Diagnostic accuracy of liver fibrosis based on red cell distribution width (RDW) to platelet ratio with fibroscan in chronic hepatitis B

NASA Astrophysics Data System (ADS)

Sembiring, J.; Jones, F.

2018-03-01

Red cell Distribution Width (RDW) and platelet ratio (RPR) can predict liver fibrosis and cirrhosis in chronic hepatitis B with relatively high accuracy. RPR was superior to other non-invasive methods to predict liver fibrosis, such as AST and ALT ratio, AST and platelet ratio Index and FIB-4. The aim of this study was to assess diagnostic accuracy liver fibrosis by using RDW and platelets ratio in chronic hepatitis B patients based on compared with Fibroscan. This cross-sectional study was conducted at Adam Malik Hospital from January-June 2015. We examine 34 patients hepatitis B chronic, screen RDW, platelet, and fibroscan. Data were statistically analyzed. The result RPR with ROC procedure has an accuracy of 72.3% (95% CI: 84.1% - 97%). In this study, the RPR had a moderate ability to predict fibrosis degree (p = 0.029 with AUC> 70%). The cutoff value RPR was 0.0591, sensitivity and spesificity were 71.4% and 60%, Positive Prediction Value (PPV) was 55.6% and Negative Predictions Value (NPV) was 75%, positive likelihood ratio was 1.79 and negative likelihood ratio was 0.48. RPR have the ability to predict the degree of liver fibrosis in chronic hepatitis B patients with moderate accuracy.

Children's use of decomposition strategies mediates the visuospatial memory and arithmetic accuracy relation.

PubMed

Foley, Alana E; Vasilyeva, Marina; Laski, Elida V

2017-06-01

This study examined the mediating role of children's use of decomposition strategies in the relation between visuospatial memory (VSM) and arithmetic accuracy. Children (N = 78; Age M = 9.36) completed assessments of VSM, arithmetic strategies, and arithmetic accuracy. Consistent with previous findings, VSM predicted arithmetic accuracy in children. Extending previous findings, the current study showed that the relation between VSM and arithmetic performance was mediated by the frequency of children's use of decomposition strategies. Identifying the role of arithmetic strategies in this relation has implications for increasing the math performance of children with lower VSM. Statement of contribution What is already known on this subject? The link between children's visuospatial working memory and arithmetic accuracy is well documented. Frequency of decomposition strategy use is positively related to children's arithmetic accuracy. Children's spatial skill positively predicts the frequency with which they use decomposition. What does this study add? Short-term visuospatial memory (VSM) positively relates to the frequency of children's decomposition use. Decomposition use mediates the relation between short-term VSM and arithmetic accuracy. Children with limited short-term VSM may struggle to use decomposition, decreasing accuracy. © 2016 The British Psychological Society.

Diagnostic accuracy of 3D-transvaginal ultrasound in detecting uterine cavity abnormalities in infertile patients as compared with hysteroscopy.

PubMed

Apirakviriya, Chayanis; Rungruxsirivorn, Tassawan; Phupong, Vorapong; Wisawasukmongchol, Wirach

2016-05-01

To assess diagnostic accuracy of 3D transvaginal ultrasound (3D-TVS) compared with hysteroscopy in detecting uterine cavity abnormalities in infertile women. This prospective observational cross-sectional study was conducted during the July 2013 to December 2013 study period. Sixty-nine women with infertility were enrolled. In the mid to late follicular phase of each subject's menstrual cycle, 3D transvaginal ultrasound and hysteroscopy were performed on the same day in each patient. Hysteroscopy is widely considered to be the gold standard method for investigation of the uterine cavity. Uterine cavity characteristics and abnormalities were recorded. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios were evaluated. Hysteroscopy was successfully performed in all subjects. Hysteroscopy diagnosed pathological findings in 22 of 69 cases (31.8%). There were 18 endometrial polyps, 3 submucous myomas, and 1 septate uterus. Three-dimensional transvaginal ultrasound in comparison with hysteroscopy had 84.1% diagnostic accuracy, 68.2% sensitivity, 91.5% specificity, 79% positive predictive value, and 86% negative predictive value. The positive and negative likelihood ratios were 8.01 and 0.3, respectively. 3D-TVS successfully detected every case of submucous myoma and uterine anomaly. For detection of endometrial polyps, 3D-TVS had 61.1% sensitivity, 91.5% specificity, and 83.1% diagnostic accuracy. 3D-TVS demonstrated 84.1% diagnostic accuracy for detecting uterine cavity abnormalities in infertile women. A significant percentage of infertile patients had evidence of uterine cavity pathology. Hysteroscopy is, therefore, recommended for accurate detection and diagnosis of uterine cavity lesion. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Cytomegalovirus frequency in neonatal intrahepatic cholestasis determined by serology, histology, immunohistochemistry and PCR

PubMed Central

Bellomo-Brandao, Maria Angela; Andrade, Paula D; Costa, Sandra CB; Escanhoela, Cecilia AF; Vassallo, Jose; Porta, Gilda; De Tommaso, Adriana MA; Hessel, Gabriel

2009-01-01

AIM: To determine cytomegalovirus (CMV) frequency in neonatal intrahepatic cholestasis by serology, histological revision (searching for cytomegalic cells), immunohistochemistry, and polymerase chain reaction (PCR), and to verify the relationships among these methods. METHODS: The study comprised 101 non-consecutive infants submitted for hepatic biopsy between March 1982 and December 2005. Serological results were obtained from the patient’s files and the other methods were performed on paraffin-embedded liver samples from hepatic biopsies. The following statistical measures were calculated: frequency, sensibility, specific positive predictive value, negative predictive value, and accuracy. RESULTS: The frequencies of positive results were as follows: serology, 7/64 (11%); histological revision, 0/84; immunohistochemistry, 1/44 (2%), and PCR, 6/77 (8%). Only one patient had positive immunohistochemical findings and a positive PCR. The following statistical measures were calculated between PCR and serology: sensitivity, 33.3%; specificity, 88.89%; positive predictive value, 28.57%; negative predictive value, 90.91%; and accuracy, 82.35%. CONCLUSION: The frequency of positive CMV varied among the tests. Serology presented the highest positive frequency. When compared to PCR, the sensitivity and positive predictive value of serology were low. PMID:19610143

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

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

Malinowski, Kathleen T.; Fischell Department of Bioengineering, University of Maryland, College Park, MD; McAvoy, Thomas J.

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precisionmore » in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.« less

Contingency Awareness Shapes Acquisition and Extinction of Emotional Responses in a Conditioning Model of Pain-Related Fear

PubMed Central

Labrenz, Franziska; Icenhour, Adriane; Benson, Sven; Elsenbruch, Sigrid

2015-01-01

As a fundamental learning process, fear conditioning promotes the formation of associations between predictive cues and biologically significant signals. In its application to pain, conditioning may provide important insight into mechanisms underlying pain-related fear, although knowledge especially in interoceptive pain paradigms remains scarce. Furthermore, while the influence of contingency awareness on excitatory learning is subject of ongoing debate, its role in pain-related acquisition is poorly understood and essentially unknown regarding extinction as inhibitory learning. Therefore, we addressed the impact of contingency awareness on learned emotional responses to pain- and safety-predictive cues in a combined dataset of two pain-related conditioning studies. In total, 75 healthy participants underwent differential fear acquisition, during which rectal distensions as interoceptive unconditioned stimuli (US) were repeatedly paired with a predictive visual cue (conditioned stimulus; CS+) while another cue (CS−) was presented unpaired. During extinction, both CS were presented without US. CS valence, indicating learned emotional responses, and CS-US contingencies were assessed on visual analog scales (VAS). Based on an integrative measure of contingency accuracy, a median-split was performed to compare groups with low vs. high contingency accuracy regarding learned emotional responses. To investigate predictive value of contingency accuracy, regression analyses were conducted. Highly accurate individuals revealed more pronounced negative emotional responses to CS+ and increased positive responses to CS− when compared to participants with low contingency accuracy. Following extinction, highly accurate individuals had fully extinguished pain-predictive cue properties, while exhibiting persistent positive emotional responses to safety signals. In contrast, individuals with low accuracy revealed equally positive emotional responses to both, CS+ and CS−. Contingency accuracy predicted variance in the formation of positive responses to safety cues while no predictive value was found for danger cues following acquisition and for neither cue following extinction. Our findings underscore specific roles of learned danger and safety in pain-related acquisition and extinction. Contingency accuracy appears to distinctly impact learned emotional responses to safety and danger cues, supporting aversive learning to occur independently from CS-US awareness. The interplay of cognitive and emotional factors in shaping excitatory and inhibitory pain-related learning may contribute to altered pain processing, underscoring its clinical relevance in chronic pain. PMID:26640433

Contingency Awareness Shapes Acquisition and Extinction of Emotional Responses in a Conditioning Model of Pain-Related Fear.

PubMed

Labrenz, Franziska; Icenhour, Adriane; Benson, Sven; Elsenbruch, Sigrid

2015-01-01

As a fundamental learning process, fear conditioning promotes the formation of associations between predictive cues and biologically significant signals. In its application to pain, conditioning may provide important insight into mechanisms underlying pain-related fear, although knowledge especially in interoceptive pain paradigms remains scarce. Furthermore, while the influence of contingency awareness on excitatory learning is subject of ongoing debate, its role in pain-related acquisition is poorly understood and essentially unknown regarding extinction as inhibitory learning. Therefore, we addressed the impact of contingency awareness on learned emotional responses to pain- and safety-predictive cues in a combined dataset of two pain-related conditioning studies. In total, 75 healthy participants underwent differential fear acquisition, during which rectal distensions as interoceptive unconditioned stimuli (US) were repeatedly paired with a predictive visual cue (conditioned stimulus; CS(+)) while another cue (CS(-)) was presented unpaired. During extinction, both CS were presented without US. CS valence, indicating learned emotional responses, and CS-US contingencies were assessed on visual analog scales (VAS). Based on an integrative measure of contingency accuracy, a median-split was performed to compare groups with low vs. high contingency accuracy regarding learned emotional responses. To investigate predictive value of contingency accuracy, regression analyses were conducted. Highly accurate individuals revealed more pronounced negative emotional responses to CS(+) and increased positive responses to CS(-) when compared to participants with low contingency accuracy. Following extinction, highly accurate individuals had fully extinguished pain-predictive cue properties, while exhibiting persistent positive emotional responses to safety signals. In contrast, individuals with low accuracy revealed equally positive emotional responses to both, CS(+) and CS(-). Contingency accuracy predicted variance in the formation of positive responses to safety cues while no predictive value was found for danger cues following acquisition and for neither cue following extinction. Our findings underscore specific roles of learned danger and safety in pain-related acquisition and extinction. Contingency accuracy appears to distinctly impact learned emotional responses to safety and danger cues, supporting aversive learning to occur independently from CS-US awareness. The interplay of cognitive and emotional factors in shaping excitatory and inhibitory pain-related learning may contribute to altered pain processing, underscoring its clinical relevance in chronic pain.

Validity of Teacher-Based Vision Screening and Factors Associated with the Accuracy of Vision Screening in Vietnamese Children.

PubMed

Paudel, Prakash; Kovai, Vilas; Naduvilath, Thomas; Phuong, Ha Thanh; Ho, Suit May; Giap, Nguyen Viet

2016-01-01

To assess validity of teacher-based vision screening and elicit factors associated with accuracy of vision screening in Vietnam. After brief training, teachers independently measured visual acuity (VA) in 555 children aged 12-15 years in Ba Ria - Vung Tau Province. Teacher VA measurements were compared to those of refractionists. Sensitivity, specificity, positive predictive value and negative predictive value were calculated for uncorrected VA (UVA) and presenting VA (PVA) 20/40 or worse in either eye. Chi-square, Fisher's exact test and multivariate logistic regression were used to assess factors associated with accuracy of vision screening. Level of significance was set at 5%. Trained teachers in Vietnam demonstrated 86.7% sensitivity, 95.7% specificity, 86.7% positive predictive value and 95.7% negative predictive value in identifying children with visual impairment using the UVA measurement. PVA measurement revealed low accuracy for teachers, which was significantly associated with child's age, sex, spectacle wear and myopic status, but UVA measurement showed no such associations. Better accuracy was achieved in measurement of VA and identification of children with visual impairment using UVA measurement compared to PVA. UVA measurement is recommended for teacher-based vision screening programs.

Accuracy of Self-Reported Cervical and Breast Cancer Screening by Women with Intellectual Disability

ERIC Educational Resources Information Center

Son, Esther; Parish, Susan L.; Swaine, Jamie G.; Luken, Karen

2013-01-01

This study examines the accuracy of self-report of cervical and breast cancer screening by women with intellectual disability ("n" ?=? 155). Data from face-to-face interviews and medical records were analyzed. Total agreement, sensitivity, specificity, positive predictive value and negative predictive value were calculated. Total…

Diagnostic accuracy of tuberculous lymphadenitis fine needle aspiration biopsy confirmed by PCR as gold standard

NASA Astrophysics Data System (ADS)

DSuryadi; Delyuzar; Soekimin

2018-03-01

Indonesia is the second country with the TB (tuberculosis) burden in the world. Improvement in controlling TB and reducing the complications can accelerate early diagnosis and correct treatment. PCR test is a gold standard. However, it is quite expensive for routine diagnosis. Therefore, an accurate and cheaper diagnostic method such as fine needle aspiration biopsy is needed. The study aimsto determine the accuracy of fine needle aspiration biopsy cytology in the diagnosis of tuberculous lymphadenitis. A cross-sectional analytic study was conducted to the samples from patients suspected with tuberculous lymphadenitis. The fine needle aspiration biopsy (FNAB)test was performed and confirmed by PCR test.There is a comparison to the sensitivity, specificity, accuracy, positive predictive value and negative predictive value of both methods. Sensitivity (92.50%), specificity (96.49%), accuracy (94.85%), positive predictive value (94.87%) and negative predictive value (94.83%) were in FNAB test compared to gold standard. We concluded that fine needle aspiration biopsy is a recommendation for a cheaper and accurate diagnostic test for tuberculous lymphadenitis diagnosis.

An Evaluation of Two Internal Surrogates for Determining the Three-Dimensional Position of Peripheral Lung Tumors

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

Spoelstra, Femke; Soernsen de Koste, John R. van; Vincent, Andrew

2009-06-01

Purpose: Both carina and diaphragm positions have been used as surrogates during respiratory-gated radiotherapy. We studied the correlation of both surrogates with three-dimensional (3D) tumor position. Methods and Materials: A total of 59 repeat artifact-free four-dimensional (4D) computed tomography (CT) scans, acquired during uncoached breathing, were identified in 23 patients with Stage I lung cancer. Repeat scans were co-registered to the initial 4D CT scan, and tumor, carina, and ipsilateral diaphragm were manually contoured in all phases of each 4D CT data set. Correlation between positions of carina and diaphragm with 3D tumor position was studied by use of log-likelihoodmore » ratio statistics. Models to predict 3D tumor position from internal surrogates at end inspiration (EI) and end expiration (EE) were developed, and model accuracy was tested by calculating SDs of differences between predicted and actual tumor positions. Results: Motion of both the carina and diaphragm significantly correlated with tumor motion, but log-likelihood ratios indicated that the carina was more predictive for tumor position. When craniocaudal tumor position was predicted by use of craniocaudal carina positions, the SDs of the differences between the predicted and observed positions were 2.2 mm and 2.4 mm at EI and EE, respectively. The corresponding SDs derived with the diaphragm positions were 3.7 mm and 3.9 mm at EI and EE, respectively. Prediction errors in the other directions were comparable. Prediction accuracy was similar at EI and EE. Conclusions: The carina is a better surrogate of 3D tumor position than diaphragm position. Because residual prediction errors were observed in this analysis, additional studies will be performed using audio-coached scans.« less

Accuracy of ultrasound in the detection of liver fibrosis in chronic viral hepatitis.

PubMed

D'Onofrio, Mirko; Martone, Enrico; Brunelli, Silvia; Faccioli, Niccolò; Zamboni, Giulia; Zagni, Irene; Fattovich, Giovanna; Pozzi Mucelli, Roberto

2005-10-01

To assess the accuracy of ultrasonography (US) in the identification and grading of hepatic fibrosis in patients afflicted with chronic viral liver disease, compared to histological examination as a gold standard. We prospectively studied 105 patients (32 F, 73 M) affected by chronic viral liver disease in 36 months. Patients were studied with B-mode US and then underwent US-guided liver biopsy. All the patients were studied with conventional US with a Sequoia 512, 6.0 (Acuson, Mountain View CA, USA). We evaluated the following US parameters: liver margins, parenchymal echotexture, portal vein caliber and spleen diameter. The four B-mode US parameters were used for the US grading (from 0 to 4). Scheuer's grading (from 0 to 4) was used for the histological score. Grades 3 and 4 were considered as positive for fibrosis. Sensitivity, specificity, positive and negative predictive values and accuracy were calculated in the case of absence, positivity of one or all the US parameters. The correlation between US and histological scores was evaluated with Spearman's test. At histology seventy-seven patients (73%) had absent grade 0 (1 patient; 1%), low-moderate grade 1 (35 patients; 33%) or grade 2 (41 patients; 39%) liver fibrosis. Twenty-eight patients (27%) had severe grade 3 (16 patients; 15%) or grade 4 (12 patients; 11%) fibrosis. In the case of absence of US parameters sensitivity was 32%, specificity 32%, positive predictive value 15%, negative predictive value 57% and accuracy 32%. In the case of positivity of at least one of the US parameters the values were 68%, 68%, 43%, 84% and 69%. In the case of presence of all the US signs the results were 25%, 100%, 100%, 79% and 80%. None of the 77 patients with a healthy liver or with low-grade fibrosis was positive for all the US parameters. All the patients positive for all of the ultrasonographic parameters had high-grade fibrosis or cirrhosis at liver biopsy. Correlation between B-mode and histological scores was not statistically significant (Rs=0.45; p=0.0001). US identification of liver fibrosis in chronic liver disease is possible with 25% sensitivity, 100% specificity, 100% positive predictive value and 79% negative predictive value, with an 80% diagnostic accuracy.

High-definition endoscopy with digital chromoendoscopy for histologic prediction of distal colorectal polyps.

PubMed

Rath, Timo; Tontini, Gian E; Nägel, Andreas; Vieth, Michael; Zopf, Steffen; Günther, Claudia; Hoffman, Arthur; Neurath, Markus F; Neumann, Helmut

2015-10-22

Distal diminutive colorectal polyps are common and accurate endoscopic prediction of hyperplastic or adenomatous polyp histology could reduce procedural time, costs and potential risks associated with the resection. Within this study we assessed whether digital chromoendoscopy can accurately predict the histology of distal diminutive colorectal polyps according to the ASGE PIVI statement. In this prospective cohort study, 224 consecutive patients undergoing screening or surveillance colonoscopy were included. Real time histology of 121 diminutive distal colorectal polyps was evaluated using high-definition endoscopy with digital chromoendoscopy and the accuracy of predicting histology with digital chromoendoscopy was assessed. The overall accuracy of digital chromoendoscopy for prediction of adenomatous polyp histology was 90.1 %. Sensitivity, specificity, positive and negative predictive values were 93.3, 88.7, 88.7, and 93.2 %, respectively. In high-confidence predictions, the accuracy increased to 96.3 % while sensitivity, specificity, positive and negative predictive values were calculated as 98.1, 94.4, 94.5, and 98.1 %, respectively. Surveillance intervals with digital chromoendoscopy were correctly predicted with >90 % accuracy. High-definition endoscopy in combination with digital chromoendoscopy allowed real-time in vivo prediction of distal colorectal polyp histology and is accurate enough to leave distal colorectal polyps in place without resection or to resect and discard them without pathologic assessment. This approach has the potential to reduce costs and risks associated with the redundant removal of diminutive colorectal polyps. ClinicalTrials NCT02217449.

Evaluating the predictive accuracy and the clinical benefit of a nomogram aimed to predict survival in node-positive prostate cancer patients: External validation on a multi-institutional database.

PubMed

Bianchi, Lorenzo; Schiavina, Riccardo; Borghesi, Marco; Bianchi, Federico Mineo; Briganti, Alberto; Carini, Marco; Terrone, Carlo; Mottrie, Alex; Gacci, Mauro; Gontero, Paolo; Imbimbo, Ciro; Marchioro, Giansilvio; Milanese, Giulio; Mirone, Vincenzo; Montorsi, Francesco; Morgia, Giuseppe; Novara, Giacomo; Porreca, Angelo; Volpe, Alessandro; Brunocilla, Eugenio

2018-04-06

To assess the predictive accuracy and the clinical value of a recent nomogram predicting cancer-specific mortality-free survival after surgery in pN1 prostate cancer patients through an external validation. We evaluated 518 prostate cancer patients treated with radical prostatectomy and pelvic lymph node dissection with evidence of nodal metastases at final pathology, at 10 tertiary centers. External validation was carried out using regression coefficients of the previously published nomogram. The performance characteristics of the model were assessed by quantifying predictive accuracy, according to the area under the curve in the receiver operating characteristic curve and model calibration. Furthermore, we systematically analyzed the specificity, sensitivity, positive predictive value and negative predictive value for each nomogram-derived probability cut-off. Finally, we implemented decision curve analysis, in order to quantify the nomogram's clinical value in routine practice. External validation showed inferior predictive accuracy as referred to in the internal validation (65.8% vs 83.3%, respectively). The discrimination (area under the curve) of the multivariable model was 66.7% (95% CI 60.1-73.0%) by testing with receiver operating characteristic curve analysis. The calibration plot showed an overestimation throughout the range of predicted cancer-specific mortality-free survival rates probabilities. However, in decision curve analysis, the nomogram's use showed a net benefit when compared with the scenarios of treating all patients or none. In an external setting, the nomogram showed inferior predictive accuracy and suboptimal calibration characteristics as compared to that reported in the original population. However, decision curve analysis showed a clinical net benefit, suggesting a clinical implication to correctly manage pN1 prostate cancer patients after surgery. © 2018 The Japanese Urological Association.

The Accuracy of the Spot Sign and the Blend Sign for Predicting Hematoma Expansion in Patients with Spontaneous Intracerebral Hemorrhage.

PubMed

Zheng, Jun; Yu, Zhiyuan; Xu, Zhao; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

2017-05-12

BACKGROUND Hematoma expansion is associated with poor outcome in intracerebral hemorrhage (ICH) patients. The spot sign and the blend sign are reliable tools for predicting hematoma expansion in ICH patients. The aim of this study was to compare the accuracy of the two signs in the prediction of hematoma expansion. MATERIAL AND METHODS Patients with spontaneous ICH were screened for the presence of the computed tomography angiography (CTA) spot sign and the non-contrast CT (NCCT) blend sign within 6 hours after onset of symptoms. The sensitivity, specificity, and positive and negative predictive values of the spot sign and the blend sign in predicting hematoma expansion were calculated. The accuracy of the spot sign and the blend sign in predicting hematoma expansion was analyzed by receiver-operator analysis. RESULTS A total of 115 patients were enrolled in this study. The spot sign was observed in 25 (21.74%) patients, whereas the blend sign was observed in 22 (19.13%) patients. Of the 28 patients with hematoma expansion, the CTA spot sign was found on admission CT scans in 16 (57.14%) and the NCCT blend sign in 12 (42.86%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of the spot sign for predicting hematoma expansion were 57.14%, 89.66%, 64.00%, and 86.67%, respectively. In contrast, the sensitivity, specificity, positive predictive value, and negative predictive value of the blend sign were 42.86%, 88.51%, 54.55%, and 82.80%, respectively. The area under the curve (AUC) of the spot sign was 0.734, which was higher than that of the blend sign (0.657). CONCLUSIONS Both the spot sign and the blend sign seemed to be good predictors for hematoma expansion, and the spot sign appeared to have better predictive accuracy.

The Accuracy of the Spot Sign and the Blend Sign for Predicting Hematoma Expansion in Patients with Spontaneous Intracerebral Hemorrhage

PubMed Central

Zheng, Jun; Yu, Zhiyuan; Xu, Zhao; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

2017-01-01

Background Hematoma expansion is associated with poor outcome in intracerebral hemorrhage (ICH) patients. The spot sign and the blend sign are reliable tools for predicting hematoma expansion in ICH patients. The aim of this study was to compare the accuracy of the two signs in the prediction of hematoma expansion. Material/Methods Patients with spontaneous ICH were screened for the presence of the computed tomography angiography (CTA) spot sign and the non-contrast CT (NCCT) blend sign within 6 hours after onset of symptoms. The sensitivity, specificity, and positive and negative predictive values of the spot sign and the blend sign in predicting hematoma expansion were calculated. The accuracy of the spot sign and the blend sign in predicting hematoma expansion was analyzed by receiver-operator analysis. Results A total of 115 patients were enrolled in this study. The spot sign was observed in 25 (21.74%) patients, whereas the blend sign was observed in 22 (19.13%) patients. Of the 28 patients with hematoma expansion, the CTA spot sign was found on admission CT scans in 16 (57.14%) and the NCCT blend sign in 12 (42.86%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of the spot sign for predicting hematoma expansion were 57.14%, 89.66%, 64.00%, and 86.67%, respectively. In contrast, the sensitivity, specificity, positive predictive value, and negative predictive value of the blend sign were 42.86%, 88.51%, 54.55%, and 82.80%, respectively. The area under the curve (AUC) of the spot sign was 0.734, which was higher than that of the blend sign (0.657). Conclusions Both the spot sign and the blend sign seemed to be good predictors for hematoma expansion, and the spot sign appeared to have better predictive accuracy. PMID:28498827

Optical coherence tomography in the diagnosis of dysplasia and adenocarcinoma in Barret's esophagus

NASA Astrophysics Data System (ADS)

Gladkova, N. D.; Zagaynova, E. V.; Zuccaro, G.; Kareta, M. V.; Feldchtein, F. I.; Balalaeva, I. V.; Balandina, E. B.

2007-02-01

Statistical analysis of endoscopic optical coherence tomography (EOCT) surveillance of 78 patients with Barrett's esophagus (BE) is presented in this study. The sensitivity of OCT device in retrospective open detection of early malignancy (including high grade dysplasia and intramucosal adenocarcinoma (IMAC)) was 75%, specificity 82%, diagnostic accuracy - 80%, positive predictive value- 60%, negative predictive value- 87%. In the open recognition of IMAC sensitivity was 81% and specificity were 85% each. Results of a blind recognition with the same material were similar: sensitivity - 77%, specificity 85%, diagnostic accuracy - 82%, positive predictive value- 70%, negative predictive value- 87%. As the endoscopic detection of early malignancy is problematic, OCT holds great promise in enhancing the diagnostic capability of clinical GI endoscopy.

Multi-Stage Target Tracking with Drift Correction and Position Prediction

NASA Astrophysics Data System (ADS)

Chen, Xin; Ren, Keyan; Hou, Yibin

2018-04-01

Most existing tracking methods are hard to combine accuracy and performance, and do not consider the shift between clarity and blur that often occurs. In this paper, we propound a multi-stage tracking framework with two particular modules: position prediction and corrective measure. We conduct tracking based on correlation filter with a corrective measure module to increase both performance and accuracy. Specifically, a convolutional network is used for solving the blur problem in realistic scene, training methodology that training dataset with blur images generated by the three blur algorithms. Then, we propose a position prediction module to reduce the computation cost and make tracker more capable of fast motion. Experimental result shows that our tracking method is more robust compared to others and more accurate on the benchmark sequences.

Artificial neural networks: Predicting head CT findings in elderly patients presenting with minor head injury after a fall.

PubMed

Dusenberry, Michael W; Brown, Charles K; Brewer, Kori L

2017-02-01

To construct an artificial neural network (ANN) model that can predict the presence of acute CT findings with both high sensitivity and high specificity when applied to the population of patients≥age 65years who have incurred minor head injury after a fall. An ANN was created in the Python programming language using a population of 514 patients ≥ age 65 years presenting to the ED with minor head injury after a fall. The patient dataset was divided into three parts: 60% for "training", 20% for "cross validation", and 20% for "testing". Sensitivity, specificity, positive and negative predictive values, and accuracy were determined by comparing the model's predictions to the actual correct answers for each patient. On the "cross validation" data, the model attained a sensitivity ("recall") of 100.00%, specificity of 78.95%, PPV ("precision") of 78.95%, NPV of 100.00%, and accuracy of 88.24% in detecting the presence of positive head CTs. On the "test" data, the model attained a sensitivity of 97.78%, specificity of 89.47%, PPV of 88.00%, NPV of 98.08%, and accuracy of 93.14% in detecting the presence of positive head CTs. ANNs show great potential for predicting CT findings in the population of patients ≥ 65 years of age presenting with minor head injury after a fall. As a good first step, the ANN showed comparable sensitivity, predictive values, and accuracy, with a much higher specificity than the existing decision rules in clinical usage for predicting head CTs with acute intracranial findings. Copyright © 2016 Elsevier Inc. All rights reserved.

Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches

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

Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001; Gupta, Shikha

Robust global models capable of discriminating positive and non-positive carcinogens; and predicting carcinogenic potency of chemicals in rodents were developed. The dataset of 834 structurally diverse chemicals extracted from Carcinogenic Potency Database (CPDB) was used which contained 466 positive and 368 non-positive carcinogens. Twelve non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals and nonlinearity in the data were evaluated using Tanimoto similarity index and Brock–Dechert–Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) models were constructed for classification and function optimization problems using the carcinogenicity end point in rat. Validation of the models wasmore » performed using the internal and external procedures employing a wide series of statistical checks. PNN constructed using five descriptors rendered classification accuracy of 92.09% in complete rat data. The PNN model rendered classification accuracies of 91.77%, 80.70% and 92.08% in mouse, hamster and pesticide data, respectively. The GRNN constructed with nine descriptors yielded correlation coefficient of 0.896 between the measured and predicted carcinogenic potency with mean squared error (MSE) of 0.44 in complete rat data. The rat carcinogenicity model (GRNN) applied to the mouse and hamster data yielded correlation coefficient and MSE of 0.758, 0.71 and 0.760, 0.46, respectively. The results suggest for wide applicability of the inter-species models in predicting carcinogenic potency of chemicals. Both the PNN and GRNN (inter-species) models constructed here can be useful tools in predicting the carcinogenicity of new chemicals for regulatory purposes. - Graphical abstract: Figure (a) shows classification accuracies (positive and non-positive carcinogens) in rat, mouse, hamster, and pesticide data yielded by optimal PNN model. Figure (b) shows generalization and predictive abilities of the interspecies GRNN model to predict the carcinogenic potency of diverse chemicals. - Highlights: • Global robust models constructed for carcinogenicity prediction of diverse chemicals. • Tanimoto/BDS test revealed structural diversity of chemicals and nonlinearity in data. • PNN/GRNN successfully predicted carcinogenicity/carcinogenic potency of chemicals. • Developed interspecies PNN/GRNN models for carcinogenicity prediction. • Proposed models can be used as tool to predict carcinogenicity of new chemicals.« less

The accuracy of HIV rapid testing in integrated bio-behavioral surveys of men who have sex with men across 5 Provinces in South Africa

PubMed Central

Kufa, Tendesayi; Lane, Tim; Manyuchi, Albert; Singh, Beverley; Isdahl, Zachary; Osmand, Thomas; Grasso, Mike; Struthers, Helen; McIntyre, James; Chipeta, Zawadi; Puren, Adrian

2017-01-01

Abstract We describe the accuracy of serial rapid HIV testing among men who have sex with men (MSM) in South Africa and discuss the implications for HIV testing and prevention. This was a cross-sectional survey conducted at five stand-alone facilities from five provinces. Demographic, behavioral, and clinical data were collected. Dried blood spots were obtained for HIV-related testing. Participants were offered rapid HIV testing using 2 rapid diagnostic tests (RDTs) in series. In the laboratory, reference HIV testing was conducted using a third-generation enzyme immunoassay (EIA) and a fourth-generation EIA as confirmatory. Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, false-positive, and false-negative rates were determined. Between August 2015 and July 2016, 2503 participants were enrolled. Of these, 2343 were tested by RDT on site with a further 2137 (91.2%) having definitive results on both RDT and EIA. Sensitivity, specificity, positive predictive value, negative predictive value, false-positive rates, and false-negative rates were 92.6% [95% confidence interval (95% CI) 89.6–94.8], 99.4% (95% CI 98.9–99.7), 97.4% (95% CI 95.2–98.6), 98.3% (95% CI 97.6–98.8), 0.6% (95% CI 0.3–1.1), and 7.4% (95% CI 5.2–10.4), respectively. False negatives were similar to true positives with respect to virological profiles. Overall accuracy of the RDT algorithm was high, but sensitivity was lower than expected. Post-HIV test counseling should include discussions of possible false-negative results and the need for retesting among HIV negatives. PMID:28700474

Accuracy test for link prediction in terms of similarity index: The case of WS and BA models

NASA Astrophysics Data System (ADS)

Ahn, Min-Woo; Jung, Woo-Sung

2015-07-01

Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction with regard to network models. In this paper, we thus apply link prediction to two network models: The Watts-Strogatz (WS) model and Barabási-Albert (BA) model. We attempt to gain a better understanding of the relation between accuracy and each network parameter (mean degree, the number of nodes and the rewiring probability in the WS model) through network models. Six similarity indices are used, with precision and area under the ROC curve (AUC) value as the accuracy metrics. We observe a positive correlation between mean degree and accuracy, and size independence of the AUC value.

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Newman, Clark P.; Slojkowski, Steven E.; Carpenter, J. Russell

2014-01-01

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

Electrophysiological evidence for preserved primacy of lexical prediction in aging.

PubMed

Dave, Shruti; Brothers, Trevor A; Traxler, Matthew J; Ferreira, Fernanda; Henderson, John M; Swaab, Tamara Y

2018-05-28

Young adults show consistent neural benefits of predictable contexts when processing upcoming words, but these benefits are less clear-cut in older adults. Here we disentangle the neural correlates of prediction accuracy and contextual support during word processing, in order to test current theories that suggest that neural mechanisms underlying predictive processing are specifically impaired in older adults. During a sentence comprehension task, older and younger readers were asked to predict passage-final words and report the accuracy of these predictions. Age-related reductions were observed for N250 and N400 effects of prediction accuracy, as well as for N400 effects of contextual support independent of prediction accuracy. Furthermore, temporal primacy of predictive processing (i.e., earlier facilitation for successful predictions) was preserved across the lifespan, suggesting that predictive mechanisms are unlikely to be uniquely impaired in older adults. In addition, older adults showed prediction effects on frontal post-N400 positivities (PNPs) that were similar in amplitude to PNPs in young adults. Previous research has shown correlations between verbal fluency and lexical prediction in older adult readers, suggesting that the production system may be linked to capacity for lexical prediction, especially in aging. The current study suggests that verbal fluency modulates PNP effects of contextual support, but not prediction accuracy. Taken together, our findings suggest that aging does not result in specific declines in lexical prediction. Copyright © 2018 Elsevier Ltd. All rights reserved.

Preoperative prediction of histopathological outcome in basal cell carcinoma: flat surface and multiple small erosions predict superficial basal cell carcinoma in lighter skin types.

PubMed

Ahnlide, I; Zalaudek, I; Nilsson, F; Bjellerup, M; Nielsen, K

2016-10-01

Prediction of the histopathological subtype of basal cell carcinoma (BCC) is important for tailoring optimal treatment, especially in patients with suspected superficial BCC (sBCC). To assess the accuracy of the preoperative prediction of subtypes of BCC in clinical practice, to evaluate whether dermoscopic examination enhances accuracy and to find dermoscopic criteria for discriminating sBCC from other subtypes. The main presurgical diagnosis was compared with the histopathological, postoperative diagnosis of routinely excised skin tumours in a predominantly fair-skinned patient cohort of northern Europe during a study period of 3 years (2011-13). The study period was split in two: during period 1, dermoscopy was optional (850 cases with a pre- or postoperative diagnosis of BCC), while during period 2 (after an educational dermoscopic update) dermoscopy was mandatory (651 cases). A classification tree based on clinical and dermoscopic features for prediction of sBCC was applied. For a total of 3544 excised skin tumours, the sensitivity for the diagnosis of BCC (any subtype) was 93·3%, specificity 91·8%, and the positive predictive value (PPV) 89·0%. The diagnostic accuracy as well as the PPV and the positive likelihood ratio for sBCC were significantly higher when dermoscopy was mandatory. A flat surface and multiple small erosions predicted sBCC. The study shows a high accuracy for an overall diagnosis of BCC and increased accuracy in prediction of sBCC for the period when dermoscopy was applied in all cases. The most discriminating findings for sBCC, based on clinical and dermoscopic features in this fair-skinned population, were a flat surface and multiple small erosions. © 2016 British Association of Dermatologists.

Alcohol use among university students: Considering a positive deviance approach.

PubMed

Tucker, Maryanne; Harris, Gregory E

2016-09-01

Harmful alcohol consumption among university students continues to be a significant issue. This study examined whether variables identified in the positive deviance literature would predict responsible alcohol consumption among university students. Surveyed students were categorized into three groups: abstainers, responsible drinkers and binge drinkers. Multinomial logistic regression modelling was significant (χ(2) = 274.49, degrees of freedom = 24, p < .001), with several variables predicting group membership. While the model classification accuracy rate (i.e. 71.2%) exceeded the proportional by chance accuracy rate (i.e. 38.4%), providing further support for the model, the model itself best predicted binge drinker membership over the other two groups. © The Author(s) 2015.

Exfoliative cytology: a helpful tool for the diagnosis of paracoccidioidomycosis.

PubMed

Cardoso, S V; Moreti, M M; Costa, I M; Loyola, A M

2001-07-01

To describe the main cytological findings associated with smears collected from oral lesions of paracoccidioidomycosis and to appraise the use of cytology as a diagnostic tool for the disease. Cytological smears and biopsies were collected from 40 lesions with a clinical suspicion of paracoccidioidomycosis. Evaluation of the sensitivity, specificity, positive and negative predictive values, accuracy and the positive likeness ratio of the oral smear when compared with the histological diagnosis, was performed. The latter is considered the 'gold standard' for comparison. The main morphological findings were the rounded-shaped, birefringent and multiple-budded fungi, Langhans' giant cells and epithelioid cells. The following associative measures were found: sensitivity, 67.9%; specificity, 91.7%; positive predictive value, 95.0%; negative predictive value, 55.0%; accuracy, 75.0%; and positive likeness ratio, 8.14. The cytological findings of paracoccidioidomycosis are characteristic and cytology is accurate in the diagnosis of the disease. Positive patients should be treated. Negative patients should be submitted to biopsy to confirm or to dismiss the diagnosis of this mycosis.

Should bedside sonography be used first to diagnose pneumothorax secondary to blunt trauma?

PubMed

Donmez, Halil; Tokmak, Turgut Tursem; Yildirim, Afra; Buyukoglan, Hakan; Ozturk, Mehmet; Yaşar Ayaz, Umit; Mavili, Ertugrul

2012-01-01

BACKGROUND.: Our purpose was to evaluate the effectiveness of bedside sonography (US) in the detection of pneumothorax secondary to blunt thoracic trauma. METHODS.: In this prospective study, 240 hemithoraces of 120 consecutive patients with multiple trauma were evaluated with chest radiographs (CXR) and bedside thoracic US for the diagnosis of pneumothorax. CT examinations were performed in 68 patients. Fifty-two patients who did not undergo CT examinations were excluded from the study. US examinations were performed independently at bedside by two radiologists who were not informed about CXR and CT findings. CXRs were interpreted by two radiologists who were unaware of the US and CT results. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CXR and US were calculated. RESULTS.: One hundred thirty-six hemithoraces were assessed in 68 patients. A total of 35 pneumothoraces were detected in 33 patients. On US, the diagnosis of pneumothorax was correct in 32 hemithoraces. In 98 hemithoraces without pneumothorax, US was normal. With US examination, there were three false-positive and three false-negative results. The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of US were 91.4%, 97%, 91.4%, 97%, and 97%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CXR were 82.7%, 89.7%, 68.5%, 95%, and 89.5%, respectively. CONCLUSIONS.: Bedside thoracic US is an accurate method that can be used in trauma patients instead of CXR for the detection of pneumothorax. Copyright © 2012 Wiley Periodicals, Inc.

PPCM: Combing multiple classifiers to improve protein-protein interaction prediction

DOE PAGES

Yao, Jianzhuang; Guo, Hong; Yang, Xiaohan

2015-08-01

Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be improved. We developed a method called protein-protein interaction prediction classifiers merger (PPCM), and this method combines output from two PPI prediction tools, GO2PPI and Phyloprof, using Random Forests algorithm. The performance of PPCM was tested by area under the curve (AUC) using anmore » assembled Gold Standard database that contains both positive and negative PPI pairs. Our AUC test showed that PPCM significantly improved the PPI prediction accuracy over the corresponding individual classifiers. We found that additional classifiers incorporated into PPCM could lead to further improvement in the PPI prediction accuracy. Furthermore, cross species PPCM could achieve competitive and even better prediction accuracy compared to the single species PPCM. This study established a robust pipeline for PPI prediction by integrating multiple classifiers using Random Forests algorithm. Ultimately, this pipeline will be useful for predicting PPI in nonmodel species.« less

SU-E-J-191: Motion Prediction Using Extreme Learning Machine in Image Guided Radiotherapy

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

Jia, J; Cao, R; Pei, X

Purpose: Real-time motion tracking is a critical issue in image guided radiotherapy due to the time latency caused by image processing and system response. It is of great necessity to fast and accurately predict the future position of the respiratory motion and the tumor location. Methods: The prediction of respiratory position was done based on the positioning and tracking module in ARTS-IGRT system which was developed by FDS Team (www.fds.org.cn). An approach involving with the extreme learning machine (ELM) was adopted to predict the future respiratory position as well as the tumor’s location by training the past trajectories. For themore » training process, a feed-forward neural network with one single hidden layer was used for the learning. First, the number of hidden nodes was figured out for the single layered feed forward network (SLFN). Then the input weights and hidden layer biases of the SLFN were randomly assigned to calculate the hidden neuron output matrix. Finally, the predicted movement were obtained by applying the output weights and compared with the actual movement. Breathing movement acquired from the external infrared markers was used to test the prediction accuracy. And the implanted marker movement for the prostate cancer was used to test the implementation of the tumor motion prediction. Results: The accuracy of the predicted motion and the actual motion was tested. Five volunteers with different breathing patterns were tested. The average prediction time was 0.281s. And the standard deviation of prediction accuracy was 0.002 for the respiratory motion and 0.001 for the tumor motion. Conclusion: The extreme learning machine method can provide an accurate and fast prediction of the respiratory motion and the tumor location and therefore can meet the requirements of real-time tumor-tracking in image guided radiotherapy.« less

The efficacy of the reverse contrast mode in digital radiography for the detection of proximal dentinal caries

PubMed Central

Miri, Shimasadat; Mehralizadeh, Sandra; Sadri, Donya; Motamedi, Mahmood Reza Kalantar

2015-01-01

Purpose This study evaluated the diagnostic accuracy of the reverse contrast mode in intraoral digital radiography for the detection of proximal dentinal caries, in comparison with the original digital radiographs. Materials and Methods Eighty extracted premolars with no clinically apparent caries were selected, and digital radiographs of them were taken separately in standard conditions. Four observers examined the original radiographs and the same radiographs in the reverse contrast mode with the goal of identifying proximal dentinal caries. Microscopic sections 5 µm in thickness were prepared from the teeth in the mesiodistal direction. Four slides prepared from each sample used as the diagnostic gold standard. The data were analyzed using SPSS (α=0.05). Results Our results showed that the original radiographs in order to identify proximal dentinal caries had the following values for sensitivity, specificity, positive predictive value, negative predictive value, and accuracy, respectively: 72.5%, 90%, 87.2%, 76.5%, and 80.9%. For the reverse contrast mode, however, the corresponding values were 63.1%, 89.4%, 87.1%, 73.5%, and 78.8%, respectively. The sensitivity of original digital radiograph for detecting proximal dentinal caries was significantly higher than that of reverse contrast mode (p<0.05). However, no statistically significant differences were found regarding specificity, positive predictive value, negative predictive value, or accuracy (p>0.05). Conclusion The sensitivity of the original digital radiograph for detecting proximal dentinal caries was significantly higher than that of the reversed contrast images. However, no statistically significant differences were found between these techniques regarding specificity, positive predictive value, negative predictive value, or accuracy. PMID:26389055

[Evaluation of performance of five bioinformatics software for the prediction of missense mutations].

PubMed

Chen, Qianting; Dai, Congling; Zhang, Qianjun; Du, Juan; Li, Wen

2016-10-01

To study the prediction performance evaluation with five kinds of bioinformatics software (SIFT, PolyPhen2, MutationTaster, Provean, MutationAssessor). From own database for genetic mutations collected over the past five years, Chinese literature database, Human Gene Mutation Database, and dbSNP, 121 missense mutations confirmed by functional studies, and 121 missense mutations suspected to be pathogenic by pedigree analysis were used as positive gold standard, while 242 missense mutations with minor allele frequency (MAF)>5% in dominant hereditary diseases were used as negative gold standard. The selected mutations were predicted with the five software. Based on the results, the performance of the five software was evaluated for their sensitivity, specificity, positive predict value, false positive rate, negative predict value, false negative rate, false discovery rate, accuracy, and receiver operating characteristic curve (ROC). In terms of sensitivity, negative predictive value and false negative rate, the rank was MutationTaster, PolyPhen2, Provean, SIFT, and MutationAssessor. For specificity and false positive rate, the rank was MutationTaster, Provean, MutationAssessor, SIFT, and PolyPhen2. For positive predict value and false discovery rate, the rank was MutationTaster, Provean, MutationAssessor, PolyPhen2, and SIFT. For area under the ROC curve (AUC) and accuracy, the rank was MutationTaster, Provean, PolyPhen2, MutationAssessor, and SIFT. The prediction performance of software may be different when using different parameters. Among the five software, MutationTaster has the best prediction performance.

Prediction of subcellular localization of eukaryotic proteins using position-specific profiles and neural network with weighted inputs.

PubMed

Zou, Lingyun; Wang, Zhengzhi; Huang, Jiaomin

2007-12-01

Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles (PSP) have been introduced as important characteristics of proteins in this article. In this study, to obtain position-specific profiles, the Position Specific Iterative-Basic Local Alignment Search Tool (PSI-BLAST) has been used to search for protein sequences in a database. Position-specific scoring matrices are extracted from the profiles as one class of characteristics. Four-part amino acid compositions and 1st-7th order dipeptide compositions have also been calculated as the other two classes of characteristics. Therefore, twelve characteristic vectors are extracted from each of the protein sequences. Next, the characteristic vectors are weighed by a simple weighing function and inputted into a BP neural network predictor named PSP-Weighted Neural Network (PSP-WNN). The Levenberg-Marquardt algorithm is employed to adjust the weight matrices and thresholds during the network training instead of the error back propagation algorithm. With a jackknife test on the RH2427 dataset, PSP-WNN has achieved a higher overall prediction accuracy of 88.4% rather than the prediction results by the general BP neural network, Markov model, and fuzzy k-nearest neighbors algorithm on this dataset. In addition, the prediction performance of PSP-WNN has been evaluated with a five-fold cross validation test on the PK7579 dataset and the prediction results have been consistently better than those of the previous method on the basis of several support vector machines, using compositions of both amino acids and amino acid pairs. These results indicate that PSP-WNN is a powerful tool for subcellular localization prediction. At the end of the article, influences on prediction accuracy using different weighting proportions among three characteristic vector categories have been discussed. An appropriate proportion is considered by increasing the prediction accuracy.

Heart imaging: the accuracy of the 64-MSCT in the detection of coronary artery disease.

PubMed

Alessandri, N; Di Matteo, A; Rondoni, G; Petrassi, M; Tufani, F; Ferrari, R; Laghi, A

2009-01-01

At present, coronary angiography represents the gold standard technique for the diagnosis of coronary artery disease. Our aim is to compare the conventional coronary angiography to the coronary 64-multislice spiral computed tomography (64-MSCT), a new and non-invasive cardiac imaging technique. The last generation of MSCT scanners show a better imaging quality, due to a greater spatial and temporal resolution. Four expert observers (two cardiologists and two radiologists) have compared the angiographic data with the accuracy of the 64-MSCT in the detection and evaluation of coronary vessels stenoses. From the data obtained, the sensibility, the specificity and the accuracy of the coronary 64-MSCT have been defined. We have enrolled 75 patients (57 male, 18 female, mean age 61.83 +/- 10.38; range 30-80 years) with known or suspected coronary artery disease. The above population has been divided into 3 groups: Group A (Gr. A) with 40 patients (mean age 60.7 +/- 12.5) affected by both non-significant and significant coronary artery disease; Group B (Gr. B) with 25 patients (mean age 60.3 +/- 14.6) who underwent to percutaneous coronary intervention (PCI); Group C (Gr. C) with 10 patients (mean age 54.20 +/- 13.7) without any coronary angiographic stenoses. All the patients underwent non-invasive exams, conventional coronary angiography and coronary 64-MSCT. The comparison of the data obtained has been carried out according to a per group analysis, per patient analysis and per segment analysis. Moreover, the accuracy of the 64-MSCT has been defined for the detection of >75%, 50-75% and <50% coronary stenoses. Coronary angiography has identified significant coronary artery disease in 75% of the patients in the Gr. A and in 73% of the patients in the Gr. B. No coronary stenoses have been detected in Gr. C. According to a per segment analysis, in Gr. A, 36% of the segments analysed have shown a coronary stenosis (37% stenoses >75%, 32% stenoses 50-75% and 31% stenoses <50%). In Gr. B, 32% of the segments have shown a coronary stenosis (33% stenoses >75%, 29% stenoses 50-75% and 38% stenoses <50%). In-stent disease has been shown in only 4 of the 29 coronary stents identified. In Gr. A, coronary 64-MSCT has confirmed the angiographic results in the 93% of cases (sensibility 93%, specificity 100%, positive predictive value 100% and negative predictive value 83%) while, in Gr. B, this confirm has been obtained only in 64% of cases (sensibility 64%, specificity 100%, positive predictive value 100% and negative predictive value 50%). In Gr. C, we have observed a complete agreement between angiographic and CT data (sensibility, specificity, positive predictive value and negative predictive value 100%). According to a per segment analysis, the angiographic results have been confirmed in 98% of cases in Gr. A (sensibility 98%, specificity 94%, positive predictive value 90% and negative predictive value 94%) but only in 55% of cases in Gr. B (sensibility 55%, specificity 90%, positive predictive value 71% and negative predictive value 81%). Moreover, only 1 of the 4 in-stent restenoses has been detected (sensibility 25%, specificity 100%, positive predictive value 100% and negative predictive value 77%). Coronary angiography has detected a greater number of coronary stenoses than the 64-MSCT. 64-MSCT has demonstrated better accuracy in the study of coronary vessels wider than 2 mm, while its accuracy is lower for smaller vessels (diameter < 2.5 mm) and for the identification of in-stent restenosis, because there is a reduced image quality for these vessels and therefore a lower accuracy in the coronary stenosis detection. Nevertheless, 64-MSCT shows high accuracy and it can be considered a comparative but not a substitutive exam of the coronary angiography. Several technical limitations of the 64-MSCT are responsible of its lower accuracy versus the conventional coronary angiography, but solving these technical problems could give us a new non-invasive imaging technique for the study of coronary stents.

Diagnostic accuracy of uriSed automated urine microscopic sediment analyzer and dipstick parameters in predicting urine culture test results.

PubMed

Huysal, Kağan; Budak, Yasemin U; Karaca, Ayse Ulusoy; Aydos, Murat; Kahvecioğlu, Serdar; Bulut, Mehtap; Polat, Murat

2013-01-01

Urinary tract infection (UTI) is one of the most common types of infection. Currently, diagnosis is primarily based on microbiologic culture, which is time- and labor-consuming. The aim of this study was to assess the diagnostic accuracy of urinalysis results from UriSed (77 Electronica, Budapest, Hungary), an automated microscopic image-based sediment analyzer, in predicting positive urine cultures. We examined a total of 384 urine specimens from hospitalized patients and outpatients attending our hospital on the same day for urinalysis, dipstick tests and semi-quantitative urine culture. The urinalysis results were compared with those of conventional semiquantitative urine culture. Of 384 urinary specimens, 68 were positive for bacteriuria by culture, and were thus considered true positives. Comparison of these results with those obtained from the UriSed analyzer indicated that the analyzer had a specificity of 91.1%, a sensitivity of 47.0%, a positive predictive value (PPV) of 53.3% (95% confidence interval (CI) = 40.8-65.3), and a negative predictive value (NPV) of 88.8% (95% CI = 85.0-91.8%). The accuracy was 83.3% when the urine leukocyte parameter was used, 76.8% when bacteriuria analysis of urinary sediment was used, and 85.1% when the bacteriuria and leukocyturia parameters were combined. The presence of nitrite was the best indicator of culture positivity (99.3% specificity) but had a negative likelihood ratio of 0.7, indicating that it was not a reliable clinical test. Although the specificity of the UriSed analyzer was within acceptable limits, the sensitivity value was low. Thus, UriSed urinalysis resuIts do not accurately predict the outcome of culture.

Accuracy of FDG-PET to diagnose lung cancer in a region of endemic granulomatous disease.

PubMed

Deppen, Stephen; Putnam, Joe B; Andrade, Gabriela; Speroff, Theodore; Nesbitt, Jonathan C; Lambright, Eric S; Massion, Pierre P; Walker, Ron; Grogan, Eric L

2011-08-01

The 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) is used to evaluate suspicious pulmonary lesions due to its diagnostic accuracy. The southeastern United States has a high prevalence of infectious granulomatous lung disease, and the accuracy of FDG-PET may be reduced in this population. We examined the diagnostic accuracy of FDG-PET in patients with known or suspected non-small cell lung cancer treated at our institution. A total of 279 patients, identified through our prospective database, underwent an operation for known or suspected lung cancer. Preoperative FDG-PET in 211 eligible patients was defined by standardized uptake value greater than 2.5 or by description ("moderate" or "intense") as avid. Sensitivity, specificity, positive and negative predictive values, likelihood ratios, and decision diagrams were calculated for FDG-PET in all patients and in patients with indeterminate nodules. In all eligible patients (n=211), sensitivity and specificity of FDG-PET were 92% and 40%, respectively. Positive and negative predictive values were 86% and 55%. Overall FDG-PET accuracy to diagnose lung cancer was 81%. Preoperative positive likelihood ratio for FDG-PET diagnosis of lung cancer in this population was 1.5 compared with previously published values of 7.1. In 113 indeterminate lesions, 65% had lung cancer and the sensitivity and specificity were 89% and 40%, respectively. Twenty-four benign nodules (60%) had false positive FDG-PET scans. Twenty-two of 43 benign nodules (51%) were granulomas. In a region with endemic granulomatous diseases, the specificity of FDG-PET for diagnosis of lung cancer was 40%. Clinical decisions and future clinical predictive models for lung cancer must accommodate regional variation of FDG-PET scan results. Copyright © 2011 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Ontario multidetector computed tomographic coronary angiography study: field evaluation of diagnostic accuracy.

PubMed

Chow, Benjamin J W; Freeman, Michael R; Bowen, James M; Levin, Leslie; Hopkins, Robert B; Provost, Yves; Tarride, Jean-Eric; Dennie, Carole; Cohen, Eric A; Marcuzzi, Dan; Iwanochko, Robert; Moody, Alan R; Paul, Narinder; Parker, John D; O'Reilly, Daria J; Xie, Feng; Goeree, Ron

2011-06-13

Computed tomographic coronary angiography (CTCA) has gained clinical acceptance for the detection of obstructive coronary artery disease. Although single-center studies have demonstrated excellent accuracy, multicenter studies have yielded variable results. The true diagnostic accuracy of CTCA in the "real world" remains uncertain. We conducted a field evaluation comparing multidetector CTCA with invasive CA (ICA) to understand CTCA's diagnostic accuracy in a real-world setting. A multicenter cohort study of patients awaiting ICA was conducted between September 2006 and June 2009. All patients had either a low or an intermediate pretest probability for coronary artery disease and underwent CTCA and ICA within 10 days. The results of CTCA and ICA were interpreted visually by local expert observers who were blinded to all clinical data and imaging results. Using a patient-based analysis (diameter stenosis ≥50%) of 169 patients, the sensitivity, specificity, positive predictive value, and negative predictive value were 81.3% (95% confidence interval [CI], 71.0%-89.1%), 93.3% (95% CI, 85.9%-97.5%), 91.6% (95% CI, 82.5%-96.8%), and 84.7% (95% CI, 76.0%-91.2%), respectively; the area under receiver operating characteristic curve was 0.873. The diagnostic accuracy varied across centers (P < .001), with a sensitivity, specificity, positive predictive value, and negative predictive value ranging from 50.0% to 93.2%, 92.0% to 100%, 84.6% to 100%, and 42.9% to 94.7%, respectively. Compared with ICA, CTCA appears to have good accuracy; however, there was variability in diagnostic accuracy across centers. Factors affecting institutional variability need to be better understood before CTCA is universally adopted. Additional real-world evaluations are needed to fully understand the impact of CTCA on clinical care. clinicaltrials.gov Identifier: NCT00371891.

Carotid bruit for detection of hemodynamically significant carotid stenosis: the Northern Manhattan Study

PubMed Central

Ratchford, Elizabeth V.; Jin, Zhezhen; Di Tullio, Marco R.; Salameh, Maya J.; Homma, Shunichi; Gan, Robert; Boden-Albala, Bernadette; Sacco, Ralph L.; Rundek, Tatjana

2009-01-01

Objective The prevalence of carotid bruits and the utility of auscultation for predicting carotid stenosis are not well known. We aimed to establish the prevalence of carotid bruits and the diagnostic accuracy of auscultation for detection of hemodynamically significant carotid stenosis, using carotid duplex as the gold standard. Methods The Northern Manhattan Study (NOMAS) is a prospective multiethnic community-based cohort designed to examine the incidence of stroke and other vascular events and the association between various vascular risk factors and subclinical atherosclerosis. Of the stroke-free cohort (n=3298), 686 were examined for carotid bruits and underwent carotid duplex. Main outcome measures included prevalence of carotid bruits and sensitivity, specificity, positive predictive value, negative predictive value and accuracy of auscultation for prediction of ipsilateral carotid stenosis. Results Among 686 subjects with a mean age of 68.2 ± 9.4 years, the prevalence of ≥60% carotid stenosis as detected by ultrasound was 2.2% and the prevalence of carotid bruits was 4.1%. For detection of carotid stenosis, sensitivity of auscultation was 56%, specificity was 98%, positive predictive value was 25%, negative predictive value was 99% and overall accuracy was 97.5%. Discussion In this ethnically diverse cohort, the prevalence of carotid bruits and hemodynamically significant carotid stenosis was low. Sensitivity and positive predictive value were also low, and the 44% false-negative rate suggests that auscultation is not sufficient to exclude carotid stenosis. While the presence of a bruit may still warrant further evaluation with carotid duplex, ultrasonography may be considered in high-risk asymptomatic patients, irrespective of findings on auscultation. PMID:19133168

Improving transmembrane protein consensus topology prediction using inter-helical interaction.

PubMed

Wang, Han; Zhang, Chao; Shi, Xiaohu; Zhang, Li; Zhou, You

2012-11-01

Alpha helix transmembrane proteins (αTMPs) represent roughly 30% of all open reading frames (ORFs) in a typical genome and are involved in many critical biological processes. Due to the special physicochemical properties, it is hard to crystallize and obtain high resolution structures experimentally, thus, sequence-based topology prediction is highly desirable for the study of transmembrane proteins (TMPs), both in structure prediction and function prediction. Various model-based topology prediction methods have been developed, but the accuracy of those individual predictors remain poor due to the limitation of the methods or the features they used. Thus, the consensus topology prediction method becomes practical for high accuracy applications by combining the advances of the individual predictors. Here, based on the observation that inter-helical interactions are commonly found within the transmembrane helixes (TMHs) and strongly indicate the existence of them, we present a novel consensus topology prediction method for αTMPs, CNTOP, which incorporates four top leading individual topology predictors, and further improves the prediction accuracy by using the predicted inter-helical interactions. The method achieved 87% prediction accuracy based on a benchmark dataset and 78% accuracy based on a non-redundant dataset which is composed of polytopic αTMPs. Our method derives the highest topology accuracy than any other individual predictors and consensus predictors, at the same time, the TMHs are more accurately predicted in their length and locations, where both the false positives (FPs) and the false negatives (FNs) decreased dramatically. The CNTOP is available at: http://ccst.jlu.edu.cn/JCSB/cntop/CNTOP.html. Copyright © 2012 Elsevier B.V. All rights reserved.

Eyeball Position in Facial Approximation: Accuracy of Methods for Predicting Globe Positioning in Lateral View.

PubMed

Zednikova Mala, Pavla; Veleminska, Jana

2018-01-01

This study measured the accuracy of traditional and validated newly proposed methods for globe positioning in lateral view. Eighty lateral head cephalograms of adult subjects from Central Europe were taken, and the actual and predicted dimensions were compared. The anteroposterior eyeball position was estimated as the most accurate method based on the proportion of the orbital height (SEE = 1.9 mm) and was followed by the "tangent to the iris method" showing SEE = 2.4 mm. The traditional "tangent to the cornea method" underestimated the eyeball projection by SEE = 5.8 mm. Concerning the superoinferior eyeball position, the results showed a deviation from a central to a more superior position by 0.3 mm, on average, and the traditional method of central positioning of the globe could not be rejected as inaccurate (SEE = 0.3 mm). Based on regression analyzes or proportionality of the orbital height, the SEE = 2.1 mm. © 2017 American Academy of Forensic Sciences.

Iodine-123 metaiodobenzylguanidine scintigraphy and iodine-123 ioflupane single photon emission computed tomography in Lewy body diseases: complementary or alternative techniques?

PubMed

Treglia, Giorgio; Cason, Ernesto; Cortelli, Pietro; Gabellini, Anna; Liguori, Rocco; Bagnato, Antonio; Giordano, Alessandro; Fagioli, Giorgio

2014-01-01

To compare myocardial sympathetic imaging using (123)I-Metaiodobenzylguanidine (MIBG) scintigraphy and striatal dopaminergic imaging using (123)I-Ioflupane (FP-CIT) single photon emission computed tomography (SPECT) in patients with suspected Lewy body diseases (LBD). Ninety-nine patients who performed both methods within 2 months for differential diagnosis between Parkinson's disease (PD) and other parkinsonism (n = 68) or between dementia with Lewy bodies (DLB) and other dementia (n = 31) were enrolled. Sensitivity, specificity, accuracy, positive and negative predictive values of both methods were calculated. For (123) I-MIBG scintigraphy, the overall sensitivity, specificity, accuracy, positive and negative predictive values in LBD were 83%, 79%, 82%, 86%, and 76%, respectively. For (123)I-FP-CIT SPECT, the overall sensitivity, specificity, accuracy, positive and negative predictive values in LBD were 93%, 41%, 73%, 71%, and 80%, respectively. There was a statistically significant difference between these two methods in patients without LBD, but not in patients with LBD. LBD usually present both myocardial sympathetic and striatal dopaminergic impairments. (123)I-FP-CIT SPECT presents high sensitivity in the diagnosis of LBD; (123)I-MIBG scintigraphy may have a complementary role in differential diagnosis between PD and other parkinsonism. These scintigraphic methods showed similar diagnostic accuracy in differential diagnosis between DLB and other dementia. Copyright © 2012 by the American Society of Neuroimaging.

Performance of blend sign in predicting hematoma expansion in intracerebral hemorrhage: A meta-analysis.

PubMed

Yu, Zhiyuan; Zheng, Jun; Guo, Rui; Ma, Lu; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

2017-12-01

Hematoma expansion is independently associated with poor outcome in intracerebral hemorrhage (ICH). Blend sign is a simple predictor for hematoma expansion on non-contrast computed tomography. However, its accuracy for predicting hematoma expansion is inconsistent in previous studies. This meta-analysis is aimed to systematically assess the performance of blend sign in predicting hematoma expansion in ICH. A systematic literature search was conducted. Original studies about predictive accuracy of blend sign for hematoma expansion in ICH were included. Pooled sensitivity, specificity, positive and negative likelihood ratios were calculated. Summary receiver operating characteristics curve was constructed. Publication bias was assessed by Deeks' funnel plot asymmetry test. A total of 5 studies with 2248 patients were included in this meta-analysis. The pooled sensitivity, specificity, positive and negative likelihood ratios of blend sign for predicting hematoma expansion were 0.28, 0.92, 3.4 and 0.78, respectively. The area under the curve (AUC) was 0.85. No significant publication bias was found. This meta-analysis demonstrates that blend sign is a useful predictor with high specificity for hematoma expansion in ICH. Further studies with larger sample size are still necessary to verify the accuracy of blend sign for predicting hematoma expansion. Copyright © 2017 Elsevier B.V. All rights reserved.

Magnetic resonance spectroscopy and brain volumetry in mild cognitive impairment. A prospective study.

PubMed

Fayed, Nicolás; Modrego, Pedro J; García-Martí, Gracián; Sanz-Requena, Roberto; Marti-Bonmatí, Luis

2017-05-01

To assess the accuracy of magnetic resonance spectroscopy (1H-MRS) and brain volumetry in mild cognitive impairment (MCI) to predict conversion to probable Alzheimer's disease (AD). Forty-eight patients fulfilling the criteria of amnestic MCI who underwent a conventional magnetic resonance imaging (MRI) followed by MRS, and T1-3D on 1.5 Tesla MR unit. At baseline the patients underwent neuropsychological examination. 1H-MRS of the brain was carried out by exploring the left medial occipital lobe and ventral posterior cingulated cortex (vPCC) using the LCModel software. A high resolution T1-3D sequence was acquired to carry out the volumetric measurement. A cortical and subcortical parcellation strategy was used to obtain the volumes of each area within the brain. The patients were followed up to detect conversion to probable AD. After a 3-year follow-up, 15 (31.2%) patients converted to AD. The myo-inositol in the occipital cortex and glutamate+glutamine (Glx) in the posterior cingulate cortex predicted conversion to probable AD at 46.1% sensitivity and 90.6% specificity. The positive predictive value was 66.7%, and the negative predictive value was 80.6%, with an overall cross-validated classification accuracy of 77.8%. The volume of the third ventricle, the total white matter and entorhinal cortex predict conversion to probable AD at 46.7% sensitivity and 90.9% specificity. The positive predictive value was 70%, and the negative predictive value was 78.9%, with an overall cross-validated classification accuracy of 77.1%. Combining volumetric measures in addition to the MRS measures the prediction to probable AD has a 38.5% sensitivity and 87.5% specificity, with a positive predictive value of 55.6%, a negative predictive value of 77.8% and an overall accuracy of 73.3%. Either MRS or brain volumetric measures are markers separately of cognitive decline and may serve as a noninvasive tool to monitor cognitive changes and progression to dementia in patients with amnestic MCI, but the results do not support the routine use in the clinical settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Time to Positivity and Detection of Growth in Anaerobic Blood Culture Vials Predict the Presence of Candida glabrata in Candidemia: a Two-Center European Cohort Study

PubMed Central

Kaasch, Achim J.; Soriano, Alex; Torres, Jorge-Luis; Vergara, Andrea; Morata, Laura; Zboromyrska, Yuliya; De La Calle, Cristina; Alejo, Izaskun; Hernández, Cristina; Cardozo, Celia; Marco, Franscesc; Del Río, Ana; Almela, Manel; Mensa, Josep; Martínez, José Antonio

2014-01-01

This study shows the accuracy of exclusive or earlier growth in anaerobic vials to predict Candida glabrata in a large series of candidemic patients from two European hospitals using the Bactec 9240 system. Alternatively, C. glabrata can be predicted by a time to positivity cutoff value, which should be determined for each setting. PMID:24899027

Ottawa Ankle Rules and Subjective Surgeon Perception to Evaluate Radiograph Necessity Following Foot and Ankle Sprain

PubMed Central

Pires, RES; Pereira, AA; Abreu-e-Silva, GM; Labronici, PJ; Figueiredo, LB; Godoy-Santos, AL; Kfuri, M

2014-01-01

Background: Foot and ankle injuries are frequent in emergency departments. Although only a few patients with foot and ankle sprain present fractures and the fracture patterns are almost always simple, lack of fracture diagnosis can lead to poor functional outcomes. Aim: The present study aims to evaluate the reliability of the Ottawa ankle rules and the orthopedic surgeon subjective perception to assess foot and ankle fractures after sprains. Subjects and Methods: A cross-sectional study was conducted from July 2012 to December 2012. Ethical approval was granted. Two hundred seventy-four adult patients admitted to the emergency department with foot and/or ankle sprain were evaluated by an orthopedic surgeon who completed a questionnaire prior to radiographic assessment. The Ottawa ankle rules and subjective perception of foot and/or ankle fractures were evaluated on the questionnaire. Results: Thirteen percent (36/274) patients presented fracture. Orthopedic surgeon subjective analysis showed 55.6% sensitivity, 90.1% specificity, 46.5% positive predictive value and 92.9% negative predictive value. The general orthopedic surgeon opinion accuracy was 85.4%. The Ottawa ankle rules presented 97.2% sensitivity, 7.8% specificity, 13.9% positive predictive value, 95% negative predictive value and 19.9% accuracy respectively. Weight-bearing inability was the Ottawa ankle rule item that presented the highest reliability, 69.4% sensitivity, 61.6% specificity, 63.1% accuracy, 21.9% positive predictive value and 93% negative predictive value respectively. Conclusion: The Ottawa ankle rules showed high reliability for deciding when to take radiographs in foot and/or ankle sprains. Weight-bearing inability was the most important isolated item to predict fracture presence. Orthopedic surgeon subjective analysis to predict fracture possibility showed a high specificity rate, representing a confident method to exclude unnecessary radiographic exams. PMID:24971221

How accurate is our clinical prediction of "minimal prostate cancer"?

PubMed

Leibovici, Dan; Shikanov, Sergey; Gofrit, Ofer N; Zagaja, Gregory P; Shilo, Yaniv; Shalhav, Arieh L

2013-07-01

Recommendations for active surveillance versus immediate treatment for low risk prostate cancer are based on biopsy and clinical data, assuming that a low volume of well-differentiated carcinoma will be associated with a low progression risk. However, the accuracy of clinical prediction of minimal prostate cancer (MPC) is unclear. To define preoperative predictors for MPC in prostatectomy specimens and to examine the accuracy of such prediction. Data collected on 1526 consecutive radical prostatectomy patients operated in a single center between 2003 and 2008 included: age, body mass index, preoperative prostate-specific antigen level, biopsy Gleason score, clinical stage, percentage of positive biopsy cores, and maximal core length (MCL) involvement. MPC was defined as < 5% of prostate volume involvement with organ-confined Gleason score < or = 6. Univariate and multivariate logistic regression analyses were used to define independent predictors of minimal disease. Classification and Regression Tree (CART) analysis was used to define cutoff values for the predictors and measure the accuracy of prediction. MPC was found in 241 patients (15.8%). Clinical stage, biopsy Gleason's score, percent of positive biopsy cores, and maximal involved core length were associated with minimal disease (OR 0.42, 0.1, 0.92, and 0.9, respectively). Independent predictors of MPC included: biopsy Gleason score, percent of positive cores and MCL (OR 0.21, 095 and 0.95, respectively). CART showed that when the MCL exceeded 11.5%, the likelihood of MPC was 3.8%. Conversely, when applying the most favorable preoperative conditions (Gleason < or = 6, < 20% positive cores, MCL < or = 11.5%) the chance of minimal disease was 41%. Biopsy Gleason score, the percent of positive cores and MCL are independently associated with MPC. While preoperative prediction of significant prostate cancer was accurate, clinical prediction of MPC was incorrect 59% of the time. Caution is necessary when implementing clinical data as selection criteria for active surveillance.

The interplay of various sources of noise on reliability of species distribution models hinges on ecological specialisation.

PubMed

Soultan, Alaaeldin; Safi, Kamran

2017-01-01

Digitized species occurrence data provide an unprecedented source of information for ecologists and conservationists. Species distribution model (SDM) has become a popular method to utilise these data for understanding the spatial and temporal distribution of species, and for modelling biodiversity patterns. Our objective is to study the impact of noise in species occurrence data (namely sample size and positional accuracy) on the performance and reliability of SDM, considering the multiplicative impact of SDM algorithms, species specialisation, and grid resolution. We created a set of four 'virtual' species characterized by different specialisation levels. For each of these species, we built the suitable habitat models using five algorithms at two grid resolutions, with varying sample sizes and different levels of positional accuracy. We assessed the performance and reliability of the SDM according to classic model evaluation metrics (Area Under the Curve and True Skill Statistic) and model agreement metrics (Overall Concordance Correlation Coefficient and geographic niche overlap) respectively. Our study revealed that species specialisation had by far the most dominant impact on the SDM. In contrast to previous studies, we found that for widespread species, low sample size and low positional accuracy were acceptable, and useful distribution ranges could be predicted with as few as 10 species occurrences. Range predictions for narrow-ranged species, however, were sensitive to sample size and positional accuracy, such that useful distribution ranges required at least 20 species occurrences. Against expectations, the MAXENT algorithm poorly predicted the distribution of specialist species at low sample size.

Role of specimen US for predicting resection margin status in breast conserving therapy.

PubMed

Moschetta, M; Telegrafo, M; Introna, T; Coi, L; Rella, L; Ranieri, V; Cirili, A; Stabile Ianora, A A; Angelelli, G

2015-01-01

To assess the diagnostic accuracy of specimen ultrasound (US) for predicting resection margin status in women undergoing breast conserving therapy for US-detected cancer, having the histological findings as the reference standard. A total of 132 consecutive patients (age range, 34-87 years; mean, 51 years) underwent breast-conserving surgery for US-detected invasive breast cancer. All surgical specimens underwent US examination. The presence of lesion within the specimen and its distance from the specimen margins were assessed considering a threshold distance between the lesion and specimen margins of 10 mm. US findings were then compared with the pathological ones and specimen US. Sensitivity, specificity, diagnostic accuracy, positive (PPV) and negative predictive values (NPV) for predicting histological margin status were evaluated, having the histological findings as the reference standard. The histological examination detected invasive ductal carcinoma in 96/132 (73%) cases, invasive lobular carcinoma in 32/132 (24%), mucinous carcinoma in 4/132 (3%). The pathological margin analysis revealed 96/132 (73%) negative margins and 36 (27%) close/positive margins. US examination detected all 132 breast lesions within the surgical specimens. 110 (83%) negative margins and 22 (17%) positive margins were found on US. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 44%, 94%, 80%, 73% and 82%, respectively, were found for specimen US. Specimen US represents a time and cost saving imaging tool for evaluating the presence of US detected-breast lesion within surgical specimen and for predicting the histological margin status.

The urine dipstick test useful to rule out infections. A meta-analysis of the accuracy

PubMed Central

Devillé, Walter LJM; Yzermans, Joris C; van Duijn, Nico P; Bezemer, P Dick; van der Windt, Daniëlle AWM; Bouter, Lex M

2004-01-01

Background Many studies have evaluated the accuracy of dipstick tests as rapid detectors of bacteriuria and urinary tract infections (UTI). The lack of an adequate explanation for the heterogeneity of the dipstick accuracy stimulates an ongoing debate. The objective of the present meta-analysis was to summarise the available evidence on the diagnostic accuracy of the urine dipstick test, taking into account various pre-defined potential sources of heterogeneity. Methods Literature from 1990 through 1999 was searched in Medline and Embase, and by reference tracking. Selected publications should be concerned with the diagnosis of bacteriuria or urinary tract infections, investigate the use of dipstick tests for nitrites and/or leukocyte esterase, and present empirical data. A checklist was used to assess methodological quality. Results 70 publications were included. Accuracy of nitrites was high in pregnant women (Diagnostic Odds Ratio = 165) and elderly people (DOR = 108). Positive predictive values were ≥80% in elderly and in family medicine. Accuracy of leukocyte-esterase was high in studies in urology patients (DOR = 276). Sensitivities were highest in family medicine (86%). Negative predictive values were high in both tests in all patient groups and settings, except for in family medicine. The combination of both test results showed an important increase in sensitivity. Accuracy was high in studies in urology patients (DOR = 52), in children (DOR = 46), and if clinical information was present (DOR = 28). Sensitivity was highest in studies carried out in family medicine (90%). Predictive values of combinations of positive test results were low in all other situations. Conclusions Overall, this review demonstrates that the urine dipstick test alone seems to be useful in all populations to exclude the presence of infection if the results of both nitrites and leukocyte-esterase are negative. Sensitivities of the combination of both tests vary between 68 and 88% in different patient groups, but positive test results have to be confirmed. Although the combination of positive test results is very sensitive in family practice, the usefulness of the dipstick test alone to rule in infection remains doubtful, even with high pre-test probabilities. PMID:15175113

The value of negative Chlamydia trachomatis antibody in prediction of normal tubes in infertile women.

PubMed

Raoofi, Z; Barchinegad, M; Haghighi, L

2013-01-01

To evaluate the value of Chlamydia trachomatis antibody testing in prediction of at least one normal tube in infertile women. Eighty infertile women without any history of abdominal or pelvic surgery, pelvic inflammatory disease, and endometriosis were recruited in this cross-sectional study from 2009 to 2010. The patients underwent hysterosalpingography, laparoscopy, and anti Chlamydia trachomatis IgG antibody (CAT) testing. We compared laparoscopy findings and CAT regarding sensitivity, specificity, accuracy, and predicting value of tubal conditions. The CAT was positive in 50 patients (62.5%) and laparoscopy was positive in 32 patients (40%). The CAT was significantly higher in women with tubal disease (1.88 +/- 0.34) versus in women with normal tubes (1.21 +/- 0.28) (p = 0.003). Five out of 30 sero-negative women had unilateral tubal abnormality and none of them had bilateral tubal obstruction or severe pelvic adhesion. The sensitivity, specificity, positive and negative predictive value, and accuracy of the CAT in prediction of one normal tube were 100%, 42.25%, 18%, 100%, and 48.75%, respectively. The negative predictive value of CAT to predict at least one normal tube in infertile women without history of abdominal or pelvic surgery, pelvic inflammatory disease, and endometriosis was 100%.

CD-Based Indices for Link Prediction in Complex Network.

PubMed

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

CD-Based Indices for Link Prediction in Complex Network

PubMed Central

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

Administrative database code accuracy did not vary notably with changes in disease prevalence.

PubMed

van Walraven, Carl; English, Shane; Austin, Peter C

2016-11-01

Previous mathematical analyses of diagnostic tests based on the categorization of a continuous measure have found that test sensitivity and specificity varies significantly by disease prevalence. This study determined if the accuracy of diagnostic codes varied by disease prevalence. We used data from two previous studies in which the true status of renal disease and primary subarachnoid hemorrhage, respectively, had been determined. In multiple stratified random samples from the two previous studies having varying disease prevalence, we measured the accuracy of diagnostic codes for each disease using sensitivity, specificity, and positive and negative predictive value. Diagnostic code sensitivity and specificity did not change notably within clinically sensible disease prevalence. In contrast, positive and negative predictive values changed significantly with disease prevalence. Disease prevalence had no important influence on the sensitivity and specificity of diagnostic codes in administrative databases. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

High accuracy prediction of beta-turns and their types using propensities and multiple alignments.

PubMed

Fuchs, Patrick F J; Alix, Alain J P

2005-06-01

We have developed a method that predicts both the presence and the type of beta-turns, using a straightforward approach based on propensities and multiple alignments. The propensities were calculated classically, but the way to use them for prediction was completely new: starting from a tetrapeptide sequence on which one wants to evaluate the presence of a beta-turn, the propensity for a given residue is modified by taking into account all the residues present in the multiple alignment at this position. The evaluation of a score is then done by weighting these propensities by the use of Position-specific score matrices generated by PSI-BLAST. The introduction of secondary structure information predicted by PSIPRED or SSPRO2 as well as taking into account the flanking residues around the tetrapeptide improved the accuracy greatly. This latter evaluated on a database of 426 reference proteins (previously used on other studies) by a sevenfold crossvalidation gave very good results with a Matthews Correlation Coefficient (MCC) of 0.42 and an overall prediction accuracy of 74.8%; this places our method among the best ones. A jackknife test was also done, which gave results within the same range. This shows that it is possible to reach neural networks accuracy with considerably less computional cost and complexity. Furthermore, propensities remain excellent descriptors of amino acid tendencies to belong to beta-turns, which can be useful for peptide or protein engineering and design. For beta-turn type prediction, we reached the best accuracy ever published in terms of MCC (except for the irregular type IV) in the range of 0.25-0.30 for types I, II, and I' and 0.13-0.15 for types VIII, II', and IV. To our knowledge, our method is the only one available on the Web that predicts types I' and II'. The accuracy evaluated on two larger databases of 547 and 823 proteins was not improved significantly. All of this was implemented into a Web server called COUDES (French acronym for: Chercher Ou Une Deviation Existe Surement), which is available at the following URL: http://bioserv.rpbs.jussieu.fr/Coudes/index.html within the new bioinformatics platform RPBS.

Sequence fingerprints distinguish erroneous from correct predictions of intrinsically disordered protein regions.

PubMed

Saravanan, Konda Mani; Dunker, A Keith; Krishnaswamy, Sankaran

2017-12-27

More than 60 prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the World Wide Web. Nearly, all of these predictors give balanced accuracies in the ~65%-~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm.

New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking.

PubMed

Sulimov, Alexey V; Kutov, Danil C; Katkova, Ekaterina V; Ilin, Ivan S; Sulimov, Vladimir B

2017-11-01

Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field. Copyright © 2017 Elsevier Inc. All rights reserved.

Circumferential resection margin (CRM) positivity after MRI assessment and adjuvant treatment in 189 patients undergoing rectal cancer resection.

PubMed

Simpson, G S; Eardley, N; McNicol, F; Healey, P; Hughes, M; Rooney, P S

2014-05-01

The management of rectal cancer relies on accurate MRI staging. Multi-modal treatments can downstage rectal cancer prior to surgery and may have an effect on MRI accuracy. We aim to correlate the findings of MRI staging of rectal cancer with histological analysis, the effect of neoadjuvant therapy on this and the implications of circumferential resection margin (CRM) positivity following neoadjuvant therapy. An analysis of histological data and radiological staging of all cases of rectal cancer in a single centre between 2006 and 2011 were conducted. Two hundred forty-one patients had histologically proved rectal cancer during the study period. One hundred eighty-two patients underwent resection. Median age was 66.6 years, and male to female ratio was 13:5. R1 resection rate was 11.1%. MRI assessments of the circumferential resection margin in patients without neoadjuvant radiotherapy were 93.6 and 88.1% in patients who underwent neoadjuvant radiotherapy. Eighteen patients had predicted positive margins following chemoradiotherapy, of which 38.9% had an involved CRM on histological analysis. MRI assessment of the circumferential resection margin in rectal cancer is associated with high accuracy. Neoadjuvant chemoradiotherapy has a detrimental effect on this accuracy, although accuracy remains high. In the presence of persistently predicted positive margins, complete resection remains achievable but may necessitate a more radical approach to resection.

CSmetaPred: a consensus method for prediction of catalytic residues.

PubMed

Choudhary, Preeti; Kumar, Shailesh; Bachhawat, Anand Kumar; Pandit, Shashi Bhushan

2017-12-22

Knowledge of catalytic residues can play an essential role in elucidating mechanistic details of an enzyme. However, experimental identification of catalytic residues is a tedious and time-consuming task, which can be expedited by computational predictions. Despite significant development in active-site prediction methods, one of the remaining issues is ranked positions of putative catalytic residues among all ranked residues. In order to improve ranking of catalytic residues and their prediction accuracy, we have developed a meta-approach based method CSmetaPred. In this approach, residues are ranked based on the mean of normalized residue scores derived from four well-known catalytic residue predictors. The mean residue score of CSmetaPred is combined with predicted pocket information to improve prediction performance in meta-predictor, CSmetaPred_poc. Both meta-predictors are evaluated on two comprehensive benchmark datasets and three legacy datasets using Receiver Operating Characteristic (ROC) and Precision Recall (PR) curves. The visual and quantitative analysis of ROC and PR curves shows that meta-predictors outperform their constituent methods and CSmetaPred_poc is the best of evaluated methods. For instance, on CSAMAC dataset CSmetaPred_poc (CSmetaPred) achieves highest Mean Average Specificity (MAS), a scalar measure for ROC curve, of 0.97 (0.96). Importantly, median predicted rank of catalytic residues is the lowest (best) for CSmetaPred_poc. Considering residues ranked ≤20 classified as true positive in binary classification, CSmetaPred_poc achieves prediction accuracy of 0.94 on CSAMAC dataset. Moreover, on the same dataset CSmetaPred_poc predicts all catalytic residues within top 20 ranks for ~73% of enzymes. Furthermore, benchmarking of prediction on comparative modelled structures showed that models result in better prediction than only sequence based predictions. These analyses suggest that CSmetaPred_poc is able to rank putative catalytic residues at lower (better) ranked positions, which can facilitate and expedite their experimental characterization. The benchmarking studies showed that employing meta-approach in combining residue-level scores derived from well-known catalytic residue predictors can improve prediction accuracy as well as provide improved ranked positions of known catalytic residues. Hence, such predictions can assist experimentalist to prioritize residues for mutational studies in their efforts to characterize catalytic residues. Both meta-predictors are available as webserver at: http://14.139.227.206/csmetapred/ .

