results 294 patients were included in this ancillary study, among whom 62% were admitted for medical reasons, including septic shock (11%), coma (11%), and pneumonia (6%). Although some variables were associated with plasma levels of RAGE soluble forms in univariate analysis, multidimensional analyses showed no significant association between admission parameters and baseline plasma sRAGE or esRAGE. Conclusions We found no obvious association between circulating levels of soluble RAGE and clinical and biological indices that are usually recorded upon ICU admission. This trial is registered with NCT02070536. PMID:29861796

Children’s Marking of Verbal –s by Nonmainstream English Dialect and Clinical Status

PubMed Central

Cleveland, Lesli H.; Oetting, Janna B.

2015-01-01

Purpose Children’s marking of verbal –s was examined by their dialect (African American English [AAE] vs. Southern White English [SWE]) and clinical status (specific language impairment [SLI] vs. typically developing [TD]) and as a function of 4 linguistic variables (verb regularity, negation, expression of a habitual activity, and expression of historical present tense). Method The data were language samples from 57 six-year-olds who varied by their dialect and clinical status (AAE: SLI = 14, TD = 12; SWE: SLI = 12, TD = 19). Results The AAE groups produced lower rates of marking than did the SWE groups, and the SWE SLI group produced lower rates of marking than did the SWE TD group. Although low numbers of verb contexts made it difficult to evaluate the linguistic variables, there was evidence of their influence, especially for verb regularity and negation. The direction and magnitude of the effects were often (but not always) consistent with what has been described in the adult dialect literature. Conclusion Verbal –s can be used to help distinguish children with and without SLI in SWE but not in AAE. Clinicians can apply these findings to other varieties of AAE and SWE and other dialects by considering rates of marking and the effects of linguistic variables on marking. PMID:23813205

Machine Learning methods for Quantitative Radiomic Biomarkers.

PubMed

Parmar, Chintan; Grossmann, Patrick; Bussink, Johan; Lambin, Philippe; Aerts, Hugo J W L

2015-08-17

Radiomics extracts and mines large number of medical imaging features quantifying tumor phenotypic characteristics. Highly accurate and reliable machine-learning approaches can drive the success of radiomic applications in clinical care. In this radiomic study, fourteen feature selection methods and twelve classification methods were examined in terms of their performance and stability for predicting overall survival. A total of 440 radiomic features were extracted from pre-treatment computed tomography (CT) images of 464 lung cancer patients. To ensure the unbiased evaluation of different machine-learning methods, publicly available implementations along with reported parameter configurations were used. Furthermore, we used two independent radiomic cohorts for training (n = 310 patients) and validation (n = 154 patients). We identified that Wilcoxon test based feature selection method WLCX (stability = 0.84 ± 0.05, AUC = 0.65 ± 0.02) and a classification method random forest RF (RSD = 3.52%, AUC = 0.66 ± 0.03) had highest prognostic performance with high stability against data perturbation. Our variability analysis indicated that the choice of classification method is the most dominant source of performance variation (34.21% of total variance). Identification of optimal machine-learning methods for radiomic applications is a crucial step towards stable and clinically relevant radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor-phenotypic characteristics in clinical practice.

Conventional heart rate variability analysis of ambulatory electrocardiographic recordings fails to predict imminent ventricular fibrillation

NASA Technical Reports Server (NTRS)

Vybiral, T.; Glaeser, D. H.; Goldberger, A. L.; Rigney, D. R.; Hess, K. R.; Mietus, J.; Skinner, J. E.; Francis, M.; Pratt, C. M.

1993-01-01

OBJECTIVES. The purpose of this report was to study heart rate variability in Holter recordings of patients who experienced ventricular fibrillation during the recording. BACKGROUND. Decreased heart rate variability is recognized as a long-term predictor of overall and arrhythmic death after myocardial infarction. It was therefore postulated that heart rate variability would be lowest when measured immediately before ventricular fibrillation. METHODS. Conventional indexes of heart rate variability were calculated from Holter recordings of 24 patients with structural heart disease who had ventricular fibrillation during monitoring. The control group consisted of 19 patients with coronary artery disease, of comparable age and left ventricular ejection fraction, who had nonsustained ventricular tachycardia but no ventricular fibrillation. RESULTS. Heart rate variability did not differ between the two groups, and no consistent trends in heart rate variability were observed before ventricular fibrillation occurred. CONCLUSIONS. Although conventional heart rate variability is an independent long-term predictor of adverse outcome after myocardial infarction, its clinical utility as a short-term predictor of life-threatening arrhythmias remains to be elucidated.

High Intrapatient Variability of Tacrolimus Levels and Outpatient Clinic Nonattendance Are Associated With Inferior Outcomes in Renal Transplant Patients

PubMed Central

Goodall, Dawn L.; Willicombe, Michelle; McLean, Adam G.; Taube, David

2017-01-01

Background Nonadherence to immunosuppressants is associated with rejection and allograft loss. Intrapatient variability (IPV) of immunosuppression levels is a marker of nonadherence. This study describes the impact of IPV of tacrolimus levels in patients receiving a tacrolimus monotherapy immunosuppression protocol. Methods We retrospectively analyzed the outpatient tacrolimus levels of kidney-only transplant patients taken between 6 and 12 months posttransplant. IPV was determined using the coefficient of variance. Results Six hundred twenty-eight patients with a mean number of 8.98 ± 3.81 tacrolimus levels and a mean follow-up of 4.72 ± 2.19 years were included. Multivariate analysis showed death was associated with increasing age (1.04 [1.01-1.07], P = 0.0055), diabetes at time of transplant (2.79 [1.44-5.41], P = 0.0024), and rejection (2.34 [1.06-5.19], P = 0.036). Variables associated with graft loss included the highest variability group (2.51 [1.01-6.27], P = 0.048), mean tacrolimus level less than 5 ng/mL (4.32 [1.94-9.63], P = 0.0003), a high clinic nonattendance rate (1.10 [1.01-1.20], P = 0.03), and rejection (9.83 [4.62-20.94], P < 0.0001). Independent risk factors for rejection were de novo donor-specific antibody (3.15 [1.84-5.39], P < 0.0001), mean tacrolimus level less than 5 ng/mL (2.57 [1.27-5.19], P = 0.00860, and a high clinic nonattendance rate (1.11 [1.05-1.18], P = 0.0005). Conclusions This study shows that high tacrolimus IPV and clinic nonattendance are associated with inferior allograft survival. Interventions to minimize the causes of high variability, particularly nonadherence are essential to improve long-term allograft outcomes. PMID:28795143

SU-G-IeP4-13: PET Image Noise Variability and Its Consequences for Quantifying Tumor Hypoxia

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

Kueng, R; Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario; Manser, P

Purpose: The values in a PET image which represent activity concentrations of a radioactive tracer are influenced by a large number of parameters including patient conditions as well as image acquisition and reconstruction. This work investigates noise characteristics in PET images for various image acquisition and image reconstruction parameters. Methods: Different phantoms with homogeneous activity distributions were scanned using several acquisition parameters and reconstructed with numerous sets of reconstruction parameters. Images from six PET scanners from different vendors were analyzed and compared with respect to quantitative noise characteristics. Local noise metrics, which give rise to a threshold value defining themore » metric of hypoxic fraction, as well as global noise measures in terms of noise power spectra (NPS) were computed. In addition to variability due to different reconstruction parameters, spatial variability of activity distribution and its noise metrics were investigated. Patient data from clinical trials were mapped onto phantom scans to explore the impact of the scanner’s intrinsic noise variability on quantitative clinical analysis. Results: Local noise metrics showed substantial variability up to an order of magnitude for different reconstruction parameters. Investigations of corresponding NPS revealed reconstruction dependent structural noise characteristics. For the acquisition parameters, noise metrics were guided by Poisson statistics. Large spatial non-uniformity of the noise was observed in both axial and radial direction of a PET image. In addition, activity concentrations in PET images of homogeneous phantom scans showed intriguing spatial fluctuations for most scanners. The clinical metric of the hypoxic fraction was shown to be considerably influenced by the PET scanner’s spatial noise characteristics. Conclusion: We showed that a hypoxic fraction metric based on noise characteristics requires careful consideration of the various dependencies in order to justify its quantitative validity. This work may result in recommendations for harmonizing QA of PET imaging for multi-institutional clinical trials.« less

Recruitment of black women with type 2 diabetes into a self-management intervention trial.

PubMed

Newlin, Kelley; Melkus, Gail D'Eramo; Jefferson, Vanessa; Langerman, Susan; Womack, Julie; Chyun, Deborah

2006-01-01

The purpose of this study was to evaluate the relationship of recruitment methods to enrollment status in Black women with type 2 diabetes screened for entry into a randomized clinical trial (RCT). Using a cross-sectional study design with convenience sampling procedures, data were collected on recruitment methods to which the women responded (N=236). Results demonstrated that the RCT had a moderate overall recruitment rate of 46% and achieved only 84% of its projected accrual goal (N=109). Chi-square analysis demonstrated that enrollment outcomes varied significantly according to recruitment methods (P=.05). Recruitment methods such as community health fairs (77.8%), private practice referrals (75.0%), participant referrals (61.5%), community clinic referrals (44.6%), community advertising and marketing (40.9%), and chart review (40.4%) demonstrated variable enrollment yields. Results confirm previous findings that indicate that Black Americans may be successfully recruited into research studies at moderate rates when traditional recruitment methods are enhanced and integrated with more culturally sensitive methods. Lessons learned are considered.

Visually estimated ejection fraction by two dimensional and triplane echocardiography is closely correlated with quantitative ejection fraction by real-time three dimensional echocardiography.

PubMed

Shahgaldi, Kambiz; Gudmundsson, Petri; Manouras, Aristomenis; Brodin, Lars-Ake; Winter, Reidar

2009-08-25

Visual assessment of left ventricular ejection fraction (LVEF) is often used in clinical routine despite general recommendations to use quantitative biplane Simpsons (BPS) measurements. Even thou quantitative methods are well validated and from many reasons preferable, the feasibility of visual assessment (eyeballing) is superior. There is to date only sparse data comparing visual EF assessment in comparison to quantitative methods available. The aim of this study was to compare visual EF assessment by two-dimensional echocardiography (2DE) and triplane echocardiography (TPE) using quantitative real-time three-dimensional echocardiography (RT3DE) as the reference method. Thirty patients were enrolled in the study. Eyeballing EF was assessed using apical 4-and 2 chamber views and TP mode by two experienced readers blinded to all clinical data. The measurements were compared to quantitative RT3DE. There were an excellent correlation between eyeballing EF by 2D and TP vs 3DE (r = 0.91 and 0.95 respectively) without any significant bias (-0.5 +/- 3.7% and -0.2 +/- 2.9% respectively). Intraobserver variability was 3.8% for eyeballing 2DE, 3.2% for eyeballing TP and 2.3% for quantitative 3D-EF. Interobserver variability was 7.5% for eyeballing 2D and 8.4% for eyeballing TP. Visual estimation of LVEF both using 2D and TP by an experienced reader correlates well with quantitative EF determined by RT3DE. There is an apparent trend towards a smaller variability using TP in comparison to 2D, this was however not statistically significant.

Incorporating Alternative Care Site Characteristics Into Estimates of Substitutable ED Visits.

PubMed

Trueger, Nathan Seth; Chua, Kao-Ping; Hussain, Aamir; Liferidge, Aisha T; Pitts, Stephen R; Pines, Jesse M

2017-07-01

Several recent efforts to improve health care value have focused on reducing emergency department (ED) visits that potentially could be treated in alternative care sites (ie, primary care offices, retail clinics, and urgent care centers). Estimates of the number of these visits may depend on assumptions regarding the operating hours and functional capabilities of alternative care sites. However, methods to account for the variability in these characteristics have not been developed. To develop methods to incorporate the variability in alternative care site characteristics into estimates of ED visit "substitutability." Our approach uses the range of hours and capabilities among alternative care sites to estimate lower and upper bounds of ED visit substitutability. We constructed "basic" and "extended" criteria that captured the plausible degree of variation in each site's hours and capabilities. To illustrate our approach, we analyzed data from 22,697 ED visits by adults in the 2011 National Hospital Ambulatory Medical Care Survey, defining a visit as substitutable if it was treat-and-release and met both the operating hours and functional capabilities criteria. Use of the combined basic hours/basic capabilities criteria and extended hours/extended capabilities generated lower and upper bounds of estimates. Our criteria classified 5.5%-27.1%, 7.6%-20.4%, and 10.6%-46.0% of visits as substitutable in primary care offices, retail clinics, and urgent care centers, respectively. Alternative care sites vary widely in operating hours and functional capabilities. Methods such as ours may help incorporate this variability into estimates of ED visit substitutability.

Quantification of mitral valve regurgitation in dogs with degenerative mitral valve disease by use of the proximal isovelocity surface area method.

PubMed

Gouni, Vassiliki; Serres, François J; Pouchelon, Jean-Louis; Tissier, Renaud; Lefebvre, Hervé P; Nicolle, Audrey P; Sampedrano, Carolina Carlos; Chetboul, Valérie

2007-08-01

To determine the within-day and between-day variability of regurgitant fraction (RF) assessed by use of the proximal isovelocity surface area (PISA) method in awake dogs with degenerative mitral valve disease (MVD), measure RF in dogs with MVD, and assess the correlation between RF and several clinical and Doppler echocardiographic variables. Prospective study. 6 MVD-affected dogs with no clinical signs and 67 dogs with MVD of differing severity (International Small Animal Cardiac Health Council [ISACHC] classification). The 6 dogs were used to determine the repeatability and reproducibility of the PISA method, and RF was then assessed in 67 dogs of various ISACHC classes. Mitral valve regurgitation was also assessed from the maximum area of regurgitant jet signal-to-left atrium area (ARJ/LAA) ratio determined via color Doppler echocardiographic mapping. Within- and between-day coefficients of variation of RF were 8% and 11%, respectively. Regurgitation fraction was significantly correlated with ISACHC classification and heart murmur grade and was higher in ISACHC class III dogs (mean +/- SD, 72.8 +/- 9.5%) than class II (57.9 +/- 20.1%) or I (40.7 +/- 19.2%) dogs. Regurgitation fraction and left atriumto-aorta ratio, fractional shortening, systolic pulmonary arterial pressure, and ARJ/LAA ratio were significantly correlated. Results suggested that RF is a repeatable and reproducible variable for noninvasive quantitative evaluation of mitral valve regurgitation in awake dogs. Regurgitation fraction also correlated well with disease severity. It appears that this Doppler echocardiographic index may be useful in longitudinal studies of MVD in dogs.

Toward a Model-Based Approach to the Clinical Assessment of Personality Psychopathology

PubMed Central

Eaton, Nicholas R.; Krueger, Robert F.; Docherty, Anna R.; Sponheim, Scott R.

2015-01-01

Recent years have witnessed tremendous growth in the scope and sophistication of statistical methods available to explore the latent structure of psychopathology, involving continuous, discrete, and hybrid latent variables. The availability of such methods has fostered optimism that they can facilitate movement from classification primarily crafted through expert consensus to classification derived from empirically-based models of psychopathological variation. The explication of diagnostic constructs with empirically supported structures can then facilitate the development of assessment tools that appropriately characterize these constructs. Our goal in this paper is to illustrate how new statistical methods can inform conceptualization of personality psychopathology and therefore its assessment. We use magical thinking as example, because both theory and earlier empirical work suggested the possibility of discrete aspects to the latent structure of personality psychopathology, particularly forms of psychopathology involving distortions of reality testing, yet other data suggest that personality psychopathology is generally continuous in nature. We directly compared the fit of a variety of latent variable models to magical thinking data from a sample enriched with clinically significant variation in psychotic symptomatology for explanatory purposes. Findings generally suggested a continuous latent variable model best represented magical thinking, but results varied somewhat depending on different indices of model fit. We discuss the implications of the findings for classification and applied personality assessment. We also highlight some limitations of this type of approach that are illustrated by these data, including the importance of substantive interpretation, in addition to use of model fit indices, when evaluating competing structural models. PMID:24007309

A novel technique for fetal heart rate estimation from Doppler ultrasound signal

PubMed Central

2011-01-01

Background The currently used fetal monitoring instrumentation that is based on Doppler ultrasound technique provides the fetal heart rate (FHR) signal with limited accuracy. It is particularly noticeable as significant decrease of clinically important feature - the variability of FHR signal. The aim of our work was to develop a novel efficient technique for processing of the ultrasound signal, which could estimate the cardiac cycle duration with accuracy comparable to a direct electrocardiography. Methods We have proposed a new technique which provides the true beat-to-beat values of the FHR signal through multiple measurement of a given cardiac cycle in the ultrasound signal. The method consists in three steps: the dynamic adjustment of autocorrelation window, the adaptive autocorrelation peak detection and determination of beat-to-beat intervals. The estimated fetal heart rate values and calculated indices describing variability of FHR, were compared to the reference data obtained from the direct fetal electrocardiogram, as well as to another method for FHR estimation. Results The results revealed that our method increases the accuracy in comparison to currently used fetal monitoring instrumentation, and thus enables to calculate reliable parameters describing the variability of FHR. Relating these results to the other method for FHR estimation we showed that in our approach a much lower number of measured cardiac cycles was rejected as being invalid. Conclusions The proposed method for fetal heart rate determination on a beat-to-beat basis offers a high accuracy of the heart interval measurement enabling reliable quantitative assessment of the FHR variability, at the same time reducing the number of invalid cardiac cycle measurements. PMID:21999764

Observational studies of patients in the emergency department: a comparison of 4 sampling methods.

PubMed

Valley, Morgan A; Heard, Kennon J; Ginde, Adit A; Lezotte, Dennis C; Lowenstein, Steven R

2012-08-01

We evaluate the ability of 4 sampling methods to generate representative samples of the emergency department (ED) population. We analyzed the electronic records of 21,662 consecutive patient visits at an urban, academic ED. From this population, we simulated different models of study recruitment in the ED by using 2 sample sizes (n=200 and n=400) and 4 sampling methods: true random, random 4-hour time blocks by exact sample size, random 4-hour time blocks by a predetermined number of blocks, and convenience or "business hours." For each method and sample size, we obtained 1,000 samples from the population. Using χ(2) tests, we measured the number of statistically significant differences between the sample and the population for 8 variables (age, sex, race/ethnicity, language, triage acuity, arrival mode, disposition, and payer source). Then, for each variable, method, and sample size, we compared the proportion of the 1,000 samples that differed from the overall ED population to the expected proportion (5%). Only the true random samples represented the population with respect to sex, race/ethnicity, triage acuity, mode of arrival, language, and payer source in at least 95% of the samples. Patient samples obtained using random 4-hour time blocks and business hours sampling systematically differed from the overall ED patient population for several important demographic and clinical variables. However, the magnitude of these differences was not large. Common sampling strategies selected for ED-based studies may affect parameter estimates for several representative population variables. However, the potential for bias for these variables appears small. Copyright © 2012. Published by Mosby, Inc.

Cesarean delivery rates among family physicians versus obstetricians: a population-based cohort study using instrumental variable methods

PubMed Central

Dawe, Russell Eric; Bishop, Jessica; Pendergast, Amanda; Avery, Susan; Monaghan, Kelly; Duggan, Norah; Aubrey-Bassler, Kris

2017-01-01

Background: Previous research suggests that family physicians have rates of cesarean delivery that are lower than or equivalent to those for obstetricians, but adjustments for risk differences in these analyses may have been inadequate. We used an econometric method to adjust for observed and unobserved factors affecting the risk of cesarean delivery among women attended by family physicians versus obstetricians. Methods: This retrospective population-based cohort study included all Canadian (except Quebec) hospital deliveries by family physicians and obstetricians between Apr. 1, 2006, and Mar. 31, 2009. We excluded women with multiple gestations, and newborns with a birth weight less than 500 g or gestational age less than 20 weeks. We estimated the relative risk of cesarean delivery using instrumental-variable-adjusted and logistic regression. Results: The final cohort included 776 299 women who gave birth in 390 hospitals. The risk of cesarean delivery was 27.3%, and the mean proportion of deliveries by family physicians was 26.9% (standard deviation 23.8%). The relative risk of cesarean delivery for family physicians versus obstetricians was 0.48 (95% confidence interval [CI] 0.41-0.56) with logistic regression and 1.27 (95% CI 1.02-1.57) with instrumental-variable-adjusted regression. Interpretation: Our conventional analyses suggest that family physicians have a lower rate of cesarean delivery than obstetricians, but instrumental variable analyses suggest the opposite. Because instrumental variable methods adjust for unmeasured factors and traditional methods do not, the large discrepancy between these estimates of risk suggests that clinical and/or sociocultural factors affecting the decision to perform cesarean delivery may not be accounted for in our database. PMID:29233843

Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images.

PubMed

Møllersen, Kajsa; Zortea, Maciel; Schopf, Thomas R; Kirchesch, Herbert; Godtliebsen, Fred

2017-01-01

Melanoma is the deadliest form of skin cancer, and early detection is crucial for patient survival. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classification of dermoscopic images of skin lesions was announced. A training set of 900 images with corresponding class labels and semi-automatic/manual segmentation masks was released for the challenge. An independent test set of 379 images, of which 75 were of melanomas, was used to rank the participants. This article demonstrates the impact of ranking criteria, segmentation method and classifier, and highlights the clinical perspective. We compare five different measures for diagnostic accuracy by analysing the resulting ranking of the computer systems in the challenge. Choice of performance measure had great impact on the ranking. Systems that were ranked among the top three for one measure, dropped to the bottom half when changing performance measure. Nevus Doctor, a computer system previously developed by the authors, was used to participate in the challenge, and investigate the impact of segmentation and classifier. The diagnostic accuracy when using an automatic versus the semi-automatic/manual segmentation is investigated. The unexpected small impact of segmentation method suggests that improvements of the automatic segmentation method w.r.t. resemblance to semi-automatic/manual segmentation will not improve diagnostic accuracy substantially. A small set of similar classification algorithms are used to investigate the impact of classifier on the diagnostic accuracy. The variability in diagnostic accuracy for different classifier algorithms was larger than the variability for segmentation methods, and suggests a focus for future investigations. From a clinical perspective, the misclassification of a melanoma as benign has far greater cost than the misclassification of a benign lesion. For computer systems to have clinical impact, their performance should be ranked by a high-sensitivity measure.

Nursing students’ satisfaction about their field of study

PubMed Central

HAKIM, ASHRAFALSADAT

2014-01-01

Introduction: Nowadays students' opinion is considered as a necessary factor to evaluate quality in universities. This study was performed to evaluate the nursing students' satisfaction about their field of study. Methods: The research population in this study consists of all the students of nursing studying at the second to fourth year of university (72 students). The data were collected from all the studied population. Data collection instrument was a research questionnaire. In this cross-sectional research, nursing students' satisfaction (72 students) in 6 major topics (situation of educational environment, situation of clinical environment, trainers, social image, relation to colleagues and management) was studied. The data were analyzed in SPSS, version 14, using quantitative variables and descriptive statistics including frequency distribution tables and diagrams. Results: The findings indicated that 83.3% of the students had little satisfaction as to the situation of educational environment, 47.2% about situation of clinical environment, 41.7% concerning the theoretical educational method by professors, and 41.7% as to the method of clinical education by clinical trainers. Also 47.2% were not that satisfied with the method of evaluation by the school professors, 80.6% with the method of relationship with colleagues and also 62.5% with the nursing social image. Moreover, findings indicated that 33.3% of the participants in this research were dissatisfied with the method of evaluation by clinical trainers and 50% with the method of nursing management. Conclusion: In the present study, most students had little satisfaction concerning their field of study. So it is necessary to make an attempt for continuous development of quality services. PMID:25512925

How large must a treatment effect be before it matters to practitioners? An estimation method and demonstration.

PubMed

Miller, William R; Manuel, Jennifer Knapp

2008-09-01

Treatment research is sometimes criticised as lacking in clinical relevance, and one potential source of this friction is a disconnection between statistical significance and what clinicians regard to be a meaningful difference in outcomes. This report demonstrates a novel methodology for estimating what substance abuse practitioners regard to be clinically important differences. To illustrate the estimation method, we surveyed 50 substance abuse treatment providers participating in the National Institute on Drug Abuse (NIDA) Clinical Trials Network. Practitioners identified thresholds for clinically meaningful differences on nine common outcome variables, indicated the size of effect that would justify their learning a new treatment method and estimated current outcomes from their services. Clinicians judged a difference between two treatments to be meaningful if outcomes were improved by about 10 - 12 points on the percentage of patients totally abstaining, arrested for driving while intoxicated, employed or having abnormal liver enzymes. A 5 percentage-point reduction in patient mortality was regarded as clinically significant. On continuous outcome measures (such as percentage of days abstinent or drinks per drinking day), practitioners judged an outcome to be significant when it doubled or halved the base rate. When a new treatment meets such criteria, practitioners were interested in learning it. Effects that are statistically significant in clinical trials may be unimpressive to practitioners. Clinicians' judgements of meaningful differences can inform the powering of clinical trials.

Definition of variables required for comprehensive description of drug dosage and clinical pharmacokinetics.

PubMed

Medem, Anna V; Seidling, Hanna M; Eichler, Hans-Georg; Kaltschmidt, Jens; Metzner, Michael; Hubert, Carina M; Czock, David; Haefeli, Walter E

2017-05-01

Electronic clinical decision support systems (CDSS) require drug information that can be processed by computers. The goal of this project was to determine and evaluate a compilation of variables that comprehensively capture the information contained in the summary of product characteristic (SmPC) and unequivocally describe the drug, its dosage options, and clinical pharmacokinetics. An expert panel defined and structured a set of variables and drafted a guideline to extract and enter information on dosage and clinical pharmacokinetics from textual SmPCs as published by the European Medicines Agency (EMA). The set of variables was iteratively revised and evaluated by data extraction and variable allocation of roughly 7% of all centrally approved drugs. The information contained in the SmPC was allocated to three information clusters consisting of 260 variables. The cluster "drug characterization" specifies the nature of the drug. The cluster "dosage" provides information on approved drug dosages and defines corresponding specific conditions. The cluster "clinical pharmacokinetics" includes pharmacokinetic parameters of relevance for dosing in clinical practice. A first evaluation demonstrated that, despite the complexity of the current free text SmPCs, dosage and pharmacokinetic information can be reliably extracted from the SmPCs and comprehensively described by a limited set of variables. By proposing a compilation of variables well describing drug dosage and clinical pharmacokinetics, the project represents a step forward towards the development of a comprehensive database system serving as information source for sophisticated CDSS.

Policy to implementation: evidence-based practice in community mental health – study protocol

PubMed Central

2013-01-01

Background Evidence-based treatments (EBTs) are not widely available in community mental health settings. In response to the call for implementation of evidence-based treatments in the United States, states and counties have mandated behavioral health reform through policies and other initiatives. Evaluations of the impact of these policies on implementation are rare. A systems transformation about to occur in Philadelphia, Pennsylvania, offers an important opportunity to prospectively study implementation in response to a policy mandate. Methods/design Using a prospective sequential mixed-methods design, with observations at multiple points in time, we will investigate the responses of staff from 30 community mental health clinics to a policy from the Department of Behavioral Health encouraging and incentivizing providers to implement evidence-based treatments to treat youth with mental health problems. Study participants will be 30 executive directors, 30 clinical directors, and 240 therapists. Data will be collected prior to the policy implementation, and then at two and four years following policy implementation. Quantitative data will include measures of intervention implementation and potential moderators of implementation (i.e., organizational- and leader-level variables) and will be collected from executive directors, clinical directors, and therapists. Measures include self-reported therapist fidelity to evidence-based treatment techniques as measured by the Therapist Procedures Checklist-Revised, organizational variables as measured by the Organizational Social Context Measurement System and the Implementation Climate Assessment, leader variables as measured by the Multifactor Leadership Questionnaire, attitudes towards EBTs as measured by the Evidence-Based Practice Attitude Scale, and knowledge of EBTs as measured by the Knowledge of Evidence- Based Services Questionnaire. Qualitative data will include semi-structured interviews with a subset of the sample to assess the implementation experience of high-, average-, and low-performing agencies. Mixed methods will be integrated through comparing and contrasting results from the two methods for each of the primary hypotheses in this study. Discussion Findings from the proposed research will inform both future policy mandates around implementation and the support required for the success of these policies, with the ultimate goal of improving the quality of treatment provided to youth in the public sector. PMID:23522556

Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?

PubMed

Bozkurt, Selen; Bostanci, Asli; Turhan, Murat

2017-08-11

The goal of this study is to evaluate the results of machine learning methods for the classification of OSA severity of patients with suspected sleep disorder breathing as normal, mild, moderate and severe based on non-polysomnographic variables: 1) clinical data, 2) symptoms and 3) physical examination. In order to produce classification models for OSA severity, five different machine learning methods (Bayesian network, Decision Tree, Random Forest, Neural Networks and Logistic Regression) were trained while relevant variables and their relationships were derived empirically from observed data. Each model was trained and evaluated using 10-fold cross-validation and to evaluate classification performances of all methods, true positive rate (TPR), false positive rate (FPR), Positive Predictive Value (PPV), F measure and Area Under Receiver Operating Characteristics curve (ROC-AUC) were used. Results of 10-fold cross validated tests with different variable settings promisingly indicated that the OSA severity of suspected OSA patients can be classified, using non-polysomnographic features, with 0.71 true positive rate as the highest and, 0.15 false positive rate as the lowest, respectively. Moreover, the test results of different variables settings revealed that the accuracy of the classification models was significantly improved when physical examination variables were added to the model. Study results showed that machine learning methods can be used to estimate the probabilities of no, mild, moderate, and severe obstructive sleep apnea and such approaches may improve accurate initial OSA screening and help referring only the suspected moderate or severe OSA patients to sleep laboratories for the expensive tests.

Multi-analytical Approaches Informing the Risk of Sepsis

NASA Astrophysics Data System (ADS)

Gwadry-Sridhar, Femida; Lewden, Benoit; Mequanint, Selam; Bauer, Michael

Sepsis is a significant cause of mortality and morbidity and is often associated with increased hospital resource utilization, prolonged intensive care unit (ICU) and hospital stay. The economic burden associated with sepsis is huge. With advances in medicine, there are now aggressive goal oriented treatments that can be used to help these patients. If we were able to predict which patients may be at risk for sepsis we could start treatment early and potentially reduce the risk of mortality and morbidity. Analytic methods currently used in clinical research to determine the risk of a patient developing sepsis may be further enhanced by using multi-modal analytic methods that together could be used to provide greater precision. Researchers commonly use univariate and multivariate regressions to develop predictive models. We hypothesized that such models could be enhanced by using multiple analytic methods that together could be used to provide greater insight. In this paper, we analyze data about patients with and without sepsis using a decision tree approach and a cluster analysis approach. A comparison with a regression approach shows strong similarity among variables identified, though not an exact match. We compare the variables identified by the different approaches and draw conclusions about the respective predictive capabilities,while considering their clinical significance.

Impact of a mHealth intervention for peer health workers on AIDS care in rural Uganda: a mixed methods evaluation of a cluster-randomized trial.

PubMed

Chang, Larry W; Kagaayi, Joseph; Arem, Hannah; Nakigozi, Gertrude; Ssempijja, Victor; Serwadda, David; Quinn, Thomas C; Gray, Ronald H; Bollinger, Robert C; Reynolds, Steven J

2011-11-01

Mobile phone access in low and middle-income countries is rapidly expanding and offers an opportunity to leverage limited human resources for health. We conducted a mixed methods evaluation of a cluster-randomized trial exploratory substudy on the impact of a mHealth (mobile phone) support intervention used by community-based peer health workers (PHW) on AIDS care in rural Uganda. 29 PHWs at 10 clinics were randomized by clinic to receive the intervention or not. PHWs used phones to call and text higher level providers with patient-specific clinical information. 970 patients cared for by the PHWs were followed over a 26 month period. No significant differences were found in patients' risk of virologic failure. Qualitative analyses found improvements in patient care and logistics and broad support for the mHealth intervention among patients, clinic staff, and PHWs. Key challenges identified included variable patient phone access, privacy concerns, and phone maintenance.