Predictive accuracy of changes in transvaginal sonographic cervical length over time for preterm birth: a systematic review and metaanalysis.

PubMed

Conde-Agudelo, Agustin; Romero, Roberto

2015-12-01

To determine the accuracy of changes in transvaginal sonographic cervical length over time in predicting preterm birth in women with singleton and twin gestations. PubMed, Embase, Cinahl, Lilacs, and Medion (all from inception to June 30, 2015), bibliographies, Google scholar, and conference proceedings. Cohort or cross-sectional studies reporting on the predictive accuracy for preterm birth of changes in cervical length over time. Two reviewers independently selected studies, assessed the risk of bias, and extracted the data. Summary receiver-operating characteristic curves, pooled sensitivities and specificities, and summary likelihood ratios were generated. Fourteen studies met the inclusion criteria, of which 7 provided data on singleton gestations (3374 women) and 8 on twin gestations (1024 women). Among women with singleton gestations, the shortening of cervical length over time had a low predictive accuracy for preterm birth at <37 and <35 weeks of gestation with pooled sensitivities and specificities, and summary positive and negative likelihood ratios ranging from 49% to 74%, 44% to 85%, 1.3 to 4.1, and 0.3 to 0.7, respectively. In women with twin gestations, the shortening of cervical length over time had a low to moderate predictive accuracy for preterm birth at <34, <32, <30, and <28 weeks of gestation with pooled sensitivities and specificities, and summary positive and negative likelihood ratios ranging from 47% to 73%, 84% to 89%, 3.8 to 5.3, and 0.3 to 0.6, respectively. There were no statistically significant differences between the predictive accuracies for preterm birth of cervical length shortening over time and the single initial and/or final cervical length measurement in 8 of 11 studies that provided data for making these comparisons. In the largest and highest-quality study, a single measurement of cervical length obtained at 24 or 28 weeks of gestation was significantly more predictive of preterm birth than any decrease in cervical length between these gestational ages. Change in transvaginal sonographic cervical length over time is not a clinically useful test to predict preterm birth in women with singleton or twin gestations. A single cervical length measurement obtained between 18 and 24 weeks of gestation appears to be a better test to predict preterm birth than changes in cervical length over time. Published by Elsevier Inc.

Time to positivity and detection of growth in anaerobic blood culture vials predict the presence of Candida glabrata in candidemia: a two-center European cohort study.

PubMed

Cobos-Trigueros, Nazaret; Kaasch, Achim J; Soriano, Alex; Torres, Jorge-Luis; Vergara, Andrea; Morata, Laura; Zboromyrska, Yuliya; De La Calle, Cristina; Alejo, Izaskun; Hernández, Cristina; Cardozo, Celia; Marco, Franscesc; Del Río, Ana; Almela, Manel; Mensa, Josep; Martínez, José Antonio

2014-08-01

This study shows the accuracy of exclusive or earlier growth in anaerobic vials to predict Candida glabrata in a large series of candidemic patients from two European hospitals using the Bactec 9240 system. Alternatively, C. glabrata can be predicted by a time to positivity cutoff value, which should be determined for each setting. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Role of specimen US for predicting resection margin status in breast conserving therapy

PubMed Central

MOSCHETTA, M.; TELEGRAFO, M.; INTRONA, T.; COI, L.; RELLA, L.; RANIERI, V.; CIRILLI, A.; IANORA, A.A. STABILE; ANGELELLI, G.

2015-01-01

Aim To assess the diagnostic accuracy of specimen ultrasound (US) for predicting resection margin status in women undergoing breast conserving therapy for US-detected cancer, having the histological findings as the reference standard. Patients and methods A total of 132 consecutive patients (age range, 34–87 years; mean, 51 years) underwent breast-conserving surgery for US-detected invasive breast cancer. All surgical specimens underwent US examination. The presence of lesion within the specimen and its distance from the specimen margins were assessed considering a threshold distance between the lesion and specimen margins of 10 mm. US findings were then compared with the pathological ones and specimen US. Sensitivity, specificity, diagnostic accuracy, positive (PPV) and negative predictive values (NPV) for predicting histological margin status were evaluated, having the histological findings as the reference standard. Results The histological examination detected invasive ductal carcinoma in 96/132 (73%) cases, invasive lobular carcinoma in 32/132 (24%), mucinous carcinoma in 4/132 (3%). The pathological margin analysis revealed 96/132 (73%) negative margins and 36 (27%) close/positive margins. US examination detected all 132 breast lesions within the surgical specimens. 110 (83%) negative margins and 22 (17%) positive margins were found on US. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 44%, 94%, 80%, 73% and 82%, respectively, were found for specimen US. Conclusions Specimen US represents a time and cost saving imaging tool for evaluating the presence of US detected-breast lesion within surgical specimen and for predicting the histological margin status. PMID:26712255

Accuracy of chest radiography for positioning of the umbilical venous catheter.

PubMed

Guimarães, Adriana F M; Souza, Aline A C G de; Bouzada, Maria Cândida F; Meira, Zilda M A

To evaluate the accuracy of the simultaneous analysis of three radiographic anatomical landmarks - diaphragm, cardiac silhouette, and vertebral bodies - in determining the position of the umbilical venous catheter distal end using echocardiography as a reference standard. This was a cross-sectional, observational study, with the prospective inclusion of data from all neonates born in a public reference hospital, between April 2012 and September 2013, submitted to umbilical venous catheter insertion as part of their medical care. The position of the catheter distal end, determined by the simultaneous analysis of three radiographic anatomical landmarks, was compared with the anatomical position obtained by echocardiography; sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. Of the 162 newborns assessed by echocardiography, only 44 (27.16%) had the catheter in optimal position, in the thoracic portion of the inferior vena cava or at the junction of the inferior vena cava with the right atrium. The catheters were located in the left atrium and interatrial septum in 54 (33.33%) newborns, in the right atrium in 26 (16.05%), intra-hepatic in 37 (22.84%), and intra-aortic in-one newborn (0.62%). The sensitivity, specificity and accuracy of the radiography to detect the catheter in the target area were 56%, 71%, and 67.28%, respectively. Anteroposterior radiography of the chest alone is not able to safely define the umbilical venous catheter position. Echocardiography allows direct visualization of the catheter tip in relation to vascular structures and, whenever possible, should be considered to identify the location of the umbilical venous catheter. Copyright © 2016 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Office gel sonovaginography for the prediction of posterior deep infiltrating endometriosis: a multicenter prospective observational study.

PubMed

Reid, S; Lu, C; Hardy, N; Casikar, I; Reid, G; Cario, G; Chou, D; Almashat, D; Condous, G

2014-12-01

To use office gel sonovaginography (SVG) to predict posterior deep infiltrating endometriosis (DIE) in women undergoing laparoscopy. This was a multicenter prospective observational study carried out between January 2009 and February 2013. All women were of reproductive age, had a history of chronic pelvic pain and underwent office gel SVG assessment for the prediction of posterior compartment DIE prior to laparoscopic endometriosis surgery. Gel SVG findings were compared with laparoscopic findings to determine the diagnostic accuracy of office gel SVG for the prediction of posterior compartment DIE. In total, 189 women underwent preoperative gel SVG and laparoscopy for endometriosis. At laparoscopy, 57 (30%) women had posterior DIE and 43 (23%) had rectosigmoid/anterior rectal DIE. For the prediction of rectosigmoid/anterior rectal (i.e. bowel) DIE, gel SVG had an accuracy of 92%, sensitivity of 88%, specificity of 93%, positive predictive value (PPV) of 79%, negative predictive value (NPV) of 97%, positive likelihood ratio (LR+) of 12.9 and negative likelihood ratio (LR-) of 0.12 (P = 3.98E-25); for posterior vaginal wall and rectovaginal septum (RVS) DIE, respectively, the accuracy was 95% and 95%, sensitivity was 18% and 18%, specificity was 99% and 100%, PPV was 67% and 100%, NPV was 95% and 95%, LR+ was 32.4 and infinity and LR- was 0.82 and 0.82 (P = 0.009 and P = 0.003). Office gel SVG appears to be an effective outpatient imaging technique for the prediction of bowel DIE, with a higher accuracy for the prediction of rectosigmoid compared with anterior rectal DIE. Although the sensitivity for vaginal and RVS DIE was limited, gel SVG had a high specificity and NPV for all forms of posterior DIE, indicating that a negative gel SVG examination is highly suggestive of the absence of DIE at laparoscopy. Copyright © 2014 ISUOG. Published by John Wiley & Sons Ltd.

Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

PubMed Central

2007-01-01

Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for pairwise RNA structure prediction methods in a principled fashion. These constraints can reduce the computational and memory requirements of these methods while maintaining or improving their accuracy of structural prediction. This extends the practical reach of these methods to longer length sequences. The revised Dynalign code is freely available for download. PMID:17445273

Effect of CTA Tube Current on Spot Sign Detection and Accuracy for Prediction of Intracerebral Hemorrhage Expansion.

PubMed

Morotti, A; Romero, J M; Jessel, M J; Brouwers, H B; Gupta, R; Schwab, K; Vashkevich, A; Ayres, A; Anderson, C D; Gurol, M E; Viswanathan, A; Greenberg, S M; Rosand, J; Goldstein, J N

2016-05-19

Reduction of CT tube current is an effective strategy to minimize radiation load. However, tube current is also a major determinant of image quality. We investigated the impact of CTA tube current on spot sign detection and diagnostic performance for intracerebral hemorrhage expansion. We retrospectively analyzed a prospectively collected cohort of consecutive patients with primary intracerebral hemorrhage from January 2001 to April 2015 who underwent CTA. The study population was divided into 2 groups according to the median CTA tube current level: low current (<350 mA) and high current (≥350 mA). CTA first-pass readings for spot sign presence were independently analyzed by 2 readers. Baseline and follow-up hematoma volumes were assessed by semiautomated computer-assisted volumetric analysis. Sensitivity, specificity, positive and negative predictive values, and accuracy of spot sign in predicting hematoma expansion were calculated. This study included 709 patients (288 and 421 in the low- and high-current groups, respectively). A higher proportion of low-current scans identified at least 1 spot sign (20.8% versus 14.7%, P = .034), but hematoma expansion frequency was similar in the 2 groups (18.4% versus 16.2%, P = .434). Sensitivity and positive and negative predictive values were not significantly different between the 2 groups. Conversely, high-current scans showed superior specificity (91% versus 84%, P = .015) and overall accuracy (84% versus 77%, P = .038). CTA obtained at high levels of tube current showed better diagnostic accuracy for prediction of hematoma expansion by using spot sign. These findings may have implications for future studies using the CTA spot sign to predict hematoma expansion for clinical trials. © 2016 American Society of Neuroradiology.

Linear array ultrasonography to stage rectal neoplasias suitable for local treatment.

PubMed

Ravizza, Davide; Tamayo, Darina; Fiori, Giancarla; Trovato, Cristina; De Roberto, Giuseppe; de Leone, Annalisa; Crosta, Cristiano

2011-08-01

Because of the many therapeutic options available, a reliable staging is crucial for rectal neoplasia management. Adenomas and cancers limited to the submucosa without lymph node involvement may be treated locally. The aim of this study is to evaluate the diagnostic accuracy of endorectal ultrasonography in the staging of neoplasias suitable for local treatment. We considered all patients who underwent endorectal ultrasonography between 2001 and 2010. The study population consisted of 92 patients with 92 neoplasias (68 adenocarcinomas and 24 adenomas). A 5 and 7.5MHz linear array echoendoscope was used. The postoperative histopathologic result was compared with the preoperative staging defined by endorectal ultrasonography. Adenomas and cancers limited to the submucosa were considered together (pT0-1). The sensitivity, specificity, overall accuracy rate, positive predictive value, and negative predictive value of endorectal ultrasonography for pT0-1 were 86%, 95.6%, 91.3%, 94.9% and 88.7%. Those for nodal involvement were 45.4%, 95.5%, 83%, 76.9% and 84%, with 3 false positive results and 12 false negative. For combined pT0-1 and pN0, endorectal ultrasonography showed an 87.5% sensitivity, 95.9% specificity, 92% overall accuracy rate, 94.9% positive predictive value and 90.2% negative predictive value. Endorectal linear array ultrasonography is a reliable tool to detect rectal neoplasias suitable for local treatment. Copyright © 2011 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Accuracy of Two Motor Assessments during the First Year of Life in Preterm Infants for Predicting Motor Outcome at Preschool Age.

PubMed

Spittle, Alicia J; Lee, Katherine J; Spencer-Smith, Megan; Lorefice, Lucy E; Anderson, Peter J; Doyle, Lex W

2015-01-01

The primary aim of this study was to investigate the accuracy of the Alberta Infant Motor Scale (AIMS) and Neuro-Sensory Motor Developmental Assessment (NSMDA) over the first year of life for predicting motor impairment at 4 years in preterm children. The secondary aims were to assess the predictive value of serial assessments over the first year and when using a combination of these two assessment tools in follow-up. Children born <30 weeks' gestation were prospectively recruited and assessed at 4, 8 and 12 months' corrected age using the AIMS and NSMDA. At 4 years' corrected age children were assessed for cerebral palsy (CP) and motor impairment using the Movement Assessment Battery for Children 2nd-edition (MABC-2). We calculated accuracy of the AIMS and NSMDA for predicting CP and MABC-2 scores ≤15th (at-risk of motor difficulty) and ≤5th centile (significant motor difficulty) for each test (AIMS and NSMDA) at 4, 8 and 12 months, for delay on one, two or all three of the time points over the first year, and finally for delay on both tests at each time point. Accuracy for predicting motor impairment was good for each test at each age, although false positives were common. Motor impairment on the MABC-2 (scores ≤5th and ≤15th) was most accurately predicted by the AIMS at 4 months, whereas CP was most accurately predicted by the NSMDA at 12 months. In regards to serial assessments, the likelihood ratio for motor impairment increased with the number of delayed assessments. When combining both the NSMDA and AIMS the best accuracy was achieved at 4 months, although results were similar at 8 and 12 months. Motor development during the first year of life in preterm infants assessed with the AIMS and NSMDA is predictive of later motor impairment at preschool age. However, false positives are common and therefore it is beneficial to follow-up children at high risk of motor impairment at more than one time point, or to use a combination of assessment tools. ACTR.org.au ACTRN12606000252516.

[Prognosis of acute pancreatitis by PANC 3 score].

PubMed

Fukuda, James Ken; Franzon, Orli; Resende-Filho, Fernando de Oliveira; Kruel, Nicolau Fernandes; Ferri, Thiago Alessandro

2013-06-01

Acute pancreatitis is a disease of great importance in clinical practice, defined as an inflammatory process of the pancreas that may involve local tissues or affect other organs in a systemic manner, requiring, in such cases, an intensive care. To analyze the simplified stratification system of the PANC 3 score, correlating it with the Ranson score, for the prognostic definition of cases of acute pancreatitis. Was conducted a prospective, observational study in which were evaluated 65 patients who were diagnosed with acute pancreatitis. PANC 3 showed sensitivity, 31.25%; specificity,100%; positive predictive value, 100%; negative predictive value, 81.66% and accuracy, 83.07%. The PANC 3 criteria are applicable to define the severity and the prognosis of acute pancreatitis, and are not a substitute method, but rather a method to be associated with the Ranson criteria, mainly due to its high accuracy, positive predictive value and specificity.

Classical fluoroscopy criteria poorly predict right ventricular lead septal positioning by comparison with echocardiography.

PubMed

Squara, Fabien; Scarlatti, Didier; Riccini, Philippe; Garret, Gauthier; Moceri, Pamela; Ferrari, Emile

2018-03-13

Fluoroscopic criteria have been described for the documentation of septal right ventricular (RV) lead positioning, but their accuracy remains questioned. Consecutive patients undergoing pacemaker or defibrillator implantation were prospectively included. RV lead was positioned using postero-anterior and left anterior oblique 40° incidences, and right anterior oblique 30° to rule out coronary sinus positioning when suspected. RV lead positioning using fluoroscopy was compared to true RV lead positioning as assessed by transthoracic echocardiography (TTE). Precise anatomical localizations were determined with both modalities; then, RV lead positioning was ultimately dichotomized into two simple clinically relevant categories: RV septal or RV free wall. Accuracy of fluoroscopy for RV lead positioning was then assessed by comparison with TTE. We included 100 patients. On TTE, 66/100 had a septal RV lead and 34/100 had a free wall RV lead. Fluoroscopy had moderate agreement with TTE for precise anatomical localization of RV lead (k = 0.53), and poor agreement for septal/free wall localization (k = 0.36). For predicting septal RV lead positioning, classical fluoroscopy criteria had a high sensitivity (95.5%; 63/66 patients having a septal RV lead on TTE were correctly identified by fluoroscopy) but a very low specificity (35.3%; only 12/34 patients having a free wall RV lead on TTE were correctly identified by fluoroscopy). Classical fluoroscopy criteria have a poor accuracy for identifying RV free wall leads, which are most of the time misclassified as septal. This raises important concerns about the efficacy and safety of RV lead positioning using classical fluoroscopy criteria.

A threshold-free summary index of prediction accuracy for censored time to event data.

PubMed

Yuan, Yan; Zhou, Qian M; Li, Bingying; Cai, Hengrui; Chow, Eric J; Armstrong, Gregory T

2018-05-10

Prediction performance of a risk scoring system needs to be carefully assessed before its adoption in clinical practice. Clinical preventive care often uses risk scores to screen asymptomatic population. The primary clinical interest is to predict the risk of having an event by a prespecified future time t 0 . Accuracy measures such as positive predictive values have been recommended for evaluating the predictive performance. However, for commonly used continuous or ordinal risk score systems, these measures require a subjective cutoff threshold value that dichotomizes the risk scores. The need for a cutoff value created barriers for practitioners and researchers. In this paper, we propose a threshold-free summary index of positive predictive values that accommodates time-dependent event status and competing risks. We develop a nonparametric estimator and provide an inference procedure for comparing this summary measure between 2 risk scores for censored time to event data. We conduct a simulation study to examine the finite-sample performance of the proposed estimation and inference procedures. Lastly, we illustrate the use of this measure on a real data example, comparing 2 risk score systems for predicting heart failure in childhood cancer survivors. Copyright © 2018 John Wiley & Sons, Ltd.

Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services.

PubMed

Kasthurirathne, Suranga N; Vest, Joshua R; Menachemi, Nir; Halverson, Paul K; Grannis, Shaun J

2018-01-01

A growing variety of diverse data sources is emerging to better inform health care delivery and health outcomes. We sought to evaluate the capacity for clinical, socioeconomic, and public health data sources to predict the need for various social service referrals among patients at a safety-net hospital. We integrated patient clinical data and community-level data representing patients' social determinants of health (SDH) obtained from multiple sources to build random forest decision models to predict the need for any, mental health, dietitian, social work, or other SDH service referrals. To assess the impact of SDH on improving performance, we built separate decision models using clinical and SDH determinants and clinical data only. Decision models predicting the need for any, mental health, and dietitian referrals yielded sensitivity, specificity, and accuracy measures ranging between 60% and 75%. Specificity and accuracy scores for social work and other SDH services ranged between 67% and 77%, while sensitivity scores were between 50% and 63%. Area under the receiver operating characteristic curve values for the decision models ranged between 70% and 78%. Models for predicting the need for any services reported positive predictive values between 65% and 73%. Positive predictive values for predicting individual outcomes were below 40%. The need for various social service referrals can be predicted with considerable accuracy using a wide range of readily available clinical and community data that measure socioeconomic and public health conditions. While the use of SDH did not result in significant performance improvements, our approach represents a novel and important application of risk predictive modeling. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Efficiency of the Bethesda System for Thyroid Cytopathology.

PubMed

Mora-Guzmán, Ismael; Muñoz de Nova, José Luis; Marín-Campos, Cristina; Jiménez-Heffernan, José Antonio; Cuesta Pérez, Juan Julián; Lahera Vargas, Marcos; Torres Mínguez, Emma; Martín-Pérez, Elena

2018-03-28

Fine-needle aspiration biopsies are a key tool for preoperative assessment of thyroid nodules, and the Bethesda system is the preferred method to report cytological analysis. The purpose of this study is to assess the efficiency of the Bethesda system to identify the malignancy risk of thyroid nodules. Patients who underwent thyroid surgery between June 2010 and June 2017 were included. Samples were classified into 6categories according to rates of malignancy associated with each diagnostic category. In order to investigate the correlation between categories, a statistical analysis compared the categories with pathology reports. Diagnostic indicators were calculated as a screening test (categories IV, V, VI as true-positive) and as a method to identify malignancy (V, VI as true-positive). In a series of 522 patients, we found 184 (35.2%) malignant tumours, papillary carcinoma being the most prevalent with 155 cases (84.2%). Malignant rates for diagnostic categories were: I, 0%; II, 1.5%; III, 6.4%; IV, 31%; V, 86.5%; VI, 100%. A robust correlation was identified between categories on statistical analysis. For the «screening test» analysis, sensitivity was 98.9%, specificity 84.4%, positive predictive value 69.6%, negative predictive value 99.5%, and diagnostic accuracy 88.2%. Analysing the accuracy to detect malignancy, values were: sensitivity 98.6%, specificity 97.6%, positive predictive value 93.5%, negative predictive value 99.5%, diagnostic accuracy 97.9%. The Bethesda system is a clear and reliable approach to report thyroid cytology and therefore is an effective tool to identify malignancy risk and guide clinical management. Copyright © 2018 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

Intra-Operative Frozen Sections for Ovarian Tumors – A Tertiary Center Experience

PubMed Central

Arshad, Nur Zaiti Md; Ng, Beng Kwang; Paiman, Noor Asmaliza Md; Mahdy, Zaleha Abdullah; Noor, Rushdan Mohd

2018-01-01

Background: Accuracy of diagnosis with intra-operative frozen sections is extremely important in the evaluation of ovarian tumors so that appropriate surgical procedures can be selected. Study design: All patients who with intra-operative frozen sections for ovarian masses in a tertiary center over nine years from June 2008 until April 2017 were reviewed. Frozen section diagnosis and final histopathological reports were compared. Main outcome measures: Sensitivity, specificity, positive and negative predictive values of intra-operative frozen section as compared to final histopathological results for ovarian tumors. Results: A total of 92 cases were recruited for final evaluation. The frozen section diagnoses were comparable with the final histopathological reports in 83.7% of cases. The sensitivity, specificity, positive predictive value and negative predictive value for benign and malignant ovarian tumors were 95.6%, 85.1%, 86.0% and 95.2% and 69.2%, 100%, 100% and 89.2% respectively. For borderline ovarian tumors, the sensitivity and specificity were 76.2% and 88.7%, respectively; the positive predictive value was 66.7% and the negative predictive value was 92.7%. Conclusion: The accuracy of intra-operative frozen section diagnoses for ovarian tumors is high and this approach remains a reliable option in assessing ovarian masses intra-operatively. PMID:29373916

Discrete Indoor Three-Dimensional Localization System Based on Neural Networks Using Visible Light Communication

PubMed Central

Ley-Bosch, Carlos; Quintana-Suárez, Miguel A.

2018-01-01

Indoor localization estimation has become an attractive research topic due to growing interest in location-aware services. Many research works have proposed solving this problem by using wireless communication systems based on radiofrequency. Nevertheless, those approaches usually deliver an accuracy of up to two metres, since they are hindered by multipath propagation. On the other hand, in the last few years, the increasing use of light-emitting diodes in illumination systems has provided the emergence of Visible Light Communication technologies, in which data communication is performed by transmitting through the visible band of the electromagnetic spectrum. This brings a brand new approach to high accuracy indoor positioning because this kind of network is not affected by electromagnetic interferences and the received optical power is more stable than radio signals. Our research focus on to propose a fingerprinting indoor positioning estimation system based on neural networks to predict the device position in a 3D environment. Neural networks are an effective classification and predictive method. The localization system is built using a dataset of received signal strength coming from a grid of different points. From the these values, the position in Cartesian coordinates (x,y,z) is estimated. The use of three neural networks is proposed in this work, where each network is responsible for estimating the position by each axis. Experimental results indicate that the proposed system leads to substantial improvements to accuracy over the widely-used traditional fingerprinting methods, yielding an accuracy above 99% and an average error distance of 0.4 mm. PMID:29601525

Diagnostic accuracy of APRI and FIB-4 for predicting hepatitis B virus-related liver fibrosis accompanied with hepatocellular carcinoma.

PubMed

Xiao, Guangqin; Zhu, Feng; Wang, Min; Zhang, Hang; Ye, Dawei; Yang, Jiayin; Jiang, Li; Liu, Chang; Yan, Lunan; Qin, Renyi

2016-10-01

Aspartate aminotransferase to platelet ratio index (APRI) and the fibrosis index based on four factors (FIB-4) are the two most focused non-invasive models to assess liver fibrosis. We aimed to examine the validity of these two models for predicting hepatitis B virus (HBV)-related liver fibrosis accompanied with hepatocellular carcinoma (HCC). We enrolled HBV-infected patients with liver cancer who had received hepatectomy. The accuracy of APRI and FIB-4 for diagnosing liver fibrosis was assessed based on their sensitivity, specificity, diagnostic efficiency, positive predictive value (PPV), negative predictive value (NPV), kappa (κ) value and area under the receiver-operating characteristic curve (AUC). Finally 2176 patients were included, with 1682 retrospective subjects and 494 prospective subjects. APRI (rs=0.310) and FIB-4 (rs=0.278) were positively correlated with liver fibrosis. And χ(2) analysis demonstrated that APRI and FIB-4 values correlated with different levels of liver fibrosis with all P values less than 0.01. The AUC values for APRI and FIB-4 were 0.685 and 0.626 (P=0.73) for predicting significant fibrosis, 0.681 and 0.648 (P=0.81) for differentiation of advanced fibrosis and 0.676 and 0.652 (P=0.77) for diagnosing cirrhosis. APRI and FIB-4 correlate with liver fibrosis. However these two models have low accuracy for predicting HBV-related liver fibrosis in HCC patients. Copyright © 2016. Published by Elsevier Ltd.

Triple Test in Carcinoma Breast

PubMed Central

Sameer; Mukherjee, Arindam

2014-01-01

Introduction: The commonest clinical presentation in majority of breast pathology is a lump. A definite diagnosis of breast lump is very important for the surgeon to decide on the final course of treatment and also saves the patient from unnecessary physical, emotional and psychological trauma if there is a definite preoperative diagnosis of benign lesion. The present study was done to evaluate the effectiveness and relevance of “TRIPLE TEST”in diagnosis of carcinoma breast in rural labour class population. Materials and Methods: The present study was a prospective study conducted on patients over 35 years of age having palpable breast lumps presenting in the out patient department of general surgery, ESI Hospital Basaidarapur New Delhi, India. The duration of study was from May 2007 to June 2009 and a total of 100 cases were studied. Each patient was subjected to a detailed history, clinical breast examination ,diagnostic mammography and FNAC. In this study, the results of each modality was divided in three groups: benign, suspicious and malignant. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of each test was calculated individually and as combined. Result: Out of 100 patients enrolled in this study, 60 cases were benign and 40 cases were of malignant breast disease. The age of patients with carcinoma breast in the series varied from 35 years to 70 years. The highest incidence of malignancy noted was 30% in 41-50 years age group (4th decade) followed by 27.5% in 51-60 years age group (5th decade). The sensitivity of clinical examination was found to be 75%, specificity was 83.3%, positive predictive value (PPV) of 75% and diagnostic accuracy of 80%. The sensitivity, specificity, positive predictive value and diagnostic accuracy of mammography was calculated and was found to be 94.9% , 90% , 86% and 92% respectively. The sensitivity, specificity, positive predictive value and diagnostic accuracy of FNAC was 94.7%, 98.3%, 97.3% and 96.6% respectively. Out of 100 cases triple test was concordant (all three test either benign or malignant) in 80 cases, all the benign cases detected by triple test were benign on final biopsy i.e. 100% specificity and 100% negative predictive value. Conclusion: TTS is an accurate and least invasive diagnostic test based on which definitive treatment can be initiated. PMID:25478391

Employing Tropospheric Numerical Weather Prediction Model for High-Precision GNSS Positioning

NASA Astrophysics Data System (ADS)

Alves, Daniele; Gouveia, Tayna; Abreu, Pedro; Magário, Jackes

2014-05-01

In the past few years is increasing the necessity of realizing high accuracy positioning. In this sense, the spatial technologies have being widely used. The GNSS (Global Navigation Satellite System) has revolutionized the geodetic positioning activities. Among the existent methods one can emphasize the Precise Point Positioning (PPP) and network-based positioning. But, to get high accuracy employing these methods, mainly in real time, is indispensable to realize the atmospheric modeling (ionosphere and troposphere) accordingly. Related to troposphere, there are the empirical models (for example Saastamoinen and Hopfield). But when highly accuracy results (error of few centimeters) are desired, maybe these models are not appropriated to the Brazilian reality. In order to minimize this limitation arises the NWP (Numerical Weather Prediction) models. In Brazil the CPTEC/INPE (Center for Weather Prediction and Climate Studies / Brazilian Institute for Spatial Researches) provides a regional NWP model, currently used to produce Zenithal Tropospheric Delay (ZTD) predictions (http://satelite.cptec.inpe.br/zenital/). The actual version, called eta15km model, has a spatial resolution of 15 km and temporal resolution of 3 hours. In this paper the main goal is to accomplish experiments and analysis concerning the use of troposphere NWP model (eta15km model) in PPP and network-based positioning. Concerning PPP it was used data from dozens of stations over the Brazilian territory, including Amazon forest. The results obtained with NWP model were compared with Hopfield one. NWP model presented the best results in all experiments. Related to network-based positioning it was used data from GNSS/SP Network in São Paulo State, Brazil. This network presents the best configuration in the country to realize this kind of positioning. Actually the network is composed by twenty stations (http://www.fct.unesp.br/#!/pesquisa/grupos-de-estudo-e-pesquisa/gege//gnss-sp-network2789/). The results obtained employing NWP model also were compared to Hopfield one, and the results were very interesting. The theoretical concepts, experiments, results and analysis will be presented in this paper.

The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion.

PubMed

Borkowski, Piotr

2017-06-20

It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship's current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships.

The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion

PubMed Central

Borkowski, Piotr

2017-01-01

It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship’s current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships. PMID:28632176

Increased genomic prediction accuracy in wheat breeding using a large Australian panel.

PubMed

Norman, Adam; Taylor, Julian; Tanaka, Emi; Telfer, Paul; Edwards, James; Martinant, Jean-Pierre; Kuchel, Haydn

2017-12-01

Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction. In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom Axiom TM Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.

Validity, accuracy, and predictive value of urinary tract infection signs and symptoms in individuals with spinal cord injury on intermittent catheterization.

PubMed

Massa, Luiz M; Hoffman, Jeanne M; Cardenas, Diana D

2009-01-01

To determine the validity, accuracy, and predictive value of the signs and symptoms of urinary tract infection (UTI) for individuals with spinal cord injury (SCI) using intermittent catheterization (IC) and the accuracy of individuals with SCI on IC at predicting their own UTI. Prospective cohort based on data from the first 3 months of a 1-year randomized controlled trial to evaluate UTI prevention effectiveness of hydrophilic and standard catheters. Fifty-six community-based individuals on IC. Presence of UTI as defined as bacteriuria with a colony count of at least 10(5) colony-forming units/mL and at least 1 sign or symptom of UTI. Analysis of monthly urine culture and urinalysis data combined with analysis of monthly data collected using a questionnaire that asked subjects to self-report on UTI signs and symptoms and whether or not they felt they had a UTI. Overall, "cloudy urine" had the highest accuracy (83.1%), and "leukocytes in the urine" had the highest sensitivity (82.8%). The highest specificity was for "fever" (99.0%); however, it had a very low sensitivity (6.9%). Subjects were able to predict their own UTI with an accuracy of 66.2%, and the negative predictive value (82.8%) was substantially higher than the positive predictive value (32.6%). The UTI signs and symptoms can predict a UTI more accurately than individual subjects can by using subjective impressions of their own signs and symptoms. Subjects were better at predicting when they did not have a UTI than when they did have a UTI.

Noninvasive Electromagnetic Detection of Bladder Cancer

PubMed Central

Cormio, Luigi; Vedruccio, Clarbruno; Leucci, Giorgio; Massenio, Paolo; Di Fino, Giuseppe; Cavaliere, Vincenzo; Carrieri, Giuseppe

2014-01-01

Objectives. Normal and neoplastic human tissues have different electromagnetic properties. This study aimed to determine the diagnostic accuracy of noninvasive electromagnetic detection of bladder cancer (BC) by the tissue-resonance interaction method (TRIM-prob). Patients and Methods. Consecutive patients were referred for cystoscopy because of (i) microscopic or gross hematuria and/or irritative voiding symptoms and (ii) bladder ultrasounds and urinary cytology findings negative or just suspicious of malignancy. Patients were first submitted to TRIM-prob bladder scanning by a single investigator and then to cystoscopy by another investigator blind to TRIM-prob data. Results. In 125 evaluated patients cystoscopy was positive for BC in 47 and negative in the remaining 78; conversely, TRIM-prob bladder scanning was positive for BC in 53 and negative in 72. In particular, TRIM-prob scanning yielded 7 false positives and only one false negative; therefore, its overall sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 97.9%, 89.9%, 86.8%, 98.6%, and 93.6%, respectively. Conclusions. TRIM-prob bladder scanning was a simple and quite accurate method for non-invasive electromagnetic detection of BC. If the elevated positive and negative predictive values will be replicated in further well-designed studies, it could be used to screen asymptomatic patients at high risk of BC. PMID:24563795

3-D sonography for diagnosis of disk dislocation of the temporomandibular joint compared with MRI.

PubMed

Landes, Constantin A; Goral, Wojciech A; Sader, Robert; Mack, Martin G

2006-05-01

This study determines the value of three-dimensional (3-D) sonography for the assessment of disk dislocation of the temporomandibular joint (TMJ). Sixty-eight patients (i.e.,136 TMJ) with clinical dysfunction were examined by 272 sonographic 3-D scans. An 8- to 12.5-MHz transducer, angulated by step-motor, was used after picking a volume box on 2-D scan; magnetic resonance imaging followed immediately. Every TMJ was scrutinized in closed- and open-mouth position for normal or dislocated disk position. Fifty-three patients had complete data sets, i.e., 106 TMJ, 212 examinations. Sonographic examination took 5 min, with 74% specificity (62% closed-mouth; 85% open-mouth); sensitivity 53% (62/43%); accuracy 70% (62/77%); positive predictive value 49% (57/41%); and negative predictive value 77% (67/86%). This study encourages more research on the diagnostic capacity of 3-D TMJ sonography, with the advantage of multidimensional joint visualization. Although fair in specificity and negative predictive value, sensitivity and accuracy may ameliorate with future higher-sound frequency, real-time 3-D viewing and automated image analysis.

Predicting Positive and Negative Relationships in Large Social Networks.

PubMed

Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N A; Fu, Yan

2015-01-01

In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

Friends' knowledge of youth internalizing and externalizing adjustment: accuracy, bias, and the influences of gender, grade, positive friendship quality, and self-disclosure.

PubMed

Swenson, Lance P; Rose, Amanda J

2009-08-01

Some evidence suggests that close friends may be knowledgeable of youth's psychological adjustment. However, friends are understudied as reporters of adjustment. The current study examines associations between self- and friend-reports of internalizing and externalizing adjustment in a community sample of fifth-, eighth-, and eleventh-grade youth. The study extends prior work by considering the degree to which friends' reports of youth adjustment are accurate (i.e., predicted by youths' actual adjustment) versus biased (i.e., predicted by the friend reporters' own adjustment). Findings indicated stronger bias effects than accuracy effects, but the accuracy effects were significant for both internalizing and externalizing adjustment. Additionally, friends who perceived their relationships as high in positive quality, friends in relationships high in disclosure, and girls perceived youths' internalizing symptoms most accurately. Knowledge of externalizing adjustment was not influenced by gender, grade, relationship quality, or self-disclosure. Findings suggest that friends could play an important role in prevention efforts.

Accuracy of Estimating Solar Radiation Pressure for GEO Debris with Tumbling Effect

NASA Astrophysics Data System (ADS)

Chao, Chia-Chun George

2009-03-01

The accuracy of estimating solar radiation pressure for GEO debris is examined and demonstrated, via numerical simulations, by fitting a batch (months) of simulated position vectors. These simulated position vectors are generated from a "truth orbit" with added white noise using high-precision numerical integration tools. After the long-arc fit of the simulated observations (position vectors), one can accurately and reliably determine how close the estimated value of solar radiation pressure is to the truth. Results of this study show that the inherent accuracy in estimating the solar radiation pressure coefficient can be as good as 1% if a long-arc fit span up to 180 days is used and the satellite is not tumbling. The corresponding position prediction accuracy can be as good as, in maximum error, 1 km along in-track, 0.3 km along radial and 0.1 km along cross-track up to 30 days. Similar accuracies can be expected when the object is tumbling as long as the rate of attitude change is different from the orbit rate. Results of this study reveal an important phenomenon that the solar radiation pressure significantly affects the orbit motion when the spin rate is equal to the orbit rate.

Comparative study to assess whether high sensitive C-reactive protein and carotid intima media thickness improve the predictive accuracy of exercise stress testing for coronary artery disease in perimenopausal women with typical angina.

PubMed

Sinha, Dhurjati Prasad; Das, Munna; Banerjee, Amal Kumar; Ahmed, Shageer; Majumdar, Sonali

2008-02-01

Anginal symptoms are less predictive of abnormal coronary anatomy in women. The diagnostic accuracy of exercise treadmill test for obstructive coronary artery disease is less in young and middle aged women. High sensitive C-reactive protein has shown a strong and consistent relationship to the risk of incident cardiovascular events. Carotid intima media thickness is a non-invasive marker of atherosclerosis burden and also predicts prognosis in patients with coronary artery disease. We investigated whether incorporation of high sensitive C-reactive protein and carotid intima media thickness along with exercise stress results improved the predictive accuracy in perimenopausal non-diabetic women subset. Fifty perimenopausal non-diabetic patients (age 45 +/- 7 years) presenting with typical angina were subjected to treadmill test (Bruce protocol). Also carotid artery images at both sides of neck were acquired by B-mode ultrasound and carotid intima media thickness were measured. High sensitive C-reactive protein was measured. Of 50 patients, 22 had a positive exercise stress result. Coronary angiography done in all 50 patients revealed coronary artery disease in 10 patients with positive exercise stress result and in 4 patients with negative exercise stress result. Treadmill exercise stress test had a sensitivity of 71.4%, specificity of 66.7% and a negative predictive accuracy of 85.7% in this study group. High sensitive C-reactive protein in patients with documented coronary artery disease was not significantly different from those without coronary artery disease (4.8 +/- 0.9 mg/l versus 3.9 +/- 1.7 mg/l, p=NS). Also carotid intima media thickness was not significantly different between either of the groups with coronary artery disease positivity and negativity respectively (left: 1.25 +/- 0.55 versus 1.20 +/- 0.51 mm, p=NS; right:1.18 +/- 0.54 versus 1.15 +/- 0.41 mm, p=NS). High sensitive C-reactive protein and carotid intima media thickness were not helpful in further adding to the predictability of coronary artery disease in perimenopausal patients with typical angina as assessed by treadmill exercise stress test.

Magnifying endoscopy for the diagnosis of specialized intestinal metaplasia in short-segment Barrett's esophagus.

PubMed

Ham, Nam Seok; Jang, Jae Young; Ryu, Sung Woo; Kim, Ji Hye; Park, Eui Ju; Lee, Woong Cheul; Shim, Kwang Yeun; Jeong, Soung Won; Kim, Hyun Gun; Lee, Tae Hee; Jeon, Sung Ran; Cho, Jun Hyung; Cho, Joo Young; Jin, So Young; Lee, Ji Sung

2013-11-07

To determine whether magnified observation of short-segment Barrett's esophagus (BE) is useful for the detection of specialized intestinal metaplasia (SIM). Thirty patients with suspected short-segment BE underwent magnifying endoscopy up to × 80. The magnified images were analyzed with respect to their pit-patterns, which were simultaneously classified into five epithelial types [I (small round), II (straight), III (long oval), IV (tubular), V (villous)] by Endo's classification. Then, a 0.5% solution of methylene blue (MB) was sprayed over columnar mucosa. The patterns of the magnified image and MB staining were analyzed. Biopsies were obtained from the regions previously observed by magnifying endoscopy and MB chromoendoscopy. Three of five patients with a type V (villous) epithelial pattern had SIM, whereas 21 patients with a non-type V epithelial patterns did not have SIM. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of pit-patterns in detecting SIM were 100%, 91.3%, 92.3%, 60% and 100%, respectively (P = 0.004). Three of the 12 patients with positive MB staining had SIM, whereas 14 patients with negative MB staining did not have SIM. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of MB staining in detecting SIM were 100%, 60.9%, 65.4%, 25% and 100%, respectively (P = 0.085). The specificity and accuracy of pit-pattern evaluation were significantly superior compared with MB staining for detecting SIM by comparison with the exact McNemar's test (P = 0.0391). The magnified observation of a short-segment BE according to the mucosal pattern and its classification can be predictive of SIM.

Should gram stains have a role in diagnosing hip arthroplasty infections?

PubMed

Johnson, Aaron J; Zywiel, Michael G; Stroh, D Alex; Marker, David R; Mont, Michael A

2010-09-01

The utility of Gram stains in diagnosing periprosthetic infections following total hip arthroplasty has recently been questioned. Several studies report low sensitivity of the test, and its poor ability to either confirm or rule out infection in patients undergoing revision total hip arthroplasty. Despite this, many institutions including that of the senior author continue to perform Gram stains during revision total hip arthroplasty. We assessed the sensitivity, specificity, accuracy, and positive and negative predictive values of Gram stains from surgical-site samplings taken from procedures on patients with both infected and aseptic revision total hip arthroplasties. A review was performed on patients who underwent revision total hip arthroplasty between 2000 and 2007. Eighty-two Gram stains were performed on patients who had infected total hip arthroplasties and underwent revision procedures. Additionally, of the 410 revision total hip arthroplasties performed on patients who were confirmed infection-free, 120 Gram stains were performed. Patients were diagnosed as infected using multiple criteria at the time of surgery. Sensitivity, specificity, positive and negative predictive values, and accuracy were calculated from these Gram stain results. The Gram stain demonstrated a sensitivity and specificity of 9.8% and 100%, respectively. In this series, the Gram stain had a negative predictive value of 62%, a positive predictive value of 100%, and an accuracy of 63%. Gram stains obtained from surgical-site samples had poor sensitivity and poor negative predictive value. Based on these findings, as well as those of other authors, we believe that Gram stains should no longer be considered for diagnosing infections in revision total hip arthroplasty. Level III, diagnostic study. See Guidelines for Authors for a complete description of levels of evidence.

Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules

PubMed Central

Desai, Aarti; Singh, Vivek K.; Jere, Abhay

2016-01-01

Introduction Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense) that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage. Results The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with ‘High’ reliability scoring), DEREK (accuracy = 72.73% and CCR = 71.44%) and TOPKAT (accuracy = 60.00% and CCR = 61.67%). Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%), the coverage was very low (only 10 out of 77 molecules were predicted reliably). Conclusions Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing. PMID:27271321

Prediction of early and late preeclampsia by flow-mediated dilation of the brachial artery*

PubMed Central

Brandão, Augusto Henriques Fulgêncio; Evangelista, Aline Aarão; Martins, Raphaela Menin Franco; Leite, Henrique Vítor; Cabral, Antônio Carlos Vieira

2014-01-01

Objective To assess the accuracy in the prediction of both early and late preeclampsia by flow-mediated dilation of the brachial artery (FMD), a biophysical marker for endothelial dysfunction. Materials and Methods A total of 91 patients, considered at high risk for development of preeclampsia were submitted to brachial artery FMD between 24 and 28 weeks of gestation. Results Nineteen out of the selected patients developed preeclampsia, 8 in its early form and 11 in the late form. With a cut-off value of 6.5%, the FMD sensitivity for early preeclampsia prediction was 75.0%, with specificity of 73.3%, positive predictive value (PPV) of 32.4% and negative predictive value (NPV) of 91.9%. For the prediction of late preeclampsia, sensitivity = 83.3%, specificity = 73.2%, PPV = 34.4% and NPV = 96.2% were observed. And for the prediction of all associated forms of preeclampsia, sensitivity = 84.2%, specificity = 73.6%, PPV = 45.7% and NPV = 94.6% were observed. Conclusion FMD of the brachial artery is a test with good accuracy in the prediction of both early and late preeclampsia, which may represent a positive impact on the follow-up of pregnant women at high risk for developing this syndrome. PMID:25741086

Accuracy of frozen section in the diagnosis of ovarian tumours.

PubMed

Toneva, F; Wright, H; Razvi, K

2012-07-01

The purpose of our retrospective study was to assess the accuracy of intraoperative frozen section diagnosis compared to final paraffin diagnosis in ovarian tumours at a gynaecological oncology centre in the UK. We analysed 66 cases and observed that frozen section consultation agreed with final paraffin diagnosis in 59 cases, which provided an accuracy of 89.4%. The overall sensitivity and specificity for all tumours were 85.4% and 100%, respectively. The positive predictive value (PPV) and negative predictive value (NPV) were 100% and 89.4%, respectively. Of the seven cases with discordant results, the majority were large, mucinous tumours, which is in line with previous studies. Our study demonstrated that despite its limitations, intraoperative frozen section has a high accuracy and sensitivity for assessing ovarian tumours; however, care needs to be taken with large, mucinous tumours.

SU-E-J-234: Application of a Breathing Motion Model to ViewRay Cine MR Images

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

O’Connell, D. P.; Thomas, D. H.; Dou, T. H.

2015-06-15

Purpose: A respiratory motion model previously used to generate breathing-gated CT images was used with cine MR images. Accuracy and predictive ability of the in-plane models were evaluated. Methods: Sagittalplane cine MR images of a patient undergoing treatment on a ViewRay MRI/radiotherapy system were acquired before and during treatment. Images were acquired at 4 frames/second with 3.5 × 3.5 mm resolution and a slice thickness of 5 mm. The first cine frame was deformably registered to following frames. Superior/inferior component of the tumor centroid position was used as a breathing surrogate. Deformation vectors and surrogate measurements were used to determinemore » motion model parameters. Model error was evaluated and subsequent treatment cines were predicted from breathing surrogate data. A simulated CT cine was created by generating breathing-gated volumetric images at 0.25 second intervals along the measured breathing trace, selecting a sagittal slice and downsampling to the resolution of the MR cines. A motion model was built using the first half of the simulated cine data. Model accuracy and error in predicting the remaining frames of the cine were evaluated. Results: Mean difference between model predicted and deformably registered lung tissue positions for the 28 second preview MR cine acquired before treatment was 0.81 +/− 0.30 mm. The model was used to predict two minutes of the subsequent treatment cine with a mean accuracy of 1.59 +/− 0.63 mm. Conclusion: Inplane motion models were built using MR cine images and evaluated for accuracy and ability to predict future respiratory motion from breathing surrogate measurements. Examination of long term predictive ability is ongoing. The technique was applied to simulated CT cines for further validation, and the authors are currently investigating use of in-plane models to update pre-existing volumetric motion models used for generation of breathing-gated CT planning images.« less

Diagnostic yield and accuracy of coronary CT angiography after abnormal nuclear myocardial perfusion imaging.

PubMed

Meinel, Felix G; Schoepf, U Joseph; Townsend, Jacob C; Flowers, Brian A; Geyer, Lucas L; Ebersberger, Ullrich; Krazinski, Aleksander W; Kunz, Wolfgang G; Thierfelder, Kolja M; Baker, Deborah W; Khan, Ashan M; Fernandes, Valerian L; O'Brien, Terrence X

2018-06-15

We aimed to determine the diagnostic yield and accuracy of coronary CT angiography (CCTA) in patients referred for invasive coronary angiography (ICA) based on clinical concern for coronary artery disease (CAD) and an abnormal nuclear stress myocardial perfusion imaging (MPI) study. We enrolled 100 patients (84 male, mean age 59.6 ± 8.9 years) with an abnormal MPI study and subsequent referral for ICA. Each patient underwent CCTA prior to ICA. We analyzed the prevalence of potentially obstructive CAD (≥50% stenosis) on CCTA and calculated the diagnostic accuracy of ≥50% stenosis on CCTA for the detection of clinically significant CAD on ICA (defined as any ≥70% stenosis or ≥50% left main stenosis). On CCTA, 54 patients had at least one ≥50% stenosis. With ICA, 45 patients demonstrated clinically significant CAD. A positive CCTA had 100% sensitivity and 84% specificity with a 100% negative predictive value and 83% positive predictive value for clinically significant CAD on a per patient basis in MPI positive symptomatic patients. In conclusion, almost half (48%) of patients with suspected CAD and an abnormal MPI study demonstrate no obstructive CAD on CCTA.

Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis.

PubMed

Conde-Agudelo, A; Papageorghiou, A T; Kennedy, S H; Villar, J

2013-05-01

Several biomarkers for predicting intrauterine growth restriction (IUGR) have been proposed in recent years. However, the predictive performance of these biomarkers has not been systematically evaluated. To determine the predictive accuracy of novel biomarkers for IUGR in women with singleton gestations. Electronic databases, reference list checking and conference proceedings. Observational studies that evaluated the accuracy of novel biomarkers proposed for predicting IUGR. Data were extracted on characteristics, quality and predictive accuracy from each study to construct 2×2 tables. Summary receiver operating characteristic curves, sensitivities, specificities and likelihood ratios (LRs) were generated. A total of 53 studies, including 39,974 women and evaluating 37 novel biomarkers, fulfilled the inclusion criteria. Overall, the predictive accuracy of angiogenic factors for IUGR was minimal (median pooled positive and negative LRs of 1.7, range 1.0-19.8; and 0.8, range 0.0-1.0, respectively). Two small case-control studies reported high predictive values for placental growth factor and angiopoietin-2 only when IUGR was defined as birthweight centile with clinical or pathological evidence of fetal growth restriction. Biomarkers related to endothelial function/oxidative stress, placental protein/hormone, and others such as serum levels of vitamin D, urinary albumin:creatinine ratio, thyroid function tests and metabolomic profile had low predictive accuracy. None of the novel biomarkers evaluated in this review are sufficiently accurate to recommend their use as predictors of IUGR in routine clinical practice. However, the use of biomarkers in combination with biophysical parameters and maternal characteristics could be more useful and merits further research. © 2013 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2013 RCOG.

Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis.

PubMed

Linden, Ariel

2006-04-01

Diagnostic or predictive accuracy concerns are common in all phases of a disease management (DM) programme, and ultimately play an influential role in the assessment of programme effectiveness. Areas, such as the identification of diseased patients, predictive modelling of future health status and costs and risk stratification, are just a few of the domains in which assessment of accuracy is beneficial, if not critical. The most commonly used analytical model for this purpose is the standard 2 x 2 table method in which sensitivity and specificity are calculated. However, there are several limitations to this approach, including the reliance on a single defined criterion or cut-off for determining a true-positive result, use of non-standardized measurement instruments and sensitivity to outcome prevalence. This paper introduces the receiver operator characteristic (ROC) analysis as a more appropriate and useful technique for assessing diagnostic and predictive accuracy in DM. Its advantages include; testing accuracy across the entire range of scores and thereby not requiring a predetermined cut-off point, easily examined visual and statistical comparisons across tests or scores, and independence from outcome prevalence. Therefore the implementation of ROC as an evaluation tool should be strongly considered in the various phases of a DM programme.

Diagnostic Accuracy of Global Pharma Health Fund Minilab™ in Assessing Pharmacopoeial Quality of Antimicrobials.

PubMed

Pan, Hui; Ba-Thein, William

2018-01-01

Global Pharma Health Fund (GPHF) Minilab™, a semi-quantitative thin-layer chromatography (TLC)-based commercially available test kit, is widely used in drug quality surveillance globally, but its diagnostic accuracy is unclear. We investigated the diagnostic accuracy of Minilab system for antimicrobials, using high-performance liquid chromatography (HPLC) as reference standard. Following the Minilab protocols and the Pharmacopoeia of the People's Republic of China protocols, Minilab-TLC and HPLC were used to test five common antimicrobials (506 batches) for relative concentration of active pharmaceutical ingredients. The prevalence of poor-quality antimicrobials determined, respectively, by Minilab TLC and HPLC was amoxicillin (0% versus 14.9%), azithromycin (0% versus 17.4%), cefuroxime axetil (14.3% versus 0%), levofloxacin (0% versus 3.0%), and metronidazole (0% versus 38.0%). The Minilab TLC had false-positive and false-negative detection rates of 2.6% (13/506) and 15.2% (77/506) accordingly, resulting in the following test characteristics: sensitivity 0%, specificity 97.0%, positive predictive value 0, negative predictive value 0.8, positive likelihood ratio 0, negative likelihood ratio 1.0, diagnostic odds ratio 0, and adjusted diagnostic odds ratio 0.2. This study demonstrates unsatisfying diagnostic accuracy of Minilab system in screening poor-quality antimicrobials of common use. Using Minilab as a stand-alone system for monitoring drug quality should be reconsidered.

THE PANC 3 SCORE PREDICTING SEVERITY OF ACUTE PANCREATITIS.

PubMed

Beduschi, Murilo Gamba; Mello, André Luiz Parizi; VON-Mühlen, Bruno; Franzon, Orli

2016-03-01

About 20% of cases of acute pancreatitis progress to a severe form, leading to high mortality rates. Several studies suggested methods to identify patients that will progress more severely. However, most studies present problems when used on daily practice. To assess the efficacy of the PANC 3 score to predict acute pancreatitis severity and its relation to clinical outcome. Acute pancreatitis patients were assessed as to sex, age, body mass index (BMI), etiology of pancreatitis, intensive care need, length of stay, length of stay in intensive care unit and mortality. The PANC 3 score was determined within the first 24 hours after diagnosis and compared to acute pancreatitis grade of the Revised Atlanta classification. Out of 64 patients diagnosed with acute pancreatitis, 58 met the inclusion criteria. The PANC 3 score was positive in five cases (8.6%), pancreatitis progressed to a severe form in 10 cases (17.2%) and five patients (8.6%) died. Patients with a positive score and severe pancreatitis required intensive care more often, and stayed for a longer period in intensive care units. The PANC 3 score showed sensitivity of 50%, specificity of 100%, accuracy of 91.4%, positive predictive value of 100% and negative predictive value of 90.6% in prediction of severe acute pancreatitis. The PANC 3 score is useful to assess acute pancreatitis because it is easy and quick to use, has high specificity, high accuracy and high predictive value in prediction of severe acute pancreatitis.

Type I and II β-turns prediction using NMR chemical shifts.

PubMed

Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

2014-07-01

A method for predicting type I and II β-turns using nuclear magnetic resonance (NMR) chemical shifts is proposed. Isolated β-turn chemical-shift data were collected from 1,798 protein chains. One-dimensional statistical analyses on chemical-shift data of three classes β-turn (type I, II, and VIII) showed different distributions at four positions, (i) to (i + 3). Considering the central two residues of type I β-turns, the mean values of Cο, Cα, H(N), and N(H) chemical shifts were generally (i + 1) > (i + 2). The mean values of Cβ and Hα chemical shifts were (i + 1) < (i + 2). The distributions of the central two residues in type II and VIII β-turns were also distinguishable by trends of chemical shift values. Two-dimensional cluster analyses on chemical-shift data show positional distributions more clearly. Based on these propensities of chemical shift classified as a function of position, rules were derived using scoring matrices for four consecutive residues to predict type I and II β-turns. The proposed method achieves an overall prediction accuracy of 83.2 and 84.2% with the Matthews correlation coefficient values of 0.317 and 0.632 for type I and II β-turns, indicating that its higher accuracy for type II turn prediction. The results show that it is feasible to use NMR chemical shifts to predict the β-turn types in proteins. The proposed method can be incorporated into other chemical-shift based protein secondary structure prediction methods.

THE PANC 3 SCORE PREDICTING SEVERITY OF ACUTE PANCREATITIS

PubMed Central

BEDUSCHI, Murilo Gamba; MELLO, André Luiz Parizi; VON-MÜHLEN, Bruno; FRANZON, Orli

2016-01-01

Background : About 20% of cases of acute pancreatitis progress to a severe form, leading to high mortality rates. Several studies suggested methods to identify patients that will progress more severely. However, most studies present problems when used on daily practice. Objective : To assess the efficacy of the PANC 3 score to predict acute pancreatitis severity and its relation to clinical outcome. Methods : Acute pancreatitis patients were assessed as to sex, age, body mass index (BMI), etiology of pancreatitis, intensive care need, length of stay, length of stay in intensive care unit and mortality. The PANC 3 score was determined within the first 24 hours after diagnosis and compared to acute pancreatitis grade of the Revised Atlanta classification. Results : Out of 64 patients diagnosed with acute pancreatitis, 58 met the inclusion criteria. The PANC 3 score was positive in five cases (8.6%), pancreatitis progressed to a severe form in 10 cases (17.2%) and five patients (8.6%) died. Patients with a positive score and severe pancreatitis required intensive care more often, and stayed for a longer period in intensive care units. The PANC 3 score showed sensitivity of 50%, specificity of 100%, accuracy of 91.4%, positive predictive value of 100% and negative predictive value of 90.6% in prediction of severe acute pancreatitis. Conclusion : The PANC 3 score is useful to assess acute pancreatitis because it is easy and quick to use, has high specificity, high accuracy and high predictive value in prediction of severe acute pancreatitis. PMID:27120730

Evaluating Diagnostic Accuracy of Noninvasive Tests in Assessment of Significant Liver Fibrosis in Chronic Hepatitis C Egyptian Patients.

PubMed

Omran, Dalia; Zayed, Rania A; Nabeel, Mohammed M; Mobarak, Lamiaa; Zakaria, Zeinab; Farid, Azza; Hassany, Mohamed; Saif, Sameh; Mostafa, Muhammad; Saad, Omar Khalid; Yosry, Ayman

2018-05-01

Stage of liver fibrosis is critical for treatment decision and prediction of outcomes in chronic hepatitis C (CHC) patients. We evaluated the diagnostic accuracy of transient elastography (TE)-FibroScan and noninvasive serum markers tests in the assessment of liver fibrosis in CHC patients, in reference to liver biopsy. One-hundred treatment-naive CHC patients were subjected to liver biopsy, TE-FibroScan, and eight serum biomarkers tests; AST/ALT ratio (AAR), AST to platelet ratio index (APRI), age-platelet index (AP index), fibrosis quotient (FibroQ), fibrosis 4 index (FIB-4), cirrhosis discriminant score (CDS), King score, and Goteborg University Cirrhosis Index (GUCI). Receiver operating characteristic curves were constructed to compare the diagnostic accuracy of these noninvasive methods in predicting significant fibrosis in CHC patients. TE-FibroScan predicted significant fibrosis at cutoff value 8.5 kPa with area under the receiver operating characteristic (AUROC) 0.90, sensitivity 83%, specificity 91.5%, positive predictive value (PPV) 91.2%, and negative predictive value (NPV) 84.4%. Serum biomarkers tests showed that AP index and FibroQ had the highest diagnostic accuracy in predicting significant liver fibrosis at cutoff 4.5 and 2.7, AUROC was 0.8 and 0.8 with sensitivity 73.6% and 73.6%, specificity 70.2% and 68.1%, PPV 71.1% and 69.8%, and NPV 72.9% and 72.3%, respectively. Combined AP index and FibroQ had AUROC 0.83 with sensitivity 73.6%, specificity 80.9%, PPV 79.6%, and NPV 75.7% for predicting significant liver fibrosis. APRI, FIB-4, CDS, King score, and GUCI had intermediate accuracy in predicting significant liver fibrosis with AUROC 0.68, 0.78, 0.74, 0.74, and 0.67, respectively, while AAR had low accuracy in predicting significant liver fibrosis. TE-FibroScan is the most accurate noninvasive alternative to liver biopsy. AP index and FibroQ, either as individual tests or combined, have good accuracy in predicting significant liver fibrosis, and are better combined for higher specificity.

Misdiagnosis of HIV infection during a South African community-based survey: implications for rapid HIV testing

PubMed Central

Kufa, Tendesayi; Kharsany, Ayesha BM; Cawood, Cherie; Khanyile, David; Lewis, Lara; Grobler, Anneke; Chipeta, Zawadi; Bere, Alfred; Glenshaw, Mary; Puren, Adrian

2017-01-01

Abstract Introduction: We describe the overall accuracy and performance of a serial rapid HIV testing algorithm used in community-based HIV testing in the context of a population-based household survey conducted in two sub-districts of uMgungundlovu district, KwaZulu-Natal, South Africa, against reference fourth-generation HIV-1/2 antibody and p24 antigen combination immunoassays. We discuss implications of the findings on rapid HIV testing programmes. Methods: Cross-sectional design: Following enrolment into the survey, questionnaires were administered to eligible and consenting participants in order to obtain demographic and HIV-related data. Peripheral blood samples were collected for HIV-related testing. Participants were offered community-based HIV testing in the home by trained field workers using a serial algorithm with two rapid diagnostic tests (RDTs) in series. In the laboratory, reference HIV testing was conducted using two fourth-generation immunoassays with all positives in the confirmatory test considered true positives. Accuracy, sensitivity, specificity, positive predictive value, negative predictive value and false-positive and false-negative rates were determined. Results: Of 10,236 individuals enrolled in the survey, 3740 were tested in the home (median age 24 years (interquartile range 19–31 years), 42.1% males and HIV positivity on RDT algorithm 8.0%). From those tested, 3729 (99.7%) had a definitive RDT result as well as a laboratory immunoassay result. The overall accuracy of the RDT when compared to the fourth-generation immunoassays was 98.8% (95% confidence interval (CI) 98.5–99.2). The sensitivity, specificity, positive predictive value and negative predictive value were 91.1% (95% CI 87.5–93.7), 99.9% (95% CI 99.8–100), 99.3% (95% CI 97.4–99.8) and 99.1% (95% CI 98.8–99.4) respectively. The false-positive and false-negative rates were 0.06% (95% CI 0.01–0.24) and 8.9% (95% CI 6.3–12.53). Compared to true positives, false negatives were more likely to be recently infected on limited antigen avidity assay and to report antiretroviral therapy (ART) use. Conclusions: The overall accuracy of the RDT algorithm was high. However, there were few false positives, and the sensitivity was lower than expected with high false negatives, despite implementation of quality assurance measures. False negatives were associated with recent (early) infection and ART exposure. The RDT algorithm was able to correctly identify the majority of HIV infections in community-based HIV testing. Messaging on the potential for false positives and false negatives should be included in these programmes. PMID:28872274

Middle cerebral artery peak systolic velocity to predict fetal hemoglobin levels in twin anemia-polycythemia sequence.

PubMed

Slaghekke, F; Pasman, S; Veujoz, M; Middeldorp, J M; Lewi, L; Devlieger, R; Favre, R; Lopriore, E; Oepkes, D

2015-10-01

To evaluate the diagnostic accuracy of middle cerebral artery peak systolic velocity (MCA-PSV) Doppler measurements in prediction of hemoglobin levels in twin anemia-polycythemia sequence (TAPS). This study involved a consecutive cohort comprising monochorionic twin pregnancies complicated by TAPS managed at three European fetal medicine centers between 2005 and 2013. The accuracy of MCA-PSV, measured immediately prior to fetal hemoglobin (Hb) measurement by fetal or cord blood sampling, for prediction of anemia and polycythemia was assessed using 2 × 2 tables. A total of 116 measurements (74 recorded in donors and 42 in recipients) from 43 twin pregnancies complicated by TAPS were available for analysis. MCA-PSV multiples of the median (MoM) values correlated well with Hb levels (r = - 0.86; P < 0.001). The sensitivity of MCA-PSV ≥ 1.5 MoM to predict severe anemia (Hb deficit > 5 SD below the mean) in TAPS donors was 94% (95% CI, 85-98%); specificity was 74% (95% CI, 62-83%); positive and negative predictive values were 76% (95% CI, 65-85%) and 94% (95% CI, 83-98%), respectively. The sensitivity of MCA-PSV ≤ 1.0 MoM to predict polycythemia (Hb level > 5 SD above the mean) in TAPS recipients was 97% (95% CI, 87-99%); specificity was 96% (95% CI, 89-99%); positive and negative predictive values were 93% (95% CI, 81-97%) and 99% (95% CI, 93-100%), respectively. MCA-PSV measurement has high diagnostic accuracy for predicting abnormal Hb levels in fetuses with TAPS. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

High accuracy satellite drag model (HASDM)

NASA Astrophysics Data System (ADS)

Storz, M.; Bowman, B.; Branson, J.

The dominant error source in the force models used to predict low perigee satellite trajectories is atmospheric drag. Errors in operational thermospheric density models cause significant errors in predicted satellite positions, since these models do not account for dynamic changes in atmospheric drag for orbit predictions. The Air Force Space Battlelab's High Accuracy Satellite Drag Model (HASDM) estimates and predicts (out three days) a dynamically varying high-resolution density field. HASDM includes the Dynamic Calibration Atmosphere (DCA) algorithm that solves for the phases and amplitudes of the diurnal, semidiurnal and terdiurnal variations of thermospheric density near real-time from the observed drag effects on a set of Low Earth Orbit (LEO) calibration satellites. The density correction is expressed as a function of latitude, local solar time and altitude. In HASDM, a time series prediction filter relates the extreme ultraviolet (EUV) energy index E10.7 and the geomagnetic storm index a p to the DCA density correction parameters. The E10.7 index is generated by the SOLAR2000 model, the first full spectrum model of solar irradiance. The estimated and predicted density fields will be used operationally to significantly improve the accuracy of predicted trajectories for all low perigee satellites.

High accuracy satellite drag model (HASDM)

NASA Astrophysics Data System (ADS)

Storz, Mark F.; Bowman, Bruce R.; Branson, Major James I.; Casali, Stephen J.; Tobiska, W. Kent

The dominant error source in force models used to predict low-perigee satellite trajectories is atmospheric drag. Errors in operational thermospheric density models cause significant errors in predicted satellite positions, since these models do not account for dynamic changes in atmospheric drag for orbit predictions. The Air Force Space Battlelab's High Accuracy Satellite Drag Model (HASDM) estimates and predicts (out three days) a dynamically varying global density field. HASDM includes the Dynamic Calibration Atmosphere (DCA) algorithm that solves for the phases and amplitudes of the diurnal and semidiurnal variations of thermospheric density near real-time from the observed drag effects on a set of Low Earth Orbit (LEO) calibration satellites. The density correction is expressed as a function of latitude, local solar time and altitude. In HASDM, a time series prediction filter relates the extreme ultraviolet (EUV) energy index E10.7 and the geomagnetic storm index ap, to the DCA density correction parameters. The E10.7 index is generated by the SOLAR2000 model, the first full spectrum model of solar irradiance. The estimated and predicted density fields will be used operationally to significantly improve the accuracy of predicted trajectories for all low-perigee satellites.

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Using Bluetooth proximity sensing to determine where office workers spend time at work.

PubMed

Clark, Bronwyn K; Winkler, Elisabeth A; Brakenridge, Charlotte L; Trost, Stewart G; Healy, Genevieve N

2018-01-01

Most wearable devices that measure movement in workplaces cannot determine the context in which people spend time. This study examined the accuracy of Bluetooth sensing (10-second intervals) via the ActiGraph GT9X Link monitor to determine location in an office setting, using two simple, bespoke algorithms. For one work day (mean±SD 6.2±1.1 hours), 30 office workers (30% men, aged 38±11 years) simultaneously wore chest-mounted cameras (video recording) and Bluetooth-enabled monitors (initialised as receivers) on the wrist and thigh. Additional monitors (initialised as beacons) were placed in the entry, kitchen, photocopy room, corridors, and the wearer's office. Firstly, participant presence/absence at each location was predicted from the presence/absence of signals at that location (ignoring all other signals). Secondly, using the information gathered at multiple locations simultaneously, a simple heuristic model was used to predict at which location the participant was present. The Bluetooth-determined location for each algorithm was tested against the camera in terms of F-scores. When considering locations individually, the accuracy obtained was excellent in the office (F-score = 0.98 and 0.97 for thigh and wrist positions) but poor in other locations (F-score = 0.04 to 0.36), stemming primarily from a high false positive rate. The multi-location algorithm exhibited high accuracy for the office location (F-score = 0.97 for both wear positions). It also improved the F-scores obtained in the remaining locations, but not always to levels indicating good accuracy (e.g., F-score for photocopy room ≈0.1 in both wear positions). The Bluetooth signalling function shows promise for determining where workers spend most of their time (i.e., their office). Placing beacons in multiple locations and using a rule-based decision model improved classification accuracy; however, for workplace locations visited infrequently or with considerable movement, accuracy was below desirable levels. Further development of algorithms is warranted.

Using electronic data to predict the probability of true bacteremia from positive blood cultures.

PubMed

Wang, S J; Kuperman, G J; Ohno-Machado, L; Onderdonk, A; Sandige, H; Bates, D W

2000-01-01

As part of a project to help physicians make more appropriate treatment decisions, we implemented a clinical prediction rule that computes the probability of true bacteremia for positive blood cultures and displays this information when culture results are viewed online. Prior to implementing the rule, we performed a revalidation study to verify the accuracy of the previously published logistic regression model. We randomly selected 114 cases of positive blood cultures from a recent one-year period and performed a paper chart review with the help of infectious disease experts to determine whether the cultures were true positives or contaminants. Based on the results of this revalidation study, we updated the probabilities reported by the model and made additional enhancements to improve the accuracy of the rule. Next, we implemented the rule into our hospital's laboratory computer system so that the probability information was displayed with all positive blood culture results. We displayed the prediction rule information on approximately half of the 2184 positive blood cultures at our hospital that were randomly selected during a 6-month period. During the study, we surveyed 54 housestaff to obtain their opinions about the usefulness of this intervention. Fifty percent (27/54) indicated that the information had influenced their belief of the probability of bacteremia in their patients, and in 28% (15/54) of cases it changed their treatment decision. Almost all (98% (53/54)) indicated that they wanted to continue receiving this information. We conclude that the probability information provided by this clinical prediction rule is considered useful to physicians when making treatment decisions.

Comparison of the influence of plastic and fully covered metal biliary stents on the accuracy of EUS-FNA for the diagnosis of pancreatic cancer.

PubMed

Siddiqui, Ali A; Fein, Michael; Kowalski, Thomas E; Loren, David E; Eloubeidi, Mohamad A

2012-09-01

Prior studies have reported that the presence of prior biliary stent may interfere with EUS visualization of pancreatic tumors. We aimed to compare the influence of the biliary plastic and fully covered self-expanding metal stents (CSEMS) on the accuracy of EUS-FNA cytology in patients with solid pancreatic masses. We conducted a retrospective study evaluating 677 patients with solid pancreatic head/uncinate lesions and a previous biliary stent in whom EUS-FNA was performed. The patients were stratified into two groups: (1) those with a plastic stents and (2) those with CSEMS. Performance characteristics of EUS-FNA including the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were compared between the two groups. The frequency of obtaining an adequate cytology by EUS-FNA was similar in both the CSEMS group and the plastic stent group (97 vs. 97.1 % respectively; p = 1.0). The sensitivity, specificity, and accuracy of EUS-FNA was not significantly different between patients with CSEMS and plastic stents (96.8, 100, 100 % and 97.3, 98, 99.8 %, respectively). The negative predictive value for EUS-FNA was lower in the CSEMS group compared to the plastic stent group (66.6 vs. 78.1 % respectively; p = 0.42). There was one false-positive cytology in the plastic stent group compared to none in the CSEMS group. In a retrospective cohort trial, EUS-FNA was found to be highly accurate and safe in diagnosing patients with suspected pancreatic cancer, even in the presence of a plastic or metallic biliary stent. The presence of a stent did not contribute to a higher false-positive cytology rate.

Clinical utility of balloon expulsion test for functional defecation disorders

PubMed Central

2016-01-01

Purpose I investigated the diagnostic accuracy of balloon expulsion test (BET) with various techniques to find out the most appropriate method, and tried to confirm its clinical utility in diagnosing functional defecation disorders (FDD) in constipated patients. Methods Eighty-seven patients constituted the study population. FDD was defined when patients had at least two positive findings in defecography, manometry, and electromyography. BET was done 4 times in each patient with 2 different positions and 2 different volumes. The positions were seated position (SP) and left lateral decubitus position (LDP). The volumes were fixed volume (FV) of 60 mL and individualized volume with which patient felt a constant desire to defecate (CDV). The results of BETs with 4 different settings (LDP-FV, LDP-CDV, SP-FV, and SP-CDV) were statistically compared and analyzed. Results Of 87 patients, 23 patients (26.4%) had at least two positive findings in 3 tests and thus were diagnosed to have FDD. On receiver operating characteristic curve analysis, area under curve was highest in BET with SP-FV. With a cutoff value of 30 seconds, the specificity of BET with SP-FV was 86.0%, sensitivity was 73.9%, negative predictive value was 89.8%, positive predictive value was 65.4%, and accuracy rate was 82.8% for diagnosing FDD. Conclusion SP-FV is the most appropriate method for BET. In this setting, BET has a diagnostic accuracy sufficient to identify constipated patients who do not have FDD. Patients with negative results in BET with SP-FV may not need other onerous tests to exclude FDD. PMID:26878016

Clinical utility of balloon expulsion test for functional defecation disorders.

PubMed

Seong, Moo-Kyung

2016-02-01

I investigated the diagnostic accuracy of balloon expulsion test (BET) with various techniques to find out the most appropriate method, and tried to confirm its clinical utility in diagnosing functional defecation disorders (FDD) in constipated patients. Eighty-seven patients constituted the study population. FDD was defined when patients had at least two positive findings in defecography, manometry, and electromyography. BET was done 4 times in each patient with 2 different positions and 2 different volumes. The positions were seated position (SP) and left lateral decubitus position (LDP). The volumes were fixed volume (FV) of 60 mL and individualized volume with which patient felt a constant desire to defecate (CDV). The results of BETs with 4 different settings (LDP-FV, LDP-CDV, SP-FV, and SP-CDV) were statistically compared and analyzed. Of 87 patients, 23 patients (26.4%) had at least two positive findings in 3 tests and thus were diagnosed to have FDD. On receiver operating characteristic curve analysis, area under curve was highest in BET with SP-FV. With a cutoff value of 30 seconds, the specificity of BET with SP-FV was 86.0%, sensitivity was 73.9%, negative predictive value was 89.8%, positive predictive value was 65.4%, and accuracy rate was 82.8% for diagnosing FDD. SP-FV is the most appropriate method for BET. In this setting, BET has a diagnostic accuracy sufficient to identify constipated patients who do not have FDD. Patients with negative results in BET with SP-FV may not need other onerous tests to exclude FDD.

Diagnosis and prediction of periodontally compromised teeth using a deep learning-based convolutional neural network algorithm.

PubMed

Lee, Jae-Hong; Kim, Do-Hyung; Jeong, Seong-Nyum; Choi, Seong-Ho

2018-04-01

The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.

Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae.

PubMed

Krajacich, Benjamin J; Meyers, Jacob I; Alout, Haoues; Dabiré, Roch K; Dowell, Floyd E; Foy, Brian D

2017-11-07

Understanding the age-structure of mosquito populations, especially malaria vectors such as Anopheles gambiae, is important for assessing the risk of infectious mosquitoes, and how vector control interventions may impact this risk. The use of near-infrared spectroscopy (NIRS) for age-grading has been demonstrated previously on laboratory and semi-field mosquitoes, but to date has not been utilized on wild-caught mosquitoes whose age is externally validated via parity status or parasite infection stage. In this study, we developed regression and classification models using NIRS on datasets of wild An. gambiae (s.l.) reared from larvae collected from the field in Burkina Faso, and two laboratory strains. We compared the accuracy of these models for predicting the ages of wild-caught mosquitoes that had been scored for their parity status as well as for positivity for Plasmodium sporozoites. Regression models utilizing variable selection increased predictive accuracy over the more common full-spectrum partial least squares (PLS) approach for cross-validation of the datasets, validation, and independent test sets. Models produced from datasets that included the greatest range of mosquito samples (i.e. different sampling locations and times) had the highest predictive accuracy on independent testing sets, though overall accuracy on these samples was low. For classification, we found that intramodel accuracy ranged between 73.5-97.0% for grouping of mosquitoes into "early" and "late" age classes, with the highest prediction accuracy found in laboratory colonized mosquitoes. However, this accuracy was decreased on test sets, with the highest classification of an independent set of wild-caught larvae reared to set ages being 69.6%. Variation in NIRS data, likely from dietary, genetic, and other factors limits the accuracy of this technique with wild-caught mosquitoes. Alternative algorithms may help improve prediction accuracy, but care should be taken to either maximize variety in models or minimize confounders.

Can 3'-Deoxy-3'-((18)F) Fluorothymidine Out Perform 2-Deoxy-2-((18)F) Fluoro-D-Glucose Positron Emission Tomography/Computed Tomography in the Diagnosis of Cervical Lymphadenopathy in Patients With Oral/Head and Neck Cancer?

PubMed

Schaefferkoetter, Joshua D; Carlson, Eric R; Heidel, Robert E

2015-07-01

The present study investigated the performance of cellular metabolism imaging with 2-deoxy-2-((18)F) fluoro-D-glucose (FDG) versus cellular proliferation imaging with 3'-deoxy-3'-((18)F) fluorothymidine (FLT) in the detection of cervical lymph node metastases in oral/head and neck cancer. We conducted a prospective cohort study to assess a head-to-head performance of FLT imaging and clinical FDG imaging for characterizing cervical lymph node metastases in patients with squamous cell carcinoma (SCC) of the oral/head and neck region. The primary predictor variable of the study was the presence of FDG or FLT avidity within the cervical lymph nodes. The primary outcome variable was the histologic presence of metastatic SCC in the cervical lymph nodes. The performance was reported in terms of the sensitivity, specificity, accuracy, and positive and negative predictive values. The overall accuracy for discriminating positive from negative lymph nodes was evaluated as a function of the positron emission tomography (PET) standardized uptake value (SUV). Receiver operating characteristic (ROC) analyses were performed for both tracers. Eleven patients undergoing surgical resection of SCC of the oral/head and neck region underwent preoperative FDG and FLT PET-computed tomography (CT) scans on separate days. The interpretation of the FDG PET-CT imaging resulted in sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of 43.2, 99.5, 94.4, 88.9, and 94.7%, respectively. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for FLT PET-CT imaging was 75.7, 99.2, 97.1, 90.3, and 97.7%, respectively. The areas under the curve for the ROC curves were 0.9 and 0.84 for FDG and FLT, respectively. Poor correlation was observed between the SUV for FDG and FLT within the lymph nodes and tumors. FLT showed better overall performance for detecting lymphadenopathy on qualitative assessment within the total nodal population. This notwithstanding, FDG SUV performed better for pathologic discrimination within the visible lymph nodes. Copyright © 2015 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Accuracy of Two Motor Assessments during the First Year of Life in Preterm Infants for Predicting Motor Outcome at Preschool Age

PubMed Central

Spittle, Alicia J.; Lee, Katherine J.; Spencer-Smith, Megan; Lorefice, Lucy E.; Anderson, Peter J.; Doyle, Lex W.

2015-01-01

Aim The primary aim of this study was to investigate the accuracy of the Alberta Infant Motor Scale (AIMS) and Neuro-Sensory Motor Developmental Assessment (NSMDA) over the first year of life for predicting motor impairment at 4 years in preterm children. The secondary aims were to assess the predictive value of serial assessments over the first year and when using a combination of these two assessment tools in follow-up. Method Children born <30 weeks’ gestation were prospectively recruited and assessed at 4, 8 and 12 months’ corrected age using the AIMS and NSMDA. At 4 years’ corrected age children were assessed for cerebral palsy (CP) and motor impairment using the Movement Assessment Battery for Children 2nd-edition (MABC-2). We calculated accuracy of the AIMS and NSMDA for predicting CP and MABC-2 scores ≤15th (at-risk of motor difficulty) and ≤5th centile (significant motor difficulty) for each test (AIMS and NSMDA) at 4, 8 and 12 months, for delay on one, two or all three of the time points over the first year, and finally for delay on both tests at each time point. Results Accuracy for predicting motor impairment was good for each test at each age, although false positives were common. Motor impairment on the MABC-2 (scores ≤5th and ≤15th) was most accurately predicted by the AIMS at 4 months, whereas CP was most accurately predicted by the NSMDA at 12 months. In regards to serial assessments, the likelihood ratio for motor impairment increased with the number of delayed assessments. When combining both the NSMDA and AIMS the best accuracy was achieved at 4 months, although results were similar at 8 and 12 months. Interpretation Motor development during the first year of life in preterm infants assessed with the AIMS and NSMDA is predictive of later motor impairment at preschool age. However, false positives are common and therefore it is beneficial to follow-up children at high risk of motor impairment at more than one time point, or to use a combination of assessment tools. Trial Registration ACTR.org.au ACTRN12606000252516 PMID:25970619

Position Information Encoded by Population Activity in Hierarchical Visual Areas

PubMed Central

Majima, Kei; Horikawa, Tomoyasu

2017-01-01

Abstract Neurons in high-level visual areas respond to more complex visual features with broader receptive fields (RFs) compared to those in low-level visual areas. Thus, high-level visual areas are generally considered to carry less information regarding the position of seen objects in the visual field. However, larger RFs may not imply loss of position information at the population level. Here, we evaluated how accurately the position of a seen object could be predicted (decoded) from activity patterns in each of six representative visual areas with different RF sizes [V1–V4, lateral occipital complex (LOC), and fusiform face area (FFA)]. We collected functional magnetic resonance imaging (fMRI) responses while human subjects viewed a ball randomly moving in a two-dimensional field. To estimate population RF sizes of individual fMRI voxels, RF models were fitted for individual voxels in each brain area. The voxels in higher visual areas showed larger estimated RFs than those in lower visual areas. Then, the ball’s position in a separate session was predicted by maximum likelihood estimation using the RF models of individual voxels. We also tested a model-free multivoxel regression (support vector regression, SVR) to predict the position. We found that regardless of the difference in RF size, all visual areas showed similar prediction accuracies, especially on the horizontal dimension. Higher areas showed slightly lower accuracies on the vertical dimension, which appears to be attributed to the narrower spatial distributions of the RF centers. The results suggest that much position information is preserved in population activity through the hierarchical visual pathway regardless of RF sizes and is potentially available in later processing for recognition and behavior. PMID:28451634

Assessment of Myometrial Invasion in Premenopausal Grade 1 Endometrial Carcinoma: Is Magnetic Resonance Imaging a Reliable Tool in Selecting Patients for Fertility-Preserving Therapy?

PubMed

Sakane, Makoto; Hori, Masatoshi; Onishi, Hiromitsu; Tsuboyama, Takahiro; Ota, Takashi; Tatsumi, Mitsuaki; Ueda, Yutaka; Kimura, Toshihiro; Kimura, Tadashi; Tomiyama, Noriyuki

The aim of this study was to evaluate the diagnostic ability of magnetic resonance imaging (MRI) in premenopausal women with G1 endometrial carcinoma. Twenty-six patients underwent T2W, diffusion weighted, and dynamic contrast-enhanced 3-T MRI. The degree of myometrial invasion was pathologically classified into no invasion, shallow (3 mm or less), and more. Two radiologists assessed myometrial invasion on MRI. Diagnostic accuracy, sensitivity, specificity, positive and negative predictive values, AUC, and interobserver agreement were analyzed. For assessing myometrial invasion, mean accuracy, sensitivity, specificity, positive predictive values, negative predictive values, and AUC, respectively, were as follows: 63%, 42%, 85%, 79%, 47%, and 0.75. Mean interobserver agreement was fair (k = 0.36). Shallow invasions were underestimated as no invasion on MRI in all 6 cases. Magnetic resonance imaging produced false-negative result on half of patients. The misjudgments tended to happen in patients with shallow invasion.

A drift line bias estimator: ARMA-based filter or calibration method, and its application in BDS/GPS-based attitude determination

NASA Astrophysics Data System (ADS)

Liang, Zhang; Yanqing, Hou; Jie, Wu

2016-12-01

The multi-antenna synchronized receiver (using a common clock) is widely applied in GNSS-based attitude determination (AD) or terrain deformations monitoring, and many other applications, since the high-accuracy single-differenced carrier phase can be used to improve the positioning or AD accuracy. Thus, the line bias (LB) parameter (fractional bias isolating) should be calibrated in the single-differenced phase equations. In the past decades, all researchers estimated the LB as a constant parameter in advance and compensated it in real time. However, the constant LB assumption is inappropriate in practical applications because of the physical length and permittivity changes of the cables, caused by the environmental temperature variation and the instability of receiver-self inner circuit transmitting delay. Considering the LB drift (or colored LB) in practical circumstances, this paper initiates a real-time estimator using auto regressive moving average-based (ARMA) prediction/whitening filter model or Moving average-based (MA) constant calibration model. In the ARMA-based filter model, four cases namely AR(1), ARMA(1, 1), AR(2) and ARMA(2, 1) are applied for the LB prediction. The real-time relative positioning model using the ARMA-based predicting LB is derived and it is theoretically proved that the positioning accuracy is better than the traditional double difference carrier phase (DDCP) model. The drifting LB is defined with a phase temperature changing rate integral function, which is a random walk process if the phase temperature changing rate is white noise, and is validated by the analysis of the AR model coefficient. The auto covariance function shows that the LB is indeed varying in time and estimating it as a constant is not safe, which is also demonstrated by the analysis on LB variation of each visible satellite during a zero and short baseline BDS/GPS experiment. Compared to the DDCP approach, in the zero-baseline experiment, the LB constant calibration (LBCC) and MA approaches improved the positioning accuracy of the vertical component, while slightly degrading the accuracy of the horizontal components. The ARMA(1, 0) model, however, improved the positioning accuracy of all three components, with 40 and 50 % improvement of the vertical component for BDS and GPS, respectively. In the short baseline experiment, compared to the DDCP approach, the LBCC approach yielded bad positioning solutions and degraded the AD accuracy; both MA and ARMA-based filter approaches improved the AD accuracy. Moreover, the ARMA(1, 0) and ARMA(1, 1) models have relatively better performance, improving to 55 % and 48 % the elevation angle in ARMA(1, 1) and MA model for GPS, respectively. Furthermore, the drifting LB variation is found to be continuous and slowly cumulative; the variation magnitudes in the unit of length are almost identical on different frequency carrier phases, so the LB variation does not show obvious correlation between different frequencies. Consequently, the wide-lane LB in the unit of cycle is very stable, while the narrow-lane LB varies largely in time. This reasoning probably also explains the phenomenon that the wide-lane LB originating in the satellites is stable, while the narrow-lane LB varies. The results of ARMA-based filters are better than the MA model, which probably implies that the modeling for drifting LB can further improve the precise point positioning accuracy.

Assessment of CTAS ETA prediction capabilities

NASA Astrophysics Data System (ADS)

Bolender, Michael A.

1994-11-01

This report summarizes the work done to date in assessing the trajectory fidelity and estimated time of arrival (ETA) prediction capability of the NASA Ames Center TRACON Automation System (CTAS) software. The CTAS software suite is a series of computer programs designed to aid air traffic controllers in their tasks of safely scheduling the landing sequence of approaching aircraft. in particular, this report concerns the accuracy of the available measurements (e.g., position, altitude, etc.) that are input to the software, as well as the accuracy of the final data that is made available to the air traffic controllers.

Prognostic significance of electrical alternans versus signal averaged electrocardiography in predicting the outcome of electrophysiological testing and arrhythmia-free survival

NASA Technical Reports Server (NTRS)

Armoundas, A. A.; Rosenbaum, D. S.; Ruskin, J. N.; Garan, H.; Cohen, R. J.

1998-01-01

OBJECTIVE: To investigate the accuracy of signal averaged electrocardiography (SAECG) and measurement of microvolt level T wave alternans as predictors of susceptibility to ventricular arrhythmias. DESIGN: Analysis of new data from a previously published prospective investigation. SETTING: Electrophysiology laboratory of a major referral hospital. PATIENTS AND INTERVENTIONS: 43 patients, not on class I or class III antiarrhythmic drug treatment, undergoing invasive electrophysiological testing had SAECG and T wave alternans measurements. The SAECG was considered positive in the presence of one (SAECG-I) or two (SAECG-II) of three standard criteria. T wave alternans was considered positive if the alternans ratio exceeded 3.0. MAIN OUTCOME MEASURES: Inducibility of sustained ventricular tachycardia or fibrillation during electrophysiological testing, and 20 month arrhythmia-free survival. RESULTS: The accuracy of T wave alternans in predicting the outcome of electrophysiological testing was 84% (p < 0.0001). Neither SAECG-I (accuracy 60%; p < 0.29) nor SAECG-II (accuracy 71%; p < 0.10) was a statistically significant predictor of electrophysiological testing. SAECG, T wave alternans, electrophysiological testing, and follow up data were available in 36 patients while not on class I or III antiarrhythmic agents. The accuracy of T wave alternans in predicting the outcome of arrhythmia-free survival was 86% (p < 0.030). Neither SAECG-I (accuracy 65%; p < 0.21) nor SAECG-II (accuracy 71%; p < 0.48) was a statistically significant predictor of arrhythmia-free survival. CONCLUSIONS: T wave alternans was a highly significant predictor of the outcome of electrophysiological testing and arrhythmia-free survival, while SAECG was not a statistically significant predictor. Although these results need to be confirmed in prospective clinical studies, they suggest that T wave alternans may serve as a non-invasive probe for screening high risk populations for malignant ventricular arrhythmias.

The accuracy with which adults who do not stutter predict stuttering-related communication attitudes.

PubMed

Logan, Kenneth J; Willis, Julie R

2011-12-01

The purpose of this study was to examine the extent to which adults who do not stutter can predict communication-related attitudes of adults who do stutter. 40 participants (mean age of 22.5 years) evaluated speech samples from an adult with mild stuttering and an adult with severe stuttering via audio-only (n=20) or audio-visual (n=20) modes to predict how the adults had responded on the S24 scale of communication attitudes. Participants correctly predicted which speaker had the more favorable S24 score, and the predicted scores were significantly different between the severity conditions. Across the four subgroups, predicted S24 scores differed from actual scores by 4-9 points. Predicted values were greater than the actual values for 3 of 4 subgroups, but still relatively positive in relation to the S24 norm sample. Stimulus presentation mode interacted with stuttering severity to affect prediction accuracy. The participants predicted the speakers' negative self-attributions more accurately than their positive self-attributions. Findings suggest that adults who do not stutter estimate the communication-related attitudes of specific adults who stutter in a manner that is generally accurate, though, in some conditions, somewhat less favorable than the speaker's actual ratings. At a group level, adults who do not stutter demonstrate the ability to discern minimal versus average levels of attitudinal impact for speakers who stutter. The participants' complex prediction patterns are discussed in relation to stereotype accuracy and classic views of negative stereotyping. The reader will be able to (a) summarize main findings on research related to listeners' attitudes toward people who stutter, (b) describe the extent to which people who do not stutter can predict the communication attitudes of people who do stutter; and (c) discuss how findings from the present study relate to previous findings on stereotypes about people who stutter. Copyright © 2011 Elsevier Inc. All rights reserved.

Psychosis prediction in secondary mental health services. A broad, comprehensive approach to the "at risk mental state" syndrome.

PubMed

Francesconi, M; Minichino, A; Carrión, R E; Delle Chiaie, R; Bevilacqua, A; Parisi, M; Rullo, S; Bersani, F Saverio; Biondi, M; Cadenhead, K

2017-02-01

Accuracy of risk algorithms for psychosis prediction in "at risk mental state" (ARMS) samples may differ according to the recruitment setting. Standardized criteria used to detect ARMS individuals may lack specificity if the recruitment setting is a secondary mental health service. The authors tested a modified strategy to predict psychosis conversion in this setting by using a systematic selection of trait-markers of the psychosis prodrome in a sample with a heterogeneous ARMS status. 138 non-psychotic outpatients (aged 17-31) were consecutively recruited in secondary mental health services and followed-up for up to 3 years (mean follow-up time, 2.2 years; SD=0.9). Baseline ARMS status, clinical, demographic, cognitive, and neurological soft signs measures were collected. Cox regression was used to derive a risk index. 48% individuals met ARMS criteria (ARMS-Positive, ARMS+). Conversion rate to psychosis was 21% for the overall sample, 34% for ARMS+, and 9% for ARMS-Negative (ARMS-). The final predictor model with a positive predictive validity of 80% consisted of four variables: Disorder of Thought Content, visuospatial/constructional deficits, sensory-integration, and theory-of-mind abnormalities. Removing Disorder of Thought Content from the model only slightly modified the predictive accuracy (-6.2%), but increased the sensitivity (+9.5%). These results suggest that in a secondary mental health setting the use of trait-markers of the psychosis prodrome may predict psychosis conversion with great accuracy despite the heterogeneity of the ARMS status. The use of the proposed predictive algorithm may enable a selective recruitment, potentially reducing duration of untreated psychosis and improving prognostic outcomes. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

CURB-65 Performance Among Admitted and Discharged Emergency Department Patients With Community-acquired Pneumonia.

PubMed

Sharp, Adam L; Jones, Jason P; Wu, Ivan; Huynh, Dan; Kocher, Keith E; Shah, Nirav R; Gould, Michael K

2016-04-01

Pneumonia severity tools were primarily developed in cohorts of hospitalized patients, limiting their applicability to the emergency department (ED). We describe current community ED admission practices and examine the accuracy of the CURB-65 to predict 30-day mortality for patients, either discharged or admitted with community-acquired pneumonia (CAP). A retrospective, observational study of adult CAP encounters in 14 community EDs within an integrated healthcare system. We calculated CURB-65 scores for all encounters and described the use of hospitalization, stratified by each score (0-5). We then used each score as a cutoff to calculate sensitivity, specificity, positive predictive value, negative predictive value (NPV), positive likelihood ratios, and negative likelihood ratios for predicting 30-day mortality. The sample included 21,183 ED encounters for CAP (7,952 discharged and 13,231 admitted). The C-statistic describing the accuracy of CURB-65 for predicting 30-day mortality in the full sample was 0.761 (95% confidence interval [CI], 0.747-0.774). The C-statistic was 0.864 (95% CI, 0.821-0.906) among patients discharged from the ED compared with 0.689 (95% CI, 0.672-0.705) among patients who were admitted. Among all ED encounters a CURB-65 threshold of ≥1 was 92.8% sensitive and 38.0% specific for predicting mortality, with a 99.9% NPV. Among all encounters, 62.5% were admitted, including 36.2% of those at lowest risk (CURB-65 = 0). CURB-65 had very good accuracy for predicting 30-day mortality among patients discharged from the ED. This severity tool may help ED providers risk stratify patients to assist with disposition decisions and identify unwarranted variation in patient care. © 2016 by the Society for Academic Emergency Medicine.

Predictive value of painful popping for a posterior root tear of the medial meniscus in middle-aged to older Asian patients.

PubMed

Bae, Ji-Hoon; Paik, Nak Hwan; Park, Gyu-Won; Yoon, Jung-Ro; Chae, Dong-Ju; Kwon, Jae Ho; Kim, Jong In; Nha, Kyung-Wook

2013-03-01

The purpose of this study was to determine the accuracy, sensitivity, specificity, and predictive values of a single event of painful popping in the presence of a posterior root tear of the medial meniscus in middle-aged to older Asian patients. We conducted a retrospective review of medical records of 936 patients who underwent arthroscopic surgeries for an isolated medial meniscus tear between January 2000 and December 2010. There were 332 men and 604 women with a mean age of 41 years (range, 25 to 66 years). The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of a painful popping sensation for a posterior root tear of the medial meniscus were calculated. Arthroscopy confirmed the presence of posterior root tears of the medial menisci in 237 of 936 patients (25.3%). A single event of a painful popping sensation was present in 86 of these 936 patients (9.1%). Of these 86 patients with a painful popping sensation, 83 (96.5%) were categorized as having an isolated posterior root tear of the medial meniscus. The positive predictive value of a painful popping sensation in identifying a posterior root tear of the medial meniscus was 96.5%, the negative predictive value was 81.8%, the sensitivity was 35.0%, the specificity was 99.5%, and the diagnostic accuracy was 77.9%. A single event of painful popping can be a highly predictive clinical sign of a posterior root tear of the medial meniscus in the middle-aged to older Asian population. However, it has low sensitivity for the detection of a posterior root tear of the medial meniscus. Level IV, therapeutic case series. Copyright © 2013 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Do positive schizotypal symptoms predict false perceptual experiences in nonclinical populations?

PubMed

Tsakanikos, Elias; Reed, Phil

2005-12-01

We examined whether positive schizotypy (i.e., reports of hallucinatory and delusional-like experiences) in nonclinical participants could predict false perceptual experiences during detection of fast-moving words beyond a possible response bias. The participants (N = 160) were assigned to one of two conditions: they were asked either to make presence/absence judgments (loose criterion) or to read aloud every detected word (strict criterion). Regression analysis showed that high levels of positive schizotypy predicted false alarms in the loose condition and false perceptions of words in the strict condition. The obtained effects were independent of detection accuracy, task order, impulsivity, and social desirability. We discuss the results in the context of information processing biases linked to the positive symptomatology of schizophrenia. Clinical and theoretical implications are also considered.

Preschool children's vision screening in New Zealand: a retrospective evaluation of referral accuracy

PubMed Central

Langeslag-Smith, Miriam A; Vandal, Alain C; Briane, Vincent; Thompson, Benjamin; Anstice, Nicola S

2015-01-01

Objectives To assess the accuracy of preschool vision screening in a large, ethnically diverse, urban population in South Auckland, New Zealand. Design Retrospective longitudinal study. Methods B4 School Check vision screening records (n=5572) were compared with hospital eye department data for children referred from screening due to impaired acuity in one or both eyes who attended a referral appointment (n=556). False positive screens were identified by comparing screening data from the eyes that failed screening with hospital data. Estimation of false negative screening rates relied on data from eyes that passed screening. Data were analysed using logistic regression modelling accounting for the high correlation between results for the two eyes of each child. Primary outcome measure Positive predictive value of the preschool vision screening programme. Results Screening produced high numbers of false positive referrals, resulting in poor positive predictive value (PPV=31%, 95% CI 26% to 38%). High estimated negative predictive value (NPV=92%, 95% CI 88% to 95%) suggested most children with a vision disorder were identified at screening. Relaxing the referral criteria for acuity from worse than 6/9 to worse than 6/12 improved PPV without adversely affecting NPV. Conclusions The B4 School Check generated numerous false positive referrals and consequently had a low PPV. There is scope for reducing costs by altering the visual acuity criterion for referral. PMID:26614622

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction

PubMed Central

Spencer, Matt; Eickholt, Jesse; Cheng, Jianlin

2014-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80% and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test data set of 198 proteins, achieving a Q3 accuracy of 80.7% and a Sov accuracy of 74.2%. PMID:25750595

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

PubMed

Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

2015-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

Adaptive Trajectory Prediction Algorithm for Climbing Flights

NASA Technical Reports Server (NTRS)

Schultz, Charles Alexander; Thipphavong, David P.; Erzberger, Heinz

2012-01-01

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.

Diagnostic accuracy of magnetic resonance imaging, transvaginal, and transrectal ultrasonography in deep infiltrating endometriosis

PubMed Central

Alborzi, Saeed; Rasekhi, Alireza; Shomali, Zahra; Madadi, Gooya; Alborzi, Mahshid; Kazemi, Mahboobeh; Hosseini Nohandani, Azam

2018-01-01

Abstract To determine the diagnostic accuracy of pelvic magnetic resonance imaging (MRI), transvaginal sonography (TVS), and transrectal sonography (TRS) in diagnosis of deep infiltrating endometriosis (DIE). This diagnostic accuracy study was conducted during a 2-year period including a total number of 317 patients with signs and symptoms of endometriosis. All the patients were evaluated by pelvic MRI, TVS, and TRS in the same center. The criterion standard was considered to be the laparoscopy and histopathologic examination. Of 317 patients being included in the present study, 252 tested positive for DIE. The sensitivity, specificity, positive predictive value, and negative predictive value of TVS was found to be 83.3%, 46.1%, 85.7%, and 41.6%, respectively. These variables were 80.5%, 18.6%, 79.3%, and 19.7% for TRS and 90.4%, 66.1%, 91.2%, and 64.1% for MRI, respectively. MRI had the highest accuracy (85.4%) when compared to TVS (75.7%) and TRS (67.8%). The sensitivity of TRS, TVS, and MRI in uterosacral ligament DIE was 82.8%, 70.9%, and 63.6%, respectively. On the contrary, specificity had a reverse trend, favoring MRI (93.9%, 92.8%, and 89.8% for TVS and TRS, respectively). The results of the present study demonstrated that TVS and TRS have appropriate diagnostic accuracy in diagnosis of DIE comparable to MRI. PMID:29465552

[MicroRNA Target Prediction Based on Support Vector Machine Ensemble Classification Algorithm of Under-sampling Technique].

PubMed

Chen, Zhiru; Hong, Wenxue

2016-02-01

Considering the low accuracy of prediction in the positive samples and poor overall classification effects caused by unbalanced sample data of MicroRNA (miRNA) target, we proposes a support vector machine (SVM)-integration of under-sampling and weight (IUSM) algorithm in this paper, an under-sampling based on the ensemble learning algorithm. The algorithm adopts SVM as learning algorithm and AdaBoost as integration framework, and embeds clustering-based under-sampling into the iterative process, aiming at reducing the degree of unbalanced distribution of positive and negative samples. Meanwhile, in the process of adaptive weight adjustment of the samples, the SVM-IUSM algorithm eliminates the abnormal ones in negative samples with robust sample weights smoothing mechanism so as to avoid over-learning. Finally, the prediction of miRNA target integrated classifier is achieved with the combination of multiple weak classifiers through the voting mechanism. The experiment revealed that the SVM-IUSW, compared with other algorithms on unbalanced dataset collection, could not only improve the accuracy of positive targets and the overall effect of classification, but also enhance the generalization ability of miRNA target classifier.

Office hysteroscopic-guided selective tubal chromopertubation: acceptability, feasibility and diagnostic accuracy of this new diagnostic non-invasive technique in infertile women.

PubMed

Carta, Gaspare; Palermo, Patrizia; Pasquale, Chiara; Conte, Valeria; Pulcinella, Ruggero; Necozione, Stefano; Cofini, Vincenza; Patacchiola, Felice

2018-06-01

The aim of this study was to evaluate accuracy, tolerability and side effects of office hysteroscopic-guided chromoperturbations in infertile women without anaesthesia. Forty-nine infertile women underwent the procedure to evaluate tubal patency and the uterine cavity. Women with unilateral or bilateral tubal stenosis at hysteroscopy with chromoperturbation, and women with bilateral tubal patency who did not conceive during the period of six months, underwent laparoscopy with chromoperturbation. The results obtained from hysteroscopy and laparoscopy in the assessment of tubal patency were compared. Sensitivity, specificity, accuracy, positive-predictive value and negative-predictive value were used to describe diagnostic performance. Pain and tolerance were assessed during procedure using a visual analogue scale (VAS). Side effects or late complications and pregnancy rate were also recorded three and six months after the procedure. The specificity was 87.8% (95% CI: 73.80-95.90), sensitivity was 85.7% (95% CI 57.20-98.20), positive and negative predictive values were 70.6% (95% CI: 44.00-89) and 94.7% (95% CI: 82.30-99.40), respectively. Pregnancy rate (PR) within six months after performance of hysteroscopy with chromoperturbation was 27%. Office hysteroscopy-guided selective chromoperturbation in infertile patients is a valid technique to evaluate tubal patency and uterine cavity.

The relevance of ultrasound imaging of suspicious axillary lymph nodes and fine-needle aspiration biopsy in the post ACOSOG Z11 era in early breast cancer

PubMed Central

Vijayaraghavan, Gopal R.; Vedantham, Srinivasan; Kataoka, Milliam; DeBenedectis, Carolynn; Quinlan, Robert

2016-01-01

Rationale and Objective Evaluation of nodal involvement in early-stage breast cancers (T1 or T2) changed following the Z11 trial; however, not all patients meet the Z11 inclusion criteria. Hence, the relevance of ultrasound imaging of the axilla and fine-needle aspiration biopsy (FNA) in early-stage breast cancers was investigated. Materials and Methods In this single-center, retrospective study, 758 subjects had pathology-verified breast cancer diagnosis over a 3-year period, of which 128 subjects with T1/T2 breast tumors had abnormal axillary lymph nodes on ultrasound, had FNA, and proceeded to axillary surgery. Ultrasound images were reviewed and analyzed using multivariable logistic regression to identify the features predictive of positive FNA. Accuracy of FNA was quantified as the area under the receiver operating characteristic curve with axillary surgery as reference standard. Results Of 128 subjects, 61 and 65 were positive on FNA and axillary surgery, respectively. Sensitivity, specificity, positive- and negative-predictive values of FNA were 52/65 (80%), 54/63 (85.7%), 52/61(85.2%) and 54/67 (80.5%), respectively. After adjusting for neoadjuvant chemotherapy between FNA and surgery, a positive FNA was associated with higher likelihood for positive axillary surgery (odds ratio: 22.7; 95% CI: 7.2–71.3, p<0.0001), and the accuracy of FNA was 0.801 (95% CI: 0.727–0.876). Among ultrasound imaging features, cortical thickness and abnormal hilum were predictive (p<0.017) of positive FNA with accuracy of 0.817 (95% CI: 0.741–0.893). Conclusion Ultrasound imaging and FNA can play an important role in the management of early breast cancers even in the post-Z11 era. Higher weightage can be accorded to cortical thickness and hilum during ultrasound evaluation. PMID:27916595

Effect of obesity on preterm delivery prediction by transabdominal recording of uterine electromyography.

PubMed

Lucovnik, Miha; Chambliss, Linda R; Blumrick, Richard; Balducci, James; Gersak, Ksenija; Garfield, Robert E

2016-10-01

It has been shown that noninvasive uterine electromyography (EMG) can identify true preterm labor more accurately than methods available to clinicians today. The objective of this study was to evaluate the effect of body mass index (BMI) on the accuracy of uterine EMG in predicting preterm delivery. Predictive values of uterine EMG for preterm delivery were compared in obese versus overweight/normal BMI patients. Hanley-McNeil test was used to compare receiver operator characteristics curves in these groups. Previously reported EMG cutoffs were used to determine groups with false positive/false negative and true positive/true negative EMG results. BMI in these groups was compared with Student t test (p < 0.05 significant). A total of 88 patients were included: 20 obese, 64 overweight, and four with normal BMI. EMG predicted preterm delivery within 7 days with area under the curve = 0.95 in the normal/overweight group, and with area under the curve = 1.00 in the obese group (p = 0.08). Six patients in true preterm labor (delivering within 7 days from EMG measurement) had low EMG values (false negative group). There were no false positive results. No significant differences in patient's BMI were noted between false negative group patients and preterm labor patients with high EMG values (true positive group) and nonlabor patients with low EMG values (true negative group; p = 0.32). Accuracy of noninvasive uterine EMG monitoring and its predictive value for preterm delivery are not affected by obesity. Copyright © 2016. Published by Elsevier B.V.

The Accuracy of Urinalysis in Predicting Intra-Abdominal Injury Following Blunt Traumas.

PubMed

Sabzghabaei, Anita; Shojaee, Majid; Safari, Saeed; Hatamabadi, Hamid Reza; Shirvani, Reza

2016-01-01

In cases of blunt abdominal traumas, predicting the possible intra-abdominal injuries is still a challenge for the physicians involved with these patients. Therefore, this study was designed, to evaluate the accuracy of urinalysis in predicting intra-abdominal injuries. Patients aged 15 to 65 years with blunt abdominal trauma who were admitted to emergency departments were enrolled. Abdominopelvic computed tomography (CT) scan with intravenous contrast and urinalysis were requested for all the included patients. Demographic data, trauma mechanism, the results of urinalysis, and the results of abdominopelvic CT scan were gathered. Finally, the correlation between the results of abdominopelvic CT scan, and urinalysis was determined. Urinalysis was considered positive in case of at least one positive value in gross appearance, blood in dipstick, or red blood cell count. 325 patients with blunt abdominal trauma were admitted to the emergency departments (83% male with the mean age of 32.63±17.48 years). Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios of urinalysis, were 77.9% (95% CI: 69.6-84.4), 58.5% (95% CI: 51.2-65.5), 56% (95% CI: 48.5-63.3), 79.6% (95% CI: 71.8-85.7), 1.27% (95% CI: 1.30-1.57), and 0.25% (95% CI: 0.18-0.36), respectively. The diagnostic value of urinalysis in prediction of blunt traumatic intra-abdominal injuries is low and it seems that it should be considered as an adjuvant diagnostic tool, in conjunction with other sources such as clinical findings and imaging.

Accuracy of ultrasonography in the detection of severe hepatic lipidosis in cats.

PubMed

Yeager, A E; Mohammed, H

1992-04-01

The accuracy of ultrasonography in detection of feline hepatic lipidosis was studied retrospectively. The following ultrasonographic criteria were associated positively with severe hepatic lipidosis: the liver hyperechoic, compared with falciform fat; the liver isoechoic or hyperechoic, compared with omental fat; poor visualization of intrahepatic vessel borders; and increased attenuation of sound by the liver. In a group of 36 cats with clinically apparent hepatobiliary disease and in which liver biopsy was done, liver hyperechoic, compared with falciform fat, was the best criterion for diagnosis of severe hepatic lipidosis with 91% sensitivity, 100% specificity, and 100% positive predictive value.

Navigating highly elliptical earth orbiters with simultaneous VLBI from orthogonal baseline pairs

NASA Technical Reports Server (NTRS)

Frauenholz, Raymond B.

1986-01-01

Navigation strategies for determining highly elliptical orbits with VLBI are described. The predicted performance of wideband VLBI and Delta VLBI measurements obtained by orthogonal baseline pairs are compared for a 16-hr equatorial orbit. It is observed that the one-sigma apogee position accuracy improves two orders of magnitude to the meter level when Delta VLBI measurements are added to coherent Doppler and range, and the simpler VLBI strategy provides nearly the same orbit accuracy. The effects of differential measurement noise and acquisition geometry on orbit accuracy are investigated. The data reveal that quasar position uncertainty limits the accuracy of wideband Delta VLBI measurements, and that polar motion and baseline uncertainties and offsets between station clocks affect the wideband VLBI data. It is noted that differential one-way range (DOR) has performance nearly equal to that of the more complex Delta DOR and is recommended for use on spacecraft in high elliptical orbits.

Comparison between presepsin and procalcitonin in early diagnosis of neonatal sepsis.

PubMed

Iskandar, Agustin; Arthamin, Maimun Z; Indriana, Kristin; Anshory, Muhammad; Hur, Mina; Di Somma, Salvatore

2018-05-09

Neonatal sepsis remains worldwide one of the leading causes of morbidity and mortality in both term and preterm infants. Lower mortality rates are related to timely diagnostic evaluation and prompt initiation of empiric antibiotic therapy. Blood culture, as gold standard examination for sepsis, has several limitations for early diagnosis, so that sepsis biomarkers could play an important role in this regard. This study was aimed to compare the value of the two biomarkers presepsin and procalcitonin in early diagnosis of neonatal sepsis. This was a prospective cross-sectional study performed, in Saiful Anwar General Hospital Malang, Indonesia, in 51 neonates that fulfill the criteria of systemic inflammatory response syndrome (SIRS) with blood culture as diagnostic gold standard for sepsis. At reviewer operating characteristic (ROC) curve analyses, using a presepsin cutoff of 706,5 pg/mL, the obtained area under the curve (AUCs) were: sensitivity = 85.7%, specificity = 68.8%, positive predictive value = 85.7%, negative predictive value = 68.8%, positive likelihood ratio = 2.75, negative likelihood ratio = 0.21, and accuracy = 80.4%. On the other hand, with a procalcitonin cutoff value of 161.33 pg/mL the obtained AUCs showed: sensitivity = 68.6%, specificity = 62.5%, positive predictive value = 80%, negative predictive value = 47.6%, positive likelihood ratio = 1.83, the odds ratio negative = 0.5, and accuracy = 66.7%. In early diagnosis of neonatal sepsis, compared with procalcitonin, presepsin seems to provide better early diagnostic value with consequent possible faster therapeutical decision making and possible positive impact on outcome of neonates.

RBind: computational network method to predict RNA binding sites.

PubMed

Wang, Kaili; Jian, Yiren; Wang, Huiwen; Zeng, Chen; Zhao, Yunjie

2018-04-26

Non-coding RNA molecules play essential roles by interacting with other molecules to perform various biological functions. However, it is difficult to determine RNA structures due to their flexibility. At present, the number of experimentally solved RNA-ligand and RNA-protein structures is still insufficient. Therefore, binding sites prediction of non-coding RNA is required to understand their functions. Current RNA binding site prediction algorithms produce many false positive nucleotides that are distance away from the binding sites. Here, we present a network approach, RBind, to predict the RNA binding sites. We benchmarked RBind in RNA-ligand and RNA-protein datasets. The average accuracy of 0.82 in RNA-ligand and 0.63 in RNA-protein testing showed that this network strategy has a reliable accuracy for binding sites prediction. The codes and datasets are available at https://zhaolab.com.cn/RBind. yjzhaowh@mail.ccnu.edu.cn. Supplementary data are available at Bioinformatics online.

Model Predictions and Observed Performance of JWST's Cryogenic Position Metrology System

NASA Technical Reports Server (NTRS)

Lunt, Sharon R.; Rhodes, David; DiAntonio, Andrew; Boland, John; Wells, Conrad; Gigliotti, Trevis; Johanning, Gary

2016-01-01

The James Webb Space Telescope cryogenic testing requires measurement systems that both obtain a very high degree of accuracy and can function in that environment. Close-range photogrammetry was identified as meeting those criteria. Testing the capability of a close-range photogrammetric system prior to its existence is a challenging problem. Computer simulation was chosen over building a scaled mock-up to allow for increased flexibility in testing various configurations. Extensive validation work was done to ensure that the actual as-built system meet accuracy and repeatability requirements. The simulated image data predicted the uncertainty in measurement to be within specification and this prediction was borne out experimentally. Uncertainty at all levels was verified experimentally to be less than 0.1 millimeters.

Sequencing of bimaxillary surgery in the correction of vertical maxillary excess: retrospective study.

PubMed

Salmen, F S; de Oliveira, T F M; Gabrielli, M A C; Pereira Filho, V A; Real Gabrielli, M F

2018-06-01

The aim of this study was to evaluate the precision of bimaxillary surgery performed to correct vertical maxillary excess, when the procedure is sequenced with mandibular surgery first or maxillary surgery first. Thirty-two patients, divided into two groups, were included in this retrospective study. Group 1 comprised patients who received bimaxillary surgery following the classical sequence with repositioning of the maxilla first. Patients in group 2 received bimaxillary surgery, but the mandible was operated on first. The precision of the maxillomandibular repositioning was determined by comparison of the digital prediction and postoperative tracings superimposed on the cranial base. The data were tabulated and analyzed statistically. In this sample, both surgical sequences provided adequate clinical accuracy. The classical sequence, repositioning the maxilla first, resulted in greater accuracy for A-point and the upper incisor edge vertical position. Repositioning the mandible first allowed greater precision in the vertical position of pogonion. In conclusion, although both surgical sequences may be used, repositioning the mandible first will result in greater imprecision in relation to the predictive tracing than repositioning the maxilla first. The classical sequence resulted in greater accuracy in the vertical position of the maxilla, which is key for aesthetics. Copyright © 2017 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Sensitivity and specificity of a CAD solution for lung nodule detection on chest radiograph with CTA correlation.

PubMed

Moore, William; Ripton-Snyder, Jennifer; Wu, George; Hendler, Craig

2011-06-01

The objective of this research was to determine the sensitivity and specificity of a commercially available computer-aided detection (CAD) system for detection of lung nodule on posterior-anterior (PA) chest radiograph in a varied patient population who are referred to computed tomographic angiogram (CTA) of the chest as a reference standard. Patients who had a PA chest radiograph with concomitant CTA of the chest were included in this retrospective study. The PA chest radiograph was analyzed by a CAD device, and results were recorded. A qualitative assessment of the CAD results was performed using a 5-point Likert scale. The CTA was then reviewed to determine if there were correlative nodules. The presence of a correlative nodule between 0.5 cm and 1.5 cm was considered a positive result. The baseline sensitivity of the system was determined to be 0.707 (95% CI = 0.52-0.86), with a specificity of 0.50 (95% CI = 0.38-0.76). Positive predictive value was 0.30 (95% CI = 0.24-0.49), with a negative predictive value of 0.858 (95% CI = 0.82-0.95), and accuracy of 0.555 (95% CI = 0.40-0.66). When excluding nodules that were qualitatively determined by a thoracic radiologist to be false positives, the specificity was 0.781 (95% CI = 0.764-0.839), the positive predictive value was 0.564 (95% CI = 0.491-0.654), the negative predictive value was 0.829 (95% CI = 0.819-0.878), and the accuracy was 0.737 (95% CI = 0.721-0.801). The use of CAD for lung nodule detection on chest radiograph, when used in conjunction with an experienced radiologist, has a very good sensitivity, specificity, and accuracy.

Mallampati test as a predictor of laryngoscopic view.

PubMed

Adamus, Milan; Fritscherova, Sarka; Hrabalek, Lumir; Gabrhelik, Tomas; Zapletalova, Jana; Janout, Vladimir

2010-12-01

To determine the accuracy of the modified Mallampati test for predicting difficult tracheal intubation. A cross-sectional, clinical, observational, non-blinded study. A quality analysis of anesthetic care. Operating theatres and department of anesthesiology in a university hospital. Following the local ethics committee approval and patients' informed consent to anesthesia, all adult patients (> 18 yrs) presenting for any type of non-emergency surgical procedures under general anesthesia requiring endotracheal intubation were enrolled. Prior to anesthesia, Samsoon and Young's modification of the Mallampati test (modified Mallampati test) was performed. Following induction, the anesthesiologist described the laryngoscopic view using the Cormack-Lehane scale. Classes 3 or 4 of the modified Mallampati test were considered a predictor of difficult intubation. Grades 3 or 4 of the Cormack-Lehane classification of the laryngoscopic view were defined as impaired glottic exposure. The sensitivity, specificity, positive and negative predictive value, relative risk, likelihood ratio and accuracy of the modified Mallampati test were calculated on 2x2 contingency tables. Of the total 1,518 patients enrolled, 48 had difficult intubation (3.2%). We failed to detect as many as 35.4% patients in whom glottis exposure during direct laryngoscopy was inadequate (sensitivity 0.646). Compared to the original article by Mallampati, we found lower specificity (0.824 vs. 0.995), lower positive predictive value (0.107 vs. 0.933), higher negative predictive value (0.986 vs. 0.928), lower likelihood ratio (3.68 vs. 91.0) and accuracy (0.819 vs. 0.929). When used as a single examination, the modified Mallampati test is of limited value in predicting difficult intubation.

First-line sonographic diagnosis of pneumothorax in major trauma: accuracy of e-FAST and comparison with multidetector computed tomography.

PubMed

Ianniello, Stefania; Di Giacomo, Vincenza; Sessa, Barbara; Miele, Vittorio

2014-09-01

Combined clinical examination and supine chest radiography have shown low accuracy in the assessment of pneumothorax in unstable patients with major chest trauma during the primary survey in the emergency room. The aim of our study was to evaluate the diagnostic accuracy of extended-focused assessment with sonography in trauma (e-FAST), in the diagnosis of pneumothorax, compared with the results of multidetector computed tomography (MDCT) and of invasive interventions (thoracostomy tube placement). This was a retrospective case series involving 368 consecutive unstable adult patients (273 men and 95 women; average age, 25 years; range, 16-68 years) admitted to our hospital's emergency department between January 2011 and December 2012 for major trauma (Injury Severity Score ≥ 15). We evaluated the accuracy of thoracic ultrasound in the detection of pneumothorax compared with the results of MDCT and invasive interventions (thoracostomy tube placement). Institutional review board approval was obtained prior to commencement of this study. Among the 736 lung fields included in the study, 87 pneumothoraces were detected with thoracic CT scans (23.6%). e-FAST detected 67/87 and missed 20 pneumothoraces (17 mild, 3 moderate). The diagnostic performance of ultrasound was: sensitivity 77% (74% in 2011 and 80% in 2012), specificity 99.8%, positive predictive value 98.5%, negative predictive value 97%, accuracy 97.2% (67 true positive; 668 true negative; 1 false positive; 20 false negative); 17 missed mild pneumothoraces were not immediately life-threatening (thickness less than 5 mm). Thoracic ultrasound (e-FAST) is a rapid and accurate first-line, bedside diagnostic modality for the diagnosis of pneumothorax in unstable patients with major chest trauma during the primary survey in the emergency room.

GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application

PubMed Central

Cheng, Qi; Xue, Dabin; Wang, Guanyu; Ochieng, Washington Yotto

2017-01-01

The increasing number of vehicles in modern cities brings the problem of increasing crashes. One of the applications or services of Intelligent Transportation Systems (ITS) conceived to improve safety and reduce congestion is collision avoidance. This safety critical application requires sub-meter level vehicle state estimation accuracy with very high integrity, continuity and availability, to detect an impending collision and issue a warning or intervene in the case that the warning is not heeded. Because of the challenging city environment, to date there is no approved method capable of delivering this high level of performance in vehicle state estimation. In particular, the current Global Navigation Satellite System (GNSS) based collision avoidance systems have the major limitation that the real-time accuracy of dynamic state estimation deteriorates during abrupt acceleration and deceleration situations, compromising the integrity of collision avoidance. Therefore, to provide the Required Navigation Performance (RNP) for collision avoidance, this paper proposes a novel Particle Filter (PF) based model for the integration or fusion of real-time kinematic (RTK) GNSS position solutions with electronic compass and road segment data used in conjunction with an Autoregressive (AR) motion model. The real-time vehicle state estimates are used together with distance based collision avoidance algorithms to predict potential collisions. The algorithms are tested by simulation and in the field representing a low density urban environment. The results show that the proposed algorithm meets the horizontal positioning accuracy requirement for collision avoidance and is superior to positioning accuracy of GNSS only, traditional Constant Velocity (CV) and Constant Acceleration (CA) based motion models, with a significant improvement in the prediction accuracy of potential collision. PMID:29186851

GNSS/Electronic Compass/Road Segment Information Fusion for Vehicle-to-Vehicle Collision Avoidance Application.

PubMed

Sun, Rui; Cheng, Qi; Xue, Dabin; Wang, Guanyu; Ochieng, Washington Yotto

2017-11-25

The increasing number of vehicles in modern cities brings the problem of increasing crashes. One of the applications or services of Intelligent Transportation Systems (ITS) conceived to improve safety and reduce congestion is collision avoidance. This safety critical application requires sub-meter level vehicle state estimation accuracy with very high integrity, continuity and availability, to detect an impending collision and issue a warning or intervene in the case that the warning is not heeded. Because of the challenging city environment, to date there is no approved method capable of delivering this high level of performance in vehicle state estimation. In particular, the current Global Navigation Satellite System (GNSS) based collision avoidance systems have the major limitation that the real-time accuracy of dynamic state estimation deteriorates during abrupt acceleration and deceleration situations, compromising the integrity of collision avoidance. Therefore, to provide the Required Navigation Performance (RNP) for collision avoidance, this paper proposes a novel Particle Filter (PF) based model for the integration or fusion of real-time kinematic (RTK) GNSS position solutions with electronic compass and road segment data used in conjunction with an Autoregressive (AR) motion model. The real-time vehicle state estimates are used together with distance based collision avoidance algorithms to predict potential collisions. The algorithms are tested by simulation and in the field representing a low density urban environment. The results show that the proposed algorithm meets the horizontal positioning accuracy requirement for collision avoidance and is superior to positioning accuracy of GNSS only, traditional Constant Velocity (CV) and Constant Acceleration (CA) based motion models, with a significant improvement in the prediction accuracy of potential collision.

A new self-report inventory of dyslexia for students: criterion and construct validity.

PubMed

Tamboer, Peter; Vorst, Harrie C M

2015-02-01

The validity of a Dutch self-report inventory of dyslexia was ascertained in two samples of students. Six biographical questions, 20 general language statements and 56 specific language statements were based on dyslexia as a multi-dimensional deficit. Dyslexia and non-dyslexia were assessed with two criteria: identification with test results (Sample 1) and classification using biographical information (both samples). Using discriminant analyses, these criteria were predicted with various groups of statements. All together, 11 discriminant functions were used to estimate classification accuracy of the inventory. In Sample 1, 15 statements predicted the test criterion with classification accuracy of 98%, and 18 statements predicted the biographical criterion with classification accuracy of 97%. In Sample 2, 16 statements predicted the biographical criterion with classification accuracy of 94%. Estimations of positive and negative predictive value were 89% and 99%. Items of various discriminant functions were factor analysed to find characteristic difficulties of students with dyslexia, resulting in a five-factor structure in Sample 1 and a four-factor structure in Sample 2. Answer bias was investigated with measures of internal consistency reliability. Less than 20 self-report items are sufficient to accurately classify students with and without dyslexia. This supports the usefulness of self-assessment of dyslexia as a valid alternative to diagnostic test batteries. Copyright © 2015 John Wiley & Sons, Ltd.

Lung Ultrasound for Diagnosing Pneumothorax in the Critically Ill Neonate.

PubMed

Raimondi, Francesco; Rodriguez Fanjul, Javier; Aversa, Salvatore; Chirico, Gaetano; Yousef, Nadya; De Luca, Daniele; Corsini, Iuri; Dani, Carlo; Grappone, Lidia; Orfeo, Luigi; Migliaro, Fiorella; Vallone, Gianfranco; Capasso, Letizia

2016-08-01

To evaluate the accuracy of lung ultrasound for the diagnosis of pneumothorax in the sudden decompensating patient. In an international, prospective study, sudden decompensation was defined as a prolonged significant desaturation (oxygen saturation <65% for more than 40 seconds) and bradycardia or sudden increase of oxygen requirement by at least 50% in less than 10 minutes with a final fraction of inspired oxygen ≥0.7 to keep stable saturations. All eligible patients had an ultrasound scan before undergoing a chest radiograph, which was the reference standard. Forty-two infants (birth weight = 1531 ± 812 g; gestational age = 31 ± 3.5 weeks) were enrolled in 6 centers; pneumothorax was detected in 26 (62%). Lung ultrasound accuracy in diagnosing pneumothorax was as follows: sensitivity 100%, specificity 100%, positive predictive value 100%, and negative predictive value 100%. Clinical evaluation of pneumothorax showed sensitivity 84%, specificity 56%, positive predictive value 76%, and negative predictive value 69%. After sudden decompensation, a lung ultrasound scan was performed in an average time of 5.3 ± 5.6 minutes vs 19 ± 11.7 minutes required for a chest radiography. Emergency drainage was performed after an ultrasound scan but before radiography in 9 cases. Lung ultrasound shows high accuracy in detecting pneumothorax in the critical infant, outperforming clinical evaluation and reducing time to imaging diagnosis and drainage. Copyright © 2016 Elsevier Inc. All rights reserved.

Group Sequential Testing of the Predictive Accuracy of a Continuous Biomarker with Unknown Prevalence

PubMed Central

Koopmeiners, Joseph S.; Feng, Ziding

2015-01-01

Group sequential testing procedures have been proposed as an approach to conserving resources in biomarker validation studies. Previously, Koopmeiners and Feng (2011) derived the asymptotic properties of the sequential empirical positive predictive value (PPV) and negative predictive value curves, which summarize the predictive accuracy of a continuous marker, under case-control sampling. A limitation of their approach is that the prevalence can not be estimated from a case-control study and must be assumed known. In this manuscript, we consider group sequential testing of the predictive accuracy of a continuous biomarker with unknown prevalence. First, we develop asymptotic theory for the sequential empirical PPV and NPV curves when the prevalence must be estimated, rather than assumed known in a case-control study. We then discuss how our results can be combined with standard group sequential methods to develop group sequential testing procedures and bias-adjusted estimators for the PPV and NPV curve. The small sample properties of the proposed group sequential testing procedures and estimators are evaluated by simulation and we illustrate our approach in the context of a study to validate a novel biomarker for prostate cancer. PMID:26537180

Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study.

PubMed

Infante, Fernando; Espada Vaquero, Mercedes; Bignardi, Tommaso; Lu, Chuan; Testa, Antonia C; Fauchon, David; Epstein, Elisabeth; Leone, Francesco P G; Van den Bosch, Thierry; Martins, Wellington P; Condous, George

2018-06-01

To assess interobserver reproducibility in detecting tubal ectopic pregnancies by reading data sets from 3-dimensional (3D) transvaginal ultrasonography (TVUS) and comparing it with real-time 2-dimensional (2D) TVUS. Images were initially classified as showing pregnancies of unknown location or tubal ectopic pregnancies on real time 2D TVUS by an experienced sonologist, who acquired 5 3D volumes. Data sets were analyzed offline by 5 observers who had to classify each case as ectopic pregnancy or pregnancy of unknown location. The interobserver reproducibility was evaluated by the Fleiss κ statistic. The performance of each observer in predicting ectopic pregnancies was compared to that of the experienced sonologist. Women were followed until they were reclassified as follows: (1) failed pregnancy of unknown location; (2) intrauterine pregnancy; (3) ectopic pregnancy; or (4) persistent pregnancy of unknown location. Sixty-one women were included. The agreement between reading offline 3D data sets and the first real-time 2D TVUS was very good (80%-82%; κ = 0.89). The overall interobserver agreement among observers reading offline 3D data sets was moderate (κ = 0.52). The diagnostic performance of experienced observers reading offline 3D data sets had accuracy of 78.3% to 85.0%, sensitivity of 66.7% to 81.3%, specificity of 79.5% to 88.4%, positive predictive value of 57.1% to 72.2%, and negative predictive value of 87.5% to 91.3%, compared to the experienced sonologist's real-time 2D TVUS: accuracy of 94.5%, sensitivity of 94.4%, specificity of 94.5%, positive predictive value of 85.0%, and negative predictive value of 98.1%. The diagnostic accuracy of 3D TVUS by reading offline data sets for predicting ectopic pregnancies is dependent on experience. Reading only static 3D data sets without clinical information does not match the diagnostic performance of real time 2D TVUS combined with clinical information obtained during the scan. © 2017 by the American Institute of Ultrasound in Medicine.

Does low dose (13)C-urea breath test maintain a satisfactory accuracy in diagnosing Helicobacter pylori infection?

PubMed

Coelho, Luiz Gonzaga Vaz; Silva, Arilto Eleutério da; Coelho, Maria Clara de Freitas; Penna, Francisco Guilherme Cancela e; Ferreira, Rafael Otto Antunes; Santa-Cecilia, Elisa Viana

2011-01-01

The standard doses of (13)C-urea in (13)C-urea breath test is 75 mg. To assess the diagnostic accuracy of (13)C-urea breath test containing 25 mg of (13)C-urea comparing with the standard doses of 75 mg in the diagnosis of Helicobacter pylori infection. Two hundred seventy adult patients (96 males, 174 females, median age 41 years) performed the standard (13)C-urea breath test (75 mg (13)C-urea) and repeated the (13)C-urea breath test using only 25 mg of (13)C-urea within a 2 week interval. The test was performed using an infrared isotope analyzer. Patients were considered positive if delta over baseline was >4.0‰ at the gold standard test. One hundred sixty-one (59.6%) patients were H. pylori negative and 109 (40.4%) were positive by the gold standard test. Using receiver operating characteristic analysis we established a cut-off value of 3.4% as the best value of 25 mg (13)C-urea breath test to discriminate positive and negative patients, considering the H. pylori prevalence (95% CI: 23.9-37.3) at our setting. Therefore, we obtained to 25 mg (13)C-urea breath test a diagnostic accuracy of 92.9% (95% CI: 88.1-97.9), sensitivity 83.5% (95% CI: 75.4-89.3), specificity 99.4% (95% CI: 96.6-99.9), positive predictive value 98.3% (95% CI: 92.4-99.4), and negative predictive value 93.0% (95% CI: 88.6-96.1). Low-dose (13)C-urea breath test (25 mg (13)C-urea) does not reach accuracy sufficient to be recommended in clinical setting where a 30% prevalence of H. pylori infection is observed. Further studies should be done to determine the diagnostic accuracy of low doses of (13)C-urea in the urea breath test.

On the accuracy and reliability of predictions by control-system theory.

PubMed

Bourbon, W T; Copeland, K E; Dyer, V R; Harman, W K; Mosley, B L

1990-12-01

In three experiments we used control-system theory (CST) to predict the results of tracking tasks on which people held a handle to keep a cursor even with a target on a computer screen. 10 people completed a total of 104 replications of the task. In each experiment, there were two conditions: in one, only the handle affected the position of the cursor; in the other, a random disturbance also affected the cursor. From a person's performance during Condition 1, we derived constants used in the CST model to predict the results of Condition 2. In two experiments, predictions occurred a few minutes before Condition 2; in one experiment, the delay was 1 yr. During a 1-min. experimental run, the positions of handle and cursor, produced by the person, were each sampled 1800 times, once every 1/30 sec. During a modeling run, the model predicted the positions of the handle and target for each of the 1800 intervals sampled in the experimental run. In 104 replications, the mean correlation between predicted and actual positions of the handle was .996; SD = .002.

Validation of automatic wheeze detection in patients with obstructed airways and in healthy subjects.

PubMed

Guntupalli, Kalpalatha K; Alapat, Philip M; Bandi, Venkata D; Kushnir, Igal

2008-12-01

Computerized lung-sound analysis is a sensitive and quantitative method to identify wheezing by its typical pattern on spectral analysis. We evaluated the accuracy of the VRI, a multi-sensor, computer-based device with an automated technique of wheeze detection. The method was validated in 100 sound files from seven subjects with asthma or chronic obstructive pulmonary disease and seven healthy subjects by comparison of auscultation findings, examination of audio files, and computer detection of wheezes. Three blinded physicians identified 40 sound files with wheezes and 60 sound files without wheezes. Sensitivity and specificity were 83% and 85%, respectively. Negative predictive value and positive predictive value were 89% and 79%, respectively. Overall inter-rater agreement was 84%. False positive cases were found to contain sounds that simulate wheezes, such as background noises with high frequencies or strong noises from the throat that could be heard and identified without a stethoscope. The present findings demonstrate that the wheeze detection algorithm has good accuracy, sensitivity, specificity, negative predictive value and positive predictive value for wheeze detection in regional analyses with a single sensor and multiple sensors. Results are similar to those reported in the literature. The device is user-friendly, requires minimal patient effort, and, distinct from other devices, it provides a dynamic image of breath sound distribution with wheeze detection output in less than 1 minute.

Accuracy of tracheal aspirate gram stain in predicting Staphylococcus aureus infection in ventilator-associated pneumonia.

PubMed

Seligman, Renato; Seligman, Beatriz Graeff Santos; Konkewicz, Loriane; Dos Santos, Rodrigo Pires

2015-01-01

The Gram stain can be used to direct initial empiric antimicrobial therapy when complete culture is not available. This rapid test could prevent the initiation of inappropriate therapy and adverse outcomes. However, several studies have attempted to determine the value of the Gram stain in the diagnosis and therapy of bacterial infection in different populations of patients with ventilator-associated pneumonia (VAP) with conflicting results. The objective of this study is to evaluate the accuracy of the Gram stain in predicting the existence of Staphylococcus aureus infections from cultures of patients suspected of having VAP. This prospective single-center open cohort study enrolled 399 patients from December 2005 to December 2010. Patients suspected of having VAP by ATS IDSA criteria were included. Respiratory secretion samples were collected by tracheal aspirate (TA) for standard bacterioscopic analysis by Gram stain and culture. Respiratory secretion samples collected by tracheal aspirates of 392 patients were analyzed by Gram stain and culture. When Gram-positive cocci were arranged in clusters, the sensitivity was 68.4%, specificity 97.8%, positive predictive value 88.1% and negative predictive value 92.8% for predicting the presence of Staphylococcus aureus in culture (p < 0.001). A tracheal aspirate Gram stain can be used to rule out the presence of Staphylococcus aureus in patients with a clinical diagnosis of VAP with a 92.8% Negative Predictive Value. Therefore, 7.2% of patients with Staphylococcus aureus would not be protected by an empiric treatment that limits antimicrobial coverage to Staphylococcus aureus only when Gram positive cocci in clusters are identified.

Evaluation of in silico tools to predict the skin sensitization potential of chemicals.

PubMed

Verheyen, G R; Braeken, E; Van Deun, K; Van Miert, S

2017-01-01

Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra - LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.

Tissue Transglutaminase Levels Are Not Sufficient to Diagnose Celiac Disease in North American Practices Without Intestinal Biopsies.

PubMed

Elitsur, Yoram; Sigman, Terry; Watkins, Runa; Porto, Anthony F; Leonard Puppa, Elaine L; Foglio, Elsie J; Preston, Deborah L

2017-01-01

Celiac serology is crucial for the diagnosis of celiac disease in children. The American guideline for celiac disease in children suggested that positive serology should be followed by confirmatory intestinal histology. The relationship between high tissue transglutaminase titers and celiac disease in children has not been well investigated in children from North America. In the present study, we investigated whether different tissue transglutaminase titers in symptomatic children could predict celiac disease without the confirmation of intestinal histology. Data from biopsy confirmed celiac children were collected from four different clinics in North America. Clinical, serological, histological, and follow-up data were collected. The accuracy rates of various tissue transglutaminase titers to predict celiac disease in children were calculated. The data from 240 children were calculated. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy rate of tissue transglutaminase titers at ≥10× upper limit of normal were 75.4, 48.8, 87.7, 29.0, and 70.8 %, respectively. Similar data were noted in the other tissue transglutaminase titers (≥3× upper limit of normal, >100 U/ml, or >100 U/ml and >10× upper limit of normal). The positive predictive value of tissue transglutaminase titers at ≥3× upper limit of normal or higher was too low to predict celiac disease in children. Our data suggested that in routine clinical practice, high titers of tissue transglutaminase are not sufficient to diagnose celiac disease in North American children without intestinal biopsies.

Positive Illusions? The Accuracy of Academic Self-Appraisals in Adolescents With ADHD.

PubMed

Chan, Todd; Martinussen, Rhonda

2016-08-01

Children with attention deficit/hyperactivity disorder (ADHD) overestimate their academic competencies (AC) relative to performance and informant indicators (i.e., positive illusory bias; PIB). Do adolescents with ADHD exhibit this PIB and does it render self-views inaccurate? We examined the magnitude of the AC-PIB in adolescents with and without ADHD, the predictive accuracy of parent and adolescent AC ratings, and whether executive functions (EF) predict the AC-PIB. Adolescents (49 ADHD; 47 typically developing) completed math and EF tests, and self-rated their AC. Parents rated their adolescents' AC and EF. Adolescents with ADHD performed more poorly on the math task (vs. comparison group) but had a larger AC-PIB relative to parents' ratings. EFs predicted the PIB within the full sample. Adolescents' AC ratings, regardless of ADHD status, were more predictive of math performance than their parents' AC ratings. Adolescents with ADHD appear self-aware in their AC despite a modest PIB; nuanced self-appraisals may depend on EFs. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Accuracy of clinical diagnosis and malaria rapid diagnostic test and its influence on the management of children with fever under reduced malaria burden in Misungwi district, Mwanza Tanzania.

PubMed

Nkonya, Daniel Ndaki; Tarimo, Donath Samuel; Kishimba, Rogath Saika

2016-01-01

Malaria diagnosis is known to be non-specific because of the overlap of symptoms of malaria with other infectious diseases that is made worse with declining malaria burden. Though the use of malaria rapid diagnostic test (mRDT) for malaria confirmation has universally been adopted, malaria decline may alter performance of mRDT. This study examined accuracy of clinical diagnosis and mRDT and its influence on prescription for febrile underfives. A cross-sectional study of 600 underfives was carried out in 6 randomly selected health facilities in Misungwi district, Mwanza; from November - December 2014. Consecutive underfives with a fever consultation were recruited: for each fever and the clinical diagnosis entertained were recorded. Parasitological confirmation of malaria was done by mRDT and microscopic examination of finger prick blood samples. Treatment was based on mRDT results, drugs prescribed recorded. Accuracy of clinical diagnosis and mRDT in predicting malaria was assessed by performance indices against microscopy. Antimalarial and antibiotics prescriptions were assessed against parasitological findings. Clinically, 37.2% had malaria; 32.8% were mRDTpositive and 17.0% microscopically positive. Sensitivity of clinical diagnosis was very high (97.0% [95%CI: 91.0-99.2]); specificity 66.7% [95%CI: 62.3-70.8], and positive predictive value 37.4% (95%CI: 31.6-43.5). Sensitivity of mRDTwas very high (99.0% [95%CI: 93.9-99.9]), specificity (80.7% [95%CI: 76.9-84.0]), positive predictive value 51.3% [95% CI: 44.1-58.4]) and negative predictive 99.75% [95%CI: 99.4-100.0]. Those receiving antimalarial prescription, 75.0% were mRDT positive; 39.4% microscopically positive. Those receiving antibiotic, 78.8% were mRDT negative; 90.1% microscopically negative. Decline in malaria lowered specificity of mRDT to < 95% against WHO recommendation. Though adherence to mRDT results was high, there was over prescription of antibiotics.

Accuracy of clinical diagnosis and malaria rapid diagnostic test and its influence on the management of children with fever under reduced malaria burden in Misungwi district, Mwanza Tanzania

PubMed Central

Nkonya, Daniel Ndaki; Tarimo, Donath Samuel; Kishimba, Rogath Saika

2016-01-01

Introduction Malaria diagnosis is known to be non-specific because of the overlap of symptoms of malaria with other infectious diseases that is made worse with declining malaria burden. Though the use of malaria rapid diagnostic test (mRDT) for malaria confirmation has universally been adopted, malaria decline may alter performance of mRDT. This study examined accuracy of clinical diagnosis and mRDT and its influence on prescription for febrile underfives. Methods A cross-sectional study of 600 underfives was carried out in 6 randomly selected health facilities in Misungwi district, Mwanza; from November - December 2014. Consecutive underfives with a fever consultation were recruited: for each fever and the clinical diagnosis entertained were recorded. Parasitological confirmation of malaria was done by mRDT and microscopic examination of finger prick blood samples. Treatment was based on mRDT results, drugs prescribed recorded. Accuracy of clinical diagnosis and mRDT in predicting malaria was assessed by performance indices against microscopy. Antimalarial and antibiotics prescriptions were assessed against parasitological findings. Results Clinically, 37.2% had malaria; 32.8% were mRDTpositive and 17.0% microscopically positive. Sensitivity of clinical diagnosis was very high (97.0% [95%CI: 91.0-99.2]); specificity 66.7% [95%CI: 62.3-70.8], and positive predictive value 37.4% (95%CI: 31.6-43.5). Sensitivity of mRDTwas very high (99.0% [95%CI: 93.9-99.9]), specificity (80.7% [95%CI: 76.9-84.0]), positive predictive value 51.3% [95% CI: 44.1-58.4]) and negative predictive 99.75% [95%CI: 99.4-100.0]. Those receiving antimalarial prescription, 75.0% were mRDT positive; 39.4% microscopically positive. Those receiving antibiotic, 78.8% were mRDT negative; 90.1% microscopically negative. Conclusion Decline in malaria lowered specificity of mRDT to < 95% against WHO recommendation. Though adherence to mRDT results was high, there was over prescription of antibiotics. PMID:28250872

Sensitivity, Specificity, Predictive Values, and Accuracy of Three Diagnostic Tests to Predict Inferior Alveolar Nerve Blockade Failure in Symptomatic Irreversible Pulpitis

PubMed Central

Rodríguez-Wong, Laura; Noguera-González, Danny; Esparza-Villalpando, Vicente; Montero-Aguilar, Mauricio

2017-01-01

Introduction The inferior alveolar nerve block (IANB) is the most common anesthetic technique used on mandibular teeth during root canal treatment. Its success in the presence of preoperative inflammation is still controversial. The aim of this study was to evaluate the sensitivity, specificity, predictive values, and accuracy of three diagnostic tests used to predict IANB failure in symptomatic irreversible pulpitis (SIP). Methodology A cross-sectional study was carried out on the mandibular molars of 53 patients with SIP. All patients received a single cartridge of mepivacaine 2% with 1 : 100000 epinephrine using the IANB technique. Three diagnostic clinical tests were performed to detect anesthetic failure. Anesthetic failure was defined as a positive painful response to any of the three tests. Sensitivity, specificity, predictive values, accuracy, and ROC curves were calculated and compared and significant differences were analyzed. Results IANB failure was determined in 71.7% of the patients. The sensitivity scores for the three tests (lip numbness, the cold stimuli test, and responsiveness during endodontic access) were 0.03, 0.35, and 0.55, respectively, and the specificity score was determined as 1 for all of the tests. Clinically, none of the evaluated tests demonstrated a high enough accuracy (0.30, 0.53, and 0.68 for lip numbness, the cold stimuli test, and responsiveness during endodontic access, resp.). A comparison of the areas under the curve in the ROC analyses showed statistically significant differences between the three tests (p < 0.05). Conclusion None of the analyzed tests demonstrated a high enough accuracy to be considered a reliable diagnostic tool for the prediction of anesthetic failure. PMID:28694714

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials.

PubMed

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A; Burgueño, Juan; Bandeira E Sousa, Massaine; Crossa, José

2018-03-28

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines ([Formula: see text]) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. Copyright © 2018 Cuevas et al.

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

PubMed Central

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

Computed tomography detection of extracapsular spread of squamous cell carcinoma of the head and neck in metastatic cervical lymph nodes.

PubMed

Carlton, Joshua A; Maxwell, Adam W; Bauer, Lyndsey B; McElroy, Sara M; Layfield, Lester J; Ahsan, Humera; Agarwal, Ajay

2017-06-01

Background and purpose In patients with squamous cell carcinoma of the head and neck (HNSCC), extracapsular spread (ECS) of metastases in cervical lymph nodes affects prognosis and therapy. We assessed the accuracy of intravenous contrast-enhanced computed tomography (CT) and the utility of imaging criteria for preoperative detection of ECS in metastatic cervical lymph nodes in patients with HNSCC. Materials and methods Preoperative intravenous contrast-enhanced neck CT images of 93 patients with histopathological HNSCC metastatic nodes were retrospectively assessed by two neuroradiologists for ECS status and ECS imaging criteria. Radiological assessments were compared with histopathological assessments of neck dissection specimens, and interobserver agreement of ECS status and ECS imaging criteria were measured. Results Sensitivity, specificity, positive predictive value, and accuracy for overall ECS assessment were 57%, 81%, 82% and 67% for observer 1, and 66%, 76%, 80% and 70% for observer 2, respectively. Correlating three or more ECS imaging criteria with histopathological ECS increased specificity and positive predictive value, but decreased sensitivity and accuracy. Interobserver agreement for overall ECS assessment demonstrated a kappa of 0.59. Central necrosis had the highest kappa of 0.74. Conclusion CT has moderate specificity for ECS assessment in HNSCC metastatic cervical nodes. Identifying three or more ECS imaging criteria raises specificity and positive predictive value, therefore preoperative identification of multiple criteria may be clinically useful. Interobserver agreement is moderate for overall ECS assessment, substantial for central necrosis. Other ECS CT criteria had moderate agreement at best and therefore should not be used individually as criteria for detecting ECS by CT.

Focused abdominal sonography for trauma (FAST) in blunt paediatric abdominal trauma.

PubMed

Faruque, Ahmad Vaqas; Qazi, Saqib Hamid; Khan, Muhammad Arif Mateen; Akhtar, Wassem; Majeed, Amina

2013-03-01

To evaluate the role of focussed abdominal sonography for trauma in blunt paediatric abdominal trauma patients, and to see if the role of computed tomography scan could be limited to only those cases in which sonography was positive. The retrospective study covered 10 years, from January 1,2000 to December 31,2009, and was conducted at the Department of Radiology and Department of Emergency Medicine, Aga Khan University Hospital, Karachi. It comprised cases of 174 children from birth to 14 years who had presented with blunt abdominal trauma and had focussed abdominal sonography for trauma done at the hospital. The findings were correlated with computed tomography scan of the abdomen and clinical follow-up. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of focussed abdominal sonography for trauma were calculated for blunt abdominal trauma. SPSS 17 was used for statistical analysis. Of the total 174 cases, 31 (17.81%) were later confirmed by abdominal scan. Of these 31 children, sonography had been positive in 29 (93.54%) children. In 21 (67.74%) of the 31 children, sonograpy had been true positive; 8 (25%) (8/31) were false positive; and 2 (6%) (2/31) were false negative. There were 6 (19.3%) children in which sonography was positive and converted to laparotomy. There was no significant difference on account of gender (p>0.356). Focussed abdominal sonography for trauma in the study had sensitivity of 91%, specificity of 95%, positive predictive value of 73%, and negative predictive value of 73% with accuracy of 94%. All patients who had negative sonography were discharged later, and had no complication on clinical follow-up. Focussed abdominal sonography for trauma is a fairly reliable mode to assess blunt abdominal trauma in children. It is a useful tool to pick high-grade solid and hollow viscous injury. The results suggest that the role of computed tomography scan can be limited to those cases in which focussed sonography is positive.

Prediction of protein long-range contacts using an ensemble of genetic algorithm classifiers with sequence profile centers.

PubMed

Chen, Peng; Li, Jinyan

2010-05-17

Prediction of long-range inter-residue contacts is an important topic in bioinformatics research. It is helpful for determining protein structures, understanding protein foldings, and therefore advancing the annotation of protein functions. In this paper, we propose a novel ensemble of genetic algorithm classifiers (GaCs) to address the long-range contact prediction problem. Our method is based on the key idea called sequence profile centers (SPCs). Each SPC is the average sequence profiles of residue pairs belonging to the same contact class or non-contact class. GaCs train on multiple but different pairs of long-range contact data (positive data) and long-range non-contact data (negative data). The negative data sets, having roughly the same sizes as the positive ones, are constructed by random sampling over the original imbalanced negative data. As a result, about 21.5% long-range contacts are correctly predicted. We also found that the ensemble of GaCs indeed makes an accuracy improvement by around 5.6% over the single GaC. Classifiers with the use of sequence profile centers may advance the long-range contact prediction. In line with this approach, key structural features in proteins would be determined with high efficiency and accuracy.

Preschool children's vision screening in New Zealand: a retrospective evaluation of referral accuracy.

PubMed

Langeslag-Smith, Miriam A; Vandal, Alain C; Briane, Vincent; Thompson, Benjamin; Anstice, Nicola S

2015-11-27

To assess the accuracy of preschool vision screening in a large, ethnically diverse, urban population in South Auckland, New Zealand. Retrospective longitudinal study. B4 School Check vision screening records (n=5572) were compared with hospital eye department data for children referred from screening due to impaired acuity in one or both eyes who attended a referral appointment (n=556). False positive screens were identified by comparing screening data from the eyes that failed screening with hospital data. Estimation of false negative screening rates relied on data from eyes that passed screening. Data were analysed using logistic regression modelling accounting for the high correlation between results for the two eyes of each child. Positive predictive value of the preschool vision screening programme. Screening produced high numbers of false positive referrals, resulting in poor positive predictive value (PPV=31%, 95% CI 26% to 38%). High estimated negative predictive value (NPV=92%, 95% CI 88% to 95%) suggested most children with a vision disorder were identified at screening. Relaxing the referral criteria for acuity from worse than 6/9 to worse than 6/12 improved PPV without adversely affecting NPV. The B4 School Check generated numerous false positive referrals and consequently had a low PPV. There is scope for reducing costs by altering the visual acuity criterion for referral. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

SU-F-E-19: A Novel Method for TrueBeam Jaw Calibration

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

Corns, R; Zhao, Y; Huang, V

2016-06-15

Purpose: A simple jaw calibration method is proposed for Varian TrueBeam using an EPID-Encoder combination that gives accurate fields sizes and a homogeneous junction dose. This benefits clinical applications such as mono-isocentric half-beam block breast cancer or head and neck cancer treatment with junction/field matching. Methods: We use EPID imager with pixel size 0.392 mm × 0.392 mm to determine the radiation jaw position as measured from radio-opaque markers aligned with the crosshair. We acquire two images with different symmetric field sizes and record each individual jaw encoder values. A linear relationship between each jaw’s position and its encoder valuemore » is established, from which we predict the encoder values that produce the jaw positions required by TrueBeam’s calibration procedure. During TrueBeam’s jaw calibration procedure, we move the jaw with the pendant to set the jaw into position using the predicted encoder value. The overall accuracy is under 0.1 mm. Results: Our in-house software analyses images and provides sub-pixel accuracy to determine field centre and radiation edges (50% dose of the profile). We verified the TrueBeam encoder provides a reliable linear relationship for each individual jaw position (R{sup 2}>0.9999) from which the encoder values necessary to set jaw calibration points (1 cm and 19 cm) are predicted. Junction matching dose inhomogeneities were improved from >±20% to <±6% using this new calibration protocol. However, one technical challenge exists for junction matching, if the collimator walkout is large. Conclusion: Our new TrueBeam jaw calibration method can systematically calibrate the jaws to crosshair within sub-pixel accuracy and provides both good junction doses and field sizes. This method does not compensate for a larger collimator walkout, but can be used as the underlying foundation for addressing the walkout issue.« less

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas.

PubMed

Morota, Gota

2017-12-20

Deterministic formulas for the accuracy of genomic predictions highlight the relationships among prediction accuracy and potential factors influencing prediction accuracy prior to performing computationally intensive cross-validation. Visualizing such deterministic formulas in an interactive manner may lead to a better understanding of how genetic factors control prediction accuracy. The software to simulate deterministic formulas for genomic prediction accuracy was implemented in R and encapsulated as a web-based Shiny application. Shiny genomic prediction accuracy simulator (ShinyGPAS) simulates various deterministic formulas and delivers dynamic scatter plots of prediction accuracy versus genetic factors impacting prediction accuracy, while requiring only mouse navigation in a web browser. ShinyGPAS is available at: https://chikudaisei.shinyapps.io/shinygpas/ . ShinyGPAS is a shiny-based interactive genomic prediction accuracy simulator using deterministic formulas. It can be used for interactively exploring potential factors that influence prediction accuracy in genome-enabled prediction, simulating achievable prediction accuracy prior to genotyping individuals, or supporting in-class teaching. ShinyGPAS is open source software and it is hosted online as a freely available web-based resource with an intuitive graphical user interface.

KFC2: a knowledge-based hot spot prediction method based on interface solvation, atomic density, and plasticity features.

PubMed

Zhu, Xiaolei; Mitchell, Julie C

2011-09-01

Hot spots constitute a small fraction of protein-protein interface residues, yet they account for a large fraction of the binding affinity. Based on our previous method (KFC), we present two new methods (KFC2a and KFC2b) that outperform other methods at hot spot prediction. A number of improvements were made in developing these new methods. First, we created a training data set that contained a similar number of hot spot and non-hot spot residues. In addition, we generated 47 different features, and different numbers of features were used to train the models to avoid over-fitting. Finally, two feature combinations were selected: One (used in KFC2a) is composed of eight features that are mainly related to solvent accessible surface area and local plasticity; the other (KFC2b) is composed of seven features, only two of which are identical to those used in KFC2a. The two models were built using support vector machines (SVM). The two KFC2 models were then tested on a mixed independent test set, and compared with other methods such as Robetta, FOLDEF, HotPoint, MINERVA, and KFC. KFC2a showed the highest predictive accuracy for hot spot residues (True Positive Rate: TPR = 0.85); however, the false positive rate was somewhat higher than for other models. KFC2b showed the best predictive accuracy for hot spot residues (True Positive Rate: TPR = 0.62) among all methods other than KFC2a, and the False Positive Rate (FPR = 0.15) was comparable with other highly predictive methods. Copyright © 2011 Wiley-Liss, Inc.

A predictive index of axillary nodal involvement in operable breast cancer.

PubMed Central

De Laurentiis, M.; Gallo, C.; De Placido, S.; Perrone, F.; Pettinato, G.; Petrella, G.; Carlomagno, C.; Panico, L.; Delrio, P.; Bianco, A. R.

1996-01-01

We investigated the association between pathological characteristics of primary breast cancer and degree of axillary nodal involvement and obtained a predictive index of the latter from the former. In 2076 cases, 17 histological features, including primary tumour and local invasion variables, were recorded. The whole sample was randomly split in a training (75% of cases) and a test sample. Simple and multiple correspondence analysis were used to select the variables to enter in a multinomial logit model to build an index predictive of the degree of nodal involvement. The response variable was axillary nodal status coded in four classes (N0, N1-3, N4-9, N > or = 10). The predictive index was then evaluated by testing goodness-of-fit and classification accuracy. Covariates significantly associated with nodal status were tumour size (P < 0.0001), tumour type (P < 0.0001), type of border (P = 0.048), multicentricity (P = 0.003), invasion of lymphatic and blood vessels (P < 0.0001) and nipple invasion (P = 0.006). Goodness-of-fit was validated by high concordance between observed and expected number of cases in each decile of predicted probability in both training and test samples. Classification accuracy analysis showed that true node-positive cases were well recognised (84.5%), but there was no clear distinction among the classes of node-positive cases. However, 10 year survival analysis showed a superimposible prognostic behaviour between predicted and observed nodal classes. Moreover, misclassified node-negative patients (i.e. those who are predicted positive) showed an outcome closer to patients with 1-3 metastatic nodes than to node-negative ones. In conclusion, the index cannot completely substitute for axillary node information, but it is a predictor of prognosis as accurate as nodal involvement and identifies a subgroup of node-negative patients with unfavourable prognosis. PMID:8630286

Impaired gas exchange: accuracy of defining characteristics in children with acute respiratory infection1

PubMed Central

Pascoal, Lívia Maia; Lopes, Marcos Venícios de Oliveira; Chaves, Daniel Bruno Resende; Beltrão, Beatriz Amorim; da Silva, Viviane Martins; Monteiro, Flávia Paula Magalhães

2015-01-01

OBJECTIVE: to analyze the accuracy of the defining characteristics of the Impaired gas exchange nursing diagnosis in children with acute respiratory infection. METHOD: open prospective cohort study conducted with 136 children monitored for a consecutive period of at least six days and not more than ten days. An instrument based on the defining characteristics of the Impaired gas exchange diagnosis and on literature addressing pulmonary assessment was used to collect data. The accuracy means of all the defining characteristics under study were computed. RESULTS: the Impaired gas exchange diagnosis was present in 42.6% of the children in the first assessment. Hypoxemia was the characteristic that presented the best measures of accuracy. Abnormal breathing presented high sensitivity, while restlessness, cyanosis, and abnormal skin color showed high specificity. All the characteristics presented negative predictive values of 70% and cyanosis stood out by its high positive predictive value. CONCLUSION: hypoxemia was the defining characteristic that presented the best predictive ability to determine Impaired gas exchange. Studies of this nature enable nurses to minimize variability in clinical situations presented by the patient and to identify more precisely the nursing diagnosis that represents the patient's true clinical condition. PMID:26155010

Evaluation of pretransplant immunologic status in kidney-transplant recipients by panel reactive antibody and soluble CD30 determinations.

PubMed

Cinti, Paola; Pretagostini, Renzo; Arpino, Alessia; Tamburro, Maria Luisa; Mengasini, Sonia; Lattanzi, Roberto; De Simone, Paolo; Berloco, Pasquale; Molajoni, Elvira Renna

2005-05-15

To retrospectively compare the accuracy of pretransplant panel of reactivity antibodies (PRA) and serum level of soluble CD30 (sCD30) in predicting early (<6 months) acute rejection (AR) in living-donor and deceased-donor kidney-transplant (KT) patients. Pretransplant sera of 24 KT recipients were retrospectively tested for sCD30 and compared with PRA. Inclusion criteria were de novo graft patients on calcineurin-inhibitor-based immunosuppression, minimum follow-up of 1 year, alive with a functioning graft, and stable renal function over the last 12 months. Objective measures were incidence of biopsy-proven AR (BPAR) within 6 months of KT and sCD30 and PRA diagnostic indexes. The relative risk (RR) of BPAR for each test was also obtained. Fourteen (58.3%) patients presented at least one episode of BPAR within 6 months of KT. All rejection episodes were responsive to steroid treatment. PRA was positive in six (25%) patients, and four (66.7%) of them presented at least one episode of BPAR. sCD30 tested positive in nine (37.5%) patients, and all these later presented at least one episode of BPAR. sCD30 and PRA diagnostic indexes in predicting early (< 6months) BPAR were sensitivity 64.2% versus 28.5%; specificity 100% versus 80%; accuracy 79.1% versus 50%; positive predictive value 100% versus 66.6%; and negative predictive value 66.6% versus 44.4%. The RR of early AR was 1.4 in PRA-positive patients and extremely higher in the sCD30-positive group. Pretransplant sCD30 is a more accurate predictor of AR when compared with PRA. These results support its use in the pretransplant work-up of kidney-graft recipients.

Evaluation of pretransplant immunologic status in kidney-transplant recipients by panel reactive antibody and soluble CD30 determinations.

PubMed

Cinti, Paola; Pretagostini, Renzo; Arpino, Alessia; Tamburro, Maria Luisa; Mengasini, Sonia; Lattanzi, Roberto; De Simone, Paolo; Berloco, Pasquale; Molajoni, Elvira Renna

2005-03-15

To retrospectively compare the accuracy of pretransplant panel of reactivity antibodies (PRA) and serum level of soluble CD30 (sCD30) in predicting early (< 6 months) acute rejection (AR) in living-donor and deceased-donor kidney-transplant (KT) patients. Pretransplant sera of 24 KT recipients were retrospectively tested for sCD30 and compared with PRA. Inclusion criteria were de novo graft patients on calcineurin-inhibitor-based immunosuppression, minimum follow-up of 1 year, alive with a functioning graft, and stable renal function over the last 12 months. Objective measures were incidence of biopsy-proven AR (BPAR) within 6 months of KT and sCD30 and PRA diagnostic indexes. The relative risk (RR) of BPAR for each test was also obtained. Fourteen (58.3%) patients presented at least one episode of BPAR within 6 months of KT. All rejection episodes were responsive to steroid treatment. PRA was positive in six (25%) patients, and four (66.7%) of them presented at least one episode of BPAR. sCD30 tested positive in nine (37.5%) patients, and all these later presented at least one episode of BPAR. sCD30 and PRA diagnostic indexes in predicting early (< 6 months) BPAR were sensitivity 64.2% versus 28.5%; specificity 100% versus 80%; accuracy 79.1% versus 50%; positive predictive value 100% versus 66.6%; and negative predictive value 66.6% versus 44.4%. The RR of early AR was 1.4 in PRA-positive patients and extremely higher in the sCD30-positive group. Pretransplant sCD30 is a more accurate predictor of AR when compared with PRA. These results support its use in the pretransplant work-up of kidney-graft recipients.

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units.

PubMed

Cai, Qingzhong; Yang, Gongliu; Song, Ningfang; Liu, Yiliang

2016-06-22

An inertial navigation system (INS) has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10(-6)°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs) using common turntables, has a great application potential in future atomic gyro INSs.

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

Accurate Autism Screening at the 18-Month Well-Child Visit Requires Different Strategies than at 24 Months

ERIC Educational Resources Information Center

Sturner, Raymond; Howard, Barbara; Bergmann, Paul; Morrel, Tanya; Landa, Rebecca; Walton, Kejuana; Marks, Danielle

2017-01-01

Accuracy of autism screening using M-CHAT plus the follow-up interview (M-CHAT/F) for children screened positive at 18-months was compared to screening at 24-months. Formal ASD testing was criterion for a community sample of M-CHAT positive children (n = 98), positive predictive value (PPV) was 0.40 for the M-CHAT and 0.58 for the M-CHAT/F.…

The diagnosis of acute appendicitis in a pediatric population: to CT or not to CT.

PubMed

Stephen, Antonia E; Segev, Dorry L; Ryan, Daniel P; Mullins, Mark E; Kim, Samuel H; Schnitzer, Jay J; Doody, Daniel P

2003-03-01

The aim of this study was to determine if focused appendiceal computed tomography with colon contrast (FACT-CC) increases the accuracy of the preoperative diagnosis of acute appendicitis in children. A 5-year retrospective review was conducted of a university hospital database of 283 patients (age 0.8 to 19.3 years; mean, 11.3 years) treated with appendectomy for presumed acute appendicitis. Of the 283 patients in whom appendectomies were performed, 268 were confirmed by pathologic analysis of the specimen to have acute appendicitis for a diagnostic accuracy in our institution of 94.7%. Ninety-six patients (34%) underwent FACT-CC scans as part of their preoperative evaluation. The sensitivity of the computed tomography (CT) scan was 94.6%, and the positive predictive value was 95.6%. In girls older than 10 years, CT imaging was not significantly more accurate in predicting appendicitis than examination alone (93.9% v. 87.5%; P =.46). Preoperative FACT-CC did not increase the accuracy in diagnosing appendicitis when compared with patients diagnosed by history, physical examination and laboratory studies. If there was a strong suspicion of appendicitis, a negative CT scan did not exclude the diagnosis of appendicitis. However, focused appendiceal CT scan is a sensitive test with a high positive predictive value and may be useful in a patient with an atypical history or examination. Copyright 2003, Elsevier Science (USA). All rights reserved.

Accuracy of MSCT Coronary Angiography with 64 Row CT Scanner—Facing the Facts

PubMed Central

Wehrschuetz, M.; Wehrschuetz, E.; Schuchlenz, H.; Schaffler, G.

2010-01-01

Improvements in multislice computed tomography (MSCT) angiography of the coronary vessels have enabled the minimally invasive detection of coronary artery stenoses, while quantitative coronary angiography (QCA) is the accepted reference standard for evaluation thereof. Sixteen-slice MSCT showed promising diagnostic accuracy in detecting coronary artery stenoses haemodynamically and the subsequent introduction of 64-slice scanners promised excellent and fast results for coronary artery studies. This prompted us to evaluate the diagnostic accuracy, sensitivity, specificity, and the negative und positive predictive value of 64-slice MSCT in the detection of haemodynamically significant coronary artery stenoses. Thirty-seven consecutive subjects with suspected coronary artery disease were evaluated with MSCT angiography and the results compared with QCA. All vessels were considered for the assessment of significant coronary artery stenosis (diameter reduction ≥ 50%). Thirteen patients (35%) were identified as having significant coronary artery stenoses on QCA with 6.3% (35/555) affected segments. None of the coronary segments were excluded from analysis. Overall sensitivity for classifying stenoses of 64-slice MSCT was 69%, specificity was 92%, positive predictive value was 38% and negative predictive value was 98%. The interobserver variability for detection of significant lesions had a k-value of 0.43. Sixty-four-slice MSCT offers the diagnostic potential to detect coronary artery disease, to quantify haemodynamically significant coronary artery stenoses and to avoid unnecessary invasive coronary artery examinations. PMID:20567636

Multistix 10 SG Leukocyte Esterage Dipstick Testing in Rapid Bedside Diagnosis of Spontaneous Bacterial Peritonitis: A Prospective Study.

PubMed

Jha, Ashish K; Kumawat, Dal C; Bolya, Yasvant K; Goenka, Mahesh K

2012-09-01

Spontaneous bacterial peritonitis (SBP) requires rapid diagnosis and the initiation of antibiotics. Diagnosis of SBP is usually based on cytobacteriological examination of ascitic fluid. These tests require good laboratory facilities and reporting time of few hours to 1-2 day. However, the 24 h laboratory facilities not widely available in country like India. We evaluated the diagnostic utility of reagent strip (Multistix 10 SG(®)) for rapid diagnosis of SBP. The study was prospectively carried out on patients of cirrhosis with ascites. Bedside leukocyte esterase reagent strip testing was performed on ascitic fluid. Cell count as determined by colorimetric scale of reagent strip was compared with counting chamber method. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. Out of 100 patients with cirrhotic ascites, [72 males: 28 female; mean age 44.34 (SD 13.03) years] 18 patients were diagnosed to have SBP by counting chamber method as compared to 14 patients detected to have SBP by reagent strip test ≥++ positive. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of reagent strip ≥++ positive were 77.77%, 95.12%, 77.77%, 95.12% and 92% respectively compared to counting chamber method. Reagent strip to diagnose SBP is very specific but less sensitive as compared to counting chamber method. This can be performed rapidly, easily and efficiently even in remote area of developing countries. This bedside test could be a useful tool for the diagnosis of SBP in country like India.