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers.

PubMed

Clementz, Brett A; Sweeney, John A; Hamm, Jordan P; Ivleva, Elena I; Ethridge, Lauren E; Pearlson, Godfrey D; Keshavan, Matcheri S; Tamminga, Carol A

2016-04-01

Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold standard.

Rationale and Design of the Registry for Stones of the Kidney and Ureter (ReSKU): A Prospective Observational Registry to Study the Natural History of Urolithiasis Patients

PubMed Central

Chang, Helena C.; Tzou, David T.; Usawachintachit, Manint; Duty, Brian D.; Hsi, Ryan S.; Harper, Jonathan D.; Sorensen, Mathew D.; Stoller, Marshall L.; Sur, Roger L.

2016-01-01

Abstract Objectives: Registry-based clinical research in nephrolithiasis is critical to advancing quality in urinary stone disease management and ultimately reducing stone recurrence. A need exists to develop Health Insurance Portability and Accountability Act (HIPAA)-compliant registries that comprise integrated electronic health record (EHR) data using prospectively defined variables. An EHR-based standardized patient database—the Registry for Stones of the Kidney and Ureter (ReSKU™)—was developed, and herein we describe our implementation outcomes. Materials and Methods: Interviews with academic and community endourologists in the United States, Canada, China, and Japan identified demographic, intraoperative, and perioperative variables to populate our registry. Variables were incorporated into a HIPAA-compliant Research Electronic Data Capture database linked to text prompts and registration data within the Epic EHR platform. Specific data collection instruments supporting New patient, Surgery, Postoperative, and Follow-up clinical encounters were created within Epic to facilitate automated data extraction into ReSKU. Results: The number of variables within each instrument includes the following: New patient—60, Surgery—80, Postoperative—64, and Follow-up—64. With manual data entry, the mean times to complete each of the clinic-based instruments were (minutes) as follows: New patient—12.06 ± 2.30, Postoperative—7.18 ± 1.02, and Follow-up—8.10 ± 0.58. These times were significantly reduced with the use of ReSKU structured clinic note templates to the following: New patient—4.09 ± 1.73, Postoperative—1.41 ± 0.41, and Follow-up—0.79 ± 0.38. With automated data extraction from Epic, manual entry is obviated. Conclusions: ReSKU is a longitudinal prospective nephrolithiasis registry that integrates EHR data, lowering the barriers to performing high quality clinical research and quality outcome assessments in urinary stone disease. PMID:27758162

Protocol for a prospective collaborative systematic review and meta-analysis of individual patient data from randomized controlled trials of vasoactive drugs in acute stroke: The Blood pressure in Acute Stroke Collaboration, stage-3.

PubMed

Sandset, Else Charlotte; Sanossian, Nerses; Woodhouse, Lisa J; Anderson, Craig; Berge, Eivind; Lees, Kennedy R; Potter, John F; Robinson, Thompson G; Sprigg, Nikola; Wardlaw, Joanna M; Bath, Philip M

2018-01-01

Rationale Despite several large clinical trials assessing blood pressure lowering in acute stroke, equipoise remains particularly for ischemic stroke. The "Blood pressure in Acute Stroke Collaboration" commenced in the mid-1990s focussing on systematic reviews and meta-analysis of blood pressure lowering in acute stroke. From the start, Blood pressure in Acute Stroke Collaboration planned to assess safety and efficacy of blood pressure lowering in acute stroke using individual patient data. Aims To determine the optimal management of blood pressure in patients with acute stroke, including both intracerebral hemorrhage and ischemic stroke. Secondary aims are to assess which clinical and therapeutic factors may alter the optimal management of high blood pressure in patients with acute stroke and to assess the effect of vasoactive treatments on hemodynamic variables. Methods and design Individual patient data from randomized controlled trials of blood pressure management in participants with ischemic stroke and/or intracerebral hemorrhage enrolled during the ultra-acute (pre-hospital), hyper-acute (<6 h), acute (<48 h), and sub-acute (<168 h) phases of stroke. Study outcomes The primary effect variable will be functional outcome defined by the ordinal distribution of the modified Rankin Scale; analyses will also be carried out in pre-specified subgroups to assess the modifying effects of stroke-related and pre-stroke patient characteristics. Key secondary variables will include clinical, hemodynamic and neuroradiological variables; safety variables will comprise death and serious adverse events. Discussion Study questions will be addressed in stages, according to the protocol, before integrating these into a final overreaching analysis. We invite eligible trials to join the collaboration.

Community-Based Seroepidemiological Survey of Hepatitis E Virus Infection in Catalonia, Spain▿

PubMed Central

Buti, Maria; Domínguez, Àngela; Plans, Pere; Jardí, Rossend; Schaper, Mélani; Espuñes, Jordi; Cardeñosa, Neus; Rodríguez-Frías, Francisco; Esteban, Rafael; Plasència, Antoni; Salleras, Luis

2006-01-01

The objective of the study was to investigate the prevalence of immunoglobulin G (IgG) antibodies to hepatitis E virus (HEV) infection in a population sample from Catalonia and to analyze the demographic and clinical variables associated with the presence of these antibodies. A total of 1,280 subjects between 15 and 74 years of age were selected randomly from urban and rural areas. Data for sociodemographic and clinical variables were collected by using a questionnaire. IgG antibodies to HEV were determined by an immunoenzymatic method. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for studied variables. Multiple logistic regression analysis was used to determine which variables were independently associated with the prevalence of HEV infection. Anti-HEV antibodies were detected in 96 (7.3%) of the 1,280 samples analyzed. The prevalence of antibodies was greater among males (7.8%) than among women (7%) and increased with age for both sexes, from 3% among subjects 15 to 24 years of age to 12% among subjects ≥65 years of age. Bivariate analysis of the sociodemographic and clinical variables showed an association between the prevalence of hepatitis E virus infection and minor surgery (OR, 1.96; 95% CI, 1.24 to 3.11), abdominal surgery (OR, 1.74; 95% CI, 1.12 to 2.73), and, for women, being uniparous or multiparous (OR, 2.84; 95% CI, 1.19 to 6.79). The multivariate analysis showed an association with minor surgery only (OR, 1.68; 95% CI, 1.03 to 2.70). In conclusion, anti-HEV antibodies were detected in 7.3% of the Catalan population. The seroprevalence of anti-HEV antibodies increased with age and was associated with previous minor surgery. PMID:17050741

Risk factors for intracranial hemorrhage in acute ischemic stroke patients treated with recombinant tissue plasminogen activator: a systematic review and meta-analysis of 55 studies.

PubMed

Whiteley, William N; Slot, Karsten Bruins; Fernandes, Peter; Sandercock, Peter; Wardlaw, Joanna

2012-11-01

Recombinant tissue plasminogen activator (rtPA) is an effective treatment for acute ischemic stroke but is associated with an increased risk of intracranial hemorrhage (ICH). We sought to identify the risk factors for ICH with a systematic review of the published literature. We searched for studies of rtPA-treated stroke patients that reported an association between a variable measured before rtPA infusion and clinically important ICH (parenchymal ICH or ICH associated with clinical deterioration). We calculated associations between baseline variables and ICH with random-effect meta-analyses. We identified 55 studies that measured 43 baseline variables in 65 264 acute ischemic stroke patients. Post-rtPA ICH was associated with higher age (odds ratio, 1.03 per year; 95% confidence interval, 1.01-1.04), higher stroke severity (odds ratio, 1.08 per National Institutes of Health Stroke Scale point; 95% confidence interval, 1.06-1.11), and higher glucose (odds ratio, 1.10 per mmol/L; 95% confidence interval, 1.05-1.14). There was approximately a doubling of the odds of ICH with the presence of atrial fibrillation, congestive heart failure, renal impairment, previous antiplatelet agents, leukoaraiosis, and a visible acute cerebral ischemic lesion on pretreatment brain imaging. Little of the variation in the sizes of the associations among different studies was explained by the source of the cohort, definition of ICH, or degree of adjustment for confounding variables. Individual baseline variables were modestly associated with post-rtPA ICH. Prediction of post-rtPA ICH therefore is likely to be difficult if based on single clinical or imaging factors alone. These observational data do not provide a reliable method for the individualization of treatment according to predicted ICH risk.

[CARDIOREABILITATION PECULIARITIES AND CORRECTION OF VIOLATIONS OF SISTOLIC, DIASOLIC FUNCTION AND HEART RATE VARIABILITY IN PATIENTS WITH ACUTE CORONARY SYNDROME AND CORONARY ARTERY REVASCULARIZATION].

PubMed

Shved, M; Tsuglevych, L; Kyrychok, I; Levytska, L; Boiko, T; Kitsak, Ya

2017-04-01

In patients with acute coronary syndrome (ACS) who underwent coronary arteries revascularization, violations of hemodynamics, metabolism and heart rate variability often develop in the postoperative period, therefore, the goal of the study was to establish the features of disturbances and the effectiveness of correction of left ventricular systolic and diastolic dysfunction and heart rate variability in stages of cardiorehabilitation in patients with acute coronary syndrome who underwent coronary arteries revascularization. The experimental group included 40 patients with ACS in the postoperative period who underwent balloon angioplasty and stenting of the coronary arteries (25 patients with ST-segment elevation ACS and 15 patients without ST-segment elevation ACS). The age of examined patients was 37 to 74 years, an average of 52.6±6.7 years. The control group consisted of 20 patients, comparable in age and clinico-laboratory manifestations of ACS, who underwent drug treatment with direct anticoagulants, double antiplatelet therapy, β-blockers, ACE inhibitors and statins. Clinical efficacy of cardiorespiratory process in patients of both groups was assessed by the dynamics of general clinical symptoms and parameters of natriuretic propeptide, systolic and diastolic function of the left ventricle and heart rate variability. In the initial state, clinical and laboratory-instrumental signs of myocardial ischemia disappear in patients with ACS undergoing surgical revascularization of the coronary arteries, but clinical and subclinical manifestations of heart failure were diagnosed. The use of the accelerated program of cardiac rehabilitation already during the first month of studies leads to a decreasement of the signs of systolic and diastolic dysfunction, the level of NT-proBNP and improve in the variability of the heart rhythm wich significantly improves the life quality of patients with ACS. To monitor the effectiveness and safety of cardiac rehabilitation in patients with ACS who underwent coronary arteries revascularization, in addition to the generally accepted methods (determination of heart rate, blood pressure, a 6-minute test), it is advisable to diagnose the subclinical stage of heart failure by determining the level of NT-proBNP, Doppler echocardiogram, parameters of the left ventricular systolic and diastolic function and heart rate variability.

Using digital photography in a clinical setting: a valid, accurate, and applicable method to assess food intake.

PubMed

Winzer, Eva; Luger, Maria; Schindler, Karin

2018-06-01

Regular monitoring of food intake is hardly integrated in clinical routine. Therefore, the aim was to examine the validity, accuracy, and applicability of an appropriate and also quick and easy-to-use tool for recording food intake in a clinical setting. Two digital photography methods, the postMeal method with a picture after the meal, the pre-postMeal method with a picture before and after the meal, and the visual estimation method (plate diagram; PD) were compared against the reference method (weighed food records; WFR). A total of 420 dishes from lunch (7 weeks) were estimated with both photography methods and the visual method. Validity, applicability, accuracy, and precision of the estimation methods, and additionally food waste, macronutrient composition, and energy content were examined. Tests of validity revealed stronger correlations for photography methods (postMeal: r = 0.971, p < 0.001; pre-postMeal: r = 0.995, p < 0.001) compared to the visual estimation method (r = 0.810; p < 0.001). The pre-postMeal method showed smaller variability (bias < 1 g) and also smaller overestimation and underestimation. This method accurately and precisely estimated portion sizes in all food items. Furthermore, the total food waste was 22% for lunch over the study period. The highest food waste was observed in salads and the lowest in desserts. The pre-postMeal digital photography method is valid, accurate, and applicable in monitoring food intake in clinical setting, which enables a quantitative and qualitative dietary assessment. Thus, nutritional care might be initiated earlier. This method might be also advantageous for quantitative and qualitative evaluation of food waste, with a resultantly reduction in costs.

Heart rate variability in idiopathic dilated cardiomyopathy: relation to disease severity and prognosis.

PubMed Central

Yi, G.; Goldman, J. H.; Keeling, P. J.; Reardon, M.; McKenna, W. J.; Malik, M.

1997-01-01

OBJECTIVE: To assess the clinical importance of heart rate variability (HRV) in patients with idiopathic dilated cardiomyopathy (DCM). PATIENTS AND METHODS: Time domain analysis of 24 hour HRV was performed in 64 patients with DCM, 19 of their relatives with left ventricular enlargement (possible early DCM), and 33 healthy control subjects. RESULTS: Measures of HRV were reduced in patients with DCM compared with controls (P < 0.05). HRV parameters were similar in relatives and controls. Measures of HRV were lower in DCM patients in whom progressive heart failure developed (n = 28) than in those who remained clinically stable (n = 36) during a follow up of 24 (20) months (P = 0.0001). Reduced HRV was associated with NYHA functional class, left ventricular end diastolic dimension, reduced left ventricular ejection fraction, and peak exercise oxygen consumption (P < 0.05) in all patients. DCM patients with standard deviation of normal to normal RR intervals calculated over the 24 hour period (SDNN) < 50 ms had a significantly lower survival rate free of progressive heart failure than those with SDNN > 50 ms (P = 0.0002, at 12 months; P = 0.0001, during overall follow up). Stepwise multiple regression analysis showed that SDNN < 50 ms identified, independently of other clinical variables, patients who were at increased risk of developing progressive heart failure (P = 0.0004). CONCLUSIONS: HRV is reduced in patients with DCM and related to disease severity. HRV is clinically useful as an early non-invasive marker of DCM deterioration. PMID:9068391

Multiple Intravenous Infusions Phase 2a: Ontario Survey

PubMed Central

Fan, Mark; Koczmara, Christine; Masino, Caterina; Cassano-Piché, Andrea; Trbovich, Patricia; Easty, Anthony

2014-01-01

Background Research conducted in earlier phases of this study prospectively identified a number of concerns related to the safe administration of multiple intravenous (IV) infusions in Ontario hospitals. Objective To investigate the potential prevalence of practices or policies that may contribute to the patient safety risks identified in Phase 1b of this study. Data Sources and Review Methods Sixty-four survey responses were analyzed from clinical units where multiple IV infusions may occur (e.g., adult intensive care units). Survey questions were organized according to the topics identified in Phase 1b as potential contributors to patient harm (e.g., labelling practices, patient transfer practices, secondary infusion policies). Results Survey results indicated suboptimal practices and policies in some clinical units, and variability in a number of infusion practices. Key areas of concern included the following: use of primary IV tubing without back check valves when administering secondary infusions administration of secondary infusions with/as high-alert continuous IV medications potential confusion about how IV tubing should be labelled to reflect replacement date and time interruptions to IV therapy due to IV pump and/or tubing changes when patients are transferred between clinical units coadministration of continuous or intermittent infusions on central venous pressure monitoring ports variability in respondents’ awareness of the infusion pump's bolus capabilities Limitations Due to the limited sample size, survey responses may not be representative of infusion practices across Ontario. Answers to some questions indicated that the intent of the questions might have been misunderstood. Due to a design error, 1 question about bolus administration methods was not shown to as many respondents as appropriate. Conclusions The Ontario survey revealed variability in IV infusion practice across the province and potential opportunities to improve safety. PMID:26257837

Heart rate variability measurement and clinical depression in acute coronary syndrome patients: narrative review of recent literature

PubMed Central

Harris, Patricia RE; Sommargren, Claire E; Stein, Phyllis K; Fung, Gordon L; Drew, Barbara J

2014-01-01

Aim We aimed to explore links between heart rate variability (HRV) and clinical depression in patients with acute coronary syndrome (ACS), through a review of recent clinical research literature. Background Patients with ACS are at risk for both cardiac autonomic dysfunction and clinical depression. Both conditions can negatively impact the ability to recover from an acute physiological insult, such as unstable angina or myocardial infarction, increasing the risk for adverse cardiovascular outcomes. HRV is recognized as a reflection of autonomic function. Methods A narrative review was undertaken to evaluate state-of-the-art clinical research, using the PubMed database, January 2013. The search terms “heart rate variability” and “depression” were used in conjunction with “acute coronary syndrome”, “unstable angina”, or “myocardial infarction” to find clinical studies published within the past 10 years related to HRV and clinical depression, in patients with an ACS episode. Studies were included if HRV measurement and depression screening were undertaken during an ACS hospitalization or within 2 months of hospital discharge. Results Nine clinical studies met the inclusion criteria. The studies’ results indicate that there may be a relationship between abnormal HRV and clinical depression when assessed early after an ACS event, offering the possibility that these risk factors play a modest role in patient outcomes. Conclusion While a definitive conclusion about the relevance of HRV and clinical depression measurement in ACS patients would be premature, the literature suggests that these measures may provide additional information in risk assessment. Potential avenues for further research are proposed. PMID:25071372

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

Bogunovic, Hrvoje; Pozo, Jose Maria; Villa-Uriol, Maria Cruz

Purpose: To evaluate the suitability of an improved version of an automatic segmentation method based on geodesic active regions (GAR) for segmenting cerebral vasculature with aneurysms from 3D x-ray reconstruction angiography (3DRA) and time of flight magnetic resonance angiography (TOF-MRA) images available in the clinical routine. Methods: Three aspects of the GAR method have been improved: execution time, robustness to variability in imaging protocols, and robustness to variability in image spatial resolutions. The improved GAR was retrospectively evaluated on images from patients containing intracranial aneurysms in the area of the Circle of Willis and imaged with two modalities: 3DRA andmore » TOF-MRA. Images were obtained from two clinical centers, each using different imaging equipment. Evaluation included qualitative and quantitative analyses of the segmentation results on 20 images from 10 patients. The gold standard was built from 660 cross-sections (33 per image) of vessels and aneurysms, manually measured by interventional neuroradiologists. GAR has also been compared to an interactive segmentation method: isointensity surface extraction (ISE). In addition, since patients had been imaged with the two modalities, we performed an intermodality agreement analysis with respect to both the manual measurements and each of the two segmentation methods. Results: Both GAR and ISE differed from the gold standard within acceptable limits compared to the imaging resolution. GAR (ISE) had an average accuracy of 0.20 (0.24) mm for 3DRA and 0.27 (0.30) mm for TOF-MRA, and had a repeatability of 0.05 (0.20) mm. Compared to ISE, GAR had a lower qualitative error in the vessel region and a lower quantitative error in the aneurysm region. The repeatability of GAR was superior to manual measurements and ISE. The intermodality agreement was similar between GAR and the manual measurements. Conclusions: The improved GAR method outperformed ISE qualitatively as well as quantitatively and is suitable for segmenting 3DRA and TOF-MRA images from clinical routine.« less

A Call to Standardize Preanalytic Data Elements for Biospecimens, Part II.

PubMed

Robb, James A; Bry, Lynn; Sluss, Patrick M; Wagar, Elizabeth A; Kennedy, Mary F

2015-09-01

Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Additional clinical preanalytic variables are the focus of this continuing study. To complete the identification of the essential preanalytic variables (data fields) that can, and in some instances should, be attached to every collected biospecimen by adding the additional specific variables for clinical chemistry and microbiology to our original 170 variables. The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a second Biorepository Working Group to complete the list of preanalytic variables for annotating biospecimens. Members of the second Biorepository Working Group are experts in clinical pathology and microbiology. Additional preanalytic area-specific variables were identified and ranked along with definitions and potential negative impacts if the variable is not attached to the biospecimen. The draft manuscript was reviewed by additional national and international stakeholders. Four additional required preanalytic variables were identified specifically for clinical chemistry and microbiology biospecimens that can be used as a guide for site-specific implementation into patient care and research biorepository processes. In our collective experience, selecting which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research is often difficult. The additional ranked list should be of practical benefit when selecting preanalytic variables for a given biospecimen collection.

Optimization and Validation of a Sensitive Method for HPLC-PDA Simultaneous Determination of Torasemide and Spironolactone in Human Plasma using Central Composite Design.

PubMed

Subramanian, Venkatesan; Nagappan, Kannappan; Sandeep Mannemala, Sai

2015-01-01

A sensitive, accurate, precise and rapid HPLC-PDA method was developed and validated for the simultaneous determination of torasemide and spironolactone in human plasma using Design of experiments. Central composite design was used to optimize the method using content of acetonitrile, concentration of buffer and pH of mobile phase as independent variables, while the retention factor of spironolactone, resolution between torasemide and phenobarbitone; and retention time of phenobarbitone were chosen as dependent variables. The chromatographic separation was achieved on Phenomenex C(18) column and the mobile phase comprising 20 mM potassium dihydrogen ortho phosphate buffer (pH-3.2) and acetonitrile in 82.5:17.5 v/v pumped at a flow rate of 1.0 mL min(-1). The method was validated according to USFDA guidelines in terms of selectivity, linearity, accuracy, precision, recovery and stability. The limit of quantitation values were 80 and 50 ng mL(-1) for torasemide and spironolactone respectively. Furthermore, the sensitivity and simplicity of the method suggests the validity of method for routine clinical studies.

An overview of longitudinal data analysis methods for neurological research.

PubMed

Locascio, Joseph J; Atri, Alireza

2011-01-01

The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models.

Implementing targeted region capture sequencing for the clinical detection of Alagille syndrome: An efficient and cost‑effective method.

PubMed

Huang, Tianhong; Yang, Guilin; Dang, Xiao; Ao, Feijian; Li, Jiankang; He, Yizhou; Tang, Qiyuan; He, Qing

2017-11-01

Alagille syndrome (AGS) is a highly variable, autosomal dominant disease that affects multiple structures including the liver, heart, eyes, bones and face. Targeted region capture sequencing focuses on a panel of known pathogenic genes and provides a rapid, cost‑effective and accurate method for molecular diagnosis. In a Chinese family, this method was used on the proband and Sanger sequencing was applied to validate the candidate mutation. A de novo heterozygous mutation (c.3254_3255insT p.Leu1085PhefsX24) of the jagged 1 gene was identified as the potential disease‑causing gene mutation. In conclusion, the present study suggested that target region capture sequencing is an efficient, reliable and accurate approach for the clinical diagnosis of AGS. Furthermore, these results expand on the understanding of the pathogenesis of AGS.

Glucose Measurement: Time for a Gold Standard

PubMed Central

Hagvik, Joakim

2007-01-01

There is no internationally recognized reference method for the measurement of blood glucose. The Centers for Disease Control and Prevention (CDC) highlighted the need for standardization some years ago when a project was started. The project objectives were to (1) investigate whether there are significant differences in calibration levels among currently used glucose monitors for home use and (2) develop a reference method for glucose determination. A first study confirmed the assumption that currently used home-use monitors differ significantly and that standardization is necessary in order to minimize variability and to improve patient care. As a reference method, CDC recommended a method based on isotope dilution gas chromatography–mass spectrometry, an assay that has received support from clinical chemists worldwide. CDC initiated a preliminary study to establish the suitability of this method, but then the project came to a halt. It is hoped that CDC, with support from the industry, as well as academic and professional organizations such as the American Association for Clinical Chemistry and International Federation of Clinical Chemistry and Laboratory Medicine, will be able to finalize the project and develop the long-awaited and much needed “gold standard” for glucose measurement. PMID:19888402

An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests

ERIC Educational Resources Information Center

Strobl, Carolin; Malley, James; Tutz, Gerhard

2009-01-01

Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and…

[Subcortical laminar heterotopia 'double cortex syndrome'].

PubMed

Teplyshova, A M; Gaskin, V V; Kustov, G V; Gudkova, A A; Luzin, R V; Trifonov, I S; Lebedeva, A V

2017-01-01

This article presents a clinical case of a 29-year-old patient with 'Double cortex syndrome' with epilepsy, intellectual and mental disorders. Subcortical band heterotopia is a rare disorder of neuronal migration. Such patients typically present with epilepsy and variable degrees of mental retardation and behavioral and intellectual disturbances. The main diagnostic method is magnetic resonance imaging (MRI).

The Prediction of Disruptive Behaviour Disorders in an Urban Community Sample: The Contribution of Person-Centred Analyses

ERIC Educational Resources Information Center

Burt, Keith B.; Hay, Dale F.; Pawlby, Susan; Harold, Gordon; Sharp, Deborah

2004-01-01

Background: Variable- and person-centred analyses were used to examine prediction of middle childhood behaviour problems from earlier child and family measures. Method: A community sample of 164 families, initially recruited at antenatal clinics at two South London practices, was assessed for children's behaviour problems and cognitive ability,…

The Behavioural Phenotype of Cornelia de Lange Syndrome: A Study of 56 Individuals

ERIC Educational Resources Information Center

Basile, Emanuele; Villa, L.; Selicorni, A.; Molteni, M.

2007-01-01

Background: Few studies have investigated functional and behavioural variables of Cornelia de Lange Syndrome (CdLS) in a large sample of individuals. The aim of this study is to provide greater insight into the clinical, behavioural and cognitive characteristics that are associated with CdLS. Methods: In total, 56 individuals with CdLS…

Recruitment methods in a clinical trial of provoked vulvodynia: Predictors of enrollment.

PubMed

Bachour, Candi C; Bachmann, Gloria A; Foster, David C; Wan, Jim Y; Rawlinson, Leslie A; Brown, Candace S

2017-02-01

Successful recruitment in clinical trials for chronic pain conditions is challenging, especially in women with provoked vulvodynia due to reluctance in discussing pain associated with sexual intercourse. The most successful recruitment methods and the characteristics of women reached with these methods are unknown. To compare the effectiveness and efficiency of four recruitment methods and to determine socioeconomic predictors for successful enrollment in a National Institutes of Health-sponsored multicenter clinical trial evaluating a gabapentin intervention in women with provoked vulvodynia. Recruitment methods utilized mass mailing, media, clinician referrals and community outreach. Effectiveness (number of participants enrolled) and efficiency (proportion screened who enrolled) were determined. Socioeconomic variables including race, educational level, annual household income, relationship status, age, menopausal status and employment status were also evaluated regarding which recruitment strategies were best at targeting specific cohorts. Of 868 potential study participants, 219 were enrolled. The most effective recruitment method in enrolling participants was mass mailing ( p < 0.001). There were no statistically significant differences in efficiency between recruitment methods ( p = 0.11). Relative to clinician referral, black women were 13 times as likely to be enrolled through mass mailing (adjusted odds ratio 12.5, 95% confidence interval, 3.6-43.1) as white women. There were no differences in enrollment according to educational level, annual income, relationship status, age, menopausal status, or employment status and recruitment method. In this clinical trial, mass mailing was the most effective recruitment method. Race of participants enrolled in a provoked vulvodynia trial was related to the recruitment method.

Pathways from Autism Spectrum Disorder (ASD) Diagnosis to Genetic Testing

PubMed Central

Barton, Krysta S.; Tabor, Holly K.; Starks, Helene; Garrison, Nanibaa’ A.; Laurino, Mercy; Burke, Wylie

2017-01-01

Purpose This study examines challenges faced by families and health providers related to genetic testing for autism spectrum disorder (ASD). Methods This qualitative study of 14 parents and 15 health providers identified an unstandardized three-step process for families who pursue ASD genetic testing. Results Step 1 is the clinical diagnosis of ASD, confirmed by providers practicing alone or in a team. Step 2 is the offer of genetic testing to find an etiology. For those offered testing, step 3 involves the parents’ decision whether to pursue testing. Despite professional guidelines and recommendations, interviews describe considerable variability in approaches to genetic testing for ASD, a lack of consensus among providers, and questions about clinical utility. Many families in our study were unaware of the option for genetic testing; testing decisions by parents appear to be influenced by both provider recommendations and insurance coverage. Conclusion Consideration of genetic testing for ASD should take into account different views about the clinical utility of testing and variability in insurance coverage. Ideally, policy makers from the range of clinical specialties involved in ASD care should revisit policies to clarify the purpose of genetic testing for ASD and promote consensus about its appropriate use. PMID:29048417

Why aren’t they happy? An analysis of end-user satisfaction with Electronic health records

PubMed Central

Unni, Prasad; Staes, Catherine; Weeks, Howard; Kramer, Heidi; Borbolla, Damion; Slager, Stacey; Taft, Teresa; Chidambaram, Valliammai; Weir, Charlene

2016-01-01

Introduction. Implementations of electronic health records (EHR) have been met with mixed outcome reviews. Complaints about these systems have led to many attempts to have useful measures of end-user satisfaction. However, most user satisfaction assessments do not focus on high-level reasoning, despite the complaints of many physicians. Our study attempts to identify some of these determinants. Method. We developed a user satisfaction survey instrument, based on pre-identified and important clinical and non-clinical clinician tasks. We surveyed a sample of in-patient physicians and focused on using exploratory factor analyses to identify underlying high-level cognitive tasks. We used the results to create unique, orthogonal variables representative of latent structure predictive of user satisfaction. Results. Our findings identified 3 latent high-level tasks that were associated with end-user satisfaction: a) High- level clinical reasoning b) Communicate/coordinate care and c) Follow the rules/compliance. Conclusion: We were able to successfully identify latent variables associated with satisfaction. Identification of communicability and high-level clinical reasoning as important factors determining user satisfaction can lead to development and design of more usable electronic health records with higher user satisfaction. PMID:28269962

Comparing four non-invasive methods to determine the ventilatory anaerobic threshold during cardiopulmonary exercise testing in children with congenital heart or lung disease.

PubMed

Visschers, Naomi C A; Hulzebos, Erik H; van Brussel, Marco; Takken, Tim

2015-11-01

The ventilatory anaerobic threshold (VAT) is an important method to assess the aerobic fitness in patients with cardiopulmonary disease. Several methods exist to determine the VAT; however, there is no consensus which of these methods is the most accurate. To compare four different non-invasive methods for the determination of the VAT via respiratory gas exchange analysis during a cardiopulmonary exercise test (CPET). A secondary objective is to determine the interobserver reliability of the VAT. CPET data of 30 children diagnosed with either cystic fibrosis (CF; N = 15) or with a surgically corrected dextro-transposition of the great arteries (asoTGA; N = 15) were included. No significant differences were found between conditions or among testers. The RER = 1 method differed the most compared to the other methods, showing significant higher results in all six variables. The PET-O2 method differed significantly on five of six and four of six exercise variables with the V-slope method and the VentEq method, respectively. The V-slope and the VentEq method differed significantly on one of six exercise variables. Ten of thirteen ICCs that were >0.80 had a 95% CI > 0.70. The RER = 1 method and the V-slope method had the highest number of significant ICCs and 95% CIs. The V-slope method, the ventilatory equivalent method and the PET-O2 method are comparable and reliable methods to determine the VAT during CPET in children with CF or asoTGA. © 2014 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Evidence of an application of a variable MEMS capacitive sensor for detecting shunt occlusions

NASA Astrophysics Data System (ADS)

Apigo, David J.; Bartholomew, Philip L.; Russell, Thomas; Kanwal, Alokik; Farrow, Reginald C.; Thomas, Gordon A.

2017-04-01

A sensor was tested subdural and in vitro, simulating a supine infant with a ventricular-peritoneal shunt and controlled occlusions. The variable MEMS capacitive device is able to detect and forecast blockages, similar to early detection procedures in cancer patients. For example, with gradual occlusion development over a year, the method forecasts a danger over one month ahead of blockage. The method also distinguishes between ventricular and peritoneal occlusions. Because the sensor provides quantitative data on the dynamics of the cerebrospinal fluid, it can help test new therapies and work toward understanding hydrocephalus as well as idiopathic normal pressure hydrocephalus. The sensor appears to be a substantial advance in treating brain injuries treated with shunts and has the potential to bring significant impact in a clinical setting.

Clinical Significance of Mobile Health Assessed Sleep Duration and Variability in Bipolar Disorder

PubMed Central

Kaufmann, Christopher N.; Gershon, Anda; Eyler, Lisa T.; Depp, Colin A.

2016-01-01

OBJECTIVE Sleep disturbances are prevalent, persistent, and impairing features of bipolar disorder. However, the near-term and cumulative impact of the severity and variability of sleep disturbances on symptoms and functioning remains unclear. We examined self-reported daily sleep duration and variability in relation to mood symptoms, medication adherence, cognitive functioning, and concurrent daily affect. METHODS Forty-one outpatients diagnosed with bipolar disorder were asked to provide daily reports of sleep duration and affect collected via ecological momentary assessment with smartphones over eleven weeks. Measures of depressive and manic symptoms, medication adherence, and cognitive function were collected at baseline and concurrent assessment of affect were collected daily. Analyses examined whether sleep duration or variability were associated with baseline measures and changes in same-day or next-day affect. RESULTS Greater sleep duration variability (but not average sleep duration) was associated with greater depressive and manic symptom severity, and lower medication adherence at baseline, and with lower and more variable ratings of positive affect and higher ratings of negative affect. Sleep durations shorter than 7-8 hours were associated with lower same-day ratings of positive and higher same-day ratings of negative affect, however this did not extend to next-day affect. CONCLUSIONS Greater cumulative day-to-day sleep duration variability, but not average sleep duration, was related to more severe mood symptoms, lower self-reported medication adherence and higher levels of negative affect. Bouts of short- or long-duration sleep had transient impact on affect. Day-to-day sleep variability may be important to incorporate into clinical assessment of sleep disturbances in bipolar disorder. PMID:27451108

Estimating verbal fluency and naming ability from the test of premorbid functioning and demographic variables: Regression equations derived from a regional UK sample.

PubMed

Jenkinson, Toni-Marie; Muncer, Steven; Wheeler, Miranda; Brechin, Don; Evans, Stephen

2018-06-01

Neuropsychological assessment requires accurate estimation of an individual's premorbid cognitive abilities. Oral word reading tests, such as the test of premorbid functioning (TOPF), and demographic variables, such as age, sex, and level of education, provide a reasonable indication of premorbid intelligence, but their ability to predict other related cognitive abilities is less well understood. This study aimed to develop regression equations, based on the TOPF and demographic variables, to predict scores on tests of verbal fluency and naming ability. A sample of 119 healthy adults provided demographic information and were tested using the TOPF, FAS, animal naming test (ANT), and graded naming test (GNT). Multiple regression analyses, using the TOPF and demographics as predictor variables, were used to estimate verbal fluency and naming ability test scores. Change scores and cases of significant impairment were calculated for two clinical samples with diagnosed neurological conditions (TBI and meningioma) using the method in Knight, McMahon, Green, and Skeaff (). Demographic variables provided a significant contribution to the prediction of all verbal fluency and naming ability test scores; however, adding TOPF score to the equation considerably improved prediction beyond that afforded by demographic variables alone. The percentage of variance accounted for by demographic variables and/or TOPF score varied from 19 per cent (FAS), 28 per cent (ANT), and 41 per cent (GNT). Change scores revealed significant differences in performance in the clinical groups, particularity the TBI group. Demographic variables, particularly education level, and scores on the TOPF should be taken into consideration when interpreting performance on tests of verbal fluency and naming ability. © 2017 The British Psychological Society.

Psychogenic Tremor: A Video Guide to Its Distinguishing Features

PubMed Central

Thenganatt, Mary Ann; Jankovic, Joseph

2014-01-01

Background Psychogenic tremor is the most common psychogenic movement disorder. It has characteristic clinical features that can help distinguish it from other tremor disorders. There is no diagnostic gold standard and the diagnosis is based primarily on clinical history and examination. Despite proposed diagnostic criteria, the diagnosis of psychogenic tremor can be challenging. While there are numerous studies evaluating psychogenic tremor in the literature, there are no publications that provide a video/visual guide that demonstrate the clinical characteristics of psychogenic tremor. Educating clinicians about psychogenic tremor will hopefully lead to earlier diagnosis and treatment. Methods We selected videos from the database at the Parkinson’s Disease Center and Movement Disorders Clinic at Baylor College of Medicine that illustrate classic findings supporting the diagnosis of psychogenic tremor. Results We include 10 clinical vignettes with accompanying videos that highlight characteristic clinical signs of psychogenic tremor including distractibility, variability, entrainability, suggestibility, and coherence. Discussion Psychogenic tremor should be considered in the differential diagnosis of patients presenting with tremor, particularly if it is of abrupt onset, intermittent, variable and not congruous with organic tremor. The diagnosis of psychogenic tremor, however, should not be simply based on exclusion of organic tremor, such as essential, parkinsonian, or cerebellar tremor, but on positive criteria demonstrating characteristic features. Early recognition and management are critical for good long-term outcome. PMID:25243097

Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data.

PubMed

Schramm, Catherine; Vial, Céline; Bachoud-Lévi, Anne-Catherine; Katsahian, Sandrine

2018-01-01

Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.

Mediators and moderators in early intervention research.

PubMed

Breitborde, Nicholas J K; Srihari, Vinod H; Pollard, Jessica M; Addington, Donald N; Woods, Scott W

2010-05-01

The goal of this paper is to provide clarification with regard to the nature of mediator and moderator variables and the statistical methods used to test for the existence of these variables. Particular attention will be devoted to discussing the ways in which the identification of mediator and moderator variables may help to advance the field of early intervention in psychiatry. We completed a literature review of the methodological strategies used to test for mediator and moderator variables. Although several tests for mediator variables are currently available, recent evaluations suggest that tests which directly evaluate the indirect effect are superior. With regard to moderator variables, two approaches ('pick-a-point' and regions of significance) are available, and we provide guidelines with regard to how researchers can determine which approach may be most appropriate to use for their specific study. Finally, we discuss how to evaluate the clinical importance of mediator and moderator relationships as well as the methodology to calculate statistical power for tests of mediation and moderation. Further exploration of mediator and moderator variables may provide valuable information with regard to interventions provided early in the course of a psychiatric illness.

Improved artificial neural networks in prediction of malignancy of lesions in contrast-enhanced MR-mammography.

PubMed

Vomweg, T W; Buscema, M; Kauczor, H U; Teifke, A; Intraligi, M; Terzi, S; Heussel, C P; Achenbach, T; Rieker, O; Mayer, D; Thelen, M

2003-09-01

The aim of this study was to evaluate the capability of improved artificial neural networks (ANN) and additional novel training methods in distinguishing between benign and malignant breast lesions in contrast-enhanced magnetic resonance-mammography (MRM). A total of 604 histologically proven cases of contrast-enhanced lesions of the female breast at MRI were analyzed. Morphological, dynamic and clinical parameters were collected and stored in a database. The data set was divided into several groups using random or experimental methods [Training & Testing (T&T) algorithm] to train and test different ANNs. An additional novel computer program for input variable selection was applied. Sensitivity and specificity were calculated and compared with a statistical method and an expert radiologist. After optimization of the distribution of cases among the training and testing sets by the T & T algorithm and the reduction of input variables by the Input Selection procedure a highly sophisticated ANN achieved a sensitivity of 93.6% and a specificity of 91.9% in predicting malignancy of lesions within an independent prediction sample set. The best statistical method reached a sensitivity of 90.5% and a specificity of 68.9%. An expert radiologist performed better than the statistical method but worse than the ANN (sensitivity 92.1%, specificity 85.6%). Features extracted out of dynamic contrast-enhanced MRM and additional clinical data can be successfully analyzed by advanced ANNs. The quality of the resulting network strongly depends on the training methods, which are improved by the use of novel training tools. The best results of an improved ANN outperform expert radiologists.

Correlations between Clinical Judgement and Learning Style Preferences of Nursing Students in the Simulation Room

PubMed Central

Hallin, Karin; Häggström, Marie; Bäckström, Britt; Kristiansen, Lisbeth Porskrog

2016-01-01

Background: Health care educators account for variables affecting patient safety and are responsible for developing the highly complex process of education planning. Clinical judgement is a multidimensional process, which may be affected by learning styles. The aim was to explore three specific hypotheses to test correlations between nursing students’ team achievements in clinical judgement and emotional, sociological and physiological learning style preferences. Methods: A descriptive cross-sectional study was conducted with Swedish university nursing students in 2012-2013. Convenience sampling was used with 60 teams with 173 nursing students in the final semester of a three-year Bachelor of Science in nursing programme. Data collection included questionnaires of personal characteristics, learning style preferences, determined by the Dunn and Dunn Productivity Environmental Preference Survey, and videotaped complex nursing simulation scenarios. Comparison with Lasater Clinical Judgement Rubric and Non-parametric analyses were performed. Results: Three significant correlations were found between the team achievements and the students’ learning style preferences: significant negative correlation with ‘Structure’ and ‘Kinesthetic’ at the individual level, and positive correlation with the ‘Tactile’ variable. No significant correlations with students’ ‘Motivation’, ‘Persistence’, ‘Wish to learn alone’ and ‘Wish for an authoritative person present’ were seen. Discussion and Conclusion: There were multiple complex interactions between the tested learning style preferences and the team achievements of clinical judgement in the simulation room, which provides important information for the becoming nurses. Several factors may have influenced the results that should be acknowledged when designing further research. We suggest conducting mixed methods to determine further relationships between team achievements, learning style preferences, cognitive learning outcomes and group processes. PMID:26755461

Variability in adherence to clinical practice guidelines and recommendations in COPD outpatients: a multi-level, cross-sectional analysis of the EPOCONSUL study.

PubMed

Calle Rubio, Myriam; López-Campos, José Luis; Soler-Cataluña, Juan J; Alcázar Navarrete, Bernardino; Soriano, Joan B; Rodríguez González-Moro, José Miguel; Fuentes Ferrer, Manuel E; Rodríguez Hermosa, Juan Luis

2017-12-02

Clinical audits have reported considerable variability in COPD medical care and frequent inconsistencies with recommendations. The objectives of this study were to identify factors associated with a better adherence to clinical practice guidelines and to explore determinants of this variability at the the hospital level. EPOCONSUL is a Spanish nationwide clinical audit that evaluates the outpatient management of COPD. Multilevel logistic regression with two levels was performed to assess the relationships between individual and disease-related factors, as well as hospital characteristics. A total of 4508 clinical records of COPD patients from 59 Spanish hospitals were evaluated. High variability was observed among hospitals in terms of medical care. Some of the patient's characteristics (airflow obstruction, degree of dyspnea, exacerbation risk, presence of comorbidities), the hospital factors (size and respiratory nurses available) and treatment at a specialized COPD outpatient clinic were identified as factors associated with a better adherence to recommendations, although this only explains a small proportion of the total variance. To be treated at a specialized COPD outpatient clinic and some intrinsic patient characteristics were factors associated with a better adherence to guideline recommendations, although these variables were only explaining part of the high variability observed among hospitals in terms of COPD medical care.

T-wave alternans and beat-to-beat variability of repolarization: pathophysiological backgrounds and clinical relevance.

PubMed

Floré, Vincent; Willems, Rik

2012-12-01

In this review, we focus on temporal variability of cardiac repolarization. This phenomenon has been related to a higher risk for ventricular arrhythmia and is therefore interesting as a marker of sudden cardiac death risk. We review two non-invasive clinical techniques quantifying repolarization variability: T-wave alternans (TWA) and beat-to-beat variability of repolarization (BVR). We discuss their pathophysiological link with ventricular arrhythmia and the current clinical relevance of these techniques.

Inter-laboratory agreement on embryo classification and clinical decision: Conventional morphological assessment vs. time lapse.

PubMed

Martínez-Granados, Luis; Serrano, María; González-Utor, Antonio; Ortíz, Nereyda; Badajoz, Vicente; Olaya, Enrique; Prados, Nicolás; Boada, Montse; Castilla, Jose A

2017-01-01

The aim of this study is to determine inter-laboratory variability on embryo assessment using time-lapse platform and conventional morphological assessment. This study compares the data obtained from a pilot study of external quality control (EQC) of time lapse, performed in 2014, with the classical EQC of the Spanish Society for the Study of Reproductive Biology (ASEBIR) performed in 2013 and 2014. In total, 24 laboratories (8 using EmbryoScope™, 15 using Primo Vision™ and one with both platforms) took part in the pilot study. The clinics that used EmbryoScope™ analysed 31 embryos and those using Primo Vision™ analysed 35. The classical EQC was implemented by 39 clinics, based on an analysis of 25 embryos per year. Both groups were required to evaluate various qualitative morphological variables (cell fragmentation, the presence of vacuoles, blastomere asymmetry and multinucleation), to classify the embryos in accordance with ASEBIR criteria and to stipulate the clinical decision taken. In the EQC time-lapse pilot study, the groups were asked to determine, as well as the above characteristics, the embryo development times, the number, opposition and size of pronuclei, the direct division of 1 into 3 cells and/or of 3 into 5 cells and false divisions. The degree of agreement was determined by calculating the intra-class correlation coefficients and the coefficient of variation for the quantitative variables and the Gwet index for the qualitative variables. For both EmbryoScope™ and Primo Vision™, two periods of greater inter-laboratory variability were observed in the times of embryo development events. One peak of variability was recorded among the laboratories addressing the first embryo events (extrusion of the second polar body and the appearance of pronuclei); the second peak took place between the times corresponding to the 8-cell and morula stages. In most of the qualitative variables analysed regarding embryo development, there was almost-perfect inter-laboratory agreement among conventional morphological assessment (CMA), EmbryoScope™ and Primo Vision™, except for false divisions, vacuoles and asymmetry (users of all methods) and multinucleation (users of Primo Vision™), where the degree of agreement was lower. The inter-laboratory agreement on embryo classification according to the ASEBIR criteria was moderate-substantial (Gwet 0.41-0.80) for the laboratories using CMA and EmbryoScope™, and fair-moderate (Gwet 0.21-0.60) for those using Primo Vision™. The inter-laboratory agreement for clinical decision was moderate (Gwet 0.41-0.60) on day 5 for CMA users and almost perfect (Gwet 0.81-1) for time-lapse users. In conclusion, time-lapse technology does not improve inter-laboratory agreement on embryo classification or the analysis of each morphological variable. Moreover, depending on the time-lapse platform used, inter-laboratory agreement may be lower than that obtained by CMA. However, inter-laboratory agreement on clinical decisions is improved with the use of time lapse, regardless of the platform used.

Inter-laboratory agreement on embryo classification and clinical decision: Conventional morphological assessment vs. time lapse

PubMed Central

Serrano, María; González-Utor, Antonio; Ortíz, Nereyda; Badajoz, Vicente; Olaya, Enrique; Prados, Nicolás; Boada, Montse; Castilla, Jose A.

2017-01-01

The aim of this study is to determine inter-laboratory variability on embryo assessment using time-lapse platform and conventional morphological assessment. This study compares the data obtained from a pilot study of external quality control (EQC) of time lapse, performed in 2014, with the classical EQC of the Spanish Society for the Study of Reproductive Biology (ASEBIR) performed in 2013 and 2014. In total, 24 laboratories (8 using EmbryoScope™, 15 using Primo Vision™ and one with both platforms) took part in the pilot study. The clinics that used EmbryoScope™ analysed 31 embryos and those using Primo Vision™ analysed 35. The classical EQC was implemented by 39 clinics, based on an analysis of 25 embryos per year. Both groups were required to evaluate various qualitative morphological variables (cell fragmentation, the presence of vacuoles, blastomere asymmetry and multinucleation), to classify the embryos in accordance with ASEBIR criteria and to stipulate the clinical decision taken. In the EQC time-lapse pilot study, the groups were asked to determine, as well as the above characteristics, the embryo development times, the number, opposition and size of pronuclei, the direct division of 1 into 3 cells and/or of 3 into 5 cells and false divisions. The degree of agreement was determined by calculating the intra-class correlation coefficients and the coefficient of variation for the quantitative variables and the Gwet index for the qualitative variables. For both EmbryoScope™ and Primo Vision™, two periods of greater inter-laboratory variability were observed in the times of embryo development events. One peak of variability was recorded among the laboratories addressing the first embryo events (extrusion of the second polar body and the appearance of pronuclei); the second peak took place between the times corresponding to the 8-cell and morula stages. In most of the qualitative variables analysed regarding embryo development, there was almost-perfect inter-laboratory agreement among conventional morphological assessment (CMA), EmbryoScope™ and Primo Vision™, except for false divisions, vacuoles and asymmetry (users of all methods) and multinucleation (users of Primo Vision™), where the degree of agreement was lower. The inter-laboratory agreement on embryo classification according to the ASEBIR criteria was moderate-substantial (Gwet 0.41–0.80) for the laboratories using CMA and EmbryoScope™, and fair-moderate (Gwet 0.21–0.60) for those using Primo Vision™. The inter-laboratory agreement for clinical decision was moderate (Gwet 0.41–0.60) on day 5 for CMA users and almost perfect (Gwet 0.81–1) for time-lapse users. In conclusion, time-lapse technology does not improve inter-laboratory agreement on embryo classification or the analysis of each morphological variable. Moreover, depending on the time-lapse platform used, inter-laboratory agreement may be lower than that obtained by CMA. However, inter-laboratory agreement on clinical decisions is improved with the use of time lapse, regardless of the platform used. PMID:28841654

Genomic Methods for Clinical and Translational Pain Research

PubMed Central

Wang, Dan; Kim, Hyungsuk; Wang, Xiao-Min; Dionne, Raymond

2012-01-01

Pain is a complex sensory experience for which the molecular mechanisms are yet to be fully elucidated. Individual differences in pain sensitivity are mediated by a complex network of multiple gene polymorphisms, physiological and psychological processes, and environmental factors. Here, we present the methods for applying unbiased molecular-genetic approaches, genome-wide association study (GWAS), and global gene expression analysis, to help better understand the molecular basis of pain sensitivity in humans and variable responses to analgesic drugs. PMID:22351080

Quantitative topographic differentiation of the neonatal EEG.

PubMed

Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

2006-09-01

To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'. 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis. All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG. The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision. The discriminatory capability of the used method represents a promise for their application in the clinical practice.

A Bayesian prediction model between a biomarker and the clinical endpoint for dichotomous variables.

PubMed

Jiang, Zhiwei; Song, Yang; Shou, Qiong; Xia, Jielai; Wang, William

2014-12-20

Early biomarkers are helpful for predicting clinical endpoints and for evaluating efficacy in clinical trials even if the biomarker cannot replace clinical outcome as a surrogate. The building and evaluation of an association model between biomarkers and clinical outcomes are two equally important concerns regarding the prediction of clinical outcome. This paper is to address both issues in a Bayesian framework. A Bayesian meta-analytic approach is proposed to build a prediction model between the biomarker and clinical endpoint for dichotomous variables. Compared with other Bayesian methods, the proposed model only requires trial-level summary data of historical trials in model building. By using extensive simulations, we evaluate the link function and the application condition of the proposed Bayesian model under scenario (i) equal positive predictive value (PPV) and negative predictive value (NPV) and (ii) higher NPV and lower PPV. In the simulations, the patient-level data is generated to evaluate the meta-analytic model. PPV and NPV are employed to describe the patient-level relationship between the biomarker and the clinical outcome. The minimum number of historical trials to be included in building the model is also considered. It is seen from the simulations that the logit link function performs better than the odds and cloglog functions under both scenarios. PPV/NPV ≥0.5 for equal PPV and NPV, and PPV + NPV ≥1 for higher NPV and lower PPV are proposed in order to predict clinical outcome accurately and precisely when the proposed model is considered. Twenty historical trials are required to be included in model building when PPV and NPV are equal. For unequal PPV and NPV, the minimum number of historical trials for model building is proposed to be five. A hypothetical example shows an application of the proposed model in global drug development. The proposed Bayesian model is able to predict well the clinical endpoint from the observed biomarker data for dichotomous variables as long as the conditions are satisfied. It could be applied in drug development. But the practical problems in applications have to be studied in further research.

Clinical and Serological Predictors of Suicide in Schizophrenia and Major Mood Disorders.

PubMed

Dickerson, Faith; Origoni, Andrea; Schweinfurth, Lucy A B; Stallings, Cassie; Savage, Christina L G; Sweeney, Kevin; Katsafanas, Emily; Wilcox, Holly C; Khushalani, Sunil; Yolken, Robert

2018-03-01

Persons with serious mental illness are at high risk for suicide, but this outcome is difficult to predict. Serological markers may help to identify suicide risk. We prospectively assessed 733 persons with a schizophrenia spectrum disorder, 483 with bipolar disorder, and 76 with major depressive disorder for an average of 8.15 years. The initial evaluation consisted of clinical and demographic data as well as a blood samples from which immunoglobulin G antibodies to herpes viruses and Toxoplasma gondii were measured. Suicide was determined using data from the National Death Index. Cox proportional hazard regression models examined the role of baseline variables on suicide outcomes. Suicide was associated with male sex, divorced/separated status, Caucasian race, and elevated levels of antibodies to Cytomegalovirus (CMV). Increasing levels of CMV antibodies were associated with increasing hazard ratios for suicide. The identification of serological variables associated with suicide might provide more personalized methods for suicide prevention.

An examination of generalized anxiety disorder and dysthymia utilizing the Rorschach inkblot method.

PubMed

Slavin-Mulford, Jenelle; Clements, Alyssa; Hilsenroth, Mark; Charnas, Jocelyn; Zodan, Jennifer

2016-06-30

This study examined transdiagnostic features of generalized anxiety disorder (GAD) and dysthymia in an outpatient clinical sample. Fifteen patients who met DSM-IV criteria for GAD and twenty-one patients who met DSM-IV criteria for dysthymia but who did not have comorbid anxiety disorder were evaluated utilizing the Rorschach. Salient clinical variables were then compared. Results showed that patients with GAD scored significantly higher on variables related to cognitive agitation and a desire/need for external soothing. In addition, there was a trend for patients with GAD to produce higher scores on a measure of ruminative focus on negative aspects of the self. Thus, not surprisingly, GAD patients' experienced more distress than the dysthymic patients. The implications of these findings are discussed with regards to better understanding the shared and distinct features of GAD and dysthymia. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Do Children and Adolescents with Anorexia Nervosa Display an Inefficient Cognitive Processing Style?

PubMed Central

Lang, Katie; Lloyd, Samantha; Khondoker, Mizanur; Simic, Mima; Treasure, Janet; Tchanturia, Kate

2015-01-01

Objective This study aimed to examine neuropsychological processing in children and adolescents with Anorexia Nervosa (AN). The relationship of clinical and demographic variables to neuropsychological functioning within the AN group was also explored. Method The performance of 41 children and adolescents with a diagnosis of AN were compared to 43 healthy control (HC) participants on a number of neuropsychological measures. Results There were no differences in IQ between AN and HC groups. However, children and adolescents with AN displayed significantly more perseverative errors on the Wisconsin Card Sorting Test, and lower Style and Central Coherence scores on the Rey Osterrieth Complex Figure Test relative to HCs. Conclusion Inefficient cognitive processing in the AN group was independent of clinical and demographic variables, suggesting it might represent an underlying trait for AN. The implications of these findings are discussed. PMID:26133552

Nursing students' satisfaction about their field of study.

PubMed

Hakim, Ashrafalsadat

2014-04-01

Nowadays students' opinion is considered as a necessary factor to evaluate quality in universities. This study was performed to evaluate the nursing students' satisfaction about their field of study. The research population in this study consists of all the students of nursing studying at the second to fourth year of university (72 students). The data were collected from all the studied population. Data collection instrument was a research questionnaire. In this cross-sectional research, nursing students' satisfaction (72 students) in 6 major topics (situation of educational environment, situation of clinical environment, trainers, social image, relation to colleagues and management) was studied. The data were analyzed in SPSS, version 14, using quantitative variables and descriptive statistics including frequency distribution tables and diagrams. The findings indicated that 83.3% of the students had little satisfaction as to the situation of educational environment, 47.2% about situation of clinical environment, 41.7% concerning the theoretical educational method by professors, and 41.7% as to the method of clinical education by clinical trainers. Also 47.2% were not that satisfied with the method of evaluation by the school professors, 80.6% with the method of relationship with colleagues and also 62.5% with the nursing social image. Moreover, findings indicated that 33.3% of the participants in this research were dissatisfied with the method of evaluation by clinical trainers and 50% with the method of nursing management. In the present study, most students had little satisfaction concerning their field of study. So it is necessary to make an attempt for continuous development of quality services.

Power calculator for instrumental variable analysis in pharmacoepidemiology

PubMed Central

Walker, Venexia M; Davies, Neil M; Windmeijer, Frank; Burgess, Stephen; Martin, Richard M

2017-01-01

Abstract Background Instrumental variable analysis, for example with physicians’ prescribing preferences as an instrument for medications issued in primary care, is an increasingly popular method in the field of pharmacoepidemiology. Existing power calculators for studies using instrumental variable analysis, such as Mendelian randomization power calculators, do not allow for the structure of research questions in this field. This is because the analysis in pharmacoepidemiology will typically have stronger instruments and detect larger causal effects than in other fields. Consequently, there is a need for dedicated power calculators for pharmacoepidemiological research. Methods and Results The formula for calculating the power of a study using instrumental variable analysis in the context of pharmacoepidemiology is derived before being validated by a simulation study. The formula is applicable for studies using a single binary instrument to analyse the causal effect of a binary exposure on a continuous outcome. An online calculator, as well as packages in both R and Stata, are provided for the implementation of the formula by others. Conclusions The statistical power of instrumental variable analysis in pharmacoepidemiological studies to detect a clinically meaningful treatment effect is an important consideration. Research questions in this field have distinct structures that must be accounted for when calculating power. The formula presented differs from existing instrumental variable power formulae due to its parametrization, which is designed specifically for ease of use by pharmacoepidemiologists. PMID:28575313

Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

PubMed Central

Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

2016-01-01

In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration (High Freq) performed similarly to non-parametric methods, but had the highest recall values, suggesting that this method could be employed for automatic tremor detection. PMID:27258018

On assessing the quality of physicians' clinical judgment: the search for outcome variables.

PubMed

Wainer, Howard; Mee, Janet

2004-12-01

A primary question that must be resolved in the development of tasks to assess the quality of physicians' clinical judgment is, "What is the outcome variable?" One natural choice would seem to be the correctness of the clinical decision. In this article, we use data on the diagnosis of urinary tract infections among young girls to illustrate why, in many clinical situations, this is not a useful variable. We propose instead a judgment weighted by the relative costs of an error. This variable has the disadvantage of requiring expert judgment for scoring, but the advantage of measuring the construct of interest.

The Relationship Between Executive Functions and Language Abilities in Children: A Latent Variables Approach.

PubMed

Kaushanskaya, Margarita; Park, Ji Sook; Gangopadhyay, Ishanti; Davidson, Meghan M; Weismer, Susan Ellis

2017-04-14

We aimed to outline the latent variables approach for measuring nonverbal executive function (EF) skills in school-age children, and to examine the relationship between nonverbal EF skills and language performance in this age group. Seventy-one typically developing children, ages 8 through 11, participated in the study. Three EF components, inhibition, updating, and task-shifting, were each indexed using 2 nonverbal tasks. A latent variables approach was used to extract latent scores that represented each EF construct. Children were also administered common standardized language measures. Multiple regression analyses were conducted to examine the relationship between EF and language skills. Nonverbal updating was associated with the Receptive Language Index on the Clinical Evaluation of Language Fundamentals-Fourth Edition (CELF-4). When composites denoting lexical-semantic and syntactic abilities were derived, nonverbal inhibition (but not shifting or updating) was found to predict children's syntactic abilities. These relationships held when the effects of age, IQ, and socioeconomic status were controlled. The study makes a methodological contribution by explicating a method by which researchers can use the latent variables approach when measuring EF performance in school-age children. The study makes a theoretical and a clinical contribution by suggesting that language performance may be related to domain-general EFs.

Clinical evaluation of a chemomechanical method for caries removal in children and adolescents.

PubMed

Peric, Tamara; Markovic, Dejan; Petrovic, Bojan

2009-01-01

The purpose of this study was to make a clinical comparison of the chemomechanical method for caries removal and the conventional rotary instruments technique when used in children and adolescents. The study comprised 120 patients aged 3-17 years randomized into two groups: caries were removed chemomechanically in 60 patients and 60 patients received conventional treatment with rotary instruments. The outcome variables were: clinically complete caries removal, pain during caries removal, need for local anesthesia, treatment time, preferences of patients, and clinical success of the restorations during the 12-month evaluation period. Complete caries removal was achieved in 92% of chemomechanically treated teeth and in all teeth treated with rotary instruments (p>0.05). The chemomechanical method significantly reduced the need for local anesthesia (p<0.001). Eighty-five percent of patients treated with Carisolv and 47% treated with rotary instruments were satisfied with the treatment (p<0.05). The mean time for chemomechanical caries removal was 11.2 ± 3.3 min and 5.2 ± 2.8 min for caries removal with rotary instruments (p<0.001). At the end of the 12-month evaluation period, there was no observed influence of the caries removal method on the survival of the restorations. The chemomechanical caries removal technique is an adequate alternative to the conventional rotary instruments method and is advantageous in pediatric dentistry.

Identifying and Assessing Interesting Subgroups in a Heterogeneous Population.

PubMed

Lee, Woojoo; Alexeyenko, Andrey; Pernemalm, Maria; Guegan, Justine; Dessen, Philippe; Lazar, Vladimir; Lehtiö, Janne; Pawitan, Yudi

2015-01-01

Biological heterogeneity is common in many diseases and it is often the reason for therapeutic failures. Thus, there is great interest in classifying a disease into subtypes that have clinical significance in terms of prognosis or therapy response. One of the most popular methods to uncover unrecognized subtypes is cluster analysis. However, classical clustering methods such as k-means clustering or hierarchical clustering are not guaranteed to produce clinically interesting subtypes. This could be because the main statistical variability--the basis of cluster generation--is dominated by genes not associated with the clinical phenotype of interest. Furthermore, a strong prognostic factor might be relevant for a certain subgroup but not for the whole population; thus an analysis of the whole sample may not reveal this prognostic factor. To address these problems we investigate methods to identify and assess clinically interesting subgroups in a heterogeneous population. The identification step uses a clustering algorithm and to assess significance we use a false discovery rate- (FDR-) based measure. Under the heterogeneity condition the standard FDR estimate is shown to overestimate the true FDR value, but this is remedied by an improved FDR estimation procedure. As illustrations, two real data examples from gene expression studies of lung cancer are provided.

Non-invasive assessment of liver fibrosis

PubMed Central

Papastergiou, Vasilios; Tsochatzis, Emmanuel; Burroughs, Andrew K.