Accuracy of three-dimensional facial soft tissue simulation in post-traumatic zygoma reconstruction.

PubMed

Li, P; Zhou, Z W; Ren, J Y; Zhang, Y; Tian, W D; Tang, W

2016-12-01

The aim of this study was to evaluate the accuracy of novel software-CMF-preCADS-for the prediction of soft tissue changes following repositioning surgery for zygomatic fractures. Twenty patients who had sustained an isolated zygomatic fracture accompanied by facial deformity and who were treated with repositioning surgery participated in this study. Cone beam computed tomography (CBCT) scans and three-dimensional (3D) stereophotographs were acquired preoperatively and postoperatively. The 3D skeletal model from the preoperative CBCT data was matched with the postoperative one, and the fractured zygomatic fragments were segmented and aligned to the postoperative position for prediction. Then, the predicted model was matched with the postoperative 3D stereophotograph for quantification of the simulation error. The mean absolute error in the zygomatic soft tissue region between the predicted model and the real one was 1.42±1.56mm for all cases. The accuracy of the prediction (mean absolute error ≤2mm) was 87%. In the subjective assessment it was found that the majority of evaluators considered the predicted model and the postoperative model to be 'very similar'. CMF-preCADS software can provide a realistic, accurate prediction of the facial soft tissue appearance after repositioning surgery for zygomatic fractures. The reliability of this software for other types of repositioning surgery for maxillofacial fractures should be validated in the future. Copyright © 2016. Published by Elsevier Ltd.

Patterns and predictors of skin score change in early diffuse systemic sclerosis from the European Scleroderma Observational Study

PubMed Central

Herrick, Ariane L; Peytrignet, Sebastien; Lunt, Mark; Pan, Xiaoyan; Hesselstrand, Roger; Mouthon, Luc; Silman, Alan J; Dinsdale, Graham; Brown, Edith; Czirják, László; Distler, Jörg H W; Distler, Oliver; Fligelstone, Kim; Gregory, William J; Ochiel, Rachel; Vonk, Madelon C; Ancuţa, Codrina; Ong, Voon H; Farge, Dominique; Hudson, Marie; Matucci-Cerinic, Marco; Balbir-Gurman, Alexandra; Midtvedt, Øyvind; Jobanputra, Paresh; Jordan, Alison C; Stevens, Wendy; Moinzadeh, Pia; Hall, Frances C; Agard, Christian; Anderson, Marina E; Diot, Elisabeth; Madhok, Rajan; Akil, Mohammed; Buch, Maya H; Chung, Lorinda; Damjanov, Nemanja S; Gunawardena, Harsha; Lanyon, Peter; Ahmad, Yasmeen; Chakravarty, Kuntal; Jacobsen, Søren; MacGregor, Alexander J; McHugh, Neil; Müller-Ladner, Ulf; Riemekasten, Gabriela; Becker, Michael; Roddy, Janet; Carreira, Patricia E; Fauchais, Anne Laure; Hachulla, Eric; Hamilton, Jennifer; İnanç, Murat; McLaren, John S; van Laar, Jacob M; Pathare, Sanjay; Proudman, Susanna M; Rudin, Anna; Sahhar, Joanne; Coppere, Brigitte; Serratrice, Christine; Sheeran, Tom; Veale, Douglas J; Grange, Claire; Trad, Georges-Selim; Denton, Christopher P

2018-01-01

Objectives Our aim was to use the opportunity provided by the European Scleroderma Observational Study to (1) identify and describe those patients with early diffuse cutaneous systemic sclerosis (dcSSc) with progressive skin thickness, and (2) derive prediction models for progression over 12 months, to inform future randomised controlled trials (RCTs). Methods The modified Rodnan skin score (mRSS) was recorded every 3 months in 326 patients. ‘Progressors’ were defined as those experiencing a 5-unit and 25% increase in mRSS score over 12 months (±3 months). Logistic models were fitted to predict progression and, using receiver operating characteristic (ROC) curves, were compared on the basis of the area under curve (AUC), accuracy and positive predictive value (PPV). Results 66 patients (22.5%) progressed, 227 (77.5%) did not (33 could not have their status assessed due to insufficient data). Progressors had shorter disease duration (median 8.1 vs 12.6 months, P=0.001) and lower mRSS (median 19 vs 21 units, P=0.030) than non-progressors. Skin score was highest, and peaked earliest, in the anti-RNA polymerase III (Pol3+) subgroup (n=50). A first predictive model (including mRSS, duration of skin thickening and their interaction) had an accuracy of 60.9%, AUC of 0.666 and PPV of 33.8%. By adding a variable for Pol3 positivity, the model reached an accuracy of 71%, AUC of 0.711 and PPV of 41%. Conclusions Two prediction models for progressive skin thickening were derived, for use both in clinical practice and for cohort enrichment in RCTs. These models will inform recruitment into the many clinical trials of dcSSc projected for the coming years. Trial registration number NCT02339441. PMID:29306872

[Comparison of two quantitative methods of endobronchial ultrasound real-time elastography for evaluating intrathoracic lymph nodes].

PubMed

Mao, X W; Yang, J Y; Zheng, X X; Wang, L; Zhu, L; Li, Y; Xiong, H K; Sun, J Y

2017-06-12

Objective: To compare the clinical value of two quantitative methods in analyzing endobronchial ultrasound real-time elastography (EBUS-RTE) images for evaluating intrathoracic lymph nodes. Methods: From January 2014 to April 2014, EBUS-RTE examination was performed in patients who received EBUS-TBNA examination in Shanghai Chest Hospital. Each intrathoracic lymph node had a selected EBUS-RTE image. Stiff area ratio and mean hue value of region of interest (ROI) in each image were calculated respectively. The final diagnosis of lymph node was based on the pathologic/microbiologic results of EBUS-TBNA, pathologic/microbiologic results of other examinations and clinical following-up. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy were evaluated for distinguishing malignant and benign lesions. Results: Fifty-six patients and 68 lymph nodes were enrolled in this study, of which 35 lymph nodes were malignant and 33 lymph nodes were benign. The stiff area ratio and mean hue value of benign and malignant lesions were 0.32±0.29, 0.62±0.20 and 109.99±28.13, 141.62±17.52, respectively, and statistical differences were found in both of those two methods ( t =-5.14, P <0.01; t =-5.53, P <0.01). The area under curves was 0.813, 0.814 in stiff area ratio and mean hue value, respectively. The optimal diagnostic cut-off value of stiff area ratio was 0.48, and the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 82.86%, 81.82%, 82.86%, 81.82% and 82.35%, respectively. The optimal diagnostic cut-off value of mean hue value was 126.28, and the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 85.71%, 75.76%, 78.95%, 83.33% and 80.88%, respectively. Conclusion: Both the stiff area ratio and mean hue value methods can be used for analyzing EBUS-RTE images quantitatively, having the value of differentiating benign and malignant intrathoracic lymph nodes, and the stiff area ratio is better than the mean hue value between the two methods.

The assessment of serum-mediated phagocytosis of necrotic material by polymorphonuclear leukocytes to diagnose and predict the clinical features of systemic lupus erythematosus: an observational longitudinal study.

PubMed

Compagno, Michele; Gullstrand, Birgitta; Jacobsen, Søren; Eilertsen, Gro Ø; Nilsson, Jan Åke; Lood, Christian; Jönsen, Andreas; Truedsson, Lennart; Sturfelt, Gunnar; Bengtsson, Anders A

2016-02-10

Serum-mediated phagocytosis of antibody- and complement-opsonized necrotic cell material (NCM) by polymorphonuclear leukocytes can be quantified by using a flow cytometry-based assay. The phagocytosis of necrotic cell material (PNC) assay parallels the well-known lupus erythematosus cell test. In this study, we aimed to investigate the diagnostic accuracy of the assay and the relationship with clinical manifestations and disease activity in systemic lupus erythematosus (SLE). The diagnostic accuracy for SLE diagnosis of the PNC assay was studied by cross-sectional assessment of blood samples from 148 healthy control subjects and a multicenter rheumatic group (MRG) of 529 patients with different rheumatic symptoms. A cohort of 69 patients with an established SLE diagnosis (SLE cohort) underwent longitudinal clinical and laboratory follow-up for analysis of the temporal relationships between PNC positivity and specific clinical manifestations. In 35 of 529 MRG patients, 13 of whom had SLE, the PNC assay result was positive. Combined positivity of the PNC assay and anti-double-stranded DNA antibodies increased specificity and positive predictive value for SLE diagnosis to 0.99 and 0.67, respectively. In the longitudinal study, 42 of 69 SLE cohort patients had positive results in the PNC assay at least once. PNC assay positivity was associated with current hematological manifestations and could predict mucocutaneous manifestations. When combined with hypocomplementemia, PNC positivity preceded increased Systemic Lupus Erythematosus Disease Activity Index 2000 score, glomerulonephritis, and alopecia. Serum-mediated PNC by polymorphonuclear leukocytes is commonly but not exclusively seen in patients with SLE. The PNC assay may be used in follow-up of patients with SLE and, especially in combination with other routinely assessed laboratory tests, may help to predict flares and different clinical manifestations, including glomerulonephritis. Our results encourage further development of the PNC assay as a complementary laboratory tool in management of patients with SLE.

Accuracy of simple biochemical tests in identifying liver fibrosis in patients co-infected with human immunodeficiency virus and hepatitis C virus.

PubMed

Tural, Cristina; Tor, Jordi; Sanvisens, Arantza; Pérez-Alvarez, Núria; Martínez, Elisenda; Ojanguren, Isabel; García-Samaniego, Javier; Rockstroh, Juergen; Barluenga, Eva; Muga, Robert; Planas, Ramon; Sirera, Guillem; Rey-Joly, Celestino; Clotet, Bonaventura

2009-03-01

We assessed the ability of 3 simple biochemical tests to stage liver fibrosis in patients co-infected with human immunodeficiency virus (HIV) and hepatitis C virus (HCV). We analyzed liver biopsy samples from 324 consecutive HIV/HCV-positive patients (72% men; mean age, 38 y; mean CD4+ T-cell counts, 548 cells/mm(3)). Scheuer fibrosis scores were as follows: 30% had F0, 22% had F1, 19% had F2, 23% had F3, and 6% had F4. Logistic regression analyses were used to predict the probability of significant (>or=F2) or advanced (>or=F3) fibrosis, based on numeric scores from the APRI, FORNS, or FIB-4 tests (alone and in combination). Area under the receiver operating characteristic curves were analyzed to assess diagnostic performance. Area under the receiver operating characteristic curves analyses indicated that the 3 tests had similar abilities to identify F2 and F3; the ability of APRI, FORNS, and FIB-4 were as follows: F2 or greater: 0.72, 0.67, and 0.72, respectively; F3 or greater: 0.75, 0.73, and 0.78, respectively. The accuracy of each test in predicting which samples were F3 or greater was significantly higher than for F2 or greater (APRI, FORNS, and FIB-4: >or=F3: 75%, 76%, and 76%, respectively; >or=F2: 66%, 62%, and 68%, respectively). By using the lowest cut-off values for all 3 tests, F3 or greater was ruled out with sensitivity and negative predictive values of 79% to 94% and 87% to 91%, respectively, and 47% to 70% accuracy. Advanced liver fibrosis (>or=F3) was identified using the highest cut-off value, with specificity and positive predictive values of 90% to 96% and 63% to 73%, respectively, and 75% to 77% accuracy. Simple biochemical tests accurately predicted liver fibrosis in more than half the HIV/HCV co-infected patients. The absence and presence of liver fibrosis are predicted fairly using the lowest and highest cut-off levels, respectively.

Use Of Clinical Decision Analysis In Predicting The Efficacy Of Newer Radiological Imaging Modalities: Radioscintigraphy Versus Single Photon Transverse Section Emission Computed Tomography

NASA Astrophysics Data System (ADS)

Prince, John R.

1982-12-01

Sensitivity, specificity, and predictive accuracy have been shown to be useful measures of the clinical efficacy of diagnostic tests and can be used to predict the potential improvement in diagnostic certitude resulting from the introduction of a competing technology. This communication demonstrates how the informal use of clinical decision analysis may guide health planners in the allocation of resources, purchasing decisions, and implementation of high technology. For didactic purposes the focus is on a comparison between conventional planar radioscintigraphy (RS) and single photon transverse section emission conputed tomography (SPECT). For example, positive predictive accuracy (PPA) for brain RS in a specialist hospital with a 50% disease prevalance is about 95%. SPECT should increase this predicted accuracy to 96%. In a primary care hospital with only a 15% disease prevalance the PPA is only 77% and SPECT may increase this accuracy to about 79%. Similar calculations based on published data show that marginal improvements are expected with SPECT in the liver. It is concluded that: a) The decision to purchase a high technology imaging modality such as SPECT for clinical purposes should be analyzed on an individual organ system and institutional basis. High technology may be justified in specialist hospitals but not necessarily in primary care hospitals. This is more dependent on disease prevalance than procedure volume; b) It is questionable whether SPECT imaging will be competitive with standard RS procedures. Research should concentrate on the development of different medical applications.

Determination of GPS orbits to submeter accuracy

NASA Technical Reports Server (NTRS)

Bertiger, W. I.; Lichten, S. M.; Katsigris, E. C.

1988-01-01

Orbits for satellites of the Global Positioning System (GPS) were determined with submeter accuracy. Tests used to assess orbital accuracy include orbit comparisons from independent data sets, orbit prediction, ground baseline determination, and formal errors. One satellite tracked 8 hours each day shows rms error below 1 m even when predicted more than 3 days outside of a 1-week data arc. Differential tracking of the GPS satellites in high Earth orbit provides a powerful relative positioning capability, even when a relatively small continental U.S. fiducial tracking network is used with less than one-third of the full GPS constellation. To demonstrate this capability, baselines of up to 2000 km in North America were also determined with the GPS orbits. The 2000 km baselines show rms daily repeatability of 0.3 to 2 parts in 10 to the 8th power and agree with very long base interferometry (VLBI) solutions at the level of 1.5 parts in 10 to the 8th power. This GPS demonstration provides an opportunity to test different techniques for high-accuracy orbit determination for high Earth orbiters. The best GPS orbit strategies included data arcs of at least 1 week, process noise models for tropospheric fluctuations, estimation of GPS solar pressure coefficients, and combine processing of GPS carrier phase and pseudorange data. For data arc of 2 weeks, constrained process noise models for GPS dynamic parameters significantly improved the situation.

Automatically identifying health outcome information in MEDLINE records.

PubMed

Demner-Fushman, Dina; Few, Barbara; Hauser, Susan E; Thoma, George

2006-01-01

Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes. An annotation scheme based on an evidence-based medicine model for critical appraisal of evidence was developed and used to annotate 633 MEDLINE citations. Textual, structural, and meta-information features essential to outcome identification were learned from the created collection and used to develop an automatic system. Accuracy of automatic outcome identification was assessed in an intrinsic evaluation and in an extrinsic evaluation, in which ranking of MEDLINE search results obtained using PubMed Clinical Queries relied on identified outcome statements. The accuracy and positive predictive value of outcome identification were calculated. Effectiveness of the outcome-based ranking was measured using mean average precision and precision at rank 10. Automatic outcome identification achieved 88% to 93% accuracy. The positive predictive value of individual sentences identified as outcomes ranged from 30% to 37%. Outcome-based ranking improved retrieval accuracy, tripling mean average precision and achieving 389% improvement in precision at rank 10. Preliminary results in outcome-based document ranking show potential validity of the evidence-based medicine-model approach in timely delivery of information critical to clinical decision support at the point of service.

Application of local binary pattern and human visual Fibonacci texture features for classification different medical images

NASA Astrophysics Data System (ADS)

Sanghavi, Foram; Agaian, Sos

2017-05-01

The goal of this paper is to (a) test the nuclei based Computer Aided Cancer Detection system using Human Visual based system on the histopathology images and (b) Compare the results of the proposed system with the Local Binary Pattern and modified Fibonacci -p pattern systems. The system performance is evaluated using different parameters such as accuracy, specificity, sensitivity, positive predictive value, and negative predictive value on 251 prostate histopathology images. The accuracy of 96.69% was observed for cancer detection using the proposed human visual based system compared to 87.42% and 94.70% observed for Local Binary patterns and the modified Fibonacci p patterns.

Boiling incipience and convective boiling of neon and nitrogen

NASA Technical Reports Server (NTRS)

Papell, S. S.; Hendricks, R. C.

1977-01-01

Forced convection and subcooled boiling heat transfer data for liquid nitrogen and liquid neon were obtained in support of a design study for a 30 tesla cryomagnet cooled by forced convection of liquid neon. The cryogen data obtained over a range of system pressures, fluid flow rates, and applied heat fluxes were used to develop correlations for predicting boiling incipience and convective boiling heat transfer coefficients in uniformly heated flow channels. The accuracy of the correlating equations was then evaluated. A technique was also developed to calculate the position of boiling incipience in a uniformly heated flow channel. Comparisons made with the experimental data showed a prediction accuracy of + or - 15 percent.

Predicting Individual Tree and Shrub Species Distributions with Empirically Derived Microclimate Surfaces in a Complex Mountain Ecosystem in Northern Idaho, USA

NASA Astrophysics Data System (ADS)

Holden, Z.; Cushman, S.; Evans, J.; Littell, J. S.

2009-12-01

The resolution of current climate interpolation models limits our ability to adequately account for temperature variability in complex mountainous terrain. We empirically derive 30 meter resolution models of June-October day and nighttime temperature and April nighttime Vapor Pressure Deficit (VPD) using hourly data from 53 Hobo dataloggers stratified by topographic setting in mixed conifer forests near Bonners Ferry, ID. 66%, of the variability in average June-October daytime temperature is explained by 3 variables (elevation, relative slope position and topographic roughness) derived from 30 meter digital elevation models. 69% of the variability in nighttime temperatures among stations is explained by elevation, relative slope position and topographic dissection (450 meter window). 54% of variability in April nighttime VPD is explained by elevation, soil wetness and the NDVIc derived from Landsat. We extract temperature and VPD predictions at 411 intensified Forest Inventory and Analysis plots (FIA). We use these variables with soil wetness and solar radiation indices derived from a 30 meter DEM to predict the presence and absence of 10 common forest tree species and 25 shrub species. Classification accuracies range from 87% for Pinus ponderosa , to > 97% for most other tree species. Shrub model accuracies are also high with greater than 90% accuracy for the majority of species. Species distribution models based on the physical variables that drive species occurrence, rather than their topographic surrogates, will eventually allow us to predict potential future distributions of these species with warming climate at fine spatial scales.

Creatinine measurement on dry blood spot sample for chronic kidney disease screening.

PubMed

Silva, Alan Castro Azevedo E; Gómez, Juan Fidel Bencomo; Lugon, Jocemir Ronaldo; Graciano, Miguel Luis

2016-03-01

Chronic kidney disease (CKD) screening is advisable due to its high morbidity and mortality and is usually performed by sampling blood and urine. Here we present an innovative and simpler method, by measuring creatinine on a dry blood spot on filter paper. One-hundred and six individuals at high risk for CKD were enrolled. The creatinine values obtained using both tests and the demographic data of each participant allowed us to determinate the eGFR. The adopted cutoff for CKD was an eGFR < 60 ml/min. Mean age was 57 ± 12 years, 74% were female, 40% white, and 60% non-white. Seventy-six percent were hypertensive, 30% diabetic, 37% had family history of CKD, and 22% of smoking. The BMI was 29.5 ± 6.9 kg/m2, median systolic blood pressure was 125 mmHg (IQR 120-140 mmHg) and median diastolic blood pressure was 80 mmHg (IQR 70-80 mmHg). According to MDRD equation, sensitivity was 96%, specificity 55%, predictive positive value 96%, predictive negative value 55% and accuracy 92%. By the CKD-EPI equation the sensitivity was 94%, specificity 55%, predictive positive value 94%, predictive negative value 55% and accuracy 90%. A Bland and Altman analysis showed a relatively narrow range of creatinine values differences (+ 0.68mg/dl to -0.55mg/dl) inside the ± 1.96 SD, without systematic differences. Measurement of creatinine on dry blood sample is an easily feasible non-invasive diagnostic test with good accuracy that may be useful to screen chronic kidney disease.

Accuracy of ultrasound in prediction of rectosigmoid infiltration in epithelial ovarian cancer.

PubMed

Zikan, M; Fischerova, D; Semeradova, I; Slama, J; Dundr, P; Weinberger, V; Dusek, L; Cibula, D

2017-10-01

To examine prospectively the accuracy of ultrasound in predicting rectosigmoid tumor infiltration in patients with epithelial ovarian cancer. Patients referred for a suspicious pelvic mass between 2012 and 2014 were examined by ultrasound following the standard protocol for assessment of tumor infiltration. Of the 245 patients examined, 191 had proven ovarian cancer and underwent primary surgery and were included in the analysis. Patients with apparently benign or inoperable disease were excluded. Rectosigmoid infiltration was evaluated by histopathology or according to perioperative findings. Clinical, pathological and laboratory parameters were analyzed as factors potentially affecting the sensitivity and specificity of sonography. The sensitivity of ultrasound in detecting rectosigmoid infiltration in patients with ovarian cancer was 86.3%, with specificity of 95.8%, positive predictive value of 92.6%, negative predictive value of 91.9% and overall accuracy of 92.1%. Ultrasound is a highly accurate method for detecting rectosigmoid tumor infiltration in ovarian cancer patients, and thus, can be used for planning adequate management, including patient consultation, surgical team planning, suitable operating time and postoperative care. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Value of lower respiratory tract surveillance cultures to predict bacterial pathogens in ventilator-associated pneumonia: systematic review and diagnostic test accuracy meta-analysis.

PubMed

Brusselaers, Nele; Labeau, Sonia; Vogelaers, Dirk; Blot, Stijn

2013-03-01

In ventilator-associated pneumonia (VAP), early appropriate antimicrobial therapy may be hampered by involvement of multidrug-resistant (MDR) pathogens. A systematic review and diagnostic test accuracy meta-analysis were performed to analyse whether lower respiratory tract surveillance cultures accurately predict the causative pathogens of subsequent VAP in adult patients. Selection and assessment of eligibility were performed by three investigators by mutual consideration. Of the 525 studies retrieved, 14 were eligible for inclusion (all in English; published since 1994), accounting for 791 VAP episodes. The following data were collected: study and population characteristics; in- and exclusion criteria; diagnostic criteria for VAP; microbiological workup of surveillance and diagnostic VAP cultures. Sub-analyses were conducted for VAP caused by Staphylococcus aureus, Pseudomonas spp., and Acinetobacter spp., MDR microorganisms, frequency of sampling, and consideration of all versus the most recent surveillance cultures. The meta-analysis showed a high accuracy of surveillance cultures, with pooled sensitivities up to 0.75 and specificities up to 0.92 in culture-positive VAP. The area under the curve (AUC) of the hierarchical summary receiver-operating characteristic curve demonstrates moderate accuracy (AUC: 0.90) in predicting multidrug resistance. A sampling frequency of >2/week (sensitivity 0.79; specificity 0.96) and consideration of only the most recent surveillance culture (sensitivity 0.78; specificity 0.96) are associated with a higher accuracy of prediction. This study provides evidence for the benefit of surveillance cultures in predicting MDR bacterial pathogens in VAP. However, clinical and statistical heterogeneity, limited samples sizes, and bias remain important limitations of this meta-analysis.

Recall Latencies, Confidence, and Output Positions of True and False Memories: Implications for Recall and Metamemory Theories

ERIC Educational Resources Information Center

Jou, Jerwen

2008-01-01

Recall latency, recall accuracy rate, and recall confidence were examined in free recall as a function of recall output serial position using a modified Deese-Roediger-McDermott paradigm to test a strength-based theory against the dual-retrieval process theory of recall output sequence. The strength theory predicts the item output sequence to be…

Diagnostic Accuracy of the Veteran Affairs' Traumatic Brain Injury Screen.

PubMed

Louise Bender Pape, Theresa; Smith, Bridget; Babcock-Parziale, Judith; Evans, Charlesnika T; Herrold, Amy A; Phipps Maieritsch, Kelly; High, Walter M

2018-01-31

To comprehensively estimate the diagnostic accuracy and reliability of the Department of Veterans Affairs (VA) Traumatic Brain Injury (TBI) Clinical Reminder Screen (TCRS). Cross-sectional, prospective, observational study using the Standards for Reporting of Diagnostic Accuracy criteria. Three VA Polytrauma Network Sites. Operation Iraqi Freedom, Operation Enduring Freedom veterans (N=433). TCRS, Comprehensive TBI Evaluation, Structured TBI Diagnostic Interview, Symptom Attribution and Classification Algorithm, and Clinician-Administered Posttraumatic Stress Disorder (PTSD) Scale. Forty-five percent of veterans screened positive on the TCRS for TBI. For detecting occurrence of historical TBI, the TCRS had a sensitivity of .56 to .74, a specificity of .63 to .93, a positive predictive value (PPV) of 25% to 45%, a negative predictive value (NPV) of 91% to 94%, and a diagnostic odds ratio (DOR) of 4 to 13. For accuracy of attributing active symptoms to the TBI, the TCRS had a sensitivity of .64 to .87, a specificity of .59 to .89, a PPV of 26% to 32%, an NPV of 92% to 95%, and a DOR of 6 to 9. The sensitivity was higher for veterans with PTSD (.80-.86) relative to veterans without PTSD (.57-.82). The specificity, however, was higher among veterans without PTSD (.75-.81) relative to veterans with PTSD (.36-.49). All indices of diagnostic accuracy changed when participants with questionably valid (QV) test profiles were eliminated from analyses. The utility of the TCRS to screen for mild TBI (mTBI) depends on the stringency of the diagnostic reference standard to which it is being compared, the presence/absence of PTSD, and QV test profiles. Further development, validation, and use of reproducible diagnostic algorithms for symptom attribution after possible mTBI would improve diagnostic accuracy. Published by Elsevier Inc.

Limb Dominance Results from Asymmetries in Predictive and Impedance Control Mechanisms

PubMed Central

Yadav, Vivek; Sainburg, Robert L.

2014-01-01

Handedness is a pronounced feature of human motor behavior, yet the underlying neural mechanisms remain unclear. We hypothesize that motor lateralization results from asymmetries in predictive control of task dynamics and in control of limb impedance. To test this hypothesis, we present an experiment with two different force field environments, a field with a predictable magnitude that varies with the square of velocity, and a field with a less predictable magnitude that varies linearly with velocity. These fields were designed to be compatible with controllers that are specialized in predicting limb and task dynamics, and modulating position and velocity dependent impedance, respectively. Because the velocity square field does not change the form of the equations of motion for the reaching arm, we reasoned that a forward dynamic-type controller should perform well in this field, while control of linear damping and stiffness terms should be less effective. In contrast, the unpredictable linear field should be most compatible with impedance control, but incompatible with predictive dynamics control. We measured steady state final position accuracy and 3 trajectory features during exposure to these fields: Mean squared jerk, Straightness, and Movement time. Our results confirmed that each arm made straighter, smoother, and quicker movements in its compatible field. Both arms showed similar final position accuracies, which were achieved using more extensive corrective sub-movements when either arm performed in its incompatible field. Finally, each arm showed limited adaptation to its incompatible field. Analysis of the dependence of trajectory errors on field magnitude suggested that dominant arm adaptation occurred by prediction of the mean field, thus exploiting predictive mechanisms for adaptation to the unpredictable field. Overall, our results support the hypothesis that motor lateralization reflects asymmetries in specific motor control mechanisms associated with predictive control of limb and task dynamics, and modulation of limb impedance. PMID:24695543

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

PubMed Central

Lingner, Thomas; Kataya, Amr R. A.; Reumann, Sigrun

2012-01-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences.1 As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity.” Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals. PMID:22415050

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

Boomerang: A method for recursive reclassification.

PubMed

Devlin, Sean M; Ostrovnaya, Irina; Gönen, Mithat

2016-09-01

While there are many validated prognostic classifiers used in practice, often their accuracy is modest and heterogeneity in clinical outcomes exists in one or more risk subgroups. Newly available markers, such as genomic mutations, may be used to improve the accuracy of an existing classifier by reclassifying patients from a heterogenous group into a higher or lower risk category. The statistical tools typically applied to develop the initial classifiers are not easily adapted toward this reclassification goal. In this article, we develop a new method designed to refine an existing prognostic classifier by incorporating new markers. The two-stage algorithm called Boomerang first searches for modifications of the existing classifier that increase the overall predictive accuracy and then merges to a prespecified number of risk groups. Resampling techniques are proposed to assess the improvement in predictive accuracy when an independent validation data set is not available. The performance of the algorithm is assessed under various simulation scenarios where the marker frequency, degree of censoring, and total sample size are varied. The results suggest that the method selects few false positive markers and is able to improve the predictive accuracy of the classifier in many settings. Lastly, the method is illustrated on an acute myeloid leukemia data set where a new refined classifier incorporates four new mutations into the existing three category classifier and is validated on an independent data set. © 2016, The International Biometric Society.

Boomerang: A Method for Recursive Reclassification

PubMed Central

Devlin, Sean M.; Ostrovnaya, Irina; Gönen, Mithat

2016-01-01

Summary While there are many validated prognostic classifiers used in practice, often their accuracy is modest and heterogeneity in clinical outcomes exists in one or more risk subgroups. Newly available markers, such as genomic mutations, may be used to improve the accuracy of an existing classifier by reclassifying patients from a heterogenous group into a higher or lower risk category. The statistical tools typically applied to develop the initial classifiers are not easily adapted towards this reclassification goal. In this paper, we develop a new method designed to refine an existing prognostic classifier by incorporating new markers. The two-stage algorithm called Boomerang first searches for modifications of the existing classifier that increase the overall predictive accuracy and then merges to a pre-specified number of risk groups. Resampling techniques are proposed to assess the improvement in predictive accuracy when an independent validation data set is not available. The performance of the algorithm is assessed under various simulation scenarios where the marker frequency, degree of censoring, and total sample size are varied. The results suggest that the method selects few false positive markers and is able to improve the predictive accuracy of the classifier in many settings. Lastly, the method is illustrated on an acute myeloid leukemia dataset where a new refined classifier incorporates four new mutations into the existing three category classifier and is validated on an independent dataset. PMID:26754051

Utility of a routine urinalysis in children who require clean intermittent catheterization.

PubMed

Forster, C S; Haslam, D B; Jackson, E; Goldstein, S L

2017-10-01

Children who require clean intermittent catheterization (CIC) frequently have positive urine cultures. However, diagnosing a urinary tract infection (UTI) can be difficult, as there are no standardized criteria. Routine urinalysis (UA) has good predictive accuracy for UTI in the general pediatric population, but data are limited on the utility of routine UA in the population of children who require CIC. To determine the utility of UA parameters (e.g. leukocyte esterase, nitrites, and pyuria) to predict UTI in children who require CIC, and identify a composite UA that has maximal predictive accuracy for UTI. A cross-sectional study of 133 children who required CIC, and had a UA and urine culture sent as part of standard of care. Patients in the no-UTI group all had UA and urine cultures sent as part of routine urodynamics, and were asymptomatic. Patients included in the UTI group had growth of ≥50,000 colony-forming units/ml of a known uropathogen on urine culture, in addition to two or more of the following symptoms: fever, abdominal pain, back pain, foul-smelling urine, new or worse incontinence, and pain with catheterization. Categorical data were compared using Chi-squared test, and continuous data were compared with Student's t-test. Sensitivity, specificity, and positive and negative predictive values were calculated for individual UA parameters, as well as the composite UA. Logistic regression was performed on potential composite UA models to identify the model that best fit the data. There was a higher proportion of patients in the no-UTI group with negative leukocyte esterase compared with the UTI group. There was a higher proportion of patients with UTI who had large leukocyte esterase and positive nitrites compared with the no-UTI group (Summary Figure). There was no between-group difference in urinary white blood cells. Positive nitrites were the most specific (84.4%) for UTI. None of the parameters had a high positive predictive value, while all had high negative predictive values. The composite model with the best Akaike information criterion was >10 urinary white blood cells and either moderate or large leukocyte esterase, which had a positive predictive value of 33.3 and a negative predictive value of 90.4. Routine UA had limited sensitivity, but moderate specificity, in predicting UTI in children who required CIC. The composite UA and moderate or large leukocyte esterase both had good negative predictive values for the outcome of UTI. Copyright © 2017 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Use of risk assessment instruments to predict violence and antisocial behaviour in 73 samples involving 24 827 people: systematic review and meta-analysis.

PubMed

Fazel, Seena; Singh, Jay P; Doll, Helen; Grann, Martin

2012-07-24

To investigate the predictive validity of tools commonly used to assess the risk of violence, sexual, and criminal behaviour. Systematic review and tabular meta-analysis of replication studies following PRISMA guidelines. PsycINFO, Embase, Medline, and United States Criminal Justice Reference Service Abstracts. We included replication studies from 1 January 1995 to 1 January 2011 if they provided contingency data for the offending outcome that the tools were designed to predict. We calculated the diagnostic odds ratio, sensitivity, specificity, area under the curve, positive predictive value, negative predictive value, the number needed to detain to prevent one offence, as well as a novel performance indicator-the number safely discharged. We investigated potential sources of heterogeneity using metaregression and subgroup analyses. Risk assessments were conducted on 73 samples comprising 24,847 participants from 13 countries, of whom 5879 (23.7%) offended over an average of 49.6 months. When used to predict violent offending, risk assessment tools produced low to moderate positive predictive values (median 41%, interquartile range 27-60%) and higher negative predictive values (91%, 81-95%), and a corresponding median number needed to detain of 2 (2-4) and number safely discharged of 10 (4-18). Instruments designed to predict violent offending performed better than those aimed at predicting sexual or general crime. Although risk assessment tools are widely used in clinical and criminal justice settings, their predictive accuracy varies depending on how they are used. They seem to identify low risk individuals with high levels of accuracy, but their use as sole determinants of detention, sentencing, and release is not supported by the current evidence. Further research is needed to examine their contribution to treatment and management.

A machine learning approach for real-time modelling of tissue deformation in image-guided neurosurgery.

PubMed

Tonutti, Michele; Gras, Gauthier; Yang, Guang-Zhong

2017-07-01

Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augmented reality (AR) applications. Current deformation models are characterised by a trade-off between accuracy and computational speed. We propose an approach to derive a patient-specific deformation model for brain pathologies by combining the results of pre-computed finite element method (FEM) simulations with machine learning algorithms. The models can be computed instantaneously and offer an accuracy comparable to FEM models. A brain tumour is used as the subject of the deformation model. Load-driven FEM simulations are performed on a tetrahedral brain mesh afflicted by a tumour. Forces of varying magnitudes, positions, and inclination angles are applied onto the brain's surface. Two machine learning algorithms-artificial neural networks (ANNs) and support vector regression (SVR)-are employed to derive a model that can predict the resulting deformation for each node in the tumour's mesh. The tumour deformation can be predicted in real time given relevant information about the geometry of the anatomy and the load, all of which can be measured instantly during a surgical operation. The models can predict the position of the nodes with errors below 0.3mm, beyond the general threshold of surgical accuracy and suitable for high fidelity AR systems. The SVR models perform better than the ANN's, with positional errors for SVR models reaching under 0.2mm. The results represent an improvement over existing deformation models for real time applications, providing smaller errors and high patient-specificity. The proposed approach addresses the current needs of image-guided surgical systems and has the potential to be employed to model the deformation of any type of soft tissue. Copyright © 2017 Elsevier B.V. All rights reserved.

Diagnostic value of alarm symptoms for upper GI malignancy in patients referred to GI clinic: A 7 years cross sectional study.

PubMed

Emami, Mohammad Hasan; Ataie-Khorasgani, Masoud; Jafari-Pozve, Nasim

2017-01-01

Early upper gastrointestinal (UGI) cancer detection had led to organ-preserving endoscopic therapy. Endoscopy is a suitable method of early diagnosis of UGI malignancies. In Iran, exclusion of malignancy is the most important indication for endoscopy. This study is designed to see whether using alarm symptoms can predict the risk of cancer in patients. A total of 3414 patients referred to a tertiary gastrointestinal (GI) clinic in Isfahan, Iran, from 2009 to 2016 with dyspepsia, gastroesophageal reflux disease (GERD), and alarm symptoms, such as weight loss, dysphagia, GI bleeding, vomiting, positive familial history for cancer, and anorexia. Each patient had been underwent UGI endoscopy and patient data, including histology results, had been collected in the computer. We used logistic regression models to estimate the diagnostic accuracy of each alarm symptoms. A total of 3414 patients with alarm symptoms entered in this study, of whom 72 (2.1%) had an UGI malignancy. According to the logistic regression model, dysphagia ( P < 0.001) and weight loss ( P < 0.001) were found to be significant positive predictive factors for malignancy. Furthermore, males were in a significantly higher risk of developing UGI malignancy. Through receiver operating characteristic curve and the area under the curve (AUC) with adequate overall calibration and model fit measures, dysphagia and weight loss as a related cancer predictor had a high diagnostic accuracy (accuracy = 0. 72, AUC = 0. 881). Using a combination of age, alarm symptoms will lead to high positive predictive value for cancer. We recommend to do an early endoscopy for any patient with UGI symptoms and to take multiple biopsies from any rudeness or suspicious lesion, especially for male gender older than 50, dysphagia, or weight loss.

Diagnostic accuracy of 3.0 T magnetic resonance imaging for the detection of meniscus posterior root pathology.

PubMed

LaPrade, Robert F; Ho, Charles P; James, Evan; Crespo, Bernardo; LaPrade, Christopher M; Matheny, Lauren M

2015-01-01

The purpose of this study was to determine the diagnostic accuracy of 3 T MRI, including sensitivity, specificity, negative and positive predictive values, for detection of posterior medial and lateral meniscus root tears and avulsions. All patients who had a 3 T MRI of the knee, followed by arthroscopic surgery, were included in this study. Arthroscopy was considered the gold standard. Meniscus root tears diagnosed at arthroscopy and on MRI were defined as a complete meniscus root detachment within 9 mm of the root. All surgical data were collected prospectively and stored in a data registry. MRI exams were reported prospectively by a musculoskeletal radiologist and reviewed retrospectively. There were 287 consecutive patients (156 males, 131 females; mean age 41.7 years) in this study. Prevalence of meniscus posterior root tears identified at arthroscopy was 9.1, 5.9% for medial and 3.5% for lateral root tears (one patient had both). Sensitivity was 0.770 (95% CI 0.570, 0.901), specificity was 0.729 (95% CI 0.708, 0.741), positive predictive value was 0.220 (95% CI 0.163, 0.257) and negative predictive value was 0.970 (95% CI 0.943, 0.987). For medial root tears, sensitivity was 0.824 (95% CI 0.569, 0.953), specificity was 0.800 (95% CI 0.784, 0.808), positive predictive value was 0.206 (95% CI 0.142, 0.238) and negative predictive value was 0.986 (95% CI 0.967, 0.996). For lateral meniscus posterior root tears, sensitivity was 0.600 (95% CI 0.281, 0.860), specificity was 0.903 (95% CI 0.891, 0.912), positive predictive value was 0.181 (95% CI 0.085, 0.261) and negative predictive value was 0.984 (95% CI 0.972, 0.994). This study demonstrated moderate sensitivity and specificity of 3 T MRI to detect posterior meniscus root tears. The negative predictive value of 3 T MRI to detect posterior meniscus root tears was high; however, the positive predictive value was low. Sensitivity was higher for medial root tears, indicating a higher risk of missing lateral root tears on MRI. Imaging has an important role in identifying meniscus posterior horn root tears; however, some root tears may not be identified until arthroscopy. Prognostic study (diagnostic), Level II.

Analysis of energy-based algorithms for RNA secondary structure prediction

PubMed Central

2012-01-01

Background RNA molecules play critical roles in the cells of organisms, including roles in gene regulation, catalysis, and synthesis of proteins. Since RNA function depends in large part on its folded structures, much effort has been invested in developing accurate methods for prediction of RNA secondary structure from the base sequence. Minimum free energy (MFE) predictions are widely used, based on nearest neighbor thermodynamic parameters of Mathews, Turner et al. or those of Andronescu et al. Some recently proposed alternatives that leverage partition function calculations find the structure with maximum expected accuracy (MEA) or pseudo-expected accuracy (pseudo-MEA) methods. Advances in prediction methods are typically benchmarked using sensitivity, positive predictive value and their harmonic mean, namely F-measure, on datasets of known reference structures. Since such benchmarks document progress in improving accuracy of computational prediction methods, it is important to understand how measures of accuracy vary as a function of the reference datasets and whether advances in algorithms or thermodynamic parameters yield statistically significant improvements. Our work advances such understanding for the MFE and (pseudo-)MEA-based methods, with respect to the latest datasets and energy parameters. Results We present three main findings. First, using the bootstrap percentile method, we show that the average F-measure accuracy of the MFE and (pseudo-)MEA-based algorithms, as measured on our largest datasets with over 2000 RNAs from diverse families, is a reliable estimate (within a 2% range with high confidence) of the accuracy of a population of RNA molecules represented by this set. However, average accuracy on smaller classes of RNAs such as a class of 89 Group I introns used previously in benchmarking algorithm accuracy is not reliable enough to draw meaningful conclusions about the relative merits of the MFE and MEA-based algorithms. Second, on our large datasets, the algorithm with best overall accuracy is a pseudo MEA-based algorithm of Hamada et al. that uses a generalized centroid estimator of base pairs. However, between MFE and other MEA-based methods, there is no clear winner in the sense that the relative accuracy of the MFE versus MEA-based algorithms changes depending on the underlying energy parameters. Third, of the four parameter sets we considered, the best accuracy for the MFE-, MEA-based, and pseudo-MEA-based methods is 0.686, 0.680, and 0.711, respectively (on a scale from 0 to 1 with 1 meaning perfect structure predictions) and is obtained with a thermodynamic parameter set obtained by Andronescu et al. called BL* (named after the Boltzmann likelihood method by which the parameters were derived). Conclusions Large datasets should be used to obtain reliable measures of the accuracy of RNA structure prediction algorithms, and average accuracies on specific classes (such as Group I introns and Transfer RNAs) should be interpreted with caution, considering the relatively small size of currently available datasets for such classes. The accuracy of the MEA-based methods is significantly higher when using the BL* parameter set of Andronescu et al. than when using the parameters of Mathews and Turner, and there is no significant difference between the accuracy of MEA-based methods and MFE when using the BL* parameters. The pseudo-MEA-based method of Hamada et al. with the BL* parameter set significantly outperforms all other MFE and MEA-based algorithms on our large data sets. PMID:22296803

Analysis of energy-based algorithms for RNA secondary structure prediction.

PubMed

Hajiaghayi, Monir; Condon, Anne; Hoos, Holger H

2012-02-01

RNA molecules play critical roles in the cells of organisms, including roles in gene regulation, catalysis, and synthesis of proteins. Since RNA function depends in large part on its folded structures, much effort has been invested in developing accurate methods for prediction of RNA secondary structure from the base sequence. Minimum free energy (MFE) predictions are widely used, based on nearest neighbor thermodynamic parameters of Mathews, Turner et al. or those of Andronescu et al. Some recently proposed alternatives that leverage partition function calculations find the structure with maximum expected accuracy (MEA) or pseudo-expected accuracy (pseudo-MEA) methods. Advances in prediction methods are typically benchmarked using sensitivity, positive predictive value and their harmonic mean, namely F-measure, on datasets of known reference structures. Since such benchmarks document progress in improving accuracy of computational prediction methods, it is important to understand how measures of accuracy vary as a function of the reference datasets and whether advances in algorithms or thermodynamic parameters yield statistically significant improvements. Our work advances such understanding for the MFE and (pseudo-)MEA-based methods, with respect to the latest datasets and energy parameters. We present three main findings. First, using the bootstrap percentile method, we show that the average F-measure accuracy of the MFE and (pseudo-)MEA-based algorithms, as measured on our largest datasets with over 2000 RNAs from diverse families, is a reliable estimate (within a 2% range with high confidence) of the accuracy of a population of RNA molecules represented by this set. However, average accuracy on smaller classes of RNAs such as a class of 89 Group I introns used previously in benchmarking algorithm accuracy is not reliable enough to draw meaningful conclusions about the relative merits of the MFE and MEA-based algorithms. Second, on our large datasets, the algorithm with best overall accuracy is a pseudo MEA-based algorithm of Hamada et al. that uses a generalized centroid estimator of base pairs. However, between MFE and other MEA-based methods, there is no clear winner in the sense that the relative accuracy of the MFE versus MEA-based algorithms changes depending on the underlying energy parameters. Third, of the four parameter sets we considered, the best accuracy for the MFE-, MEA-based, and pseudo-MEA-based methods is 0.686, 0.680, and 0.711, respectively (on a scale from 0 to 1 with 1 meaning perfect structure predictions) and is obtained with a thermodynamic parameter set obtained by Andronescu et al. called BL* (named after the Boltzmann likelihood method by which the parameters were derived). Large datasets should be used to obtain reliable measures of the accuracy of RNA structure prediction algorithms, and average accuracies on specific classes (such as Group I introns and Transfer RNAs) should be interpreted with caution, considering the relatively small size of currently available datasets for such classes. The accuracy of the MEA-based methods is significantly higher when using the BL* parameter set of Andronescu et al. than when using the parameters of Mathews and Turner, and there is no significant difference between the accuracy of MEA-based methods and MFE when using the BL* parameters. The pseudo-MEA-based method of Hamada et al. with the BL* parameter set significantly outperforms all other MFE and MEA-based algorithms on our large data sets.

The Upper and Lower Bounds of the Prediction Accuracies of Ensemble Methods for Binary Classification

PubMed Central

Wang, Xueyi; Davidson, Nicholas J.

2011-01-01

Ensemble methods have been widely used to improve prediction accuracy over individual classifiers. In this paper, we achieve a few results about the prediction accuracies of ensemble methods for binary classification that are missed or misinterpreted in previous literature. First we show the upper and lower bounds of the prediction accuracies (i.e. the best and worst possible prediction accuracies) of ensemble methods. Next we show that an ensemble method can achieve > 0.5 prediction accuracy, while individual classifiers have < 0.5 prediction accuracies. Furthermore, for individual classifiers with different prediction accuracies, the average of the individual accuracies determines the upper and lower bounds. We perform two experiments to verify the results and show that it is hard to achieve the upper and lower bounds accuracies by random individual classifiers and better algorithms need to be developed. PMID:21853162

A clock-aided positioning algorithm based on Kalman model of GNSS receiver clock bias

NASA Astrophysics Data System (ADS)

Zhu, Lingyao; Li, Zishen; Yuan, Hong

2017-10-01

The modeling and forecasting of the receiver clock bias is of practical significance, including the improvement of positioning accuracy, etc. When the clock frequency of the receiver is stable, the model can be established according to the historical clock bias data and the clock bias of the following time can be predicted. For this, we adopted the Kalman model to predict the receiver clock bias based on the calculated clock bias data obtained from the laboratory via sliding mode. Meanwhile, the relevant clock-aided positioning algorithm was presented. The results show that: the Kalman model can be used in practical work; and that under the condition that only 3 satellite signal can be received, this clock-aided positioning results can meet the needs of civilian users, which improves the continuity of positioning in harsh conditions.

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

PubMed Central

Kai, Joe; Garibaldi, Jonathan M.; Qureshi, Nadeem

2017-01-01

Background Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiting complex interactions between risk factors. We assessed whether machine-learning can improve cardiovascular risk prediction. Methods Prospective cohort study using routine clinical data of 378,256 patients from UK family practices, free from cardiovascular disease at outset. Four machine-learning algorithms (random forest, logistic regression, gradient boosting machines, neural networks) were compared to an established algorithm (American College of Cardiology guidelines) to predict first cardiovascular event over 10-years. Predictive accuracy was assessed by area under the ‘receiver operating curve’ (AUC); and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) to predict 7.5% cardiovascular risk (threshold for initiating statins). Findings 24,970 incident cardiovascular events (6.6%) occurred. Compared to the established risk prediction algorithm (AUC 0.728, 95% CI 0.723–0.735), machine-learning algorithms improved prediction: random forest +1.7% (AUC 0.745, 95% CI 0.739–0.750), logistic regression +3.2% (AUC 0.760, 95% CI 0.755–0.766), gradient boosting +3.3% (AUC 0.761, 95% CI 0.755–0.766), neural networks +3.6% (AUC 0.764, 95% CI 0.759–0.769). The highest achieving (neural networks) algorithm predicted 4,998/7,404 cases (sensitivity 67.5%, PPV 18.4%) and 53,458/75,585 non-cases (specificity 70.7%, NPV 95.7%), correctly predicting 355 (+7.6%) more patients who developed cardiovascular disease compared to the established algorithm. Conclusions Machine-learning significantly improves accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment, while avoiding unnecessary treatment of others. PMID:28376093

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

PubMed

Weng, Stephen F; Reps, Jenna; Kai, Joe; Garibaldi, Jonathan M; Qureshi, Nadeem

2017-01-01

Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiting complex interactions between risk factors. We assessed whether machine-learning can improve cardiovascular risk prediction. Prospective cohort study using routine clinical data of 378,256 patients from UK family practices, free from cardiovascular disease at outset. Four machine-learning algorithms (random forest, logistic regression, gradient boosting machines, neural networks) were compared to an established algorithm (American College of Cardiology guidelines) to predict first cardiovascular event over 10-years. Predictive accuracy was assessed by area under the 'receiver operating curve' (AUC); and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) to predict 7.5% cardiovascular risk (threshold for initiating statins). 24,970 incident cardiovascular events (6.6%) occurred. Compared to the established risk prediction algorithm (AUC 0.728, 95% CI 0.723-0.735), machine-learning algorithms improved prediction: random forest +1.7% (AUC 0.745, 95% CI 0.739-0.750), logistic regression +3.2% (AUC 0.760, 95% CI 0.755-0.766), gradient boosting +3.3% (AUC 0.761, 95% CI 0.755-0.766), neural networks +3.6% (AUC 0.764, 95% CI 0.759-0.769). The highest achieving (neural networks) algorithm predicted 4,998/7,404 cases (sensitivity 67.5%, PPV 18.4%) and 53,458/75,585 non-cases (specificity 70.7%, NPV 95.7%), correctly predicting 355 (+7.6%) more patients who developed cardiovascular disease compared to the established algorithm. Machine-learning significantly improves accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment, while avoiding unnecessary treatment of others.

Development of a Natural Language Processing Engine to Generate Bladder Cancer Pathology Data for Health Services Research.

PubMed

Schroeck, Florian R; Patterson, Olga V; Alba, Patrick R; Pattison, Erik A; Seigne, John D; DuVall, Scott L; Robertson, Douglas J; Sirovich, Brenda; Goodney, Philip P

2017-12-01

To take the first step toward assembling population-based cohorts of patients with bladder cancer with longitudinal pathology data, we developed and validated a natural language processing (NLP) engine that abstracts pathology data from full-text pathology reports. Using 600 bladder pathology reports randomly selected from the Department of Veterans Affairs, we developed and validated an NLP engine to abstract data on histology, invasion (presence vs absence and depth), grade, the presence of muscularis propria, and the presence of carcinoma in situ. Our gold standard was based on an independent review of reports by 2 urologists, followed by adjudication. We assessed the NLP performance by calculating the accuracy, the positive predictive value, and the sensitivity. We subsequently applied the NLP engine to pathology reports from 10,725 patients with bladder cancer. When comparing the NLP output to the gold standard, NLP achieved the highest accuracy (0.98) for the presence vs the absence of carcinoma in situ. Accuracy for histology, invasion (presence vs absence), grade, and the presence of muscularis propria ranged from 0.83 to 0.96. The most challenging variable was depth of invasion (accuracy 0.68), with an acceptable positive predictive value for lamina propria (0.82) and for muscularis propria (0.87) invasion. The validated engine was capable of abstracting pathologic characteristics for 99% of the patients with bladder cancer. NLP had high accuracy for 5 of 6 variables and abstracted data for the vast majority of the patients. This now allows for the assembly of population-based cohorts with longitudinal pathology data. Published by Elsevier Inc.

Evaluation with 3.0-T MR imaging: predicting the pathological response of triple-negative breast cancer treated with anthracycline and taxane neoadjuvant chemotherapy.

PubMed

Kim, Min Jung; Kim, Eun-Kyung; Park, Seho; Moon, Hee Jung; Kim, Seung Il; Park, Byeong-Woo

2015-09-01

Triple-negative breast cancer (TNBC) which expresses neither hormonal receptors nor HER-2 is associated with poor prognosis and shorter survival. Several studies have suggested that TNBC patients attaining pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) show a longer survival than those without pCR. To assess the accuracy of 3.0-T breast magnetic resonance imaging (MRI) in predicting pCR and to evaluate the clinicoradiologic factors affecting the diagnostic accuracy of 3.0-T breast MRI in TNBC patients treated with anthracycline and taxane (ACD). This retrospective study was approved by the institutional review board; patient consent was not required. Between 2009 and 2012, 35 TNBC patients with 3.0-T breast MRI prior to (n = 26) or after (n = 35) NAC were included. MRI findings were reviewed according to pCR to chemotherapy. The diagnostic accuracy of 3.0-T breast MRI for predicting pCR and the clinicoradiological factors affecting MRI accuracy and response to NAC were analyzed. 3.0-T MRI following NAC with ACD accurately predicted pCR in 91.4% of TNBC patients. The residual tumor size between pathology and 3.0-T MRI in non-pCR cases showed a higher correlation in the Ki-67-positive TNBC group (r = 0.947) than in the Ki-67 negative group (r = 0.375) with statistical trends (P = 0.069). Pre-treatment MRI in the non-pCR group compared to the pCR group showed a larger tumor size (P = 0.030) and non-mass presentation (P = 0.015). 3.0-T MRI in TNBC patients following NAC with ACD showed a high accuracy for predicting pCR to NAC. Ki-67 can affect the diagnostic accuracy of 3.0-T MRI for pCR to NAC with ACD in TNBC patients. © The Foundation Acta Radiologica 2014.

Anatomical placement of the human eyeball in the orbit--validation using CT scans of living adults and prediction for facial approximation.

PubMed

Guyomarc'h, Pierre; Dutailly, Bruno; Couture, Christine; Coqueugniot, Hélène

2012-09-01

Accuracy of forensic facial approximation and superimposition techniques relies on the knowledge of anatomical correlations between soft and hard tissues. Recent studies by Stephan and collaborators (6,8,10) reviewed traditional guidelines leading to a wrong placement of the eyeball in the orbit. As those statements are based on a small cadaver sample, we propose a validation of these findings on a large database (n = 375) of living people. Computed tomography scans of known age and sex subjects were used to collect landmarks on three-dimensional surfaces and DICOM with TIVMI. Results confirmed a more superior and lateral position of the eyeball relatively to the orbital rims. Orbital height and breadth were used to compute regression formulae and proportional placement using percentages to find the most probable position of the eyeball in the orbit. A size-related sexual dimorphism was present but did not impact on the prediction accuracy. © 2012 American Academy of Forensic Sciences.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation.

PubMed

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-08-01

The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient ( P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation

PubMed Central

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-01-01

Background and Aims: The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. Materials and Methods: In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. Results: The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient (P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). Conclusion: The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning. PMID:28904477

Does imprint cytology improve the accuracy of transrectal prostate needle biopsy?

PubMed

Sayar, Hamide; Bulut, Burak Besir; Bahar, Abdulkadir Yasir; Bahar, Mustafa Remzi; Seringec, Nurten; Resim, Sefa; Çıralık, Harun

2015-02-01

To evaluate the accuracy of imprint cytology of core needle biopsy specimens in the diagnosis of prostate cancer. Between December 24, 2011 and May 9, 2013, patients with an abnormal DRE and/or serum PSA level of >2.5 ng/mL underwent transrectal prostate needle biopsy. Samples with positive imprint cytology but negative initial histologic exam underwent repeat sectioning and histological examination. 1,262 transrectal prostate needle biopsy specimens were evaluated from 100 patients. Malignant imprint cytology was found in 236 specimens (18.7%), 197 (15.6%) of which were confirmed by histologic examination, giving an initial 3.1% (n = 39) rate of discrepant results by imprint cytology. Upon repeat sectioning and histologic examination of these 39 biopsy samples, 14 (1.1% of the original specimens) were then diagnosed as malignant, 3 (0.2%) as atypical small acinar proliferation (ASAP), and 5 (0.4%) as high-grade prostatic intraepithelial neoplasia (HGPIN). Overall, 964 (76.4%) specimens were negative for malignancy by imprint cytology. Seven (0.6%) specimens were benign by cytology but malignant cells were found on histological evaluation. On imprint cytology examination, nonmalignant but abnormal findings were seen in 62 specimens (4.9%). These were all due to benign processes. After reexamination, the accuracy, sensitivity, specificity, positive predictive value, negative predictive value, false-positive rate, false-negative rate of imprint preparations were 98.1, 96.9, 98.4, 92.8, 99.3, 1.6, 3.1%, respectively. Imprint cytology is valuable tool for evaluating TRUS-guided core needle biopsy specimens from the prostate. Use of imprint cytology in combination with histopathology increases diagnostic accuracy when compared with histopathologic assessment alone. © 2014 Wiley Periodicals, Inc.

Magnetic resonance imaging in local staging of endometrial carcinoma: diagnostic performance, pitfalls, and literature review.

PubMed

Zandrino, Franco; La Paglia, Ernesto; Musante, Francesco

2010-01-01

To assess the diagnostic accuracy of magnetic resonance imaging in local staging of endometrial carcinoma, and to review the results and pitfalls described in the literature. Thirty women with a histological diagnosis of endometrial carcinoma underwent magnetic resonance imaging. Unenhanced T2-weighted and dynamic contrast-enhanced Ti-weighted sequences were obtained. Hysterectomy and salpingo-oophorectomy was performed in all patients. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for the detection of deep myometrial and cervical infiltration. For deep myometrial infiltration T2-weighted sequences reached a sensitivity of 85%, specificity of 76%, PPV of 73%, NVP of 87%, and accuracy of 80%, while contrast-enhanced scans reached a sensitivity of 90%, specificity of 80%, PPV of 82%, NPV of 89%, and accuracy of 85%. For cervical infiltration T2-weighted sequences reached a sensitivity of 75%, specificity of 88%, PPV of 50%, NPV of 96%, and accuracy of 87%, while contrast-enhanced scans reached a sensitivity of 100%, specificity of 94%, PPV of 75%, NPV of 100%, and accuracy of 95%. Unenhanced and dynamic gadolinium-enhanced magnetic resonance allows accurate assessment of myometrial and cervical infiltration. Information provided by magnetic resonance imaging can define prognosis and management.

The Stroke Assessment of Fall Risk (SAFR): predictive validity in inpatient stroke rehabilitation.

PubMed

Breisinger, Terry P; Skidmore, Elizabeth R; Niyonkuru, Christian; Terhorst, Lauren; Campbell, Grace B

2014-12-01

To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. Patients admitted for inpatient stroke rehabilitation (N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. Not applicable. Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales' classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen (p < 0.001), with area under the curve of 0.73, positive predictive value of 0.29, and negative predictive value of 0.94. For the Fall Harm Risk Screen, area under the curve was 0.56, positive predictive value was 0.19, and negative predictive value was 0.86. Sensitivity and specificity of the SAFR (0.78 and 0.63, respectively) was higher than the Fall Harm Risk Screen (0.57 and 0.48, respectively). An evidence-derived, population-specific fall risk assessment may more accurately predict fallers than a general fall risk screen for stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted. © The Author(s) 2014.

Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information

NASA Astrophysics Data System (ADS)

Dolloff, John; Hottel, Bryant; Edwards, David; Theiss, Henry; Braun, Aaron

2017-05-01

This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.

Meta-Accuracy and Relationship Quality: Weighing the Costs and Benefits of Knowing What People Really Think About You

PubMed Central

Carlson, Erika N.

2016-01-01

People use metaperceptions, or their beliefs about how other people perceive them, to initiate and maintain social bonds. Are accurate metaperceptions associated with higher quality relationships? In four studies, the current research answers this question but considers the possibility that the self might not experience the same relational benefits of accurate metaperceptions, or meta-accuracy, as the people who form judgments about the self. For example, people tend to like individuals who have accurate self-perceptions, yet individuals tend to enjoy their own relationships more with people they believe see them in desirable ways. To test whether meta-accuracy is linked to relationship quality and whether this link differs for the self and others, meta-accuracy for personality traits as well as metaperceiver- and judge-reported relationship quality were assessed among new acquaintances (N = 184), peers (N = 228), friends (N = 273), and romantic partners (N = 401). Results suggested that judges enjoyed relationships more with metaperceivers who knew the impression they made, regardless of whether judges’ impressions were desirable (i.e., positive or self-verifying). Initial meta-accuracy also predicted greater relationship quality over time, suggesting that accurate metaperceptions have positive effects on relationships. In contrast, rather than enjoying relationships more when they were accurate, metaperceivers enjoyed relationships more when they believed judges perceived them in positive or self-verifying ways. Thus, meta-accuracy seems to be a virtue in the eyes of judges, but metaperceivers do not seem to reap the same benefits of knowing what others really think. Implications for improving meta-accuracy are discussed. PMID:27337137

Colonic polyps: application value of computer-aided detection in computed tomographic colonography.

PubMed

Zhang, Hui-Mao; Guo, Wei; Liu, Gui-Feng; An, Dong-Hong; Gao, Shuo-Hui; Sun, Li-Bo; Yang, Hai-Shan

2011-02-01

Colonic polyps are frequently encountered in clinics. Computed tomographic colonography (CTC), as a painless and quick detection, has high values in clinics. In this study, we evaluated the application value of computer-aided detection (CAD) in CTC detection of colonic polyps in the Chinese population. CTC was performed with a GE 64-row multidetector computed tomography (MDCT) scanner. Data of 50 CTC patients (39 patients positive for at least one polyp of ≥ 0.5 cm in size and the other 11 patients negative by endoscopic detection) were retrospectively reviewed first without computer-aided detection (CAD) and then with CAD by four radiologists (two were experienced and another two inexperienced) blinded to colonoscopy findings. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of detected colonic polyps, as well as the areas under the ROC curves (Az value) with and without CAD were calculated. CAD increased the overall sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the colonic polyps detected by experienced and inexperienced readers. The sensitivity in detecting small polyps (5 - 9 mm) with CAD in experienced and inexperienced readers increased from 82% and 44% to 93% and 82%, respectively (P > 0.05 and P < 0.001). With the use of CAD, the overall false positive rate and false negative rate for the detection of polyps by experienced and inexperienced readers decreased in different degrees. Among 13 sessile polyps not detected by CAD, two were ≥ 1.0 cm, eleven were 5 - 9 mm in diameter, and nine were flat-shaped lesions. The application of CAD in combination with CTC can increase the ability to detect colonic polyps, particularly for inexperienced readers. However, CAD is of limited value for the detection of flat polyps.

Fecal immunochemical test for predicting mucosal healing in ulcerative colitis patients: A systematic review and meta-analysis.

PubMed

Dai, Cong; Jiang, Min; Sun, Ming-Jun; Cao, Qin

2018-05-01

Fecal immunochemical test (FIT) is a promising marker for assessment of inflammatory bowel disease activity. However, the utility of FIT for predicting mucosal healing (MH) of ulcerative colitis (UC) patients has yet to be clearly demonstrated. The objective of our study was to perform a diagnostic test accuracy test meta-analysis evaluating the diagnostic accuracy of FIT in predicting MH of UC patients. We systematically searched the databases from inception to November 2017 that evaluated MH in UC. The methodological quality of each study was assessed according to the Quality Assessment of Diagnostic Accuracy Studies checklist. The extracted data were pooled using a summary receiver operating characteristic curve model. Random-effects model was used to summarize the diagnostic odds ratio, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio. Six studies comprising 625 UC patients were included in the meta-analysis. The pooled sensitivity and specificity values for predicting MH in UC were 0.77 (95% confidence interval [CI], 0.72-0.81) and 0.81 (95% CI, 0.76-0.85), respectively. The FIT level had a high rule-in value (positive likelihood ratio, 3.79; 95% CI, 2.85-5.03) and a moderate rule-out value (negative likelihood ratio, 0.26; 95% CI, 0.16-0.43) for predicting MH in UC. The results of the receiver operating characteristic curve analysis (area under the curve, 0.88; standard error of the mean, 0.02) and diagnostic odds ratio (18.08; 95% CI, 9.57-34.13) also revealed improved discrimination for identifying MH in UC with FIT concentration. Our meta-analysis has found that FIT is a simple, reliable non-invasive marker for predicting MH in UC patients. © 2018 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Long-term effects of child abuse and neglect on emotion processing in adulthood.

PubMed

Young, Joanna Cahall; Widom, Cathy Spatz

2014-08-01

To determine whether child maltreatment has a long-term impact on emotion processing abilities in adulthood and whether IQ, psychopathology, or psychopathy mediate the relationship between childhood maltreatment and emotion processing in adulthood. Using a prospective cohort design, children (ages 0-11) with documented cases of abuse and neglect during 1967-1971 were matched with non-maltreated children and followed up into adulthood. Potential mediators (IQ, Post-Traumatic Stress [PTSD], Generalized Anxiety [GAD], Dysthymia, and Major Depressive [MDD] Disorders, and psychopathy) were assessed in young adulthood with standardized assessment techniques. In middle adulthood (Mage=47), the International Affective Picture System was used to measure emotion processing. Structural equation modeling was used to test mediation models. Individuals with a history of childhood maltreatment were less accurate in emotion processing overall and in processing positive and neutral pictures than matched controls. Childhood physical abuse predicted less accuracy in neutral pictures and childhood sexual abuse and neglect predicted less accuracy in recognizing positive pictures. MDD, GAD, and IQ predicted overall picture recognition accuracy. However, of the mediators examined, only IQ acted to mediate the relationship between child maltreatment and emotion processing deficits. Although research has focused on emotion processing in maltreated children, these new findings show an impact child abuse and neglect on emotion processing in middle adulthood. Research and interventions aimed at improving emotional processing deficiencies in abused and neglected children should consider the role of IQ. Copyright © 2014 Elsevier Ltd. All rights reserved.

Influence of hormonal therapy in prostate cancer patients undergoing [18F]fluoromethyl choline PET/CT: a retrospective study.

PubMed

Palumbo, Barbara; Sivolella, Silvio; Palumbo, Isabella; Buresta, Tommaso; Radicchia, Valentina; Fravolini, Mario L; Ferretti, Francesca; Bellavita, Rita; Mearini, Luigi; Scialpi, Michele; Aristei, Cynthia; Pelliccia, Gianfranco

2016-12-01

Patients with suspected recurrence of prostate cancer undergoing [18F]fluoromethyl choline ([18F]FCH) PET/CT were retrospectively evaluated to investigate the influence of hormonal therapy (HT) in [18F]FCH uptake. [18F]FCH PET/CT was performed in 102 surgically treated patients with suspected recurrence (PSA increase >0.2 ng/mL) of prostate cancer, divided in two groups: under HT (N.=54) and without HT (N.=48) at the time of PET scanning. PET/CT was carried out by an integrated system (Biograph 6, CTI/Siemens, Knoxville, TN, USA) intravenously by administering 4.1 MBq/kg of [18F]FCH to each patient; images were acquired 60 minutes later. On the total number of patients, 66 were found to be true positives (TP), 9 false positives (FP), 5 false negatives (FN) and 22 true negatives (TN), sensitivity to [18F]FCH PET/CT was 93%, specificity 71%, accuracy 86%, positive predictive value (PPV) 88%, negative predictive value (NPV) 81%. In the 54 patients under HT, 38 were TP, 6 FP, 3 FN and 7 TN, sensitivity was 93%, specificity 54%, accuracy 83%, PPV 86% and NPV was 70%. In the 48 patients receiving no HT, 28 were TP, 3 FP, 2 FN and 15 TN, sensitivity was 93%, specificity 83%, accuracy 90%, PPV 90% and NPV 88%. A χ2 test showed that sensitivity, accuracy and PPV did not differ among patients with and without HT, while specificity and NPV were significantly lower (P<0.001) in HT treated patients. Sensitivity, accuracy and PPV were similar in patients with and without HT. Specificity and NPV were reduced in patients under HT, but further data are necessary to support if this reduction is casual or related to therapy and it could be confirmed in a larger series of patients.

Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences.

PubMed

Mi, Tian; Merlin, Jerlin Camilus; Deverasetty, Sandeep; Gryk, Michael R; Bill, Travis J; Brooks, Andrew W; Lee, Logan Y; Rathnayake, Viraj; Ross, Christian A; Sargeant, David P; Strong, Christy L; Watts, Paula; Rajasekaran, Sanguthevar; Schiller, Martin R

2012-01-01

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.

Improvement of background solar wind predictions

NASA Astrophysics Data System (ADS)

Dálya, Zsuzsanna; Opitz, Andrea

2016-04-01

In order to estimate the solar wind properties at any heliospheric positions propagation tools use solar measurements as input data. The ballistic method extrapolates in-situ solar wind observations to the target position. This works well for undisturbed solar wind, while solar wind disturbances such as Corotating Interaction Regions (CIRs) and Coronal Mass Ejections (CMEs) need more consideration. We are working on dedicated ICME lists to clean these signatures from the input data in order to improve our prediction accuracy. These ICME lists are created from several heliospheric spacecraft measurements: ACE, WIND, STEREO, SOHO, MEX and VEX. As a result, we are able to filter out these events from the time series. Our corrected predictions contribute to the investigation of the quiet solar wind and space weather studies.

Computerized tomography with 3-dimensional reconstruction for the evaluation of renal size and arterial anatomy in the living kidney donor.

PubMed

Janoff, Daniel M; Davol, Patrick; Hazzard, James; Lemmers, Michael J; Paduch, Darius A; Barry, John M

2004-01-01

Computerized tomography (CT) with 3-dimensional (3-D) reconstruction has gained acceptance as an imaging study to evaluate living renal donors. We report our experience with this technique in 199 consecutive patients to validate its predictions of arterial anatomy and kidney volumes. Between January 1997 and March 2002, 199 living donor nephrectomies were performed at our institution using an open technique. During the operation arterial anatomy was recorded as well as kidney weight in 98 patients and displacement volume in 27. Each donor had been evaluated preoperatively by CT angiography with 3-D reconstruction. Arterial anatomy described by a staff radiologist was compared with intraoperative findings. CT estimated volumes were reported. Linear correlation graphs were generated to assess the reliability of CT volume predictions. The accuracy of CT angiography for predicting arterial anatomy was 90.5%. However, as the number of renal arteries increased, predictive accuracy decreased. The ability of CT to predict multiple arteries remained high with a positive predictive value of 95.2%. Calculated CT volume and kidney weight significantly correlated (0.654). However, the coefficient of variation index (how much average CT volume differed from measured intraoperative volume) was 17.8%. CT angiography with 3-D reconstruction accurately predicts arterial vasculature in more than 90% of patients and it can be used to compare renal volumes. However, accuracy decreases with multiple renal arteries and volume comparisons may be inaccurate when the difference in kidney volumes is within 17.8%.

Generation, estimation, utilization, availability and compatibility aspects of geodetic and meteorological data

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

Luetzow, H.B.v.

1983-08-01

Following an introduction, the paper discusses in section 2 the collection or generation of final geodetic data from conventional surveys, satellite observations, satellite altimetry, the Global Positioning System, and moving base gravity gradiometers. Section 3 covers data utilization and accuracy aspects including gravity programmed inertial positioning and subterraneous mass detection. Section 4 addresses the usefulness and limitation of the collocation method of physical geodesy. Section 5 is concerned with the computation of classical climatological data. In section 6, meteorological data assimilation is considered. Section 7 deals with correlated aspects of initial data generation with emphasis on initial wind field determination,more » parameterized and classical hydrostatic prediction models, non-hydrostatic prediction, computational networks, and computer capacity. The paper concludes that geodetic and meteorological data are expected to become increasingly more diversified and voluminous both regionally and globally, that its general availability will be more or less restricted for some time to come, that its quality and quantity are subject to change, and that meteorological data generation, accuracy and density have to be considered in conjunction with advanced as well as cost-effective numerical weather prediction models and associated computational efforts.« less

Accuracy of Prediction Instruments for Diagnosing Large Vessel Occlusion in Individuals With Suspected Stroke: A Systematic Review for the 2018 Guidelines for the Early Management of Patients With Acute Ischemic Stroke.

PubMed

Smith, Eric E; Kent, David M; Bulsara, Ketan R; Leung, Lester Y; Lichtman, Judith H; Reeves, Mathew J; Towfighi, Amytis; Whiteley, William N; Zahuranec, Darin B

2018-03-01

Endovascular thrombectomy is a highly efficacious treatment for large vessel occlusion (LVO). LVO prediction instruments, based on stroke signs and symptoms, have been proposed to identify stroke patients with LVO for rapid transport to endovascular thrombectomy-capable hospitals. This evidence review committee was commissioned by the American Heart Association/American Stroke Association to systematically review evidence for the accuracy of LVO prediction instruments. Medline, Embase, and Cochrane databases were searched on October 27, 2016. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy-2 tool. Thirty-six relevant studies were identified. Most studies (21 of 36) recruited patients with ischemic stroke, with few studies in the prehospital setting (4 of 36) and in populations that included hemorrhagic stroke or stroke mimics (12 of 36). The most frequently studied prediction instrument was the National Institutes of Health Stroke Scale. Most studies had either some risk of bias or unclear risk of bias. Reported discrimination of LVO mostly ranged from 0.70 to 0.85, as measured by the C statistic. In meta-analysis, sensitivity was as high as 87% and specificity was as high as 90%, but no threshold on any instruments predicted LVO with both high sensitivity and specificity. With a positive LVO prediction test, the probability of LVO could be 50% to 60% (depending on the LVO prevalence in the population), but the probability of LVO with a negative test could still be ≥10%. No scale predicted LVO with both high sensitivity and high specificity. Systems that use LVO prediction instruments for triage will miss some patients with LVO and milder stroke. More prospective studies are needed to assess the accuracy of LVO prediction instruments in the prehospital setting in all patients with suspected stroke, including patients with hemorrhagic stroke and stroke mimics. © 2018 American Heart Association, Inc.

Electroencephalography Predicts Poor and Good Outcomes After Cardiac Arrest: A Two-Center Study.

PubMed

Rossetti, Andrea O; Tovar Quiroga, Diego F; Juan, Elsa; Novy, Jan; White, Roger D; Ben-Hamouda, Nawfel; Britton, Jeffrey W; Oddo, Mauro; Rabinstein, Alejandro A

2017-07-01

The prognostic role of electroencephalography during and after targeted temperature management in postcardiac arrest patients, relatively to other predictors, is incompletely known. We assessed performances of electroencephalography during and after targeted temperature management toward good and poor outcomes, along with other recognized predictors. Cohort study (April 2009 to March 2016). Two academic hospitals (Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland; Mayo Clinic, Rochester, MN). Consecutive comatose adults admitted after cardiac arrest, identified through prospective registries. All patients were managed with targeted temperature management, receiving prespecified standardized clinical, neurophysiologic (particularly, electroencephalography during and after targeted temperature management), and biochemical evaluations. We assessed electroencephalography variables (reactivity, continuity, epileptiform features, and prespecified "benign" or "highly malignant" patterns based on the American Clinical Neurophysiology Society nomenclature) and other clinical, neurophysiologic (somatosensory-evoked potential), and biochemical prognosticators. Good outcome (Cerebral Performance Categories 1 and 2) and mortality predictions at 3 months were calculated. Among 357 patients, early electroencephalography reactivity and continuity and flexor or better motor reaction had greater than 70% positive predictive value for good outcome; reactivity (80.4%; 95% CI, 75.9-84.4%) and motor response (80.1%; 95% CI, 75.6-84.1%) had highest accuracy. Early benign electroencephalography heralded good outcome in 86.2% (95% CI, 79.8-91.1%). False positive rates for mortality were less than 5% for epileptiform or nonreactive early electroencephalography, nonreactive late electroencephalography, absent somatosensory-evoked potential, absent pupillary or corneal reflexes, presence of myoclonus, and neuron-specific enolase greater than 75 µg/L; accuracy was highest for early electroencephalography reactivity (86.6%; 95% CI, 82.6-90.0). Early highly malignant electroencephalography had an false positive rate of 1.5% with accuracy of 85.7% (95% CI, 81.7-89.2%). This study provides class III evidence that electroencephalography reactivity predicts both poor and good outcomes, and motor reaction good outcome after cardiac arrest. Electroencephalography reactivity seems to be the best discriminator between good and poor outcomes. Standardized electroencephalography interpretation seems to predict both conditions during and after targeted temperature management.

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

PubMed

Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

2017-01-01

Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as we have done here, utilizing readily-available off-the-shelf machine learning techniques and resulting in only a fraction of narratives that require manual review. Human-machine ensemble methods are likely to improve performance over total manual coding. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tracking and Data Relay Satellite (TDRS-3) Range Biases and Momentum Unload Modeling for Terra (EOS-AMI)

NASA Technical Reports Server (NTRS)

Ward, Douglas T.

2001-01-01

The Flight Dynamics Facility (FDF) reports its performance in meeting Tracking and Data Relay Satellite (TDRS) predicted ephemeris accuracy requirements with TDRS-3. The Terra (Earth Observing System AM-1) satellite has 3-sigma TDRS requirements of 75 m for total position accuracy predicted over one day onboard. The study sample includes selected cases over 21 months after Guam Remote Ground Terminal (GRGT) support started in June 1998. For daily solutions with a 1.5-day prediction span, predicted results of the study were below the Terra requirement by at least 12 m. Refined range bias estimation and modeled momentum unloads are needed to meet Terra's requirements for TDRS-3. Maintained at 275 W longitude over the zone of exclusion, TDRS-3 is analyzed separately from other TDRSs because of its unique tracking data. Only the Bilateration Ranging Transponder (BRT) at Alice Springs (ALS), Australia, and the Telemetry, Tracking and Command (TT&C) system at Guam are used for routine operational tracking data for TDRS-3. Simultaneous batch orbit solutions with three TDRSs and either the Compton Gamma Ray Observatory (GRO) or Terra were done with the Goddard Trajectory Determination System (GTDS) to periodically refine the TT&C and BRT System (BRTS) range biases. As new biases were determined, significant changes were made in estimating the absolute position. FDF achieved similar results using a sequential filter with all operational TDRSs and four user satellites. Definitive accuracy (3-sigma) is expected to be below 50 m. The White Sands Complex (WSC) performs momentum unloads to maintain three-axis stabilized attitude of TDRSs. The relationship between velocity changes (delta-V) and reaction wheel speed changes was empirically determined for roll/yaw unloads. A theoretical relationship was verified and used for pitch unloads. Modeling both pitch and roll/yaw momentum unloads is necessary to meet the 75-m requirement. Moving the orbit solution epoch an hour before a momentum unload can improve delta-V optimization and prediction accuracy over 1.5 days.

Comparison of an IgG-Specific Enzyme-Linked Immunosorbent Assay Cutoff of 0.4 Versus 0.8 and 1.0 Optical Density Units for Heparin-Induced Thrombocytopenia.

PubMed

Ritchie, Brianne M; Connors, Jean M; Sylvester, Katelyn W

2017-04-01

Previous studies have demonstrated optimized diagnostic accuracy in utilizing higher antiheparin-platelet factor 4 (PF4) enzyme-linked immunosorbent assay (ELISA) optical density (OD) thresholds for diagnosing heparin-induced thrombocytopenia (HIT). We describe the incidence of positive serotonin release assay (SRA) results, as well as performance characteristics, for antiheparin-PF4 ELISA thresholds ≥0.4, ≥0.8, and ≥1.0 OD units in the diagnosis of HIT at our institution. Following institutional review board approval, we conducted a single-center retrospective chart review on adult inpatients with a differential diagnosis of HIT evaluated by both antiheparin-PF4 ELISA and SRA from 2012 to 2014. The major endpoints were to assess incidence of positive SRA results, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy at antiheparin-PF4 ELISA values ≥0.4 OD units when compared to values ≥0.8 and ≥1.0 OD units. Clinical characteristics, including demographics, laboratory values, clinical and safety outcomes, length of stay, and mortality, were collected. A total of 140 patients with 140 antiheparin-PF4 ELISA and SRA values were evaluated, of which 23 patients were SRA positive (16.4%) and 117 patients were SRA negative (83.6%). We identified a sensitivity of 91.3% versus 82.6% and 73.9%, specificity of 61.5% versus 87.2% and 91.5%, PPV of 31.8% versus 55.9% and 63.0%, NPV of 97.3% versus 96.2% and 94.7%, and accuracy of 66.4% versus 86.4% and 88.6% at antiheparin-PF4 ELISA thresholds ≥0.4, ≥0.8, and ≥1.0 OD units, respectively. Our study suggests an increased antiheparin-PF4 ELISA threshold of 0.8 or 1.0 OD units enhances specificity, PPV, and accuracy while maintaining NPV with decreased sensitivity.

Accuracy, Sensitivity and Specificity of Fine Needle Aspiration Biopsy for Salivary Gland Tumors: A Retrospective Study from 2006 to 2011

PubMed

Silva, William P P; Stramandinoli-Zanicotti, Roberta T; Schussel, Juliana L; Ramos, Gyl H A; Ioshi, Sergio O; Sassi, Laurindo M

2016-11-01

Objective: This article concerns evaluation of the sensitivity, specificity and accuracy of FNAB for pre-surgical diagnosis of benign and malignant lesions of major and minor salivary glands of patients treated in the Department of Head and Neck Surgery of Erasto Gartner Hospital. Methods: This retrospective study analyzed medical records from January 2006 to December 2011 from patients with salivary gland lesions who underwent preoperative FNAB and, after surgical excision of the lesion, histopathological examination. Results: The study had a cohort of 130 cases, but 34 cases (26.2%) were considered unsatisfactory regarding cytology analyses. Based on the data, sensitivity was 66.7% (6/9), specificity was 81.6% (71/87), accuracy was 80.2% (77/96), the positive predictive value was 66,7% (6/9) and the negative predictive value was 81.6% (71/87). Conclusion: Despite the high rate of inadequate samples obtained in the FNAB in this study the technique offers high specificity, accuracy and acceptable sensitivity. Creative Commons Attribution License

Comparison of the accuracy of radiography and ultrasonography for detection of articular lesions in horses.

PubMed

Hinz, Antje; Fischer, Andrew T

2011-10-01

To compare the accuracy of ultrasonographic and radiographic examination for evaluation of articular lesions in horses. Cross-sectional study. Horses (n = 137) with articular lesions. Radiographic and ultrasonographic examinations of the affected joint(s) were performed before diagnostic or therapeutic arthroscopic surgery. Findings were recorded and compared to lesions identified during arthroscopy. In 254 joints, 432 lesions were identified by arthroscopy. The overall accuracy was 82.9% for ultrasonography and 62.2% for radiography (P < .0001) with a sensitivity of 91.4% for ultrasonography and 66.7% for radiography (P < .0001). The difference in specificity was not statistically significant (P = .2628). The negative predictive value for ultrasonography was 31.5% and 13.2% for radiography (P = .0022), the difference for the positive predictive value was not statistically significant (P = .3898). The accuracy for ultrasonography and radiography for left versus right joints was equal and corresponded with the overall results. Ultrasonographic evaluation of articular lesions was more accurate than radiographic evaluation. © Copyright 2011 by The American College of Veterinary Surgeons.

The paradox of verbal autopsy in cause of death assignment: symptom question unreliability but predictive accuracy.