2012-01-01

The presence and degree of hepatic fibrosis is crucial in order to make therapeutic decisions and predict clinical outcomes. Currently, the place of liver biopsy as the standard of reference for assessing liver fibrosis has been challenged by the increasing awareness of a number of drawbacks related to its use (invasiveness, sampling error, inter-/intraobserver variability). In parallel with this, noninvasive assessment of liver fibrosis has experienced explosive growth in recent years and a wide spectrum of noninvasive methods ranging from serum assays to imaging techniques have been developed. Some are validated methods, such as the Fibrotest/ Fibrosure and transient elastography in Europe, and are gaining a growing role in routine clinical practice, especially in chronic hepatitis C. Large-scale validation is awaited in the setting of other chronic liver diseases. However, noninvasive tests used to detect significant fibrosis and cirrhosis, the two major clinical endpoints, are not yet at a level of performance suitable for routine diagnostic tests, and there is still no perfect surrogate or method able to completely replace an optimal liver biopsy. This article aims to review current noninvasive tests for the assessment of liver fibrosis and the perspectives for their rational use in clinical practice. PMID:24714123

Review and classification of variability analysis techniques with clinical applications.

PubMed

Bravi, Andrea; Longtin, André; Seely, Andrew J E

2011-10-10

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

Review and classification of variability analysis techniques with clinical applications

PubMed Central

2011-01-01

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis. PMID:21985357

The effect of alternative clinical teaching experience on preservice science teachers' self-efficacy

NASA Astrophysics Data System (ADS)

Klett, Mitchell Dean

The purpose of this study was to compare different methods of alternative clinical experience; family science nights and Saturday science (authentic teaching) against micro-teaching (peer teaching) in terms of self-efficacy in science teaching and teaching self-efficacy. The independent variable, or cause, is teaching experiences (clinical vs. peer teaching); the dependent variable, or effect, is two levels of self-efficacy. This study was conducted at the University of Idaho's main campus in Moscow and extension campus in Coeur d'Alene. Four sections of science methods were exposed to the same science methods curriculum and will have opportunities to teach. However, each of the four sections were exposed to different levels or types of clinical experience. One section of preservice teachers worked with students in a Saturday science program. Another section worked with students during family science nights. The third worked with children at both the Saturday science program and family science nights. The last section did not have a clinical experience with children, instead they taught in their peer groups and acted as a control group. A pre-test was given at the beginning of the semester to measure their content knowledge, teaching self-efficacy and self-efficacy in science teaching. A post-test was given at the end of the semester to see if there was any change in self-efficacy or science teaching self-efficacy. Throughout the semester participants kept journals about their experiences and were interviewed after their alternative clinical teaching experiences. These responses were categorized into three groups; gains in efficacy, no change in efficacy, and drop in efficacy. There was a rise in teaching efficacy for all groups. The mean scores for personal teaching efficacy dropped for the Monday-Wednesday and Tuesday-Thursday group while the both Coeur D'Alene groups remained nearly unchanged. There was no significant change in the overall means for science teaching efficacy for any of the groups. Finally, the mean scores for all groups dropped for personal science teaching efficacy.

Clinical peripherality: development of a peripherality index for rural health services

PubMed Central

Swan, Gillian M; Selvaraj, Sivasubramaniam; Godden, David J

2008-01-01

Background The configuration of rural health services is influenced by geography. Rural health practitioners provide a broader range of services to smaller populations scattered over wider areas or more difficult terrain than their urban counterparts. This has implications for training and quality assurance of outcomes. This exploratory study describes the development of a "clinical peripherality" indicator that has potential application to remote and rural general practice communities for planning and research purposes. Methods Profiles of general practice communities in Scotland were created from a variety of public data sources. Four candidate variables were chosen that described demographic and geographic characteristics of each practice: population density, number of patients on the practice list, travel time to nearest specialist led hospital and travel time to Health Board administrative headquarters. A clinical peripherality index, based on these variables, was derived using factor analysis. Relationships between the clinical peripherality index and services offered by the practices and the staff profile of the practices were explored in a series of univariate analyses. Results Factor analysis on the four candidate variables yielded a robust one-factor solution explaining 75% variance with factor loadings ranging from 0.83 to 0.89. Rural and remote areas had higher median values and a greater scatter of clinical peripherality indices among their practices than an urban comparison area. The range of services offered and the profile of staffing of practices was associated with the peripherality index. Conclusion Clinical peripherality is determined by the nature of the practice and its location relative to secondary care and administrative and educational facilities. It has features of both gravity model-based and travel time/accessibility indicators and has the potential to be applied to training of staff for rural and remote locations and to other aspects of health policy and planning. It may assist planners in conceptualising the effects on general practices of centralising specialist clinical services or administrative and educational facilities. PMID:18221533

How to regress and predict in a Bland-Altman plot? Review and contribution based on tolerance intervals and correlated-errors-in-variables models.

PubMed

Francq, Bernard G; Govaerts, Bernadette

2016-06-30

Two main methodologies for assessing equivalence in method-comparison studies are presented separately in the literature. The first one is the well-known and widely applied Bland-Altman approach with its agreement intervals, where two methods are considered interchangeable if their differences are not clinically significant. The second approach is based on errors-in-variables regression in a classical (X,Y) plot and focuses on confidence intervals, whereby two methods are considered equivalent when providing similar measures notwithstanding the random measurement errors. This paper reconciles these two methodologies and shows their similarities and differences using both real data and simulations. A new consistent correlated-errors-in-variables regression is introduced as the errors are shown to be correlated in the Bland-Altman plot. Indeed, the coverage probabilities collapse and the biases soar when this correlation is ignored. Novel tolerance intervals are compared with agreement intervals with or without replicated data, and novel predictive intervals are introduced to predict a single measure in an (X,Y) plot or in a Bland-Atman plot with excellent coverage probabilities. We conclude that the (correlated)-errors-in-variables regressions should not be avoided in method comparison studies, although the Bland-Altman approach is usually applied to avert their complexity. We argue that tolerance or predictive intervals are better alternatives than agreement intervals, and we provide guidelines for practitioners regarding method comparison studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Influence of Body Mass Index and Albumin on Perioperative Morbidity and Clinical Outcomes in Resected Pancreatic Adenocarcinoma

PubMed Central

Hendifar, Andrew; Osipov, Arsen; Khanuja, Jasleen; Nissen, Nicholas; Naziri, Jason; Yang, Wensha; Li, Quanlin; Tuli, Richard

2016-01-01

Obesity is a known risk factor for PDA and recent reports suggest obesity has a negative impact on clinical outcomes in patients with PDA. Pretreatment body mass index (BMI) and serum albumin (SA) have been shown to be associated with worse overall survival in patients with advanced and metastatic PDA. However, minimal data exists on the impact of BMI and SA on perioperative and long-term clinical outcomes in patients with early-stage resected PDA. Herein, we report on the impact of these variables on perioperative clinical outcomes, overall survival (OS) and disease free survival (DFS) in patients with resected PDA. With IRB approval, we evaluated 1,545 patients with PDA treated at a single institution from 2007–2013 and identified 106 patients who underwent upfront resection with curative intent. BMI and SA were calculated preoperatively and at the time of last clinical evaluation. Influence of preoperative BMI, SA, change in either variable, and influence of other clinical and pathologic variables on perioperative morbidity and mortality was assessed. The impact of these variables on DFS and OS was assessed with cox regression modeling and ANOVA. Actuarial estimates for DFS and OS were calculated using Kaplan-Meier methods. Median follow up time was 16 months (3–89). Mean age was 68 years. Median survival was 14 months (3–65) and median time to recurrence was 11 months (1–79). Length of hospital stay was associated with BMI (p = .023), change in BMI (p = .003) and SA (p = .004). Post-operative transfusion rate was associated with SA (p = .021). There was a strong correlation between BMI change and positive margin (p = .04) and lymph node status (p = .01). On multivariate analysis, change in SA (p = .03) and node positivity (p = .008) were associated with decreased DFS. Additionally, preoperative SA (p = .023), node positivity (p = .026) and poor differentiation (p = .045) were associated with worse OS on multivariate analysis. Low preoperative SA was associated with worse DFS and OS in patients with resected PDA. Lower BMI and SA were associated with longer post-operative hospital stay. Our study is one of the first to describe how pre-operative BMI and SA and post-operative changes in these variables impact clinical and perioperative outcomes. This data supports nutritional status and weight loss as predictors of outcome in resected pancreatic cancer patients and warrants further prospective investigation. PMID:27015568

Influence of Body Mass Index and Albumin on Perioperative Morbidity and Clinical Outcomes in Resected Pancreatic Adenocarcinoma.

PubMed

Hendifar, Andrew; Osipov, Arsen; Khanuja, Jasleen; Nissen, Nicholas; Naziri, Jason; Yang, Wensha; Li, Quanlin; Tuli, Richard

2016-01-01

Obesity is a known risk factor for PDA and recent reports suggest obesity has a negative impact on clinical outcomes in patients with PDA. Pretreatment body mass index (BMI) and serum albumin (SA) have been shown to be associated with worse overall survival in patients with advanced and metastatic PDA. However, minimal data exists on the impact of BMI and SA on perioperative and long-term clinical outcomes in patients with early-stage resected PDA. Herein, we report on the impact of these variables on perioperative clinical outcomes, overall survival (OS) and disease free survival (DFS) in patients with resected PDA. With IRB approval, we evaluated 1,545 patients with PDA treated at a single institution from 2007-2013 and identified 106 patients who underwent upfront resection with curative intent. BMI and SA were calculated preoperatively and at the time of last clinical evaluation. Influence of preoperative BMI, SA, change in either variable, and influence of other clinical and pathologic variables on perioperative morbidity and mortality was assessed. The impact of these variables on DFS and OS was assessed with cox regression modeling and ANOVA. Actuarial estimates for DFS and OS were calculated using Kaplan-Meier methods. Median follow up time was 16 months (3-89). Mean age was 68 years. Median survival was 14 months (3-65) and median time to recurrence was 11 months (1-79). Length of hospital stay was associated with BMI (p = .023), change in BMI (p = .003) and SA (p = .004). Post-operative transfusion rate was associated with SA (p = .021). There was a strong correlation between BMI change and positive margin (p = .04) and lymph node status (p = .01). On multivariate analysis, change in SA (p = .03) and node positivity (p = .008) were associated with decreased DFS. Additionally, preoperative SA (p = .023), node positivity (p = .026) and poor differentiation (p = .045) were associated with worse OS on multivariate analysis. Low preoperative SA was associated with worse DFS and OS in patients with resected PDA. Lower BMI and SA were associated with longer post-operative hospital stay. Our study is one of the first to describe how pre-operative BMI and SA and post-operative changes in these variables impact clinical and perioperative outcomes. This data supports nutritional status and weight loss as predictors of outcome in resected pancreatic cancer patients and warrants further prospective investigation.

Birth Control in Clinical Trials: Industry Survey of Current Use Practices, Governance, and Monitoring.

PubMed

Stewart, J; Breslin, W J; Beyer, B K; Chadwick, K; De Schaepdrijver, L; Desai, M; Enright, B; Foster, W; Hui, J Y; Moffat, G J; Tornesi, B; Van Malderen, K; Wiesner, L; Chen, C L

2016-03-01

The Health and Environmental Sciences Institute (HESI) Developmental and Reproductive Toxicology Technical Committee sponsored a pharmaceutical industry survey on current industry practices for contraception use during clinical trials. The objectives of the survey were to improve our understanding of the current industry practices for contraception requirements in clinical trials, the governance processes set up to promote consistency and/or compliance with contraception requirements, and the effectiveness of current contraception practices in preventing pregnancies during clinical trials. Opportunities for improvements in current practices were also considered. The survey results from 12 pharmaceutical companies identified significant variability among companies with regard to contraception practices and governance during clinical trials. This variability was due primarily to differences in definitions, areas of scientific uncertainty or misunderstanding, and differences in company approaches to enrollment in clinical trials. The survey also revealed that few companies collected data in a manner that would allow a retrospective understanding of the reasons for failure of birth control during clinical trials. In this article, suggestions are made for topics where regulatory guidance or scientific publications could facilitate best practice. These include provisions for a pragmatic definition of women of childbearing potential, guidance on how animal data can influence the requirements for male and female birth control, evidence-based guidance on birth control and pregnancy testing regimes suitable for low- and high-risk situations, plus practical methods to ascertain the risk of drug-drug interactions with hormonal contraceptives.

[Pulmonary involvement in connective tissue disease].

PubMed

Bartosiewicz, Małgorzata

2016-01-01

The connective tissue diseases are a variable group of autoimmune mediated disorders characterized by multiorgan damage. Pulmonary complications are common, usually occur after the onset of joint symptoms, but can also be initially presenting complaint. The respiratory system may be involved in all its component: airways, vessels, parenchyma, pleura and respiratory muscles. Lung involvement is an increasing cause of morbidity and mortality in the connective tissue diseases. Clinical course is highly variable - can range from mild to rapidly progressive, some processes are reversible, while others are irreversible. Thus, the identification of reversible disease , and separately progressive disease, are important clinical issues. The frequency, clinical presentation, prognosis and responce to therapy are different, depending on the pattern of involvement as well as on specyfic diagnostic method used to identify it. High- resolution computed tompography plays an important role in identifying patients with respiratory involvement. Pulmonary function tests are a sensitive tool detecting interstitial lung disease. In this article, pulmonary lung involvement accompanying most frequently apperaing connective tissue diseases - rheumatoid arthritis, systemic sclerosis, lupus erythematosus, polymyositis/dermatomyositis, Sjögrens syndrome and mixed connective tissue disaese are reviewed.

A Semiautomatic Method for Multiple Sclerosis Lesion Segmentation on Dual-Echo MR Imaging: Application in a Multicenter Context.

PubMed

Storelli, L; Pagani, E; Rocca, M A; Horsfield, M A; Gallo, A; Bisecco, A; Battaglini, M; De Stefano, N; Vrenken, H; Thomas, D L; Mancini, L; Ropele, S; Enzinger, C; Preziosa, P; Filippi, M

2016-07-21

The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS. © 2016 American Society of Neuroradiology.

Evaluation of a Serum Lung Cancer Biomarker Panel.

PubMed

Mazzone, Peter J; Wang, Xiao-Feng; Han, Xiaozhen; Choi, Humberto; Seeley, Meredith; Scherer, Richard; Doseeva, Victoria

2018-01-01

A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results.

Sputum neutrophils are associated with more severe asthma phenotypes using cluster analysis

PubMed Central

Moore, Wendy C.; Hastie, Annette T.; Li, Xingnan; Li, Huashi; Busse, William W.; Jarjour, Nizar N.; Wenzel, Sally E.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

2013-01-01

Background Clinical cluster analysis from the Severe Asthma Research Program (SARP) identified five asthma subphenotypes that represent the severity spectrum of early onset allergic asthma, late onset severe asthma and severe asthma with COPD characteristics. Analysis of induced sputum from a subset of SARP subjects showed four sputum inflammatory cellular patterns. Subjects with concurrent increases in eosinophils (≥2%) and neutrophils (≥40%) had characteristics of very severe asthma. Objective To better understand interactions between inflammation and clinical subphenotypes we integrated inflammatory cellular measures and clinical variables in a new cluster analysis. Methods Participants in SARP at three clinical sites who underwent sputum induction were included in this analysis (n=423). Fifteen variables including clinical characteristics and blood and sputum inflammatory cell assessments were selected by factor analysis for unsupervised cluster analysis. Results Four phenotypic clusters were identified. Cluster A (n=132) and B (n=127) subjects had mild-moderate early onset allergic asthma with paucigranulocytic or eosinophilic sputum inflammatory cell patterns. In contrast, these inflammatory patterns were present in only 7% of Cluster C (n=117) and D (n=47) subjects who had moderate-severe asthma with frequent health care utilization despite treatment with high doses of inhaled or oral corticosteroids, and in Cluster D, reduced lung function. The majority these subjects (>83%) had sputum neutrophilia either alone or with concurrent sputum eosinophilia. Baseline lung function and sputum neutrophils were the most important variables determining cluster assignment. Conclusion This multivariate approach identified four asthma subphenotypes representing the severity spectrum from mild-moderate allergic asthma with minimal or eosinophilic predominant sputum inflammation to moderate-severe asthma with neutrophilic predominant or mixed granulocytic inflammation. PMID:24332216

Monitoring disease progression with plasma creatinine in amyotrophic lateral sclerosis clinical trials

PubMed Central

van Eijk, Ruben P A; Eijkemans, Marinus J C; Ferguson, Toby A; Nikolakopoulos, Stavros; Veldink, Jan H; van den Berg, Leonard H

2018-01-01

Objectives Plasma creatinine is a predictor of survival in amyotrophic lateral sclerosis (ALS). It remains, however, to be established whether it can monitor disease progression and serve as surrogate endpoint in clinical trials. Methods We used clinical trial data from three cohorts of clinical trial participants in the LITRA, EMPOWER and PROACT studies. Longitudinal associations between functional decline, muscle strength and survival with plasma creatinine were assessed. Results were translated to trial design in terms of sample size and power. Results A total of 13 564 measurements were obtained for 1241 patients. The variability between patients in rate of decline was lower in plasma creatinine than in ALS functional rating scale–Revised (ALSFRS-R; p<0.001). The average rate of decline was faster in the ALSFRS-R, with less between-patient variability at baseline (p<0.001). Plasma creatinine had strong longitudinal correlations with the ALSFRS-R (0.43 (0.39–0.46), p<0.001), muscle strength (0.55 (0.51–0.58), p<0.001) and overall mortality (HR 0.88 (0.86–0.91, p<0.001)). Using plasma creatinine as outcome could reduce the sample size in trials by 21.5% at 18 months. For trials up to 10 months, the ALSFRS-R required a lower sample size. Conclusions Plasma creatinine is an inexpensive and easily accessible biomarker that exhibits less variability between patients with ALS over time and is predictive for the patient’s functional status, muscle strength and mortality risk. Plasma creatinine may, therefore, increase the power to detect treatment effects and could be incorporated in future ALS clinical trials as potential surrogate outcome. PMID:29084868

A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score

PubMed Central

Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars

2018-01-01

Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359

A clinical return-to-work rule for patients with back pain

PubMed Central

Dionne, Clermont E.; Bourbonnais, Renée; Frémont, Pierre; Rossignol, Michel; Stock, Susan R.; Larocque, Isabelle

2005-01-01

Background Tools for early identification of workers with back pain who are at high risk of adverse occupational outcome would help concentrate clinical attention on the patients who need it most, while helping reduce unnecessary interventions (and costs) among the others. This study was conducted to develop and validate clinical rules to predict the 2-year work disability status of people consulting for nonspecific back pain in primary care settings. Methods This was a 2-year prospective cohort study conducted in 7 primary care settings in the Quebec City area. The study enrolled 1007 workers (participation, 68.4% of potential participants expected to be eligible) aged 18–64 years who consulted for nonspecific back pain associated with at least 1 day's absence from work. The majority (86%) completed 5 telephone interviews documenting a large array of variables. Clinical information was abstracted from the medical files. The outcome measure was “return to work in good health” at 2 years, a variable that combined patients' occupational status, functional limitations and recurrences of work absence. Predictive models of 2-year outcome were developed with a recursive partitioning approach on a 40% random sample of our study subjects, then validated on the rest. Results The best predictive model included 7 baseline variables (patient's recovery expectations, radiating pain, previous back surgery, pain intensity, frequent change of position because of back pain, irritability and bad temper, and difficulty sleeping) and was particularly efficient at identifying patients with no adverse occupational outcome (negative predictive value 78%– 94%). Interpretation A clinical prediction rule accurately identified a large proportion of workers with back pain consulting in a primary care setting who were at a low risk of an adverse occupational outcome. PMID:15939915

First Clinical Experience with Retrospective Flash Glucose Monitoring (FGM) Analysis in South Africa

PubMed Central

Distiller, Larry A.; Cranston, Iain; Mazze, Roger

2016-01-01

Background: In 2014, an innovative blinded continuous glucose monitoring system was introduced with automated ambulatory glucose profile (AGP) reporting. The clinical use and interpretation of this new technology has not previously been described. Therefore we wanted to understand its use in characterizing key factors related to glycemic control: glucose exposure, variability, and stability, and risk of hypoglycemia in clinical practice. Methods: Clinicians representing affiliated diabetes centers throughout South Africa were trained and subsequently were given flash glucose monitoring readers and 2-week glucose sensors to use at their discretion. After patient use, sensor data were collected and uploaded for AGP reporting. Results: Complete data (sensor AGP with corresponding clinical information) were obtained for 50 patients with type 1 (70%) and type 2 diabetes (30%), irrespective of therapy. Aggregated analysis of AGP data comparing patients with type 1 versus type 2 diabetes, revealed that despite similar HbA1c values between both groups (8.4 ± 2 vs 8.6 ± 1.7%, respectively), those with type 2 diabetes had lower mean glucose levels (9.2 ± 3 vs 10.3 mmol/l [166 ± 54 vs 185 mg/dl]) and lower indices of glucose variability (3.0 ± 1.5 vs 5.0 ± 1.9 mmol/l [54 ± 27 vs 90 ± 34.2 mg/dl]). This highlights key areas for future focus. Conclusions: Using AGP, the characteristics of glucose exposure, variability, stability, and hypoglycemia risk and occurrence were obtained within a short time and with minimal provider and patient input. In a survey at the time of the follow-up visit, clinicians indicated that aggregated AGP data analysis provided important new clinical information and insights. PMID:27154973

The wisdom of the commons: ensemble tree classifiers for prostate cancer prognosis.

PubMed

Koziol, James A; Feng, Anne C; Jia, Zhenyu; Wang, Yipeng; Goodison, Seven; McClelland, Michael; Mercola, Dan

2009-01-01

Classification and regression trees have long been used for cancer diagnosis and prognosis. Nevertheless, instability and variable selection bias, as well as overfitting, are well-known problems of tree-based methods. In this article, we investigate whether ensemble tree classifiers can ameliorate these difficulties, using data from two recent studies of radical prostatectomy in prostate cancer. Using time to progression following prostatectomy as the relevant clinical endpoint, we found that ensemble tree classifiers robustly and reproducibly identified three subgroups of patients in the two clinical datasets: non-progressors, early progressors and late progressors. Moreover, the consensus classifications were independent predictors of time to progression compared to known clinical prognostic factors.

Early detection of glaucoma using fully automated disparity analysis of the optic nerve head (ONH) from stereo fundus images

NASA Astrophysics Data System (ADS)

Sharma, Archie; Corona, Enrique; Mitra, Sunanda; Nutter, Brian S.

2006-03-01

Early detection of structural damage to the optic nerve head (ONH) is critical in diagnosis of glaucoma, because such glaucomatous damage precedes clinically identifiable visual loss. Early detection of glaucoma can prevent progression of the disease and consequent loss of vision. Traditional early detection techniques involve observing changes in the ONH through an ophthalmoscope. Stereo fundus photography is also routinely used to detect subtle changes in the ONH. However, clinical evaluation of stereo fundus photographs suffers from inter- and intra-subject variability. Even the Heidelberg Retina Tomograph (HRT) has not been found to be sufficiently sensitive for early detection. A semi-automated algorithm for quantitative representation of the optic disc and cup contours by computing accumulated disparities in the disc and cup regions from stereo fundus image pairs has already been developed using advanced digital image analysis methodologies. A 3-D visualization of the disc and cup is achieved assuming camera geometry. High correlation among computer-generated and manually segmented cup to disc ratios in a longitudinal study involving 159 stereo fundus image pairs has already been demonstrated. However, clinical usefulness of the proposed technique can only be tested by a fully automated algorithm. In this paper, we present a fully automated algorithm for segmentation of optic cup and disc contours from corresponding stereo disparity information. Because this technique does not involve human intervention, it eliminates subjective variability encountered in currently used clinical methods and provides ophthalmologists with a cost-effective and quantitative method for detection of ONH structural damage for early detection of glaucoma.

Referring patients to specialists: A structured vignette survey of Australian and British GPs

PubMed Central

Jiwa, Moyez; Gordon, Michael; Arnet, Hayley; Ee, Hooi; Bulsara, Max; Colwell, Brigitte

2008-01-01

Background In Australia and in the United Kingdom (UK) access to specialists is sanctioned by General Practitioners (GPs). It is important to understand how practitioners determine which patients warrant referral. Methods A self-administered structured vignette postal survey of General Practitioners in Western Australia and the United Kingdom. Sixty-four vignettes describing patients with colorectal symptoms were constructed encompassing six clinical details. Nine vignettes, chosen at random, were presented to each individual. Respondents were asked if they would refer the patient to a specialist and how urgently. Logistic regression and parametric tests were used to analyse the data Results We received 260 completed questionnaires. 58% of 'cancer vignettes' were selected for 'urgent' referral. 1632/2367 or 69% of all vignettes were selected for referral. After adjusting for clustering the model suggests that 38.4% of the variability is explained by all the clinical variables as well as the age and experience of the respondents. 1012 or 42.8 % of vignettes were referred 'urgently'. After adjusting for clustering the data suggests that 31.3 % of the variability is explained by the model. The age of the respondents, the location of the practice and all the clinical variables were significant in the decision to refer urgently. Conclusion GPs' referral decisions for patients with lower bowel symptoms are similar in the two countries. We question the wisdom of streaming referrals from primary care without a strong evidence base and an effective intervention for implementing guidelines. We conclude that implementation must take into account the profile of patients but also the characteristics of GPs and referral policies. PMID:18194578

Three-factor model of premorbid adjustment in a sample with chronic schizophrenia and first-episode psychosis.

PubMed

Barajas, Ana; Usall, Judith; Baños, Iris; Dolz, Montserrat; Villalta-Gil, Victoria; Vilaplana, Miriam; Autonell, Jaume; Sánchez, Bernardo; Cervilla, Jorge A; Foix, Alexandrina; Obiols, Jordi E; Haro, Josep Maria; Ochoa, Susana

2013-12-01

The dimensionality of premorbid adjustment (PA) has been a debated issue, with attempts to determine whether PA is a unitary construct or composed of several independent domains characterized by a differential deterioration pattern and specific outcome correlates. This study examines the factorial structure of PA, as well as, the course and correlates of its domains. Retrospective study of 84 adult patients experiencing first-episode psychosis (FEP) (n=33) and individuals with schizophrenia (SCH) (n=51). All patients were evaluated with a comprehensive battery of instruments including clinical, functioning and neuropsychological variables. A principal component analysis accompanied by a varimax rotation method was used to examine the factor structure of the PAS-S scale. Paired t tests and Wilcoxon rank tests were used to assess the changes in PAS domains over time. Bivariate correlation analyses were performed to analyse the relationship between PAS factors and clinical, social and cognitive variables. PA was better explained by three factors (71.65% of the variance): Academic PA, Social PA and Socio-sexual PA. The academic domain showed higher scores of PA from childhood. Social and clinical variables were more strongly related to Social PA and Socio-sexual PA domains, and the Academic PA domain was exclusively associated with cognitive variables. This study supports previous evidence, emphasizing the validity of dividing PA into its sub-components. A differential deterioration pattern and specific correlates were observed in each PA domains, suggesting that impairments in each PA domain might predispose individuals to develop different expressions of psychotic dimensions. © 2013.

Development of a rapid, robust, and universal picogreen-based method to titer adeno-associated vectors.

PubMed

Piedra, Jose; Ontiveros, Maria; Miravet, Susana; Penalva, Cristina; Monfar, Mercè; Chillon, Miguel

2015-02-01

Recombinant adeno-associated viruses (rAAVs) are promising vectors in preclinical and clinical assays for the treatment of diseases with gene therapy strategies. Recent technological advances in amplification and purification have allowed the production of highly purified rAAV vector preparations. Although quantitative polymerase chain reaction (qPCR) is the current method of choice for titrating rAAV genomes, it shows high variability. In this work, we report a rapid and robust rAAV titration method based on the quantitation of encapsidated DNA with the fluorescent dye PicoGreen®. This method allows detection from 3×10(10) viral genome/ml up to 2.4×10(13) viral genome/ml in a linear range. Contrasted with dot blot or qPCR, the PicoGreen-based assay has less intra- and interassay variability. Moreover, quantitation is rapid, does not require specific primers or probes, and is independent of the rAAV pseudotype analyzed. In summary, development of this universal rAAV-titering method may have substantive implications in rAAV technology.

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

PubMed

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Development of the Likelihood of Low Glucose (LLG) algorithm for evaluating risk of hypoglycemia: a new approach for using continuous glucose data to guide therapeutic decision making.

PubMed

Dunn, Timothy C; Hayter, Gary A; Doniger, Ken J; Wolpert, Howard A

2014-07-01

The objective was to develop an analysis methodology for generating diabetes therapy decision guidance using continuous glucose (CG) data. The novel Likelihood of Low Glucose (LLG) methodology, which exploits the relationship between glucose median, glucose variability, and hypoglycemia risk, is mathematically based and can be implemented in computer software. Using JDRF Continuous Glucose Monitoring Clinical Trial data, CG values for all participants were divided into 4-week periods starting at the first available sensor reading. The safety and sensitivity performance regarding hypoglycemia guidance "stoplights" were compared between the LLG method and one based on 10th percentile (P10) values. Examining 13 932 hypoglycemia guidance outputs, the safety performance of the LLG method ranged from 0.5% to 5.4% incorrect "green" indicators, compared with 0.9% to 6.0% for P10 value of 110 mg/dL. Guidance with lower P10 values yielded higher rates of incorrect indicators, such as 11.7% to 38% at 80 mg/dL. When evaluated only for periods of higher glucose (median above 155 mg/dL), the safety performance of the LLG method was superior to the P10 method. Sensitivity performance of correct "red" indicators of the LLG method had an in sample rate of 88.3% and an out of sample rate of 59.6%, comparable with the P10 method up to about 80 mg/dL. To aid in therapeutic decision making, we developed an algorithm-supported report that graphically highlights low glucose risk and increased variability. When tested with clinical data, the proposed method demonstrated equivalent or superior safety and sensitivity performance. © 2014 Diabetes Technology Society.

Hormonal contraception and female pain, orgasm and sexual pleasure.

PubMed

Smith, Nicole K; Jozkowski, Kristen N; Sanders, Stephanie A

2014-02-01

Almost half of all pregnancies in the United States are unintentional, unplanned, or mistimed. Most unplanned pregnancies result from inconsistent, incorrect, or nonuse of a contraceptive method. Diminished sexual function and pleasure may be a barrier to using hormonal contraception. This study explores sexual function and behaviors of women in relation to the use of hormonal vs. nonhormonal methods of contraception. Data were collected as part of an online health and sexuality study of women. Main outcomes variables assess frequencies in two domains: (i) sexual function (proportion of sexual events with experiences of pain or discomfort, arousal, contentment and satisfaction, pleasure and enjoyment, lubrication difficulty, and orgasm) and (ii) sexual behavior (number of times engaged in sexual activity, proportion of sexual events initiated by the woman, and proportion of sexual events for which a lubricant was used). Sociodemographic variables and contraceptive use were used as sample descriptors and correlates. The recall period was the past 4 weeks. The sample included 1,101 women with approximately half (n = 535) using a hormonal contraceptive method exclusively or a combination of a hormonal and nonhormonal method, and about half (n = 566) using a nonhormonal method of contraception exclusively. Hierarchical regression analyses were conducted to examine the relation of hormonal contraceptive use to each of the dependent variables. Women using a hormonal contraceptive method experienced less frequent sexual activity, arousal, pleasure, and orgasm and more difficulty with lubrication even when controlling for sociodemographic variables. This study adds to the literature on the potential negative sexual side effects experienced by many women using hormonal contraception. Prospective research with diverse women is needed to enhance the understanding of potential negative sexual side effects of hormonal contraceptives, their prevalence, and possible mechanisms. Clinical and counseling implications are discussed. © 2013 International Society for Sexual Medicine.

Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study

PubMed Central

2017-01-01

A challenge that must be addressed when conducting studies with complex natural products is how to evaluate their complexity and variability. Traditional methods of quantifying a single or a small range of metabolites may not capture the full chemical complexity of multiple samples. Different metabolomics approaches were evaluated to discern how they facilitated comparison of the chemical composition of commercial green tea [Camellia sinensis (L.) Kuntze] products, with the goal of capturing the variability of commercially used products and selecting representative products for in vitro or clinical evaluation. Three metabolomic-related methods—untargeted ultraperformance liquid chromatography–mass spectrometry (UPLC-MS), targeted UPLC-MS, and untargeted, quantitative 1HNMR—were employed to characterize 34 commercially available green tea samples. Of these methods, untargeted UPLC-MS was most effective at discriminating between green tea, green tea supplement, and non-green-tea products. A method using reproduced correlation coefficients calculated from principal component analysis models was developed to quantitatively compare differences among samples. The obtained results demonstrated the utility of metabolomics employing UPLC-MS data for evaluating similarities and differences between complex botanical products. PMID:28453261

Analysis of pressure-flow data in terms of computer-derived urethral resistance parameters.

PubMed

van Mastrigt, R; Kranse, M

1995-01-01

The simultaneous measurement of detrusor pressure and flow rate during voiding is at present the only way to measure or grade infravesical obstruction objectively. Numerous methods have been introduced to analyze the resulting data. These methods differ in aim (measurement of urethral resistance and/or diagnosis of obstruction), method (manual versus computerized data processing), theory or model used, and resolution (continuously variable parameters or a limited number of classes, the so-called monogram). In this paper, some aspects of these fundamental differences are discussed and illustrated. Subsequently, the properties and clinical performance of two computer-based methods for deriving continuous urethral resistance parameters are treated.

Automated quantification of myocardial infarction from MR images by accounting for partial volume effects: animal, phantom, and human study.

PubMed

Heiberg, Einar; Ugander, Martin; Engblom, Henrik; Götberg, Matthias; Olivecrona, Göran K; Erlinge, David; Arheden, Håkan

2008-02-01

Ethics committees approved human and animal study components; informed written consent was provided (prospective human study [20 men; mean age, 62 years]) or waived (retrospective human study [16 men, four women; mean age, 59 years]). The purpose of this study was to prospectively evaluate a clinically applicable method, accounting for the partial volume effect, to automatically quantify myocardial infarction from delayed contrast material-enhanced magnetic resonance images. Pixels were weighted according to signal intensity to calculate infarct fraction for each pixel. Mean bias +/- variability (or standard deviation), expressed as percentage left ventricular myocardium (%LVM), were -0.3 +/- 1.3 (animals), -1.2 +/- 1.7 (phantoms), and 0.3 +/- 2.7 (patients), respectively. Algorithm had lower variability than dichotomous approach (2.7 vs 7.7 %LVM, P < .01) and did not differ from interobserver variability for bias (P = .31) or variability (P = .38). The weighted approach provides automatic quantification of myocardial infarction with higher accuracy and lower variability than a dichotomous algorithm. (c) RSNA, 2007.

Evaluation of inter-day and inter-individual variability of tear peptide/protein profiles by MALDI-TOF MS analyses

PubMed Central

González, Nerea; Iloro, Ibon; Durán, Juan A.; Elortza, Félix

2012-01-01

Purpose To characterize the tear film peptidome and low molecular weight protein profiles of healthy control individuals, and to evaluate changes due to day-to-day and individual variation and tear collection methods, by using solid phase extraction coupled to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling. Methods The tear protein profiles of six healthy volunteers were analyzed over seven days and inter-day and inter-individual variability was evaluated. The bilaterality of tear film and the effect of tear collection methods on protein profiles were also analyzed in some of these patients. MALDI-TOF MS analyses were performed on tear samples purified by using a solid phase extraction (SPE) method based on C18 functionalized magnetic beads for peptide and low molecular weight protein enrichment, focusing spectra acquisition on the 1 to 20 kDa range. Spectra were analyzed using principal component analysis (PCA) with MultiExperiment Viewer (TMeV) software. Volunteers were examined in terms of tear production status (Schirmer I test), clinical assessment of palpebral lids and meibomian glands, and a subjective OSD questionnaire before tear collection by a glass micro-capillary. Results Analysis of peptides and proteins in the 1–20 kDa range showed no significant inter-day differences in tear samples collected from six healthy individuals during seven days of monitoring, but revealed subtle intrinsic inter-individual differences. Profile analyses of tears collected from the right and left eyes confirmed tear bilaterality in four healthy patients. The addition of physiologic serum for tear sample collection did not affect the peptide and small protein profiles with respect to the number of resolved peaks, but it did reduce the signal intensity of the peaks, and increased variability. Magnetic beads were found to be a suitable method for tear film purification for the profiling study. Conclusions No significant variability in tear peptide and protein profiles below 20 kDa was found in healthy controls over a seven day period, nor in right versus left eye profiles from the same individual. Subtle inter-individual differences can be observed upon tear profiling analysis and confirm intrinsic variability between control subjects. Addition of physiologic serum for tear collection affects the proteome and peptidome in terms of peak intensities, but not in the composition of the profiles themselves. This work shows that MALDI-TOF MS coupled with C18 magnetic beads is an effective and reproducible methodology for tear profiling studies in the clinical monitoring of patients. PMID:22736947

Cost-effectiveness analysis using data from multinational trials: The use of bivariate hierarchical modelling

PubMed Central

Manca, Andrea; Lambert, Paul C; Sculpher, Mark; Rice, Nigel

2008-01-01

Healthcare cost-effectiveness analysis (CEA) often uses individual patient data (IPD) from multinational randomised controlled trials. Although designed to account for between-patient sampling variability in the clinical and economic data, standard analytical approaches to CEA ignore the presence of between-location variability in the study results. This is a restrictive limitation given that countries often differ in factors that could affect the results of CEAs, such as the availability of healthcare resources, their unit costs, clinical practice, and patient case-mix. We advocate the use of Bayesian bivariate hierarchical modelling to analyse multinational cost-effectiveness data. This analytical framework explicitly recognises that patient-level costs and outcomes are nested within countries. Using real life data, we illustrate how the proposed methods can be applied to obtain (a) more appropriate estimates of overall cost-effectiveness and associated measure of sampling uncertainty compared to standard CEA; and (b) country-specific cost-effectiveness estimates which can be used to assess the between-location variability of the study results, while controlling for differences in country-specific and patient-specific characteristics. It is demonstrated that results from standard CEA using IPD from multinational trials display a large degree of variability across the 17 countries included in the analysis, producing potentially misleading results. In contrast, ‘shrinkage estimates’ obtained from the modelling approach proposed here facilitate the appropriate quantification of country-specific cost-effectiveness estimates, while weighting the results based on the level of information available within each country. We suggest that the methods presented here represent a general framework for the analysis of economic data collected from different locations. PMID:17641141

A Bayesian network approach for modeling local failure in lung cancer

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Craft, Jeffrey; Lozi, Rawan Al; Vaidya, Manushka; Meng, Yifan; Deasy, Joseph O.; Bradley, Jeffrey D.; El Naqa, Issam

2011-03-01

Locally advanced non-small cell lung cancer (NSCLC) patients suffer from a high local failure rate following radiotherapy. Despite many efforts to develop new dose-volume models for early detection of tumor local failure, there was no reported significant improvement in their application prospectively. Based on recent studies of biomarker proteins' role in hypoxia and inflammation in predicting tumor response to radiotherapy, we hypothesize that combining physical and biological factors with a suitable framework could improve the overall prediction. To test this hypothesis, we propose a graphical Bayesian network framework for predicting local failure in lung cancer. The proposed approach was tested using two different datasets of locally advanced NSCLC patients treated with radiotherapy. The first dataset was collected retrospectively, which comprises clinical and dosimetric variables only. The second dataset was collected prospectively in which in addition to clinical and dosimetric information, blood was drawn from the patients at various time points to extract candidate biomarkers as well. Our preliminary results show that the proposed method can be used as an efficient method to develop predictive models of local failure in these patients and to interpret relationships among the different variables in the models. We also demonstrate the potential use of heterogeneous physical and biological variables to improve the model prediction. With the first dataset, we achieved better performance compared with competing Bayesian-based classifiers. With the second dataset, the combined model had a slightly higher performance compared to individual physical and biological models, with the biological variables making the largest contribution. Our preliminary results highlight the potential of the proposed integrated approach for predicting post-radiotherapy local failure in NSCLC patients.

Integrating Allergen Analysis Within a Risk Assessment Framework: Approaches to Development of Targeted Mass Spectrometry Methods for Allergen Detection and Quantification in the iFAAM Project.

PubMed

Nitride, Chiara; Lee, Victoria; Baricevic-Jones, Ivona; Adel-Patient, Karine; Baumgartner, Sabine; Mills, E N Clare

2018-01-01

Allergen analysis is central to implementing and monitoring food allergen risk assessment and management processes by the food industry, but current methods for the determination of allergens in foods give highly variable results. The European Union-funded "Integrated Approaches to Food Allergen and Allergy Risk Management" (iFAAM) project has been working to address gaps in knowledge regarding food allergen management and analysis, including the development of novel MS and immuno-based allergen determination methods. Common allergenic food ingredients (peanut, hazelnut, walnut, cow's milk [Bos domesticus], and hen's egg [Gallus domesticus]) and common food matrixes (chocolate dessert and cookie) have been used for both clinical studies and analytical method development to ensure that the new methods are clinically relevant. Allergen molecules have been used as analytical targets and allergenic ingredients incurred into matrixes at levels close to reference doses that may trigger the use of precautionary allergen labeling. An interlaboratory method comparison has been undertaken for the determination of peanut in chocolate dessert using MS and immuno-based methods. The iFAAM approach has highlighted the need for methods to report test results in allergenic protein. This will allow food business operators to use them in risk assessments that are founded on clinical study data in which protein has been used as a measure of allergenic potency.

Defining poor and optimum performance in an IVF programme.

PubMed

Castilla, Jose A; Hernandez, Juana; Cabello, Yolanda; Lafuente, Alejandro; Pajuelo, Nuria; Marqueta, Javier; Coroleu, Buenaventura

2008-01-01

At present there is considerable interest in healthcare administration, among professionals and among the general public concerning the quality of programmes of assisted reproduction. There exist various methods for comparing and analysing the results of clinical activity, with graphical methods being the most commonly used for this purpose. As yet, there is no general consensus as to how the poor performance (PP) or optimum performance (OP) of assisted reproductive technologies should be defined. Data from the IVF/ICSI register of the Spanish Fertility Society were used to compare and analyse different definitions of PP or OP. The primary variable best reflecting the quality of an IVF/ICSI programme was taken to be the percentage of singleton births per IVF/ICSI cycle initiated. Of the 75 infertility clinics that took part in the SEF-2003 survey, data on births were provided by 58. A total of 25 462 cycles were analysed. The following graphical classification methods were used: ranking of the proportion of singleton births per cycles started in each centre (league table), Shewhart control charts, funnel plots, best and worst-case scenarios and state of the art methods. The clinics classified as producing PP or OP varied considerably depending on the classification method used. Only three were rated as providing 'PP' or 'OP' by all methods, unanimously. Another four clinics were classified as 'poor' or 'optimum' by all the methods except one. On interpreting the results derived from IVF/ICSI centres, it is essential to take into account the characteristics of the method used for this purpose.

Efficacy of Atomoxetine for the Treatment of ADHD Symptoms in Patients with Pervasive Developmental Disorders: A Prospective, Open-Label Study

ERIC Educational Resources Information Center

Fernandez-Jaen, Alberto; Fernandez-Mayoralas, Daniel Martin; Calleja-Perez, Beatriz; Munoz-Jareno, Nuria; Campos Diaz, Maria del Rosario; Lopez-Arribas, Sonia

2013-01-01

Objective: Atomoxetine's tolerance and efficacy were studied in 24 patients with pervasive developmental disorder and symptoms of ADHD. Method: Prospective, open-label, 16-week study was performed, using the variables of the Clinical Global Impression Scale and the Conners' Scale, among others. Results: A significant difference was found between…

Employment among Working-Age Adults with Multiple Sclerosis: A Data-Mining Approach to Identifying Employment Interventions

ERIC Educational Resources Information Center

Bishop, Malachy; Chan, Fong; Rumrill, Phillip D., Jr.; Frain, Michael P.; Tansey, Timothy N.; Chiu, Chung-Yi; Strauser, David; Umeasiegbu, Veronica I.

2015-01-01

Purpose: To examine demographic, functional, and clinical multiple sclerosis (MS) variables affecting employment status in a national sample of adults with MS in the United States. Method: The sample included 4,142 working-age (20-65 years) Americans with MS (79.1% female) who participated in a national survey. The mean age of participants was…

A method for developing outcome measures in the clinical laboratory.

PubMed

Jones, J

1996-01-01

Measuring and reporting outcomes in health care is becoming more important for quality assessment, utilization assessment, accreditation standards, and negotiating contracts in managed care. How does one develop an outcome measure for the laboratory to assess the value of the services? A method is described which outlines seven steps in developing outcome measures for a laboratory service or process. These steps include the following: 1. Identify the process or service to be monitored for performance and outcome assessment. 2. If necessary, form an multidisciplinary team of laboratory staff, other department staff, physicians, and pathologists. 3. State the purpose of the test or service including a review of published data for the clinical pathological correlation. 4. Prepare a process cause and effect diagram including steps critical to the outcome. 5. Identify key process variables that contribute to positive or negative outcomes. 6. Identify outcome measures that are not process measures. 7. Develop an operational definition, identify data sources, and collect data. Examples, including a process cause and effect diagram, process variables, and outcome measures, are given using the Therapeutic Drug Monitoring service (TDM). A summary of conclusions and precautions for outcome measurement is then provided.

PRP For the Treatment of Cartilage Pathology

PubMed Central

Kon, Elizaveta; Filardo, Giuseppe; Di Matteo, Berardo; Marcacci, Maurilio

2013-01-01

In recent years biological strategies are being more widely used to treat cartilage lesions. One of the most exploited novel treatments is Platelet-rich Plasma (PRP), whose high content of growth factors is supposed to determine a regenerative stimulus to cartilaginous tissue. Despite many promising in vitro and in vivo studies, when discussing clinical application a clear indication for the use of PRP cannot be assessed. There are initial encouraging clinical data, but only a few randomized controlled trials have been published, so it is not possible to fully endorse this kind of approach for the treatment of cartilage pathology. Furthermore, study comparison is very difficult due to the great variability in PRP preparation methods, cell content and concentration, storage modalities, activation methods and even application protocols. These factors partially explain the lack of high quality controlled trials up to now. This paper discusses the main aspects concerning the basic biology of PRP, the principal sources of variability, and summarizes the available literature on PRP use, both in surgical and conservative treatments. Based on current evidence, PRP treatment should only be indicated for low-grade cartilage degeneration and in case of failure of more traditional conservative approaches. PMID:23730375

Immunization in pregnancy clinical research in low- and middle-income countries - Study design, regulatory and safety considerations.

PubMed

Kochhar, Sonali; Bonhoeffer, Jan; Jones, Christine E; Muñoz, Flor M; Honrado, Angel; Bauwens, Jorgen; Sobanjo-Ter Meulen, Ajoke; Hirschfeld, Steven

2017-12-04

Immunization of pregnant women is a promising public health strategy to reduce morbidity and mortality among both the mothers and their infants. Establishing safety and efficacy of vaccines generally uses a hybrid design between a conventional interventional study and an observational study that requires enrolling thousands of study participants to detect an unknown number of uncommon events. Historically, enrollment of pregnant women in clinical research studies encountered many barriers based on risk aversion, lack of knowledge, and regulatory ambiguity. Conducting research enrolling pregnant women in low- and middle-income countries can have additional factors to address such as limited availability of baseline epidemiologic data on disease burden and maternal and neonatal outcomes during and after pregnancy; challenges in recruiting and retaining pregnant women in research studies, variability in applying and interpreting assessment methods, and variability in locally acceptable and available infrastructure. Some measures to address these challenges include adjustment of study design, tailoring recruitment, consent process, retention strategies, operational and logistical processes, and the use of definitions and data collection methods that will align with efforts globally. Copyright © 2017. Published by Elsevier Ltd.

[Using infrared thermal asymmetry analysis for objective assessment of the lesion of facial nerve function].

PubMed

Liu, Xu-long; Hong, Wen-xue; Song, Jia-lin; Wu, Zhen-ying

2012-03-01

The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Some lesions of facial nerve function are associated with an alteration of the thermal distribution of the human body. Since the dissipation of heat through the skin occurs for the most part in the form of infrared radiation, infrared thermography is the method of choice to capture the alteration of the infrared thermal distribution. This paper presents a new method of analysis of the thermal asymmetry named effective thermal area ratio, which is a product of two variables. The first variable is mean temperature difference between the specific facial region and its contralateral region. The second variable is a ratio, which is equal to the area of the abnormal region divided by the total area. Using this new method, we performed a controlled trial to assess the facial nerve function of the healthy subjects and the patients with Bell's palsy respectively. The results show: that the mean specificity and sensitivity of this method are 0.90 and 0.87 respectively, improved by 7% and 26% compared with conventional methods. Spearman correlation coefficient between effective thermal area ratio and the degree of facial nerve function is an average of 0.664. Hence, concerning the diagnosis and assessment of facial nerve function, infrared thermography is a powerful tool; while the effective ther mal area ratio is an efficient clinical indicator.

An Overview of Longitudinal Data Analysis Methods for Neurological Research

PubMed Central

Locascio, Joseph J.; Atri, Alireza

2011-01-01

The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models. PMID:22203825

Exploring the viability of using online social media advertising as a recruitment method for smoking cessation clinical trials.

PubMed

Frandsen, Mai; Walters, Julia; Ferguson, Stuart G

2014-02-01

The aim of the present study was to explore the viability of using social media as a recruitment tool in a clinical research trial. Sociodemographic data and smoking characteristics were assessed in 266 participants recruited to investigate the effectiveness of a behavioral support program for smoking cessation. For analysis, participants were separated into 2 groups based on whether they were recruited either using traditional means (flyers, word of mouth, or newspaper advertisement; n = 125, 47.0%) or by advertisements in online social media (n = 138, 51.9%). Participants recruited via social media were significantly younger, but there were no differences in other socioeconomic variables or smoking characteristics compared with participants recruited via other traditional means. The findings of the present study suggest that using online social media is a viable recruitment method for smoking studies and compliments other more traditional recruitment methods.

[Clinical features of patients with Becker muscular dystrophy and deletions of the rod domain of dystrophin gene].

PubMed

Wang, Yanyun; Zhu, Yuling; Yang, Juan; Li, Yaqin; Sun, Jiangwen; Zhan, Yixin; Zhang, Cheng

2018-02-10

OBJECTIVE To explore the clinical features of patients carrying deletions of the rod domain of the dystrophin gene. METHODS Clinical data of 12 Chinese patients with Becker muscular dystrophy (BMD) and such deletions was reviewed. RESULTS Most patients complained of muscle weakness of lower limbs. Two patients had muscle cramps, one had increased creatine kinase (CK) level, and one had dilated cardiomyopathy. CONCLUSION Compared with DMD, the clinical features of BMD are much more variable, particularly for those carrying deletions of the rod domain of the dystrophin gene. Muscular weakness may not be the sole complaint of BMD. The diagnosis of BMD cannot be excluded by moderately elevated CK. For male patients with dilated cardiomyopathy, the possibility of BMD should be considered.

What variables can influence clinical reasoning?

PubMed

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-12-01

Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R(2) chnage = 0.46, P Value = 0.000). Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction.

Five year follow-up of a smoking withdrawal clinic population.

PubMed Central

West, D W; Graham, S; Swanson, M; Wilkinson, G

1977-01-01

Eight hundred volunteers who attended smoking clinics at Roswell Park Memorial Institute from 1964-1965 were followed up five years later to ascertain their current smoking status. From three waves of a mailed questionnaire, plus a telephone campaign, we obtained 559 usable responses. The relationship between smoking status at the five-year follow-up and clinic protocols and selected social and psychological characteristics as determined during the clinics were examined. Of those individuals contacted five years after the clinic, 17.8 per cent were not smoking. Variations in clinic protocol in terms of drugs and education methods had no relation to long-term smoking withdrawal. Several social and psychological variables, however, were related to smoking behavior five years after the clinics. Non-smokers were more likely than smokers to be males, to be older, to have smoked less before the clinic, to have started smoking at a later age, to have a milieu that was supportive of their stopping, and to have fewer indices of neurosis and fewer psychosomatic symptoms. PMID:869086

Formant Frequencies and Bandwidths in Relation to Clinical Variables in an Obstructive Sleep Apnea Population.

PubMed

Montero Benavides, Ana; Blanco Murillo, José Luis; Fernández Pozo, Rubén; Espinoza Cuadros, Fernando; Torre Toledano, Doroteo; Alcázar-Ramírez, José D; Hernández Gómez, Luis A

2016-01-01

We investigated whether differences in formants and their bandwidths, previously reported comparing small sample population of healthy individuals and patients with obstructive sleep apnea (OSA), are detected on a larger population representative of a clinical practice scenario. We examine possible indirect or mediated effects of clinical variables, which may shed some light on the connection between speech and OSA. In a retrospective study, 241 male subjects suspected to suffer from OSA were examined. The apnea-hypopnea index (AHI) was obtained for every subject using overnight polysomnography. Furthermore, the clinical variables usually reported as predictors of OSA, body mass index (BMI), cervical perimeter, height, weight, and age, were collected. Voice samples of sustained phonations of the vowels /a/, /e/, /i/, /o/, and /u/ were recorded. Formant frequencies F1, F2, and F3 and bandwidths BW1, BW2, and BW3 of the sustained vowels were determined using spectrographic analysis. Correlations among AHI, clinical parameters, and formants and bandwidths were determined. Correlations between AHI and clinical variables were stronger than those between AHI and voice features. AHI only correlates poorly with BW2 of /a/ and BW3 of /e/. A number of further weak but significant correlations have been detected between voice and clinical variables. Most of them were for height and age, with two higher values for age and F2 of /o/ and F2 of /u/. Only few very weak correlations were detected between voice and BMI, weight and cervical perimeter, wich are the clinical variables more correlated with AHI. No significant correlations were detected between AHI and formant frequencies and bandwidths. Correlations between voice and other clinical factors characterizing OSA are weak but highlight the importance of considering indirect or mediated effects of such clinical variables in any research on speech and OSA. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Blood pressure monitoring: theory and practice. European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability Teaching Course Proceedings.

PubMed

Stergiou, George S; Palatini, Paolo; Asmar, Roland; Bilo, Grzegorz; de la Sierra, Alejandro; Head, Geoff; Kario, Kazuomi; Mihailidou, Anastasia; Wang, Jiguang; Mancia, Giuseppe; O'Brien, Eoin; Parati, Gianfranco

2018-02-01

The European Society of Hypertension (ESH) Working Group on Blood Pressure (BP) Monitoring and Cardiovascular Variability organized a Teaching Course on 'Blood Pressure Monitoring: Theory and Practice' during the 2017 ESH Meeting in Milan, Italy. This course performed by 11 international BP monitoring experts covered key topics of BP monitoring, including office BP measurement, ambulatory BP monitoring, home BP monitoring, ambulatory versus home BP, white-coat and masked hypertension, cuff use, and BP variability. This article presents a summary of the proceedings of the ESH BP Monitoring Teaching Course, including essential information, practical issues, and recommendations on the clinical application of BP monitoring methods, aiming to the optimal management of patients with suspected or diagnosed hypertension.

Hematologic reference intervals and age effect in European Strigiformes.

PubMed

Agusti Montolio, Susana; Molina López, Rafael; Cray, Carolyn; Lavín González, Santiago; Nicolás Francisco, Olga; Marco Sánchez, Ignasi; Casas-Díaz, Encarna; Cuenca Valera, Rafaela

2017-09-01

The clinical importance of hematologic testing in avian veterinary medicine is reflected in the increasing number of studies for the establishment of hematologic RIs of Strigiformes and other species. Age is an important physiologic factor in birds and the effect on hematology variable should be understood. The objective of this study was to determine baseline data of hematologic variables in 5 species of Iberian Strigiformes in different age classes. Nocturnal birds of prey were sampled at Wildlife Health Centers. Packed cell volume was determined by the microhematocrit centrifugation method, and RBC and WBC counts were determined using the direct hemocytometer count method with Natt and Herrick solution. Hemoglobin concentration was measured spectrophotometrically. The MCV, MCHC, and MHC were calculated using the standard formulas. The differential WBC count was performed by the routine microscopic evaluation of 200 cells on a blood smear manually stained with Wright stain. Thrombocyte blood count estimate was obtained from the blood film. No differences were observed between juveniles and adults for any variable evaluated in Tawny owl, Little owl, Scops owl, Long-eared owl, and Barn owl. In addition, PCV, RBC, and HGB of chicks were statistically significantly lower than in juveniles and adults, and total WBC was significantly higher in Tawny owl, Little owl, Scops owl, and Long-eared owl. Our findings provide evidence that laboratory data from chicks of Strigiformes are different compared to juveniles and adults; therefore, separate RIs were defined. © 2017 American Society for Veterinary Clinical Pathology.

[Assessment of the correlation between histological degeneration and radiological and clinical parameters in a series of patients who underwent lumbar disc herniation surgery].

PubMed

Munarriz, Pablo M; Paredes, Igor; Alén, José F; Castaño-Leon, Ana M; Cepeda, Santiago; Hernandez-Lain, Aurelio; Lagares, Alfonso

The use of histological degeneration scores in surgically-treated herniated lumbar discs is not common in clinical practice and its use has been primarily restricted to research. The objective of this study is to evaluate if there is an association between a higher grade of histological degeneration when compared with clinical or radiological parameters. Retrospective consecutive analysis of 122 patients who underwent single-segment lumbar disc herniation surgery. Clinical information was available on all patients, while the histological study and preoperative magnetic resonance imaging were also retrieved for 75 patients. Clinical variables included age, duration of symptoms, neurological deficits, or affected deep tendon reflex. The preoperative magnetic resonance imaging was evaluated using Modic and Pfirrmann scores for the affected segment by 2 independent observers. Histological degeneration was evaluated using Weiler's score; the presence of inflammatory infiltrates and neovascularization, not included in the score, were also studied. Correlation and chi-square tests were used to assess the association between histological variables and clinical or radiological variables. Interobserver agreement was also evaluated for the MRI variables using weighted kappa. No statistically significant correlation was found between histological variables (histological degeneration score, inflammatory infiltrates or neovascularization) and clinical or radiological variables. Interobserver agreement for radiological scores resulted in a kappa of 0.79 for the Pfirrmann scale and 0.65 for the Modic scale, both statistically significant. In our series of patients, we could not demonstrate any correlation between the degree of histological degeneration or the presence of inflammatory infiltrates when compared with radiological degeneration scales or clinical variables such as the patient's age or duration of symptoms. Copyright © 2017 Sociedad Española de Neurocirugía. Publicado por Elsevier España, S.L.U. All rights reserved.

Temporal data mining for the quality assessment of hemodialysis services.

PubMed

Bellazzi, Riccardo; Larizza, Cristiana; Magni, Paolo; Bellazzi, Roberto

2005-05-01

This paper describes the temporal data mining aspects of a research project that deals with the definition of methods and tools for the assessment of the clinical performance of hemodialysis (HD) services, on the basis of the time series automatically collected during hemodialysis sessions. Intelligent data analysis and temporal data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, two new methods for association rule discovery and temporal rule discovery are applied to the time series. Such methods exploit several pre-processing techniques, comprising data reduction, multi-scale filtering and temporal abstractions. We have analyzed the data of more than 5800 dialysis sessions coming from 43 different patients monitored for 19 months. The qualitative rules associating the outcome parameters and the measured variables were examined by the domain experts, which were able to distinguish between rules confirming available background knowledge and unexpected but plausible rules. The new methods proposed in the paper are suitable tools for knowledge discovery in clinical time series. Their use in the context of an auditing system for dialysis management helped clinicians to improve their understanding of the patients' behavior.

Symbolic dynamics marker of heart rate variability combined with clinical variables enhance obstructive sleep apnea screening

NASA Astrophysics Data System (ADS)

Ravelo-García, A. G.; Saavedra-Santana, P.; Juliá-Serdá, G.; Navarro-Mesa, J. L.; Navarro-Esteva, J.; Álvarez-López, X.; Gapelyuk, A.; Penzel, T.; Wessel, N.

2014-06-01

Many sleep centres try to perform a reduced portable test in order to decrease the number of overnight polysomnographies that are expensive, time-consuming, and disturbing. With some limitations, heart rate variability (HRV) has been useful in this task. The aim of this investigation was to evaluate if inclusion of symbolic dynamics variables to a logistic regression model integrating clinical and physical variables, can improve the detection of subjects for further polysomnographies. To our knowledge, this is the first contribution that innovates in that strategy. A group of 133 patients has been referred to the sleep center for suspected sleep apnea. Clinical assessment of the patients consisted of a sleep related questionnaire and a physical examination. The clinical variables related to apnea and selected in the statistical model were age (p < 10-3), neck circumference (p < 10-3), score on a questionnaire scale intended to quantify daytime sleepiness (p < 10-3), and intensity of snoring (p < 10-3). The validation of this model demonstrated an increase in classification performance when a variable based on non-linear dynamics of HRV (p < 0.01) was used additionally to the other variables. For diagnostic rule based only on clinical and physical variables, the corresponding area under the receiver operating characteristic (ROC) curve was 0.907 (95% confidence interval (CI) = 0.848, 0.967), (sensitivity 87.10% and specificity 80%). For the model including the average of a symbolic dynamic variable, the area under the ROC curve was increased to 0.941 (95% = 0.897, 0.985), (sensitivity 88.71% and specificity 82.86%). In conclusion, symbolic dynamics, coupled with significant clinical and physical variables can help to prioritize polysomnographies in patients with a high probability of apnea. In addition, the processing of the HRV is a well established low cost and robust technique.

Significance of the impact of motion compensation on the variability of PET image features

NASA Astrophysics Data System (ADS)

Carles, M.; Bach, T.; Torres-Espallardo, I.; Baltas, D.; Nestle, U.; Martí-Bonmatí, L.

2018-03-01

In lung cancer, quantification by positron emission tomography/computed tomography (PET/CT) imaging presents challenges due to respiratory movement. Our primary aim was to study the impact of motion compensation implied by retrospectively gated (4D)-PET/CT on the variability of PET quantitative parameters. Its significance was evaluated by comparison with the variability due to (i) the voxel size in image reconstruction and (ii) the voxel size in image post-resampling. The method employed for feature extraction was chosen based on the analysis of (i) the effect of discretization of the standardized uptake value (SUV) on complementarity between texture features (TF) and conventional indices, (ii) the impact of the segmentation method on the variability of image features, and (iii) the variability of image features across the time-frame of 4D-PET. Thirty-one PET-features were involved. Three SUV discretization methods were applied: a constant width (SUV resolution) of the resampling bin (method RW), a constant number of bins (method RN) and RN on the image obtained after histogram equalization (method EqRN). The segmentation approaches evaluated were 40% of SUVmax and the contrast oriented algorithm (COA). Parameters derived from 4D-PET images were compared with values derived from the PET image obtained for (i) the static protocol used in our clinical routine (3D) and (ii) the 3D image post-resampled to the voxel size of the 4D image and PET image derived after modifying the reconstruction of the 3D image to comprise the voxel size of the 4D image. Results showed that TF complementarity with conventional indices was sensitive to the SUV discretization method. In the comparison of COA and 40% contours, despite the values not being interchangeable, all image features showed strong linear correlations (r  >  0.91, p\\ll 0.001 ). Across the time-frames of 4D-PET, all image features followed a normal distribution in most patients. For our patient cohort, the compensation of tumor motion did not have a significant impact on the quantitative PET parameters. The variability of PET parameters due to voxel size in image reconstruction was more significant than variability due to voxel size in image post-resampling. In conclusion, most of the parameters (apart from the contrast of neighborhood matrix) were robust to the motion compensation implied by 4D-PET/CT. The impact on parameter variability due to the voxel size in image reconstruction and in image post-resampling could not be assumed to be equivalent.