PubMed

Serina, Peter; Riley, Ian; Hernandez, Bernardo; Flaxman, Abraham D; Praveen, Devarsetty; Tallo, Veronica; Joshi, Rohina; Sanvictores, Diozele; Stewart, Andrea; Mooney, Meghan D; Murray, Christopher J L; Lopez, Alan D

2016-01-01

We believe that it is important that governments understand the reliability of the mortality data which they have at their disposable to guide policy debates. In many instances, verbal autopsy (VA) will be the only source of mortality data for populations, yet little is known about how the accuracy of VA diagnoses is affected by the reliability of the symptom responses. We previously described the effect of the duration of time between death and VA administration on VA validity. In this paper, using the same dataset, we assess the relationship between the reliability and completeness of symptom responses and the reliability and accuracy of cause of death (COD) prediction. The study was based on VAs in the Population Health Metrics Research Consortium (PHMRC) VA Validation Dataset from study sites in Bohol and Manila, Philippines and Andhra Pradesh, India. The initial interview was repeated within 3-52 months of death. Question responses were assessed for reliability and completeness between the two survey rounds. COD was predicted by Tariff Method. A sample of 4226 VAs was collected for 2113 decedents, including 1394 adults, 349 children, and 370 neonates. Mean question reliability was unexpectedly low ( kappa  = 0.447): 42.5 % of responses positive at the first interview were negative at the second, and 47.9 % of responses positive at the second had been negative at the first. Question reliability was greater for the short form of the PHMRC instrument ( kappa  = 0.497) and when analyzed at the level of the individual decedent ( kappa  = 0.610). Reliability at the level of the individual decedent was associated with COD predictive reliability and predictive accuracy. Families give coherent accounts of events leading to death but the details vary from interview to interview for the same case. Accounts are accurate but inconsistent; different subsets of symptoms are identified on each occasion. However, there are sufficient accurate and consistent subsets of symptoms to enable the Tariff Method to assign a COD. Questions which contributed most to COD prediction were also the most reliable and consistent across repeat interviews; these have been included in the short form VA questionnaire. Accuracy and reliability of diagnosis for an individual death depend on the quality of interview. This has considerable implications for the progressive roll out of VAs into civil registration and vital statistics (CRVS) systems.

Accuracy of conventional radiography and computed tomography in predicting implant position in relation to the vertebral canal in dogs.

PubMed

Hettlich, Bianca F; Fosgate, Geoffrey T; Levine, Jonathan M; Young, Benjamin D; Kerwin, Sharon C; Walker, Michael; Griffin, Jay; Maierl, Johann

2010-08-01

To compare the accuracy of radiography and computed tomography (CT) in predicting implant position in relation to the vertebral canal in the cervical and thoracolumbar vertebral column. In vitro imaging and anatomic study. Medium-sized canine cadaver vertebral columns (n=12). Steinmann pins were inserted into cervical and thoracolumbar vertebrae based on established landmarks but without predetermination of vertebral canal violation. Radiographs and CT images were obtained and evaluated by 6 individuals. A random subset of pins was evaluated for ability to distinguish left from right pins on radiographs. The ability to correctly identify vertebral canal penetration for all pins was assessed both on radiographs and CT. Spines were then anatomically prepared and visual examination of pin penetration into the canal served as the gold standard. Left/right accuracy was 93.1%. Overall sensitivity of radiographs and CT to detect vertebral canal penetration by an implant were significantly different and estimated as 50.7% and 93.4%, respectively (P<.0001). Sensitivity was significantly higher for complete versus partial penetration and for radiologists compared with nonradiologists for both imaging modalities. Overall specificity of radiographs and CT to detect vertebral canal penetration was 82.9% and 86.4%, respectively (P=.049). CT was superior to radiographic assessment and is the recommended imaging modality to assess penetration into the vertebral canal. CT is significantly more accurate in identifying vertebral canal violation by Steinmann pins and should be performed postoperatively to assess implant position.

The Accuracy of Integrated [18F] Fluorodeoxyglucose-Positron Emission Tomography/Computed Tomography in Detection of Pelvic and Para-aortic Nodal Metastasis in Patients with High Risk Endometrial Cancer

PubMed Central

Gholkar, Nikhil Shirish; Saha, Subhas Chandra; Prasad, GRV; Bhattacharya, Anish; Srinivasan, Radhika; Suri, Vanita

2014-01-01

Lymph nodal (LN) metastasis is the most important prognostic factor in high-risk endometrial cancer. However, the benefit of routine lymphadenectomy in endometrial cancer is controversial. This study was conducted to assess the accuracy of [18F] fluorodeoxyglucose-positron emission tomography/computed tomography ([18F] FDG-PET/CT) in detection of pelvic and para-aortic nodal metastases in high-risk endometrial cancer. 20 patients with high-risk endometrial carcinoma underwent [18F] FDG-PET/CT followed by total abdominal hysterectomy, bilateral salpingo-oophorectomy and systematic pelvic lymphadenectomy with or without para-aortic lymphadenectomy. The findings on histopathology were compared with [18F] FDG-PET/CT findings to calculate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of [18F] FDG-PET/CT. The pelvic nodal findings were analyzed on a patient and nodal chain based criteria. The para-aortic nodal findings were reported separately. Histopathology documented nodal involvement in two patients (10%). For detection of pelvic nodes, on a patient based analysis, [18F] FDG-PET/CT had a sensitivity of 100%, specificity of 61.11%, PPV of 22.22%, NPV of 100% and accuracy of 65% and on a nodal chain based analysis, [18F] FDG-PET/CT had a sensitivity of 100%, specificity of 80%, PPV of 20%, NPV of 100%, and accuracy of 80.95%. For detection of para-aortic nodes, [18F] FDG-PET/CT had sensitivity of 100%, specificity of 66.67%, PPV of 20%, NPV of 100%, and accuracy of 69.23%. Although [18F] FDG-PET/CT has high sensitivity for detection of LN metastasis in endometrial carcinoma, it had moderate accuracy and high false positivity. However, the high NPV is important in selecting patients in whom lymphadenectomy may be omitted. PMID:25538488

FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications.

PubMed

Backenroth, Daniel; He, Zihuai; Kiryluk, Krzysztof; Boeva, Valentina; Pethukova, Lynn; Khurana, Ekta; Christiano, Angela; Buxbaum, Joseph D; Ionita-Laza, Iuliana

2018-05-03

We describe a method based on a latent Dirichlet allocation model for predicting functional effects of noncoding genetic variants in a cell-type- and/or tissue-specific way (FUN-LDA). Using this unsupervised approach, we predict tissue-specific functional effects for every position in the human genome in 127 different tissues and cell types. We demonstrate the usefulness of our predictions by using several validation experiments. Using eQTL data from several sources, including the GTEx project, Geuvadis project, and TwinsUK cohort, we show that eQTLs in specific tissues tend to be most enriched among the predicted functional variants in relevant tissues in Roadmap. We further show how these integrated functional scores can be used for (1) deriving the most likely cell or tissue type causally implicated for a complex trait by using summary statistics from genome-wide association studies and (2) estimating a tissue-based correlation matrix of various complex traits. We found large enrichment of heritability in functional components of relevant tissues for various complex traits, and FUN-LDA yielded higher enrichment estimates than existing methods. Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods. In particular, our results suggest that tissue- and cell-type-specific functional prediction methods tend to have substantially better prediction accuracy than organism-level prediction methods. Scores for each position in the human genome and for each ENCODE and Roadmap tissue are available online (see Web Resources). Copyright © 2018 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

PubMed Central

Wang, Jie-Sheng; Han, Shuang

2015-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:26583034

Accuracy of Satellite Optical Observations and Precise Orbit Determination

NASA Astrophysics Data System (ADS)

Shakun, L.; Koshkin, N.; Korobeynikova, E.; Strakhova, S.; Dragomiretsky, V.; Ryabov, A.; Melikyants, S.; Golubovskaya, T.; Terpan, S.

The monitoring of low-orbit space objects (LEO-objects) is performed in the Astronomical Observatory of Odessa I.I. Mechnikov National University (Ukraine) for many years. Decades-long archives of these observations are accessible within Ukrainian network of optical observers (UMOS). In this work, we give an example of orbit determination for the satellite with the 1500-km height of orbit based on angular observations in our observatory (Int. No. 086). For estimation of the measurement accuracy and accuracy of determination and propagation of satellite position, we analyze the observations of Ajisai satellite with the well-determined orbit. This allows making justified conclusions not only about random errors of separate measurements, but also to analyze the presence of systematic errors, including external ones to the measurement process. We have shown that the accuracy of one measurement has the standard deviation about 1 arcsec across the track and 1.4 arcsec along the track and systematical shifts in measurements of one track do not exceed 0.45 arcsec. Ajisai position in the interval of the orbit fitting is predicted with accuracy better than 30 m along the orbit and better than 10 m across the orbit for any its point.

Software-based on-site estimation of fractional flow reserve using standard coronary CT angiography data.

PubMed

De Geer, Jakob; Sandstedt, Mårten; Björkholm, Anders; Alfredsson, Joakim; Janzon, Magnus; Engvall, Jan; Persson, Anders

2016-10-01

The significance of a coronary stenosis can be determined by measuring the fractional flow reserve (FFR) during invasive coronary angiography. Recently, methods have been developed which claim to be able to estimate FFR using image data from standard coronary computed tomography angiography (CCTA) exams. To evaluate the accuracy of non-invasively computed fractional flow reserve (cFFR) from CCTA. A total of 23 vessels in 21 patients who had undergone both CCTA and invasive angiography with FFR measurement were evaluated using a cFFR software prototype. The cFFR results were compared to the invasively obtained FFR values. Correlation was calculated using Spearman's rank correlation, and agreement using intraclass correlation coefficient (ICC). Sensitivity, specificity, accuracy, negative predictive value, and positive predictive value for significant stenosis (defined as both FFR ≤0.80 and FFR ≤0.75) were calculated. The mean cFFR value for the whole group was 0.81 and the corresponding mean invFFR value was 0.84. The cFFR sensitivity for significant stenosis (FFR ≤0.80/0.75) on a per-lesion basis was 0.83/0.80, specificity was 0.76/0.89, and accuracy 0.78/0.87. The positive predictive value was 0.56/0.67 and the negative predictive value was 0.93/0.94. The Spearman rank correlation coefficient was ρ = 0.77 (P < 0.001) and ICC = 0.73 (P < 0.001). This particular CCTA-based cFFR software prototype allows for a rapid, non-invasive on-site evaluation of cFFR. The results are encouraging and cFFR may in the future be of help in the triage to invasive coronary angiography. © The Foundation Acta Radiologica 2015.

Fusion of Computed Tomography and PROPELLER Diffusion-Weighted Magnetic Resonance Imaging for the Detection and Localization of Middle Ear Cholesteatoma.

PubMed

Locketz, Garrett D; Li, Peter M M C; Fischbein, Nancy J; Holdsworth, Samantha J; Blevins, Nikolas H

2016-10-01

A method to optimize imaging of cholesteatoma by combining the strengths of available modalities will improve diagnostic accuracy and help to target treatment. To assess whether fusing Periodically Rotated Overlapping Parallel Lines With Enhanced Reconstruction (PROPELLER) diffusion-weighted magnetic resonance imaging (DW-MRI) with corresponding temporal bone computed tomography (CT) images could increase cholesteatoma diagnostic and localization accuracy across 6 distinct anatomical regions of the temporal bone. Case series and preliminary technology evaluation of adults with preoperative temporal bone CT and PROPELLER DW-MRI scans who underwent surgery for clinically suggested cholesteatoma at a tertiary academic hospital. When cholesteatoma was encountered surgically, the precise location was recorded in a diagram of the middle ear and mastoid. For each patient, the 3 image data sets (CT, PROPELLER DW-MRI, and CT-MRI fusion) were reviewed in random order for the presence or absence of cholesteatoma by an investigator blinded to operative findings. If cholesteatoma was deemed present on review of each imaging modality, the location of the lesion was mapped presumptively. Image analysis was then compared with surgical findings. Twelve adults (5 women and 7 men; median [range] age, 45.5 [19-77] years) were included. The use of CT-MRI fusion had greater diagnostic sensitivity (0.88 vs 0.75), positive predictive value (0.88 vs 0.86), and negative predictive value (0.75 vs 0.60) than PROPELLER DW-MRI alone. Image fusion also showed increased overall localization accuracy when stratified across 6 distinct anatomical regions of the temporal bone (localization sensitivity and specificity, 0.76 and 0.98 for CT-MRI fusion vs 0.58 and 0.98 for PROPELLER DW-MRI). For PROPELLER DW-MRI, there were 15 true-positive, 45 true-negative, 1 false-positive, and 11 false-negative results; overall accuracy was 0.83. For CT-MRI fusion, there were 20 true-positive, 45 true-negative, 1 false-positive, and 6 false-negative results; overall accuracy was 0.90. The poor anatomical spatial resolution of DW-MRI makes precise localization of cholesteatoma within the middle ear and mastoid a diagnostic challenge. This study suggests that the bony anatomic detail obtained via CT coupled with the excellent sensitivity and specificity of PROPELLER DW-MRI for cholesteatoma can improve both preoperative identification and localization of disease over DW-MRI alone.

Positional Accuracy in Optical Trap-Assisted Nanolithography

NASA Astrophysics Data System (ADS)

Arnold, Craig B.; McLeod, Euan

2009-03-01

The ability to directly print patterns on size scales below 100 nm is important for many applications where the production or repair of high resolution and density features are important. Laser-based direct-write methods have the benefit of quickly and easily being able to modify and create structures on existing devices, but feature sizes are conventionally limited by diffraction. In this presentation, we show how to overcome this limit with a new method of probe-based near-field nanopatterning in which we employ a CW laser to optically trap and manipulate dispersed microspheres against a substrate using a 2-d Bessel beam optical trap. A secondary, pulsed nanosecond laser at 355 nm is directed through the bead and used to modify the surface below the microsphere, taking advantage of the near-field enhancement in order to produce materials modification with feature sizes under 100 nm. Here, we analyze the 3-d positioning accuracy of the microsphere through analytic modeling as a function of experimental parameters. The model is verified in all directions for our experimental conditions and is used to predict the conditions required for improved positional accuracy.

Affective processes in human-automation interactions.

PubMed

Merritt, Stephanie M

2011-08-01

This study contributes to the literature on automation reliance by illuminating the influences of user moods and emotions on reliance on automated systems. Past work has focused predominantly on cognitive and attitudinal variables, such as perceived machine reliability and trust. However, recent work on human decision making suggests that affective variables (i.e., moods and emotions) are also important. Drawing from the affect infusion model, significant effects of affect are hypothesized. Furthermore, a new affectively laden attitude termed liking is introduced. Participants watched video clips selected to induce positive or negative moods, then interacted with a fictitious automated system on an X-ray screening task At five time points, important variables were assessed including trust, liking, perceived machine accuracy, user self-perceived accuracy, and reliance.These variables, along with propensity to trust machines and state affect, were integrated in a structural equation model. Happiness significantly increased trust and liking for the system throughout the task. Liking was the only variable that significantly predicted reliance early in the task. Trust predicted reliance later in the task, whereas perceived machine accuracy and user self-perceived accuracy had no significant direct effects on reliance at any time. Affective influences on automation reliance are demonstrated, suggesting that this decision-making process may be less rational and more emotional than previously acknowledged. Liking for a new system may be key to appropriate reliance, particularly early in the task. Positive affect can be easily induced and may be a lever for increasing liking.

Understanding less than nothing: children's neural response to negative numbers shifts across age and accuracy.

PubMed

Gullick, Margaret M; Wolford, George

2013-01-01

We examined the brain activity underlying the development of our understanding of negative numbers, which are amounts lacking direct physical counterparts. Children performed a paired comparison task with positive and negative numbers during an fMRI session. As previously shown in adults, both pre-instruction fifth-graders and post-instruction seventh-graders demonstrated typical behavioral and neural distance effects to negative numbers, where response times and parietal and frontal activity increased as comparison distance decreased. We then determined the factors impacting the distance effect in each age group. Behaviorally, the fifth-grader distance effect for negatives was significantly predicted only by positive comparison accuracy, indicating that children who were generally better at working with numbers were better at comparing negatives. In seventh-graders, negative number comparison accuracy significantly predicted their negative number distance effect, indicating that children who were better at working with negative numbers demonstrated a more typical distance effect. Across children, as age increased, the negative number distance effect increased in the bilateral IPS and decreased frontally, indicating a frontoparietal shift consistent with previous numerical development literature. In contrast, as negative comparison task accuracy increased, the parietal distance effect increased in the left IPS and decreased in the right, possibly indicating a change from an approximate understanding of negatives' values to a more exact, precise representation (particularly supported by the left IPS) with increasing expertise. These shifts separately indicate the effects of increasing maturity generally in numeric processing and specifically in negative number understanding.

Comparison of the diagnostic accuracy of a rapid immunochromatographic test and the rapid plasma reagin test for antenatal syphilis screening in Mozambique.

PubMed Central

Montoya, Pablo J.; Lukehart, Sheila A.; Brentlinger, Paula E.; Blanco, Ana J.; Floriano, Florencia; Sairosse, Josefa; Gloyd, Stephen

2006-01-01

OBJECTIVE: Programmes to control syphilis in developing countries are hampered by a lack of laboratory services, delayed diagnosis, and doubts about current screening methods. We aimed to compare the diagnostic accuracy of an immunochromatographic strip (ICS) test and the rapid plasma reagin (RPR) test with the combined gold standard (RPR, Treponema pallidum haemagglutination assay and direct immunofluorescence stain done at a reference laboratory) for the detection of syphilis in pregnancy. METHODS: We included test results from 4789 women attending their first antenatal visit at one of six health facilities in Sofala Province, central Mozambique. We compared diagnostic accuracy (sensitivity, specificity, and positive and negative predictive values) of ICS and RPR done at the health facilities and ICS performed at the reference laboratory. We also made subgroup comparisons by human immunodeficiency virus (HIV) and malaria status. FINDINGS: For active syphilis, the sensitivity of the ICS was 95.3% at the reference laboratory, and 84.1% at the health facility. The sensitivity of the RPR at the health facility was 70.7%. Specificity and positive and negative predictive values showed a similar pattern. The ICS outperformed RPR in all comparisons (P<0.001). CONCLUSION: The diagnostic accuracy of the ICS compared favourably with that of the gold standard. The use of the ICS in Mozambique and similar settings may improve the diagnosis of syphilis in health facilities, both with and without laboratories. PMID:16501726

Thoracic injury rule out criteria and NEXUS chest in predicting the risk of traumatic intra-thoracic injuries: A diagnostic accuracy study.

PubMed

Safari, Saeed; Radfar, Fatemeh; Baratloo, Alireza

2018-05-01

This study aimed to compare the diagnostic accuracy of NEXUS chest and Thoracic Injury Rule out criteria (TIRC) models in predicting the risk of intra-thoracic injuries following blunt multiple trauma. In this diagnostic accuracy study, using the 2 mentioned models, blunt multiple trauma patients over the age of 15 years presenting to emergency department were screened regarding the presence of intra-thoracic injuries that are detectable via chest x-ray and screening performance characteristics of the models were compared. In this study, 3118 patients with the mean (SD) age of 37.4 (16.9) years were studied (57.4% male). Based on TIRC and NEXUS chest, respectively, 1340 (43%) and 1417 (45.4%) patients were deemed in need of radiography performance. Sensitivity, specificity, and positive and negative predictive values of TIRC were 98.95%, 62.70%, 21.19% and 99.83%. These values were 98.61%, 59.94%, 19.97% and 99.76%, for NEXUS chest, respectively. Accuracy of TIRC and NEXUS chest models were 66.04 (95% CI: 64.34-67.70) and 63.50 (95% CI: 61.78-65.19), respectively. TIRC and NEXUS chest models have proper and similar sensitivity in prediction of blunt traumatic intra-thoracic injuries that are detectable via chest x-ray. However, TIRC had a significantly higher specificity in this regard. Copyright © 2018 Elsevier Ltd. All rights reserved.

Usefulness of gram staining of blood collected from total parenteral nutrition catheter for rapid diagnosis of catheter-related sepsis.

PubMed Central

Moonens, F; el Alami, S; Van Gossum, A; Struelens, M J; Serruys, E

1994-01-01

The accuracy of Gram staining of blood drawn from catheters used to administer total parenteral nutrition was compared with paired quantitative blood cultures for the diagnosis of catheter-related sepsis. Gram staining was positive in 11 of 18 episodes of catheter-related sepsis documented by quantitative culture (sensitivity, 61%) but in none of the 5 episodes of fever unrelated to catheter infection. Thus, this procedure enabled the rapid presumptive diagnosis and guidance of antimicrobial therapy for total parenteral nutrition catheter sepsis, with a positive predictive value of 100% and a negative predictive value of 42%. PMID:7521359

Measurement and interpretation of skin prick test results.

PubMed

van der Valk, J P M; Gerth van Wijk, R; Hoorn, E; Groenendijk, L; Groenendijk, I M; de Jong, N W

2015-01-01

There are several methods to read skin prick test results in type-I allergy testing. A commonly used method is to characterize the wheal size by its 'average diameter'. A more accurate method is to scan the area of the wheal to calculate the actual size. In both methods, skin prick test (SPT) results can be corrected for histamine-sensitivity of the skin by dividing the results of the allergic reaction by the histamine control. The objectives of this study are to compare different techniques of quantifying SPT results, to determine a cut-off value for a positive SPT for histamine equivalent prick -index (HEP) area, and to study the accuracy of predicting cashew nut reactions in double-blind placebo-controlled food challenge (DBPCFC) tests with the different SPT methods. Data of 172 children with cashew nut sensitisation were used for the analysis. All patients underwent a DBPCFC with cashew nut. Per patient, the average diameter and scanned area of the wheal size were recorded. In addition, the same data for the histamine-induced wheal were collected for each patient. The accuracy in predicting the outcome of the DBPCFC using four different SPT readings (i.e. average diameter, area, HEP-index diameter, HEP-index area) were compared in a Receiver-Operating Characteristic (ROC) plot. Characterizing the wheal size by the average diameter method is inaccurate compared to scanning method. A wheal average diameter of 3 mm is generally considered as a positive SPT cut-off value and an equivalent HEP-index area cut-off value of 0.4 was calculated. The four SPT methods yielded a comparable area under the curve (AUC) of 0.84, 0.85, 0.83 and 0.83, respectively. The four methods showed comparable accuracy in predicting cashew nut reactions in a DBPCFC. The 'scanned area method' is theoretically more accurate in determining the wheal area than the 'average diameter method' and is recommended in academic research. A HEP-index area of 0.4 is determined as cut-off value for a positive SPT. However, in clinical practice, the 'average diameter method' is also useful, because this method provides similar accuracy in predicting cashew nut allergic reactions in the DBPCFC. Trial number NTR3572.

Optimization of rotamers prior to template minimization improves stability predictions made by computational protein design.

PubMed

Davey, James A; Chica, Roberto A

2015-04-01

Computational protein design (CPD) predictions are highly dependent on the structure of the input template used. However, it is unclear how small differences in template geometry translate to large differences in stability prediction accuracy. Herein, we explored how structural changes to the input template affect the outcome of stability predictions by CPD. To do this, we prepared alternate templates by Rotamer Optimization followed by energy Minimization (ROM) and used them to recapitulate the stability of 84 protein G domain β1 mutant sequences. In the ROM process, side-chain rotamers for wild-type (WT) or mutant sequences are optimized on crystal or nuclear magnetic resonance (NMR) structures prior to template minimization, resulting in alternate structures termed ROM templates. We show that use of ROM templates prepared from sequences known to be stable results predominantly in improved prediction accuracy compared to using the minimized crystal or NMR structures. Conversely, ROM templates prepared from sequences that are less stable than the WT reduce prediction accuracy by increasing the number of false positives. These observed changes in prediction outcomes are attributed to differences in side-chain contacts made by rotamers in ROM templates. Finally, we show that ROM templates prepared from sequences that are unfolded or that adopt a nonnative fold result in the selective enrichment of sequences that are also unfolded or that adopt a nonnative fold, respectively. Our results demonstrate the existence of a rotamer bias caused by the input template that can be harnessed to skew predictions toward sequences displaying desired characteristics. © 2014 The Protein Society.

Asymmetric bagging and feature selection for activities prediction of drug molecules.

PubMed

Li, Guo-Zheng; Meng, Hao-Hua; Lu, Wen-Cong; Yang, Jack Y; Yang, Mary Qu

2008-05-28

Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cycle by employing the traditional experimental method. With the fact that the number of drug molecules with positive activity is rather fewer than that of negatives, it is important to predict molecular activities considering such an unbalanced situation. Here, asymmetric bagging and feature selection are introduced into the problem and asymmetric bagging of support vector machines (asBagging) is proposed on predicting drug activities to treat the unbalanced problem. At the same time, the features extracted from the structures of drug molecules affect prediction accuracy of QSAR models. Therefore, a novel algorithm named PRIFEAB is proposed, which applies an embedded feature selection method to remove redundant and irrelevant features for asBagging. Numerical experimental results on a data set of molecular activities show that asBagging improve the AUC and sensitivity values of molecular activities and PRIFEAB with feature selection further helps to improve the prediction ability. Asymmetric bagging can help to improve prediction accuracy of activities of drug molecules, which can be furthermore improved by performing feature selection to select relevant features from the drug molecules data sets.

Confidence Testing for Knowledge-Based Global Communities

ERIC Educational Resources Information Center

Jack, Brady Michael; Liu, Chia-Ju; Chiu, Houn-Lin; Shymansky, James A.

2009-01-01

This proposal advocates the position that the use of confidence wagering (CW) during testing can predict the accuracy of a student's test answer selection during between-subject assessments. Data revealed female students were more favorable to taking risks when making CW and less inclined toward risk aversion than their male counterparts. Student…

Confidence Wagering during Mathematics and Science Testing

ERIC Educational Resources Information Center

Jack, Brady Michael; Liu, Chia-Ju; Chiu, Hoan-Lin; Shymansky, James A.

2009-01-01

This proposal presents the results of a case study involving five 8th grade Taiwanese classes, two mathematics and three science classes. These classes used a new method of testing called confidence wagering. This paper advocates the position that confidence wagering can predict the accuracy of a student's test answer selection during…

Accuracy of the prostate health index versus the urinary prostate cancer antigen 3 score to predict overall and significant prostate cancer at initial biopsy.

PubMed

Seisen, Thomas; Rouprêt, Morgan; Brault, Didier; Léon, Priscilla; Cancel-Tassin, Géraldine; Compérat, Eva; Renard-Penna, Raphaële; Mozer, Pierre; Guechot, Jérome; Cussenot, Olivier

2015-01-01

It remains unclear whether the Prostate Health Index (PHI) or the urinary Prostate-Cancer Antigen 3 (PCA-3) score is more accurate at screening for prostate cancer (PCa). The aim of this study was to prospectively compare the accuracy of PHI and PCA-3 scores to predict overall and significant PCa in men undergoing an initial prostate biopsy. Double-blind assessments of PHI and PCA-3 were conducted by referent physicians in 138 patients who subsequently underwent trans-rectal ultrasound-guided prostate biopsy according to a 12-core scheme. Predictive accuracies of PHI and PCA-3 were assessed using AUC and compared according to the DeLong method. Diagnostic performances with usual cut-off values for positivity (i.e., PHI >40 and PCA-3 >35) were calculated, and odds ratios associated with predicting PCa overall and significant PCa as defined by pathological updated Epstein criteria (i.e., Gleason score ≥7, more than three positive cores, or >50% cancer involvement in any core) were estimated using logistic regression. Prevalences of overall and significant PCa were 44.9% and 28.3%, respectively. PCA-3 (AUC = 0.71) was the most accurate predictor of PCa overall, and significantly outperformed PHI (AUC = 0.65; P = 0.03). However, PHI (AUC = 0.80) remained the most accurate predictor when screening exclusively for significant PCa and significantly outperformed PCA-3 (AUC = 0.55; P = 0.03). Furthermore, PCA-3 >35 had the best accuracy, and positive or negative predictive values when screening for PCa overall whereas these diagnostic performances were greater for PHI >40 when exclusively screening for significant PCa. PHI > 40 combined with PCA-3 > 35 was more specific in both cases. In multivariate analyses, PCA-3 >35 (OR = 5.68; 95%CI = [2.21-14.59]; P < 0.001) was significantly correlated with the presence of PCa overall, but PHI >40 (OR = 9.60; 95%CI = [1.72-91.32]; P = 0.001) was the only independent predictor for detecting significant PCa. Although PCA-3 score is the best predictor for PCa overall at initial biopsy, our findings strongly indicate that PHI should be used for population-based screening to avoid over-diagnosis of indolent tumors that are unlikely to cause death. © 2014 Wiley Periodicals, Inc.

Outcomes analysis of new entrant screening for active tuberculosis in Heathrow and Gatwick airports, United Kingdom 2009/2010.

PubMed

Severi, Ettore; Maguire, Helen; Ihekweazu, Chikwe; Bickler, Graham; Abubakar, Ibrahim

2016-04-22

In 2012, the United Kingdom (UK) Government announced that the new entrant screening for active tuberculosis (TB) in Heathrow and Gatwick airports would end. Our study objective was to estimate screening yield and diagnostic accuracy, and identify those at risk of active TB after entry. We designed a retrospective cohort study and linked new entrants screened from June 2009 to September 2010 through probabilistic matching with UK Enhanced TB Surveillance (ETS) data (June 2009 to December 2010). Yield was the proportion of cases reported to ETS within three months of airport screening in the screened population. To estimate screening diagnostic accuracy we assessed sensitivity, specificity, positive and negative predictive values. Through Poisson regression we identified groups at increased risk of TB diagnosis after entry. We identified 200,199 screened entrants, of these 59 had suspected TB at screening and were reported within 3 months to ETS (yield = 0.03 %). Sensitivity was 26 %; specificity was 99.7 %; positive predictive value was 13.2 %; negative predictive value was 99.9 %. Overall, 350 entrants were reported in ETS. Persons from countries with annual TB incidence higher than 150 cases per 100,000 population and refugees and asylum seekers were at increased risk of TB diagnosis after entry (population attributable risk 77 and 3 % respectively). Airport screening has very low screening yields, sensitivity and positive predictive value. New entrants coming from countries with annual TB incidence higher than 150 per 100,000 population, refugees and asylum seekers should be prioritised at pre- or post-entry screening.

Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.

PubMed

Gao, Yu-Fei; Li, Bi-Qing; Cai, Yu-Dong; Feng, Kai-Yan; Li, Zhan-Dong; Jiang, Yang

2013-01-27

Identification of catalytic residues plays a key role in understanding how enzymes work. Although numerous computational methods have been developed to predict catalytic residues and active sites, the prediction accuracy remains relatively low with high false positives. In this work, we developed a novel predictor based on the Random Forest algorithm (RF) aided by the maximum relevance minimum redundancy (mRMR) method and incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility to predict active sites of enzymes and achieved an overall accuracy of 0.885687 and MCC of 0.689226 on an independent test dataset. Feature analysis showed that every category of the features except disorder contributed to the identification of active sites. It was also shown via the site-specific feature analysis that the features derived from the active site itself contributed most to the active site determination. Our prediction method may become a useful tool for identifying the active sites and the key features identified by the paper may provide valuable insights into the mechanism of catalysis.

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

Diagnostic accuracy of loop-mediated isothermal amplification (LAMP) for screening patients with imported malaria in a non-endemic setting

PubMed Central

Ponce, Camille; Kaczorowski, Flora; Perpoint, Thomas; Miailhes, Patrick; Sigal, Alain; Javouhey, Etienne; Gillet, Yves; Jacquin, Laurent; Douplat, Marion; Tazarourte, Karim; Potinet, Véronique; Simon, Bruno; Lavoignat, Adeline; Bonnot, Guillaume; Sow, Fatimata; Bienvenu, Anne-Lise; Picot, Stéphane

2017-01-01

Background: Sensitive and easy-to-perform methods for the diagnosis of malaria are not yet available. Improving the limit of detection and following the requirements for certification are issues to be addressed in both endemic and non-endemic settings. The aim of this study was to test whether loop-mediated isothermal amplification of DNA (LAMP) may be an alternative to microscopy or real-time PCR for the screening of imported malaria cases in non-endemic area. Results: 310 blood samples associated with 829 suspected cases of imported malaria were tested during a one year period. Microscopy (thin and thick stained blood slides, reference standard) was used for the diagnosis. Real-time PCR was used as a standard of truth, and LAMP (Meridian Malaria Plus) was used as an index test in a prospective study conducted following the Standards for Reporting Diagnosis Accuracy Studies. In the 83 positive samples, species identification was P. falciparum (n = 66), P. ovale (n = 9), P. vivax (n = 3) P. malariae (n = 3) and 2 co-infections with P. falciparum + P.malariae. Using LAMP methods, 93 samples gave positive results, including 4 false-positives. Sensitivity, specificity, positive predictive value and negative predictive value for LAMP tests were 100%, 98.13%, 95.51%, and 100% compared to PCR. Conclusion: High negative predictive value, and limit of detection suggest that LAMP can be used for screening of imported malaria cases in non-endemic countries when expert microscopists are not immediately available. However, the rare occurrence of non-valid results and the need for species identification and quantification of positive samples preclude the use of LAMP as a single reference method. PMID:29251261

Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.

PubMed

Zhao, Xiaowei; Ning, Qiao; Chai, Haiting; Ma, Zhiqiang

2015-06-07

As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimental approaches, computational predictions of succinylation sites are much desirable due to their convenient and fast speed. Currently, numerous computational models have been developed to identify PTMs sites through various types of two-class machine learning algorithms. These methods require both positive and negative samples for training. However, designation of the negative samples of PTMs was difficult and if it is not properly done can affect the performance of computational models dramatically. So that in this work, we implemented the first application of positive samples only learning (PSoL) algorithm to succinylation sites prediction problem, which was a special class of semi-supervised machine learning that used positive samples and unlabeled samples to train the model. Meanwhile, we proposed a novel succinylation sites computational predictor called SucPred (succinylation site predictor) by using multiple feature encoding schemes. Promising results were obtained by the SucPred predictor with an accuracy of 88.65% using 5-fold cross validation on the training dataset and an accuracy of 84.40% on the independent testing dataset, which demonstrated that the positive samples only learning algorithm presented here was particularly useful for identification of protein succinylation sites. Besides, the positive samples only learning algorithm can be applied to build predictors for other types of PTMs sites with ease. A web server for predicting succinylation sites was developed and was freely accessible at http://59.73.198.144:8088/SucPred/. Copyright © 2015 Elsevier Ltd. All rights reserved.

JPL's GNSS Real-Time Earthquake and Tsunami (GREAT) Alert System

NASA Astrophysics Data System (ADS)

Bar-Sever, Yoaz; Miller, Mark; Vallisneri, Michele; Khachikyan, Robert; Meyer, Robert

2017-04-01

We describe recent developments to the GREAT Alert natural hazard monitoring service from JPL's Global Differential GPS (GDGPS) System. GREAT Alert provides real-time, 1 Hz positioning solutions for hundreds of GNSS tracking sites, from both global and regional networks, aiming to monitor ground motion in the immediate aftermath of earthquakes. We take advantage of the centralized data processing, which is collocated with the GNSS orbit determination operations of the GDGPS System, to combine orbit determination with large-scale point-positioning in a grand estimation scheme, and as a result realize significant improvement to the positioning accuracy compared to conventional stand-alone point positioning techniques. For example, the measured median site (over all sites) real-time horizontal positioning accuracy is 2 cm 1DRMS, and the median real-time vertical accuracy is 4 cm RMS. The GREAT Alert positioning service is integrated with automated global earthquake notices from the United States Geodetic Survey (USGS) to support near-real-time calculations of co-seismic displacements with attendant formal errors based both short-term and long-term error analysis for each individual site. We will show the millimeter-level resolution of co-seismic displacement can be achieved by this system. The co-seismic displacements, in turn, are fed into a JPL geodynamics and ocean models, that estimate the Earthquake magnitude and predict the potential tsunami scale.

Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction.

PubMed

Zhou, Yao; Vales, M Isabel; Wang, Aoxue; Zhang, Zhiwu

2017-09-01

Accuracy of genomic prediction is commonly calculated as the Pearson correlation coefficient between the predicted and observed phenotypes in the inference population by using cross-validation analysis. More frequently than expected, significant negative accuracies of genomic prediction have been reported in genomic selection studies. These negative values are surprising, given that the minimum value for prediction accuracy should hover around zero when randomly permuted data sets are analyzed. We reviewed the two common approaches for calculating the Pearson correlation and hypothesized that these negative accuracy values reflect potential bias owing to artifacts caused by the mathematical formulas used to calculate prediction accuracy. The first approach, Instant accuracy, calculates correlations for each fold and reports prediction accuracy as the mean of correlations across fold. The other approach, Hold accuracy, predicts all phenotypes in all fold and calculates correlation between the observed and predicted phenotypes at the end of the cross-validation process. Using simulated and real data, we demonstrated that our hypothesis is true. Both approaches are biased downward under certain conditions. The biases become larger when more fold are employed and when the expected accuracy is low. The bias of Instant accuracy can be corrected using a modified formula. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

GPS Satellite Orbit Prediction at User End for Real-Time PPP System.

PubMed

Yang, Hongzhou; Gao, Yang

2017-08-30

This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth's gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge-Kutta and multi-step Adams-Bashforth-Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively.

GPS Satellite Orbit Prediction at User End for Real-Time PPP System

PubMed Central

Yang, Hongzhou; Gao, Yang

2017-01-01

This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth’s gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge–Kutta and multi-step Adams–Bashforth–Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively. PMID:28867771

Application and analysis of debris-flow early warning system in Wenchuan earthquake-affected area

NASA Astrophysics Data System (ADS)

Liu, D. L.; Zhang, S. J.; Yang, H. J.; Zhao, L. Q.; Jiang, Y. H.; Tang, D.; Leng, X. P.

2016-02-01

The activities of debris flow (DF) in the Wenchuan earthquake-affected area significantly increased after the earthquake on 12 May 2008. The safety of the lives and property of local people is threatened by DFs. A physics-based early warning system (EWS) for DF forecasting was developed and applied in this earthquake area. This paper introduces an application of the system in the Wenchuan earthquake-affected area and analyzes the prediction results via a comparison to the DF events triggered by the strong rainfall events reported by the local government. The prediction accuracy and efficiency was first compared with a contribution-factor-based system currently used by the weather bureau of Sichuan province. The storm on 17 August 2012 was used as a case study for this comparison. The comparison shows that the false negative rate and false positive rate of the new system is, respectively, 19 and 21 % lower than the system based on the contribution factors. Consequently, the prediction accuracy is obviously higher than the system based on the contribution factors with a higher operational efficiency. On the invitation of the weather bureau of Sichuan province, the authors upgraded their prediction system of DF by using this new system before the monsoon of Wenchuan earthquake-affected area in 2013. Two prediction cases on 9 July 2013 and 10 July 2014 were chosen to further demonstrate that the new EWS has high stability, efficiency, and prediction accuracy.

Comparing Magnetic Resonance Imaging and High-Resolution Dynamic Ultrasonography for Diagnosis of Plantar Plate Pathology: A Case Series.

PubMed

Donegan, Ryan J; Stauffer, Anthony; Heaslet, Michael; Poliskie, Michael

Plantar plate pathology has gained noticeable attention in recent years as an etiology of lesser metatarsophalangeal joint pain. The heightened clinical awareness has led to the need for more effective diagnostic imaging accuracy. Numerous reports have established the accuracy of both magnetic resonance imaging and ultrasonography for the diagnosis of plantar plate pathology. However, no conclusions have been made regarding which is the superior imaging modality. The present study reports a case series directly comparing high-resolution dynamic ultrasonography and magnetic resonance imaging. A multicenter retrospective comparison of magnetic resonance imaging versus high-resolution dynamic ultrasonography to evaluate plantar plate pathology with surgical confirmation was conducted. The sensitivity, specificity, and positive and negative predictive values for magnetic resonance imaging were 60%, 100%, 100%, and 33%, respectively. The overall diagnostic accuracy compared with the intraoperative findings was 66%. The sensitivity, specificity, and positive and negative predictive values for high-resolution dynamic ultrasound imaging were 100%, 100%, 100%, and 100%, respectively. The overall diagnostic accuracy compared with the intraoperative findings was 100%. The p value using Fisher's exact test for magnetic resonance imaging and high-resolution dynamic ultrasonography was p = .45, a difference that was not statistically significant. High-resolution dynamic ultrasonography had greater accuracy than magnetic resonance imaging in diagnosing lesser metatarsophalangeal joint plantar plate pathology, although the difference was not statistically significant. The present case series suggests that high-resolution dynamic ultrasonography can be considered an equally accurate imaging modality for plantar plate pathology at a potential cost savings compared with magnetic resonance imaging. Therefore, high-resolution dynamic ultrasonography warrants further investigation in a prospective study. Copyright © 2016 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

A meta-analysis of use of Prostate Imaging Reporting and Data System Version 2 (PI-RADS V2) with multiparametric MR imaging for the detection of prostate cancer.

PubMed

Zhang, Li; Tang, Min; Chen, Sipan; Lei, Xiaoyan; Zhang, Xiaoling; Huan, Yi

2017-12-01

This meta-analysis was undertaken to review the diagnostic accuracy of PI-RADS V2 for prostate cancer (PCa) detection with multiparametric MR (mp-MR). A comprehensive literature search of electronic databases was performed by two observers independently. Inclusion criteria were original research using the PI-RADS V2 system in reporting prostate MRI. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Data necessary to complete 2 × 2 contingency tables were obtained from the included studies. Thirteen studies (2,049 patients) were analysed. This is an initial meta-analysis of PI-RADs V2 and the overall diagnostic accuracy in diagnosing PCa was as follows: pooled sensitivity, 0.85 (0.78-0.91); pooled specificity, 0.71 (0.60-0.80); pooled positive likelihood ratio (LR+), 2.92 (2.09-4.09); pooled negative likelihood ratio (LR-), 0.21 (0.14-0.31); pooled diagnostic odds ratio (DOR), 14.08 (7.93-25.01), respectively. Positive predictive values ranged from 0.54 to 0.97 and negative predictive values ranged from 0.26 to 0.92. Currently available evidence indicates that PI-RADS V2 appears to have good diagnostic accuracy in patients with PCa lesions with high sensitivity and moderate specificity. However, no recommendation regarding the best threshold can be provided because of heterogeneity. • PI-RADS V2 shows good diagnostic accuracy for PCa detection. • Initially pooled specificity of PI-RADS v2 remains moderate. • PCa detection is increased by experienced radiologists. • There is currently a high heterogeneity in prostate diagnostics with MRI.

Diagnostic accuracy of bedside swallow evaluation versus videofluoroscopy to assess dysphagia in individuals with tetraplegia.

PubMed

Shem, Kazuko L; Castillo, Kathleen; Wong, Sandra Lynn; Chang, James; Kao, Ming-Chih; Kolakowsky-Hayner, Stephanie A

2012-04-01

To assess the accuracy of bedside swallow evaluation (BSE) compared with videofluorosopic swallow study (VFSS) in diagnosing dysphagia in individuals with tetraplegia due to spinal cord injury (SCI). A prospective diagnostic accuracy study according to STAndards for the Reporting of Diagnostic accuracy studies (STARD) criteria. A county hospital with acute inpatient SCI unit. Thirty-nine subjects with SCI and tetraplegia were enrolled. All of the subjects underwent BSE, and 26 subjects completed the VFSS. Individuals with SCI underwent a BSE followed by a VFSS within 72 hours of the BSE. The subjects were diagnosed as having dysphagia if they had positive findings in either BSE or VFSS. Sensitivity, specificity, and positive and negative predictive values were calculated by using VFSS as the criterion standard. Fifteen subjects (38%) were diagnosed as having dysphagia based on the BSE results. Among the subjects who completed the VFSS, 11 were diagnosed with dysphagia (42%) and 4 were diagnosed with aspiration (10%). Of the 26 subjects who completed both BSE and VFSS, only 1 subject was diagnosed differently compared with BSE (3.8%). Different diet recommendations were made in 4 cases after VFSS versus BSE. Different liquid recommendations were made in 8 cases after VFSS versus BSE. Sensitivity of BSE was 100% (95% confidence interval [CI], 71.5%-100%), specificity was 93.3% (95% CI, 68.1%-99.8%). A positive predictive value of BSE was 91.7% (95% CI, 61.5%-100%), and the negative predictive value was 100% (95% CI, 76.8%-100%). Dysphagia is present in approximately 38% of individuals with acute tetraplegia. Because only one of the 21 subjects was diagnosed differently based on VFSS, we believe that BSE is an appropriate screening tool for dysphagia for individuals with cervical SCI. However, VFSS provided additional information on diet and liquid recommendations, so there appears to be an important clinical role for the VFSS. Copyright © 2012 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Assessing the accuracy of predictive models for numerical data: Not r nor r2, why not? Then what?

PubMed Central

2017-01-01

Assessing the accuracy of predictive models is critical because predictive models have been increasingly used across various disciplines and predictive accuracy determines the quality of resultant predictions. Pearson product-moment correlation coefficient (r) and the coefficient of determination (r2) are among the most widely used measures for assessing predictive models for numerical data, although they are argued to be biased, insufficient and misleading. In this study, geometrical graphs were used to illustrate what were used in the calculation of r and r2 and simulations were used to demonstrate the behaviour of r and r2 and to compare three accuracy measures under various scenarios. Relevant confusions about r and r2, has been clarified. The calculation of r and r2 is not based on the differences between the predicted and observed values. The existing error measures suffer various limitations and are unable to tell the accuracy. Variance explained by predictive models based on cross-validation (VEcv) is free of these limitations and is a reliable accuracy measure. Legates and McCabe’s efficiency (E1) is also an alternative accuracy measure. The r and r2 do not measure the accuracy and are incorrect accuracy measures. The existing error measures suffer limitations. VEcv and E1 are recommended for assessing the accuracy. The applications of these accuracy measures would encourage accuracy-improved predictive models to be developed to generate predictions for evidence-informed decision-making. PMID:28837692

Accuracy of ultrasonography and magnetic resonance imaging in the diagnosis of placenta accreta.

PubMed

Riteau, Anne-Sophie; Tassin, Mikael; Chambon, Guillemette; Le Vaillant, Claudine; de Laveaucoupet, Jocelyne; Quéré, Marie-Pierre; Joubert, Madeleine; Prevot, Sophie; Philippe, Henri-Jean; Benachi, Alexandra

2014-01-01

To evaluate the accuracy of ultrasonography and magnetic resonance imaging (MRI) in the diagnosis of placenta accreta and to define the most relevant specific ultrasound and MRI features that may predict placental invasion. This study was approved by the institutional review board of the French College of Obstetricians and Gynecologists. We retrospectively reviewed the medical records of all patients referred for suspected placenta accreta to two university hospitals from 01/2001 to 05/2012. Our study population included 42 pregnant women who had been investigated by both ultrasonography and MRI. Ultrasound images and MRI were blindly reassessed for each case by 2 raters in order to score features that predict abnormal placental invasion. Sensitivity in the diagnosis of placenta accreta was 100% with ultrasound and 76.9% for MRI (P = 0.03). Specificity was 37.5% with ultrasonography and 50% for MRI (P = 0.6). The features of greatest sensitivity on ultrasonography were intraplacental lacunae and loss of the normal retroplacental clear space. Increased vascularization in the uterine serosa-bladder wall interface and vascularization perpendicular to the uterine wall had the best positive predictive value (92%). At MRI, uterine bulging had the best positive predictive value (85%) and its combination with the presence of dark intraplacental bands on T2-weighted images improved the predictive value to 90%. Ultrasound imaging is the mainstay of screening for placenta accreta. MRI appears to be complementary to ultrasonography, especially when there are few ultrasound signs.

Predictive values of thermal and electrical dental pulp tests: a clinical study.

PubMed

Villa-Chávez, Carlos E; Patiño-Marín, Nuria; Loyola-Rodríguez, Juan P; Zavala-Alonso, Norma V; Martínez-Castañón, Gabriel A; Medina-Solís, Carlo E

2013-08-01

For a diagnostic test to be useful, it is necessary to determine the probability that the test will provide the correct diagnosis. Therefore, it is necessary to calculate the predictive value of diagnostics. The aim of the present study was to identify the sensitivity, specificity, positive and negative predictive values, accuracy, and reproducibility of thermal and electrical tests of pulp sensitivity. The thermal tests studied were the 1, 1, 1, 2-tetrafluoroethane (cold) and hot gutta-percha (hot) tests. For the electrical test, the Analytic Technology Pulp Tester (Analytic Technology, Redmond, WA) was used. A total of 110 teeth were tested: 60 teeth with vital pulp and 50 teeth with necrotic pulps (disease prevalence of 45%). The ideal standard was established by direct pulp inspection. The sensitivities of the diagnostic tests were 0.88 for the cold test, 0.86 for the heat test, and 0.76 for the electrical test, and the specificity was 1.0 for all 3 tests. The negative predictive value was 0.90 for the cold test, 0.89 for the heat test, and 0.83 for the electrical test, and the positive predictive value was 1.0 for all 3 tests. The highest accuracy (0.94) and reproducibility (0.88) were observed for the cold test. The cold test was the most accurate method for diagnostic testing. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Meta-accuracy and relationship quality: Weighing the costs and benefits of knowing what people really think about you.

PubMed

Carlson, Erika N

2016-08-01

People use metaperceptions, or their beliefs about how other people perceive them, to initiate and maintain social bonds. Are accurate metaperceptions associated with higher quality relationships? In four studies, the current research answers this question but considers the possibility that the self might not experience the same relational benefits of accurate metaperceptions, or meta-accuracy, as the people who form judgments about the self. For example, people tend to like individuals who have accurate self-perceptions, yet individuals tend to enjoy their own relationships more with people they believe see them in desirable ways. To test whether meta-accuracy is linked to relationship quality and whether this link differs for the self and others, meta-accuracy for personality traits as well as metaperceiver- and judge-reported relationship quality were assessed among new acquaintances (N = 184), peers (N = 228), friends (N = 273), and romantic partners (N = 401). Results suggested that judges enjoyed relationships more with metaperceivers who knew the impression they made, regardless of whether judges' impressions were desirable (i.e., positive or self-verifying). Initial meta-accuracy also predicted greater relationship quality over time, suggesting that accurate metaperceptions have positive effects on relationships. In contrast, rather than enjoying relationships more when they were accurate, metaperceivers enjoyed relationships more when they believed judges perceived them in positive or self-verifying ways. Thus, meta-accuracy seems to be a virtue in the eyes of judges, but metaperceivers do not seem to reap the same benefits of knowing what others really think. Implications for improving meta-accuracy are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes

PubMed Central

Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

2015-01-01

In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. PMID:25977299

Perendoscopic gastric pH determination. Simple method for increasing accuracy in diagnosing chronic atrophic gastritis.

PubMed

Farinati, F; Cardin, F; Di Mario, F; Sava, G A; Piccoli, A; Costa, F; Penon, G; Naccarato, R

1987-08-01

The endoscopic diagnosis of chronic atrophic gastritis is often underestimated, and most of the procedures adopted to increase diagnostic accuracy are time consuming and complex. In this study, we evaluated the usefulness of the determination of gastric juice pH by means of litmus paper. Values obtained by this method correlate well with gastric acid secretory capacity as measured by gastric acid analysis (r = -0.64, p less than 0.001) and are not affected by the presence of bile. Gastric juice pH determination increases sensitivity and other diagnostic parameters such as performance index (Youden J test), positive predictive value, and post-test probability difference by 50%. Furthermore, the negative predictive value is very high, the probability of missing a patient with chronic atrophic gastritis with this simple method being 2% for fundic and 15% for antral atrophic change. We conclude that gastric juice pH determination, which substantially increases diagnostic accuracy and is very simple to perform, should be routinely adopted.

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Slojkowski, Steven; Lowe, Jonathan; Woodburn, James

2015-01-01

Since launch, the FDF has performed daily OD for LRO using the Goddard Trajectory Determination System (GTDS). GTDS is a batch least-squares (BLS) estimator. The tracking data arc for OD is 36 hours. Current operational OD uses 200 x 200 lunar gravity, solid lunar tides, solar radiation pressure (SRP) using a spherical spacecraft area model, and point mass gravity for the Earth, Sun, and Jupiter. LRO tracking data consists of range and range-rate measurements from: Universal Space Network (USN) stations in Sweden, Germany, Australia, and Hawaii. A NASA antenna at White Sands, New Mexico (WS1S). NASA Deep Space Network (DSN) stations. DSN data was sparse and not included in this study. Tracking is predominantly (50) from WS1S. The OD accuracy requirements are: Definitive ephemeris accuracy of 500 meters total position root-mean-squared (RMS) and18 meters radial RMS. Predicted orbit accuracy less than 800 meters root sum squared (RSS) over an 84-hour prediction span.

Factors involved in making post-performance judgments in mathematics problem-solving.

PubMed

García Fernández, Trinidad; Kroesbergen, Evelyn; Rodríguez Pérez, Celestino; González-Castro, Paloma; González-Pienda, Julio A

2015-01-01

This study examines the impact of executive functions, affective-motivational variables related to mathematics, mathematics achievement and task characteristics on fifth and sixth graders’ calibration accuracy after completing two mathematical problems. A sample of 188 students took part in the study. They were divided into two groups as function of their judgment accuracy after completing the two tasks (accurate= 79, inaccurate= 109). Differences between these groups were examined. The discriminative value of these variables to predict group membership was analyzed, as well as the effect of age, gender, and grade level. The results indicated that accurate students showed better levels of executive functioning, and more positive feelings, beliefs, and motivation related to mathematics. They also spent more time on the tasks. Mathematics achievement, perceived usefulness of mathematics, and time spent on Task 1 significantly predicted group membership, classifying 71.3% of the sample correctly. These results support the relationship between academic achievement and calibration accuracy, suggesting the need to consider a wide range of factors when explaining performance judgments.

[Study of beta-turns in globular proteins].

PubMed

Amirova, S R; Milchevskiĭ, Iu V; Filatov, I V; Esipova, N G; Tumanian, V G

2005-01-01

The formation of beta-turns in globular proteins has been studied by the method of molecular mechanics. Statistical method of discriminant analysis was applied to calculate energy components and sequences of oligopeptide segments, and after this prediction of I type beta-turns has been drawn. The accuracy of true positive prediction is 65%. Components of conformational energy considerably affecting beta-turn formation were delineated. There are torsional energy, energy of hydrogen bonds, and van der Waals energy.

Cytological Sampling Versus Forceps Biopsy During Percutaneous Transhepatic Biliary Drainage and Analysis of Factors Predicting Success

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

Tapping, C. R.; Byass, O. R.; Cast, J. E. I., E-mail: james.cast@hey.nhs.uk

Purpose: To assess the accuracy of cytological sampling and forceps biopsy in obstructing biliary lesions and to identify factors predictive of success. Methods: Consecutive patients (n = 119) with suspected malignant inoperable obstructive jaundice treated with percutaneous transhepatic biliary drainage during 7 years were included (60 male; mean age 72.5 years). All patients underwent forceps biopsy plus cytological sampling by washing the forceps device in cytological solution. Patient history, procedural and pathological records, and clinical follow-up were reviewed. Statistical analysis included chi-square test and multivariate regression analysis. Results: Histological diagnosis after forceps biopsy was more successful than cytology: Sensitivity wasmore » 78 versus 61%, and negative predictive value was 30 versus 19%. Cytology results were never positive when the forceps biopsy was negative. The cytological sample was negative and forceps sample positive in 2 cases of cholangiocarcinoma, 16 cases of pancreatic carcinoma, and 1 case of benign disease. Diagnostic accuracy was predicted by low bilirubin (p < 0.001), aspartate transaminase (p < 0.05), and white cell count (p {<=} 0.05). Conclusions: This technique is safe and effective and is recommended for histological diagnosis during PTBD in patients with inoperable malignant biliary strictures. Diagnostic yield is greater when bilirubin levels are low and there is no sepsis; histological diagnosis by way of forceps biopsy renders cytological sampling unnecessary.« less

Role of ascitic fluid adenosine deaminase (ADA) and serum CA-125 in the diagnosis of tuberculous peritonitis.

PubMed

Ali, N; Nath, N C; Parvin, R; Rahman, A; Bhuiyan, T M; Rahman, M; Mohsin M N

2014-12-01

This cross sectional study was carried out in the department of gastroenterology, BIRDEM, Dhaka from January 2010 to May 2011 to determine the role of ascitic fluid ADA and serum CA-125 in the diagnosis of clinically suspected tubercular peritonitis. Total 30 patients (age 39.69 ± 21.26, 18M/12F) with clinical suspicion of tuberculosis peritonitis were included in this study after analyzing selection criteria. Laparoscopic peritoneal biopsy with 'histopathological diagnosis' was considered gold standard against which accuracics of two biomarkers (ADA & CA-125) were compared. Cut off value of ADA and CA-125 are 24 u/l, 35 U/ml respectively. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of ADA as a diagnostic modality in tuberculos peritonitis were 87.5%, 83.33%, 95.45%, 62.5% and 86.67% respectively where as CA-125 was found to have 83.33% sensitivity, 50% specificity, 86.9% positive predictive value, 42.85% negative predictive value and 76.6% accuracy. Both biomarkers are simple, non-invasive, rapid and relatively cheap diagnostic test where as laparoscopy is an invasive procedure, costly & requires trained staff and not without risk and also not feasible in all the centre in our country. So ascitic fluid ADA and serum CA-125 are important diagnostic test for peritoneal tuberculosis.

Patterns and predictors of skin score change in early diffuse systemic sclerosis from the European Scleroderma Observational Study.

PubMed

Herrick, Ariane L; Peytrignet, Sebastien; Lunt, Mark; Pan, Xiaoyan; Hesselstrand, Roger; Mouthon, Luc; Silman, Alan J; Dinsdale, Graham; Brown, Edith; Czirják, László; Distler, Jörg H W; Distler, Oliver; Fligelstone, Kim; Gregory, William J; Ochiel, Rachel; Vonk, Madelon C; Ancuţa, Codrina; Ong, Voon H; Farge, Dominique; Hudson, Marie; Matucci-Cerinic, Marco; Balbir-Gurman, Alexandra; Midtvedt, Øyvind; Jobanputra, Paresh; Jordan, Alison C; Stevens, Wendy; Moinzadeh, Pia; Hall, Frances C; Agard, Christian; Anderson, Marina E; Diot, Elisabeth; Madhok, Rajan; Akil, Mohammed; Buch, Maya H; Chung, Lorinda; Damjanov, Nemanja S; Gunawardena, Harsha; Lanyon, Peter; Ahmad, Yasmeen; Chakravarty, Kuntal; Jacobsen, Søren; MacGregor, Alexander J; McHugh, Neil; Müller-Ladner, Ulf; Riemekasten, Gabriela; Becker, Michael; Roddy, Janet; Carreira, Patricia E; Fauchais, Anne Laure; Hachulla, Eric; Hamilton, Jennifer; İnanç, Murat; McLaren, John S; van Laar, Jacob M; Pathare, Sanjay; Proudman, Susanna M; Rudin, Anna; Sahhar, Joanne; Coppere, Brigitte; Serratrice, Christine; Sheeran, Tom; Veale, Douglas J; Grange, Claire; Trad, Georges-Selim; Denton, Christopher P

2018-04-01

Our aim was to use the opportunity provided by the European Scleroderma Observational Study to (1) identify and describe those patients with early diffuse cutaneous systemic sclerosis (dcSSc) with progressive skin thickness, and (2) derive prediction models for progression over 12 months, to inform future randomised controlled trials (RCTs). The modified Rodnan skin score (mRSS) was recorded every 3 months in 326 patients. 'Progressors' were defined as those experiencing a 5-unit and 25% increase in mRSS score over 12 months (±3 months). Logistic models were fitted to predict progression and, using receiver operating characteristic (ROC) curves, were compared on the basis of the area under curve (AUC), accuracy and positive predictive value (PPV). 66 patients (22.5%) progressed, 227 (77.5%) did not (33 could not have their status assessed due to insufficient data). Progressors had shorter disease duration (median 8.1 vs 12.6 months, P=0.001) and lower mRSS (median 19 vs 21 units, P=0.030) than non-progressors. Skin score was highest, and peaked earliest, in the anti-RNA polymerase III (Pol3+) subgroup (n=50). A first predictive model (including mRSS, duration of skin thickening and their interaction) had an accuracy of 60.9%, AUC of 0.666 and PPV of 33.8%. By adding a variable for Pol3 positivity, the model reached an accuracy of 71%, AUC of 0.711 and PPV of 41%. Two prediction models for progressive skin thickening were derived, for use both in clinical practice and for cohort enrichment in RCTs. These models will inform recruitment into the many clinical trials of dcSSc projected for the coming years. NCT02339441. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Real-time tracheal ultrasonography for confirmation of endotracheal tube placement during cardiopulmonary resuscitation.

PubMed

Chou, Hao-Chang; Chong, Kah-Meng; Sim, Shyh-Shyong; Ma, Matthew Huei-Ming; Liu, Shih-Hung; Chen, Nai-Chuan; Wu, Meng-Che; Fu, Chia-Ming; Wang, Chih-Hung; Lee, Chien-Chang; Lien, Wan-Ching; Chen, Shyr-Chyr

2013-12-01

This study aimed to evaluate the accuracy of tracheal ultrasonography for assessing endotracheal tube position during cardiopulmonary resuscitation (CPR). We performed a prospective observational study of patients undergoing emergency intubation during CPR. Real-time tracheal ultrasonography was performed during the intubation with the transducer placed transversely just above the suprasternal notch, to assess for endotracheal tube positioning and exclude esophageal intubation. The position of trachea was identified by a hyperechoic air-mucosa (A-M) interface with posterior reverberation artifact (comet-tail artifact). The endotracheal tube position was defined as endotracheal if single A-M interface with comet-tail artifact was observed. Endotracheal tube position was defined as intraesophageal if a second A-M interface appeared, suggesting a false second airway (double tract sign). The gold standard of correct endotracheal intubation was the combination of clinical auscultation and quantitative waveform capnography. The main outcome was the accuracy of tracheal ultrasonography in assessing endotracheal tube position during CPR. Among the 89 patients enrolled, 7 (7.8%) had esophageal intubations. The sensitivity, specificity, positive predictive value, and negative predictive value of tracheal ultrasonography were 100% (95% confidence interval [CI]: 94.4-100%), 85.7% (95% CI: 42.0-99.2%), 98.8% (95% CI: 92.5-99.0%) and 100% (95% CI: 54.7-100%), respectively. Positive and negative likelihood ratios were 7.0 (95% CI: 1.1-43.0) and 0.0, respectively. Real-time tracheal ultrasonography is an accurate method for identifying endotracheal tube position during CPR without the need for interruption of chest compression. Tracheal ultrasonography in resuscitation management may serve as a powerful adjunct in trained hands. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Novel non-invasive biological predictive index for liver fibrosis in hepatitis C virus genotype 4 patients

PubMed Central

Khattab, Mahmoud; Sakr, Mohamed Amin; Fattah, Mohamed Abdel; Mousa, Youssef; Soliman, Elwy; Breedy, Ashraf; Fathi, Mona; Gaber, Salwa; Altaweil, Ahmed; Osman, Ashraf; Hassouna, Ahmed; Motawea, Ibrahim

2016-01-01

AIM To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy. METHODS A cohort of 332 patients infected with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensin-converting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance (HOMA-IR). RESULTS Fibrosis stages were distributed based on Metavir score as follows: F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis (F0-F) = 179, moderate fibrosis (F2) = 64, and advanced fibrosis (F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage (P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤ -0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were: 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis. CONCLUSION Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy. PMID:27917265

Novel non-invasive biological predictive index for liver fibrosis in hepatitis C virus genotype 4 patients.

PubMed

Khattab, Mahmoud; Sakr, Mohamed Amin; Fattah, Mohamed Abdel; Mousa, Youssef; Soliman, Elwy; Breedy, Ashraf; Fathi, Mona; Gaber, Salwa; Altaweil, Ahmed; Osman, Ashraf; Hassouna, Ahmed; Motawea, Ibrahim

2016-11-18

To investigate the diagnostic ability of a non-invasive biological marker to predict liver fibrosis in hepatitis C genotype 4 patients with high accuracy. A cohort of 332 patients infected with hepatitis C genotype 4 was included in this cross-sectional study. Fasting plasma glucose, insulin, C-peptide, and angiotensin-converting enzyme serum levels were measured. Insulin resistance was mathematically calculated using the homeostasis model of insulin resistance (HOMA-IR). Fibrosis stages were distributed based on Metavir score as follows: F0 = 43, F1 = 136, F2 = 64, F3 = 45 and F4 = 44. Statistical analysis relied upon reclassification of fibrosis stages into mild fibrosis (F0-F) = 179, moderate fibrosis (F2) = 64, and advanced fibrosis (F3-F4) = 89. Univariate analysis indicated that age, log aspartate amino transaminase, log HOMA-IR and log platelet count were independent predictors of liver fibrosis stage ( P < 0.0001). A stepwise multivariate discriminant functional analysis was used to drive a discriminative model for liver fibrosis. Our index used cut-off values of ≥ 0.86 and ≤ -0.31 to diagnose advanced and mild fibrosis, respectively, with receiving operating characteristics of 0.91 and 0.88, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio were: 73%, 91%, 75%, 90% and 8.0 respectively for advanced fibrosis, and 67%, 88%, 84%, 70% and 4.9, respectively, for mild fibrosis. Our predictive model is easily available and reproducible, and predicted liver fibrosis with acceptable accuracy.

Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

PubMed

Dyrba, Martin; Barkhof, Frederik; Fellgiebel, Andreas; Filippi, Massimo; Hausner, Lucrezia; Hauenstein, Karlheinz; Kirste, Thomas; Teipel, Stefan J

2015-01-01

Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI). We applied a Support Vector Machine (SVM) classifier to DTI and volumetric magnetic resonance imaging data from 35 amyloid-β42 negative MCI subjects (MCI-Aβ42-), 35 positive MCI subjects (MCI-Aβ42+), and 25 healthy controls (HC) retrieved from the European DTI Study on Dementia. The SVM was applied to DTI-derived fractional anisotropy, mean diffusivity (MD), and mode of anisotropy (MO) maps. For comparison, we studied classification based on gray matter (GM) and WM volume. We obtained accuracies of up to 68% for MO and 63% for GM volume when it came to distinguishing between MCI-Aβ42- and MCI-Aβ42+. When it came to separating MCI-Aβ42+ from HC we achieved an accuracy of up to 77% for MD and a significantly lower accuracy of 68% for GM volume. The accuracy of multimodal classification was not higher than the accuracy of the best single modality. Our results suggest that DTI data provide better prediction accuracy than GM volume in predementia AD. Copyright © 2015 by the American Society of Neuroimaging.

Coding of position by simultaneously recorded sensory neurones in the cat dorsal root ganglion

PubMed Central

Stein, R B; Weber, D J; Aoyagi, Y; Prochazka, A; Wagenaar, J B M; Shoham, S; Normann, R A

2004-01-01

Muscle, cutaneous and joint afferents continuously signal information about the position and movement of individual joints. How does the nervous system extract more global information, for example about the position of the foot in space? To study this question we used microelectrode arrays to record impulses simultaneously from up to 100 discriminable nerve cells in the L6 and L7 dorsal root ganglia (DRG) of the anaesthetized cat. When the hindlimb was displaced passively with a random trajectory, the firing rate of the neurones could be predicted from a linear sum of positions and velocities in Cartesian (x, y), polar or joint angular coordinates. The process could also be reversed to predict the kinematics of the limb from the firing rates of the neurones with an accuracy of 1–2 cm. Predictions of position and velocity could be combined to give an improved fit to limb position. Decoders trained using random movements successfully predicted cyclic movements and movements in which the limb was displaced from a central point to various positions in the periphery. A small number of highly informative neurones (6–8) could account for over 80% of the variance in position and a similar result was obtained in a realistic limb model. In conclusion, this work illustrates how populations of sensory receptors may encode a sense of limb position and how the firing of even a small number of neurones can be used to decode the position of the limb in space. PMID:15331686

Modeling and controller design of a 6-DOF precision positioning system

NASA Astrophysics Data System (ADS)

Cai, Kunhai; Tian, Yanling; Liu, Xianping; Fatikow, Sergej; Wang, Fujun; Cui, Liangyu; Zhang, Dawei; Shirinzadeh, Bijan

2018-05-01

A key hurdle to meet the needs of micro/nano manipulation in some complex cases is the inadequate workspace and flexibility of the operation ends. This paper presents a 6-degree of freedom (DOF) serial-parallel precision positioning system, which consists of two compact type 3-DOF parallel mechanisms. Each parallel mechanism is driven by three piezoelectric actuators (PEAs), guided by three symmetric T-shape hinges and three elliptical flexible hinges, respectively. It can extend workspace and improve flexibility of the operation ends. The proposed system can be assembled easily, which will greatly reduce the assembly errors and improve the positioning accuracy. In addition, the kinematic and dynamic model of the 6-DOF system are established, respectively. Furthermore, in order to reduce the tracking error and improve the positioning accuracy, the Discrete-time Model Predictive Controller (DMPC) is applied as an effective control method. Meanwhile, the effectiveness of the DMCP control method is verified. Finally, the tracking experiment is performed to verify the tracking performances of the 6-DOF stage.

Short-arc orbit determination using coherent X-band ranging data

NASA Technical Reports Server (NTRS)

Thurman, S. W.; Mcelrath, T. P.; Pollmeier, V. M.

1992-01-01

The use of X-band frequencies in ground-spacecraft and spacecraft-ground telecommunication links for current and future robotic interplanetary missions makes it possible to perform ranging measurements of greater accuracy than previously obtained. It is shown that ranging data of sufficient accuracy, when acquired from multiple stations, can sense the geocentric angular position of a distant spacecraft. The application of high-accuracy S/X-band and X-band ranging to orbit determination with relatively short data arcs is investigated in planetary approach and encounter scenarios. Actual trajectory solutions for the Ulysses spacecraft constructed from S/X-band ranging and Doppler data are presented; error covariance calculations are used to predict the performance of X-band ranging and Doppler data. The Ulysses trajectory solutions indicate that the aim point for the spacecraft's February 1992 Jupiter encounter was predicted to a geocentric accuracy of 0.20 to 0.23/microrad. Explicit modeling of range bias parameters for each station pass is shown to largely remove systematic ground system calibration errors and transmission media effects from the Ulysses range measurements, which would otherwise corrupt the angle finding capabilities of the data. The Ulysses solutions were found to be reasonably consistent with the theoretical results, which suggest that angular accuracies of 0.08 to 0.1/microrad are achievable with X-band ranging.

Comparison between fine needle aspiration cytology (FNAC) and core needle biopsy (CNB) in the diagnosis of breast lesions.

PubMed

Moschetta, M; Telegrafo, M; Carluccio, D A; Jablonska, J P; Rella, L; Serio, Gabriella; Carrozzo, M; Stabile Ianora, A A; Angelelli, G

2014-01-01

To compare the diagnostic accuracy of fine-needle aspiration cytology (FNAC) and core needle biopsy (CNB) in patients with USdetected breast lesions. Between September 2011 and May 2013, 3469 consecutive breast US examinations were performed. 400 breast nodules were detected in 398 patients. 210 FNACs and 190 CNBs were performed. 183 out of 400 (46%) lesions were surgically removed within 30 days form diagnosis; in the remaining cases, a six month follow up US examination was performed. Sensitivity, specificity, diagnostic accuracy, positive predictive (PPV) and negative predictive (NPV) values were calculated for FNAC and CNB. 174 out of 400 (43%) malignant lesions were found while the remaining 226 resulted to be benign lesions. 166 out of 210 (79%) FNACs and 154 out of 190 (81%) CNBs provided diagnostic specimens. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 97%, 94%, 95%, 91% and 98% were found for FNAC, and values of 92%, 82%, 89%, 92% and 82% were obtained for CNB. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 97%, 96%, 96%, 97% and 96% were found for FNAC, and values of 97%, 96%, 96%, 97% and 96% were obtained for CNB. FNAC and CNB provide similar values of diagnostic accuracy.

Diagnostic Accuracy of a New Cardiac Electrical Biomarker for Detection of Electrocardiogram Changes Suggestive of Acute Myocardial Ischemic Injury

PubMed Central

Schreck, David M; Fishberg, Robert D

2014-01-01

Objective A new cardiac “electrical” biomarker (CEB) for detection of 12-lead electrocardiogram (ECG) changes indicative of acute myocardial ischemic injury has been identified. Objective was to test CEB diagnostic accuracy. Methods This is a blinded, observational retrospective case-control, noninferiority study. A total of 508 ECGs obtained from archived digital databases were interpreted by cardiologist and emergency physician (EP) blinded reference standards for presence of acute myocardial ischemic injury. CEB was constructed from three ECG cardiac monitoring leads using nonlinear modeling. Comparative active controls included ST voltage changes (J-point, ST area under curve) and a computerized ECG interpretive algorithm (ECGI). Training set of 141 ECGs identified CEB cutoffs by receiver-operating-characteristic (ROC) analysis. Test set of 367 ECGs was analyzed for validation. Poor-quality ECGs were excluded. Sensitivity, specificity, and negative and positive predictive values were calculated with 95% confidence intervals. Adjudication was performed by consensus. Results CEB demonstrated noninferiority to all active controls by hypothesis testing. CEB adjudication demonstrated 85.3–94.4% sensitivity, 92.5–93.0% specificity, 93.8–98.6% negative predictive value, and 74.6–83.5% positive predictive value. CEB was superior against all active controls in EP analysis, and against ST area under curve and ECGI by cardiologist. Conclusion CEB detects acute myocardial ischemic injury with high diagnostic accuracy. CEB is instantly constructed from three ECG leads on the cardiac monitor and displayed instantly allowing immediate cost-effective identification of patients with acute ischemic injury during cardiac rhythm monitoring. PMID:24118724

Comparing diagnostic accuracy of bedside ultrasound and radiography for bone fracture screening in multiple trauma patients at the ED.

PubMed

Bolandparvaz, Shahram; Moharamzadeh, Payman; Jamali, Kazem; Pouraghaei, Mahboob; Fadaie, Maryam; Sefidbakht, Sepideh; Shahsavari, Kavous

2013-11-01

Long bone fractures are currently diagnosed using radiography, but radiography has some disadvantages (radiation and being time consuming). The present study compared the diagnostic accuracy of bedside ultrasound and radiography in multiple trauma patients at the emergency department (ED). The study assessed 80 injured patients with multiple trauma from February 2011 to July 2012. The patients were older than 18 years and triaged to the cardiopulmonary resuscitation ward of the ED. Bedside ultrasound and radiography were conducted for them. The findings were separately and blindly assessed by 2 radiologists. Sensitivity, specificity, the positive and negative predictive value, and κ coefficient were measured to assess the accuracy and validity of ultrasound as compared with radiography. The sensitivity of ultrasound for diagnosis of limb bone fractures was not high enough and ranged between 55% and 75% depending on the fracture site. The specificity of this diagnostic method had an acceptable range of 62% to 84%. Ultrasound negative prediction value was higher than other indices under study and ranged between 73% and 83%, but its positive prediction value varied between 33.3% and 71%. The κ coefficient for diagnosis of long bone fractures of upper limb (κ = 0.58) and upper limb joints (κ = 0.47) and long bones of lower limb (κ = 0.52) was within the medium range. However, the value for diagnosing fractures of lower limb joints (κ = 0.47) was relatively low. Bedside ultrasound is not a reliable method for diagnosing fractures of upper and lower limb bones compared with radiography. © 2013 Elsevier Inc. All rights reserved.

Improving multi-GNSS ultra-rapid orbit determination for real-time precise point positioning

NASA Astrophysics Data System (ADS)

Li, Xingxing; Chen, Xinghan; Ge, Maorong; Schuh, Harald

2018-03-01

Currently, with the rapid development of multi-constellation Global Navigation Satellite Systems (GNSS), the real-time positioning and navigation are undergoing dramatic changes with potential for a better performance. To provide more precise and reliable ultra-rapid orbits is critical for multi-GNSS real-time positioning, especially for the three merging constellations Beidou, Galileo and QZSS which are still under construction. In this contribution, we present a five-system precise orbit determination (POD) strategy to fully exploit the GPS + GLONASS + BDS + Galileo + QZSS observations from CDDIS + IGN + BKG archives for the realization of hourly five-constellation ultra-rapid orbit update. After adopting the optimized 2-day POD solution (updated every hour), the predicted orbit accuracy can be obviously improved for all the five satellite systems in comparison to the conventional 1-day POD solution (updated every 3 h). The orbit accuracy for the BDS IGSO satellites can be improved by about 80, 45 and 50% in the radial, cross and along directions, respectively, while the corresponding accuracy improvement for the BDS MEO satellites reaches about 50, 20 and 50% in the three directions, respectively. Furthermore, the multi-GNSS real-time precise point positioning (PPP) ambiguity resolution has been performed by using the improved precise satellite orbits. Numerous results indicate that combined GPS + BDS + GLONASS + Galileo (GCRE) kinematic PPP ambiguity resolution (AR) solutions can achieve the shortest time to first fix (TTFF) and highest positioning accuracy in all coordinate components. With the addition of the BDS, GLONASS and Galileo observations to the GPS-only processing, the GCRE PPP AR solution achieves the shortest average TTFF of 11 min with 7{°} cutoff elevation, while the TTFF of GPS-only, GR, GE and GC PPP AR solution is 28, 15, 20 and 17 min, respectively. As the cutoff elevation increases, the reliability and accuracy of GPS-only PPP AR solutions decrease dramatically, but there is no evident decrease for the accuracy of GCRE fixed solutions which can still achieve an accuracy of a few centimeters in the east and north components.

Predictive capacity of a non-radioisotopic local lymph node assay using flow cytometry, LLNA:BrdU-FCM: Comparison of a cutoff approach and inferential statistics.

PubMed

Kim, Da-Eun; Yang, Hyeri; Jang, Won-Hee; Jung, Kyoung-Mi; Park, Miyoung; Choi, Jin Kyu; Jung, Mi-Sook; Jeon, Eun-Young; Heo, Yong; Yeo, Kyung-Wook; Jo, Ji-Hoon; Park, Jung Eun; Sohn, Soo Jung; Kim, Tae Sung; Ahn, Il Young; Jeong, Tae-Cheon; Lim, Kyung-Min; Bae, SeungJin

2016-01-01

In order for a novel test method to be applied for regulatory purposes, its reliability and relevance, i.e., reproducibility and predictive capacity, must be demonstrated. Here, we examine the predictive capacity of a novel non-radioisotopic local lymph node assay, LLNA:BrdU-FCM (5-bromo-2'-deoxyuridine-flow cytometry), with a cutoff approach and inferential statistics as a prediction model. 22 reference substances in OECD TG429 were tested with a concurrent positive control, hexylcinnamaldehyde 25%(PC), and the stimulation index (SI) representing the fold increase in lymph node cells over the vehicle control was obtained. The optimal cutoff SI (2.7≤cutoff <3.5), with respect to predictive capacity, was obtained by a receiver operating characteristic curve, which produced 90.9% accuracy for the 22 substances. To address the inter-test variability in responsiveness, SI values standardized with PC were employed to obtain the optimal percentage cutoff (42.6≤cutoff <57.3% of PC), which produced 86.4% accuracy. A test substance may be diagnosed as a sensitizer if a statistically significant increase in SI is elicited. The parametric one-sided t-test and non-parametric Wilcoxon rank-sum test produced 77.3% accuracy. Similarly, a test substance could be defined as a sensitizer if the SI means of the vehicle control, and of the low, middle, and high concentrations were statistically significantly different, which was tested using ANOVA or Kruskal-Wallis, with post hoc analysis, Dunnett, or DSCF (Dwass-Steel-Critchlow-Fligner), respectively, depending on the equal variance test, producing 81.8% accuracy. The absolute SI-based cutoff approach produced the best predictive capacity, however the discordant decisions between prediction models need to be examined further. Copyright © 2015 Elsevier Inc. All rights reserved.

Efficacy of Transcerebellar Diameter/Abdominal Circumference Versus Head Circumference/Abdominal Circumference in Predicting Asymmetric Intrauterine Growth Retardation

PubMed Central

Bhimarao; Bhat, Venkataramana; Gowda, Puttanna VN

2015-01-01

Background The high incidence of IUGR and its low recognition lead to increasing perinatal morbidity and mortality for which prediction of IUGR with timely management decisions is of paramount importance. Many studies have compared the efficacy of several gestational age independent parameters and found that TCD/AC is a better predictor of asymmetric IUGR. Aim To compare the accuracy of transcerebellar diameter/abdominal circumference with head circumference/abdominal circumference in predicting asymmetric intrauterine growth retardation after 20 weeks of gestation. Materials and Methods The prospective study was conducted over a period of one year on 50 clinically suspected IUGR pregnancies who were evaluated with 3.5 MHz frequency ultrasound scanner by a single sonologist. BPD, HC, AC and FL along with TCD were measured for assessing the sonological gestational age. Two morphometric ratios- TCD/AC and HC/AC were calculated. Estimated fetal weight was calculated for all these pregnancies and its percentile was determined. Statistical Methods The TCD/AC and HC/AC ratios were correlated with advancing gestational age to know if these were related to GA. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy (DA) for TCD/AC and HC/AC ratios in evaluating IUGR fetuses were calculated. Results In the present study, linear relation of TCD and HC in IUGR fetuses with gestation was noted. The sensitivity, specificity, PPV, NPV & DA were 88%, 93.5%, 77.1%, 96.3% & 92.4% respectively for TCD/AC ratio versus 84%, 92%, 72.4%, 95.8% & 90.4% respectively for HC/AC ratio in predicting IUGR. Conclusion Both ratios were gestational age independent and can be used in detecting IUGR with good diagnostic accuracy. However, TCD/AC ratio had a better diagnostic validity and accuracy compared to HC/AC ratio in predicting asymmetric IUGR. PMID:26557588

Mortality, morbidity and refractoriness prediction in status epilepticus: Comparison of STESS and EMSE scores.

PubMed

Giovannini, Giada; Monti, Giulia; Tondelli, Manuela; Marudi, Andrea; Valzania, Franco; Leitinger, Markus; Trinka, Eugen; Meletti, Stefano

2017-03-01

Status epilepticus (SE) is a neurological emergency, characterized by high short-term morbidity and mortality. We evaluated and compared two scores that have been developed to evaluate status epilepticus prognosis: STESS (Status Epilepticus Severity Score) and EMSE (Epidemiology based Mortality score in Status Epilepticus). A prospective observational study was performed on consecutive patients with SE admitted between September 2013 and August 2015. Demographics, clinical variables, STESS-3 and -4, and EMSE-64 scores were calculated for each patient at baseline. SE drug response, 30-day mortality and morbidity were the outcomes measure. 162 episodes of SE were observed: 69% had a STESS ≥3; 34% had a STESS ≥4; 51% patients had an EMSE ≥64. The 30-days mortality was 31.5%: EMSE-64 showed greater negative predictive value (NPV) (97.5%), positive predictive value (PPV) (59.8%) and accuracy in the prediction of death than STESS-3 and STESS-4 (p<0.001). At 30 days, the clinical condition had deteriorated in 59% of the cases: EMSE-64 showed greater NPV (71.3%), PPV (87.8%) and accuracy than STESS-3 and STESS-4 (p<0.001) in the prediction of this outcome. In 23% of all cases, status epilepticus proved refractory to non-anaesthetic treatment. All three scales showed a high NPV (EMSE-64: 87.3%; STESS-4: 89.4%; STESS-3: 87.5%) but a low PPV (EMSE-64: 40.9%; STESS-4: 52.9%; STESS-3: 32%) for the prediction of refractoriness to first and second line drugs. This means that accuracy for the prediction of refractoriness was equally poor for all scales. EMSE-64 appears superior to STESS-3 and STESS-4 in the prediction of 30-days mortality and morbidity. All scales showed poor accuracy in the prediction of response to first and second line antiepileptic drugs. At present, there are no reliable scores capable of predicting treatment responsiveness. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Predicting Ambulance Time of Arrival to the Emergency Department Using Global Positioning System and Google Maps

PubMed Central

Fleischman, Ross J.; Lundquist, Mark; Jui, Jonathan; Newgard, Craig D.; Warden, Craig

2014-01-01

Objective To derive and validate a model that accurately predicts ambulance arrival time that could be implemented as a Google Maps web application. Methods This was a retrospective study of all scene transports in Multnomah County, Oregon, from January 1 through December 31, 2008. Scene and destination hospital addresses were converted to coordinates. ArcGIS Network Analyst was used to estimate transport times based on street network speed limits. We then created a linear regression model to improve the accuracy of these street network estimates using weather, patient characteristics, use of lights and sirens, daylight, and rush-hour intervals. The model was derived from a 50% sample and validated on the remainder. Significance of the covariates was determined by p < 0.05 for a t-test of the model coefficients. Accuracy was quantified by the proportion of estimates that were within 5 minutes of the actual transport times recorded by computer-aided dispatch. We then built a Google Maps-based web application to demonstrate application in real-world EMS operations. Results There were 48,308 included transports. Street network estimates of transport time were accurate within 5 minutes of actual transport time less than 16% of the time. Actual transport times were longer during daylight and rush-hour intervals and shorter with use of lights and sirens. Age under 18 years, gender, wet weather, and trauma system entry were not significant predictors of transport time. Our model predicted arrival time within 5 minutes 73% of the time. For lights and sirens transports, accuracy was within 5 minutes 77% of the time. Accuracy was identical in the validation dataset. Lights and sirens saved an average of 3.1 minutes for transports under 8.8 minutes, and 5.3 minutes for longer transports. Conclusions An estimate of transport time based only on a street network significantly underestimated transport times. A simple model incorporating few variables can predict ambulance time of arrival to the emergency department with good accuracy. This model could be linked to global positioning system data and an automated Google Maps web application to optimize emergency department resource use. Use of lights and sirens had a significant effect on transport times. PMID:23865736

Information Filtering Based on Users' Negative Opinions

NASA Astrophysics Data System (ADS)

Guo, Qiang; Li, Yang; Liu, Jian-Guo

2013-05-01

The process of heat conduction (HC) has recently found application in the information filtering [Zhang et al., Phys. Rev. Lett.99, 154301 (2007)], which is of high diversity but low accuracy. The classical HC model predicts users' potential interested objects based on their interesting objects regardless to the negative opinions. In terms of the users' rating scores, we present an improved user-based HC (UHC) information model by taking into account users' positive and negative opinions. Firstly, the objects rated by users are divided into positive and negative categories, then the predicted interesting and dislike object lists are generated by the UHC model. Finally, the recommendation lists are constructed by filtering out the dislike objects from the interesting lists. By implementing the new model based on nine similarity measures, the experimental results for MovieLens and Netflix datasets show that the new model considering negative opinions could greatly enhance the accuracy, measured by the average ranking score, from 0.049 to 0.036 for Netflix and from 0.1025 to 0.0570 for Movielens dataset, reduced by 26.53% and 44.39%, respectively. Since users prefer to give positive ratings rather than negative ones, the negative opinions contain much more information than the positive ones, the negative opinions, therefore, are very important for understanding users' online collective behaviors and improving the performance of HC model.