Computerized system for assessing heart rate variability.

PubMed

Frigy, A; Incze, A; Brânzaniuc, E; Cotoi, S

1996-01-01

The principal theoretical, methodological and clinical aspects of heart rate variability (HRV) analysis are reviewed. This method has been developed over the last 10 years as a useful noninvasive method of measuring the activity of the autonomic nervous system. The main components and the functioning of the computerized rhythm-analyzer system developed by our team are presented. The system is able to perform short-term (maximum 20 minutes) time domain HRV analysis and statistical analysis of the ventricular rate in any rhythm, particularly in atrial fibrillation. The performances of our system are demonstrated by using the graphics (RR histograms, delta RR histograms, RR scattergrams) and the statistical parameters resulted from the processing of three ECG recordings. These recordings are obtained from a normal subject, from a patient with advanced heart failure, and from a patient with atrial fibrillation.

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study.

PubMed

Walker, Martin; Basáñez, María-Gloria; Ouédraogo, André Lin; Hermsen, Cornelus; Bousema, Teun; Churcher, Thomas S

2015-01-16

Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens.

Using bioimpedance spectroscopy parameters as real-time feedback during tDCS.

PubMed

Nejadgholi, Isar; Caytak, Herschel; Bolic, Miodrag

2016-08-01

An exploratory analysis is carried out to investigate the feasibility of using BioImpedance Spectroscopy (BIS) parameters, measured on scalp, as real-time feedback during Transcranial Direct Current Stimulation (tDCS). TDCS is shown to be a potential treatment for neurological disorders. However, this technique is not considered as a reliable clinical treatment, due to the lack of a measurable indicator of treatment efficacy. Although the voltage that is applied on the head is very simple to measure during a tDCS session, changes of voltage are difficult to interpret in terms of variables that affect clinical outcome. BIS parameters are considered as potential feedback parameters, because: 1) they are shown to be associated with the DC voltage applied on the head, 2) they are interpretable in terms of conductive and capacitive properties of head tissues, 3) physical interpretation of BIS measurements makes them prone to be adjusted by clinically controllable variables, 4) BIS parameters are measurable in a cost-effective and safe way and do not interfere with DC stimulation. This research indicates that a quadratic regression model can predict the DC voltage between anode and cathode based on parameters extracted from BIS measurements. These parameters are extracted by fitting the measured BIS spectra to an equivalent electrical circuit model. The effect of clinical tDCS variables on BIS parameters needs to be investigated in future works. This work suggests that BIS is a potential method to be used for monitoring a tDCS session in order to adjust, tailor, or personalize tDCS treatment protocols.

Executive function impairments in fibromyalgia syndrome: Relevance of clinical variables and body mass index

PubMed Central

2018-01-01

Background Several investigations suggest the presence of deterioration of executive function in fibromyalgia syndrome (FMS). The study quantified executive functions in patients with FMS. A wide array of functions was assessed, including updating, shifting and inhibition, as well as decision making and mental planning. Moreover, clinical variables were investigated as possible mediators of executive dysfunction, including pain severity, psychiatric comorbidity, medication and body mass index (BMI). Methods Fifty-two FMS patients and 32 healthy controls completed a battery of 14 neuropsychological tests. Clinical interviews were conducted and the McGill Pain Questionnaire, Beck Depression Inventory, State-Trait Anxiety Inventory, Fatigue Severity Scale and Oviedo Quality of Sleep Questionnaire were presented. Results Patients performed poorer than controls on the Letter Number Sequencing, Arithmetic and Similarities subtests of the Wechsler Adult Intelligence Scale, the Spatial Span subtest of the Wechsler Memory Scale, an N-back task, a verbal fluency task, the Ruff Figural Fluency Test, the Inhibition score of the Stroop Test, the Inhibition and Shifting scores of the Five Digits Test, the Key Search Test and the Zoo Map Task. Moreover, patients exhibited less steep learning curves on the Iowa Gambling Task. Among clinical variables, BMI and pain severity explained the largest proportion of performance variance. Conclusions This study demonstrated impairments in executive functions of updating, shifting inhibition, decision making and planning in FMS. While the mediating role of pain in cognitive impairments in FMS had been previously established, the influence of BMI is a novel finding. Overweight and obesity should be considered by FMS researchers, and in the treatment of the condition. PMID:29694417

Modeling continuous covariates with a "spike" at zero: Bivariate approaches.

PubMed

Jenkner, Carolin; Lorenz, Eva; Becher, Heiko; Sauerbrei, Willi

2016-07-01

In epidemiology and clinical research, predictors often take value zero for a large amount of observations while the distribution of the remaining observations is continuous. These predictors are called variables with a spike at zero. Examples include smoking or alcohol consumption. Recently, an extension of the fractional polynomial (FP) procedure, a technique for modeling nonlinear relationships, was proposed to deal with such situations. To indicate whether or not a value is zero, a binary variable is added to the model. In a two stage procedure, called FP-spike, the necessity of the binary variable and/or the continuous FP function for the positive part are assessed for a suitable fit. In univariate analyses, the FP-spike procedure usually leads to functional relationships that are easy to interpret. This paper introduces four approaches for dealing with two variables with a spike at zero (SAZ). The methods depend on the bivariate distribution of zero and nonzero values. Bi-Sep is the simplest of the four bivariate approaches. It uses the univariate FP-spike procedure separately for the two SAZ variables. In Bi-D3, Bi-D1, and Bi-Sub, proportions of zeros in both variables are considered simultaneously in the binary indicators. Therefore, these strategies can account for correlated variables. The methods can be used for arbitrary distributions of the covariates. For illustration and comparison of results, data from a case-control study on laryngeal cancer, with smoking and alcohol intake as two SAZ variables, is considered. In addition, a possible extension to three or more SAZ variables is outlined. A combination of log-linear models for the analysis of the correlation in combination with the bivariate approaches is proposed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Liver Transplantation for Fulminant Hepatic Failure

PubMed Central

Farmer, Douglas G.; Anselmo, Dean M.; Ghobrial, R. Mark; Yersiz, Hasan; McDiarmid, Suzanne V.; Cao, Carlos; Weaver, Michael; Figueroa, Jesus; Khan, Khurram; Vargas, Jorge; Saab, Sammy; Han, Steven; Durazo, Francisco; Goldstein, Leonard; Holt, Curtis; Busuttil, Ronald W.

2003-01-01

Objective To analyze outcomes after liver transplantation (LT) in patients with fulminant hepatic failure (FHF) with emphasis on pretransplant variables that can potentially help predict posttransplant outcome. Summary Background Data FHF is a formidable clinical problem associated with a high mortality rate. While LT is the treatment of choice for irreversible FHF, few investigations have examined pretransplant variables that can potentially predict outcome after LT. Methods A retrospective review was undertaken of all patients undergoing LT for FHF at a single transplant center. The median follow-up was 41 months. Thirty-five variables were analyzed by univariate and multivariate analysis to determine their impact on patient and graft survival. Results Two hundred four patients (60% female, median age 20.2 years) required urgent LT for FHF. Before LT, the majority of patients were comatose (76%), on hemodialysis (16%), and ICU-bound. The 1- and 5-year survival rates were 73% and 67% (patient) and 63% and 57% (graft). The primary cause of patient death was sepsis, and the primary cause of graft failure was primary graft nonfunction. Univariate analysis of pre-LT variables revealed that 19 variables predicted survival. From these results, multivariate analysis determined that the serum creatinine was the single most important prognosticator of patient survival. Conclusions This study, representing one of the largest published series on LT for FHF, demonstrates a long-term survival of nearly 70% and develops a clinically applicable and readily measurable set of pretransplant factors that determine posttransplant outcome. PMID:12724633

Predictors of Full Enteral Feeding Achievement in Very Low Birth Weight Infants

PubMed Central

Corvaglia, Luigi; Fantini, Maria Pia; Aceti, Arianna; Gibertoni, Dino; Rucci, Paola; Baronciani, Dante; Faldella, Giacomo

2014-01-01

Background To elucidate the role of prenatal, neonatal and early postnatal variables in influencing the achievement of full enteral feeding (FEF) in very low birth weight (VLBW) infants and to determine whether neonatal intensive care units (NICUs) differ in this outcome. Methods Population-based retrospective cohort study using data on 1,864 VLBW infants drawn from the “Emilia-Romagna Perinatal Network” Registry from 2004 to 2009. The outcome of interest was time to FEF achievement. Eleven prenatal, neonatal and early postnatal variables and the study NICUs were selected as potential predictors of time to FEF. Parametric survival analysis was used to model time to FEF as a function of the predictors. Marginal effects were used to obtain adjusted estimates of median time to FEF for specific subgroups of infants. Results Lower gestational age, exclusive formula feeding, higher CRIB II score, maternal hypertension, cesarean delivery, SGA and PDA predicted delayed FEF. NICUs proved to be heterogeneous in terms of FEF achievement. Newborns with PDA had a 4.2 days longer predicted median time to FEF compared to those without PDA; newborns exclusively formula-fed had a 1.4 days longer time to FEF compared to those fed human milk. Conclusions The results of our study suggest that time to FEF is influenced by clinical variables and NICU-specific practices. Knowledge of the variables associated with delayed/earlier FEF achievement could help in improving specific aspects of routine clinical management of VLBW infants and to reduce practice variability. PMID:24647523

Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.

PubMed

Chase, J Geoffrey; Preiser, Jean-Charles; Dickson, Jennifer L; Pironet, Antoine; Chiew, Yeong Shiong; Pretty, Christopher G; Shaw, Geoffrey M; Benyo, Balazs; Moeller, Knut; Safaei, Soroush; Tawhai, Merryn; Hunter, Peter; Desaive, Thomas

2018-02-20

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.

Validating a Web-based Diabetes Education Program in continuing nursing education: knowledge and competency change and user perceptions on usability and quality

PubMed Central

2014-01-01

Background Nurses as the members of health care professionals need to improve their knowledge and competencies particularly in diabetes mellitus through continuing nursing education programs. E-learning is an indirect method of training that can meet nurses’ educational needs. This study is aimed at validating a web-based diabetes education program through measurement of nurses’ knowledge and clinical competency in diabetes and nurses’ perception about its usability and quality. Methods This Quasi-experimental research was conducted on a single group of 31 nurses employed in hospitals affiliated with Shiraz University of Medical Sciences. We used a 125 MCQ knowledge test and Objective Structured Clinical Exam (OSCE) to measure knowledge and clinical competency of nurses in diabetes before and after intervention. A Learning Management System (LMS) was designed to provide educational content in the form of 12 multimedia electronic modules, interactive tests; a forum and learning activities. Nurses were trained for two months in this system after which the post-test was administered. Each nurse completed two questionnaires for measurement of their perceptions on usability and quality. We used descriptive statistics for demographic and descriptive data analysis. Paired t-test was used to compare pre- and post-data using SPSS. Results The findings showed significant differences in knowledge scores (p < 0.001), total score of clinical competencies (p < 0.001), and all ten assessed clinical competencies. The range of ratings given by participants varied on the six usability variables of Web-based training (2.96-4.23 from 5) and eight quality variables of Web-based training (3.58-4.37 from 5). Conclusion Web-based education increased nurses’ knowledge and competencies in diabetes. They positively evaluated Web-based learning usability and quality. It is hoped that this course will have a positive clinical outcomes. PMID:26086025

Development of a dynamic quality assurance testing protocol for multisite clinical trial DCE-CT accreditation

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

Driscoll, B.; Keller, H.; Jaffray, D.

2013-08-15

Purpose: Credentialing can have an impact on whether or not a clinical trial produces useful quality data that is comparable between various institutions and scanners. With the recent increase of dynamic contrast enhanced-computed tomography (DCE-CT) usage as a companion biomarker in clinical trials, effective quality assurance, and control methods are required to ensure there is minimal deviation in the results between different scanners and protocols at various institutions. This paper attempts to address this problem by utilizing a dynamic flow imaging phantom to develop and evaluate a DCE-CT quality assurance (QA) protocol.Methods: A previously designed flow phantom, capable of producingmore » predictable and reproducible time concentration curves from contrast injection was fully validated and then utilized to design a DCE-CT QA protocol. The QA protocol involved a set of quantitative metrics including injected and total mass error, as well as goodness of fit comparison to the known truth concentration curves. An additional region of interest (ROI) sensitivity analysis was also developed to provide additional details on intrascanner variability and determine appropriate ROI sizes for quantitative analysis. Both the QA protocol and ROI sensitivity analysis were utilized to test variations in DCE-CT results using different imaging parameters (tube voltage and current) as well as alternate reconstruction methods and imaging techniques. The developed QA protocol and ROI sensitivity analysis was then applied at three institutions that were part of clinical trial involving DCE-CT and results were compared.Results: The inherent specificity of robustness of the phantom was determined through calculation of the total intraday variability and determined to be less than 2.2 ± 1.1% (total calculated output contrast mass error) with a goodness of fit (R{sup 2}) of greater than 0.99 ± 0.0035 (n= 10). The DCE-CT QA protocol was capable of detecting significant deviations from the expected phantom result when scanning at low mAs and low kVp in terms of quantitative metrics (Injected Mass Error 15.4%), goodness of fit (R{sup 2}) of 0.91, and ROI sensitivity (increase in minimum input function ROI radius by 146 ± 86%). These tests also confirmed that the ASIR reconstruction process was beneficial in reducing noise without substantially increasing partial volume effects and that vendor specific modes (e.g., axial shuttle) did not significantly affect the phantom results. The phantom and QA protocol were finally able to quickly (<90 min) and successfully validate the DCE-CT imaging protocol utilized at the three separate institutions of a multicenter clinical trial; thereby enhancing the confidence in the patient data collected.Conclusions: A DCE QA protocol was developed that, in combination with a dynamic multimodality flow phantom, allows the intrascanner variability to be separated from other sources of variability such as the impact of injection protocol and ROI selection. This provides a valuable resource that can be utilized at various clinical trial institutions to test conformance with imaging protocols and accuracy requirements as well as ensure that the scanners are performing as expected for dynamic scans.« less

Integrative analysis of gene expression and copy number alterations using canonical correlation analysis.

PubMed

Soneson, Charlotte; Lilljebjörn, Henrik; Fioretos, Thoas; Fontes, Magnus

2010-04-15

With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia. Using the correlation-maximizing methods, regularized dual CCA and PCA+CCA, we show that without pre-selection of known disease-relevant genes, and without using information about clinical class membership, an exploratory analysis singles out two patient groups, corresponding to well-known leukemia subtypes. Furthermore, the variables showing the highest relevance to the extracted features agree with previous biological knowledge concerning copy number alterations and gene expression changes in these subtypes. Finally, the correlation-maximizing methods are shown to yield results which are more biologically interpretable than those resulting from a covariance-maximizing method, and provide different insight compared to when each variable set is studied separately using PCA. We conclude that regularized dual CCA as well as PCA+CCA are useful methods for exploratory analysis of paired genetic data sets, and can be efficiently implemented also when the number of variables is very large.

Causal inference from observational data.

PubMed

Listl, Stefan; Jürges, Hendrik; Watt, Richard G

2016-10-01

Randomized controlled trials have long been considered the 'gold standard' for causal inference in clinical research. In the absence of randomized experiments, identification of reliable intervention points to improve oral health is often perceived as a challenge. But other fields of science, such as social science, have always been challenged by ethical constraints to conducting randomized controlled trials. Methods have been established to make causal inference using observational data, and these methods are becoming increasingly relevant in clinical medicine, health policy and public health research. This study provides an overview of state-of-the-art methods specifically designed for causal inference in observational data, including difference-in-differences (DiD) analyses, instrumental variables (IV), regression discontinuity designs (RDD) and fixed-effects panel data analysis. The described methods may be particularly useful in dental research, not least because of the increasing availability of routinely collected administrative data and electronic health records ('big data'). © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Systematic evaluation of a targeted gene capture sequencing panel for molecular diagnosis of retinitis pigmentosa

PubMed Central

Ma, Yuanyuan; Chiang, Pei-Wen; Zhong, Jing; Liu, Xuyang; Asan; Wu, Jing; Su, Yan; Li, Xin; Deng, Jianlian; Huang, Yingping; Zhang, Xinxin; Li, Yang; Fan, Ning; Wang, Ying; Tang, Lihui; Shen, Jinting; Chen, Meiyan; Zhang, Xiuqing; Te, Deng; Banerjee, Santasree; Liu, Hui; Qi, Ming; Yi, Xin

2018-01-01

Background Inherited eye diseases are major causes of vision loss in both children and adults. Inherited eye diseases are characterized by clinical variability and pronounced genetic heterogeneity. Genetic testing may provide an accurate diagnosis for ophthalmic genetic disorders and allow gene therapy for specific diseases. Methods A targeted gene capture panel was designed to capture exons of 283 inherited eye disease genes including 58 known causative retinitis pigmentosa (RP) genes. 180 samples were tested with this panel, 68 were previously tested by Sanger sequencing. Systematic evaluation of our method and comprehensive molecular diagnosis were carried on 99 RP patients. Results 96.85% targeted regions were covered by at least 20 folds, the accuracy of variants detection was 99.994%. In 4 of the 68 samples previously tested by Sanger sequencing, mutations of other diseases not consisting with the clinical diagnosis were detected by next-generation sequencing (NGS) not Sanger. Among the 99 RP patients, 64 (64.6%) were detected with pathogenic mutations, while in 3 patients, it was inconsistent between molecular diagnosis and their initial clinical diagnosis. After revisiting, one patient’s clinical diagnosis was reclassified. In addition, 3 patients were found carrying large deletions. Conclusions We have systematically evaluated our method and compared it with Sanger sequencing, and have identified a large number of novel mutations in a cohort of 99 RP patients. The results showed a sufficient accuracy of our method and suggested the importance of molecular diagnosis in clinical diagnosis. PMID:29641573

A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials.

PubMed

Verma, Nishant; Beretvas, S Natasha; Pascual, Belen; Masdeu, Joseph C; Markey, Mia K

2018-03-14

Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer's disease. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Improving patient outcomes in fibrous dysplasia/McCune-Albright syndrome: an international multidisciplinary workshop to inform an international partnership.

PubMed

Boyce, A M; Turner, A; Watts, L; Forestier-Zhang, L; Underhill, A; Pinedo-Villanueva, R; Monsell, F; Tessaris, D; Burren, C; Masi, L; Hamdy, N; Brandi, M L; Chapurlat, R; Collins, M T; Javaid, Muhammad Kassim

2017-12-01

To develop consensus on improving the management of patients, we convened an international workshop involving patients, clinicians, and researchers. Key findings included the diagnostic delay and variability in subsequent management with agreement to develop an international natural history study. We now invite other stakeholders to join the partnership. The aim of this study was develop a consensus on how to improve the management of patients with fibrous dysplasia and prioritize areas for research METHODS: An international workshop was held over 3 days involving patients, clinicians, and researchers. Each day had a combination of formal presentations and facilitated discussions that focused on clinical pathways and research. The patient workshop day highlighted the variability of patients' experience in getting a diagnosis, the knowledge of general clinical staff, and understanding long-term outcomes. The research workshop prioritized collaborations that improved understanding of the contemporary natural history of fibrous dysplasia/McCune-Albright syndrome (FD/MAS). The clinical workshop outlined the key issues around diagnostics, assessment of severity, treatment and monitoring of patients. In spite of advances in understanding the genetic and molecular underpinnings of fibrous dysplasia/McCune-Albright syndrome, clinical management remains a challenge. From the workshop, a consensus was reached to create an international, multi-stakeholder partnership to advance research and clinical care in FD/MAS. We invite other stakeholders to join the partnership.

Reduced dose to urethra and rectum with the use of variable needle spacing in prostate brachytherapy: a potential role for robotic technology

PubMed Central

Vyas, Shilpa; Le, Yi; Zhang, Zhe; Armour, Woody

2015-01-01

Purpose Several robotic delivery systems for prostate brachytherapy are under development or in pre-clinical testing. One of the features of robotic brachytherapy is the ability to vary spacing of needles at non-fixed intervals. This feature may play an important role in prostate brachytherapy, which is traditionally template-based with fixed needle spacing of 0.5 cm. We sought to quantify potential reductions in the dose to urethra and rectum by utilizing variable needle spacing, as compared to fixed needle spacing. Material and methods Transrectal ultrasound images from 10 patients were used by 3 experienced planners to create 120 treatment plans. Each planner created 4 plan variations per patient with respect to needle positions: 125I fixed spacing, 125I variable spacing, 103Pd fixed spacing, and 103Pd variable spacing. The primary planning objective was to achieve a prostate V100 of 100% while minimizing dose to urethra and rectum. Results All plans met the objective of achieving prostate V100 of 100%. Combined results for all plans show statistically significant improvements in all assessed dosimetric variables for urethra (Umax, Umean, D30, D5) and rectum (Rmax, Rmean, RV100) when using variable spacing. The dose reductions for mean and maximum urethra dose using variable spacing had p values of 0.011 and 0.024 with 103Pd, and 0.007 and 0.029 with 125I plans. Similarly dose reductions for mean and maximum rectal dose using variable spacing had p values of 0.007 and 0.052 with 103Pd, and 0.012 and 0.037 with 125I plans. Conclusions The variable needle spacing achievable by the use of robotics in prostate brachytherapy allows for reductions in both urethral and rectal planned doses while maintaining prostate dose coverage. Such dosimetric advantages have the potential in translating to significant clinical benefits with the use of robotic brachytherapy. PMID:26622227

3D.07: CORRELATION BETWEEN THE ARTERIAL PRESSURE VARIABILITY ESTIMATED AT CLINICS, MAPA AND AMPA.

PubMed

Abellan-Huerta, J; García-Escribano, I A; Soto, R M; Leal, M; Torres, A; Guerrero, B; Melgar, A C; Soto, M; Soria, F; Abellan-Aleman, J

2015-06-01

To measure the variability (VB) of the arterial pressure (AP) with the use of serial measurements at the clinics (VBCLIN), with 24 h ambulatory monitoring (MAPA) (VBMAPA) and home automonitoring -AMPA- (VBAMPA) and to estimate a relationship among each method. This is an observational, descriptive and transversal study assessed with 91 hypertensive patients in treatment and stable with AP < 160/100 mmHg for the last 3 months. Patients between 50-80 years old were included. The VB of the AP was defined as the standard deviation for both, diastolic and systolic pressures. The different VB were determined with the use of tensiometers and validated AP monitors. VBCLIN was estimated from 8 measurements per week in the clinics. A 24 h MAPA was assessed to all the patients included in the study in order to obtain the VBMAPA and an AMPA in two non-consecutive weeks to obtain the VBAMPA (total of 54 measurements). 91 patients with 66 ± 7.7 years old and 58.2% males were recruited. AP values were 134 ± 14/82 ± 10 mmHg for systolic and diastolic APCLIN, respectively. AP values were 122 ± 17 / 68 ± 12 mmHg for systolic and diastolic APMAPA, respectively. AP values were 125 ± 13/75 ± 7 mmHg for systolic and diastolic APAMPA, respectively. The systolic VB for the three above methods was significantly correlated being maximal between VBCLIN and VBAMPA (r = 0.45; 0 < 0.001) and lower for VBCLIN and VBMAPA (r = 0.25; p = 0.015) and VBMAPA and VBAMPA (r = 0.32; p = 0.002). Means of the systolic AP between each method were statistically different except for VBCLIN and VBAMPA. Corresponding to diastolic AP VB, we could only found a significant relationship between VBCLIN and VBAMPA (r = 0.243; p = 0.021). The correlation between VB of AP measured in the clinics, with AMPA and MAPA methods is weak. This observation suggests that these are not interchangeable methodologies. Future studies focused on the relationship between VB -with different methods- and vascular target organ damage would be of great help in order to define the best analytical method.

Management of pericardial fluid in blunt trauma: variability in practice and predictors of operative outcome in patients with computed tomography evidence of pericardial fluid

PubMed Central

Witt, Cordelie E.; Linnau, Ken F.; Maier, Ronald V.; Rivara, Frederick P.; Vavilala, Monica S.; Bulger, Eileen M.; Arbabi, Saman

2017-01-01

Background The objectives of this study were to assess current variability in management preferences for blunt trauma patients with pericardial fluid, and to identify characteristics associated with operative intervention for patients with pericardial fluid on admission computed tomography (CT) scan. Methods This was a mixed-methods study of blunt trauma patients with pericardial fluid. The first portion was a research survey of members of the Eastern Association for the Surgery of Trauma conducted in 2016, in which surgeons were presented with four clinical scenarios of blunt trauma patients with pericardial fluid. The second portion of the study was a retrospective evaluation of all blunt trauma patients ≥14 years treated at our Level I trauma center between 1/1/2010 and 11/1/2015 with pericardial fluid on admission CT scan. Results For the survey portion of our study, 393 surgeons responded (27% response rate). There was significant variability in management preferences for scenarios depicting trace pericardial fluid on CT with concerning hemodynamics, and for scenarios depicting hemopericardium intraoperatively. For the separate retrospective portion of our study, we identified 75 blunt trauma patients with pericardial fluid on admission CT scan. Seven underwent operative management; six of these had hypotension and/or electrocardiogram changes. In multivariable analysis, pericardial fluid amount was a significant predictor of receiving pericardial window (relative risk for one category increase in pericardial fluid amount: 3.99, 95% CI 1.47-10.81) but not of mortality. Conclusions There is significant variability in management preferences for patients with pericardial fluid from blunt trauma, indicating a need for evidence-based research. Our institutional data suggest that patients with minimal to small amounts of pericardial fluid without concerning clinical findings may be observed. Patients with moderate to large amounts of pericardial fluid who are clinically stable with normal hemodynamics may also appear appropriate for observation, although confirmation in larger studies is needed. Patients with hemodynamic instability should undergo operative exploration. Level of Evidence Level IV, Therapeutic/Care Management PMID:28129264

Bayesian functional integral method for inferring continuous data from discrete measurements.

PubMed

Heuett, William J; Miller, Bernard V; Racette, Susan B; Holloszy, John O; Chow, Carson C; Periwal, Vipul

2012-02-08

Inference of the insulin secretion rate (ISR) from C-peptide measurements as a quantification of pancreatic β-cell function is clinically important in diseases related to reduced insulin sensitivity and insulin action. ISR derived from C-peptide concentration is an example of nonparametric Bayesian model selection where a proposed ISR time-course is considered to be a "model". An inferred value of inaccessible continuous variables from discrete observable data is often problematic in biology and medicine, because it is a priori unclear how robust the inference is to the deletion of data points, and a closely related question, how much smoothness or continuity the data actually support. Predictions weighted by the posterior distribution can be cast as functional integrals as used in statistical field theory. Functional integrals are generally difficult to evaluate, especially for nonanalytic constraints such as positivity of the estimated parameters. We propose a computationally tractable method that uses the exact solution of an associated likelihood function as a prior probability distribution for a Markov-chain Monte Carlo evaluation of the posterior for the full model. As a concrete application of our method, we calculate the ISR from actual clinical C-peptide measurements in human subjects with varying degrees of insulin sensitivity. Our method demonstrates the feasibility of functional integral Bayesian model selection as a practical method for such data-driven inference, allowing the data to determine the smoothing timescale and the width of the prior probability distribution on the space of models. In particular, our model comparison method determines the discrete time-step for interpolation of the unobservable continuous variable that is supported by the data. Attempts to go to finer discrete time-steps lead to less likely models. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Probabilistic multiple sclerosis lesion classification based on modeling regional intensity variability and local neighborhood information.

PubMed

Harmouche, Rola; Subbanna, Nagesh K; Collins, D Louis; Arnold, Douglas L; Arbel, Tal

2015-05-01

In this paper, a fully automatic probabilistic method for multiple sclerosis (MS) lesion classification is presented, whereby the posterior probability density function over healthy tissues and two types of lesions (T1-hypointense and T2-hyperintense) is generated at every voxel. During training, the system explicitly models the spatial variability of the intensity distributions throughout the brain by first segmenting it into distinct anatomical regions and then building regional likelihood distributions for each tissue class based on multimodal magnetic resonance image (MRI) intensities. Local class smoothness is ensured by incorporating neighboring voxel information in the prior probability through Markov random fields. The system is tested on two datasets from real multisite clinical trials consisting of multimodal MRIs from a total of 100 patients with MS. Lesion classification results based on the framework are compared with and without the regional information, as well as with other state-of-the-art methods against the labels from expert manual raters. The metrics for comparison include Dice overlap, sensitivity, and positive predictive rates for both voxel and lesion classifications. Statistically significant improvements in Dice values ( ), for voxel-based and lesion-based sensitivity values ( ), and positive predictive rates ( and respectively) are shown when the proposed method is compared to the method without regional information, and to a widely used method [1]. This holds particularly true in the posterior fossa, an area where classification is very challenging. The proposed method allows us to provide clinicians with accurate tissue labels for T1-hypointense and T2-hyperintense lesions, two types of lesions that differ in appearance and clinical ramifications, and with a confidence level in the classification, which helps clinicians assess the classification results.

Educating the ambulance technician, paramedic, and clinical supervisor: using factor analysis to inform the curriculum

PubMed Central

Kilner, T

2004-01-01

Methods: Data generated by a Delphi study investigating the desirable attributes of ambulance technician, paramedic, and clinical supervisor were subject to factor analysis to explore inter-relations between the variables or desirable attributes. Variables that loaded onto any factor at a correlation level of >0.3 were included in the analysis. Results: Three factors emerged in each of the occupational groups. In respect of the ambulance technician these factors may be described as; core professional skills, individual and collaborative approaches to health and safety, and the management of self and clinical situations. For the paramedic the themes are; core professional skills, management of self and clinical situations, and approaches to health and safety. For the clinical supervisor there is again a theme described as core professional skills, with a further two themes described as role model and lifelong learning. Conclusions: The profile of desirable attributes emerging from this study are remarkably similar to the generic benchmark statements for health care programmes outlined by the Quality Assurance Agency for Higher Education. It seems that a case is emerging for a revision of the curriculum currently used for the education and training of ambulance staff, which is more suited to a consumer led health service and which reflects the broader professional base seen in programmes associated with other healthcare professions. This study has suggested outline content, and module structure for the education of the technician, paramedic, and clinical supervisor, based on empirical evidence. PMID:15107389

The correlation between organizational justice and trust among employees of rehabilitation clinics in hospitals of Ahvaz, Iran

PubMed Central

Khiavi, Farzad Faraji; Shakhi, Kamal; Dehghani, Roohallah; Zahiri, Mansour

2016-01-01

Introduction Organizational justice is an intricate concept that refers to fair and ethical conduct of individuals within organizations. No research has been conducted on the variables associated with organizational justice in rehabilitation clinics. Thus, the aim of this research was to determine the correlation between organizational justice and organizational trust among the employees of rehabilitation clinics in hospitals of Ahvaz, Iran. Methods This was a cross-sectional research, and it was conducted on 140 rehabilitation staff members of hospital clinics in Ahvaz. The data were gathered using organizational justice and trust questionnaires. The data were analyzed using the independent-samples t-test, ANOVA, and Pearson’s product-moment correlation SPSS software. Results Significant correlations between procedure and interaction justice and organizational trust were identified (p < 0.001). Distributive justice showed small correlation with trust (r = 0.25, p < 0.021). Organizational justice was significantly associated with organizational trust (r = 0.42, p < 0.001). Organizational justice was not significantly related to any demographic variable (p > 0.05). Conclusion There was a positive, medium, and significant correlation between organizational justice and trust. It is suggested that rehabilitation clinics’ managers develop plans to increase their organizational justice subscales in order to develop organizational trust among their employees. PMID:27053997

Low to high frequency ratio of heart rate variability spectra fails to describe sympatho-vagal balance in cardiac patients.

PubMed

Milicević, Goran

2005-06-01

Heart rate variability (HRV) reflects an influence of autonomic nervous system on heart work. In healthy subjects, ratio between low and high frequency components (LF/HF ratio) of HRV spectra represents a measure of sympatho-vagal balance. The ratio was defined by the authorities as an useful clinical tool, but it seems that it fails to summarise sympatho-vagal balance in a clinical setting. Value of the method was re-evaluated in several categories of cardiac patients. HRV was analysed from 24-hour Holter ECGs in 132 healthy subjects, and 2159 cardiac patients dichotomised by gender, median of age, diagnosis of myocardial infarction or coronary artery surgery, left ventricular systolic function and divided by overall HRV into several categories. In healthy subjects, LF/HF ratio correlated with overall HRV negatively, as expected. The paradoxical finding was obtained in cardiac patients; the lower the overall HRV and the time-domain indices of vagal modulation activity were the lower the LF/HF ratio was. If used as a measure of sympatho-vagal balance, long-term recordings of LF/HF ratio contradict to clinical finding and time-domain HRV indices in cardiac patients. The ratio cannot therefore be used as a reliable marker of autonomic activity in a clinical setting.

Pulmonary atelectasis in newborns with clinically treatable diseases who are on mechanical ventilation: clinical and radiological aspects

PubMed Central

Dominguez, Mariana Chiaradia; Alvares, Beatriz Regina

2018-01-01

Objective To analyze the radiological aspects of pulmonary atelectasis in newborns on mechanical ventilation and treated in an intensive care unit, associating the characteristics of atelectasis with the positioning of the head and endotracheal tube seen on the chest X-ray, as well as with the clinical variables. Materials and Methods This was a retrospective cross-sectional study of 60 newborns treated between 1985 and 2015. Data were collected from medical records and radiology reports. To identify associations between variables, we used Fisher's exact test. The level of significance was set at p < 0.05. Results The clinical characteristics associated with improper positioning of the endotracheal tube were prematurity and a birth weight of less than 1000 g. Among the newborns evaluated, the most common comorbidity was hyaline membrane disease. Atelectasis was seen most frequently in the right upper lobe, although cases of total atelectasis were more common in the left lung. Malpositioning of the head showed a trend toward an association with atelectasis in the left upper lobe. Conclusion Pulmonary atelectasis is a common complication in newborns on mechanical ventilation. Radiological evaluation of the endotracheal tube placement provides relevant information for the early correction of this condition. PMID:29559762

Performance Evaluation of an Automated ELISA System for Alzheimer's Disease Detection in Clinical Routine.

PubMed

Chiasserini, Davide; Biscetti, Leonardo; Farotti, Lucia; Eusebi, Paolo; Salvadori, Nicola; Lisetti, Viviana; Baschieri, Francesca; Chipi, Elena; Frattini, Giulia; Stoops, Erik; Vanderstichele, Hugo; Calabresi, Paolo; Parnetti, Lucilla

2016-07-22

The variability of Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers undermines their full-fledged introduction into routine diagnostics and clinical trials. Automation may help to increase precision and decrease operator errors, eventually improving the diagnostic performance. Here we evaluated three new CSF immunoassays, EUROIMMUNtrademark amyloid-β 1-40 (Aβ1-40), amyloid-β 1-42 (Aβ1-42), and total tau (t-tau), in combination with automated analysis of the samples. The CSF biomarkers were measured in a cohort consisting of AD patients (n = 28), mild cognitive impairment (MCI, n = 77), and neurological controls (OND, n = 35). MCI patients were evaluated yearly and cognitive functions were assessed by Mini-Mental State Examination. The patients clinically diagnosed with AD and MCI were classified according to the CSF biomarkers profile following NIA-AA criteria and the Erlangen score. Technical evaluation of the immunoassays was performed together with the calculation of their diagnostic performance. Furthermore, the results for EUROIMMUN Aβ1-42 and t-tau were compared to standard immunoassay methods (INNOTESTtrademark). EUROIMMUN assays for Aβ1-42 and t-tau correlated with INNOTEST (r = 0.83, p < 0.001 for both) and allowed a similar interpretation of the CSF profiles. The Aβ1-42/Aβ1-40 ratio measured with EUROIMMUN was the best parameter for AD detection and improved the diagnostic accuracy of Aβ1-42 (area under the curve = 0.93). In MCI patients, the Aβ1-42/Aβ1-40 ratio was associated with cognitive decline and clinical progression to AD.The diagnostic performance of the EUROIMMUN assays with automation is comparable to other currently used methods. The variability of the method and the value of the Aβ1-42/Aβ1-40 ratio in AD diagnosis need to be validated in large multi-center studies.

Accounting for the sedative and analgesic effects of medication changes during patient participation in clinical research studies: measurement development and application to a sample of institutionalized geriatric patients.

PubMed

Sloane, Philip; Ivey, Jena; Roth, Mary; Roederer, Mary; Williams, Christianna S

2008-03-01

To date, no system has been published that allows investigators to adjust for the overall sedative and/or analgesic effects of medications, or changes in medications, in clinical trial participants for whom medication use cannot be controlled. This is common in clinical trials of behavioral and complementary/alternative therapies, and in research involving elderly or chronically ill patients for whom ongoing medical care continues during the trial. This paper describes the development, and illustrates the use, of a method we developed to address this issue, in which we generate single continuous variables to represent the daily sedative and analgesic loads of multiple medications. Medications for 90 study participants in a clinical trial of a nonpharmacological intervention were abstracted from medication administration records across multiple treatment periods. An expert panel of three academic clinical pharmacists and a geriatrician met to develop a system by which each study medication could be assigned a sedative and analgesic effect rating. The two measures, when applied to data on 90 institutionalized persons with Alzheimer's disease, resulted in variables with moderately skewed distributions that are consistent with the clinical profile of analgesia and sedation use in long-term care populations. The average study participant received 1.89 analgesic medications per day and had a daily analgesic load of 2.96; the corresponding figures for sedation were 2.07 daily medications and an average daily load of 11.41. A system of classifying the sedative and analgesic effects of non-study medications was created that divides drugs into categories based on the strength of their effects and assigns a rating to express overall sedative and analgesic effects. These variables may be useful in comparing patients and populations, and to control for drug effects in future studies.

Efficacy and toxicity differences in lung cancer populations in the era of clinical trials globalization: the 'common arm' approach.

PubMed

Mack, Philip C; Gandara, David R; Lara, Primo N

2012-12-01

Historically, notable variability has been observed in clinical trial outcomes between different regions and populations worldwide, even when employing the same cytotoxic regimen in lung cancer. These divergent results underscore the inherent challenges in interpreting trials conducted abroad and raise questions regarding the general applicability of transnational clinical trials. Various reasons have been postulated to account for these differences in efficacy and toxicity, including trial design, eligibility criteria, patient demographics and, perhaps most intriguingly, population-related pharmacogenomics. However, without methodology to control for such variables, these hypotheses remain largely untested. The authors previously developed the 'common arm' approach in order to directly compare efficacy and toxicity results of trials simultaneously performed in different countries. By standardizing clinical trial-associated variables such as treatment regimens (dose, schedule, and so on), eligibility, staging, response and toxicity criteria, this approach has the potential to determine the underlying reasons for divergences in trial outcomes across countries, and whether population-associated polymorphisms contribute to these differences. In the past decade, Japanese and US investigators have applied the common arm analytic method to trials in both extensive-stage small-cell lung cancer (SCLC) and advanced nonSCLC. In the SCLC analysis, a comparison of the cisplatin/irinotecan arms from both trials revealed significant differences in response rates and overall survival. Significant differences were also observed in the distribution of gender and performance status. The common arm analysis in nonSCLC included two trials from Japan and one from the USA, each containing a 'common' carboplatin/paclitaxel arm. Clinical results were similar in the two Japanese trials, but were significantly different from the US trial with regard to survival, neutropenia, febrile neutropenia and anemia. The underlying basis for these divergent outcomes is discussed. The common arm methodology provides a template for identifying and interpreting patient outcome differences across populations, and is an instructive lesson in the burgeoning era of clinical trials globalization.

Network Analysis of Associations between Serum Interferon Alpha Activity, Autoantibodies, and Clinical Features in Systemic Lupus Erythematosus

PubMed Central

Weckerle, Corinna E.; Franek, Beverly S.; Kelly, Jennifer A.; Kumabe, Marissa; Mikolaitis, Rachel A.; Green, Stephanie L.; Utset, Tammy O.; Jolly, Meenakshi; James, Judith A.; Harley, John B.; Niewold, Timothy B.

2010-01-01

Background Interferon-alpha (IFN-α) is a primary pathogenic factor in systemic lupus erythematosus (SLE), and high IFN-α levels may be associated with particular clinical manifestations. The prevalence of individual clinical and serologic features differs significantly by ancestry. We used multivariate and network analyses to detect associations between clinical and serologic disease manifestations and serum IFN-α activity in a large diverse SLE cohort. Methods 1089 SLE patients were studied (387 African-American, 186 Hispanic-American, and 516 European-American). Presence or absence of ACR clinical criteria for SLE, autoantibodies, and serum IFN-α activity data were analyzed in univariate and multivariate models. Iterative multivariate logistic regression was performed in each background separately to establish the network of associations between variables that were independently significant following Bonferroni correction. Results In all ancestral backgrounds, high IFN-α activity was associated with anti-Ro and anti-dsDNA antibodies (p-values 4.6×10−18 and 2.9 × 10−16 respectively). Younger age, non-European ancestry, and anti-RNP were also independently associated with increased serum IFN-α activity (p≤6.7×10−4). We found 14 unique associations between variables in network analysis, and only 7 of these associations were shared by more than one ancestral background. Associations between clinical criteria were different in different ancestral backgrounds, while autoantibody-IFN-α relationships were similar across backgrounds. IFN-α activity and autoantibodies were not associated with ACR clinical features in multivariate models. Conclusions Serum IFN-α activity was strongly and consistently associated with autoantibodies, and not independently associated with clinical features in SLE. IFN-α may be more relevant to humoral tolerance and initial pathogenesis than later clinical disease manifestations. PMID:21162028

Reduced susceptibility of clinical strains of Mycobacterium tuberculosis to reactive nitrogen species promotes survival in activated macrophages

PubMed Central

Idh, Jonna; Andersson, Blanka; Lerm, Maria; Raffetseder, Johanna; Eklund, Daniel; Woksepp, Hanna; Werngren, Jim; Mansjö, Mikael; Sundqvist, Tommy; Stendahl, Olle

2017-01-01

Background Drugs such as isoniazid (INH) and pretomanid (PRT), used against Mycobacterium tuberculosis are active partly through generation of reactive nitrogen species (RNS). The aim of this study was to explore variability in intracellular susceptibility to nitric oxide (NO) in clinical strains of M. tuberculosis. Method Luciferase-expressing clinical M. tuberculosis strains with or without INH resistance were exposed to RNS donors (DETA/NO and SIN-1) in broth cultures and bacterial survival was analysed by luminometry. NO-dependent intracellular killing in a selection of strains was assessed in interferon gamma/lipopolysaccharide-activated murine macrophages using the NO inhibitor L-NMMA. Results When M. tuberculosis H37Rv was compared to six clinical isolates and CDC1551, three isolates with inhA mediated INH resistance showed significantly reduced NO-susceptibility in broth culture. All strains showed a variable but dose-dependent susceptibility to RNS donors. Two clinical isolates with increased susceptibility to NO exposure in broth compared to H37Rv were significantly inhibited by activated macrophages whereas there was no effect on growth inhibition when activated macrophages were infected by clinical strains with higher survival to NO exposure in broth. Furthermore, the most NO-tolerant clinical isolate showed increased resistance to PRT both in broth culture and the macrophage model compared to H37Rv in the absence of mutational resistance in genes associated to reduced susceptibility against PRT or NO. Conclusion In a limited number of clinical M. tuberculosis isolates we found a significant difference in susceptibility to NO between clinical isolates, both in broth cultures and in macrophages. Our results indicate that mycobacterial susceptibility to cellular host defence mechanisms such as NO need to be taken into consideration when designing new therapeutic strategies. PMID:28704501

Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

PubMed Central

Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

2015-01-01

Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression

PubMed Central

Shimizu, Yu; Yoshimoto, Junichiro; Takamura, Masahiro; Okada, Go; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS) regression to resting-state functional magnetic resonance imaging (rs-fMRI) data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area. PMID:28700672

[Modulating variables of work disability in depressive disorders].

PubMed

Catalina Romero, C; Cabrera Sierra, M; Sainz Gutiérrez, J C; Barrenechea Albarrán, J L; Madrid Conesa, A; Calvo Bonacho, E

2011-01-01

To describe the duration of sickness absence in unipolar depression and to determine the relationship of demographic, job-related and clinical variables with length of temporary work disability in depressive disorders. Prospective observational study. A total of 1,292 subjects with depressive disorder diagnosis (ICD-9-CM) were selected claiming sick leave in an Occupational Diseases and Accident sat Work Insurance Scheme (sampling on successive occasions). Descriptive analyses of sickness absence duration, and bivariate (median test) and multivariate analysis (logistic regression) were performed to find relationships between demographic, job-related and clinical variables. Mean duration of sickness absence episodes due to a depressive disorder was 120 days. After multivariate analyses, female sex (p < 0.01), higher age (p < 0.01), lower educational level (p < 0.01), method of payment according to whether self-employed or unemployed workers (p < 0.01) and being referred to both psychiatrist and psychologist (p < 0.01) remained significantly associated with sick leave length. These findings confirm a strong association of depression with long periods of work disability and high absenteeism, and also suggest the need for improvements in functional ability assessment and promotion, treatment and referral of depressed patients. Copyright © 2010 SECA. Published by Elsevier Espana. All rights reserved.

A Description of Weekend Physiotherapy Services in Three Tertiary Hospitals in the Greater Toronto Area

PubMed Central

Hill, Kylie

2010-01-01

ABSTRACT Purpose: The aims of this study were (1) to describe the cardiorespiratory physiotherapy weekend service (PWS) at three tertiary hospitals in the Greater Toronto Area (GTA) and (2) to compare measures of staff burden among the clinical service areas in one of the hospitals that had a programme-based management structure. Method: Two focus-group meetings were held with physiotherapists from hospitals within the GTA. Thereafter, variables characterizing the PWS were collected over 8 months, using a standardized data-collection form. Results: A total of 632 data-collection forms were received. Response rates exceeded 75% at each hospital. Workload variables, including the number of patient visits, new referrals per hour, and the proportion of staff completing unpaid overtime, differed between the hospitals (p<0.002). There was no difference in any variable when data were compared between Saturday, Sunday, and statutory holidays (p>0.13). Workload measures varied between clinical service areas at the hospital that provided PWS using a programme-based approach. Conclusions: These findings highlight the important shortcomings of a programme-based management approach to providing PWS and may constitute a catalyst for change. PMID:21359048

Use of personalized Dynamic Treatment Regimes (DTRs) and Sequential Multiple Assignment Randomized Trials (SMARTs) in mental health studies

PubMed Central

Liu, Ying; ZENG, Donglin; WANG, Yuanjia

2014-01-01

Summary Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each point where a clinical decision is made based on each patient’s time-varying characteristics and intermediate outcomes observed at earlier points in time. The complexity, patient heterogeneity, and chronicity of mental disorders call for learning optimal DTRs to dynamically adapt treatment to an individual’s response over time. The Sequential Multiple Assignment Randomized Trial (SMARTs) design allows for estimating causal effects of DTRs. Modern statistical tools have been developed to optimize DTRs based on personalized variables and intermediate outcomes using rich data collected from SMARTs; these statistical methods can also be used to recommend tailoring variables for designing future SMART studies. This paper introduces DTRs and SMARTs using two examples in mental health studies, discusses two machine learning methods for estimating optimal DTR from SMARTs data, and demonstrates the performance of the statistical methods using simulated data. PMID:25642116

Variable threshold method for ECG R-peak detection.

PubMed

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

Testing the 4Rs and 2Ss Multiple Family Group intervention: study protocol for a randomized controlled trial.

PubMed

Acri, Mary; Hamovitch, Emily; Mini, Maria; Garay, Elene; Connolly, Claire; McKay, Mary

2017-12-04

Oppositional defiant disorder (ODD) is a major mental health concern and highly prevalent among children living in poverty-impacted communities. Despite that treatments for ODD are among the most effective, few children living in poverty receive these services due to substantial barriers to access, as well as difficulties in the uptake and sustained adoption of evidence-based practices (EBPs) in community settings. The purpose of this study is to examine implementation processes that impact uptake of an evidence-based practice for childhood ODD, and the impact of a Clinic Implementation Team (CIT)-driven structured adaptation to enhance its fit within the public mental health clinic setting. This study, a Hybrid Type II effectiveness-implementation research trial, blends clinical effectiveness and implementation research methods to examine the impact of the 4Rs and 2Ss Multiple Family Group (MFG) intervention, family level mediators of child outcomes, clinic/provider-level mediators of implementation, and the impact of CITs on uptake and long-term utilization of this model. All New York City public outpatient mental health clinics have been invited to participate. A sampling procedure that included randomization at the agency level and a sub-study to examine the impact of clinic choice upon outcomes yielded a distribution of clinics across three study conditions. Quantitative data measuring child outcomes, organizational factors and implementation fidelity will be collected from caregivers and providers at baseline, 8, and 16 weeks from baseline, and 6 months from treatment completion. The expected participation is 134 clinics, 268 providers, and 2688 caregiver/child dyads. We will use mediation analysis with a multi-level Structural Equation Modeling (SEM) (MSEM including family level variables, provider variables, and clinic variables), as well as mediation tests to examine study hypotheses. The aim of the study is to generate knowledge about effectiveness and mediating factors in the treatment of ODDs in children in the context of family functioning, and to propose an innovative approach to the adaptation and implementation of new treatment interventions within clinic settings. The proposed CIT adaptation and implementation model has the potential to enhance implementation and sustainability, and ultimately increase the extent to which effective interventions are available and can impact children and families in need of services for serious behavior problems. ClinicalTrials.gov, ID: NCT02715414 . Registered on 3 March 2016.

Recommendations for standardized pathological characterization of residual disease for neoadjuvant clinical trials of breast cancer by the BIG-NABCG collaboration

PubMed Central

Bossuyt, V.; Provenzano, E.; Symmans, W. F.; Boughey, J. C.; Coles, C.; Curigliano, G.; Dixon, J. M.; Esserman, L. J.; Fastner, G.; Kuehn, T.; Peintinger, F.; von Minckwitz, G.; White, J.; Yang, W.; Badve, S.; Denkert, C.; MacGrogan, G.; Penault-Llorca, F.; Viale, G.; Cameron, D.; Earl, Helena; Alba, Emilio; Lluch, Ana; Albanell, Joan; Amos, Keith; Biernat, Wojciech; Bonnefoi, Hervé; Buzdar, Aman; Cane, Paul; Pinder, Sarah; Carson, Lesley; Dickson-Witmer, Diana; Gong, Gyungyub; Green, Jimmy; Hsu, Chih-Yi; Tseng, Ling-Ming; Kroep, Judith; Leitch, A. Marilyn; Sarode, Venetia; Mamounas, Eleftherios; Marcom, Paul Kelly; Nuciforo, Paolo; Paik, Soonmyung; Peg, Vicente; Peston, David; Pierga, Jean-Yves; Quintela-Fandino, Miguel; Salgado, Roberto; Sikov, William; Thomas, Jeremy; Unzeitig, Gary; Wesseling, Jelle

2015-01-01

Neoadjuvant systemic therapy (NAST) provides the unique opportunity to assess response to treatment after months rather than years of follow-up. However, significant variability exists in methods of pathologic assessment of response to NAST, and thus its interpretation for subsequent clinical decisions. Our international multidisciplinary working group was convened by the Breast International Group-North American Breast Cancer Group (BIG-NABCG) collaboration and tasked to recommend practical methods for standardized evaluation of the post-NAST surgical breast cancer specimen for clinical trials that promote accurate and reliable designation of pathologic complete response (pCR) and meaningful characterization of residual disease. Recommendations include multidisciplinary communication; clinical marking of the tumor site (clips); and radiologic, photographic, or pictorial imaging of the sliced specimen, to map the tissue sections and reconcile macroscopic and microscopic findings. The information required to define pCR (ypT0/is ypN0 or ypT0 yp N0), residual ypT and ypN stage using the current AJCC/UICC system, and the Residual Cancer Burden system were recommended for quantification of residual disease in clinical trials. PMID:26019189

Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.

PubMed

Haddad, Tarek; Himes, Adam; Thompson, Laura; Irony, Telba; Nair, Rajesh

2017-01-01

Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture. Different discount functions are used to cover a wide range of scenarios in which the type I error rates and power vary for the same number of enrolled patients. Incorporation of engineering models as prior knowledge in a Bayesian clinical trial design can provide benefits of decreased sample size and trial length while still controlling type I error rate and power.

Effect of task-oriented training and high-variability practice on gross motor performance and activities of daily living in children with spastic diplegia.

PubMed

Kwon, Hae-Yeon; Ahn, So-Yoon

2016-10-01

[Purpose] This study investigates how a task-oriented training and high-variability practice program can affect the gross motor performance and activities of daily living for children with spastic diplegia and provides an effective and reliable clinical database for future improvement of motor performances skills. [Subjects and Methods] This study randomly assigned seven children with spastic diplegia to each intervention group including that of a control group, task-oriented training group, and a high-variability practice group. The control group only received neurodevelopmental treatment for 40 minutes, while the other two intervention groups additionally implemented a task-oriented training and high-variability practice program for 8 weeks (twice a week, 60 min per session). To compare intra and inter-relationships of the three intervention groups, this study measured gross motor performance measure (GMPM) and functional independence measure for children (WeeFIM) before and after 8 weeks of training. [Results] There were statistically significant differences in the amount of change before and after the training among the three intervention groups for the gross motor performance measure and functional independence measure. [Conclusion] Applying high-variability practice in a task-oriented training course may be considered an efficient intervention method to improve motor performance skills that can tune to movement necessary for daily livelihood through motor experience and learning of new skills as well as change of tasks learned in a complex environment or similar situations to high-variability practice.

Risk Factors and Protective Factors in Relation to Subjective Health among Adult Female Victims of Child Sexual Abuse

ERIC Educational Resources Information Center

Jonzon, Eva; Lindblad, Frank

2006-01-01

Objective: To investigate the relationships between risk and protective factors and health outcome in a sample of adult females who had been victims of child sexual abuse. Method: Both person- and variable-oriented analyses were applied to questionnaire data from a non-clinical group of women (n=152) reporting sexual abuse during childhood.…

Personality Disorders in Offenders with Intellectual Disability: A Comparison of Clinical, Forensic and Outcome Variables and Implications for Service Provision

ERIC Educational Resources Information Center

Alexander, R. T.; Green, F. N.; O'Mahony, B.; Gunaratna, I. J.; Gangadharan, S. K.; Hoare, S.

2010-01-01

Aim: To establish any differences between patients with and without a diagnosis of personality disorders, being treated in a secure inpatient service for offenders with intellectual disability (ID) in the UK. Method: A cohort study involving a selected population of people with ID and offending behaviours. Results: The study included a total of…

Policy to implementation: evidence-based practice in community mental health--study protocol.

PubMed

Beidas, Rinad S; Aarons, Gregory; Barg, Frances; Evans, Arthur; Hadley, Trevor; Hoagwood, Kimberly; Marcus, Steven; Schoenwald, Sonja; Walsh, Lucia; Mandell, David S

2013-03-24

Evidence-based treatments (EBTs) are not widely available in community mental health settings. In response to the call for implementation of evidence-based treatments in the United States, states and counties have mandated behavioral health reform through policies and other initiatives. Evaluations of the impact of these policies on implementation are rare. A systems transformation about to occur in Philadelphia, Pennsylvania, offers an important opportunity to prospectively study implementation in response to a policy mandate. Using a prospective sequential mixed-methods design, with observations at multiple points in time, we will investigate the responses of staff from 30 community mental health clinics to a policy from the Department of Behavioral Health encouraging and incentivizing providers to implement evidence-based treatments to treat youth with mental health problems. Study participants will be 30 executive directors, 30 clinical directors, and 240 therapists. Data will be collected prior to the policy implementation, and then at two and four years following policy implementation. Quantitative data will include measures of intervention implementation and potential moderators of implementation (i.e., organizational- and leader-level variables) and will be collected from executive directors, clinical directors, and therapists. Measures include self-reported therapist fidelity to evidence-based treatment techniques as measured by the Therapist Procedures Checklist-Revised, organizational variables as measured by the Organizational Social Context Measurement System and the Implementation Climate Assessment, leader variables as measured by the Multifactor Leadership Questionnaire, attitudes towards EBTs as measured by the Evidence-Based Practice Attitude Scale, and knowledge of EBTs as measured by the Knowledge of Evidence- Based Services Questionnaire. Qualitative data will include semi-structured interviews with a subset of the sample to assess the implementation experience of high-, average-, and low-performing agencies. Mixed methods will be integrated through comparing and contrasting results from the two methods for each of the primary hypotheses in this study. Findings from the proposed research will inform both future policy mandates around implementation and the support required for the success of these policies, with the ultimate goal of improving the quality of treatment provided to youth in the public sector.

Increased Intra-Participant Variability in Children with Autistic Spectrum Disorders: Evidence from Single-Trial Analysis of Evoked EEG

PubMed Central

Milne, Elizabeth

2011-01-01

Intra-participant variability in clinical conditions such as autistic spectrum disorder (ASD) is an important indicator of pathophysiological processing. The data reported here illustrate that trial-by-trial variability can be reliably measured from EEG, and that intra-participant EEG variability is significantly greater in those with ASD than in neuro-typical matched controls. EEG recorded at the scalp is a linear mixture of activity arising from muscle artifacts and numerous concurrent brain processes. To minimize these additional sources of variability, EEG data were subjected to two different methods of spatial filtering. (i) The data were decomposed using infomax independent component analysis, a method of blind source separation which un-mixes the EEG signal into components with maximally independent time-courses, and (ii) a surface Laplacian transform was performed (current source density interpolation) in order to reduce the effects of volume conduction. Data are presented from 13 high functioning adolescents with ASD without co-morbid ADHD, and 12 neuro-typical age-, IQ-, and gender-matched controls. Comparison of variability between the ASD and neuro-typical groups indicated that intra-participant variability of P1 latency and P1 amplitude was greater in the participants with ASD, and inter-trial α-band phase coherence was lower in the participants with ASD. These data support the suggestion that individuals with ASD are less able to synchronize the activity of stimulus-related cell assemblies than neuro-typical individuals, and provide empirical evidence in support of theories of increased neural noise in ASD. PMID:21716921

Nerve Ultrasound and Electrophysiology for Therapy Monitoring in Chronic Inflammatory Demyelinating Polyneuropathy.

PubMed

Kerasnoudis, Antonios; Pitarokoili, Kalliopi; Gold, Ralf; Yoon, Min-Suk

2015-01-01

We evaluated prospectively nerve ultrasound and electrophysiology as monitoring methods of intravenous immunoglobulin (IVIG) therapy in chronic inflammatory demyelinating polyneuropathy (CIDP). Overall 15 healthy subjects and 11 CIDP patients undergoing IVIG therapy were recruited in the study. All patients underwent clinical, ultrasound, and electrophysiological evaluation at the time point of first onset of symptoms (<6 weeks of symptoms) and 4, 8, and 12 months after onset. The intranerve cross-sectional area (CSA) variability of each nerve, but not the CSA alone, correlated with the MRC Scale score during 12-month follow-up. On the other hand, none of the electrophysiological parameters correlated with the MRC Scale Score in each of the peripheral nerves. Interestingly, in ¾ of the CIDP patients, the resolution of the conduction block correlated with the improvement in the MRC Sum score. Nerve ultrasound and in particular the intranerve CSA variability seems to be a useful method in monitoring CIDP patients. Although the sample size is small, the intranerve CSA variability seems to be more promising than neurophysiology. Copyright © 2015 by the American Society of Neuroimaging.

Consistency of clinical biomechanical measures between three different institutions: implications for multi-center biomechanical and epidemiological research.

PubMed

Myer, Gregory D; Wordeman, Samuel C; Sugimoto, Dai; Bates, Nathaniel A; Roewer, Benjamin D; Medina McKeon, Jennifer M; DiCesare, Christopher A; Di Stasi, Stephanie L; Barber Foss, Kim D; Thomas, Staci M; Hewett, Timothy E

2014-05-01

Multi-center collaborations provide a powerful alternative to overcome the inherent limitations to single-center investigations. Specifically, multi-center projects can support large-scale prospective, longitudinal studies that investigate relatively uncommon outcomes, such as anterior cruciate ligament injury. This project was conceived to assess within- and between-center reliability of an affordable, clinical nomogram utilizing two-dimensional video methods to screen for risk of knee injury. The authors hypothesized that the two-dimensional screening methods would provide good-to-excellent reliability within and between institutions for assessment of frontal and sagittal plane biomechanics. Nineteen female, high school athletes participated. Two-dimensional video kinematics of the lower extremity during a drop vertical jump task were collected on all 19 study participants at each of the three facilities. Within-center and between-center reliability were assessed with intra- and inter-class correlation coefficients. Within-center reliability of the clinical nomogram variables was consistently excellent, but between-center reliability was fair-to-good. Within-center intra-class correlation coefficient for all nomogram variables combined was 0.98, while combined between-center inter-class correlation coefficient was 0.63. Injury risk screening protocols were reliable within and repeatable between centers. These results demonstrate the feasibility of multi-site biomechanical studies and establish a framework for further dissemination of injury risk screening algorithms. Specifically, multi-center studies may allow for further validation and optimization of two-dimensional video screening tools. 2b.

Characterization of the porosity of human dental enamel and shear bond strength in vitro after variable etch times: initial findings using the BET method.

PubMed

Nguyen, Trang T; Miller, Arthur; Orellana, Maria F

2011-07-01

(1) To quantitatively characterize human enamel porosity and surface area in vitro before and after etching for variable etching times; and (2) to evaluate shear bond strength after variable etching times. Specifically, our goal was to identify the presence of any correlation between enamel porosity and shear bond strength. Pore surface area, pore volume, and pore size of enamel from extracted human teeth were analyzed by Brunauer-Emmett-Teller (BET) gas adsorption before and after etching for 15, 30, and 60 seconds with 37% phosphoric acid. Orthodontic brackets were bonded with Transbond to the samples with variable etch times and were subsequently applied to a single-plane lap shear testing system. Pore volume and surface area increased after etching for 15 and 30 seconds. At 60 seconds, this increase was less pronounced. On the contrary, pore size appears to decrease after etching. No correlation was found between variable etching times and shear strength. Samples etched for 15, 30, and 60 seconds all demonstrated clinically viable shear strength values. The BET adsorption method could be a valuable tool in enhancing our understanding of enamel characteristics. Our findings indicate that distinct quantitative changes in enamel pore architecture are evident after etching. Further testing with a larger sample size would have to be carried out for more definitive conclusions to be made.

Changes in Keratocyte Density and Visual Function Five Years after Laser in situ Keratomileusis: Femtosecond Laser vs Mechanical Microkeratome

PubMed Central

McLaren, Jay W.; Bourne, William M.; Maguire, Leo J.; Patel, Sanjay V.