Neural network control of focal position during time-lapse microscopy of cells.

PubMed

Wei, Ling; Roberts, Elijah

2018-05-09

Live-cell microscopy is quickly becoming an indispensable technique for studying the dynamics of cellular processes. Maintaining the specimen in focus during image acquisition is crucial for high-throughput applications, especially for long experiments or when a large sample is being continuously scanned. Automated focus control methods are often expensive, imperfect, or ill-adapted to a specific application and are a bottleneck for widespread adoption of high-throughput, live-cell imaging. Here, we demonstrate a neural network approach for automatically maintaining focus during bright-field microscopy. Z-stacks of yeast cells growing in a microfluidic device were collected and used to train a convolutional neural network to classify images according to their z-position. We studied the effect on prediction accuracy of the various hyperparameters of the neural network, including downsampling, batch size, and z-bin resolution. The network was able to predict the z-position of an image with ±1 μm accuracy, outperforming human annotators. Finally, we used our neural network to control microscope focus in real-time during a 24 hour growth experiment. The method robustly maintained the correct focal position compensating for 40 μm of focal drift and was insensitive to changes in the field of view. About ~100 annotated z-stacks were required to train the network making our method quite practical for custom autofocus applications.

WASP (Write a Scientific Paper) using Excel - 11: Test characteristics.

PubMed

Grech, Victor

2018-07-01

The calculation of various test characteristics may be required as part of a data analysis exercise. This paper explains how to set up these calculations in Microsoft Excel in order to obtain sensitivity, specificity, positive and negative predictive values, diagnostic accuracy and prevalence. Copyright © 2018 Elsevier B.V. All rights reserved.

General Knowledge Monitoring as a Predictor of In-Class Exam Performance

ERIC Educational Resources Information Center

Hartwig, Marissa K.; Was, Chris A.; Isaacson, Randy M.; Dunlosky, John

2012-01-01

Background: Current theories of self-regulated learning predict a positive link between student monitoring accuracy and performance: students who more accurately monitor their knowledge of a particular set of materials are expected to more effectively regulate their subsequent study of those materials, which in turn should lead to higher test…

Branchial cleft anomalies: accuracy of pre-operative diagnosis, clinical presentation and management.

PubMed

Guldfred, L-A; Philipsen, B B; Siim, C

2012-06-01

To examine the accuracy of the pre-operative diagnosis of branchial cleft anomalies, and also to describe their occurrence, clinical presentation and management. Retrospective review of the records of patients diagnosed with a branchial cleft anomaly between 1997 and 2006. One hundred and twenty-six patients were included. Pre-operative diagnosis had a positive predictive value of 0.856 (95 per cent confidence interval, 0.771-0.918) and a sensitivity of 0.944 (95 per cent confidence interval, 0.869-0.979). These patients' demographic data, investigations, findings and management are presented, along with a possible strategy for dealing with solitary cystic masses in the neck. As pre-operative diagnosis has a positive predictive value of 86 per cent, cystic lesions in the neck should be presumed to be carcinomatous until proven otherwise. Branchial fistulae and sinuses seem to be a disease of childhood, while branchial cysts occur mainly in adults. Branchial cleft anomalies are equally frequent in men and women, and equally distributed on the left and right side of the neck.

Routine preoperative colour Doppler duplex ultrasound scanning in anterolateral thigh flaps.

PubMed

Lichte, Johanna; Teichmann, Jan; Loberg, Christina; Kloss-Brandstätter, Anita; Bartella, Alexander; Steiner, Timm; Modabber, Ali; Hölzle, Frank; Lethaus, Bernd

2016-10-01

The anterolateral thigh flap (ALT) is often used to reconstruct the head and neck and depends on one or more skin perforators, which often present with variable anatomy. The aim of this study was to localise and evaluate the precise position of these perforators preoperatively with colour Doppler duplex ultrasound scanning (US). We detected 74 perforators in 30 patients. The mean duration of examination with colour Doppler was 29 (range 13-51) minutes. Adequate perforators and their anatomical course could be detected preoperatively extremely accurately (p<0.001). The mean difference between the preoperatively marked, and the real, positions was 6.3 (range 0-16) mm. There was a highly significant correlation between the accuracy of the prediction and the body mass index of the patient (0.75; p<0.001). Neither the age nor the sex of the patient correlated with the accuracy of the prediction. Colour Doppler duplex US used preoperatively to localise perforators in ALT flaps is reliable and could be adopted as standard procedure. Copyright © 2016 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Poster - 51: A tumor motion-compensating system with tracking and prediction – a proof-of-concept study

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

Guo, Kaiming; Teo, Peng; Kawalec, Philip

2016-08-15

Purpose: This work reports on the development of a mechanical slider system for the counter-steering of tumor motion in adaptive Radiation Therapy (RT). The tumor motion was tracked using a weighted optical flow algorithm and its position is being predicted with a neural network (NN). Methods: The components of the proposed mechanical counter-steering system includes: (1) an actuator which provides the tumor motion, (2) the motion detection using an optical flow algorithm, (3) motion prediction using a neural network, (4) a control module and (5) a mechanical slider to counter-steer the anticipated motion of the tumor phantom. An asymmetrical cosinemore » function and five patient traces (P1–P5) were used to evaluate the tracking of a 3D printed lung tumor. In the proposed mechanical counter-steering system, both actuator (Zaber NA14D60) and slider (Zaber A-BLQ0070-E01) were programed to move independently with LabVIEW and their positions were recorded by 2 potentiometers (ETI LCP12S-25). The accuracy of this counter-steering system is given by the difference between the two potentiometers. Results: The inherent accuracy of the system, measured using the cosine function, is −0.15 ± 0.06 mm. While the errors when tracking and prediction were included, is (0.04 ± 0.71) mm. Conclusion: A prototype tumor motion counter-steering system with tracking and prediction was implemented. The inherent errors are small in comparison to the tracking and prediction errors, which in turn are small in comparison to the magnitude of tumor motion. The results show that this system is suited for evaluating RT tracking and prediction.« less

Predicting prolonged length of hospital stay in older emergency department users: use of a novel analysis method, the Artificial Neural Network.

PubMed

Launay, C P; Rivière, H; Kabeshova, A; Beauchet, O

2015-09-01

To examine performance criteria (i.e., sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], likelihood ratios [LR], area under receiver operating characteristic curve [AUROC]) of a 10-item brief geriatric assessment (BGA) for the prediction of prolonged length hospital stay (LHS) in older patients hospitalized in acute care wards after an emergency department (ED) visit, using artificial neural networks (ANNs); and to describe the contribution of each BGA item to the predictive accuracy using the AUROC value. A total of 993 geriatric ED users admitted to acute care wards were included in this prospective cohort study. Age >85years, gender male, polypharmacy, non use of formal and/or informal home-help services, history of falls, temporal disorientation, place of living, reasons and nature for ED admission, and use of psychoactive drugs composed the 10 items of BGA and were recorded at the ED admission. The prolonged LHS was defined as the top third of LHS. The ANNs were conducted using two feeds forward (multilayer perceptron [MLP] and modified MLP). The best performance was reported with the modified MLP involving the 10 items (sensitivity=62.7%; specificity=96.6%; PPV=87.1; NPV=87.5; positive LR=18.2; AUC=90.5). In this model, presence of chronic conditions had the highest contributions (51.3%) in AUROC value. The 10-item BGA appears to accurately predict prolonged LHS, using the ANN MLP method, showing the best criteria performance ever reported until now. Presence of chronic conditions was the main contributor for the predictive accuracy. Copyright © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Improving tRNAscan-SE Annotation Results via Ensemble Classifiers.

PubMed

Zou, Quan; Guo, Jiasheng; Ju, Ying; Wu, Meihong; Zeng, Xiangxiang; Hong, Zhiling

2015-11-01

tRNAScan-SE is a tRNA detection program that is widely used for tRNA annotation; however, the false positive rate of tRNAScan-SE is unacceptable for large sequences. Here, we used a machine learning method to try to improve the tRNAScan-SE results. A new predictor, tRNA-Predict, was designed. We obtained real and pseudo-tRNA sequences as training data sets using tRNAScan-SE and constructed three different tRNA feature sets. We then set up an ensemble classifier, LibMutil, to predict tRNAs from the training data. The positive data set of 623 tRNA sequences was obtained from tRNAdb 2009 and the negative data set was the false positive tRNAs predicted by tRNAscan-SE. Our in silico experiments revealed a prediction accuracy rate of 95.1 % for tRNA-Predict using 10-fold cross-validation. tRNA-Predict was developed to distinguish functional tRNAs from pseudo-tRNAs rather than to predict tRNAs from a genome-wide scan. However, tRNA-Predict can work with the output of tRNAscan-SE, which is a genome-wide scanning method, to improve the tRNAscan-SE annotation results. The tRNA-Predict web server is accessible at http://datamining.xmu.edu.cn/∼gjs/tRNA-Predict. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Accuracy of Single Frequency GPS Observations Processing In Near Real-time With Use of Code Predicted Products

NASA Astrophysics Data System (ADS)

Wielgosz, P. A.

In this year, the system of active geodetic GPS permanent stations is going to be estab- lished in Poland. This system should provide GPS observations for a wide spectrum of users, especially it will be a great opportunity for surveyors. Many of surveyors still use cheaper, single frequency receivers. This paper focuses on processing of single frequency GPS observations only. During processing of such observations the iono- sphere plays an important role, so we concentrated on the influence of the ionosphere on the positional coordinates. Twenty consecutive days of GPS data from 2001 year were processed to analyze the accuracy of a derived three-dimensional relative vec- tor position between GPS stations. Observations from two Polish EPN/IGS stations: BOGO and JOZE were used. In addition to, a new test station - IGIK was created. In this paper, the results of single frequency GPS observations processing in near real- time are presented. Baselines of 15, 27 and 42 kilometers and sessions of 1, 2, 3, 4, and 6 hours long were processed. While processing we used CODE (Centre for Orbit De- termination in Europe, Bern, Switzerland) predicted products: orbits and ionosphere info. These products are available in real-time and enable near real-time processing. Software Bernese v. 4.2 for Linux and BPE (Bernese Processing Engine) mode were used. These results are shown with a reference to dual frequency weekly solution (the best solution). Obtained GPS positional time and GPS baseline length dependency accuracy is presented for single frequency GPS observations.

Technical and financial evaluation of assays for progesterone in canine practice in the UK.

PubMed

Moxon, R; Copley, D; England, G C W

2010-10-02

The concentration of progesterone was measured in 60 plasma samples from bitches at various stages of the oestrous cycle, using commercially available quantitative and semi-quantitative ELISA test kits, as well as by two commercial laboratories undertaking radioimmunoassay (RIA). The RIA, which was assumed to be the 'gold standard' in terms of reliability and accuracy, was the most expensive method when analysing more than one sample per week, and had the longest delay in obtaining results, but had minimal requirements for practice staff time. When compared with the RIA, the quantitative ELISA had a strong positive correlation (r=0.97, P<0.05) and a sensitivity and specificity of 70.6 per cent and 100.0 per cent, respectively, and positive and negative predictive values of 100.0 per cent and 71.0 per cent, respectively, with an overall accuracy of 90.0 per cent. This method was the least expensive when analysing five or more samples per week, but had longer turnaround times than that of the semi-quantitative ELISA and required more staff time. When compared with the RIA, the semi-quantitative ELISA had a sensitivity and specificity of 100.0 per cent and 95.5 per cent, respectively, and positive and negative predictive values of 73.9 per cent and 77.8 per cent, respectively, with an overall accuracy of 89.2 per cent. This method was more expensive than the quantitative ELISA when analysing five or more samples per week, but had the shortest turnaround time and low requirements in terms of staff time.

Added value of diffusion-weighted MRI in detection of cervical cancer recurrence: comparison with morphologic and dynamic contrast-enhanced MRI sequences.

PubMed

Lucas, Rita; Lopes Dias, João; Cunha, Teresa Margarida

2015-01-01

We aimed to evaluate the added value of diffusion-weighted imaging (DWI) to standard magnetic resonance imaging (MRI) for detecting post-treatment cervical cancer recurrence. The detection accuracy of T2-weighted (T2W) images was compared with that of T2W MRI combined with either dynamic contrast-enhanced (DCE) MRI or DWI. Thirty-eight women with clinically suspected uterine cervical cancer recurrence more than six months after treatment completion were examined with 1.5 Tesla MRI including T2W, DCE, and DWI sequences. Disease was confirmed histologically and correlated with MRI findings. The diagnostic performance of T2W imaging and its combination with either DCE or DWI were analyzed. Sensitivity, positive predictive value, and accuracy were calculated. Thirty-six women had histologically proven recurrence. The accuracy for recurrence detection was 80% with T2W/DCE MRI and 92.1% with T2W/DWI. The addition of DCE sequences did not significantly improve the diagnostic ability of T2W imaging, and this sequence combination misclassified two patients as falsely positive and seven as falsely negative. The T2W/DWI combination revealed a positive predictive value of 100% and only three false negatives. The addition of DWI to T2W sequences considerably improved the diagnostic ability of MRI. Our results support the inclusion of DWI in the initial MRI protocol for the detection of cervical cancer recurrence, leaving DCE sequences as an option for uncertain cases.

Use of risk assessment instruments to predict violence and antisocial behaviour in 73 samples involving 24 827 people: systematic review and meta-analysis

PubMed Central

Singh, Jay P; Doll, Helen; Grann, Martin

2012-01-01

Objective To investigate the predictive validity of tools commonly used to assess the risk of violence, sexual, and criminal behaviour. Design Systematic review and tabular meta-analysis of replication studies following PRISMA guidelines. Data sources PsycINFO, Embase, Medline, and United States Criminal Justice Reference Service Abstracts. Review methods We included replication studies from 1 January 1995 to 1 January 2011 if they provided contingency data for the offending outcome that the tools were designed to predict. We calculated the diagnostic odds ratio, sensitivity, specificity, area under the curve, positive predictive value, negative predictive value, the number needed to detain to prevent one offence, as well as a novel performance indicator—the number safely discharged. We investigated potential sources of heterogeneity using metaregression and subgroup analyses. Results Risk assessments were conducted on 73 samples comprising 24 847 participants from 13 countries, of whom 5879 (23.7%) offended over an average of 49.6 months. When used to predict violent offending, risk assessment tools produced low to moderate positive predictive values (median 41%, interquartile range 27-60%) and higher negative predictive values (91%, 81-95%), and a corresponding median number needed to detain of 2 (2-4) and number safely discharged of 10 (4-18). Instruments designed to predict violent offending performed better than those aimed at predicting sexual or general crime. Conclusions Although risk assessment tools are widely used in clinical and criminal justice settings, their predictive accuracy varies depending on how they are used. They seem to identify low risk individuals with high levels of accuracy, but their use as sole determinants of detention, sentencing, and release is not supported by the current evidence. Further research is needed to examine their contribution to treatment and management. PMID:22833604

Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding

PubMed Central

2013-01-01

Background In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. Results The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. Conclusions The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least biased, the most precise, robust and stable estimates of predictive accuracy. These properties argue for routinely using Methods 5 and 7 to assess predictive accuracy in genomic selection studies. PMID:24314298

Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding.

PubMed

Ould Estaghvirou, Sidi Boubacar; Ogutu, Joseph O; Schulz-Streeck, Torben; Knaak, Carsten; Ouzunova, Milena; Gordillo, Andres; Piepho, Hans-Peter

2013-12-06

In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least biased, the most precise, robust and stable estimates of predictive accuracy. These properties argue for routinely using Methods 5 and 7 to assess predictive accuracy in genomic selection studies.

Comparison of bronchoalveolar lavage cytology and transbronchial biopsy in the diagnosis of carcinoma of lung.

PubMed

Ahmed, Ayesha; Ahmed, Sajjad

2004-01-01

The objectives of this study were to compare bronchoalveolar lavage (BAL) cytology and transbronchial biopsy in the diagnosis of carcinoma lung and to determine accuracy of BAL cytology using histopathlologic examination of transbronchial biopsy as gold standard at our center. This study was carried out at Department of Histopathology, Ayub Medical College, Abbottabad, from 1.09.2000 to 28.02.2003. BAL fluid and bronchial biopsy were received and processed simultaneously. Four cytology and a set of histopathology slides were prepared. These were screened and diagnosis recorded. Sensitivity, Specificity, False Positive, False Negative, Positive predictive value and Negative predictive value of BAL cytology were determined using histopathology of transbronchial biopsy as gold standard. We found the sensitivity of BAL cytology to be 93.44% as compared with transbronchial biopsy. The specificity was 100%. There was no false positive while false negative results were 6.55 %. The positive predictive value was 100 %, while the negative predictive value was 75 %. The overall diagnostic efficacy of BAL cytology was 94.52 %. BAL cytology is a highly sensitive and specific test for diagnosis of carcinoma lung. It can be used as a quick and reliable diagnostic method for diagnosis of lung malignancy.

Common polygenic variation enhances risk prediction for Alzheimer’s disease

PubMed Central

Sims, Rebecca; Bannister, Christian; Harold, Denise; Vronskaya, Maria; Majounie, Elisa; Badarinarayan, Nandini; Morgan, Kevin; Passmore, Peter; Holmes, Clive; Powell, John; Brayne, Carol; Gill, Michael; Mead, Simon; Goate, Alison; Cruchaga, Carlos; Lambert, Jean-Charles; van Duijn, Cornelia; Maier, Wolfgang; Ramirez, Alfredo; Holmans, Peter; Jones, Lesley; Hardy, John; Seshadri, Sudha; Schellenberg, Gerard D.; Amouyel, Philippe

2015-01-01

The identification of subjects at high risk for Alzheimer’s disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer’s disease and the accuracy of Alzheimer’s disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer’s Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer’s disease (P = 4.9 × 10−26). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10−19). The best prediction accuracy AUC = 78.2% (95% confidence interval 77–80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer’s disease has a significant polygenic component, which has predictive utility for Alzheimer’s disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes. PMID:26490334

Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Jiang, Yuan Yuan; Kim, Sung Min

2015-01-01

This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangiomas, and 33 malignancies. A total of 42 hybrid textural features that composed of 5 first order statistics, 18 gray level co-occurrence matrices, 18 Law's, and echogenicity were extracted. A total of 29 key features that were selected by principal component analysis were used as a set of inputs for a feed-forward neural network. For each lesion, the performance of the diagnosis was evaluated by using the positive predictive value, negative predictive value, sensitivity, specificity, and accuracy. The results of the experiment indicate that the proposed method exhibits great performance, a high diagnosis accuracy of over 96% among all focal liver lesion groups (cyst vs. hemangioma, cyst vs. malignant, and hemangioma vs. malignant) on ultrasound images. The accuracy was slightly increased when echogenicity was included in the optimal feature set. These results indicate that it is possible for the proposed method to be applied clinically.

Improving BeiDou real-time precise point positioning with numerical weather models

NASA Astrophysics Data System (ADS)

Lu, Cuixian; Li, Xingxing; Zus, Florian; Heinkelmann, Robert; Dick, Galina; Ge, Maorong; Wickert, Jens; Schuh, Harald

2017-09-01

Precise positioning with the current Chinese BeiDou Navigation Satellite System is proven to be of comparable accuracy to the Global Positioning System, which is at centimeter level for the horizontal components and sub-decimeter level for the vertical component. But the BeiDou precise point positioning (PPP) shows its limitation in requiring a relatively long convergence time. In this study, we develop a numerical weather model (NWM) augmented PPP processing algorithm to improve BeiDou precise positioning. Tropospheric delay parameters, i.e., zenith delays, mapping functions, and horizontal delay gradients, derived from short-range forecasts from the Global Forecast System of the National Centers for Environmental Prediction (NCEP) are applied into BeiDou real-time PPP. Observational data from stations that are capable of tracking the BeiDou constellation from the International GNSS Service (IGS) Multi-GNSS Experiments network are processed, with the introduced NWM-augmented PPP and the standard PPP processing. The accuracy of tropospheric delays derived from NCEP is assessed against with the IGS final tropospheric delay products. The positioning results show that an improvement in convergence time up to 60.0 and 66.7% for the east and vertical components, respectively, can be achieved with the NWM-augmented PPP solution compared to the standard PPP solutions, while only slight improvement in the solution convergence can be found for the north component. A positioning accuracy of 5.7 and 5.9 cm for the east component is achieved with the standard PPP that estimates gradients and the one that estimates no gradients, respectively, in comparison to 3.5 cm of the NWM-augmented PPP, showing an improvement of 38.6 and 40.1%. Compared to the accuracy of 3.7 and 4.1 cm for the north component derived from the two standard PPP solutions, the one of the NWM-augmented PPP solution is improved to 2.0 cm, by about 45.9 and 51.2%. The positioning accuracy for the up component improves from 11.4 and 13.2 cm with the two standard PPP solutions to 8.0 cm with the NWM-augmented PPP solution, an improvement of 29.8 and 39.4%, respectively.

A hybrid localization technique for patient tracking.

PubMed

Rodionov, Denis; Kolev, George; Bushminkin, Kirill

2013-01-01

Nowadays numerous technologies are employed for tracking patients and assets in hospitals or nursing homes. Each of them has advantages and drawbacks. For example, WiFi localization has relatively good accuracy but cannot be used in case of power outage or in the areas with poor WiFi coverage. Magnetometer positioning or cellular network does not have such problems but they are not as accurate as localization with WiFi. This paper describes technique that simultaneously employs different localization technologies for enhancing stability and average accuracy of localization. The proposed algorithm is based on fingerprinting method paired with data fusion and prediction algorithms for estimating the object location. The core idea of the algorithm is technology fusion using error estimation methods. For testing accuracy and performance of the algorithm testing simulation environment has been implemented. Significant accuracy improvement was showed in practical scenarios.

Exploring the Solar System using stellar occultations

NASA Astrophysics Data System (ADS)

Sicardy, Bruno

2018-04-01

Stellar occultations by solar system objects allow kilometric accuracy, permit the detection of tenuous atmospheres (at nbar level), and the discovery of rings. The main limitation was the prediction accuracy, typically 40 mas, corresponding to about 1,000 km projected at the body. This lead to large time dedicated to astrometry, tedious logistical issues, and more often than not, mere miss of the event. The Gaia catalog, with sub-mas accuracy, hugely improves both the star positions, resulting in achievable accuracies of about 1 mas for the shadow track on Earth. This permits much more carefully planned campaigns, with success rate approaching 100%, weather permitting. Scientific perspectives are presented, e.g. central flashes caused by Plutos atmosphere revealing hazes and winds near its surface, grazing occultations showing topographic features, occultations by Chariklos rings unveiling dynamical features such as proper mode ``breathing''.

Acoustic results of the Boeing model 360 whirl tower test

NASA Astrophysics Data System (ADS)

Watts, Michael E.; Jordan, David

1990-09-01

An evaluation is presented for whirl tower test results of the Model 360 helicopter's advanced, high-performance four-bladed composite rotor system intended to facilitate over-200-knot flight. During these performance measurements, acoustic data were acquired by seven microphones. A comparison of whirl-tower tests with theory indicate that theoretical prediction accuracies vary with both microphone position and the inclusion of ground reflection. Prediction errors varied from 0 to 40 percent of the measured signal-to-peak amplitude.

Is scanning in probed order recall articulatory?

PubMed

Farrell, Simon; Lelièvre, Anna

2009-09-01

We consider how theories of serial recall might apply to other short-term memory tasks involving recall of order. In particular, we consider the possibility that when participants are cued to recall an item at an arbitrary position in a sequence, they covertly serially recall the list up to the cued position. One question is whether such "scanning" is articulatory in nature. Two experiments are presented in which the syllabic length of words preceding and following target positions were manipulated, to test the prediction of an articulatory-based mechanism that time to recall an item at a particular position will depend on the number of preceding long words. Although latency was dependent on target position, no word length effects on latency were observed. Additionally, the effects of word length on accuracy replicate recent demonstrations in serial recall that recall accuracy is dependent on the word length of all list items, not just that of target items, in line with distinctiveness assumptions. It is concluded that if scanning does occur, it is not carried out by covert or overt articulation.

Application of high-precision two-way ranging to Galileo Earth-1 encounter navigation

NASA Technical Reports Server (NTRS)

Pollmeier, V. M.; Thurman, S. W.

1992-01-01

The application of precision two-way ranging to orbit determination with relatively short data arcs is investigated for the Galileo spacecraft's approach to its first Earth encounter (December 8, 1990). Analysis of previous S-band (2.3-GHz) ranging data acquired from Galileo indicated that under good signal conditions submeter precision and 10-m ranging accuracy were achieved. It is shown that ranging data of sufficient accuracy, when acquired from multiple stations, can sense the geocentric angular position of a distant spacecraft. A range data filtering technique, in which explicit modeling of range measurement bias parameters for each station pass is utilized, is shown to largely remove the systematic ground system calibration errors and transmission media effects from the Galileo range measurements, which would otherwise corrupt the angle-finding capabilities of the data. The accuracy of the Galileo orbit solutions obtained with S-band Doppler and precision ranging were found to be consistent with simple theoretical calculations, which predicted that angular accuracies of 0.26-0.34 microrad were achievable. In addition, the navigation accuracy achieved with precision ranging was marginally better than that obtained using delta-differenced one-way range (delta DOR), the principal data type that was previously used to obtain spacecraft angular position measurements operationally.

An in vitro study of the accuracy of a new protocol for planning distraction osteogenesis of the mandible.

PubMed

Gateno, J; Allen, M E; Teichgraeber, J F; Messersmith, M L

2000-09-01

The purpose of this study was to determine the in vitro accuracy of a new protocol for distraction osteogenesis of the mandible that involves a planning process and a surgical technique. An experimental design was developed to simulate distraction osteogenesis on stereolithographic models of patients with craniofacial deformities. All patients had previously undergone 3-dimensional computerized scans of the craniofacial skeleton. The data from these scans were used to generate stereolithographic models. Before the fabrication of the models, the computed tomography (CT) data were manipulated to add a series of rulers and markers to the models. The 3-dimensional computerized scans were also used as the basis of the planning process. They were imported into an animation software (3D-Studio Max; Discreet, Montreal, Canada), and a virtual distractor was built and installed on the model, and the osteotomies and distraction processes were simulated. Finally, a recipe for sequencing the linear and angular changes of the distractor were calculated. A surgical technique was developed to facilitate the precise installation of the distractor as indicated in the presurgical plan. The transfer of information regarding pin position and orientation from the computer model to the patient was accomplished by creating a surgical template. This template was designed in the computer and fabricated by use of stereolithography. Mock surgery was performed on the stereolithographic models, and the results were compared with those predicted by the computer. The difference between the actual position and the predicted position was recorded. On the X-axis, the difference between the predicted position for the condylar marker and the actual position of the marker on the stereolithographic models was 0.6 +/- 1.1 mm. On the Y-axis, the difference between the predicted position for the condylar marker and the actual position of the marker on the stereolithographic models was -0.9 +/- 2.6. On the Z-axis, the difference between the predicted position for the condylar marker and the actual position of the marker on the stereolithographic models was 0.04 +/- 0.8 mm. There was excellent correlation between the predicted and the actual measurements for the X, Y, and Z axes: 0.98, 0.93, and 0.98, respectively. The results indicate that the combination of this planning process and surgical technique was very accurate. This in vitro study is the first step in determining the clinical usefulness of this protocol. If the results of this study are validated in clinical practice, this protocol will allow clinicians to improve the clinical outcomes of patients treated with distraction osteogenesis.

Assessing the role of 18F-FDG PET and 18F-FDG PET/CT in the diagnosis of soft tissue musculoskeletal malignancies – A systematic review and meta-analysis

PubMed Central

Etchebehere, Elba C.; Hobbs, Brian P.; R.Milton, Denái; Malawi, Osama; Patel, Shreyaskumar; Benjamin, Robert S.; Macapinlac, Homer A.

2016-01-01

Purpose Twelve years ago a meta-analysis evaluated the diagnostic performance of 18F-FDG PET in assessing musculoskeletal soft tissue lesions (MsSTL). Currently, PET/CT has substituted PET imaging however there has not been any published meta-analysis on the use of PET/CT or a comparison of PET/CT with PET in the diagnosis of MsSTL. Therefore, we conducted a meta-analysis to identify the current diagnostic performance of 18F-FDG PET/CT and determine if there is added value when compared to PET. Patients and Methods A systematic review of English articles using MEDLINE PubMed, the Cochrane Library and EMBASE were searched from 1996 to March 2015. Studies exploring the diagnostic accuracy of 18F-FDG PET/CT (or dedicated PET) compared to histopathology in patients with MsSTL undergoing investigation for malignancy were included. Results Our meta-analysis included 14 articles composed of 755 patients with 757 soft tissue lesions. There were 451 (60%) malignant tumors and 306 benign lesions. The 18F-FDG PET/CT (and dedicated PET) mean sensitivity, specificity, accuracy, positive and negative predictive values for diagnosing MsSTL was 0.96 (0.90, 1.00), 0.77 (0.67, 0.86), 0.88 (0.85, 0.91), 0.86 (0.78, 0.94) and 0.91 (0.83, 0.99), respectively. The posterior mean (95% HPD interval) for the AUC was 0.92 (0.88, 0.96). PET/CT had higher specificity, accuracy and positive predictive value when compared to a dedicated PET (0.85, 0.89 and 0.91 vs 0.71, 0.85 and 0.82, respectively). Conclusions 18F-FDG PET/CT and dedicated PET are both highly accurate in the diagnosis of MsSTL. PET/CT is more accurate, specific and has a higher positive predictive value than PET. PMID:26631240

The use of ex vivo human skin tissue for genotoxicity testing

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

Reus, Astrid A.; Usta, Mustafa; Krul, Cyrille A.M., E-mail: cyrille.krul@tno.nl

2012-06-01

As a result of the chemical legislation concerning the registration, evaluation, authorization and restriction of chemicals (REACH), and the Seventh Amendment to the Cosmetics Directive, which prohibits animal testing in Europe for cosmetics, alternative methods for safety evaluation of chemicals are urgently needed. Current in vitro genotoxicity assays are not sufficiently predictive for the in vivo situation, resulting in an unacceptably high number of misleading positives. For many chemicals and ingredients of personal care products the skin is the first site of contact, but there are no in vitro genotoxicity assays available in the skin for additional evaluation of positivemore » or equivocal responses observed in regulatory in vitro genotoxicity assays. In the present study ex vivo human skin tissue obtained from surgery was used for genotoxicity evaluation of chemicals by using the comet assay. Fresh ex vivo human skin tissue was cultured in an air–liquid interface and topically exposed to 20 chemicals, including true positive, misleading positive and true negative genotoxins. Based on the results obtained in the present study, the sensitivity, specificity and accuracy of the ex vivo skin comet assay to predict in vivo genotoxicity were 89%, 90% and 89%, respectively. Donor and experimental variability were mainly reflected in the magnitude of the response and not the difference between the presence and absence of a genotoxic response. The present study indicates that human skin obtained from surgery is a promising and robust model for safety evaluation of chemicals that are in direct contact with the skin. -- Highlights: ► We use human skin obtained from surgery for genotoxicity evaluation of chemicals. ► We use the comet assay as parameter for genotoxicity in ex vivo human skin. ► Sensitivity, specificity and accuracy to predict in vivo genotoxins are determined. ► Sensitivity, specificity and accuracy are 89%, 90% and 90%, respectively. ► The method is suitable for evaluation of chemicals that are in contact with skin.« less

Flight Test Results: CTAS Cruise/Descent Trajectory Prediction Accuracy for En route ATC Advisories

NASA Technical Reports Server (NTRS)

Green, S.; Grace, M.; Williams, D.

1999-01-01

The Center/TRACON Automation System (CTAS), under development at NASA Ames Research Center, is designed to assist controllers with the management and control of air traffic transitioning to/from congested airspace. This paper focuses on the transition from the en route environment, to high-density terminal airspace, under a time-based arrival-metering constraint. Two flight tests were conducted at the Denver Air Route Traffic Control Center (ARTCC) to study trajectory-prediction accuracy, the key to accurate Decision Support Tool advisories such as conflict detection/resolution and fuel-efficient metering conformance. In collaboration with NASA Langley Research Center, these test were part of an overall effort to research systems and procedures for the integration of CTAS and flight management systems (FMS). The Langley Transport Systems Research Vehicle Boeing 737 airplane flew a combined total of 58 cruise-arrival trajectory runs while following CTAS clearance advisories. Actual trajectories of the airplane were compared to CTAS and FMS predictions to measure trajectory-prediction accuracy and identify the primary sources of error for both. The research airplane was used to evaluate several levels of cockpit automation ranging from conventional avionics to a performance-based vertical navigation (VNAV) FMS. Trajectory prediction accuracy was analyzed with respect to both ARTCC radar tracking and GPS-based aircraft measurements. This paper presents detailed results describing the trajectory accuracy and error sources. Although differences were found in both accuracy and error sources, CTAS accuracy was comparable to the FMS in terms of both meter-fix arrival-time performance (in support of metering) and 4D-trajectory prediction (key to conflict prediction). Overall arrival time errors (mean plus standard deviation) were measured to be approximately 24 seconds during the first flight test (23 runs) and 15 seconds during the second flight test (25 runs). The major source of error during these tests was found to be the predicted winds aloft used by CTAS. Position and velocity estimates of the airplane provided to CTAS by the ATC Host radar tracker were found to be a relatively insignificant error source for the trajectory conditions evaluated. Airplane performance modeling errors within CTAS were found to not significantly affect arrival time errors when the constrained descent procedures were used. The most significant effect related to the flight guidance was observed to be the cross-track and turn-overshoot errors associated with conventional VOR guidance. Lateral navigation (LNAV) guidance significantly reduced both the cross-track and turn-overshoot error. Pilot procedures and VNAV guidance were found to significantly reduce the vertical profile errors associated with atmospheric and aircraft performance model errors.

Evaluating of small intracranial aneurysms by 64-detector CT Angiography: a comparison with 3-dimensional rotation DSA or surgical findings.

PubMed

Zhang, He; Hou, Chang; Zhou, Zhi; Zhang, Hao; Zhou, Gen; Zhang, Gui

2014-01-01

The diagnostic performance of 64-detector computed tomographic angiography (CTA) for detection of small intracranial aneurysms (SIAs) was evaluated. In this prospective study, 112 consecutive patients underwent 64-detector CTA before volume-rendering rotation digital subtraction angiography (VR-RDSA) or surgery. VR-RDSA or intraoperative findings or both were used as the gold standards. The accuracy, sensitivity, specificity, and positive predictive values (PPV) and negative predictive values (NPV), as measures to detect or rule out SIAs, were determined by patient-based and aneurysm size-based evaluations. The reference standard methods revealed 84 small aneurysms in 71 patients. The results of patient-based 64-detector CTA evaluation for SIAs were: accuracy, 98.2%; sensitivity, 98.6%; specificity, 97.6%; PPV, 98.6%; and NPV, 97.6%. The aneurysm-based evaluation results were: accuracy, 96.8%; sensitivity, 97.6%; specificity, 95.1%; PPV, 97.6%; and NPV, 95.1%. Two false-positive and two false-negative findings for aneurysms <3 mm in size occurred in the 64-detector CTA analysis. The diagnostic performance of 64-detector CTA did not improve much compared with 16-detector CTA for detecting SIAs, especially for very small aneurysms. VR-RDSA is still necessary for patients with a history of subarachnoid hemorrhage if the CTA findings are negative. Copyright © 2012 by the American Society of Neuroimaging.

Evaluation of grades 3 and 4 chondromalacia of the knee using T2*-weighted 3D gradient-echo articular cartilage imaging.

PubMed

Murphy, B J

2001-06-01

To determine the accuracy of T2*-weighted three-dimensional (3D) gradient-echo articular cartilage imaging in the identification of grades 3 and 4 chondromalacia of the knee. A retrospective evaluation of 80 patients who underwent both arthroscopic and MRI evaluation was performed. The 3D images were interpreted by one observer without knowledge of the surgical results. The medial and lateral femoral condyles, the medial and lateral tibial plateau, the patellar cartilage and trochlear groove were evaluated. MR cartilage images were considered positive if focal reduction of cartilage thickness was present (grade 3 chondromalacia) or if complete loss of cartilage was present (grade 4 chondromalacia). Comparison of the 3D MR results with the arthroscopic findings was performed. Eighty patients were included in the study group. A total of 480 articular cartilage sites were evaluated with MRI and arthroscopy. Results of MR identification of grades 3 and 4 chondromalacia, all sites combined, were: sensitivity 83%, specificity 97%, false negative rate 17%, false positive rate 3%, positive predictive value 87%, negative predictive value 95%, overall accuracy 93%. The results demonstrate that T2*-weighted 3D gradient-echo articular cartilage imaging can identify grades 3 and 4 chondromalacia of the knee.

Assessing Breast Cancer Risk with an Artificial Neural Network

PubMed

Sepandi, Mojtaba; Taghdir, Maryam; Rezaianzadeh, Abbas; Rahimikazerooni, Salar

2018-04-25

Objectives: Radiologists face uncertainty in making decisions based on their judgment of breast cancer risk. Artificial intelligence and machine learning techniques have been widely applied in detection/recognition of cancer. This study aimed to establish a model to aid radiologists in breast cancer risk estimation. This incorporated imaging methods and fine needle aspiration biopsy (FNAB) for cyto-pathological diagnosis. Methods: An artificial neural network (ANN) technique was used on a retrospectively collected dataset including mammographic results, risk factors, and clinical findings to accurately predict the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: The network incorporating the selected features performed best (AUC = 0.955). Sensitivity and specificity of the ANN were respectively calculated as 0.82 and 0.90. In addition, negative and positive predictive values were respectively computed as 0.90 and 0.80. Conclusion: ANN has potential applications as a decision-support tool to help underperforming practitioners to improve the positive predictive value of biopsy recommendations. Creative Commons Attribution License

A generic approach for the development of short-term predictions of Escherichia coli and biotoxins in shellfish

PubMed Central

Schmidt, Wiebke; Evers-King, Hayley L.; Campos, Carlos J. A.; Jones, Darren B.; Miller, Peter I.; Davidson, Keith; Shutler, Jamie D.

2018-01-01

Microbiological contamination or elevated marine biotoxin concentrations within shellfish can result in temporary closure of shellfish aquaculture harvesting, leading to financial loss for the aquaculture business and a potential reduction in consumer confidence in shellfish products. We present a method for predicting short-term variations in shellfish concentrations of Escherichia coli and biotoxin (okadaic acid and its derivates dinophysistoxins and pectenotoxins). The approach was evaluated for 2 contrasting shellfish harvesting areas. Through a meta-data analysis and using environmental data (in situ, satellite observations and meteorological nowcasts and forecasts), key environmental drivers were identified and used to develop models to predict E. coli and biotoxin concentrations within shellfish. Models were trained and evaluated using independent datasets, and the best models were identified based on the model exhibiting the lowest root mean square error. The best biotoxin model was able to provide 1 wk forecasts with an accuracy of 86%, a 0% false positive rate and a 0% false discovery rate (n = 78 observations) when used to predict the closure of shellfish beds due to biotoxin. The best E. coli models were used to predict the European hygiene classification of the shellfish beds to an accuracy of 99% (n = 107 observations) and 98% (n = 63 observations) for a bay (St Austell Bay) and an estuary (Turnaware Bar), respectively. This generic approach enables high accuracy short-term farm-specific forecasts, based on readily accessible environmental data and observations. PMID:29805719

Neural Network Prediction of ICU Length of Stay Following Cardiac Surgery Based on Pre-Incision Variables

PubMed Central

Pothula, Venu M.; Yuan, Stanley C.; Maerz, David A.; Montes, Lucresia; Oleszkiewicz, Stephen M.; Yusupov, Albert; Perline, Richard

2015-01-01

Background Advanced predictive analytical techniques are being increasingly applied to clinical risk assessment. This study compared a neural network model to several other models in predicting the length of stay (LOS) in the cardiac surgical intensive care unit (ICU) based on pre-incision patient characteristics. Methods Thirty six variables collected from 185 cardiac surgical patients were analyzed for contribution to ICU LOS. The Automatic Linear Modeling (ALM) module of IBM-SPSS software identified 8 factors with statistically significant associations with ICU LOS; these factors were also analyzed with the Artificial Neural Network (ANN) module of the same software. The weighted contributions of each factor (“trained” data) were then applied to data for a “new” patient to predict ICU LOS for that individual. Results Factors identified in the ALM model were: use of an intra-aortic balloon pump; O2 delivery index; age; use of positive cardiac inotropic agents; hematocrit; serum creatinine ≥ 1.3 mg/deciliter; gender; arterial pCO2. The r2 value for ALM prediction of ICU LOS in the initial (training) model was 0.356, p <0.0001. Cross validation in prediction of a “new” patient yielded r2 = 0.200, p <0.0001. The same 8 factors analyzed with ANN yielded a training prediction r2 of 0.535 (p <0.0001) and a cross validation prediction r2 of 0.410, p <0.0001. Two additional predictive algorithms were studied, but they had lower prediction accuracies. Our validated neural network model identified the upper quartile of ICU LOS with an odds ratio of 9.8(p <0.0001). Conclusions ANN demonstrated a 2-fold greater accuracy than ALM in prediction of observed ICU LOS. This greater accuracy would be presumed to result from the capacity of ANN to capture nonlinear effects and higher order interactions. Predictive modeling may be of value in early anticipation of risks of post-operative morbidity and utilization of ICU facilities. PMID:26710254

ROC-ing along: Evaluation and interpretation of receiver operating characteristic curves.

PubMed

Carter, Jane V; Pan, Jianmin; Rai, Shesh N; Galandiuk, Susan

2016-06-01

It is vital for clinicians to understand and interpret correctly medical statistics as used in clinical studies. In this review, we address current issues and focus on delivering a simple, yet comprehensive, explanation of common research methodology involving receiver operating characteristic (ROC) curves. ROC curves are used most commonly in medicine as a means of evaluating diagnostic tests. Sample data from a plasma test for the diagnosis of colorectal cancer were used to generate a prediction model. These are actual, unpublished data that have been used to describe the calculation of sensitivity, specificity, positive predictive and negative predictive values, and accuracy. The ROC curves were generated to determine the accuracy of this plasma test. These curves are generated by plotting the sensitivity (true-positive rate) on the y axis and 1 - specificity (false-positive rate) on the x axis. Curves that approach closest to the coordinate (x = 0, y = 1) are more highly predictive, whereas ROC curves that lie close to the line of equality indicate that the result is no better than that obtained by chance. The optimum sensitivity and specificity can be determined from the graph as the point where the minimum distance line crosses the ROC curve. This point corresponds to the Youden index (J), a function of sensitivity and specificity used commonly to rate diagnostic tests. The area under the curve is used to quantify the overall ability of a test to discriminate between 2 outcomes. By following these simple guidelines, interpretation of ROC curves will be less difficult and they can then be interpreted more reliably when writing, reviewing, or analyzing scientific papers. Copyright © 2016 Elsevier Inc. All rights reserved.

Predictive performance of the Vitrigel‐eye irritancy test method using 118 chemicals

PubMed Central

Yamaguchi, Hiroyuki; Kojima, Hajime

2015-01-01

Abstract We recently developed a novel Vitrigel‐eye irritancy test (EIT) method. The Vitrigel‐EIT method is composed of two parts, i.e., the construction of a human corneal epithelium (HCE) model in a collagen vitrigel membrane chamber and the prediction of eye irritancy by analyzing the time‐dependent profile of transepithelial electrical resistance values for 3 min after exposing a chemical to the HCE model. In this study, we estimated the predictive performance of Vitrigel‐EIT method by testing a total of 118 chemicals. The category determined by the Vitrigel‐EIT method in comparison to the globally harmonized system classification revealed that the sensitivity, specificity and accuracy were 90.1%, 65.9% and 80.5%, respectively. Here, five of seven false‐negative chemicals were acidic chemicals inducing the irregular rising of transepithelial electrical resistance values. In case of eliminating the test chemical solutions showing pH 5 or lower, the sensitivity, specificity and accuracy were improved to 96.8%, 67.4% and 84.4%, respectively. Meanwhile, nine of 16 false‐positive chemicals were classified irritant by the US Environmental Protection Agency. In addition, the disappearance of ZO‐1, a tight junction‐associated protein and MUC1, a cell membrane‐spanning mucin was immunohistologically confirmed in the HCE models after exposing not only eye irritant chemicals but also false‐positive chemicals, suggesting that such false‐positive chemicals have an eye irritant potential. These data demonstrated that the Vitrigel‐EIT method could provide excellent predictive performance to judge the widespread eye irritancy, including very mild irritant chemicals. We hope that the Vitrigel‐EIT method contributes to the development of safe commodity chemicals. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd. PMID:26472347

Sequence-Specific Model for Peptide Retention Time Prediction in Strong Cation Exchange Chromatography.

PubMed

Gussakovsky, Daniel; Neustaeter, Haley; Spicer, Victor; Krokhin, Oleg V

2017-11-07

The development of a peptide retention prediction model for strong cation exchange (SCX) separation on a Polysulfoethyl A column is reported. Off-line 2D LC-MS/MS analysis (SCX-RPLC) of S. cerevisiae whole cell lysate was used to generate a retention dataset of ∼30 000 peptides, sufficient for identifying the major sequence-specific features of peptide retention mechanisms in SCX. In contrast to RPLC/hydrophilic interaction liquid chromatography (HILIC) separation modes, where retention is driven by hydrophobic/hydrophilic contributions of all individual residues, SCX interactions depend mainly on peptide charge (number of basic residues at acidic pH) and size. An additive model (incorporating the contributions of all 20 residues into the peptide retention) combined with a peptide length correction produces a 0.976 R 2 value prediction accuracy, significantly higher than the additive models for either HILIC or RPLC. Position-dependent effects on peptide retention for different residues were driven by the spatial orientation of tryptic peptides upon interaction with the negatively charged surface functional groups. The positively charged N-termini serve as a primary point of interaction. For example, basic residues (Arg, His, Lys) increase peptide retention when located closer to the N-terminus. We also found that hydrophobic interactions, which could lead to a mixed-mode separation mechanism, are largely suppressed at 20-30% of acetonitrile in the eluent. The accuracy of the final Sequence-Specific Retention Calculator (SSRCalc) SCX model (∼0.99 R 2 value) exceeds all previously reported predictors for peptide LC separations. This also provides a solid platform for method development in 2D LC-MS protocols in proteomics and peptide retention prediction filtering of false positive identifications.

Occultation Predictions Using CCD Strip-Scanning Astrometry

NASA Technical Reports Server (NTRS)

Dunham, Edward W.; Ford, C. H.; Stone, R. P. S.; McDonald, S. W.; Olkin, C. B.; Elliot, J. L.; Witteborn, Fred C. (Technical Monitor)

1994-01-01

We are developing the method of CCD strip-scanning astrometry for the purpose of deriving reliable advance predictions for occultations involving small objects in the outer solar system. We are using a camera system based on a Ford/Loral 2Kx2K CCD with the Crossley telescope at Lick Observatory for this work. The columns of die CCD are aligned East-West, the telescope drive is stopped, and the CCD is clocked at the same rate that the stars drift across it. In this way we obtain arbitrary length strip images 20 arcmin wide with 0.58" pixels. Since planets move mainly in RA, it is possible to obtain images of the planet and star to be occulted on the same strip well before the occultation occurs. The strip-to-strip precision (i.e. reproducibility) of positions is limited by atmospheric image motion to about 0.1" rms per strip. However, for objects that are nearby in R.A., the image motion is highly correlated and their relative positions are good to 0.02" rms per strip. We will show that the effects of atmospheric image motion on a given strip can be removed if a sufficient number of strips of a given area have been obtained. Thus, it is possible to reach an rms precision of 0.02" per strip, corresponding to about 0.3 of Pluto or Triton's angular radius. The ultimate accuracy of a prediction based on strip-scanning astrometry is currently limited by the accuracy of the positions of the stars in the astrometric network used and by systematic errors most likely due to the optical system. We will show the results of . the prediction of some recent occultations as examples of the current capabilities and limitations of this technique.

[Evaluation of serology as a diagnostic method for Helicobacter pylori infection in the local population of Guayaquil].

PubMed

Zapatier, Jorge A; Gómez, Néstor A; Vargas, Paola E; Maya, Susana V

2007-06-01

The infection with Helicobacter pylori (H. pylori), and the diagnostic efficacy of the serologic tests has certain variability among the different geographic regions. The objective of the present work was to find the local validation of serological methods for diagnosis of H. pylori infection and to determine the best cutoff value for the local population. Forty-eight patients were evaluated, 27 males and 21 females, with a mean age of 29.2 years. On each patient, 3 tests for H. pylori diagnosis were performed: IgG serology, IgA serology and histology. We performed IgG and IgA serologic test for H. pylori infection and a histological examination for each patient. Efficacy parameters as well as the ROC curve were obtained for the IgG and IgA serology using histology as the gold standard. The cutoff point with the highest efficacy for IgG serology was 16 U/ml (sensitivity 81%, specificity 65%, positive predictive value 81%, negative predictive value 65%, and accuracy 75%), and for IgA serology was 17 U/ml (sensitivity 61%, specificity 53%, positive predictive value 70%, negative predictive value 43%, and accuracy 58%). The area under the curve was 67.1% (CI 95%: 50 to 84.1) and 54.4% (CI 95%: 38.3 to 72.5) for IgG and IgA respectively. The serology is a valuable tool in our population with high prevalence of H. pylori, especially due to its low cost and easy performance, but a reduction ofthe cutoff value was necessary to obtain more sensibility and a more adequate identification of true positives cases.

Accuracy of a Mouse Bioassay for the Diagnosis of Botulism in Horses.

PubMed

Johnson, A L; McAdams-Gallagher, S C; Aceto, H

2016-07-01

The laboratory diagnosis of botulism in horses traditionally has relied upon the mouse bioassay (MBA). The accuracy of this test for the diagnosis of botulism in horses is unknown. Our goal was to determine the sensitivity, specificity, positive predictive value, and negative predictive value of the MBA on laboratory-processed fecal and gastrointestinal samples for foals and adult horses. Cases included all horses with a final clinical diagnosis of botulism that were admitted between 1986 and 2011 and had MBA testing performed. Controls included horses without botulism that were admitted during the same time period and had MBA testing performed. Retrospective study. Horses suspected of having botulism had fecal or (less commonly) gastrointestinal content samples tested using MBA. For every hospitalized botulism suspect, control samples were obtained from ≥1 additional hospitalized horses not suspected to have botulism. One hundred and twenty-nine adult horses and 253 adult controls were identified. Overall sensitivity of the MBA was only 32% but specificity was 97%. Forty-three foal cases and 21 foal controls were evaluated; sensitivity of the MBA was 53% and specificity was 100%. Positive predictive value was substantially higher (100% for foals and 89% for adults) than negative predictive value (51% for foals and 67% for adults). Mouse bioassay has low sensitivity but high specificity for the diagnosis of botulism in horses. Positive results are highly suggestive of botulism but negative results do not exclude the diagnosis. Unaffected horses and foals rarely shed C. botulinum in their feces. Copyright © 2016 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Focal point determination in magnetic resonance-guided focused ultrasound using tracking coils.

PubMed

Svedin, Bryant T; Beck, Michael J; Hadley, J Rock; Merrill, Robb; de Bever, Joshua T; Bolster, Bradley D; Payne, Allison; Parker, Dennis L

2017-06-01

To develop a method for rapid prediction of the geometric focus location in MR coordinates of a focused ultrasound (US) transducer with arbitrary position and orientation without sonicating. Three small tracker coil circuits were designed, constructed, attached to the transducer housing of a breast-specific MR-guided focused US (MRgFUS) system with 5 degrees of freedom, and connected to receiver channel inputs of an MRI scanner. A one-dimensional sequence applied in three orthogonal directions determined the position of each tracker, which was then corrected for gradient nonlinearity. In a calibration step, low-level heating located the US focus in one transducer position orientation where the tracker positions were also known. Subsequent US focus locations were determined from the isometric transformation of the trackers. The accuracy of this method was verified by comparing the tracking coil predictions to thermal center of mass calculated using MR thermometry data acquired at 16 different transducer positions for MRgFUS sonications in a homogeneous gelatin phantom. The tracker coil predicted focus was an average distance of 2.1 ± 1.1 mm from the thermal center of mass. The one-dimensional locator sequence and prediction calculations took less than 1 s to perform. This technique accurately predicts the geometric focus for a transducer with arbitrary position and orientation without sonicating. Magn Reson Med 77:2424-2430, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Arrhythmia Evaluation in Wearable ECG Devices

PubMed Central

Sadrawi, Muammar; Lin, Chien-Hung; Hsieh, Yita; Kuo, Chia-Chun; Chien, Jen Chien; Haraikawa, Koichi; Abbod, Maysam F.; Shieh, Jiann-Shing

2017-01-01

This study evaluates four databases from PhysioNet: The American Heart Association database (AHADB), Creighton University Ventricular Tachyarrhythmia database (CUDB), MIT-BIH Arrhythmia database (MITDB), and MIT-BIH Noise Stress Test database (NSTDB). The ANSI/AAMI EC57:2012 is used for the evaluation of the algorithms for the supraventricular ectopic beat (SVEB), ventricular ectopic beat (VEB), atrial fibrillation (AF), and ventricular fibrillation (VF) via the evaluation of the sensitivity, positive predictivity and false positive rate. Sample entropy, fast Fourier transform (FFT), and multilayer perceptron neural network with backpropagation training algorithm are selected for the integrated detection algorithms. For this study, the result for SVEB has some improvements compared to a previous study that also utilized ANSI/AAMI EC57. In further, VEB sensitivity and positive predictivity gross evaluations have greater than 80%, except for the positive predictivity of the NSTDB database. For AF gross evaluation of MITDB database, the results show very good classification, excluding the episode sensitivity. In advanced, for VF gross evaluation, the episode sensitivity and positive predictivity for the AHADB, MITDB, and CUDB, have greater than 80%, except for MITDB episode positive predictivity, which is 75%. The achieved results show that the proposed integrated SVEB, VEB, AF, and VF detection algorithm has an accurate classification according to ANSI/AAMI EC57:2012. In conclusion, the proposed integrated detection algorithm can achieve good accuracy in comparison with other previous studies. Furthermore, more advanced algorithms and hardware devices should be performed in future for arrhythmia detection and evaluation. PMID:29068369

Football experts versus sports economists: Whose forecasts are better?

PubMed

Frick, Bernd; Wicker, Pamela

2016-08-01

Given the uncertainty of outcome in sport, predicting the outcome of sporting contests is a major topic in sport sciences. This study examines the accuracy of expert predictions in the German Bundesliga and compares their predictions to those of sports economists. Prior to the start of each season, a set of distinguished experts (head coaches and players) express their subjective evaluations of the teams in school grades. While experts may be driven by irrational sentiments and may therefore systematically over- or underestimate specific teams, sports economists use observable characteristics to predict season outcomes. The latter typically use team wage bills given the positive pay-performance relationship as well as other factors (average team age, tenure, appearances on national team, and attendance). Using data from 15 consecutive Bundesliga seasons, the predictive accuracy of expert evaluations and sports economists is analysed. The results of separate estimations show that relative grade and relative wage bill significantly affect relative points, while age, tenure, appearances, and attendance are insignificant. In a joint model, relative grade and relative wage bill are still statistically significant, suggesting that the two types of predictions are complements rather than substitutes. Consequently, football experts and sports economists seem to rely on completely different sources of information when making their predictions.

A prediction tool incorporating the biomarker S-100B for patient selection for completion lymph node dissection in stage III melanoma.

PubMed

Damude, S; Wevers, K P; Murali, R; Kruijff, S; Hoekstra, H J; Bastiaannet, E

2017-09-01

Completion lymph node dissection (CLND) in sentinel node (SN)-positive melanoma patients is accompanied with morbidity, while about 80% yield no additional metastases in non-sentinel nodes (NSNs). A prediction tool for NSN involvement could be of assistance in patient selection for CLND. This study investigated which parameters predict NSN-positivity, and whether the biomarker S-100B improves the accuracy of a prediction model. Recorded clinicopathologic factors were tested for their association with NSN-positivity in 110 SN-positive patients who underwent CLND. A prediction model was developed with multivariable logistic regression, incorporating all predictive factors. Five models were compared for their predictive power by calculating the Area Under the Curve (AUC). A weighted risk score, 'S-100B Non-Sentinel Node Risk Score' (SN-SNORS), was derived for the model with the highest AUC. Besides, a nomogram was developed as visual representation. NSN-positivity was present in 24 (21.8%) patients. Sex, ulceration, number of harvested SNs, number of positive SNs, and S-100B value were independently associated with NSN-positivity. The AUC for the model including all these factors was 0.78 (95%CI 0.69-0.88). SN-SNORS was the sum of scores for the five parameters. Scores of ≤9.5, 10-11.5, and ≥12 were associated with low (0%), intermediate (21.0%) and high (43.2%) risk of NSN involvement. A prediction tool based on five parameters, including the biomarker S-100B, showed accurate risk stratification for NSN-involvement in SN-positive melanoma patients. If validated in future studies, this tool could help to identify patients with low risk for NSN-involvement. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Predictive genetic testing for the identification of high-risk groups: a simulation study on the impact of predictive ability

PubMed Central

2011-01-01

Background Genetic risk models could potentially be useful in identifying high-risk groups for the prevention of complex diseases. We investigated the performance of this risk stratification strategy by examining epidemiological parameters that impact the predictive ability of risk models. Methods We assessed sensitivity, specificity, and positive and negative predictive value for all possible risk thresholds that can define high-risk groups and investigated how these measures depend on the frequency of disease in the population, the frequency of the high-risk group, and the discriminative accuracy of the risk model, as assessed by the area under the receiver-operating characteristic curve (AUC). In a simulation study, we modeled genetic risk scores of 50 genes with equal odds ratios and genotype frequencies, and varied the odds ratios and the disease frequency across scenarios. We also performed a simulation of age-related macular degeneration risk prediction based on published odds ratios and frequencies for six genetic risk variants. Results We show that when the frequency of the high-risk group was lower than the disease frequency, positive predictive value increased with the AUC but sensitivity remained low. When the frequency of the high-risk group was higher than the disease frequency, sensitivity was high but positive predictive value remained low. When both frequencies were equal, both positive predictive value and sensitivity increased with increasing AUC, but higher AUC was needed to maximize both measures. Conclusions The performance of risk stratification is strongly determined by the frequency of the high-risk group relative to the frequency of disease in the population. The identification of high-risk groups with appreciable combinations of sensitivity and positive predictive value requires higher AUC. PMID:21797996

Predicting Player Position for Talent Identification in Association Football

NASA Astrophysics Data System (ADS)

Razali, Nazim; Mustapha, Aida; Yatim, Faiz Ahmad; Aziz, Ruhaya Ab

2017-08-01

This paper is set to introduce a new framework from the perspective of Computer Science for identifying talents in the sport of football based on the players’ individual qualities; physical, mental, and technical. The combination of qualities as assessed by coaches are then used to predict the players’ position in a match that suits the player the best in a particular team formation. Evaluation of the proposed framework is two-fold; quantitatively via classification experiments to predict player position, and qualitatively via a Talent Identification Site developed to achieve the same goal. Results from the classification experiments using Bayesian Networks, Decision Trees, and K-Nearest Neighbor have shown an average of 98% accuracy, which will promote consistency in decision-making though elimination of personal bias in team selection. The positive reviews on the Football Identification Site based on user acceptance evaluation also indicates that the framework is sufficient to serve as the basis of developing an intelligent team management system in different sports, whereby growth and performance of sport players can be monitored and identified.

Using DNA mechanics to predict in vitro nucleosome positions and formation energies

PubMed Central

Morozov, Alexandre V.; Fortney, Karissa; Gaykalova, Daria A.; Studitsky, Vasily M.; Widom, Jonathan; Siggia, Eric D.

2009-01-01

In eukaryotic genomes, nucleosomes function to compact DNA and to regulate access to it both by simple physical occlusion and by providing the substrate for numerous covalent epigenetic tags. While competition with other DNA-binding factors and action of chromatin remodeling enzymes significantly affect nucleosome formation in vivo, nucleosome positions in vitro are determined by steric exclusion and sequence alone. We have developed a biophysical model, DNABEND, for the sequence dependence of DNA bending energies, and validated it against a collection of in vitro free energies of nucleosome formation and a set of in vitro nucleosome positions mapped at high resolution. We have also made a first ab initio prediction of nucleosomal DNA geometries, and checked its accuracy against the nucleosome crystal structure. We have used DNABEND to design both strong and weak histone- binding sequences, and measured the corresponding free energies of nucleosome formation. We find that DNABEND can successfully predict in vitro nucleosome positions and free energies, providing a physical explanation for the intrinsic sequence dependence of histone–DNA interactions. PMID:19509309

Overall accuracy of cervical cytology and clinicopathological significance of LSIL cells in ASC-H cytology.

PubMed

Kim, S H; Lee, J M; Yun, H G; Park, U S; Hwang, S U; Pyo, J-S; Sohn, J H

2017-02-01

The aims of this study were (i) to investigate the diagnostic accuracy of Papanicolaou (Pap) smears and (ii) to evaluate the clinicopathological significance of the presence of low-grade squamous intraepithelial lesion (LSIL) cells in atypical squamous cells cannot exclude high-grade squamous intraepithelial lesion (HSIL) (ASC-H) cytology. We retrospectively reviewed paired cytological and histological findings from 3141 patients. ASC-H cytology was classified as either ASC-H or LSIL with some features suggestive of the presence of a concurrent HSIL (LSIL-H). Clinicopathological characteristics were evaluated through a retrospective study and meta-analysis. The accuracy of the cytological diagnosis was 93.7% (2942 of 3141 cases). The positive predictive value (PPV) of ASC-H for cervical intraepithelial neoplasia grade 2 or worse (CIN 2+ ) was 51.4%. In cases of LSIL-H, CIN 2+ histology was more prevalent in the pre-menopausal period (19-44 years) than in peri- and postmenopausal periods (older than 45 years) (P = 0.024). There was no difference in the ability of LSIL-H and ASC-H to predict CIN 2+. The Pap smear is a good cervical cancer screening method. Although there was no difference in the predictive value for CIN 2+ between LSIL-H and ASC-H, the presence of definite LSIL cells was more predictive of CIN 2+ in younger patients than in older patients. © 2016 John Wiley & Sons Ltd.

Transmembrane protein topology prediction using support vector machines.

PubMed

Nugent, Timothy; Jones, David T

2009-05-26

Alpha-helical transmembrane (TM) proteins are involved in a wide range of important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion. Many are also prime drug targets, and it has been estimated that more than half of all drugs currently on the market target membrane proteins. However, due to the experimental difficulties involved in obtaining high quality crystals, this class of protein is severely under-represented in structural databases. In the absence of structural data, sequence-based prediction methods allow TM protein topology to be investigated. We present a support vector machine-based (SVM) TM protein topology predictor that integrates both signal peptide and re-entrant helix prediction, benchmarked with full cross-validation on a novel data set of 131 sequences with known crystal structures. The method achieves topology prediction accuracy of 89%, while signal peptides and re-entrant helices are predicted with 93% and 44% accuracy respectively. An additional SVM trained to discriminate between globular and TM proteins detected zero false positives, with a low false negative rate of 0.4%. We present the results of applying these tools to a number of complete genomes. Source code, data sets and a web server are freely available from http://bioinf.cs.ucl.ac.uk/psipred/. The high accuracy of TM topology prediction which includes detection of both signal peptides and re-entrant helices, combined with the ability to effectively discriminate between TM and globular proteins, make this method ideally suited to whole genome annotation of alpha-helical transmembrane proteins.

Improving the accuracy of protein stability predictions with multistate design using a variety of backbone ensembles.

PubMed

Davey, James A; Chica, Roberto A

2014-05-01

Multistate computational protein design (MSD) with backbone ensembles approximating conformational flexibility can predict higher quality sequences than single-state design with a single fixed backbone. However, it is currently unclear what characteristics of backbone ensembles are required for the accurate prediction of protein sequence stability. In this study, we aimed to improve the accuracy of protein stability predictions made with MSD by using a variety of backbone ensembles to recapitulate the experimentally measured stability of 85 Streptococcal protein G domain β1 sequences. Ensembles tested here include an NMR ensemble as well as those generated by molecular dynamics (MD) simulations, by Backrub motions, and by PertMin, a new method that we developed involving the perturbation of atomic coordinates followed by energy minimization. MSD with the PertMin ensembles resulted in the most accurate predictions by providing the highest number of stable sequences in the top 25, and by correctly binning sequences as stable or unstable with the highest success rate (≈90%) and the lowest number of false positives. The performance of PertMin ensembles is due to the fact that their members closely resemble the input crystal structure and have low potential energy. Conversely, the NMR ensemble as well as those generated by MD simulations at 500 or 1000 K reduced prediction accuracy due to their low structural similarity to the crystal structure. The ensembles tested herein thus represent on- or off-target models of the native protein fold and could be used in future studies to design for desired properties other than stability. Copyright © 2013 Wiley Periodicals, Inc.

Early prediction of lung cancer recurrence after stereotactic radiotherapy using second order texture statistics

NASA Astrophysics Data System (ADS)

Mattonen, Sarah A.; Palma, David A.; Haasbeek, Cornelis J. A.; Senan, Suresh; Ward, Aaron D.

2014-03-01

Benign radiation-induced lung injury is a common finding following stereotactic ablative radiotherapy (SABR) for lung cancer, and is often difficult to differentiate from a recurring tumour due to the ablative doses and highly conformal treatment with SABR. Current approaches to treatment response assessment have shown limited ability to predict recurrence within 6 months of treatment. The purpose of our study was to evaluate the accuracy of second order texture statistics for prediction of eventual recurrence based on computed tomography (CT) images acquired within 6 months of treatment, and compare with the performance of first order appearance and lesion size measures. Consolidative and ground-glass opacity (GGO) regions were manually delineated on post-SABR CT images. Automatic consolidation expansion was also investigated to act as a surrogate for GGO position. The top features for prediction of recurrence were all texture features within the GGO and included energy, entropy, correlation, inertia, and first order texture (standard deviation of density). These predicted recurrence with 2-fold cross validation (CV) accuracies of 70-77% at 2- 5 months post-SABR, with energy, entropy, and first order texture having leave-one-out CV accuracies greater than 80%. Our results also suggest that automatic expansion of the consolidation region could eliminate the need for manual delineation, and produced reproducible results when compared to manually delineated GGO. If validated on a larger data set, this could lead to a clinically useful computer-aided diagnosis system for prediction of recurrence within 6 months of SABR and allow for early salvage therapy for patients with recurrence.

Positive affect, intuition, and feelings of meaning.

PubMed

Hicks, Joshua A; Cicero, David C; Trent, Jason; Burton, Chad M; King, Laura A

2010-06-01

Subjective rationality, or the feeling of meaning, was identified by William James (1893) as a central aspect of the non-sensory fringe of consciousness. Three studies examined the interaction of positive affect (PA) and individual differences in intuitive information processing in predicting feelings of meaning for various stimuli and life events. In Study 1 (N = 352), PA and intuition interacted to predict understanding for ambiguous quotes and abstract artwork. In Study 2 (N = 211), similar interactions were found for feelings of meaning for fans after their football team lost a conference championship game and for individuals not directly affected by Hurricane Katrina in events surrounding the hurricane. In Study 3 (N = 41), induced PA interacted with individual differences in intuition in predicting accuracy for coherence judgments for loosely related linguistic triads. Intuitive individuals in the positive mood condition recognized coherent triads more accurately than did other participants. Results are discussed in terms of the role of individual differences in intuitive information processing in the relationship of PA to cognition. (c) 2010 APA, all rights reserved).

Cross-national comparison of screening mammography accuracy measures in U.S., Norway, and Spain.

PubMed

Domingo, Laia; Hofvind, Solveig; Hubbard, Rebecca A; Román, Marta; Benkeser, David; Sala, Maria; Castells, Xavier

2016-08-01

To compare accuracy measures for mammographic screening in Norway, Spain, and the US. Information from women aged 50-69 years who underwent mammographic screening 1996-2009 in the US (898,418 women), Norway (527,464), and Spain (517,317) was included. Screen-detected cancer, interval cancer, and the false-positive rates, sensitivity, specificity, positive predictive value (PPV) for recalls (PPV-1), PPV for biopsies (PPV-2), 1/PPV-1 and 1/PPV-2 were computed for each country. Analyses were stratified by age, screening history, time since last screening, calendar year, and mammography modality. The rate of screen-detected cancers was 4.5, 5.5, and 4.0 per 1000 screening exams in the US, Norway, and Spain respectively. The highest sensitivity and lowest specificity were reported in the US (83.1 % and 91.3 %, respectively), followed by Spain (79.0 % and 96.2 %) and Norway (75.5 % and 97.1 %). In Norway, Spain and the US, PPV-1 was 16.4 %, 9.8 %, and 4.9 %, and PPV-2 was 39.4 %, 38.9 %, and 25.9 %, respectively. The number of women needed to recall to detect one cancer was 20.3, 6.1, and 10.2 in the US, Norway, and Spain, respectively. Differences were found across countries, suggesting that opportunistic screening may translate into higher sensitivity at the cost of lower specificity and PPV. • Positive predictive value is higher in population-based screening programmes in Spain and Norway. • Opportunistic mammography screening in the US has lower positive predictive value. • Screening settings in the US translate into higher sensitivity and lower specificity. • The clinical burden may be higher for women screened opportunistically.

Diagnostic value of 99mTc-bombesin scintigraphy for differentiation of malignant from benign breast lesions.

PubMed

Shariati, Farzaneh; Aryana, Kamran; Fattahi, Asiehsadat; Forghani, Mohammad N; Azarian, Azita; Zakavi, Seyed R; Sadeghi, Ramin; Ayati, Narjes; Sadri, Keyvan

2014-06-01

In this study, we evaluated the diagnostic accuracy of (99m)Tc-bombesin scintigraphy for differentiation of benign from malignant palpable breast lesions. (99m)Tc-Bombesin is a tracer with high affinity for gastrin-releasing peptide receptor, which is overexpressed on a variety of human tumors including breast carcinoma. We examined 33 consecutive women who were referred to our center with suspicious palpable breast lesions but had no definitive diagnosis in other imaging procedures. A volume of 370-444 MBq of (99m)Tc-bombesin was injected and dynamic 1-min images were taken for 20 min immediately after injection in anterior view. Thereafter, two static images in anterior and prone-lateral views were taken for 5 min. Finally, single-photon emission computed tomography images were taken for each patient. Definitive diagnosis was based on biopsy and histopathological evaluation. The scan findings were positive in 19 patients and negative in 11 on visual assessment of the planar and single-photon emission computed tomography images. Pathologic examination confirmed breast carcinoma in 12 patients with positive scans and benign pathology for 18 patients. The overall sensitivity, specificity, negative and positive predictive values, and accuracy of this radiotracer for diagnosis of breast cancer were 100, 66.1, 100, 63, and 76%, respectively. Semiquantitative analysis improved the specificity of the visual assessment from 66 to 84%. Our study showed that (99m)Tc-bombesin scintigraphy has a high sensitivity and negative predictive value for detecting malignant breast lesions, but the specificity and positive predictive value of this radiotracer for differentiation of malignant breast abnormalities from benign ones are relatively low.

Accuracy of CNV Detection from GWAS Data.

PubMed

Zhang, Dandan; Qian, Yudong; Akula, Nirmala; Alliey-Rodriguez, Ney; Tang, Jinsong; Gershon, Elliot S; Liu, Chunyu

2011-01-13

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.

Using support vector machine to predict beta- and gamma-turns in proteins.

PubMed

Hu, Xiuzhen; Li, Qianzhong

2008-09-01

By using the composite vector with increment of diversity, position conservation scoring function, and predictive secondary structures to express the information of sequence, a support vector machine (SVM) algorithm for predicting beta- and gamma-turns in the proteins is proposed. The 426 and 320 nonhomologous protein chains described by Guruprasad and Rajkumar (Guruprasad and Rajkumar J. Biosci 2000, 25,143) are used for training and testing the predictive model of the beta- and gamma-turns, respectively. The overall prediction accuracy and the Matthews correlation coefficient in 7-fold cross-validation are 79.8% and 0.47, respectively, for the beta-turns. The overall prediction accuracy in 5-fold cross-validation is 61.0% for the gamma-turns. These results are significantly higher than the other algorithms in the prediction of beta- and gamma-turns using the same datasets. In addition, the 547 and 823 nonhomologous protein chains described by Fuchs and Alix (Fuchs and Alix Proteins: Struct Funct Bioinform 2005, 59, 828) are used for training and testing the predictive model of the beta- and gamma-turns, and better results are obtained. This algorithm may be helpful to improve the performance of protein turns' prediction. To ensure the ability of the SVM method to correctly classify beta-turn and non-beta-turn (gamma-turn and non-gamma-turn), the receiver operating characteristic threshold independent measure curves are provided. (c) 2008 Wiley Periodicals, Inc.

Computed tomography arthrography using a radial plane view for the detection of triangular fibrocartilage complex foveal tears.

PubMed

Moritomo, Hisao; Arimitsu, Sayuri; Kubo, Nobuyuki; Masatomi, Takashi; Yukioka, Masao

2015-02-01

To classify triangular fibrocartilage complex (TFCC) foveal lesions on the basis of computed tomography (CT) arthrography using a radial plane view and to correlate the CT arthrography results with surgical findings. We also tested the interobserver and intra-observer reliability of the radial plane view. A total of 33 patients with a suspected TFCC foveal tear who had undergone wrist CT arthrography and subsequent surgical exploration were enrolled. We classified the configurations of TFCC foveal lesions into 5 types on the basis of CT arthrography with the radial plane view in which the image slices rotate clockwise centered on the ulnar styloid process. Sensitivity, specificity, and positive predictive values were calculated for each type of foveal lesion in CT arthrography to detect foveal tears. We determined interobserver and intra-observer agreements using kappa statistics. We also compared accuracies with the radial plane views with those with the coronal plane views. Among the tear types on CT arthrography, type 3, a roundish defect at the fovea, and type 4, a large defect at the overall ulnar insertion, had high specificity and positive predictive value for the detection of foveal tears. Specificity and positive predictive values were 90% and 89% for type 3 and 100% and 100% for type 4, respectively, whereas sensitivity was 35% for type 3 and 22% for type 4. Interobserver and intra-observer agreement was substantial and almost perfect, respectively. The radial plane view identified foveal lesion of each palmar and dorsal radioulnar ligament separately, but accuracy results with the radial plane views were not statistically different from those with the coronal plane views. Computed tomography arthrography with a radial plane view exhibited enhanced specificity and positive predictive value when a type 3 or 4 lesion was identified in the detection of a TFCC foveal tear compared with historical controls. Diagnostic II. Copyright © 2015 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

The diagnostic accuracy of physical examination compared to lung ultrasound for determining lung congestion in hemodialysis patients who have reached their dry weight

NASA Astrophysics Data System (ADS)

Rahardjo, K. D.; Dharmaeizar; Nainggolan, G.; Harimurti, K.

2017-08-01

Research has shown that hemodialysis patients with lung congestion have high morbidity and mortality. Patients were assumed to be free of lung congestion if they had reached their post-dialysis dry weight. Most often, to determine if the patient was free of lung congestion, physical examination was used. However, the accuracy of physical examination in detecting lung congestion has not been established. To compare the capabilities of physical examination and lung ultrasound in detection of lung congestion, cross-sectional data collection was conducted on hemodialysis patients. Analysis was done to obtain proportion, sensitivity, specificity, positive predictive value, negative predictive value, and positive likelihood ratio. Sixty patients participated in this study. The inter observer variation of 20 patients revealed a kappa value of 0.828. When all 60 patients were taken into account, we found that 36 patients (57.1%) had lung congestion. Mild lung congestion was found in 24 (38.1%), and 12 (19%) had a moderate degree of congestion. In the analysis comparing jugular venous pressure to lung ultrasound, we found that sensitivity was 0.47 (0.31-0.63), specificity was 0.73 (0.54-0.86), positive predictive value (PPV) was 0.51 (0.36-0.67), negative predictive value (NPV) was 0.70 (0.49-0.84), positive likelihood ratio (PLR) was 1.75 (0.88-3.47), and the negative likelihood ratio (NLR) was 0.72 (0.47-1.12). In terms of lung auscultation, we found that sensitivity was 0.56 (0.39-0.71), specificity was 0.54 (0.35-0.71), PPV was 0.61 (0.44-0.76), NPV was 0.48 (0.31-0.66), PLR was 1.21 (0.73-2.0), and NLR was 0.82 (0.49-1.38). The results of our study showed that jugular venous distention and lung auscultation examination are not reliable means of detecting lung congestion.

Noninvasive scoring system for significant inflammation related to chronic hepatitis B

NASA Astrophysics Data System (ADS)

Hong, Mei-Zhu; Ye, Linglong; Jin, Li-Xin; Ren, Yan-Dan; Yu, Xiao-Fang; Liu, Xiao-Bin; Zhang, Ru-Mian; Fang, Kuangnan; Pan, Jin-Shui

2017-03-01

Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A total of 396 patients with chronic hepatitis B were enrolled in the present study. Liver biopsies were performed, liver histology was scored using the Scheuer scoring system, and serum markers and liver function were investigated. Inflammatory activity scoring models were constructed for both hepatitis B envelope antigen (+) and hepatitis B envelope antigen (-) patients. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 86.00%, 84.80%, 62.32%, 95.39%, and 0.9219, respectively, in the hepatitis B envelope antigen (+) group and 91.89%, 89.86%, 70.83%, 97.64%, and 0.9691, respectively, in the hepatitis B envelope antigen (-) group. Significant inflammation related to chronic hepatitis B can be predicted with satisfactory accuracy by using our logistic regression-based scoring system.

Starry sky sign: A prevalent sonographic finding in mediastinal tuberculous lymph nodes.

PubMed

Alici, Ibrahim Onur; Demirci, Nilg N Yilmaz; Yilmaz, Aydin; Karakaya, Jale; Erdogan, Yurdanur

2015-01-01

We report a prevalent finding in tuberculous lymphadenitis (TL): Starry sky sign, hyperechoic foci without acoustic shadows over a hypoechoic background. We retrospectively searched the database for a possible relationship of starry sky sign with a specific diagnosis and also the prevalence and accuracy of the finding. Starry sky sign was found in 16 of 31 tuberculous lymph nodes, while none of other lymph nodes (1,015 lymph nodes) exhibited this finding; giving a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of 51.6%, 100%, 100%, 98.5%, and 98.5%, respectively. Bacteriologic and histologic findings are gold standard in the diagnosis of tuberculosis, but this finding may guide the bronchoscopist in choosing the more pathologic node within a station and increase the diagnostic yield as it may relate to actively dividing mycobacteria.

Accuracy of Ultrasonography and Magnetic Resonance Imaging in the Diagnosis of Placenta Accreta

PubMed Central

Riteau, Anne-Sophie; Tassin, Mikael; Chambon, Guillemette; Le Vaillant, Claudine; de Laveaucoupet, Jocelyne; Quéré, Marie-Pierre; Joubert, Madeleine; Prevot, Sophie; Philippe, Henri-Jean; Benachi, Alexandra

2014-01-01

Purpose To evaluate the accuracy of ultrasonography and magnetic resonance imaging (MRI) in the diagnosis of placenta accreta and to define the most relevant specific ultrasound and MRI features that may predict placental invasion. Material and Methods This study was approved by the institutional review board of the French College of Obstetricians and Gynecologists. We retrospectively reviewed the medical records of all patients referred for suspected placenta accreta to two university hospitals from 01/2001 to 05/2012. Our study population included 42 pregnant women who had been investigated by both ultrasonography and MRI. Ultrasound images and MRI were blindly reassessed for each case by 2 raters in order to score features that predict abnormal placental invasion. Results Sensitivity in the diagnosis of placenta accreta was 100% with ultrasound and 76.9% for MRI (P = 0.03). Specificity was 37.5% with ultrasonography and 50% for MRI (P = 0.6). The features of greatest sensitivity on ultrasonography were intraplacental lacunae and loss of the normal retroplacental clear space. Increased vascularization in the uterine serosa-bladder wall interface and vascularization perpendicular to the uterine wall had the best positive predictive value (92%). At MRI, uterine bulging had the best positive predictive value (85%) and its combination with the presence of dark intraplacental bands on T2-weighted images improved the predictive value to 90%. Conclusion Ultrasound imaging is the mainstay of screening for placenta accreta. MRI appears to be complementary to ultrasonography, especially when there are few ultrasound signs. PMID:24733409

Assessment of Ultrasound Features Predicting Axillary Nodal Metastasis in Breast Cancer: The Impact of Cortical Thickness

PubMed Central

Stachs, A.; Thi, A. Tra-Ha; Dieterich, M.; Stubert, J.; Hartmann, S.; Glass, Ä.; Reimer, T.; Gerber, B.