2015-01-01

Purpose To determine the effects of keratocyte loss on optical properties and vision after laser in situ keratomileusis (LASIK) with the flap created with a femtosecond laser or a mechanical microkeratome. Design Randomized clinical paired-eye study. Methods Both eyes of 21 patients received LASIK for myopia or myopic astigmatism. One eye of each patient was randomized by ocular dominance to flap creation with a femtosecond laser and the other eye to flap creation with a mechanical microkeratome. Before LASIK and at 1, 3, 6 months and 1, 3, and 5 years after LASIK, keratocyte density was measured by using confocal microscopy, and high-contrast visual acuity and anterior corneal wavefront aberrations were measured by standard methods. At each visit, all variables were compared between methods of creating the flap and to the same variable before treatment by using paired tests with Bonferroni correction for multiple comparisons. Results Keratocyte density in the flap decreased by 20% during the first year after LASIK and remained low through 5 years (p<0.001). High-order wavefront aberrations increased and uncorrected visual acuity improved immediately after surgery but these variables did not change further to five years. There were no differences in any variables between treatments. Conclusions A sustained reduction in keratocyte density does not affect vision or optical properties of the cornea through 5 years after LASIK. The method of creating a LASIK flap does not influence the changes in keratocyte density in the flap. PMID:25868758

The Association Between Internet Use and Ambulatory Care-Seeking Behaviors in Taiwan: A Cross-Sectional Study

PubMed Central

Chen, Tsung-Fu; Liang, Jyh-Chong; Lin, Tzu-Bin; Tsai, Chin-Chung

2016-01-01

Background Compared with the traditional ways of gaining health-related information from newspapers, magazines, radio, and television, the Internet is inexpensive, accessible, and conveys diverse opinions. Several studies on how increasing Internet use affected outpatient clinic visits were inconclusive. Objective The objective of this study was to examine the role of Internet use on ambulatory care-seeking behaviors as indicated by the number of outpatient clinic visits after adjusting for confounding variables. Methods We conducted this study using a sample randomly selected from the general population in Taiwan. To handle the missing data, we built a multivariate logistic regression model for propensity score matching using age and sex as the independent variables. The questionnaires with no missing data were then included in a multivariate linear regression model for examining the association between Internet use and outpatient clinic visits. Results We included a sample of 293 participants who answered the questionnaire with no missing data in the multivariate linear regression model. We found that Internet use was significantly associated with more outpatient clinic visits (P=.04). The participants with chronic diseases tended to make more outpatient clinic visits (P<.01). Conclusions The inconsistent quality of health-related information obtained from the Internet may be associated with patients’ increasing need for interpreting and discussing the information with health care professionals, thus resulting in an increasing number of outpatient clinic visits. In addition, the media literacy of Web-based health-related information seekers may also affect their ambulatory care-seeking behaviors, such as outpatient clinic visits. PMID:27927606

Milestones: Critical Elements in Clinical Informatics Fellowship Programs

PubMed Central

Lehmann, Christoph U.; Munger, Benson

2016-01-01

Summary Background Milestones refer to points along a continuum of a competency from novice to expert. Resident and fellow assessment and program evaluation processes adopted by the ACGME include the mandate that programs report the educational progress of residents and fellows twice annually utilizing Milestones developed by a specialty specific ACGME working group of experts. Milestones in clinical training programs are largely unmapped to specific assessment tools. Residents and fellows are mainly assessed using locally derived assessment instruments. These assessments are then reviewed by the Clinical Competency Committee which assigns and reports trainee ratings using the specialty specific reporting Milestones. Methods and Results The challenge and opportunity facing the nascent specialty of Clinical Informatics is how to optimally utilize this framework across a growing number of accredited fellowships. The authors review how a mapped milestone framework, in which each required sub-competency is mapped to a single milestone assessment grid, can enable the use of milestones for multiple uses including individualized learning plans, fellow assessments, and program evaluation. Furthermore, such a mapped strategy will foster the ability to compare fellow progress within and between Clinical Informatics Fellowships in a structured and reliable fashion. Clinical Informatics currently has far less variability across programs and thus could easily utilize a more tightly defined set of milestones with a clear mapping to sub-competencies. This approach would enable greater standardization of assessment instruments and processes across programs while allowing for variability in how those sub-competencies are taught. Conclusions A mapped strategy for Milestones offers significant advantages for Clinical Informatics programs. PMID:27081414

The fractal heart — embracing mathematics in the cardiology clinic

PubMed Central

Captur, Gabriella; Karperien, Audrey L.; Hughes, Alun D.; Francis, Darrel P.; Moon, James C.

2017-01-01

For clinicians grappling with quantifying the complex spatial and temporal patterns of cardiac structure and function (such as myocardial trabeculae, coronary microvascular anatomy, tissue perfusion, myocyte histology, electrical conduction, heart rate, and blood-pressure variability), fractal analysis is a powerful, but still underused, mathematical tool. In this Perspectives article, we explain some fundamental principles of fractal geometry and place it in a familiar medical setting. We summarize studies in the cardiovascular sciences in which fractal methods have successfully been used to investigate disease mechanisms, and suggest potential future clinical roles in cardiac imaging and time series measurements. We believe that clinical researchers can deploy innovative fractal solutions to common cardiac problems that might ultimately translate into advancements for patient care. PMID:27708281

Another Piece of the Antibody Puzzle: Observations from the HALT study\\.

PubMed

Snyder, Laurie D; Tinckam, Kathryn J

2018-06-04

In the rapidly evolving domain of clinical transplantation immunobiology, the interrogation and interpretation of HLA antibodies and their associated clinical consequences are in the spotlight. In lung transplant, HLA antibodies, in particular donor specific antibodies (DSA), are a determining component of the lung transplant antibody mediated rejection (AMR) definition (1). DSA after lung transplant are widely regarded as poor prognosticator, though sparse data to date necessitate ongoing discourse and continued investigation into incidence, timing and treatment. Prior studies reported a wide range of DSA incidence with differing consequences on a background of highly variable timing, methods, antibody analytic strategies and clinical definitions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The wisdom of the commons: ensemble tree classifiers for prostate cancer prognosis

PubMed Central

Koziol, James A.; Feng, Anne C.; Jia, Zhenyu; Wang, Yipeng; Goodison, Seven; McClelland, Michael; Mercola, Dan

2009-01-01

Motivation: Classification and regression trees have long been used for cancer diagnosis and prognosis. Nevertheless, instability and variable selection bias, as well as overfitting, are well-known problems of tree-based methods. In this article, we investigate whether ensemble tree classifiers can ameliorate these difficulties, using data from two recent studies of radical prostatectomy in prostate cancer. Results: Using time to progression following prostatectomy as the relevant clinical endpoint, we found that ensemble tree classifiers robustly and reproducibly identified three subgroups of patients in the two clinical datasets: non-progressors, early progressors and late progressors. Moreover, the consensus classifications were independent predictors of time to progression compared to known clinical prognostic factors. Contact: dmercola@uci.edu PMID:18628288

Applications of biomaterials in corneal wound healing.

PubMed

Tsai, I-Lun; Hsu, Chih-Chien; Hung, Kuo-Hsuan; Chang, Chi-Wen; Cheng, Yung-Hsin

2015-04-01

Disease affecting the cornea is a common cause of blindness worldwide. To date, the amniotic membrane (AM) is the most widely used clinical method for cornea regeneration. However, donor-dependent differences in the AM may result in variable clinical outcomes. To overcome this issue, biomaterials are currently under investigation for corneal regeneration in vitro and in vivo. In this article, we highlight the recent advances in hydrogels, bioengineered prosthetic devices, contact lenses, and drug delivery systems for corneal regeneration. In clinical studies, the therapeutic effects of biomaterials, including fibrin and collagen-based hydrogels and silicone contact lenses, have been demonstrated in damaged cornea. The combination of cells and biomaterials may provide potential treatment in corneal wound healing in the future. Copyright © 2014. Published by Elsevier Taiwan.

Application of machine learning algorithms for clinical predictive modeling: a data-mining approach in SCT.

PubMed

Shouval, R; Bondi, O; Mishan, H; Shimoni, A; Unger, R; Nagler, A

2014-03-01

Data collected from hematopoietic SCT (HSCT) centers are becoming more abundant and complex owing to the formation of organized registries and incorporation of biological data. Typically, conventional statistical methods are used for the development of outcome prediction models and risk scores. However, these analyses carry inherent properties limiting their ability to cope with large data sets with multiple variables and samples. Machine learning (ML), a field stemming from artificial intelligence, is part of a wider approach for data analysis termed data mining (DM). It enables prediction in complex data scenarios, familiar to practitioners and researchers. Technological and commercial applications are all around us, gradually entering clinical research. In the following review, we would like to expose hematologists and stem cell transplanters to the concepts, clinical applications, strengths and limitations of such methods and discuss current research in HSCT. The aim of this review is to encourage utilization of the ML and DM techniques in the field of HSCT, including prediction of transplantation outcome and donor selection.

Accounting for dropout reason in longitudinal studies with nonignorable dropout.

PubMed

Moore, Camille M; MaWhinney, Samantha; Forster, Jeri E; Carlson, Nichole E; Allshouse, Amanda; Wang, Xinshuo; Routy, Jean-Pierre; Conway, Brian; Connick, Elizabeth

2017-08-01

Dropout is a common problem in longitudinal cohort studies and clinical trials, often raising concerns of nonignorable dropout. Selection, frailty, and mixture models have been proposed to account for potentially nonignorable missingness by relating the longitudinal outcome to time of dropout. In addition, many longitudinal studies encounter multiple types of missing data or reasons for dropout, such as loss to follow-up, disease progression, treatment modifications and death. When clinically distinct dropout reasons are present, it may be preferable to control for both dropout reason and time to gain additional clinical insights. This may be especially interesting when the dropout reason and dropout times differ by the primary exposure variable. We extend a semi-parametric varying-coefficient method for nonignorable dropout to accommodate dropout reason. We apply our method to untreated HIV-infected subjects recruited to the Acute Infection and Early Disease Research Program HIV cohort and compare longitudinal CD4 + T cell count in injection drug users to nonusers with two dropout reasons: anti-retroviral treatment initiation and loss to follow-up.

Predictive validity of pre-admission assessments on medical student performance

PubMed Central

Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M. Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef

2017-01-01

Objectives To examine the predictive validity of pre-admission variables on students’ performance in a medical school in Saudi Arabia.  Methods In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. Results In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students’ progress test performance (p<0.001 and B=19.02). Conclusions Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years. PMID:29176032

Bi-exponential T2 analysis of healthy and diseased Achilles tendons: an in vivo preliminary magnetic resonance study and correlation with clinical score.

PubMed

Juras, Vladimir; Apprich, Sebastian; Szomolanyi, Pavol; Bieri, Oliver; Deligianni, Xeni; Trattnig, Siegfried

2013-10-01

To compare mono- and bi-exponential T2 analysis in healthy and degenerated Achilles tendons using a recently introduced magnetic resonance variable-echo-time sequence (vTE) for T2 mapping. Ten volunteers and ten patients were included in the study. A variable-echo-time sequence was used with 20 echo times. Images were post-processed with both techniques, mono- and bi-exponential [T2 m, short T2 component (T2 s) and long T2 component (T2 l)]. The number of mono- and bi-exponentially decaying pixels in each region of interest was expressed as a ratio (B/M). Patients were clinically assessed with the Achilles Tendon Rupture Score (ATRS), and these values were correlated with the T2 values. The means for both T2 m and T2 s were statistically significantly different between patients and volunteers; however, for T2 s, the P value was lower. In patients, the Pearson correlation coefficient between ATRS and T2 s was -0.816 (P = 0.007). The proposed variable-echo-time sequence can be successfully used as an alternative method to UTE sequences with some added benefits, such as a short imaging time along with relatively high resolution and minimised blurring artefacts, and minimised susceptibility artefacts and chemical shift artefacts. Bi-exponential T2 calculation is superior to mono-exponential in terms of statistical significance for the diagnosis of Achilles tendinopathy. • Magnetic resonance imaging offers new insight into healthy and diseased Achilles tendons • Bi-exponential T2 calculation in Achilles tendons is more beneficial than mono-exponential • A short T2 component correlates strongly with clinical score • Variable echo time sequences successfully used instead of ultrashort echo time sequences.

Predictors and moderators of response to cognitive behavioral therapy and medication for the treatment of binge eating disorder.

PubMed

Grilo, Carlos M; Masheb, Robin M; Crosby, Ross D

2012-10-01

To examine predictors and moderators of response to cognitive behavioral therapy (CBT) and medication treatments for binge-eating disorder (BED). 108 BED patients in a randomized double-blind placebo-controlled trial testing CBT and fluoxetine treatments were assessed prior, throughout, and posttreatment. Demographic factors, psychiatric and personality disorder comorbidity, eating disorder psychopathology, psychological features, and 2 subtyping methods (negative affect, overvaluation of shape/weight) were tested as predictors and moderators for the primary outcome of remission from binge eating and 4 secondary dimensional outcomes (binge-eating frequency, eating disorder psychopathology, depression, and body mass index). Mixed-effects models analyzed all available data for each outcome variable. In each model, effects for baseline value and treatment were included with tests of both prediction and moderator effects. Several demographic and clinical variables significantly predicted and/or moderated outcomes. One demographic variable signaled a statistical advantage for medication only (younger participants had greater binge-eating reductions), whereas several demographic and clinical variables (lower self-esteem, negative affect, and overvaluation of shape/weight) signaled better improvements if receiving CBT. Overvaluation was the most salient predictor/moderator of outcomes. Overvaluation significantly predicted binge-eating remission (29% of participants with vs. 57% of participants without overvaluation remitted). Overvaluation was especially associated with lower remission rates if receiving medication only (10% vs. 42% for participants without overvaluation). Overvaluation moderated dimensional outcomes: Participants with overvaluation had significantly greater reductions in eating disorder psychopathology and depression levels if receiving CBT. Overvaluation predictor/moderator findings persisted after controlling for negative affect. Our findings have clinical utility for prescription of CBT and medication and implications for refinement of the BED diagnosis. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Stigma and its correlates in patients with schizophrenia attending a general hospital psychiatric unit

PubMed Central

Singh, Aakanksha; Mattoo, Surendra K.; Grover, Sandeep

2016-01-01

Background: Very few studies from India have studied stigma experienced by patients with schizophrenia. Aim of the Study: To study stigma in patients with schizophrenia (in the form of internalized stigma, perceived stigma and social-participation-restriction stigma) and its relationship with specified demographic and clinical variables (demographic variables, clinical profile, level of psychopathology, knowledge about illness, and insight). Materials and Methods: Selected by purposive random sampling, 100 patients with schizophrenia in remission were evaluated on internalized stigma of mental illness scale (ISMIS), explanatory model interview catalog stigma scale, participation scale (P-scale), positive and negative syndrome scale for schizophrenia, global assessment of functioning scale, scale to assess unawareness of mental disorder, and knowledge of mental illness scale. Results: On ISMIS scale, 81% patients experienced alienation and 45% exhibited stigma resistance. Stereotype endorsement was seen in 26% patients, discrimination experience was faced by 21% patients, and only 16% patients had social withdrawal. Overall, 29% participants had internalized stigma when total ISMIS score was taken into consideration. On P-scale, 67% patients experienced significant restriction, with a majority reporting moderate to mild restriction. In terms of associations between stigma and sociodemographic variables, no consistent correlations emerged, except for those who were not on paid job, had higher participation restriction. Of the clinical variables, level of functioning was the only consistent predictor of stigma. While better knowledge about the disorder was associated with lower level of stigma, there was no association between stigma and insight. Conclusion: Significant proportion of patients with schizophrenia experience stigma and stigma is associated with lower level of functioning and better knowledge about illness is associated with lower level of stigma. PMID:28066007

Characterization of Noise Signatures of Involuntary Head Motion in the Autism Brain Imaging Data Exchange Repository

PubMed Central

Caballero, Carla; Mistry, Sejal; Vero, Joe; Torres, Elizabeth B

2018-01-01

The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access repositories. Such repositories combine data collected from multiple research sites using variable sampling resolutions. One example is the Autism Brain Imaging Data Exchange repository containing thousands of imaging and demographic records from participants in the spectrum of autism and age-matched neurotypical controls. Further, statistical analyses of groups from different diagnoses and demographics may be challenging, owing to the disparate number of participants across different clinical subgroups. In this paper, we examine the noise signatures of head motion data extracted from resting state fMRI data harnessed under different sampling resolutions. We characterize the quality of the noise in the variability of the raw linear and angular speeds for different clinical phenotypes in relation to age-matched controls. Further, we use bootstrapping methods to ensure compatible group sizes for statistical comparison and report the ranges of physical involuntary head excursions of these groups. We conclude that different sampling rates do affect the quality of noise in the variability of head motion data and, consequently, the type of random process appropriate to characterize the time series data. Further, given a qualitative range of noise, from pink to brown noise, it is possible to characterize different clinical subtypes and distinguish them in relation to ranges of neurotypical controls. These results may be of relevance to the pre-processing stages of the pipeline of analyses of resting state fMRI data, whereby head motion enters the criteria to clean imaging data from motion artifacts. PMID:29556179

Impact of acquisition and interpretation on total inter-observer variability in echocardiography: results from the quality assurance program of the STAAB cohort study.

PubMed

Morbach, Caroline; Gelbrich, Götz; Breunig, Margret; Tiffe, Theresa; Wagner, Martin; Heuschmann, Peter U; Störk, Stefan

2018-02-14

Variability related to image acquisition and interpretation is an important issue of echocardiography in clinical trials. Nevertheless, there is no broadly accepted standard method for quality assessment of echocardiography in clinical research reports. We present analyses based on the echocardiography quality-assurance program of the ongoing STAAB cohort study (characteristics and course of heart failure stages A-B and determinants of progression). In 43 healthy individuals (mean age 50 ± 14 years; 18 females), duplicate echocardiography scans were acquired and mutually interpreted by one of three trained sonographers and an EACVI certified physician, respectively. Acquisition (AcV), interpretation (InV), and inter-observer variability (IOV; i.e., variability between the acquisition-interpretation sequences of two different observers), were determined for selected M-mode, B-mode, and Doppler parameters. We calculated Bland-Altman upper 95% limits of absolute differences, implying that 95% of measurement differences were smaller/equal to the given value: e.g. LV end-diastolic volume (mL): 25.0, 25.0, 27.9; septal e' velocity (cm/s): 3.03, 1.25, 3.58. Further, 90, 85, and 80% upper limits of absolute differences were determined for the respective parameters. Both, acquisition and interpretation, independently and sizably contributed to IOV. As such, separate assessment of AcV and InV is likely to aid in echocardiography training and quality-assurance. Our results further suggest to routinely determine IOV in clinical trials as a comprehensive measure of imaging quality. The derived 95, 90, 85, and 80% upper limits of absolute differences are suggested as reproducibility targets of future studies, thus contributing to the international efforts of standardization in quality-assurance.

What patient characteristics guide nurses' clinical judgement on pressure ulcer risk? A mixed methods study.

PubMed

Balzer, K; Kremer, L; Junghans, A; Halfens, R J G; Dassen, T; Kottner, J

2014-05-01

Nurses' clinical judgement plays a vital role in pressure ulcer risk assessment, but evidence is lacking which patient characteristics are important for nurses' perception of patients' risk exposure. To explore which patient characteristics nurses employ when assessing pressure ulcer risk without use of a risk assessment scale. Mixed methods design triangulating observational data from the control group of a quasi-experimental trial and data from semi-structured interviews with nurses. Two traumatological wards at a university hospital. Quantitative data: A consecutive sample of 106 patients matching the eligibility criteria (age ≥ 18 years, no pressure ulcers category ≥ 2 at admission and ≥ 5 days expected length of stay). Qualitative data: A purposive sample of 16 nurses. Quantitative data: Predictor variables for pressure ulcer risk were measured by study assistants at the bedside each second day. Concurrently, nurses documented their clinical judgement on patients' pressure ulcer risk by means of a 4-step global judgement scale. Bivariate correlations between predictor variables and nurses' risk estimates were established. Qualitative data: In interviews, nurses were asked to assess fictitious patients' pressure ulcer risk and to justify their risk estimates. Patient characteristics perceived as relevant for nurses' judements were thematically clustered. Triangulation: Firstly, predictors of nurses' risk estimates identified in bivariate analysis were cross-mapped with interview findings. Secondly, three models to predict nurses' risk estimates underwent multiple linear regression analysis. Nurses consider multiple patient characteristics for pressure ulcer risk assessment, but regard some conditions more important than others. Triangulation showed that these are measures reflecting patients' exposure to pressure or overall care dependency. Qualitative data furthermore indicate that nurses are likely to trade off risk-enhancing conditions against conditions perceived to be protective. Here, patients' mental capabilities like willingness to engage in one owns care seem to be particularly important. Due to missing information on these variables in the quantitative data, they could not be incorporated into triangulation. Nurses' clinical judgement draws on well-known aetiological factors, and tends to expand conditions covered by risk assessment scales. Patients' care dependency and self-care abilities seem to be core concepts for nurses' risk assessment. Copyright © 2013 Elsevier Ltd. All rights reserved.

PRIME – PRocess modelling in ImpleMEntation research: selecting a theoretical basis for interventions to change clinical practice

PubMed Central

Walker, Anne E; Grimshaw, Jeremy; Johnston, Marie; Pitts, Nigel; Steen, Nick; Eccles, Martin

2003-01-01

Background Biomedical research constantly produces new findings but these are not routinely translated into health care practice. One way to address this problem is to develop effective interventions to translate research findings into practice. Currently a range of empirical interventions are available and systematic reviews of these have demonstrated that there is no single best intervention. This evidence base is difficult to use in routine settings because it cannot identify which intervention is most likely to be effective (or cost effective) in a particular situation. We need to establish a scientific rationale for interventions. As clinical practice is a form of human behaviour, theories of human behaviour that have proved useful in other similar settings may provide a basis for developing a scientific rationale for the choice of interventions to translate research findings into clinical practice. The objectives of the study are: to amplify and populate scientifically validated theories of behaviour with evidence from the experience of health professionals; to use this as a basis for developing predictive questionnaires using replicable methods; to identify which elements of the questionnaire (i.e., which theoretical constructs) predict clinical practice and distinguish between evidence compliant and non-compliant practice; and on the basis of these results, to identify variables (based on theoretical constructs) that might be prime targets for behaviour change interventions. Methods We will develop postal questionnaires measuring two motivational, three action and one stage theory to explore five behaviours with 800 general medical and 600 general dental practitioners. We will collect data on performance for each of the behaviours. The relationships between predictor variables (theoretical constructs) and outcome measures (data on performance) in each survey will be assessed using multiple regression analysis and structural equation modelling. In the final phase of the project, the findings from all surveys will be analysed simultaneously adopting a random effects approach to investigate whether the relationships between predictor variables and outcome measures are modified by behaviour, professional group or geographical location. PMID:14683530

“Wish You Were Here”: Examining Characteristics, Outcomes, and Statistical Solutions for Missing Cases in Web-Based Psychotherapeutic Trials

PubMed Central

Dear, Blake F; Heller, Gillian Z; Crane, Monique F; Titov, Nickolai

2018-01-01

Background Missing cases following treatment are common in Web-based psychotherapy trials. Without the ability to directly measure and evaluate the outcomes for missing cases, the ability to measure and evaluate the effects of treatment is challenging. Although common, little is known about the characteristics of Web-based psychotherapy participants who present as missing cases, their likely clinical outcomes, or the suitability of different statistical assumptions that can characterize missing cases. Objective Using a large sample of individuals who underwent Web-based psychotherapy for depressive symptoms (n=820), the aim of this study was to explore the characteristics of cases who present as missing cases at posttreatment (n=138), their likely treatment outcomes, and compare between statistical methods for replacing their missing data. Methods First, common participant and treatment features were tested through binary logistic regression models, evaluating the ability to predict missing cases. Second, the same variables were screened for their ability to increase or impede the rate symptom change that was observed following treatment. Third, using recontacted cases at 3-month follow-up to proximally represent missing cases outcomes following treatment, various simulated replacement scores were compared and evaluated against observed clinical follow-up scores. Results Missing cases were dominantly predicted by lower treatment adherence and increased symptoms at pretreatment. Statistical methods that ignored these characteristics can overlook an important clinical phenomenon and consequently produce inaccurate replacement outcomes, with symptoms estimates that can swing from −32% to 70% from the observed outcomes of recontacted cases. In contrast, longitudinal statistical methods that adjusted their estimates for missing cases outcomes by treatment adherence rates and baseline symptoms scores resulted in minimal measurement bias (<8%). Conclusions Certain variables can characterize and predict missing cases likelihood and jointly predict lesser clinical improvement. Under such circumstances, individuals with potentially worst off treatment outcomes can become concealed, and failure to adjust for this can lead to substantial clinical measurement bias. Together, this preliminary research suggests that missing cases in Web-based psychotherapeutic interventions may not occur as random events and can be systematically predicted. Critically, at the same time, missing cases may experience outcomes that are distinct and important for a complete understanding of the treatment effect. PMID:29674311

The reliability of sensitive information provided by injecting drug users in a clinical setting: clinician-administered versus audio computer-assisted self-interviewing (ACASI).

PubMed

Islam, M Mofizul; Topp, Libby; Conigrave, Katherine M; van Beek, Ingrid; Maher, Lisa; White, Ann; Rodgers, Craig; Day, Carolyn A

2012-01-01

Research with injecting drug users (IDUs) suggests greater willingness to report sensitive and stigmatised behaviour via audio computer-assisted self-interviewing (ACASI) methods than during face-to-face interviews (FFIs); however, previous studies were limited in verifying this within the same individuals at the same time point. This study examines the relative willingness of IDUs to report sensitive information via ACASI and during a face-to-face clinical assessment administered in health services for IDUs. During recruitment for a randomised controlled trial undertaken at two IDU-targeted health services, assessments were undertaken as per clinical protocols, followed by referral of eligible clients to the trial, in which baseline self-report data were collected via ACASI. Five questions about sensitive injecting and sexual risk behaviours were administered to participants during both clinical interviews and baseline research data collection. "Percentage agreement" determined the magnitude of concordance/discordance in responses across interview methods, while tests appropriate to data format assessed the statistical significance of this variation. Results for all five variables suggest that, relative to ACASI, FFI elicited responses that may be perceived as more socially desirable. Discordance was statistically significant for four of the five variables examined. Participants who reported a history of sex work were more likely to provide discordant responses to at least one socially sensitive item. In health services for IDUs, information collection via ACASI may elicit more reliable and valid responses than FFI. Adoption of a universal precautionary approach to complement individually tailored assessment of and advice regarding health risk behaviours for IDUs may address this issue.

Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

PubMed Central

Gilbert, Peter B.; Janes, Holly E.; Huang, Yunda

2016-01-01

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods. PMID:27037797

How novice, skilled and advanced clinical researchers include variables in a case report form for clinical research: a qualitative study.

PubMed

Chu, Hongling; Zeng, Lin; Fetters, Micheal D; Li, Nan; Tao, Liyuan; Shi, Yanyan; Zhang, Hua; Wang, Xiaoxiao; Li, Fengwei; Zhao, Yiming

2017-09-18

Despite varying degrees in research training, most academic clinicians are expected to conduct clinical research. The objective of this research was to understand how clinical researchers of different skill levels include variables in a case report form for their clinical research. The setting for this research was a major academic institution in Beijing, China. The target population was clinical researchers with three levels of experience, namely, limited clinical research experience, clinicians with rich clinical research experience and clinical research experts. Using a qualitative approach, we conducted 13 individual interviews (face to face) and one group interview (n=4) with clinical researchers from June to September 2016. Based on maximum variation sampling to identify researchers with three levels of research experience: eight clinicians with limited clinical research experience, five clinicians with rich clinical research experience and four clinical research experts. These 17 researchers had diverse hospital-based medical specialties and or specialisation in clinical research. Our analysis yields a typology of three processes developing a case report form that varies according to research experience level. Novice clinician researchers often have an incomplete protocol or none at all, and conduct data collection and publication based on a general framework. Experienced clinician researchers include variables in the case report form based on previous experience with attention to including domains or items at risk for omission and by eliminating unnecessary variables. Expert researchers consider comprehensively in advance data collection and implementation needs and plan accordingly. These results illustrate increasing levels of sophistication in research planning that increase sophistication in selection for variables in the case report form. These findings suggest that novice and intermediate-level researchers could benefit by emulating the comprehensive planning procedures such as those used by expert clinical researchers. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Dental age estimation of growing children by measurement of open apices: A Malaysian formula

PubMed Central

Cugati, Navaneetha; Kumaresan, Ramesh; Srinivasan, Balamanikanda; Karthikeyan, Priyadarshini

2015-01-01

Background: Age estimation is of prime importance in forensic science and clinical dentistry. Age estimation based on teeth development is one reliable approach. Many radiographic methods are proposed on the Western population for estimating dental age, and a similar assessment was found to be inadequate in Malaysian population. Hence, this study aims at formulating a regression model for dental age estimation in Malaysian children population using Cameriere's method. Materials and Methods: Orthopantomographs of 421 Malaysian children aged between 5 and 16 years involving all the three ethnic origins were digitalized and analyzed using Cameriere's method of age estimation. The subjects’ age was modeled as a function of the morphological variables, gender (g), ethnicity, sum of normalized open apices (s), number of tooth with completed root formation (N0) and the first-order interaction between s and N0. Results: The variables that contributed significantly to the fit were included in the regression model, yielding the following formula: Age = 11.368-0.345g + 0.553No -1.096s - 0.380s.No, where g is a variable, 1 for males and 2 for females. The equation explained 87.1% of total deviance. Conclusion: The results obtained insist on reframing the original Cameriere's formula to suit the population of the nation specifically. Further studies are to be conducted to evaluate the applicability of this formula on a larger sample size. PMID:26816464

Reliable quantification of BOLD fMRI cerebrovascular reactivity despite poor breath-hold performance.

PubMed

Bright, Molly G; Murphy, Kevin

2013-12-01

Cerebrovascular reactivity (CVR) can be mapped using BOLD fMRI to provide a clinical insight into vascular health that can be used to diagnose cerebrovascular disease. Breath-holds are a readily accessible method for producing the required arterial CO2 increases but their implementation into clinical studies is limited by concerns that patients will demonstrate highly variable performance of breath-hold challenges. This study assesses the repeatability of CVR measurements despite poor task performance, to determine if and how robust results could be achieved with breath-holds in patients. Twelve healthy volunteers were scanned at 3 T. Six functional scans were acquired, each consisting of 6 breath-hold challenges (10, 15, or 20 s duration) interleaved with periods of paced breathing. These scans simulated the varying breath-hold consistency and ability levels that may occur in patient data. Uniform ramps, time-scaled ramps, and end-tidal CO2 data were used as regressors in a general linear model in order to measure CVR at the grey matter, regional, and voxelwise level. The intraclass correlation coefficient (ICC) quantified the repeatability of the CVR measurement for each breath-hold regressor type and scale of interest across the variable task performances. The ramp regressors did not fully account for variability in breath-hold performance and did not achieve acceptable repeatability (ICC<0.4) in several regions analysed. In contrast, the end-tidal CO2 regressors resulted in "excellent" repeatability (ICC=0.82) in the average grey matter data, and resulted in acceptable repeatability in all smaller regions tested (ICC>0.4). Further analysis of intra-subject CVR variability across the brain (ICCspatial and voxelwise correlation) supported the use of end-tidal CO2 data to extract robust whole-brain CVR maps, despite variability in breath-hold performance. We conclude that the incorporation of end-tidal CO2 monitoring into scanning enables robust, repeatable measurement of CVR that makes breath-hold challenges suitable for routine clinical practice. © 2013.