2015-01-01

Purpose: To evaluate the accuracy of axillary ultrasound (AUS) in detecting nodal metastasis in patients with early-stage breast cancer and to identify AUS features with high predictive power. Materials and Methods: Prospective single-center preliminary study in 105 patients with a primary diagnosis of breast cancer and clinically negative axilla. AUS was performed using a 12 MHz linear-array transducer before ultrasound-guided needle biopsy. Nodal characteristics (shape, longitudinal-transverse [LT] axis ratio, margins, cortical thickness, hyperechoic hilum) were correlated with histopathological nodal status after SLNB or axillary lymph node dissection (ALND). Results: Nodal metastases were present in 42/105 patients (40.0%). Univariate analyses showed that absence of hyperechoic hilum, round shape, LT axis ratio<2, sharp margins and cortical thickness>3 mm were associated with lymph node metastasis. Multivariate logistic regression analysis revealed cortical thickness > 3 mm as an independent predictive parameter for nodal involvement. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 66.7, 74.6, 63.6, 77.0% and 71.4% respectively when cortical thickness > 3 mm was applied as the criterion for AUS positivity. Axillary tumor volume was low in patients with pT1/2 tumors and negative AUS, since only 3.2% of patients had > 2 metastatic lymph nodes. Conclusion: Cortical thickness>3 mm is a reliable predictor of nodal metastatic involvement. Negative AUS does not exclude lymph node metastases, but extensive axillary tumor volume is rare. PMID:27689144

Prediction of Dementia in Primary Care Patients

PubMed Central

Jessen, Frank; Wiese, Birgitt; Bickel, Horst; Eiffländer-Gorfer, Sandra; Fuchs, Angela; Kaduszkiewicz, Hanna; Köhler, Mirjam; Luck, Tobias; Mösch, Edelgard; Pentzek, Michael; Riedel-Heller, Steffi G.; Wagner, Michael; Weyerer, Siegfried; Maier, Wolfgang; van den Bussche, Hendrik

2011-01-01

Background Current approaches for AD prediction are based on biomarkers, which are however of restricted availability in primary care. AD prediction tools for primary care are therefore needed. We present a prediction score based on information that can be obtained in the primary care setting. Methodology/Principal Findings We performed a longitudinal cohort study in 3.055 non-demented individuals above 75 years recruited via primary care chart registries (Study on Aging, Cognition and Dementia, AgeCoDe). After the baseline investigation we performed three follow-up investigations at 18 months intervals with incident dementia as the primary outcome. The best set of predictors was extracted from the baseline variables in one randomly selected half of the sample. This set included age, subjective memory impairment, performance on delayed verbal recall and verbal fluency, on the Mini-Mental-State-Examination, and on an instrumental activities of daily living scale. These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD. The score was applied to the second half of the sample (test cohort). Here, the prediction accuracy was 0.79. With a cut-off of at least 80% sensitivity in the first cohort, 79.6% sensitivity, 66.4% specificity, 14.7% positive predictive value (PPV) and 97.8% negative predictive value of (NPV) for AD were achieved in the test cohort. At a cut-off for a high risk population (5% of individuals with the highest risk score in the first cohort) the PPV for AD was 39.1% (52% for any dementia) in the test cohort. Conclusions The prediction score has useful prediction accuracy. It can define individuals (1) sensitively for low cost-low risk interventions, or (2) more specific and with increased PPV for measures of prevention with greater costs or risks. As it is independent of technical aids, it may be used within large scale prevention programs. PMID:21364746

Prediction of dementia in primary care patients.

PubMed

Jessen, Frank; Wiese, Birgitt; Bickel, Horst; Eiffländer-Gorfer, Sandra; Fuchs, Angela; Kaduszkiewicz, Hanna; Köhler, Mirjam; Luck, Tobias; Mösch, Edelgard; Pentzek, Michael; Riedel-Heller, Steffi G; Wagner, Michael; Weyerer, Siegfried; Maier, Wolfgang; van den Bussche, Hendrik

2011-02-18

Current approaches for AD prediction are based on biomarkers, which are however of restricted availability in primary care. AD prediction tools for primary care are therefore needed. We present a prediction score based on information that can be obtained in the primary care setting. We performed a longitudinal cohort study in 3.055 non-demented individuals above 75 years recruited via primary care chart registries (Study on Aging, Cognition and Dementia, AgeCoDe). After the baseline investigation we performed three follow-up investigations at 18 months intervals with incident dementia as the primary outcome. The best set of predictors was extracted from the baseline variables in one randomly selected half of the sample. This set included age, subjective memory impairment, performance on delayed verbal recall and verbal fluency, on the Mini-Mental-State-Examination, and on an instrumental activities of daily living scale. These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD. The score was applied to the second half of the sample (test cohort). Here, the prediction accuracy was 0.79. With a cut-off of at least 80% sensitivity in the first cohort, 79.6% sensitivity, 66.4% specificity, 14.7% positive predictive value (PPV) and 97.8% negative predictive value of (NPV) for AD were achieved in the test cohort. At a cut-off for a high risk population (5% of individuals with the highest risk score in the first cohort) the PPV for AD was 39.1% (52% for any dementia) in the test cohort. The prediction score has useful prediction accuracy. It can define individuals (1) sensitively for low cost-low risk interventions, or (2) more specific and with increased PPV for measures of prevention with greater costs or risks. As it is independent of technical aids, it may be used within large scale prevention programs.

In-house PCR with DNA extracted directly from positive slides to confirm or exclude the diagnosis of tuberculosis: focus on biosafety.

PubMed

de Almeida, Isabela Neves; Aleixo, Agdemir Valéria; Carvalho, Wânia da Silva; de Miranda, Silvana Spindola

2015-01-01

The possibility to obtain DNA from smears is a valuable alternative to remedy the lack of samples when they are totally used for bacilloscopy; this technique solves the biosafety problem related to a possible accident with the transportation of flasks containing potentially transmissible clinical samples. Hence, the purpose of this study was to utilize the insertion sequence IS6110 for amplification of DNA from a smear-positive sample for tuberculosis (TB) diagnosis. Among the 52 positive bacilloscopies, sensitivity, specificity, positive predictive value and negative predictive value were 52.3%, 100%, 100% and 89.7%, respectively whereas accuracy was 90.7%. The IS6110-based PCR for TB diagnosis developed in DNA extracted from a positive smear is a fast, simple, specific, and safe method. Copyright © 2014 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Development and validation of the SIMPLE endoscopic classification of diminutive and small colorectal polyps.

PubMed

Iacucci, Marietta; Trovato, Cristina; Daperno, Marco; Akinola, Oluseyi; Greenwald, David; Gross, Seth A; Hoffman, Arthur; Lee, Jeffrey; Lethebe, Brendan C; Lowerison, Mark; Nayor, Jennifer; Neumann, Helmut; Rath, Timo; Sanduleanu, Silvia; Sharma, Prateek; Kiesslich, Ralf; Ghosh, Subrata; Saltzman, John R

2018-03-23

Prediction of histology of small polyps facilitates colonoscopic treatment. The aims of this study were: 1) to develop a simplified polyp classification, 2) to evaluate its performance in predicting polyp histology, and 3) to evaluate the reproducibility of the classification by trainees using multiplatform endoscopic systems. In phase 1, a new simplified endoscopic classification for polyps - Simplified Identification Method for Polyp Labeling during Endoscopy (SIMPLE) - was created, using the new I-SCAN OE system (Pentax, Tokyo, Japan), by eight international experts. In phase 2, the accuracy, level of confidence, and interobserver agreement to predict polyp histology before and after training, and univariable/multivariable analysis of the endoscopic features, were performed. In phase 3, the reproducibility of SIMPLE by trainees using different endoscopy platforms was evaluated. Using the SIMPLE classification, the accuracy of experts in predicting polyps was 83 % (95 % confidence interval [CI] 77 % - 88 %) before and 94 % (95 %CI 89 % - 97 %) after training ( P   = 0.002). The sensitivity, specificity, positive predictive value, and negative predictive value after training were 97 %, 88 %, 95 %, and 91 %. The interobserver agreement of polyp diagnosis improved from 0.46 (95 %CI 0.30 - 0.64) before to 0.66 (95 %CI 0.48 - 0.82) after training. The trainees demonstrated that the SIMPLE classification is applicable across endoscopy platforms, with similar post-training accuracies for narrow-band imaging NBI classification (0.69; 95 %CI 0.64 - 0.73) and SIMPLE (0.71; 95 %CI 0.67 - 0.75). Using the I-SCAN OE system, the new SIMPLE classification demonstrated a high degree of accuracy for adenoma diagnosis, meeting the ASGE PIVI recommendations. We demonstrated that SIMPLE may be used with either I-SCAN OE or NBI. © Georg Thieme Verlag KG Stuttgart · New York.

Does Incorporating Change in APRI or FIB-4 Indices Over Time Improve the Accuracy of a Single Index for Identifying Liver Fibrosis in Persons With Chronic Hepatitis C Virus Infection?

PubMed

Gounder, Prabhu P; Haering, Celia; Bruden, Dana J T; Townshend-Bulson, Lisa; Simons, Brenna C; Spradling, Philip R; McMahon, Brian J

2018-01-01

The aspartate aminotransferase-to-platelet ratio index (APRI) and a fibrosis index calculated using platelets (FIB-4) have been proposed as noninvasive markers of liver fibrosis. To determine APRI/FIB-4 accuracy for predicting histologic liver fibrosis and evaluate whether incorporating change in index improves test accuracy in hepatitis C virus (HCV)-infected Alaska Native persons. Using liver histology as the gold standard, we determined the test characteristics of APRI to predict Metavir ≥F2 fibrosis and FIB-4 to predict Metavir ≥F3 fibrosis. Index discrimination was measured as the area under the receiver operator characteristic curve. We fit a logistic regression model to determine whether incorporating change in APRI/FIB-4 over time improved index discrimination. Among 283 participants, 46% were female, 48% had a body mass index >30, 11% had diabetes mellitus, 8% reported current heavy alcohol use. Participants were infected with HCV genotypes 1 (68%), 2 (17%), or 3 (15%). On liver histology, 30% of study participants had ≥F2 fibrosis and 15% had ≥F3 fibrosis. The positive predictive value of an APRI>1.5/FIB-4>3.25 for identifying fibrosis was 77%/78%. The negative predictive value of an APRI<0.5/FIB-4<1.45 was 91%/87%. The area under the receiver operator characteristic curve of an APRI/FIB-4 for identifying fibrosis was 0.82/0.84. Incorporating change in APRI/FIB-4 did not improve index discrimination. The accuracy of APRI/FIB-4 for identifying liver fibrosis in HCV-infected Alaska Native persons is similar to that reported in other populations and could help prioritize patients for treatment living in areas without access to liver biopsy. Change in APRI/FIB-4 was not predictive of degree of fibrosis.

COMSAT: Residue contact prediction of transmembrane proteins based on support vector machines and mixed integer linear programming.

PubMed

Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A

2016-03-01

In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/. © 2016 Wiley Periodicals, Inc.

Diagnostic accuracy of patch test in children with food allergy.

PubMed

Caglayan Sozmen, Sule; Povesi Dascola, Carlotta; Gioia, Edoardo; Mastrorilli, Carla; Rizzuti, Laura; Caffarelli, Carlo

2015-08-01

The gold standard test for confirming whether a child has clinical hypersensitivity reactions to foods is the oral food challenge. Therefore, there is increasing interest in simpler diagnostic markers of food allergy, especially in children, to avoid oral food challenge. The goal of this study was to assess the diagnostic accuracy of atopy patch test in comparison with oral food challenge. We investigated 243 children (mean age, 51 months) referred for evaluation of suspected egg or cow's milk allergy. Skin prick test and atopy patch test were carried out, and after a 2 weeks elimination diet, oral food challenge was performed. Two hundred and forty-three children underwent OFC to the suspected food. We found clinically relevant food allergies in 40 (65%) children to egg and in 22 (35%) to cow's milk. The sensitivity of skin prick test for both milk and egg was 92%, specificity 91%, positive predictive value 35%, and negative predictive value of 93%. Sensitivity, specificity, positive predictive value, and negative predictive value of atopy patch test for both milk and egg were 21%, 73%, 20%, and 74%, respectively. Our study suggests that there is insufficient evidence for the routine use of atopy patch test for the evaluation of egg and cow's milk allergy. OFC remains gold standard for the diagnosis of egg and milk allergy even in the presence of high costs in terms of both time and risks during application. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Diagnostic value of 18F-FDG-PET/CT for the follow-up and restaging of soft tissue sarcomas in adults.

PubMed

Kassem, T W; Abdelaziz, O; Emad-Eldin, S

2017-10-01

The purpose of this study was to evaluate the clinical utility of 2-[ 18 F] fluoro-2-deoxy-D-glucose ( 18 FDG) positron emission tomography (PET)/computed tomography (CT) ( 18 F-FDG-PET/CT) in the follow-up of adult patients with soft tissue sarcomas. We prospectively evaluated 37 consecutive patients with known soft tissue sarcoma with 18 F-FDG-PET/CT examination for suspected recurrence of disease. They were 21 men and 16 women with a mean age of 49.6±10.6 (SD) years (range, 34-75years). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of 18 F-FDG-PET/CT examination were calculated on a per patient basis. 18 F-FDG-PET/CT showed an overall diagnostic accuracy of 91.8%, sensitivity of 90% and a specificity of 100%. The positive predictive value and negative predictive value were 100 and 70%, respectively. The 18 F-FDG-PET/CT interpretations were correct in 34/37 patients (91.8%). Incorrect interpretations occurred in three patients (8.1%). Reasons for false negative findings were low 18 F-FDG uptake of local recurrence in one patient and low 18 F-FDG uptake of subcentimetric inguinal lymph node metastases. 18 F-FDG-PET/CT has a high diagnostic value in the follow-up of patients with soft tissue sarcoma. Copyright © 2017 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

[Predictive value of breast imaging report and database system (BIRADS) to detect cancer in a reference regional hospital].

PubMed

Bellolio, Enrique; Pineda, Viviana; Burgos, María Eugenia; Iriarte, M José; Becker, Renato; Araya, Juan Carlos; Villaseca, Miguel; Mardones, Noldy

2015-12-01

To validate the BIRADS in mammography, the calculation of its predictive value in each center is required, as recommended by the American College of Radiology. To determine the predictive value of the BIRADS system in our center. All ultrasound guided needle percutaneous biopsies, performed at our center between 2006 and 2010 were reviewed. Predictive value, sensitivity, specificity and diagnostic accuracy of BIRADS were calculated, with a confidence interval of 95%. Of 1,313 biopsies available, 1,058 met the inclusion criteria. Fifty eight percent of biopsies were performed to women with mammographies classified as BIRADS 4 or 5. The presence of cancer in mammographies classified as BIRADS 0 was 4%. The prevalence of cancer for mammographies BIRADS 1, 2, 3, 4 and 5 were 0, 3, 2.7, 17.7 and 72.4% respectively. The positive and negative predictive values of BIRADS classification were 55 and 92 % respectively. In our institution BIRADS classification 4 and 5 has a high positive predictive value for detecting cancer as in developed countries.

Collision prediction software for radiotherapy treatments.

PubMed

Padilla, Laura; Pearson, Erik A; Pelizzari, Charles A

2015-11-01

This work presents a method of collision predictions for external beam radiotherapy using surface imaging. The present methodology focuses on collision prediction during treatment simulation to evaluate the clearance of a patient's treatment position and allow for its modification if necessary. A Kinect camera (Microsoft, Redmond, WA) is used to scan the patient and immobilization devices in the treatment position at the simulator. The surface is reconstructed using the skanect software (Occipital, Inc., San Francisco, CA). The treatment isocenter is marked using simulated orthogonal lasers projected on the surface scan. The point cloud of this surface is then shifted to isocenter and converted from Cartesian to cylindrical coordinates. A slab models the treatment couch. A cylinder with a radius equal to the normal distance from isocenter to the collimator plate, and a height defined by the collimator diameter is used to estimate collisions. Points within the cylinder clear through a full gantry rotation with the treatment couch at 0°, while points outside of it collide. The angles of collision are reported. This methodology was experimentally verified using a mannequin positioned in an alpha cradle with both arms up. A planning CT scan of the mannequin was performed, two isocenters were marked in pinnacle, and this information was exported to AlignRT (VisionRT, London, UK)--a surface imaging system for patient positioning. This was used to ensure accurate positioning of the mannequin in the treatment room, when available. Collision calculations were performed for the two treatment isocenters and the results compared to the collisions detected the room. The accuracy of the Kinect-Skanect surface was evaluated by comparing it to the external surface of the planning CT scan. Experimental verification results showed that the predicted angles of collision matched those recorded in the room within 0.5°, in most cases (largest deviation -1.2°). The accuracy study for the Kinect-Skanect surface showed an average discrepancy between the CT external contour and the surface scan of 2.2 mm. This methodology provides fast and reliable collision predictions using surface imaging. The use of the Kinect-Skanect system allows for a comprehensive modeling of the patient topography including all the relevant anatomy and immobilization devices that may lead to collisions. The use of this tool at the treatment simulation stage may allow therapists to evaluate the clearance of a patient's treatment position and optimize it before the planning CT scan is performed. This can allow for safer treatments for the patients due to better collision predictions and improved clinical workflow by minimizing replanning and resimulations due to unforeseen clearance issues.

Diagnostic Accuracy of APRI, AAR, FIB-4, FI, King, Lok, Forns, and FibroIndex Scores in Predicting the Presence of Esophageal Varices in Liver Cirrhosis

PubMed Central

Deng, Han; Qi, Xingshun; Guo, Xiaozhong

2015-01-01

Abstract Aspartate aminotransferase-to-platelet ratio (APRI), aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), FIB-4, FI, King, Lok, Forns, and FibroIndex scores may be simple and convenient noninvasive diagnostic tests, because they are based on the regular laboratory tests and demographic data. This study aimed to systematically evaluate their diagnostic accuracy for the prediction of varices in liver cirrhosis. All relevant papers were searched via PubMed, EMBASE, CNKI, and Wanfang databases. The area under the summary receiver operating characteristic curve (AUSROC), sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR), and diagnostic odds ratio (DOR) were calculated. Overall, 12, 4, 5, 0, 0, 4, 3, and 1 paper was identified to explore the diagnostic accuracy of APRI, AAR, FIB-4, FI, King, Lok, Forns, and FibroIndex scores, respectively. The AUSROCs of APRI, AAR, FIB-4, Lok, and Forns scores for the prediction of varices were 0.6774, 0.7275, 0.7755, 0.7885, and 0.7517, respectively; and those for the prediction of large varices were 0.7278, 0.7448, 0.7095, 0.7264, and 0.6530, respectively. The diagnostic threshold effects of FIB-4 and Forns scores for the prediction of varices were statistically significant. The sensitivities/specificities/PLRs/NLRs/DORs of APRI, AAR, and Lok scores for the prediction of varices were 0.60/0.67/1.77/0.58/3.13, 0.64/0.63/1.97/0.54/4.18, and 0.74/0.68/2.34/0.40/5.76, respectively. The sensitivities/specificities/PLRs/NLRs/DORs of APRI, AAR, FIB-4, Lok, and Forns scores for the prediction of large varices were 0.65/0.66/2.15/0.47/4.97, 0.68/0.58/2.07/0.54/3.93, 0.62/0.64/2.02/0.56/3.57, 0.78/0.63/2.09/0.37/5.55, and 0.65/0.61/1.62/0.59/2.75, respectively. APRI, AAR, FIB-4, Lok, and Forns scores had low to moderate diagnostic accuracy in predicting the presence of varices in liver cirrhosis. PMID:26496312

A scoring algorithm for predicting the presence of adult asthma: a prospective derivation study.

PubMed

Tomita, Katsuyuki; Sano, Hiroyuki; Chiba, Yasutaka; Sato, Ryuji; Sano, Akiko; Nishiyama, Osamu; Iwanaga, Takashi; Higashimoto, Yuji; Haraguchi, Ryuta; Tohda, Yuji

2013-03-01

To predict the presence of asthma in adult patients with respiratory symptoms, we developed a scoring algorithm using clinical parameters. We prospectively analysed 566 adult outpatients who visited Kinki University Hospital for the first time with complaints of nonspecific respiratory symptoms. Asthma was comprehensively diagnosed by specialists using symptoms, signs, and objective tools including bronchodilator reversibility and/or the assessment of bronchial hyperresponsiveness (BHR). Multiple logistic regression analysis was performed to categorise patients and determine the accuracy of diagnosing asthma. A scoring algorithm using the symptom-sign score was developed, based on diurnal variation of symptoms (1 point), recurrent episodes (2 points), medical history of allergic diseases (1 point), and wheeze sound (2 points). A score of >3 had 35% sensitivity and 97% specificity for discriminating between patients with and without asthma and assigned a high probability of having asthma (accuracy 90%). A score of 1 or 2 points assigned intermediate probability (accuracy 68%). After providing additional data of forced expiratory volume in 1 second/forced vital capacity (FEV(1)/FVC) ratio <0.7, the post-test probability of having asthma was increased to 93%. A score of 0 points assigned low probability (accuracy 31%). After providing additional data of positive reversibility, the post-test probability of having asthma was increased to 88%. This pragmatic diagnostic algorithm is useful for predicting the presence of adult asthma and for determining the appropriate time for consultation with a pulmonologist.

Diagnostic accuracy of CT in assessing extra-regional lymphadenopathy in pancreatic and peri-ampullary cancer: a systematic review and meta-analysis.

PubMed

Tseng, Dorine S J; van Santvoort, Hjalmar C; Fegrachi, Samira; Besselink, Marc G; Zuithoff, Nicolaas P A; Borel Rinkes, Inne H; van Leeuwen, Maarten S; Molenaar, I Quintus

2014-12-01

Computed tomography (CT) is the most widely used method to assess resectability of pancreatic and peri-ampullary cancer. One of the contra-indications for curative resection is the presence of extra-regional lymph node metastases. This meta-analysis investigates the accuracy of CT in assessing extra-regional lymph node metastases in pancreatic and peri-ampullary cancer. We systematically reviewed the literature according to the PRISMA guidelines. Studies reporting on CT assessment of extra-regional lymph nodes in patients undergoing pancreatoduodenectomy were included. Data on baseline characteristics, CT-investigations and histopathological outcomes were extracted. Diagnostic accuracy, positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity were calculated for individual studies and pooled data. After screening, 4 cohort studies reporting on CT-findings and histopathological outcome in 157 patients with pancreatic or peri-ampullary cancer were included. Overall, diagnostic accuracy, specificity and NPV varied from 63 to 81, 80-100% and 67-90% respectively. However, PPV and sensitivity ranged from 0 to 100% and 0-38%. Pooled sensitivity, specificity, PPV and NPV were 25%, 86%, 28% and 84% respectively. CT has a low diagnostic accuracy in assessing extra-regional lymph node metastases in pancreatic and peri-ampullary cancer. Therefore, suspicion of extra-regional lymph node metastases on CT alone should not be considered a contra-indication for exploration. Copyright © 2014 Elsevier Ltd. All rights reserved.

Time-Resolved Intrafraction Target Translations and Rotations During Stereotactic Liver Radiation Therapy: Implications for Marker-based Localization Accuracy

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

Bertholet, Jenny, E-mail: jennbe@rm.dk; Worm, Esben S.; Fledelius, Walther

Purpose: Image guided liver stereotactic body radiation therapy (SBRT) often relies on implanted fiducial markers. The target localization accuracy decreases with increased marker-target distance. This may occur partly because of liver rotations. The aim of this study was to examine time-resolved translations and rotations of liver marker constellations and investigate if time-resolved intrafraction rotational corrections can improve localization accuracy in liver SBRT. Methods and Materials: Twenty-nine patients with 3 implanted markers received SBRT in 3 to 6 fractions. The time-resolved trajectory of each marker was estimated from the projections of 1 to 3 daily cone beam computed tomography scans andmore » used to calculate the translation and rotation of the marker constellation. In all cone beam computed tomography projections, the time-resolved position of each marker was predicted from the position of another surrogate marker by assuming that the marker underwent either (1) the same translation as the surrogate marker; or (2) the same translation as the surrogate marker corrected by the rotation of the marker constellation. The localization accuracy was quantified as the root-mean-square error (RMSE) between the estimated and the actual marker position. For comparison, the RMSE was also calculated when the marker's position was estimated as its mean position for all the projections. Results: The mean translational and rotational range (2nd-98th percentile) was 2.0 mm/3.9° (right-left), 9.2 mm/2.9° (superior-inferior), 4.0 mm/4.0° (anterior-posterior), and 10.5 mm (3-dimensional). Rotational corrections decreased the mean 3-dimensional RMSE from 0.86 mm to 0.54 mm (P<.001) and halved the RMSE increase per millimeter increase in marker distance. Conclusions: Intrafraction rotations during liver SBRT reduce the accuracy of marker-guided target localization. Rotational correction can improve the localization accuracy with a factor of approximately 2 for large marker-target distances.« less

Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region

PubMed Central

Penížek, Vít; Zádorová, Tereza; Kodešová, Radka; Vaněk, Aleš

2016-01-01

The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. PMID:27846230

Circumferential resection margin positivity after preoperative chemoradiotherapy based on magnetic resonance imaging for locally advanced rectal cancer: implication of boost radiotherapy to the involved mesorectal fascia.

PubMed

Kim, Kyung Hwan; Park, Min Jung; Lim, Joon Seok; Kim, Nam Kyu; Min, Byung Soh; Ahn, Joong Bae; Kim, Tae Il; Kim, Ho Geun; Koom, Woong Sub

2016-04-01

To identify patients who are at a higher risk of pathologic circumferential resection margin involvement using preoperative magnetic resonance imaging. Between October 2008 and November 2012, 165 patients with locally advanced rectal cancer (cT4 or cT3 with <2 mm distance from tumour to mesorectal fascia) who received preoperative chemoradiotherapy were analysed. The morphologic patterns on post-chemoradiotherapy magnetic resonance imaging were categorized into five patterns from Pattern A (most-likely negative pathologic circumferential resection margin) to Pattern E (most-likely positive pathologic circumferential resection margin). In addition, the location of mesorectal fascia involvement was classified as lateral, posterior and anterior. The diagnostic accuracy of the morphologic criteria was calculated using receiver operating characteristic curve analysis. Pathologic circumferential resection margin involvement was identified in 17 patients (10.3%). The diagnostic accuracy of predicting pathologic circumferential resection margin involvement was 0.73 using the five-scale magnetic resonance imaging pattern. The sensitivity, specificity, positive predictive value and negative predictive value for predicting pathologic circumferential resection margin involvement were 76.5, 65.5, 20.3 and 96.0%, respectively, when cut-off was set between Patterns C and D. On multivariate logistic regression, the magnetic resonance imaging patterns D and E (P= 0.005) and posterior or lateral mesorectal fascia involvement (P= 0.017) were independently associated with increased probability of pathologic circumferential resection margin involvement. The rate of pathologic circumferential resection margin involvement was 30.0% when the patient had Pattern D or E with posterior or lateral mesorectal fascia involvement. Patients who are at a higher risk of pathologic circumferential resection margin involvement can be identified using preoperative magnetic resonance imaging although the predictability is moderate. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Usefulness of a Novel Ultrasonographic Classification Based on Anechoic Area Patterns for Differentiating Warthin Tumors from Pleomorphic Adenomas of the Parotid Gland

PubMed Central

Matsuda, Eriko; Fukuhara, Takahiro; Donishi, Ryohei; Kawamoto, Katsuyuki; Hirooka, Yasuaki; Takeuchi, Hiromi

2018-01-01

Background Ultrasonographic homogeneity is an important differential finding between Warthin tumor and pleomorphic adenoma, two types of benign parotid gland tumors, with the former likely to be heterogeneous and the latter homogeneous. However, differences in the performance of ultrasound machines or the homogeneity cut-off level affect the judgment of ultrasonographic homogeneity. Therefore, in this study, we adopted a novel system for classifying the composition of tumors via ultrasonography, using anechoic area as a substitute for differences in homogeneity to differentiate between Warthin tumors and pleomorphic adenomas. Methods We evaluated 68 tumors that were histopathologically diagnosed as Warthin tumor or pleomorphic adenoma between July 2009 and November 2015. Ultrasonographic images of the tumors were evaluated on the basis of key differentiating features, including features on B-mode imaging and color Doppler imaging. Additionally, the tumors were classified into four groups based on anechoic area, and findings were compared between Warthin tumors and pleomorphic adenomas. Results While 38 of the tumors were pleomorphic adenomas, 30 were Warthin tumors. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for detection of Warthin tumors using our novel classification system were 73.3%, 76.3%, 71.0%, 78.4% and 75.0%, respectively. Compared to pleomorphic adenomas, Warthin tumors showed large or sponge-like anechoic areas, rich vascularization and an oval shape even at large tumor sizes, and the difference was significant. On defining Warthin tumor as a tumor demonstrating two or more of the findings noted above, the sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy for its detection were 73.3%, 84.2%, 78.6%, 80.0% and 79.4%, respectively. Conclusion Our novel classification system based on anechoic area patterns demonstrated by the tumors had high sensitivity, specificity and diagnostic accuracy for differentiating Warthin tumors from pleomorphic adenomas. PMID:29434491

Usefulness of a Novel Ultrasonographic Classification Based on Anechoic Area Patterns for Differentiating Warthin Tumors from Pleomorphic Adenomas of the Parotid Gland.

PubMed

Matsuda, Eriko; Fukuhara, Takahiro; Donishi, Ryohei; Kawamoto, Katsuyuki; Hirooka, Yasuaki; Takeuchi, Hiromi

2017-12-01

Ultrasonographic homogeneity is an important differential finding between Warthin tumor and pleomorphic adenoma, two types of benign parotid gland tumors, with the former likely to be heterogeneous and the latter homogeneous. However, differences in the performance of ultrasound machines or the homogeneity cut-off level affect the judgment of ultrasonographic homogeneity. Therefore, in this study, we adopted a novel system for classifying the composition of tumors via ultrasonography, using anechoic area as a substitute for differences in homogeneity to differentiate between Warthin tumors and pleomorphic adenomas. We evaluated 68 tumors that were histopathologically diagnosed as Warthin tumor or pleomorphic adenoma between July 2009 and November 2015. Ultrasonographic images of the tumors were evaluated on the basis of key differentiating features, including features on B-mode imaging and color Doppler imaging. Additionally, the tumors were classified into four groups based on anechoic area, and findings were compared between Warthin tumors and pleomorphic adenomas. While 38 of the tumors were pleomorphic adenomas, 30 were Warthin tumors. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for detection of Warthin tumors using our novel classification system were 73.3%, 76.3%, 71.0%, 78.4% and 75.0%, respectively. Compared to pleomorphic adenomas, Warthin tumors showed large or sponge-like anechoic areas, rich vascularization and an oval shape even at large tumor sizes, and the difference was significant. On defining Warthin tumor as a tumor demonstrating two or more of the findings noted above, the sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy for its detection were 73.3%, 84.2%, 78.6%, 80.0% and 79.4%, respectively. Our novel classification system based on anechoic area patterns demonstrated by the tumors had high sensitivity, specificity and diagnostic accuracy for differentiating Warthin tumors from pleomorphic adenomas.

Predictive accuracy of risk scales following self-harm: multicentre, prospective cohort study†

PubMed Central

Quinlivan, Leah; Cooper, Jayne; Meehan, Declan; Longson, Damien; Potokar, John; Hulme, Tom; Marsden, Jennifer; Brand, Fiona; Lange, Kezia; Riseborough, Elena; Page, Lisa; Metcalfe, Chris; Davies, Linda; O'Connor, Rory; Hawton, Keith; Gunnell, David; Kapur, Nav

2017-01-01

Background Scales are widely used in psychiatric assessments following self-harm. Robust evidence for their diagnostic use is lacking. Aims To evaluate the performance of risk scales (Manchester Self-Harm Rule, ReACT Self-Harm Rule, SAD PERSONS scale, Modified SAD PERSONS scale, Barratt Impulsiveness Scale); and patient and clinician estimates of risk in identifying patients who repeat self-harm within 6 months. Method A multisite prospective cohort study was conducted of adults aged 18 years and over referred to liaison psychiatry services following self-harm. Scale a priori cut-offs were evaluated using diagnostic accuracy statistics. The area under the curve (AUC) was used to determine optimal cut-offs and compare global accuracy. Results In total, 483 episodes of self-harm were included in the study. The episode-based 6-month repetition rate was 30% (n = 145). Sensitivity ranged from 1% (95% CI 0–5) for the SAD PERSONS scale, to 97% (95% CI 93–99) for the Manchester Self-Harm Rule. Positive predictive values ranged from 13% (95% CI 2–47) for the Modified SAD PERSONS Scale to 47% (95% CI 41–53) for the clinician assessment of risk. The AUC ranged from 0.55 (95% CI 0.50–0.61) for the SAD PERSONS scale to 0.74 (95% CI 0.69–0.79) for the clinician global scale. The remaining scales performed significantly worse than clinician and patient estimates of risk (P<0.001). Conclusions Risk scales following self-harm have limited clinical utility and may waste valuable resources. Most scales performed no better than clinician or patient ratings of risk. Some performed considerably worse. Positive predictive values were modest. In line with national guidelines, risk scales should not be used to determine patient management or predict self-harm. PMID:28302702

Predictive accuracy of risk scales following self-harm: multicentre, prospective cohort study.

PubMed

Quinlivan, Leah; Cooper, Jayne; Meehan, Declan; Longson, Damien; Potokar, John; Hulme, Tom; Marsden, Jennifer; Brand, Fiona; Lange, Kezia; Riseborough, Elena; Page, Lisa; Metcalfe, Chris; Davies, Linda; O'Connor, Rory; Hawton, Keith; Gunnell, David; Kapur, Nav

2017-06-01

Background Scales are widely used in psychiatric assessments following self-harm. Robust evidence for their diagnostic use is lacking. Aims To evaluate the performance of risk scales (Manchester Self-Harm Rule, ReACT Self-Harm Rule, SAD PERSONS scale, Modified SAD PERSONS scale, Barratt Impulsiveness Scale); and patient and clinician estimates of risk in identifying patients who repeat self-harm within 6 months. Method A multisite prospective cohort study was conducted of adults aged 18 years and over referred to liaison psychiatry services following self-harm. Scale a priori cut-offs were evaluated using diagnostic accuracy statistics. The area under the curve (AUC) was used to determine optimal cut-offs and compare global accuracy. Results In total, 483 episodes of self-harm were included in the study. The episode-based 6-month repetition rate was 30% ( n = 145). Sensitivity ranged from 1% (95% CI 0-5) for the SAD PERSONS scale, to 97% (95% CI 93-99) for the Manchester Self-Harm Rule. Positive predictive values ranged from 13% (95% CI 2-47) for the Modified SAD PERSONS Scale to 47% (95% CI 41-53) for the clinician assessment of risk. The AUC ranged from 0.55 (95% CI 0.50-0.61) for the SAD PERSONS scale to 0.74 (95% CI 0.69-0.79) for the clinician global scale. The remaining scales performed significantly worse than clinician and patient estimates of risk ( P <0.001). Conclusions Risk scales following self-harm have limited clinical utility and may waste valuable resources. Most scales performed no better than clinician or patient ratings of risk. Some performed considerably worse. Positive predictive values were modest. In line with national guidelines, risk scales should not be used to determine patient management or predict self-harm. © The Royal College of Psychiatrists 2017.

ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes.

PubMed

Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

2015-07-01

In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Predicting Likelihood of Having Four or More Positive Nodes in Patient With Sentinel Lymph Node-Positive Breast Cancer: A Nomogram Validation Study

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

Unal, Bulent; Gur, Akif Serhat; Beriwal, Sushil

2009-11-15

Purpose: Katz suggested a nomogram for predicting having four or more positive nodes in sentinel lymph node (SLN)-positive breast cancer patients. The findings from this formula might influence adjuvant radiotherapy decisions. Our goal was to validate the accuracy of the Katz nomogram. Methods and Materials: We reviewed the records of 309 patients with breast cancer who had undergone completion axillary lymph node dissection. The factors associated with the likelihood of having four or more positive axillary nodes were evaluated in patients with one to three positive SLNs. The nomogram developed by Katz was applied to our data set. The areamore » under the curve of the corresponding receiver operating characteristics curve was calculated for the nomogram. Results: Of the 309 patients, 80 (25.9%) had four or more positive axillary lymph nodes. On multivariate analysis, the number of positive SLNs (p < .0001), overall metastasis size (p = .019), primary tumor size (p = .0001), and extracapsular extension (p = .01) were significant factors predicting for four or more positive nodes. For patients with <5% probability, 90.3% had fewer than four positive nodes and 9.7% had four or more positive nodes. The negative predictive value was 91.7%, and sensitivity was 80%. The nomogram was accurate and discriminating (area under the curve, .801). Conclusion: The probability of four or more involved nodes is significantly greater in patients who have an increased number of positive SLNs, increased overall metastasis size, increased tumor size, and extracapsular extension. The Katz nomogram was validated in our patients. This nomogram will be helpful to clinicians making adjuvant treatment recommendations to their patients.« less

Stimulus probability effects in absolute identification.

PubMed

Kent, Christopher; Lamberts, Koen

2016-05-01

This study investigated the effect of stimulus presentation probability on accuracy and response times in an absolute identification task. Three schedules of presentation were used to investigate the interaction between presentation probability and stimulus position within the set. Data from individual participants indicated strong effects of presentation probability on both proportion correct and response times. The effects were moderated by the ubiquitous stimulus position effect. The accuracy and response time data were predicted by an exemplar-based model of perceptual cognition (Kent & Lamberts, 2005). The bow in discriminability was also attenuated when presentation probability for middle items was relatively high, an effect that will constrain future model development. The study provides evidence for item-specific learning in absolute identification. Implications for other theories of absolute identification are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The correlation between malaria RDT (Paracheck pf.®) faint test bands and microscopy in the diagnosis of malaria in Malawi.

PubMed

Makuuchi, Ryoko; Jere, Sandy; Hasejima, Nobuchika; Chigeda, Thoms; Gausi, January

2017-05-02

Faint test bands of Paracheck Pf.® are interpreted as malaria positive according to world health organization (WHO) guideline. However if there are conspicuous number of faint test bands, a performance of Paracheck Pf.® could be influenced depending on whether interpreting faint test bands as malaria positive or negative. Finding out the frequency and accurate interpretation of faint test bands are important to prevent the overdiagnosis and drug resistance. A cross-sectional, descriptive study was conducted to find out the frequency of faint test bands and evaluate the performance of Paracheck Pf.® by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of diagnosis of Paracheck Pf.® using microscopy as the gold standard. 388 suspected patients with malaria in Malawi were recruited in this study. Malaria rapid diagnostic tests (RDTs) and microscopy were used and patients' information which includes age, sex, body temperature and signs or symptoms of malaria were recorded. Among all patients involved in the study, 29.1% (113/388) were found malaria positive by RDT. Overall 5.4% (21/388) of all Paracheck Pf.® tests resulted in a "faint test band" and 85.7% (18/21) corresponded with malaria negative by microscopy. Faint test bands which corresponded with malaria positive by microscopy were lower parasite density and there are no patients who showed definitive symptom of malaria, such as fever. When Paracheck Pf.® "faint test bands" were classified as positive, accuracy of diagnosis was 76.5% (95% CI 72%-80.7%) as compared to 80.4% (95% CI 76.1%-84.2%) when Paracheck Pf.® "faint test bands" were classified as negative. This study shows that frequency of faint test bands is 5.4% in all malaria RDTs. The accuracy of diagnosis was improved when faint test bands were interpreted as malaria negative. However information and data obtained in this study may not be enough and more intensive research including a frequency and property of faint test bands is needed for significant interpretation of faint test bands.

Occlusal factors are not related to self-reported bruxism.

PubMed

Manfredini, Daniele; Visscher, Corine M; Guarda-Nardini, Luca; Lobbezoo, Frank

2012-01-01

To estimate the contribution of various occlusal features of the natural dentition that may identify self-reported bruxers compared to nonbruxers. Two age- and sex-matched groups of self-reported bruxers (n = 67) and self-reported nonbruxers (n = 75) took part in the study. For each patient, the following occlusal features were clinically assessed: retruded contact position (RCP) to intercuspal contact position (ICP) slide length (< 2 mm was considered normal), vertical overlap (< 0 mm was considered an anterior open bite; > 4 mm, a deep bite), horizontal overlap (> 4 mm was considered a large horizontal overlap), incisor dental midline discrepancy (< 2 mm was considered normal), and the presence of a unilateral posterior crossbite, mediotrusive interferences, and laterotrusive interferences. A multiple logistic regression model was used to identify the significant associations between the assessed occlusal features (independent variables) and self-reported bruxism (dependent variable). Accuracy values to predict self-reported bruxism were unacceptable for all occlusal variables. The only variable remaining in the final regression model was laterotrusive interferences (P = .030). The percentage of explained variance for bruxism by the final multiple regression model was 4.6%. This model including only one occlusal factor showed low positive (58.1%) and negative predictive values (59.7%), thus showing a poor accuracy to predict the presence of self-reported bruxism (59.2%). This investigation suggested that the contribution of occlusion to the differentiation between bruxers and nonbruxers is negligible. This finding supports theories that advocate a much diminished role for peripheral anatomical-structural factors in the pathogenesis of bruxism.

Diagnostic Accuracy of the Berlin Questionnaire in Detecting Sleep-Disordered Breathing in Patients With a Recent Myocardial Infarction

PubMed Central

Sert Kuniyoshi, Fatima H.; Zellmer, Mark R.; Calvin, Andrew D.; Lopez-Jimenez, Francisco; Albuquerque, Felipe N.; van der Walt, Christelle; Trombetta, Ivani C; Caples, Sean M.; Shamsuzzaman, Abu S.; Bukartyk, Jan; Konecny, Tomas; Gami, Apoor S.; Kara, Tomas

2011-01-01

Background: The Berlin Questionnaire (BQ) has been used to identify patients at high risk for sleep-disordered breathing (SDB) in a variety of populations. However, there are no data regarding the validity of the BQ in detecting the presence of SDB in patients after myocardial infarction (MI). The aim of this study was to determine the performance of the BQ in patients after MI. Methods: We conducted a cross-sectional study of 99 patients who had an MI 1 to 3 months previously. The BQ was administered, scored using the published methods, and followed by completed overnight polysomnography as the “gold standard.” SDB was defined as an apnea-hypopnea index of ≥ 5 events/h. The sensitivity, specificity, and positive and negative predictive values of the BQ were calculated. Results: Of the 99 patients, the BQ identified 64 (65%) as being at high-risk for having SDB. Overnight polysomnography showed that 73 (73%) had SDB. The BQ sensitivity and specificity was 0.68 and 0.34, respectively, with a positive predictive value of 0.68 and a negative predictive value of 0.50. Positive and negative likelihood ratios were 1.27 and 0.68, respectively, and the BQ overall diagnostic accuracy was 63%. Using different apnea-hypopnea index cutoff values did not meaningfully alter these results. Conclusion: The BQ performed with modest sensitivity, but the specificity was poor, suggesting that the BQ is not ideal in identifying SDB in patients with a recent MI. PMID:21596794

Initial accuracy assessment of the modified S-LANSS for the detection of neuropathic orofacial pain conditions.

PubMed

Herrero Babiloni, Alberto; Nixdorf, Donald R; Law, Alan S; Moana-Filho, Estephan J; Shueb, Sarah S; Nguyen, Ruby H; Durham, Justin

2017-01-01

To evaluate the accuracy of a questionnaire modified for the identification of intraoral pain with neuropathic characteristics in a clinical orofacial pain sample population. 136 participants with at least one of four orofacial pain diagnoses (temporomandibular disorders [TMD, n = 41], acute dental pain [ADP, n = 41], trigeminal neuralgia [TN, n = 19], persistent dentoalveolar pain disorder [PDAP, n = 14]) and a group of pain-free controls (n = 21) completed the modified S-LANSS, a previously adapted version of the original questionnaire devised to detected patients suffering from intraoral pain with neuropathic characteristics. Psychometric properties (sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV]) were calculated in two analyses with two different thresholds: (1) Detection of pain with neuropathic characteristics: PDAP + TN were considered positive, and TMD + ADP + controls were considered negative per gold standard (expert opinion). (2) Detection of PDAP: PDAP was considered positive and TMD + ADP were considered negative per gold standard. For both analyses, target values for adequate sensitivity and specificity were defined as ≥ 80%. For detection of orofacial pain with neuropathic characteristics (PDAP + TN), the modified S-LANSS presented with the most optimistic threshold sensitivity of 52% (95% confidence interval [CI], 34-69), specificity of 70% (95% CI, 60-79), PPV of 35% (95% CI, 22-51), and NPV of 82% (95% CI, 72-89). For detection of PDAP only, with the most optimistic threshold sensitivity was 64% (95% CI, 35-87), specificity 63% (95% CI, 52-74), PPV 23% (95% CI, 11-39) and NPV 91% (95% CI, 81-97). Based on a priori defined criteria, the modified S-LANSS did not show adequate accuracy to detect intraoral pain with neuropathic characteristics in a clinical orofacial pain sample.

Diagnostic Accuracy and Effectiveness of Automated Electronic Sepsis Alert Systems: A Systematic Review

PubMed Central

Makam, Anil N.; Nguyen, Oanh K.; Auerbach, Andrew D.

2015-01-01

Background Although timely treatment of sepsis improves outcomes, delays in administering evidence-based therapies are common. Purpose To determine whether automated real-time electronic sepsis alerts can: 1) accurately identify sepsis, and 2) improve process measures and outcomes. Data Sources We systematically searched MEDLINE, Embase, The Cochrane Library, and CINAHL from database inception through June 27, 2014. Study Selection Included studies that empirically evaluated one or both of the prespecified objectives. Data Extraction Two independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive (PPV) and negative predictive values (NPV) and likelihood ratios (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes. Data Synthesis Of 1,293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n=35,423) and 5 for the effectiveness of sepsis alerts (n=6,894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5-53.8%, NPV 76.5-99.7%; LR+ 1.2-145.8; and LR- 0.06-0.86. There was modest evidence for improvement in process measures (i.e., antibiotic escalation), but only among patients in non-critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts. Conclusions Automated sepsis alerts derived from electronic health data may improve care processes but tend to have poor positive predictive value and do not improve mortality or length of stay. PMID:25758641

Evaluation of GeneXpert MTB/RIF for detection of pulmonary tuberculosis at peripheral tuberculosis clinics.

PubMed

Shao, Yan; Peng, Hong; Chen, Cheng; Zhu, Tao; Ji, Ming; Jiang, Wei; Zhu, Wei; Zhai, Xiang Jun; Lu, Wei

2017-04-01

Tuberculosis is one of the most common infectious diseases in China, while delayed patient finding obstructed disease control, especially for smear-negative patients. The current study was undertaken to evaluate the diagnostic accuracy of GeneXpert MTB/RIF compared with conventional methods in the detection of pulmonary tuberculosis patients. A total of 295 spot sputum samples from confirmed pulmonary tuberculosis patients were evaluated from September 2014 to June 2015. Each sample was examined by acid-fast bacillus smear microscopy, culture and GeneXpert MTB/RIF. The sputum culture on Löwenstein-Jensen (L-J) was considered as the gold-standard. After testing by smear, 68.81% (203/295) was negative and 31.19% (92/295) was positive. As the gold-standard, L-J culture detected 37.97% (112/295) positive of all specimens, while the positivity for GeneXpert MTB/RIF was 46.44% (137/295). Compared with L-J culture, the combined sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for GeneXpert MTB/RIF were 94.64%, 82.97%, 77.37% and 96.18% respectively. For smear-negative specimens, the sensitivity, specificity, PPV and NPV for GeneXpert MTB/RIF were 96.00%, 83.05%, 44.44% and 99.32%; while for smear-positive specimens, the corresponding accuracy values were 94.25%, 80.00%, 98.80% and 44.44%. The findings of study indicated that GeneXpert MTB/RIF assay demonstrated a high sensitivity in detecting Mycobacterium tuberculosis compared to smear method and a high NPV among smear negative patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Aerodynamic study of different cyclist positions: CFD analysis and full-scale wind-tunnel tests.

PubMed

Defraeye, Thijs; Blocken, Bert; Koninckx, Erwin; Hespel, Peter; Carmeliet, Jan

2010-05-07

Three different cyclist positions were evaluated with Computational Fluid Dynamics (CFD) and wind-tunnel experiments were used to provide reliable data to evaluate the accuracy of the CFD simulations. Specific features of this study are: (1) both steady Reynolds-averaged Navier-Stokes (RANS) and unsteady flow modelling, with more advanced turbulence modelling techniques (Large-Eddy Simulation - LES), were evaluated; (2) the boundary layer on the cyclist's surface was resolved entirely with low-Reynolds number modelling, instead of modelling it with wall functions; (3) apart from drag measurements, also surface pressure measurements on the cyclist's body were performed in the wind-tunnel experiment, which provided the basis for a more detailed evaluation of the predicted flow field by CFD. The results show that the simulated and measured drag areas differed about 11% (RANS) and 7% (LES), which is considered to be a close agreement in CFD studies. A fair agreement with wind-tunnel data was obtained for the predicted surface pressures, especially with LES. Despite the higher accuracy of LES, its much higher computational cost could make RANS more attractive for practical use in some situations. CFD is found to be a valuable tool to evaluate the drag of different cyclist positions and to investigate the influence of small adjustments in the cyclist's position. A strong advantage of CFD is that detailed flow field information is obtained, which cannot easily be obtained from wind-tunnel tests. This detailed information allows more insight in the causes of the drag force and provides better guidance for position improvements. Copyright 2010 Elsevier Ltd. All rights reserved.

Reduced fMRI activity predicts relapse in patients recovering from stimulant dependence.

PubMed

Clark, Vincent P; Beatty, Gregory K; Anderson, Robert E; Kodituwakku, Piyadassa; Phillips, John P; Lane, Terran D R; Kiehl, Kent A; Calhoun, Vince D

2014-02-01

Relapse presents a significant problem for patients recovering from stimulant dependence. Here we examined the hypothesis that patterns of brain function obtained at an early stage of abstinence differentiates patients who later relapse versus those who remain abstinent. Forty-five recently abstinent stimulant-dependent patients were tested using a randomized event-related functional MRI (ER-fMRI) design that was developed in order to replicate a previous ERP study of relapse using a selective attention task, and were then monitored until 6 months of verified abstinence or stimulant use occurred. SPM revealed smaller absolute blood oxygen level-dependent (BOLD) response amplitude in bilateral ventral posterior cingulate and right insular cortex in 23 patients positive for relapse to stimulant use compared with 22 who remained abstinent. ER-fMRI, psychiatric, neuropsychological, demographic, personal and family history of drug use were compared in order to form predictive models. ER-fMRI was found to predict abstinence with higher accuracy than any other single measure obtained in this study. Logistic regression using fMRI amplitude in right posterior cingulate and insular cortex predicted abstinence with 77.8% accuracy, which increased to 89.9% accuracy when history of mania was included. Using 10-fold cross-validation, Bayesian logistic regression and multilayer perceptron algorithms provided the highest accuracy of 84.4%. These results, combined with previous studies, suggest that the functional organization of paralimbic brain regions including ventral anterior and posterior cingulate and right insula are related to patients' ability to maintain abstinence. Novel therapies designed to target these paralimbic regions identified using ER-fMRI may improve treatment outcome. Copyright © 2012 Wiley Periodicals, Inc.

The accuracy of the SONOBREAST statistical model in comparison to BI-RADS for the prediction of malignancy in solid breast nodules detected at ultrasonography.

PubMed

Paulinelli, Regis R; Oliveira, Luis-Fernando P; Freitas-Junior, Ruffo; Soares, Leonardo R

2016-01-01

The objective of the present study was to compare the accuracy of SONOBREAST for the prediction of malignancy in solid breast nodules detected at ultrasonography with that of the BI-RADS system and to assess the agreement between these two methods. This prospective study included 274 women and evaluated 500 breast nodules detected at ultrasonography. The probability of malignancy was calculated based on the SONOBREAST model, available at www.sonobreast.com.br, and on the BI-RADS system, with results being compared with the anatomopathology report. The lesions were considered suspect in 171 cases (34.20%), according to both SONOBREAST and BI-RADS. Agreement between the methods was perfect, as shown by a Kappa coefficient of 1 (p<0.001). SONOBREAST and BI-RADS proved identical insofar as sensitivity (95.40%), specificity (78.69%), positive predictive value (48.54%), negative predictive value (98.78%) and accuracy (81.60%) are concerned. With respect to the categorical variables (BI-RADS categories 3, 4 and 5), the area under the receiver operating characteristic (ROC) curve was 94.41 for SONOBREAST (range 92.20-96.62) and 89.99 for BI-RADS (range 86.60-93.37). The accuracy of the SONOBREAST model is identical to that found with BI-RADS when the same parameters are used with respect to the cut-off point at which malignancy is suspected. Regarding the continuous probability of malignancy with BI-RADS categories 3, 4 and 5, SONOBREAST permits a more precise and individualized evaluation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Combined panel of serum human tissue kallikreins and CA-125 for the detection of epithelial ovarian cancer.

PubMed

Koh, Stephen Chee Liang; Huak, Chan Yiong; Lutan, Delfi; Marpuang, Johny; Ketut, Suwiyoga; Budiana, Nyoma Gede; Saleh, Agustria Zainu; Aziz, Mohamad Farid; Winarto, Hariyono; Pradjatmo, Heru; Hoan, Nguyen Khac Han; Thanh, Pham Viet; Choolani, Mahesh

2012-07-01

To determine the predictive accuracy of the combined panels of serum human tissue kallikreins (hKs) and CA-125 for the detection of epithelial ovarian cancer. Serum specimens collected from 5 Indonesian centers and 1 Vietnamese center were analyzed for CA-125, hK6, and hK10 levels. A total of 375 specimens from patients presenting with ovarian tumors, which include 156 benign cysts, 172 epithelial ovarian cancers (stage I/II, n=72; stage III/IV, n=100), 36 germ cell tumors and 11 borderline tumors, were included in the study analysis. Receiver operating characteristic analysis were performed to determine the cutoffs for age, CA-125, hK6, and hK10. Sensitivity, specificity, negative, and positive predictive values were determined for various combinations of the biomarkers. The levels of hK6 and hK10 were significantly elevated in ovarian cancer cases compared to benign cysts. Combination of 3 markers, age/CA-125/hk6 or CA-125/hk6/hk10, showed improved specificity (100%) and positive predictive value (100%) for prediction of ovarian cancer, when compared to the performance of single markers having 80-92% specificity and 74-87% positive predictive value. Four-marker combination, age/CA-125/hK6/hK10 also showed 100% specificity and 100% positive predictive value, although it demonstrated low sensitivity (11.9%) and negative predictive value (52.8%). The combination of human tissue kallikreins and CA-125 showed potential for improving prediction of epithelial ovarian cancer in patients presenting with ovarian tumors.

Usefulness of conventional transbronchial needle aspiration in the diagnosis, staging and molecular characterization of pulmonary neoplasias by thin-prep based cytology: experience of a single oncological institute.

PubMed

Ramieri, Maria Teresa; Marandino, Ferdinando; Visca, Paolo; Salvitti, Tommaso; Gallo, Enzo; Casini, Beatrice; Giordano, Francesca Romana; Frigieri, Claudia; Caterino, Mauro; Carlini, Sandro; Rinaldi, Massimo; Ceribelli, Anna; Pennetti, Annarita; Alò, Pier Luigi; Marino, Mirella; Pescarmona, Edoardo; Filippetti, Massimo

2016-08-01

Conventional transbronchial needle aspiration (c-TBNA) contributed to improve the bronchoscopic examination, allowing to sample lesions located even outside the tracheo-bronchial tree and in the hilo-mediastinal district, both for diagnostic and staging purposes. We have evaluated the sensitivity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of the c-TBNA performed during the 2005-2015 period for suspicious lung neoplasia and/or hilar and mediastinal lymphadenopathy at the Thoracic endoscopy of the Thoracic Surgery Department of the Regina Elena National Cancer Institute, Rome. Data from 273 consecutive patients (205 males and 68 females) were analyzed. Among 158 (58%) adequate specimens, 112 (41%) were neoplastic or contained atypical cells, 46 (17%) were negative or not diagnostic. We considered in the analysis first the overall period; then we compared the findings of the first [2005-2011] and second period [2012-2015] and, finally, only those of adequate specimens. During the overall period, sensibility and accuracy values were respectively of 53% and 63%, in the first period they reached 41% and 53% respectively; in the second period sensibility and accuracy reached 60% and 68%. Considering only the adequate specimens, sensibility and accuracy during the overall period were respectively of 80% and 82%; the values obtained for the first period were 68% and 72%. Finally, in the second period, sensibility reached 86% and accuracy 89%. Carcinoma-subtyping was possible in 112 cases, adenocarcinomas being diagnosed in 50 cases; further, in 30 cases molecular predictive data could be obtained. The c-TBNA proved to be an efficient method for the diagnosis/staging of lung neoplasms and for the diagnosis of mediastinal lymphadenopathy. Endoscopist's skill and technical development, associated to thin-prep cytology and to a rapid on site examination (ROSE), were able to provide by c-TBNA a high diagnostic yield and molecular predictive data in advanced lung carcinomas.

Ensemble-based prediction of RNA secondary structures.

PubMed

Aghaeepour, Nima; Hoos, Holger H

2013-04-24

Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between false negative and false positive base pair predictions. Finally, AveRNA can make use of arbitrary sets of secondary structure prediction procedures and can therefore be used to leverage improvements in prediction accuracy offered by algorithms and energy models developed in the future. Our data, MATLAB software and a web-based version of AveRNA are publicly available at http://www.cs.ubc.ca/labs/beta/Software/AveRNA.

How a GNSS Receiver Is Held May Affect Static Horizontal Position Accuracy

PubMed Central

Weaver, Steven A.; Ucar, Zennure; Bettinger, Pete; Merry, Krista

2015-01-01

The static horizontal position accuracy of a mapping-grade GNSS receiver was tested in two forest types over two seasons, and subsequently was tested in one forest type against open sky conditions in the winter season. The main objective was to determine whether the holding position during data collection would result in significantly different static horizontal position accuracy. Additionally, we wanted to determine whether the time of year (season), forest type, or environmental variables had an influence on accuracy. In general, the F4Devices Flint GNSS receiver was found to have mean static horizontal position accuracy levels within the ranges typically expected for this general type of receiver (3 to 5 m) when differential correction was not employed. When used under forest cover, in some cases the GNSS receiver provided a higher level of static horizontal position accuracy when held vertically, as opposed to held at an angle or horizontally (the more natural positions), perhaps due to the orientation of the antenna within the receiver, or in part due to multipath or the inability to use certain satellite signals. Therefore, due to the fact that numerous variables may affect static horizontal position accuracy, we only conclude that there is weak to moderate evidence that the results of holding position are significant. Statistical test results also suggest that the season of data collection had no significant effect on static horizontal position accuracy, and results suggest that atmospheric variables had weak correlation with horizontal position accuracy. Forest type was found to have a significant effect on static horizontal position accuracy in one aspect of one test, yet otherwise there was little evidence that forest type affected horizontal position accuracy. Since the holding position was found in some cases to be significant with regard to the static horizontal position accuracy of positions collected in forests, it may be beneficial to have an understanding of antenna positioning within the receiver to achieve the greatest accuracy during data collection. PMID:25923667

How a GNSS Receiver Is Held May Affect Static Horizontal Position Accuracy.

PubMed

Weaver, Steven A; Ucar, Zennure; Bettinger, Pete; Merry, Krista

2015-01-01

The static horizontal position accuracy of a mapping-grade GNSS receiver was tested in two forest types over two seasons, and subsequently was tested in one forest type against open sky conditions in the winter season. The main objective was to determine whether the holding position during data collection would result in significantly different static horizontal position accuracy. Additionally, we wanted to determine whether the time of year (season), forest type, or environmental variables had an influence on accuracy. In general, the F4Devices Flint GNSS receiver was found to have mean static horizontal position accuracy levels within the ranges typically expected for this general type of receiver (3 to 5 m) when differential correction was not employed. When used under forest cover, in some cases the GNSS receiver provided a higher level of static horizontal position accuracy when held vertically, as opposed to held at an angle or horizontally (the more natural positions), perhaps due to the orientation of the antenna within the receiver, or in part due to multipath or the inability to use certain satellite signals. Therefore, due to the fact that numerous variables may affect static horizontal position accuracy, we only conclude that there is weak to moderate evidence that the results of holding position are significant. Statistical test results also suggest that the season of data collection had no significant effect on static horizontal position accuracy, and results suggest that atmospheric variables had weak correlation with horizontal position accuracy. Forest type was found to have a significant effect on static horizontal position accuracy in one aspect of one test, yet otherwise there was little evidence that forest type affected horizontal position accuracy. Since the holding position was found in some cases to be significant with regard to the static horizontal position accuracy of positions collected in forests, it may be beneficial to have an understanding of antenna positioning within the receiver to achieve the greatest accuracy during data collection.

Development of Quality Assessment Techniques for Large Eddy Simulation of Propulsion and Power Systems in Complex Geometries

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

Lacaze, Guilhem; Oefelein, Joseph

Large-eddy-simulation (LES) is quickly becoming a method of choice for studying complex thermo-physics in a wide range of propulsion and power systems. It provides a means to study coupled turbulent combustion and flow processes in parameter spaces that are unattainable using direct-numerical-simulation (DNS), with a degree of fidelity that can be far more accurate than conventional engineering methods such as the Reynolds-averaged Navier-Stokes (RANS) approx- imation. However, development of predictive LES is complicated by the complex interdependence of different type of errors coming from numerical methods, algorithms, models and boundary con- ditions. On the other hand, control of accuracy hasmore » become a critical aspect in the development of predictive LES for design. The objective of this project is to create a framework of metrics aimed at quantifying the quality and accuracy of state-of-the-art LES in a manner that addresses the myriad of competing interdependencies. In a typical simulation cycle, only 20% of the computational time is actually usable. The rest is spent in case preparation, assessment, and validation, because of the lack of guidelines. This work increases confidence in the accuracy of a given solution while min- imizing the time obtaining the solution. The approach facilitates control of the tradeoffs between cost, accuracy, and uncertainties as a function of fidelity and methods employed. The analysis is coupled with advanced Uncertainty Quantification techniques employed to estimate confidence in model predictions and calibrate model's parameters. This work has provided positive conse- quences on the accuracy of the results delivered by LES and will soon have a broad impact on research supported both by the DOE and elsewhere.« less

Walking on thin ice! Identifying methamphetamine "drug mules" on digital plain radiography.

PubMed

Abdul Rashid, S N; Mohamad Saini, S B; Abdul Hamid, S; Muhammad, S J; Mahmud, R; Thali, M J; Flach, P M

2014-04-01

The purpose of this study was to retrospectively evaluate the sensitivity, specificity and accuracy of identifying methamphetamine (MA) internal payloads in "drug mules" by plain abdominal digital radiography (DR). The study consisted of 35 individuals suspected of internal MA drug containers. A total of 59 supine digital radiographs were collected. An overall calculation regarding the diagnostic accuracy for all "drug mules" and a specific evaluation concerning the radiological appearance of drug packs as well as the rate of clearance and complications in correlation with the reader's experience were performed. The gold standard was the presence of secured drug packs in the faeces. There were 16 true-positive "drug mules" identified. DR of all drug carriers for Group 1 (forensic imaging experienced readers, n = 2) exhibited a sensitivity of 100%, a mean specificity of 76.3%, positive predictive value (PPV) of 78.5%, negative predictive value (NPV) of 100% and a mean accuracy 87.2%. Group 2 (inexperienced readers, n = 3) showed a lower sensitivity (93.7%), a mean specificity of 86%, a PPV of 86.5%, an NPV of 94.1% and a mean accuracy of 89.5%. The interrater agreement within Group 1 was 0.72 and within Group 2 averaged to 0.79, indicating a fair to very good agreement. DR is a valuable screening tool in cases of MA body packers with huge internal payloads being associated with a high diagnostic insecurity. Diagnostic insecurity on plain films may be overcome by low-dose CT as a cross-sectional imaging modality and addressed by improved radiological education in reporting drug carriers on imaging. Diagnostic signs (double-condom and halo signs) on digital plain radiography are specific in MA "drug mules", although DR is associated with high diagnostic insecurity and underreports the total internal payload.

Learning curve of office-based ultrasonography for rotator cuff tendons tears.

PubMed

Ok, Ji-Hoon; Kim, Yang-Soo; Kim, Jung-Man; Yoo, Tae-Wook

2013-07-01

To compare the accuracy of ultrasonography and MR arthrography (MRA) imaging in detecting of rotator cuff tears with arthroscopic finding used as the reference standard. The ultrasonography and MRA findings of 51 shoulders that underwent the arthroscopic surgery were prospectively analysed. Two orthopaedic doctors independently performed ultrasonography and interpreted the findings at the office. The tear size measured at ultrasonography and MRA was compared with the size measured at surgery using Pearson correlation coefficients (r). The sensitivity, specificity, accuracy, positive predictive value, negative predictive value and false-positive rate were calculated for a diagnosis of partial-and full-thickness rotator cuff tears. The kappa coefficient was calculated to verify the inter-observer agreement. The sensitivity of ultrasonography and MRA for detecting partial-thickness tears was 45.5 and 72.7 %, and that for full-thickness tears was 80.0 and 100 %, respectively. The accuracy of ultrasonograpy and MRA for detecting partial-thickness tears was 45.1 and 88.2 %, and that for full-thickness tears was 82.4 and 98 %, respectively. Tear size measured based on ultrasonography examination showed a poor correlation with the size measured at arthroscopic surgery (r = 0.21; p < 0.05). However, tear size estimated by MRA showed a strong correlation (r = 0.75; p < 0.05). The kappa coefficient was 0.47 between the two independent examiners. The accuracy of office-based ultrasonography for beginner orthopaedic surgeons to detect full-thickness rotator cuff tears was comparable to that of MRA but was less accurate for detecting partial-thickness tears and torn size measurement. Inter-observer agreement on the interpretation was fair. These results highlight the importance of the correct technique and experience in operation of ultrasonography in shoulder joint. Diagnostic study, Level II.

Diagnostic accuracy assessment of cytopathological examination of feline sporotrichosis.

PubMed

Jessica, N; Sonia, R L; Rodrigo, C; Isabella, D F; Tânia, M P; Jeferson, C; Anna, B F; Sandro, A

2015-11-01

Sporotrichosis is an implantation mycosis caused by pathogenic species of Sporothrix schenckii complex that affects humans and animals, especially cats. Its main forms of zoonotic transmission include scratching, biting and/or contact with the exudate from lesions of sick cats. In Brazil, epidemic involving humans, dogs and cats has occurred since 1998. The definitive diagnosis of sporotrichosis is obtained by the isolation of the fungus in culture; however, the result can take up to four weeks, which may delay the beginning of antifungal treatment in some cases. Cytopathological examination is often used in feline sporotrichosis diagnosis, but accuracy parameters have not been established yet. The aim of this study was to evaluate the accuracy and reliability of cytopathological examination in the diagnosis of feline sporotrichosis. The present study included 244 cats from the metropolitan region of Rio de Janeiro, mostly males in reproductive age with three or more lesions in non-adjacent anatomical places. To evaluate the inter-observer reliability, two different observers performed the microscopic examination of the slides blindly. Test sensitivity was 84.9%. The values of positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio and accuracy were 86.0, 24.4, 2.02, 0.26 and 82.8%, respectively. The reliability between the two observers was considered substantial. We conclude that the cytopathological examination is a sensitive, rapid and practical method to be used in feline sporotrichosis diagnosis in outbreaks of this mycosis. © The Author 2015. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

PrAS: Prediction of amidation sites using multiple feature extraction.

PubMed

Wang, Tong; Zheng, Wei; Wuyun, Qiqige; Wu, Zhenfeng; Ruan, Jishou; Hu, Gang; Gao, Jianzhao

2017-02-01

Amidation plays an important role in a variety of pathological processes and serious diseases like neural dysfunction and hypertension. However, identification of protein amidation sites through traditional experimental methods is time consuming and expensive. In this paper, we proposed a novel predictor for Prediction of Amidation Sites (PrAS), which is the first software package for academic users. The method incorporated four representative feature types, which are position-based features, physicochemical and biochemical properties features, predicted structure-based features and evolutionary information features. A novel feature selection method, positive contribution feature selection was proposed to optimize features. PrAS achieved AUC of 0.96, accuracy of 92.1%, sensitivity of 81.2%, specificity of 94.9% and MCC of 0.76 on the independent test set. PrAS is freely available at https://sourceforge.net/p/praspkg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of spatial distribution of land cover maps accuracy

NASA Astrophysics Data System (ADS)

Khatami, R.; Mountrakis, G.; Stehman, S. V.

2017-12-01

Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain yielded similar AUC; iv) for the larger sample size (i.e., very dense spatial sample) and per-class predictions, the spatial domain yielded larger AUC; v) increasing the sample size improved accuracy predictions with a greater benefit accruing to the spatial domain; and vi) the function used for interpolation had the smallest effect on AUC.

Modeling to predict pilot performance during CDTI-based in-trail following experiments

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Goka, T.

1984-01-01

A mathematical model was developed of the flight system with the pilot using a cockpit display of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. Both in-trail and vertical dynamics were included. The nominal spacing was based on one of three criteria (Constant Time Predictor; Constant Time Delay; or Acceleration Cue). This model was used to simulate digitally the dynamics of a string of multiple following aircraft, including response to initial position errors. The simulation was used to predict the outcome of a series of in-trail following experiments, including pilot performance in maintaining correct longitudinal spacing and vertical position. The experiments were run in the NASA Ames Research Center multi-cab cockpit simulator facility. The experimental results were then used to evaluate the model and its prediction accuracy. Model parameters were adjusted, so that modeled performance matched experimental results. Lessons learned in this modeling and prediction study are summarized.

Predicting protein-binding regions in RNA using nucleotide profiles and compositions.

PubMed

Choi, Daesik; Park, Byungkyu; Chae, Hanju; Lee, Wook; Han, Kyungsook

2017-03-14

Motivated by the increased amount of data on protein-RNA interactions and the availability of complete genome sequences of several organisms, many computational methods have been proposed to predict binding sites in protein-RNA interactions. However, most computational methods are limited to finding RNA-binding sites in proteins instead of protein-binding sites in RNAs. Predicting protein-binding sites in RNA is more challenging than predicting RNA-binding sites in proteins. Recent computational methods for finding protein-binding sites in RNAs have several drawbacks for practical use. We developed a new support vector machine (SVM) model for predicting protein-binding regions in mRNA sequences. The model uses sequence profiles constructed from log-odds scores of mono- and di-nucleotides and nucleotide compositions. The model was evaluated by standard 10-fold cross validation, leave-one-protein-out (LOPO) cross validation and independent testing. Since actual mRNA sequences have more non-binding regions than protein-binding regions, we tested the model on several datasets with different ratios of protein-binding regions to non-binding regions. The best performance of the model was obtained in a balanced dataset of positive and negative instances. 10-fold cross validation with a balanced dataset achieved a sensitivity of 91.6%, a specificity of 92.4%, an accuracy of 92.0%, a positive predictive value (PPV) of 91.7%, a negative predictive value (NPV) of 92.3% and a Matthews correlation coefficient (MCC) of 0.840. LOPO cross validation showed a lower performance than the 10-fold cross validation, but the performance remains high (87.6% accuracy and 0.752 MCC). In testing the model on independent datasets, it achieved an accuracy of 82.2% and an MCC of 0.656. Testing of our model and other state-of-the-art methods on a same dataset showed that our model is better than the others. Sequence profiles of log-odds scores of mono- and di-nucleotides were much more powerful features than nucleotide compositions in finding protein-binding regions in RNA sequences. But, a slight performance gain was obtained when using the sequence profiles along with nucleotide compositions. These are preliminary results of ongoing research, but demonstrate the potential of our approach as a powerful predictor of protein-binding regions in RNA. The program and supporting data are available at http://bclab.inha.ac.kr/RBPbinding .

Estimating the diagnostic accuracy of rheumatoid factor in UK primary care: a study using the Clinical Practice Research Datalink.

PubMed

Miller, Anne; Nightingale, Alison L; Sammon, Cormac J; Mahtani, Kamal R; Holt, Tim A; McHugh, Neil J; Luqmani, Raashid A

2015-10-01

To investigate the diagnostic accuracy of RF as a test for RA in primary care and its impact on referral times using the Clinical Practice Research Datalink. We identified all patients with a first RF test recorded in the Clinical Practice Research Datalink between 1 January 2000 and 31 December 2008 and those diagnosed with RA within 2 years of testing. We calculated likelihood ratios (LRs), sensitivity, specificity and predictive values of RF for a diagnosis of RA. We compared time to hospital referral in those testing positive and negative using Kaplan-Meier failure curves and log-rank tests. Of 62 436 first RF tests, 4679 (7.5%) were positive. There were 1753 incident cases of RA, of which 57.8% were seropositive. The positive LR for RF was 9.5 (95% CI 9.0, 10.0) and the negative LR was 0.5 (95% CI 0.4, 0.5). Sensitivity and specificity were 57.8% (95% CI 55.4%, 60.1%) and 93.9% (95% CI 93.7%, 94.1%) and the positive predictive value and negative predictive value were 21.4% (95% CI 20.3%, 22.6%) and 98.7% (95% CI 98.6%, 98.8%), respectively. Median time to first hospital contact after the first RF test in those with seropositive vs seronegative results was 54 days (95% CI 49, 58) vs 150 (95% CI 147, 152). Only 2.8% of patients undergoing RF testing were diagnosed with RA, suggesting that RF is used to screen patients with musculoskeletal symptoms rather than those with more specific features of RA. A positive RF test may be helpful in diagnosing RA in primary care but performs badly in excluding RA and may delay referral. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Accuracy of routine magnetic resonance imaging in meniscal and ligamentous injuries of the knee: comparison with arthroscopy

PubMed Central

Behairy, Noha H.; Dorgham, Mohsen A.

2008-01-01

The aim of this study was to detect the accuracy of routine magnetic resonance imaging (MRI) done in different centres and its agreement with arthroscopy in meniscal and ligamentous injuries of the knee. We prospectively examined 70 patients ranging in age between 22 and 59 years. History taking, plain X-ray, clinical examination, routine MRI and arthroscopy were done for all patients. Sensitivity, specificity, accuracy, positive and negative predictive values, P value and kappa agreement measures were calculated. We found a sensitivity of 47 and 100%, specificity of 95 and 75% and accuracy of 73 and 78.5%, respectively, for the medial and lateral meniscus. A sensitivity of 77.8%, specificity of 100% and accuracy of 94% was noted for the anterior cruciate ligament (ACL). We found good kappa agreements (0.43 and 0.45) for both menisci and excellent agreement (0.84) for the ACL. MRI shows high accuracy and should be used as the primary diagnostic tool for selection of candidates for arthroscopy. Level of evidence: 4. PMID:18506445

Accuracy of maximum likelihood and least-squares estimates in the lidar slope method with noisy data.

PubMed

Eberhard, Wynn L

2017-04-01

The maximum likelihood estimator (MLE) is derived for retrieving the extinction coefficient and zero-range intercept in the lidar slope method in the presence of random and independent Gaussian noise. Least-squares fitting, weighted by the inverse of the noise variance, is equivalent to the MLE. Monte Carlo simulations demonstrate that two traditional least-squares fitting schemes, which use different weights, are less accurate. Alternative fitting schemes that have some positive attributes are introduced and evaluated. The principal factors governing accuracy of all these schemes are elucidated. Applying these schemes to data with Poisson rather than Gaussian noise alters accuracy little, even when the signal-to-noise ratio is low. Methods to estimate optimum weighting factors in actual data are presented. Even when the weighting estimates are coarse, retrieval accuracy declines only modestly. Mathematical tools are described for predicting retrieval accuracy. Least-squares fitting with inverse variance weighting has optimum accuracy for retrieval of parameters from single-wavelength lidar measurements when noise, errors, and uncertainties are Gaussian distributed, or close to optimum when only approximately Gaussian.

Seismic activity prediction using computational intelligence techniques in northern Pakistan

NASA Astrophysics Data System (ADS)

Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

2017-10-01

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

Prediction of neonatal respiratory morbidity by quantitative ultrasound lung texture analysis: a multicenter study.

PubMed

Palacio, Montse; Bonet-Carne, Elisenda; Cobo, Teresa; Perez-Moreno, Alvaro; Sabrià, Joan; Richter, Jute; Kacerovsky, Marian; Jacobsson, Bo; García-Posada, Raúl A; Bugatto, Fernando; Santisteve, Ramon; Vives, Àngels; Parra-Cordero, Mauro; Hernandez-Andrade, Edgar; Bartha, José Luis; Carretero-Lucena, Pilar; Tan, Kai Lit; Cruz-Martínez, Rogelio; Burke, Minke; Vavilala, Suseela; Iruretagoyena, Igor; Delgado, Juan Luis; Schenone, Mauro; Vilanova, Josep; Botet, Francesc; Yeo, George S H; Hyett, Jon; Deprest, Jan; Romero, Roberto; Gratacos, Eduard

2017-08-01

Prediction of neonatal respiratory morbidity may be useful to plan delivery in complicated pregnancies. The limited predictive performance of the current diagnostic tests together with the risks of an invasive procedure restricts the use of fetal lung maturity assessment. The objective of the study was to evaluate the performance of quantitative ultrasound texture analysis of the fetal lung (quantusFLM) to predict neonatal respiratory morbidity in preterm and early-term (<39.0 weeks) deliveries. This was a prospective multicenter study conducted in 20 centers worldwide. Fetal lung ultrasound images were obtained at 25.0-38.6 weeks of gestation within 48 hours of delivery, stored in Digital Imaging and Communication in Medicine format, and analyzed with quantusFLM. Physicians were blinded to the analysis. At delivery, perinatal outcomes and the occurrence of neonatal respiratory morbidity, defined as either respiratory distress syndrome or transient tachypnea of the newborn, were registered. The performance of the ultrasound texture analysis test to predict neonatal respiratory morbidity was evaluated. A total of 883 images were collected, but 17.3% were discarded because of poor image quality or exclusion criteria, leaving 730 observations for the final analysis. The prevalence of neonatal respiratory morbidity was 13.8% (101 of 730). The quantusFLM predicted neonatal respiratory morbidity with a sensitivity, specificity, positive and negative predictive values of 74.3% (75 of 101), 88.6% (557 of 629), 51.0% (75 of 147), and 95.5% (557 of 583), respectively. Accuracy was 86.5% (632 of 730) and positive and negative likelihood ratios were 6.5 and 0.3, respectively. The quantusFLM predicted neonatal respiratory morbidity with an accuracy similar to that previously reported for other tests with the advantage of being a noninvasive technique. Copyright © 2017. Published by Elsevier Inc.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

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

Alves, Vinicius M.; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599; Muratov, Eugene

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putativemore » sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative chemical hazards in the Scorecard database were found using our models.« less

A pilot study evaluating 99mTc-anti-TNF-alpha scintigraphy in graves' ophtalmopathy patients with different clinical activity score.

PubMed

Rebelo Pinto, E dos S; Lopes, F P P L; de Souza, S A L; da Fonseca, L M B; Vaisman, M; Gutfilen, B; dos Santos Teixeira, P de F

2013-09-01

The present study describes the preliminary results of the use of 99mTc-anti-TNF-α scintigraphy as a new diagnostic approach to evaluate patients presenting with Graves' ophthalmopathy (GO). Patients (n=25) presenting at different inflammatory stages of GO and 10 healthy volunteers underwent 99mTc-anti-TNF-α scintigraphy. Images were obtained 15 min after the intravenous injection of 370 MBq (10 mCi) 99mTc-anti-TNF-α. Planar images were obtained in a 256×256 matrix (each lasting 5 min) and single photon emission computed tomography (SPECT) scan lasting 13 min. Regions of interest (ROI) were drawn on the orbit and cerebral hemispheres. The uptake of 99m Tc-anti-TNF-α in these regions was compared and positive scintigraphy established when the ROI was >2.5. In addition, uptake for each positive exam was scored as either slight (2.6-5.1), moderate (5.2-7.6), or high (>7.6). In this pilot study, 69 orbits were evaluated (1 patient had only 1 eye), and 27 had a positive CAS (≥3/7). Scintigraphies were positive in 38 orbits. Comparing the results of the exams with CAS, a high sensitivity and negative predictive values were determined for scintigraphy (96.3% and 96.7%, respectively). However, the specificity and the positive predictive values were 71.4% and 68.4%, respectively, with an accuracy of 81.2%. The exclusion of examinations that were slightly positive from the analysis resulted in an improvement in test accuracy (95.5%). The preliminary results suggest that 99mTc-anti-TNF-α scintigraphy is a promising procedure for the evaluation of active orbital inflammation in GO. © Georg Thieme Verlag KG Stuttgart · New York.

Accuracy and Reproducibility Using Patient-Specific Instrumentation in Total Ankle Arthroplasty.

PubMed

Daigre, Justin; Berlet, Gregory; Van Dyke, Bryan; Peterson, Kyle S; Santrock, Robert

2017-04-01

Implant survivorship is dependent on accuracy of implantation and successful soft tissue balancing. System instrumentation for total ankle arthroplasty implantation has a key influence on surgeon accuracy and reproducibility. The purpose of this study was to determine the accuracy and reproducibility of implant position with patient-specific guides for total ankle arthroplasty across multiple surgeons at multiple facilities. This retrospective, multicenter study included 44 patients who received a total ankle implant (INBONE II Total Ankle System; Wright Medical Technology, Memphis, TN) using PROPHECY patient-specific guides from January 2012 to December 2014. Forty-four patients with an average age of 63.0 years underwent total ankle arthroplasty using this preoperative patient-specific system. Preoperative computed tomography (CT) scans were obtained to assess coronal plane deformity, assess mechanical and anatomic alignment, and build patient-specific guides that referenced bony anatomy. The mean preoperative coronal deformity was 4.6 ± 4.6 degrees (range, 14 degrees varus to 17 degrees valgus). The first postoperative weightbearing radiographs were used to measure coronal and sagittal alignment of the implant vs the anatomic axis of the tibia. In 79.5% of patients, the postoperative implant position of the tibia corresponded to the preoperative plan of the tibia within 3 degrees of the intended target, within 4 degrees in 88.6% of patients, and within 5 degrees in 100% of patients. The tibial component coronal size was correctly predicted in 98% of cases, whereas the talar component was correctly predicted in 80% of cases. The use of patient-specific instrumentation for total ankle arthroplasty provided reliable alignment and reproducibility in the clinical situation similar to that shown in cadaveric testing. This study has shown that the preoperative patient-specific instrumentation provided for accuracy and reproducibility of ankle arthroplasty implantation in a cohort across multiple surgeons and facilities. Level III, retrospective comparative series.

Diagnostic accuracy of 64-slice multidetector CT angiography for detection of in-stent restenosis of vertebral artery ostium stents: comparison with conventional angiography.

PubMed

Lee, Youn Joo; Lim, Yeon Soo; Lim, Hyun Wook; Yoo, Won Jong; Choi, Byung Gil; Kim, Bum Soo

2014-10-01

There are very few reports assessing in-stent restenosis (ISR) after vertebral artery ostium (VAO) stents using multidetector computed tomography (MDCT). To compare the diagnostic accuracy of computed tomography angiography (CTA) using 64-slice MDCT with digital subtraction angiography (DSA) for detection of significant ISR after VAO stenting. The study evaluated 57 VAO stents in 57 patients (39 men, 18 women; mean age 64 years [range, 48-90 years]). All stents were scanned with a 64-slice MDCT scanner. Three sets of images were reconstructed with three different convolution kernels. Two observers who were blinded to the results of DSA assessed the diagnostic accuracy of CTA for detecting significant ISR (≥50% diameter narrowing) of VAO stents in comparison with DSA as the reference standard. The sensitivity, specificity, positive and negative predictive values, and accuracy were calculated. Of the 57 stents, 46 (81%) were assessable using CTA, while 11 (19%) were not. No stents with diameters ≤2.75 mm were assessable. DSA revealed 13 cases of significant ISR in all stents. The respective sensitivity, specificity, positive and negative predictive values, and accuracy were 92%, 82%, 60%, 97%, and 84% for all stents. On excluding the 11 non-assessable stents, the respective values were 88%, 95%, 78%, 97%, and 93%. Of the 46 CTA assessable stents, eight significant ISRs were diagnosed on DSA. Seven of eight patients with significant ISR by DSA were diagnosed correctly with CTA. The area under the receiver-operating characteristic curve (AUC) was 0.87 for all stents and 0.91 for assessable stents, indicating good to excellent agreement between CTA and DSA for detecting significant ISR after VAO stenting. Sixty-four-slice MDCT is a promising non-invasive method of assessing stent patency and can exclude significant ISR with high diagnostic values after VAO stenting. © The Foundation Acta Radiologica 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Diagnostic Accuracy of 64Copper Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Primary Lymph Node Staging of Intermediate- to High-risk Prostate Cancer: Our Preliminary Experience.

PubMed

Cantiello, Francesco; Gangemi, Vincenzo; Cascini, Giuseppe Lucio; Calabria, Ferdinando; Moschini, Marco; Ferro, Matteo; Musi, Gennaro; Butticè, Salvatore; Salonia, Andrea; Briganti, Alberto; Damiano, Rocco

2017-08-01

To assess the diagnostic accuracy of 64 Copper prostate-specific membrane antigen ( 64 Cu-PSMA) positron emission tomography/computed tomography (PET/CT) in the primary lymph node (LN) staging of a selected cohort of intermediate- to high-risk prostate cancer (PCa) patients. An observational prospective study was performed in 23 patients with intermediate- to high-risk PCa, who underwent 64 Cu-PSMA PET/CT for local and lymph nodal staging before laparoscopic radical prostatectomy with an extended pelvic LN dissection. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for LN status of 64 Cu-PSMA PET/CT were calculated using the final pathological findings as reference. Furthermore, we evaluated the correlation of intraprostatic tumor extent and grading with 64 Cu-PSMA intraprostatic distribution. Pathological analysis of LN involvement in 413 LNs harvested from our study cohort identified a total of 22 LN metastases in 8 (5%) of the 23 (35%) PCa patients. Imaging-based LN staging in a per-patient analysis showed that 64 Cu-PSMA PET/CT was positive in 7 of 8 LN-positive patients (22%) with a sensitivity of 87.5%, specificity of 100%, PPV of 100%, and NPV of 93.7%, considering the maximum standardized uptake value (SUV max ) at 4 hours as our reference. Receiver operating characteristic curve was characterized by an area under the curve of 0.938. A significant positive association was observed between SUV max at 4 hours with Gleason score, index, and cumulative tumor volume. In our intermediate- to high-risk PCa patients study cohort, we showed the high diagnostic accuracy of 64 Cu-PSMA PET/CT for primary LN staging before radical prostatectomy. Copyright © 2017 Elsevier Inc. All rights reserved.

Computer-aided diagnosis of contrast-enhanced spectral mammography: A feasibility study.

PubMed

Patel, Bhavika K; Ranjbar, Sara; Wu, Teresa; Pockaj, Barbara A; Li, Jing; Zhang, Nan; Lobbes, Mark; Zhang, Bin; Mitchell, J Ross

2018-01-01

To evaluate whether the use of a computer-aided diagnosis-contrast-enhanced spectral mammography (CAD-CESM) tool can further increase the diagnostic performance of CESM compared with that of experienced radiologists. This IRB-approved retrospective study analyzed 50 lesions described on CESM from August 2014 to December 2015. Histopathologic analyses, used as the criterion standard, revealed 24 benign and 26 malignant lesions. An expert breast radiologist manually outlined lesion boundaries on the different views. A set of morphologic and textural features were then extracted from the low-energy and recombined images. Machine-learning algorithms with feature selection were used along with statistical analysis to reduce, select, and combine features. Selected features were then used to construct a predictive model using a support vector machine (SVM) classification method in a leave-one-out-cross-validation approach. The classification performance was compared against the diagnostic predictions of 2 breast radiologists with access to the same CESM cases. Based on the SVM classification, CAD-CESM correctly identified 45 of 50 lesions in the cohort, resulting in an overall accuracy of 90%. The detection rate for the malignant group was 88% (3 false-negative cases) and 92% for the benign group (2 false-positive cases). Compared with the model, radiologist 1 had an overall accuracy of 78% and a detection rate of 92% (2 false-negative cases) for the malignant group and 62% (10 false-positive cases) for the benign group. Radiologist 2 had an overall accuracy of 86% and a detection rate of 100% for the malignant group and 71% (8 false-positive cases) for the benign group. The results of our feasibility study suggest that a CAD-CESM tool can provide complementary information to radiologists, mainly by reducing the number of false-positive findings. Copyright © 2017 Elsevier B.V. All rights reserved.

THE DIAGNOSTIC ACCURACY OF THE LEVER SIGN FOR DETECTING ANTERIOR CRUCIATE LIGAMENT INJURY

PubMed Central

Anderson, Amanda; Watson, Seth; Dimeff, Robert J.

2017-01-01

Background An alternative physical examination procedure for evaluating the integrity of the anterior cruciate ligament (ACL) has been proposed in the literature but has not been validated in a broad population of patients with a symptomatic complaint of knee pain for its diagnostic value. Purpose To investigate the diagnostic accuracy of the Lever Sign to detect ACL tears and compare the results to Lachman testing in both supine and prone positions. Study design Prospective, blinded, diagnostic accuracy study. Methods Sixty-two consecutive patients with a complaint of knee pain were independently evaluated for the status of the ACL's integrity with the Lever Sign and the Lachman test in a prone and supine by a blinded examiner before any other diagnostic assessments were completed. Results Twenty-four of the 60 patients included in the analysis had a torn ACL resulting in a prevalence of 40%. The sensitivity of the Lever Sign, prone, and supine Lachman tests were 38, 83, and 67 % respectively and the specificity was 72, 89, and 97% resulting in positive likelihood ratios of 1.4, 7.5, and 24 and negative likelihood ratios of 0.86, 0.19, and 0.34 respectively. The positive predictive values were 47, 83, and 94% and the negative predictive values were 63, 89, and 81% respectively. The diagnostic odds ratios were 1.6, 40, and 70 with a number needed to diagnose of 10.3, 1.4, and 1.6 respectively. Conclusions The results of this study suggest that Lever Sign, in isolation, does not accurately detect the status of the ACL. During the clinical examination, the Lever Sign should be used as an adjunct to the gold standard assessment technique of anterior tibial translation assessment as employed in the Lachman tests in either prone or supine position. Level of Evidence 2 PMID:29234557

Assessing Self-Assessment: Can Age and Prior Literacy Attainment Predict the Accuracy of Children's Self-Assessments in Literacy?

ERIC Educational Resources Information Center

Keane, Lainey; Griffin, Claire P.

2018-01-01

Self-assessment practices have been advocated in recent Irish educational documents due to their potential to enhance school children's learning and self-regulatory skills. However, the literature has highlighted how some children struggle to make accurate self-assessments of their academic work, which diminishes such positive effects (Keane and…

Does Evidence-Based PTS Treatment Reduce PTS Symptoms and Suicide in Iraq and Afghanistan Veterans Seeking VA Care

DTIC Science & Technology

We succeeded in developing a Natural Language Processing ( NLP ) System with excellent performance characteristics for determining the type of...people (quadruple-annotated) and7,226 of which were double annotated. We also developed an NLP system to extract PT Checklist (PCL) scores from clinical notes with excellent accuracy (98 positive predictive value).

Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review

PubMed Central

Cordero, David; Riccadonna, Samantha; Solé, Xavier; Crous-Bou, Marta; Guinó, Elisabet; Sanjuan, Xavier; Biondo, Sebastiano; Soriano, Antonio; Jurman, Giuseppe; Capella, Gabriel; Furlanello, Cesare; Moreno, Victor

2012-01-01

Introduction The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic. PMID:23145004

The comparative accuracy of rapid diagnostic test with microscopy to diagnose malaria in subdistrict lima puluh batubara regency North Sumatera province

NASA Astrophysics Data System (ADS)

Rezeki, S.; Pasaribu, A. P.

2018-03-01

Indonesia is the country where malaria is still the most common population problem. The high rate of mortality and morbidity occurred due to delays in diagnosis whichis strongly influenced by the availability of diagnostic tools and personnel with required laboratory skill. This diagnostic study aims to compare the accuracy of a Rapid Diagnostic Test (RDT) without skill requirement, to agold standard microscopic method for malaria diagnosis. The study was conducted in Subdistrict Lima Puluh North Sumatera Province from December 2015 to January 2016. The subject was taken cross-sectionally from a population with characteristics typically found in malaria patients in Subdistrict Lima Puluh. The result showed a sensitivity of 100% and a specificity of 72.4% with a positive predictive value of 89.9% and a negative predictive value of 100%; the negative likelihood ratio is 0 and the positive likelihood ratio of 27.6 for Parascreen. This research indicates that Parascreen had a high sensitivity and specificity and may be consideredas an alternative for the diagnosis of malaria in Subdistrict Lima Puluh North Sumatera Province especially in areas where no skilled microscopist is available.

Cerebrospinal fluid lactate: a differential biomarker for bacterial and viral meningitis in children.

PubMed

Nazir, Mudasir; Wani, Wasim Ahmad; Malik, Muzaffar Ahmad; Mir, Mohd Rafiq; Ashraf, Younis; Kawoosa, Khalid; Ali, Syed Wajid

To assess the performance of cerebrospinal fluid (CSF) lactate as a biomarker to differentiate bacterial meningitis from viral meningitis in children, and to define an optimal CSF lactate concentration that can be called significant for the differentiation. Children with clinical findings compatible with meningitis were studied. CSF lactate and other conventional CSF parameters were recorded. At a cut-off value of 3mmol/L, CSF lactate had a sensitivity of 0.90, specificity of 1.0, positive predictive value of 1.0, and negative predictive value of 0.963, with an accuracy of 0.972. The positive and negative likelihood ratios were 23.6 and 0.1, respectively. When comparing between bacterial and viral meningitis, the area under the curve for CSF lactate was 0.979. The authors concluded that CSF lactate has high sensitivity and specificity in differentiating bacterial from viral meningitis. While at a cut-off value of 3mmol/L, CSF lactate has high diagnostic accuracy for bacterial meningitis, mean levels in viral meningitis remain essentially below 2mmol/L. Copyright © 2017 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

64-slice MDCT angiography of upper extremity in assessment of native hemodialysis access.

PubMed

Wasinrat, Jitladda; Siriapisith, Thanongchai; Thamtorawat, Somrach; Tongdee, Trongtum

2011-01-01

To compare multidetector row computed tomographic (MDCT) angiography with conventional digital subtraction angiography (DSA) in the evaluation of vascular access stenoses in hemodialysis patients. Twenty-one consecutive patients were imaged with MDCT angiography and subsequent DSA. The superficial vein of leg was used as the route for intravenous administration. The vascular stenosis was assessed in not significant (<50% stenosis), moderate stenosis (50%-74% stenosis), severe stenosis (75%-99%), and total occlusion (100%). The accuracy, sensitivity, specificity, positive, and negative predictive values were calculated for significant vascular stenosis using DSA as the standard reference. The sensitivity and specificity of MDCT angiography for the detection of significant hemodialysis vascular access were 100% (95% CI, 89.3%-100%) and 94.8% (95% CI, 89.1%-97.6%), respectively. The positive and negative predictive values were 84.2% (95% CI, 68.1%-93.4%) and 100% (95% CI, 95.8%-100%), respectively. The accuracy of MDCT angiography for detection of significant stenoses was 95.9% (95% CI, 91.4%-97.0%). MDCT angiography provides excellent correlation in vascular stenosis as compared with DSA in hemodialysis access. Complete assessment of entire vascular segments could be performing with MDCT angiography in planning before endovascular intervention or surgical correction.

Clinical value of polymerase chain reaction in the diagnosis of joint tuberculosis by detecting the DNA of Mycobacterium tuberculosis.

PubMed

Sun, Yong-sheng; Lou, Si-quan; Wen, Jian-min; Lv, Wei-xin; Jiao, Chang-geng; Yang, Su-min; Xu, Hai-bin

2011-02-01

To assess the clinical value of polymerase chain reaction (PCR) in the diagnosis and differential diagnosis of joint tuberculosis (TB). PCR was used blindly to detect the DNA of Mycobacterium tuberculosis (M.TB) in five specimens of M.TB, 5 of BCG, and 10 of other bacteria. Then, M. TB in 98 samples from patients with joint TB and 100 samples from patients with non-tubercular joint disorders were detected by PCR, acid-fast staining and culture,. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of PCR were calculated. The χ2 test was used for statistical analysis of the frequency of various factors. At the same time, some problems with PCR were also systematically analyzed. (1) In the "standard samples", both M. TB and BCG showed positive while other bacteria were negative. (2) In 98 cases from patients with joint TB, 81 were positive by PCR, 6 by acid-fast staining, and 17 by culture. In 100 cases from patients with non-tuberculous joint disorders, 9 were positive by PCR, and none by either acid-fast staining or culture. Sensitivity, specificity, accuracy, positive and negative predictive value of PCR were 82.65% (81/98), 91.00% (91/100), 86.87% (172/198), 90.00% (81/90) and 84.26% (91/108), respectively. (3) The positive rates for PCR, acid-fast staining and culture in detection of M. TB were 82.65% (81/98), 6.12% (6/98), and 17.34% (17/98), respectively. There were statistically significant differences between the three methods (P < 0.001). (4) The process of PCR is automatic, and can be completed within 3 to 6 hours, whereas 4 to 8 weeks are required for the conventional culture of M. TB. PCR is a sensitive, specific, rapid, simple and minimally invasive method for detection of M. TB in samples from joint TB, and can play an important role in early and rapid diagnosis and differential diagnosis of joint TB. But it also has some limitations, such as false positivity and false negativity. © 2011 Tianjin Hospital and Blackwell Publishing Asia Pty Ltd.

The Relationship between Feelings-of-Knowing and Partial Knowledge for General Knowledge Questions

PubMed Central

Norman, Elisabeth; Blakstad, Oskar; Johnsen, Øivind; Martinsen, Stig K.; Price, Mark C.

2016-01-01

Feelings of knowing (FoK) are introspective self-report ratings of the felt likelihood that one will be able to recognize a currently unrecallable memory target. Previous studies have shown that FoKs are influenced by retrieved fragment knowledge related to the target, which is compatible with the accessibility hypothesis that FoK is partly based on currently activated partial knowledge about the memory target. However, previous results have been inconsistent as to whether or not FoKs are influenced by the accuracy of such information. In our study (N = 26), we used a recall-judge-recognize procedure where stimuli were general knowledge questions. The measure of partial knowledge was wider than those applied previously, and FoK was measured before rather than after partial knowledge. The accuracy of reported partial knowledge was positively related to subsequent recognition accuracy, and FoK only predicted recognition on trials where there was correct partial knowledge. Importantly, FoK was positively related to the amount of correct partial knowledge, but did not show a similar incremental relation with incorrect knowledge. PMID:27445950

Children's memory and suggestibility about a distressing event: the role of children's and parents' attachment.

PubMed

Chae, Yoojin; Goodman, Gail S; Larson, Rakel P; Augusti, Else-Marie; Alley, Deborah; VanMeenen, Kirsten M; Culver, Michelle; Coulter, Kevin P

2014-07-01

Our goal was to identify individual difference predictors of children's memory and suggestibility for distressing personally experienced events. Specifically, we examined children's and parents' attachment orientations and children's observable levels of distress, as well as other individual difference factors, as predictors of children's memory and suggestibility. Children (N=91) aged 3 to 6years were interviewed about inoculations received at medical clinics. For children whose parents scored as more avoidant, higher distress levels during the inoculations predicted less accuracy, whereas for children whose parents scored as less avoidant, higher distress levels predicted greater accuracy. Children with more rather than less positive representations of parents and older rather than younger children answered memory questions more accurately. Two children provided false reports of child sexual abuse. Implications for theory, research, and practice are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Boiling incipience and convective boiling of neon and nitrogen

NASA Technical Reports Server (NTRS)

Papell, S. S.; Hendricks, R. C.

1977-01-01

Forced convection and subcooled boiling heat transfer data for liquid nitrogen and liquid neon were obtained in support of a design study for a 30 tesla cryomagnet cooled by forced convection of liquid neon. This design precludes nucleate boiling in the flow channels as they are too small to handle vapor flow. Consequently, it was necessary to determine boiling incipience under the operating conditions of the magnet system. The cryogen data obtained over a range of system pressures, fluid flow rates, and applied heat fluxes were used to develop correlations for predicting boiling incipience and convective boiling heat transfer coefficients in uniformly heated flow channels. The accuracy of the correlating equations was then evaluated. A technique was also developed to calculate the position of boiling incipience in a uniformly heated flow channel. Comparisons made with the experimental data showed a prediction accuracy of plus or minus 15 percent

Adaptive learning compressive tracking based on Markov location prediction

NASA Astrophysics Data System (ADS)

Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

2017-03-01

Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

EUV local CDU healing performance and modeling capability towards 5nm node

NASA Astrophysics Data System (ADS)

Jee, Tae Kwon; Timoshkov, Vadim; Choi, Peter; Rio, David; Tsai, Yu-Cheng; Yaegashi, Hidetami; Koike, Kyohei; Fonseca, Carlos; Schoofs, Stijn

2017-10-01

Both local variability and optical proximity correction (OPC) errors are big contributors to the edge placement error (EPE) budget which is closely related to the device yield. The post-litho contact hole healing will be demonstrated to meet after-etch local variability specifications using a low dose, 30mJ/cm2 dose-to-size, positive tone developed (PTD) resist with relevant throughput in high volume manufacturing (HVM). The total local variability of the node 5nm (N5) contact holes will be characterized in terms of local CD uniformity (LCDU), local placement error (LPE), and contact edge roughness (CER) using a statistical methodology. The CD healing process has complex etch proximity effects, so the OPC prediction accuracy is challenging to meet EPE requirements for the N5. Thus, the prediction accuracy of an after-etch model will be investigated and discussed using ASML Tachyon OPC model.

Improving protein–protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model

PubMed Central

An, Ji‐Yong; Meng, Fan‐Rong; Chen, Xing; Yan, Gui‐Ying; Hu, Ji‐Pu

2016-01-01

Abstract Predicting protein–protein interactions (PPIs) is a challenging task and essential to construct the protein interaction networks, which is important for facilitating our understanding of the mechanisms of biological systems. Although a number of high‐throughput technologies have been proposed to predict PPIs, there are unavoidable shortcomings, including high cost, time intensity, and inherently high false positive rates. For these reasons, many computational methods have been proposed for predicting PPIs. However, the problem is still far from being solved. In this article, we propose a novel computational method called RVM‐BiGP that combines the relevance vector machine (RVM) model and Bi‐gram Probabilities (BiGP) for PPIs detection from protein sequences. The major improvement includes (1) Protein sequences are represented using the Bi‐gram probabilities (BiGP) feature representation on a Position Specific Scoring Matrix (PSSM), in which the protein evolutionary information is contained; (2) For reducing the influence of noise, the Principal Component Analysis (PCA) method is used to reduce the dimension of BiGP vector; (3) The powerful and robust Relevance Vector Machine (RVM) algorithm is used for classification. Five‐fold cross‐validation experiments executed on yeast and Helicobacter pylori datasets, which achieved very high accuracies of 94.57 and 90.57%, respectively. Experimental results are significantly better than previous methods. To further evaluate the proposed method, we compare it with the state‐of‐the‐art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM‐BiGP method is significantly better than the SVM‐based method. In addition, we achieved 97.15% accuracy on imbalance yeast dataset, which is higher than that of balance yeast dataset. The promising experimental results show the efficiency and robust of the proposed method, which can be an automatic decision support tool for future proteomics research. For facilitating extensive studies for future proteomics research, we developed a freely available web server called RVM‐BiGP‐PPIs in Hypertext Preprocessor (PHP) for predicting PPIs. The web server including source code and the datasets are available at http://219.219.62.123:8888/BiGP/. PMID:27452983

Genomic Prediction of Gene Bank Wheat Landraces.

PubMed

Crossa, José; Jarquín, Diego; Franco, Jorge; Pérez-Rodríguez, Paulino; Burgueño, Juan; Saint-Pierre, Carolina; Vikram, Prashant; Sansaloni, Carolina; Petroli, Cesar; Akdemir, Deniz; Sneller, Clay; Reynolds, Matthew; Tattaris, Maria; Payne, Thomas; Guzman, Carlos; Peña, Roberto J; Wenzl, Peter; Singh, Sukhwinder

2016-07-07

This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, "diversity" and "prediction", including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15-20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials. Copyright © 2016 Crossa et al.

Improved detection of DNA-binding proteins via compression technology on PSSM information.

PubMed

Wang, Yubo; Ding, Yijie; Guo, Fei; Wei, Leyi; Tang, Jijun

2017-01-01

Since the importance of DNA-binding proteins in multiple biomolecular functions has been recognized, an increasing number of researchers are attempting to identify DNA-binding proteins. In recent years, the machine learning methods have become more and more compelling in the case of protein sequence data soaring, because of their favorable speed and accuracy. In this paper, we extract three features from the protein sequence, namely NMBAC (Normalized Moreau-Broto Autocorrelation), PSSM-DWT (Position-specific scoring matrix-Discrete Wavelet Transform), and PSSM-DCT (Position-specific scoring matrix-Discrete Cosine Transform). We also employ feature selection algorithm on these feature vectors. Then, these features are fed into the training SVM (support vector machine) model as classifier to predict DNA-binding proteins. Our method applys three datasets, namely PDB1075, PDB594 and PDB186, to evaluate the performance of our approach. The PDB1075 and PDB594 datasets are employed for Jackknife test and the PDB186 dataset is used for the independent test. Our method achieves the best accuracy in the Jacknife test, from 79.20% to 86.23% and 80.5% to 86.20% on PDB1075 and PDB594 datasets, respectively. In the independent test, the accuracy of our method comes to 76.3%. The performance of independent test also shows that our method has a certain ability to be effectively used for DNA-binding protein prediction. The data and source code are at https://doi.org/10.6084/m9.figshare.5104084.

Assessment of articular disc displacement of temporomandibular joint with ultrasound.

PubMed

Razek, Ahmed Abdel Khalek Abdel; Al Mahdy Al Belasy, Fouad; Ahmed, Wael Mohamed Said; Haggag, Mai Ahmed

2015-06-01

To assess pattern of articular disc displacement in patients with internal derangement (ID) of temporomandibular joint (TMJ) with ultrasound. Prospective study was conducted upon 40 TMJ of 20 patients (3 male, 17 female with mean age of 26.1 years) with ID of TMJ. They underwent high-resolution ultrasound and MR imaging of TMJ. The MR images were used as the gold standard for calculating sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) of ultrasound for diagnosis of anterior or sideway displacement of the disc. The anterior displaced disc was seen in 26 joints at MR and 22 joints at ultrasound. The diagnostic efficacy of ultrasound for anterior displacement has sensitivity of 79.3 %, specificity of 72.7 %, accuracy of 77.5 %, PPV of 88.5 %, NPV of 57.1 %, PLR of 2.9 and NLR of 0.34. The sideway displacement of disc was seen in four joints at MR and three joints at ultrasound. The diagnostic efficacy of ultrasound for sideway displacement has a sensitivity of 75 %, specificity of 63.6 %, accuracy of 66.7 %, PPV of 42.8, NPV of 87.5 %, PLR of 2.06, and NLR of 0.39. We concluded that ultrasound is a non-invasive imaging modality used for assessment of anterior and sideway displacement of the articular disc in patients with ID of TMJ.

Migrant deaths at the Arizona-Mexico border: Spatial trends of a mass disaster.

PubMed

Giordano, Alberto; Spradley, M Katherine

2017-11-01

Geographic Information Science (GIScience) technology has been used to document, investigate, and predict patterns that may be of utility in both forensic academic research and applied practice. In examining spatial and temporal trends of the mass disaster that is occurring along the U.S.-Mexico border, other researchers have highlighted predictive patterns for search and recovery efforts as well as water station placement. The purpose of this paper is to use previously collected spatial data of migrant deaths from Arizona to address issues of data uncertainty and data accuracy that affect our understanding of this phenomenon, including local and federal policies that impact the U.S.-Mexico border. The main objective of our study was to explore how the locations of migrant deaths have varied over time. Our results confirm patterns such as a lack of relationship between Border Patrol apprehensions and migrant deaths, as well as highlight new patterns such as the increased positional accuracy of migrant deaths recorded closer to the border. This paper highlights the importance of using positionally accurate data to detect spatio-temporal trends in forensic investigations of mass disasters: without qualitative and quantitative information concerning the accuracy of the data collected, the reliability of the results obtained remains questionable. We conclude by providing a set of guidelines for standardizing the collection and documentation of migrant remains at the U.S.-Mexico border. Copyright © 2017 Elsevier B.V. All rights reserved.

SU-F-T-235: Optical Scan Based Collision Avoidance Using Multiple Stereotactic Cameras During Simulation

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

Cardan, R; Popple, R; Dobelbower, M

Purpose: To demonstrate the ability to quickly generate an accurate collision avoidance map using multiple stereotactic cameras during simulation. Methods: Three Kinect stereotactic cameras were placed in the CT simulation room and optically calibrated to the DICOM isocenter. Immediately before scanning, the patient was optically imaged to generate a 3D polygon mesh, which was used to calculate the collision avoidance area using our previously developed framework. The mesh was visually compared to the CT scan body contour to ensure accurate coordinate alignment. To test the accuracy of the collision calculation, the patient and machine were physically maneuvered in the treatmentmore » room to calculated collision boundaries. Results: The optical scan and collision calculation took 38.0 seconds and 2.5 seconds to complete respectively. The collision prediction accuracy was determined using a receiver operating curve (ROC) analysis, where the true positive, true negative, false positive and false negative values were 837, 821, 43, and 79 points respectively. The ROC accuracy was 93.1% over the sampled collision space. Conclusion: We have demonstrated a framework which is fast and accurate for predicting collision avoidance for treatment which can be determined during the normal simulation process. Because of the speed, the system could be used to add a layer of safety with a negligible impact on the normal patient simulation experience. This information could be used during treatment planning to explore the feasible geometries when optimizing plans. Research supported by Varian Medical Systems.« less

Assessment of electrocardiographic criteria of left atrial enlargement.

PubMed

Batra, Mahesh Kumar; Khan, Atif; Farooq, Fawad; Masood, Tariq; Karim, Musa

2018-05-01

Background Left atrial enlargement is considered to be a robust, strong, and widely acceptable indicator of cardiovascular outcomes. Echocardiography is the gold standard for measurement of left atrial size, but electrocardiography can be simple, cost-effective, and noninvasive in clinical practice. This study was undertaken to assess the diagnostic accuracy of an established electrocardiographic criterion for left atrial enlargement, taking 2-dimensional echocardiography as the gold-standard technique. Methods A cross-sectional study was conducted on 146 consecutively selected patients with the complaints of dyspnea and palpitation and with a murmur detected on clinical examination, from September 10, 2016 to February 10, 2017. Electrocardiography and echocardiography were performed in all patients. Patients with a negative P wave terminal force in lead V 1  > 40 ms·mm on electrocardiography or left atrial dimension > 40 mm on echocardiography were classified as having left atrial enlargement. Sensitivity and specificity were calculated to assess the diagnostic accuracy. Results Taking 2-dimensional echocardiography as the gold-standard technique, electrocardiography correctly diagnosed 68 patients as positive for left atrial enlargement and 12 as negative. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of electrocardiography for left atrial enlargement were 54.4%, 57.1%, 88.3%, 17.4%, and 54.8%, respectively. Conclusion The electrocardiogram appears to be a reasonable indicator of left atrial enlargement. In case of nonavailability of echocardiography, electrocardiography can be used for diagnosis of left atrial enlargement.

Developmental Differences across Middle Childhood in Memory and Suggestibility for Negative and Positive Events.

PubMed

Paz-Alonso, Pedro M; Goodman, Gail S

2016-01-01

In the present study, we investigated age differences in children's eyewitness memory and suggestibility for negative and positive events that children often experience during middle childhood. We first examined 216 ratings by children aged 8-12 years of the frequency and intensity of personal negative and positive experiences (Study 1). Based on those ratings, videotapes depicting the most frequent and intense negative (an accident) and positive (a family excursion) events were developed. A new sample of 227 children aged 8-12 years was tested for recognition memory of the videotapes using the three-stage post-event misinformation procedure (Study 2). Compared with 8- to 9-year-olds, 10- to 12-year-olds exhibited less memory malleability and less compliance with false information. Age improvements in recognition accuracy were also evident for children who watched the negative event, but not for those who watched the positive event. Compliance predicted misinformation effects, particularly in regard to peripheral details. Thus, using ecologically representative emotional events, age differences in suggestibility and memory accuracy emerged, especially for negative events.Theoretical and forensic implications concerning children's eyewitness memory and suggestibility are discussed. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Building a knowledge-based statistical potential by capturing high-order inter-residue interactions and its applications in protein secondary structure assessment.

PubMed

Li, Yaohang; Liu, Hui; Rata, Ionel; Jakobsson, Eric

2013-02-25

The rapidly increasing number of protein crystal structures available in the Protein Data Bank (PDB) has naturally made statistical analyses feasible in studying complex high-order inter-residue correlations. In this paper, we report a context-based secondary structure potential (CSSP) for assessing the quality of predicted protein secondary structures generated by various prediction servers. CSSP is a sequence-position-specific knowledge-based potential generated based on the potentials of mean force approach, where high-order inter-residue interactions are taken into consideration. The CSSP potential is effective in identifying secondary structure predictions with good quality. In 56% of the targets in the CB513 benchmark, the optimal CSSP potential is able to recognize the native secondary structure or a prediction with Q3 accuracy higher than 90% as best scored in the predicted secondary structures generated by 10 popularly used secondary structure prediction servers. In more than 80% of the CB513 targets, the predicted secondary structures with the lowest CSSP potential values yield higher than 80% Q3 accuracy. Similar performance of CSSP is found on the CASP9 targets as well. Moreover, our computational results also show that the CSSP potential using triplets outperforms the CSSP potential using doublets and is currently better than the CSSP potential using quartets.

Development and validation of a preoperative prediction model for colorectal cancer T-staging based on MDCT images and clinical information.

PubMed

Sa, Sha; Li, Jing; Li, Xiaodong; Li, Yongrui; Liu, Xiaoming; Wang, Defeng; Zhang, Huimao; Fu, Yu

2017-08-15

This study aimed to establish and evaluate the efficacy of a prediction model for colorectal cancer T-staging. T-staging was positively correlated with the level of carcinoembryonic antigen (CEA), expression of carbohydrate antigen 19-9 (CA19-9), wall deformity, blurred outer edges, fat infiltration, infiltration into the surrounding tissue, tumor size and wall thickness. Age, location, enhancement rate and enhancement homogeneity were negatively correlated with T-staging. The predictive results of the model were consistent with the pathological gold standard, and the kappa value was 0.805. The total accuracy of staging improved from 51.04% to 86.98% with the proposed model. The clinical, imaging and pathological data of 611 patients with colorectal cancer (419 patients in the training group and 192 patients in the validation group) were collected. A spearman correlation analysis was used to validate the relationship among these factors and pathological T-staging. A prediction model was trained with the random forest algorithm. T staging of the patients in the validation group was predicted by both prediction model and traditional method. The consistency, accuracy, sensitivity, specificity and area under the curve (AUC) were used to compare the efficacy of the two methods. The newly established comprehensive model can improve the predictive efficiency of preoperative colorectal cancer T-staging.

Predicting epidermal growth factor receptor gene amplification status in glioblastoma multiforme by quantitative enhancement and necrosis features deriving from conventional magnetic resonance imaging.

PubMed

Dong, Fei; Zeng, Qiang; Jiang, Biao; Yu, Xinfeng; Wang, Weiwei; Xu, Jingjing; Yu, Jinna; Li, Qian; Zhang, Minming

2018-05-01

To study whether some of the quantitative enhancement and necrosis features in preoperative conventional MRI (cMRI) had a predictive value for epidermal growth factor receptor (EGFR) gene amplification status in glioblastoma multiforme (GBM).Fifty-five patients with pathologically determined GBMs who underwent cMRI were retrospectively reviewed. The following cMRI features were quantitatively measured and recorded: long and short diameters of the enhanced portion (LDE and SDE), maximum and minimum thickness of the enhanced portion (MaxTE and MinTE), and long and short diameters of the necrotic portion (LDN and SDN). Univariate analysis of each feature and a decision tree model fed with all the features were performed. Area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the performance of features, and predictive accuracy was used to assess the performance of the model.For single feature, MinTE showed the best performance in differentiating EGFR gene amplification negative (wild-type) (nEGFR) GBM from EGFR gene amplification positive (pEGFR) GBM, and it got an AUC of 0.68 with a cut-off value of 2.6 mm. The decision tree model included 2 features MinTE and SDN, and got an accuracy of 0.83 in validation dataset.Our results suggest that quantitative measurement of the features MinTE and SDN in preoperative cMRI had a high accuracy for predicting EGFR gene amplification status in GBM.

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).

PubMed

Yan, Long; Wang, Hong; Zhang, Xuan; Li, Ming-Yue; He, Juan

2017-01-01

Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model. A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE). Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy. The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.

Screening ultrasonography of 2,204 patients with blunt abdominal trauma in the Wenchuan earthquake.

PubMed

Zhou, Jixiang; Huang, Jiwei; Wu, Hong; Jiang, Hui; Zhang, Heqing; Prasoon, Pankaj; Xu, Yinglong; Bai, Yannan; Qiu, Jianguo; Zeng, Yong

2012-10-01

Abdominal injuries constitute a small proportion of all earthquake-related traumas; however, it often resulted in fatal hemorrhage. Ultrasonography has been described as an effective triage tool in the evaluation of blunt abdominal trauma. We aimed to present an overview of the diagnostic accuracy of screening ultrasonography for patients with blunt abdominal trauma admitted to various hospitals during the Wenchuan earthquake in China. We retrospectively analyzed the patients with blunt abdominal trauma who underwent ultrasonography after admission to various hospitals. Ultrasonography findings were considered positive if evidence of free fluid or a parenchymal injury was identified. Ultrasonography findings were compared with the findings of computed tomography, diagnostic peritoneal lavage, repeated ultrasonography, cystography, operation, and/or the clinical course. Findings from 2,204 ultrasonographic examinations were evaluated. Findings of 199 ultrasonographic examinations (9.0%) were considered positive. Of the patients, 12 (0.5%) had a false-negative ultrasonographic findings; of this group, 3 (25%) required exploratory laparotomy. Ultrasonography had a sensitivity of 91.9%, specificity of 96.9%, and an accuracy of 96.6% for detection of abdominal injuries. Positive predictive value was 68.3%, and negative predictive value was 99.4%. Screening ultrasonography is highly reliable in the setting of blunt abdominal trauma after earthquake. It should be used as an initial diagnostic modality in the evaluation of most blunt abdominal trauma. Diagnostic study, level III.

Visual inspection of cervix with acetic acid: a good alternative to pap smear for cervical cancer screening in resource-limited setting.

PubMed

Khan, Momna; Sultana, Syeda Seema; Jabeen, Nigar; Arain, Uzma; Khans, Salma

2015-02-01

To determine the diagnostic accuracy of visual inspection of cervix using 3% acetic acid as a screening test for early detection of cervical cancer taking histopathology as the gold standard. The cross-sectional study was conducted at Civil Hospital Karachi from July 1 to December 31, 2012 and comprised all sexually active women aged 19-60 years. During speculum examination 3% acetic acid was applied over the cervix with the help of cotton swab. The observations were noted as positive or negative on visual inspection of the cervix after acetic acid application according to acetowhite changes. Colposcopy-guided cervical biopsy was done in patients with positive or abnormal looking cervix. Colposcopic-directed biopsy was taken as the gold standard to assess visual inspection readings. SPSS 17 was used for statistical analysis. There were 500 subjects with a mean age of 35.74 ± 9.64 years. Sensitivity, specifically, positive predicted value, negative predicted value of visual inspection of the cervix after acetic acid application was 93.5%, 95.8%, 76.3%, 99%, and the diagnostic accuracy was 95.6%. Visual inspection of the cervix after acetic acid application is an effective method of detecting pre-invasive phase of cervical cancer and a good alternative to cytological screening for cervical cancer in resource-poor setting like Pakistan and can reduce maternal morbidity and mortality.

PREOPERATIVE MRI IMPROVES PREDICTION OF EXTENSIVE OCCULT AXILLARY LYMPH NODE METASTASES IN BREAST CANCER PATIENTS WITH A POSITIVE SENTINEL LYMPH NODE BIOPSY

PubMed Central

Loiselle, Christopher; Eby, Peter R.; Kim, Janice N.; Calhoun, Kristine E.; Allison, Kimberly H.; Gadi, Vijayakrishna K.; Peacock, Sue; Storer, Barry; Mankoff, David A.; Partridge, Savannah C.; Lehman, Constance D.

2014-01-01

Rationale and Objectives To test the ability of quantitative measures from preoperative Dynamic Contrast Enhanced MRI (DCE-MRI) to predict, independently and/or with the Katz pathologic nomogram, which breast cancer patients with a positive sentinel lymph node biopsy will have ≥ 4 positive axillary lymph nodes upon completion axillary dissection. Methods and Materials A retrospective review was conducted to identify clinically node-negative invasive breast cancer patients who underwent preoperative DCE-MRI, followed by sentinel node biopsy with positive findings and complete axillary dissection (6/2005 – 1/2010). Clinical/pathologic factors, primary lesion size and quantitative DCE-MRI kinetics were collected from clinical records and prospective databases. DCE-MRI parameters with univariate significance (p < 0.05) to predict ≥ 4 positive axillary nodes were modeled with stepwise regression and compared to the Katz nomogram alone and to a combined MRI-Katz nomogram model. Results Ninety-eight patients with 99 positive sentinel biopsies met study criteria. Stepwise regression identified DCE-MRI total persistent enhancement and volume adjusted peak enhancement as significant predictors of ≥4 metastatic nodes. Receiver operating characteristic (ROC) curves demonstrated an area under the curve (AUC) of 0.78 for the Katz nomogram, 0.79 for the DCE-MRI multivariate model, and 0.87 for the combined MRI-Katz model. The combined model was significantly more predictive than the Katz nomogram alone (p = 0.003). Conclusion Integration of DCE-MRI primary lesion kinetics significantly improved the Katz pathologic nomogram accuracy to predict presence of metastases in ≥ 4 nodes. DCE-MRI may help identify sentinel node positive patients requiring further localregional therapy. PMID:24331270

Processing of positive-causal and negative-causal coherence relations in primary school children and adults: a test of the cumulative cognitive complexity approach in German.

PubMed

Knoepke, Julia; Richter, Tobias; Isberner, Maj-Britt; Naumann, Johannes; Neeb, Yvonne; Weinert, Sabine

2017-03-01

Establishing local coherence relations is central to text comprehension. Positive-causal coherence relations link a cause and its consequence, whereas negative-causal coherence relations add a contrastive meaning (negation) to the causal link. According to the cumulative cognitive complexity approach, negative-causal coherence relations are cognitively more complex than positive-causal ones. Therefore, they require greater cognitive effort during text comprehension and are acquired later in language development. The present cross-sectional study tested these predictions for German primary school children from Grades 1 to 4 and adults in reading and listening comprehension. Accuracy data in a semantic verification task support the predictions of the cumulative cognitive complexity approach. Negative-causal coherence relations are cognitively more demanding than positive-causal ones. Moreover, our findings indicate that children's comprehension of negative-causal coherence relations continues to develop throughout the course of primary school. Findings are discussed with respect to the generalizability of the cumulative cognitive complexity approach to German.

Discovering Peripheral Arterial Disease Cases from Radiology Notes Using Natural Language Processing

PubMed Central

Savova, Guergana K.; Fan, Jin; Ye, Zi; Murphy, Sean P.; Zheng, Jiaping; Chute, Christopher G.; Kullo, Iftikhar J.

2010-01-01

As part of the Electronic Medical Records and Genomics Network, we applied, extended and evaluated an open source clinical Natural Language Processing system, Mayo’s Clinical Text Analysis and Knowledge Extraction System, for the discovery of peripheral arterial disease cases from radiology reports. The manually created gold standard consisted of 223 positive, 19 negative, 63 probable and 150 unknown cases. Overall accuracy agreement between the system and the gold standard was 0.93 as compared to a named entity recognition baseline of 0.46. Sensitivity for the positive, probable and unknown cases was 0.93–0.96, and for the negative cases was 0.72. Specificity and negative predictive value for all categories were in the 90’s. The positive predictive value for the positive and unknown categories was in the high 90’s, for the negative category was 0.84, and for the probable category was 0.63. We outline the main sources of errors and suggest improvements. PMID:21347073

Predicting High Imaging Utilization Based on Initial Radiology Reports: A Feasibility Study of Machine Learning.

PubMed

Hassanpour, Saeed; Langlotz, Curtis P

2016-01-01

Imaging utilization has significantly increased over the last two decades, and is only recently showing signs of moderating. To help healthcare providers identify patients at risk for high imaging utilization, we developed a prediction model to recognize high imaging utilizers based on their initial imaging reports. The prediction model uses a machine learning text classification framework. In this study, we used radiology reports from 18,384 patients with at least one abdomen computed tomography study in their imaging record at Stanford Health Care as the training set. We modeled the radiology reports in a vector space and trained a support vector machine classifier for this prediction task. We evaluated our model on a separate test set of 4791 patients. In addition to high prediction accuracy, in our method, we aimed at achieving high specificity to identify patients at high risk for high imaging utilization. Our results (accuracy: 94.0%, sensitivity: 74.4%, specificity: 97.9%, positive predictive value: 87.3%, negative predictive value: 95.1%) show that a prediction model can enable healthcare providers to identify in advance patients who are likely to be high utilizers of imaging services. Machine learning classifiers developed from narrative radiology reports are feasible methods to predict imaging utilization. Such systems can be used to identify high utilizers, inform future image ordering behavior, and encourage judicious use of imaging. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Contact high: Mania proneness and positive perception of emotional touches.

PubMed

Piff, Paul K; Purcell, Amanda; Gruber, June; Hertenstein, Matthew J; Keltner, Dacher

2012-01-01

How do extreme degrees of positive emotion-such as those characteristic of mania-influence emotion perception? The present study investigated how mania proneness, assessed using the Hypomanic Personality Scale, influences the perception of emotion via touch. Using a validated dyadic interaction paradigm for communicating emotion through touch (Hertenstein, Keltner, App, Bulleit, & Jaskolka, 2006), participants (N=53) received eight different touches to their forearm from a stranger and then identified the emotion via forced-choice methodology. Mania proneness predicted increased overall accuracy in touch perception, particularly for positive emotion touches, as well as the over-attribution of positive and under-attribution of negative emotions across all touches. These findings highlight the effects of positive emotion extremes on the perception of emotion in social interactions.

Sensitivity, specificity and predictive values of anterior chamber tap in cases of bacterial endophthalmitis.

PubMed

Sjoholm-Gomez de Liano, Carl; Soberon-Ventura, Vidal F; Salcedo-Villanueva, Guillermo; Santos-Palacios, Abril; Guerrero-Naranjo, Jose Luis; Fromow-Guerra, Jans; García-Aguirre, Gerardo; Morales-Canton, Virgilio; Velez-Montoya, Raul

2017-01-01

To assess the sensitivity, specificity, positive predictive value and negative predictive value of anterior chamber tap for the diagnosis of bacterial endophthalmitis on a population with high prevalence. Retrospective, single centre, case series study. We reviewed all medical records with clinical diagnosis of bacterial endophthalmitis in our hospital from January 1st, 2000 to December 31st 2014. From each record, we documented general demographic data, best corrected visual acuity and vitreous and aqueous tap microbiological results. All cases were further divided according to the endophthalmitis aetiology to perform individual calculations of sensitivity, specificity, positive predictive value, negative predictive value, accuracy and prevalence. We used the results of the vitreous tap as the gold standard for diagnosis of bacterial endophthalmitis. We excluded those records in which the aqueous and vitreous samples were not taken simultaneously or had an incomplete microbiological report. Significance were assessed with chi squared statistics, with an alpha value of 0.05 for statistical significance. A total of 190 cases fulfilled the inclusion/exclusion criteria. Positive culture rate from vitreous samples was 64.74%. Positive culture rate from aqueous sample was 32.11%. Bacteria isolated from aqueous samples matched those isolated from vitreous samples 78.68% of the time. The overall sensitivity was 38.21%, specificity: 75.51%, positive predictive value: 79.66%, negative predictive value: 32.74% ( p  = 0.08). Subgroup analysis showed that anterior chamber taps in cases of post-surgical endophthalmitis had a moderate to low sensitivity (37.73%), high specificity (93%) and high positive predictive value (95%) ( p  < 0.04). The sensitivity and specificity of anterior chamber tap are low and should not be used for critical therapeutic decisions in patients with suspected bacterial endophthalmitis. In cases of post-surgical endophthalmitis, the result of an anterior chamber tap could be used for therapeutic guidance, but only in conjunction with clinical presentation and in the absence of a better method for diagnosis.

Role of PI-RADS Version 2 for Prediction of Upgrading in Biopsy-Proven Prostate Cancer With Gleason Score 6.

PubMed

Song, Wan; Bang, Seok Hwan; Jeon, Hwang Gyun; Jeong, Byong Chang; Seo, Seong Il; Jeon, Seong Soo; Choi, Han Yong; Kim, Chan Kyo; Lee, Hyun Moo

2018-02-23

The objective of this study was to investigate the effect of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) on prediction of postoperative Gleason score (GS) upgrading for patients with biopsy GS 6 prostate cancer. We retrospectively reviewed 443 patients who underwent magnetic resonance imaging (MRI) and radical prostatectomy for biopsy-proven GS 6 prostate cancer between January 2011 and December 2013. Preoperative clinical variables and pathologic GS were examined, and all MRI findings were assessed with PI-RADSv2. Receiver operating characteristic curves were used to compare predictive accuracies of multivariate logistic regression models with or without PI-RADSv2. Of the total 443 patients, 297 (67.0%) experienced GS upgrading postoperatively. PI-RADSv2 scores 1 to 3 and 4 to 5 were identified in 157 (25.4%) and 286 (64.6%) patients, respectively, and the rate of GS upgrading was 54.1% and 74.1%, respectively (P < .001). In multivariate analysis, prostate-specific antigen density > 0.16 ng/mL 2 , number of positive cores ≥ 2, maximum percentage of cancer per core > 20, and PI-RADSv2 score 4 to 5 were independent predictors influencing GS upgrading (each P < .05). When predictive accuracies of multivariate models with or without PI-RADSv2 were compared, the model including PI-RADSv2 was shown to have significantly higher accuracy (area under the curve, 0.729 vs. 0.703; P = .041). Use of PI-RADSv2 is an independent predictor of postoperative GS upgrading and increases the predictive accuracy of GS upgrading. PI-RADSv2 might be used as a preoperative imaging tool to determine risk classification and to help counsel patients with regard to treatment decision and prognosis of disease. Copyright © 2018 Elsevier Inc. All rights reserved.

In silico platform for predicting and initiating β-turns in a protein at desired locations.

PubMed

Singh, Harinder; Singh, Sandeep; Raghava, Gajendra P S

2015-05-01

Numerous studies have been performed for analysis and prediction of β-turns in a protein. This study focuses on analyzing, predicting, and designing of β-turns to understand the preference of amino acids in β-turn formation. We analyzed around 20,000 PDB chains to understand the preference of residues or pair of residues at different positions in β-turns. Based on the results, a propensity-based method has been developed for predicting β-turns with an accuracy of 82%. We introduced a new approach entitled "Turn level prediction method," which predicts the complete β-turn rather than focusing on the residues in a β-turn. Finally, we developed BetaTPred3, a Random forest based method for predicting β-turns by utilizing various features of four residues present in β-turns. The BetaTPred3 achieved an accuracy of 79% with 0.51 MCC that is comparable or better than existing methods on BT426 dataset. Additionally, models were developed to predict β-turn types with better performance than other methods available in the literature. In order to improve the quality of prediction of turns, we developed prediction models on a large and latest dataset of 6376 nonredundant protein chains. Based on this study, a web server has been developed for prediction of β-turns and their types in proteins. This web server also predicts minimum number of mutations required to initiate or break a β-turn in a protein at specified location of a protein. © 2015 Wiley Periodicals, Inc.

Stellar Occultations by TNOs and Centaurs: first results in the “Gaia era”

NASA Astrophysics Data System (ADS)

Rossi, Gustavo; Vieira-Martins, Roberto; Sicardy, Bruno; Ortiz, Jose Luis; Rio Group, Lucky Star Occultation Team, Granada Occultation Team

2017-10-01

After the first release of the GAIA catalog (in September/2016), stellar positions are now known with unprecedented accuracy, reaching values of the order of milliarcseconds. This improvement reflected into a stunning accuracy on the astrometry of moving objects, such as TNOs. Unfortunately, Gaia stars proper motions will be only available on the second data release (DR2) next year, so there is still a need to use hybrid stellar catalogs for occultation predictions until then. Despite that, stellar occultations predictions are now much more accurate, and the biggest uncertainties comes mainly from the object ephemerides. This issue will be overcome by large surveys such as the LSST, which will provide positions for the known TNOs and it is expected to increase the number of known TNOs by nearly 40,000, with an unprecedent amount of acquired information.This huge amount of data also poses a new era in stellar occultations: predictions will be very accurate and the participation of professional astronomers, laboratories, and the amateur community will be crucial to observe the predicted events; observation campaigns will need to be selected according to a specific scientific purpose such as the probability to detect rings or archs around a body, the presence of atmosphere or even the detection of topographic features; the development of softwares capable of reducing the data more efficiently and an easier method to coordinate observation campaigns are needed.Here we present some impressive results obtained from predictions and observed occultations in 2017 (among them we have Pluto, Chariklo and Haumea), the problems we are starting to face in the beginning of the “Gaia era” and the future challenges of stellar occultation.

Clinical Prediction Rule for Declines in Activities of Daily Living at 6 Months After Surgery for Hip Fracture Repair.

PubMed

Tanaka, Ryo; Umehara, Takuya; Fujimura, Takafumi; Ozawa, Junya

2016-12-01

To develop and assess a clinical prediction rule (CPR) to predict declines in activities of daily living (ADL) at 6 months after surgery for hip fracture repair. Prospective, cohort study. From hospital to home. Patients (N=104) with hip fractures after surgery. Not applicable. ADL were assessed using the Barthel Index at 6 months after surgery. At 6 months after surgery, 86 patients (82.6%) were known to be alive, 1 patient (1.0%) had died, and 17 (16.3%) were lost to follow-up. Thirty-two patients (37.2%) did not recover their ADL at 6 months after surgery to levels before fracture. The classification and regression trees methodology was used to develop 2 models to predict a decline in ADL: (1) model 1 included age, type of fracture, and care level before fracture (sensitivity=75.0%, specificity=81.5%, positive predictive value=70.6%, positive likelihood ratio=4.050); and (2) model 2 included the degree of independence 2 weeks postsurgery for ADL chair transfer, ADL ambulation, and age (sensitivity=65.6%, specificity=87.0%, positive predictive value=75.0%, positive likelihood ratio=5.063). The areas under the receiver operating characteristic curves of both CPR models were .825 (95% confidential interval, .728-.923) and .790 (95% confidence interval, .683-.897), respectively. CPRs with moderate accuracy were developed to predict declines in ADL at 6 months after surgery for hip fracture repair. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Sensitivity and positive predictive values of presurgical clinical diagnosis of excised benign and malignant skin tumors: a prospective study of 835 lesions in 778 patients.

PubMed

Har-Shai, Y; Hai, N; Taran, A; Mayblum, S; Barak, A; Tzur, E; Schafer, I; David, R; David, E; Linn, S

2001-12-01

This article reports on the sensitivity and positive predictive value of clinical diagnosis of benign and malignant skin tumors by expert plastic surgeons in an Israeli clinic. Most published reports have focused on the sensitivity of clinicians' diagnoses, a general measure of the physician's skill that does not predict the rate of accuracy of a physician's diagnoses. Our study of 835 lesions in 778 patients, one of the largest Israeli series, assesses the clinical diagnosis of malignant and benign skin tumors and is one of the few that provide information on the positive predictive value, the measure that is of interest to both physicians and patients. The majority of tumors were benign (56.8 percent), 31.6 percent were malignant, and 11.6 percent were premalignant. Among the 474 benign lesions, 46 percent were nevi. The most common nevi subclass was compound nevi (53 percent), 9 percent of the nevi were dysplastic, and 5 percent were blue nevi. The most common malignant tumor was basal cell carcinoma, accounting for 78 percent of malignant tumors. Although sensitivity for clinical diagnosis of malignancy was 91.3 percent, the positive predictive value for clinical diagnosis of malignancy was 71.3 percent. The sensitivity rate for clinically diagnosing premalignant tumors was 42.3 percent, whereas the positive predictive value for these diagnoses was higher (64.1 percent). The sensitivity rate for diagnosis of all benign lesions was 85.9 percent, and the positive predictive value was 94.2 percent. The sensitivity rate for diagnosis of all nevi was 87.6 percent, and the positive predictive value was 85.7 percent: i.e., only seven of the 218 pathologically proven diagnoses of nevi (3.2 percent) were falsely diagnosed as malignant lesions. Even more interestingly, five of the 223 clinical diagnoses of nevi (2.2 percent) were pathologically proven to be malignant melanomas, and seven were found to be premalignant lesions (3.1 percent). It was concluded that publications which report only on the sensitivity neglect to provide information of interest regarding the positive predictive value. Often, positive predictive value is qualitatively different from the sensitivity, and thus relying only on the sensitivity may lead to incorrect evaluation of a clinical judgment, which may result in erroneous surgical decisions.

Wireless Wearable Multisensory Suite and Real-Time Prediction of Obstructive Sleep Apnea Episodes.

PubMed

Le, Trung Q; Cheng, Changqing; Sangasoongsong, Akkarapol; Wongdhamma, Woranat; Bukkapatnam, Satish T S

2013-01-01

Obstructive sleep apnea (OSA) is a common sleep disorder found in 24% of adult men and 9% of adult women. Although continuous positive airway pressure (CPAP) has emerged as a standard therapy for OSA, a majority of patients are not tolerant to this treatment, largely because of the uncomfortable nasal air delivery during their sleep. Recent advances in wireless communication and advanced ("bigdata") preditive analytics technologies offer radically new point-of-care treatment approaches for OSA episodes with unprecedented comfort and afforadability. We introduce a Dirichlet process-based mixture Gaussian process (DPMG) model to predict the onset of sleep apnea episodes based on analyzing complex cardiorespiratory signals gathered from a custom-designed wireless wearable multisensory suite. Extensive testing with signals from the multisensory suite as well as PhysioNet's OSA database suggests that the accuracy of offline OSA classification is 88%, and accuracy for predicting an OSA episode 1-min ahead is 83% and 3-min ahead is 77%. Such accurate prediction of an impending OSA episode can be used to adaptively adjust CPAP airflow (toward improving the patient's adherence) or the torso posture (e.g., minor chin adjustments to maintain steady levels of the airflow).

Genomic Prediction of Gene Bank Wheat Landraces

PubMed Central

Crossa, José; Jarquín, Diego; Franco, Jorge; Pérez-Rodríguez, Paulino; Burgueño, Juan; Saint-Pierre, Carolina; Vikram, Prashant; Sansaloni, Carolina; Petroli, Cesar; Akdemir, Deniz; Sneller, Clay; Reynolds, Matthew; Tattaris, Maria; Payne, Thomas; Guzman, Carlos; Peña, Roberto J.; Wenzl, Peter; Singh, Sukhwinder

2016-01-01

This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials. PMID:27172218

Real time endoscopic ultrasound elastography and strain ratio in the diagnosis of solid pancreatic lesions.

PubMed

Okasha, Hussein; Elkholy, Shaimaa; El-Sayed, Ramy; Wifi, Mohamed-Naguib; El-Nady, Mohamed; El-Nabawi, Walid; El-Dayem, Waleed A; Radwan, Mohamed I; Farag, Ali; El-Sherif, Yahya; Al-Gemeie, Emad; Salman, Ahmed; El-Sherbiny, Mohamed; El-Mazny, Ahmed; Mahdy, Reem E

2017-08-28

To evaluate the accuracy of the elastography score combined to the strain ratio in the diagnosis of solid pancreatic lesions (SPL). A total of 172 patients with SPL identified by endoscopic ultrasound were enrolled in the study to evaluate the efficacy of elastography and strain ratio in differentiating malignant from benign lesions. The semi quantitative score of elastography was represented by the strain ratio method. Two areas were selected, area (A) representing the region of interest and area (B) representing the normal area. Area (B) was then divided by area (A). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated by comparing diagnoses made by elastography, strain ratio and final diagnoses. SPL were shown to be benign in 49 patients and malignant in 123 patients. Elastography alone had a sensitivity of 99%, a specificity of 63%, and an accuracy of 88%, a PPV of 87% and an NPV of 96%. The best cut-off level of strain ratio to obtain the maximal area under the curve was 7.8 with a sensitivity of 92%, specificity of 77%, PPV of 91%, NPV of 80% and an accuracy of 88%. Another estimated cut off strain ratio level of 3.8 had a higher sensitivity of 99% and NPV of 96%, but with less specificity, PPV and accuracy 53%, 84% and 86%, respectively. Adding both elastography to strain ratio resulted in a sensitivity of 98%, specificity of 77%, PPV of 91%, NPV of 95% and accuracy of 92% for the diagnosis of SPL. Combining elastography to strain ratio increases the accuracy of the differentiation of benign from malignant SPL.

Real time endoscopic ultrasound elastography and strain ratio in the diagnosis of solid pancreatic lesions

PubMed Central

Okasha, Hussein; Elkholy, Shaimaa; El-Sayed, Ramy; Wifi, Mohamed-Naguib; El-Nady, Mohamed; El-Nabawi, Walid; El-Dayem, Waleed A; Radwan, Mohamed I; Farag, Ali; El-sherif, Yahya; Al-Gemeie, Emad; Salman, Ahmed; El-Sherbiny, Mohamed; El-Mazny, Ahmed; Mahdy, Reem E

2017-01-01

AIM To evaluate the accuracy of the elastography score combined to the strain ratio in the diagnosis of solid pancreatic lesions (SPL). METHODS A total of 172 patients with SPL identified by endoscopic ultrasound were enrolled in the study to evaluate the efficacy of elastography and strain ratio in differentiating malignant from benign lesions. The semi quantitative score of elastography was represented by the strain ratio method. Two areas were selected, area (A) representing the region of interest and area (B) representing the normal area. Area (B) was then divided by area (A). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated by comparing diagnoses made by elastography, strain ratio and final diagnoses. RESULTS SPL were shown to be benign in 49 patients and malignant in 123 patients. Elastography alone had a sensitivity of 99%, a specificity of 63%, and an accuracy of 88%, a PPV of 87% and an NPV of 96%. The best cut-off level of strain ratio to obtain the maximal area under the curve was 7.8 with a sensitivity of 92%, specificity of 77%, PPV of 91%, NPV of 80% and an accuracy of 88%. Another estimated cut off strain ratio level of 3.8 had a higher sensitivity of 99% and NPV of 96%, but with less specificity, PPV and accuracy 53%, 84% and 86%, respectively. Adding both elastography to strain ratio resulted in a sensitivity of 98%, specificity of 77%, PPV of 91%, NPV of 95% and accuracy of 92% for the diagnosis of SPL. CONCLUSION Combining elastography to strain ratio increases the accuracy of the differentiation of benign from malignant SPL. PMID:28932088

Diagnostic Accuracy Assessment of Sensititre and Agar Disk Diffusion for Determining Antimicrobial Resistance Profiles of Bovine Clinical Mastitis Pathogens▿

PubMed Central

Saini, V.; Riekerink, R. G. M. Olde; McClure, J. T.; Barkema, H. W.

2011-01-01

Determining the accuracy and precision of a measuring instrument is pertinent in antimicrobial susceptibility testing. This study was conducted to predict the diagnostic accuracy of the Sensititre MIC mastitis panel (Sensititre) and agar disk diffusion (ADD) method with reference to the manual broth microdilution test method for antimicrobial resistance profiling of Escherichia coli (n = 156), Staphylococcus aureus (n = 154), streptococcal (n = 116), and enterococcal (n = 31) bovine clinical mastitis isolates. The activities of ampicillin, ceftiofur, cephalothin, erythromycin, oxacillin, penicillin, the penicillin-novobiocin combination, pirlimycin, and tetracycline were tested against the isolates. Diagnostic accuracy was determined by estimating the area under the receiver operating characteristic curve; intertest essential and categorical agreements were determined as well. Sensititre and the ADD method demonstrated moderate to highly accurate (71 to 99%) and moderate to perfect (71 to 100%) predictive accuracies for 74 and 76% of the isolate-antimicrobial MIC combinations, respectively. However, the diagnostic accuracy was low for S. aureus-ceftiofur/oxacillin combinations and other streptococcus-ampicillin combinations by either testing method. Essential agreement between Sensititre automatic MIC readings and MIC readings obtained by the broth microdilution test method was 87%. Essential agreement between Sensititre automatic and manual MIC reading methods was 97%. Furthermore, the ADD test method and Sensititre MIC method exhibited 92 and 91% categorical agreement (sensitive, intermediate, resistant) of results, respectively, compared with the reference method. However, both methods demonstrated lower agreement for E. coli-ampicillin/cephalothin combinations than for Gram-positive isolates. In conclusion, the Sensititre and ADD methods had moderate to high diagnostic accuracy and very good essential and categorical agreement for most udder pathogen-antimicrobial combinations and can be readily employed in veterinary diagnostic laboratories. PMID:21270215

Accuracy of four commonly used color vision tests in the identification of cone disorders.

PubMed

Thiadens, Alberta A H J; Hoyng, Carel B; Polling, Jan Roelof; Bernaerts-Biskop, Riet; van den Born, L Ingeborgh; Klaver, Caroline C W

2013-04-01

To determine which color vision test is most appropriate for the identification of cone disorders. In a clinic-based study, four commonly used color vision tests were compared between patients with cone dystrophy (n = 37), controls with normal visual acuity (n = 35), and controls with low vision (n = 39) and legal blindness (n = 11). Mean outcome measures were specificity, sensitivity, positive predictive value and discriminative accuracy of the Ishihara test, Hardy-Rand-Rittler (HRR) test, and the Lanthony and Farnsworth Panel D-15 tests. In the comparison between cone dystrophy and all controls, sensitivity, specificity and predictive value were highest for the HRR and Ishihara tests. When patients were compared to controls with normal vision, discriminative accuracy was highest for the HRR test (c-statistic for PD-axes 1, for T-axis 0.851). When compared to controls with poor vision, discriminative accuracy was again highest for the HRR test (c-statistic for PD-axes 0.900, for T-axis 0.766), followed by the Lanthony Panel D-15 test (c-statistic for PD-axes 0.880, for T-axis 0.500) and Ishihara test (c-statistic 0.886). Discriminative accuracies of all tests did not further decrease when patients were compared to controls who were legally blind. The HRR, Lanthony Panel D-15 and Ishihara all have a high discriminative accuracy to identify cone disorders, but the highest scores were for the HRR test. Poor visual acuity slightly decreased the accuracy of all tests. Our advice is to use the HRR test since this test also allows for evaluation of all three color axes and quantification of color defects.

Clinical accuracy of point-of-care urine culture in general practice.

PubMed

Holm, Anne; Cordoba, Gloria; Sørensen, Tina Møller; Jessen, Lisbeth Rem; Frimodt-Møller, Niels; Siersma, Volkert; Bjerrum, Lars

2017-06-01

To assess the clinical accuracy (sensitivity (SEN), specificity (SPE), positive predictive value and negative predictive value) of two point-of-care (POC) urine culture tests for the identification of urinary tract infection (UTI) in general practice. Prospective diagnostic accuracy study comparing two index tests (Flexicult™ SSI-Urinary Kit or ID Flexicult™) with a reference standard (urine culture performed in the microbiological department). General practice in the Copenhagen area patients. Adult female patients consulting their general practitioner with suspected uncomplicated, symptomatic UTI. (1) Overall accuracy of POC urine culture in general practice. (2) Individual accuracy of each of the two POC tests in this study. (3) Accuracy of POC urine culture in general practice with enterococci excluded, since enterococci are known to multiply in boric acid used for transportation for the reference standard. (4) Accuracy based on expert reading of photographs of POC urine cultures performed in general practice. Standard culture performed in the microbiological department was used as reference standard for all four measures. Twenty general practices recruited 341 patients with suspected uncomplicated UTI. The overall agreement between index test and reference was 0.76 (CI: 0.71-0.80), SEN 0.88 (CI: 0.83-0.92) and SPE 0.55 (CI: 0.46-0.64). The two POC tests produced similar results individually. Overall agreement with enterococci excluded was 0.82 (0.77-0.86) and agreement between expert readings of photographs and reference results was 0.81 (CI: 0.76-0.85). POC culture used in general practice has high SEN but low SPE. Low SPE could be due to both misinterpretation in general practice and an imperfect reference standard. Registration number: ClinicalTrials.gov NCT02323087.

[Diagnostic value of cardiac magnetic resonance in patients with acute viral myocarditis].

PubMed

Ouyang, Haichun; Chen, Haixiong; Hu, Yunzhao; Wu, Yanxian; Li, Wensheng; Chen, Yuying; Cen, Yujian

2014-11-01

To assess the diagnostic value of cardiac magnetic resonance (CMR) in patients with acute viral myocarditis. Thirty patients with suspected acute viral myocarditis admitted in first people's hospital of Shunde from June 2011 to June 2013 were included in this prospective study. The diagnostic sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of acute viral myocarditis were evaluated by clinical diagnosis. Diagnostic value among different scan methods and Lake Louise criteria were compared. Acute viral myocarditis was diagnosed in 63.33% (19/30) patients.Values for sensitivity, specificity, PPV, NPV, and diagnostic accuracy within the overall cohort were 57.89%, 72.73%, 78.57%, 50.00%, 63.33%, respectively by edema imaging (ER).Values for sensitivity, specificity, PPV, NPV, and diagnostic accuracy within the overall cohort were 78.95%, 63.64%, 78.95%, 63.64%, 73.33%, respectively using global relative enhancement (gRE).Values for sensitivity, specificity, PPV, NPV, and diagnostic accuracy within the overall cohort were 78.95%, 54.55%, 75.00%, 60.00%, 70.00%, respectively using late gadolinium enhancement (LGE) criteria.Values for sensitivity, specificity, PPV, NPV, and diagnostic accuracy within the overall cohort were 84.21%, 81.82%, 88.89%, 75.00%, 83.33% using Lake Louise criteria. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy using Lake Louise criteria were significantly higher than using ER, gRE, LGE alone(all P < 0.05).Specificity was higher using ER than using gRE and LGE (both P < 0.05). The sensitivity, NPV, and diagnostic accuracy were significantly higher using gRE than using ER (all P < 0.05) and was similar as using LGE (all P > 0.05). Cardiac magnetic resonance is an excellent imaging modality for the diagnosis of acute viral myocarditis.

Accuracy of Predicted Genomic Breeding Values in Purebred and Crossbred Pigs.

PubMed

Hidalgo, André M; Bastiaansen, John W M; Lopes, Marcos S; Harlizius, Barbara; Groenen, Martien A M; de Koning, Dirk-Jan

2015-05-26

Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent. Copyright © 2015 Hidalgo et al.

The accuracy of Genomic Selection in Norwegian red cattle assessed by cross-validation.

PubMed

Luan, Tu; Woolliams, John A; Lien, Sigbjørn; Kent, Matthew; Svendsen, Morten; Meuwissen, Theo H E

2009-11-01

Genomic Selection (GS) is a newly developed tool for the estimation of breeding values for quantitative traits through the use of dense markers covering the whole genome. For a successful application of GS, accuracy of the prediction of genomewide breeding value (GW-EBV) is a key issue to consider. Here we investigated the accuracy and possible bias of GW-EBV prediction, using real bovine SNP genotyping (18,991 SNPs) and phenotypic data of 500 Norwegian Red bulls. The study was performed on milk yield, fat yield, protein yield, first lactation mastitis traits, and calving ease. Three methods, best linear unbiased prediction (G-BLUP), Bayesian statistics (BayesB), and a mixture model approach (MIXTURE), were used to estimate marker effects, and their accuracy and bias were estimated by using cross-validation. The accuracies of the GW-EBV prediction were found to vary widely between 0.12 and 0.62. G-BLUP gave overall the highest accuracy. We observed a strong relationship between the accuracy of the prediction and the heritability of the trait. GW-EBV prediction for production traits with high heritability achieved higher accuracy and also lower bias than health traits with low heritability. To achieve a similar accuracy for the health traits probably more records will be needed.

POPISK: T-cell reactivity prediction using support vector machines and string kernels

PubMed Central

2011-01-01

Background Accurate prediction of peptide immunogenicity and characterization of relation between peptide sequences and peptide immunogenicity will be greatly helpful for vaccine designs and understanding of the immune system. In contrast to the prediction of antigen processing and presentation pathway, the prediction of subsequent T-cell reactivity is a much harder topic. Previous studies of identifying T-cell receptor (TCR) recognition positions were based on small-scale analyses using only a few peptides and concluded different recognition positions such as positions 4, 6 and 8 of peptides with length 9. Large-scale analyses are necessary to better characterize the effect of peptide sequence variations on T-cell reactivity and design predictors of a peptide's T-cell reactivity (and thus immunogenicity). The identification and characterization of important positions influencing T-cell reactivity will provide insights into the underlying mechanism of immunogenicity. Results This work establishes a large dataset by collecting immunogenicity data from three major immunology databases. In order to consider the effect of MHC restriction, peptides are classified by their associated MHC alleles. Subsequently, a computational method (named POPISK) using support vector machine with a weighted degree string kernel is proposed to predict T-cell reactivity and identify important recognition positions. POPISK yields a mean 10-fold cross-validation accuracy of 68% in predicting T-cell reactivity of HLA-A2-binding peptides. POPISK is capable of predicting immunogenicity with scores that can also correctly predict the change in T-cell reactivity related to point mutations in epitopes reported in previous studies using crystal structures. Thorough analyses of the prediction results identify the important positions 4, 6, 8 and 9, and yield insights into the molecular basis for TCR recognition. Finally, we relate this finding to physicochemical properties and structural features of the MHC-peptide-TCR interaction. Conclusions A computational method POPISK is proposed to predict immunogenicity with scores which are useful for predicting immunogenicity changes made by single-residue modifications. The web server of POPISK is freely available at http://iclab.life.nctu.edu.tw/POPISK. PMID:22085524

POPISK: T-cell reactivity prediction using support vector machines and string kernels.

PubMed

Tung, Chun-Wei; Ziehm, Matthias; Kämper, Andreas; Kohlbacher, Oliver; Ho, Shinn-Ying

2011-11-15

Accurate prediction of peptide immunogenicity and characterization of relation between peptide sequences and peptide immunogenicity will be greatly helpful for vaccine designs and understanding of the immune system. In contrast to the prediction of antigen processing and presentation pathway, the prediction of subsequent T-cell reactivity is a much harder topic. Previous studies of identifying T-cell receptor (TCR) recognition positions were based on small-scale analyses using only a few peptides and concluded different recognition positions such as positions 4, 6 and 8 of peptides with length 9. Large-scale analyses are necessary to better characterize the effect of peptide sequence variations on T-cell reactivity and design predictors of a peptide's T-cell reactivity (and thus immunogenicity). The identification and characterization of important positions influencing T-cell reactivity will provide insights into the underlying mechanism of immunogenicity. This work establishes a large dataset by collecting immunogenicity data from three major immunology databases. In order to consider the effect of MHC restriction, peptides are classified by their associated MHC alleles. Subsequently, a computational method (named POPISK) using support vector machine with a weighted degree string kernel is proposed to predict T-cell reactivity and identify important recognition positions. POPISK yields a mean 10-fold cross-validation accuracy of 68% in predicting T-cell reactivity of HLA-A2-binding peptides. POPISK is capable of predicting immunogenicity with scores that can also correctly predict the change in T-cell reactivity related to point mutations in epitopes reported in previous studies using crystal structures. Thorough analyses of the prediction results identify the important positions 4, 6, 8 and 9, and yield insights into the molecular basis for TCR recognition. Finally, we relate this finding to physicochemical properties and structural features of the MHC-peptide-TCR interaction. A computational method POPISK is proposed to predict immunogenicity with scores which are useful for predicting immunogenicity changes made by single-residue modifications. The web server of POPISK is freely available at http://iclab.life.nctu.edu.tw/POPISK.

[Diagnostic value of dynamic-extended focused assessment with sonography for trauma in patients with multiple trauma].

PubMed

Xu, Yongsong; Wang, Runze; Zhu, Mengmeng; Li, Xuexue; Pan, Xiaodong; Ni, Tong; Zhou, Shusheng

2018-01-01

To investigate the diagnostic value of dynamic-extended focused assessment with sonography for trauma (D-EFAST) in patients with multiple trauma in intensive care unit (ICU). A prospective clinical study was conducted. Eighty patients with multiple trauma admitted to ICU of Anhui Provincial Hospital from September 1st, 2014 to December 31st, 2016 were enrolled. Extended focused assessment with sonography for trauma (E-FAST) check was conducted at first, for those who had positive findings diagnosis was confirmed by immediately CT examination or surgical exploration. If it was negative, the patients received E-FAST every morning for 7 days (defined as D-EFAST), for those with positive findings, immediately CT or surgery was performed to clarify the diagnosis. The final clinical diagnosis was used as the "gold standard" to calculate the diagnostic accordance rate of EFAST and D-EFAST examination technique for pneumothorax, pleural effusion, spleen injury, kidney damage, liver damage, gastrointestinal injury, pericardial effusion, bladder rupture, and pancreatic injury, as well as their sensitivity, specificity, positive predictive value, negative predictive value, accuracy rate, and missed diagnosis rate, and the difference between EFAST and D-EFAST was compared. There were 4 patients excluded because of death and abandoning treatment, and finally 76 patients were included in the study. The total sensitivity of E-FAST examination technique for pneumothorax, pleural effusion, spleen injury, liver damage, gastrointestinal injury, pericardial effusion, and bladder rupture was 75.9% (66/87), and the specificity was 98.3% (587/597), the positive predictive value was 86.8% (66/76), and the negative predictive value was 96.5% (587/608), the accuracy rate was 95.5% (653/684), and the rate of missed diagnosis was 24.1% (21/87). The most of the delayed injury in patients with multiple trauma occurred at 2-7 days after injury with incidence of 4.8% (33/684). The diagnostic sensitivity of D-EFAST for delayed injury was 98.3% (118/120), the specificity was 99.8% (563/564), the positive predictive value was 99.2% (118/119), the negative predictive value was 99.6% (563/565), the diagnostic accuracy rate was 99.6% (681/684), and rate of missed diagnosis was 1.7% (2/120). When the final clinical diagnosis was set as the "gold standard", D-EFAST technology for the detection rate was 98.3% (118/120) for patients with multiple trauma on organ injury while the detection rate of E-FAST was 75.9% (66/87), with statistical significant difference (P < 0.01), indicating that D-EFAST was better than E-FAST in check of multiple trauma patients with organ injury. Although the E-FAST technology can quickly diagnose the multiple trauma patients and win the rescue time for critical patients, multiple trauma patients injured after 2-7 days prone to delayed damage and are difficult to detect, and D-EFAST can be used to find delayed damage earlier, and reduce the misdiagnosis rate of multiple trauma patients.

EVALUATING RISK-PREDICTION MODELS USING DATA FROM ELECTRONIC HEALTH RECORDS.

PubMed

Wang, L E; Shaw, Pamela A; Mathelier, Hansie M; Kimmel, Stephen E; French, Benjamin

2016-03-01

The availability of data from electronic health records facilitates the development and evaluation of risk-prediction models, but estimation of prediction accuracy could be limited by outcome misclassification, which can arise if events are not captured. We evaluate the robustness of prediction accuracy summaries, obtained from receiver operating characteristic curves and risk-reclassification methods, if events are not captured (i.e., "false negatives"). We derive estimators for sensitivity and specificity if misclassification is independent of marker values. In simulation studies, we quantify the potential for bias in prediction accuracy summaries if misclassification depends on marker values. We compare the accuracy of alternative prognostic models for 30-day all-cause hospital readmission among 4548 patients discharged from the University of Pennsylvania Health System with a primary diagnosis of heart failure. Simulation studies indicate that if misclassification depends on marker values, then the estimated accuracy improvement is also biased, but the direction of the bias depends on the direction of the association between markers and the probability of misclassification. In our application, 29% of the 1143 readmitted patients were readmitted to a hospital elsewhere in Pennsylvania, which reduced prediction accuracy. Outcome misclassification can result in erroneous conclusions regarding the accuracy of risk-prediction models.

Intraoperative serum parathyroid hormone level is an indicator of hypocalcaemia in total thyroidectomy patients.

PubMed

Islam, M S; Sultana, T; Paul, D; Huq, A H M Z; Chowdhury, A A; Ferdous, C; Ahmed, A N N

2012-12-01

Postoperative hypocalcaemia is the most frequent and common complication after total thyroidectomy. It is necessary to diagnose or to predict hypocalcaemia immediately after total thyroidectomy for minimizing complications. A prospective observational study was carried out in the Department of Clinical Pathology in collaboration with Department of Microbiology & Immunology, Department of Surgery, Department of Otolaryngology, Bangabandhu Sheikh Mujib Medical University (BSMMU) and Department of Otolaryngology, Dhaka Medical College & Hospital (DMC&H), Dhaka, during the period of September 2010 to August 2011 to evaluate intraoperative (20 minutes after total thyroidectomy) parathyroid hormone (PTH) measurement as a predictor of post thyroidectomy hypocalcaemia. Total 65 patients were enrolled in this study those came for total thyroidectomy. Postoperative hypocalcaemia developed in 25 cases. Intraoperative PTH was assessed and significant correlation was found between intraoperative PTH level and development of hypocalcaemia. The sensitivity, specificity, accuracy, positive predictive value, negative predictive value of intraoperative serum PTH for prediction of post total thyroidectomy hypocalcaemia were 84.0%, 85.0%, 84.6%, 77.8%, and 89.5% respectively. Because of the high sensitivity, specificity and accuracy of intraoperative serum PTH of this study, the early prediction of hypocalcaemia could be made by single assay of intraoperative serum PTH level at 20 minutes after total thyroidectomy.

Localizome: a server for identifying transmembrane topologies and TM helices of eukaryotic proteins utilizing domain information

PubMed Central

Lee, Sunghoon; Lee, Byungwook; Jang, Insoo; Kim, Sangsoo; Bhak, Jong

2006-01-01

The Localizome server predicts the transmembrane (TM) helix number and TM topology of a user-supplied eukaryotic protein and presents the result as an intuitive graphic representation. It utilizes hmmpfam to detect the presence of Pfam domains and a prediction algorithm, Phobius, to predict the TM helices. The results are combined and checked against the TM topology rules stored in a protein domain database called LocaloDom. LocaloDom is a curated database that contains TM topologies and TM helix numbers of known protein domains. It was constructed from Pfam domains combined with Swiss-Prot annotations and Phobius predictions. The Localizome server corrects the combined results of the user sequence to conform to the rules stored in LocaloDom. Compared with other programs, this server showed the highest accuracy for TM topology prediction: for soluble proteins, the accuracy and coverage were 99 and 75%, respectively, while for TM protein domain regions, they were 96 and 68%, respectively. With a graphical representation of TM topology and TM helix positions with the domain units, the Localizome server is a highly accurate and comprehensive information source for subcellular localization for soluble proteins as well as membrane proteins. The Localizome server can be found at . PMID:16845118

A Novel Strategy to Predict Carcinogenicity of Antiparasitics Based on a Combination of DNA Lesions and Bacterial Mutagenicity Tests

PubMed Central

Liu, Qianying; Lei, Zhixin; Zhu, Feng; Ihsan, Awais; Wang, Xu; Yuan, Zonghui

2017-01-01

Genotoxicity and carcinogenicity testing of pharmaceuticals prior to commercialization is requested by regulatory agencies. The bacterial mutagenicity test was considered having the highest accuracy of carcinogenic prediction. However, some evidences suggest that it always results in false-positive responses when the bacterial mutagenicity test is used to predict carcinogenicity. Along with major changes made to the International Committee on Harmonization guidance on genotoxicity testing [S2 (R1)], the old data (especially the cytotgenetic data) may not meet current guidelines. This review provides a compendium of retrievable results of genotoxicity and animal carcinogenicity of 136 antiparasitics. Neither genotoxicity nor carcinogenicity data is available for 84 (61.8%), while 52 (38.2%) have been evaluated in at least one genotoxicity or carcinogenicity study, and only 20 (14.7%) in both genotoxicity and carcinogenicity studies. Among 33 antiparasitics with at least one old result in in vitro genotoxicity, 15 (45.5%) are in agreement with the current ICH S2 (R1) guidance for data acceptance. Compared with other genotoxicity assays, the DNA lesions can significantly increase the accuracy of prediction of carcinogenicity. Together, a combination of DNA lesion and bacterial tests is a more accurate way to predict carcinogenicity. PMID:29170735

A Systematic Approach to Predicting Spring Force for Sagittal Craniosynostosis Surgery.

PubMed

Zhang, Guangming; Tan, Hua; Qian, Xiaohua; Zhang, Jian; Li, King; David, Lisa R; Zhou, Xiaobo

2016-05-01

Spring-assisted surgery (SAS) can effectively treat scaphocephaly by reshaping crania with the appropriate spring force. However, it is difficult to accurately estimate spring force without considering biomechanical properties of tissues. This study presents and validates a reliable system to accurately predict the spring force for sagittal craniosynostosis surgery. The authors randomly chose 23 patients who underwent SAS and had been followed for at least 2 years. An elastic model was designed to characterize the biomechanical behavior of calvarial bone tissue for each individual. After simulating the contact force on accurate position of the skull strip with the springs, the finite element method was applied to calculating the stress of each tissue node based on the elastic model. A support vector regression approach was then used to model the relationships between biomechanical properties generated from spring force, bone thickness, and the change of cephalic index after surgery. Therefore, for a new patient, the optimal spring force can be predicted based on the learned model with virtual spring simulation and dynamic programming approach prior to SAS. Leave-one-out cross-validation was implemented to assess the accuracy of our prediction. As a result, the mean prediction accuracy of this model was 93.35%, demonstrating the great potential of this model as a useful adjunct for preoperative planning tool.

Practice increases procedural errors after task interruption.

PubMed

Altmann, Erik M; Hambrick, David Z

2017-05-01

Positive effects of practice are ubiquitous in human performance, but a finding from memory research suggests that negative effects are possible also. The finding is that memory for items on a list depends on the time interval between item presentations. This finding predicts a negative effect of practice on procedural performance under conditions of task interruption. As steps of a procedure are performed more quickly, memory for past performance should become less accurate, increasing the rate of skipped or repeated steps after an interruption. We found this effect, with practice generally improving speed and accuracy, but impairing accuracy after interruptions. The results show that positive effects of practice can interact with architectural constraints on episodic memory to have negative effects on performance. In practical terms, the results suggest that practice can be a risk factor for procedural errors in task environments with a high incidence of task interruption. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Mapping Gnss Restricted Environments with a Drone Tandem and Indirect Position Control

NASA Astrophysics Data System (ADS)

Cledat, E.; Cucci, D. A.

2017-08-01

The problem of autonomously mapping highly cluttered environments, such as urban and natural canyons, is intractable with the current UAV technology. The reason lies in the absence or unreliability of GNSS signals due to partial sky occlusion or multi-path effects. High quality carrier-phase observations are also required in efficient mapping paradigms, such as Assisted Aerial Triangulation, to achieve high ground accuracy without the need of dense networks of ground control points. In this work we consider a drone tandem in which the first drone flies outside the canyon, where GNSS constellation is ideal, visually tracks the second drone and provides an indirect position control for it. This enables both autonomous guidance and accurate mapping of GNSS restricted environments without the need of ground control points. We address the technical feasibility of this concept considering preliminary real-world experiments in comparable conditions and we perform a mapping accuracy prediction based on a simulation scenario.

The Role of Fine Needle Aspiration in the Diagnosis of Parotid Gland Tumors: Correlation With Preoperative Computerized Tomography Tumor Size.

PubMed

Ghantous, Yasmine; Naddaf, Raja; Barak, Michal; Abd-Elraziq, Murad; Abu Eln-Naaj, Imad

2016-03-01

The role of fine needle aspiration cytology (FNAC) in the diagnosis of parotid gland masses is still controversial, regarding its sensitivity and specificity that vary between 41% and 100% and between 86% and 100% respectively.The aim of this study was to identify the specificity and sensitivity of FNAC of parotid gland tumors in relation to the tumor size as characterized preoperatively by computer tomography. The medical files of 79 patients whom were referred to the MaxilloFacila Surgery Department, Rambam medical center, over a 10.5-year period (2000-2010) were analyzed retrospectively.The extensity of the operation was determined by the location of the tumor as presented in computed tomography (CT) radiography, and preoperative FNAC examination.The majority of the masses were located in the superficial lobe (88.52%), and only 11.48% of the patients were located in the deep lobe (8:1 ratio). FNAC results were nondiagnostic in 7 patients (8.86%), 62 patients were diagnosed as inflammatory and benign lesion in (78.48%), malignant tumors were diagnosed in 10 patients (12.65%).The sensitivity in our study was 90%, the specificity was 98%, positive predictive value was 90%, negative predictive value was 98%, and diagnostic accuracy was 88%. The positive predictive value was 90%, the negative predictive value was 98%.Analyzing the effect of the preoperative CT size upon the accuracy of the FNAC diagnosis, we found that lesion with preoperative CT size greater than 24 mm has a more accurate FNAC result (P = 0.034).

Evaluation of dental pulp sensibility tests in a clinical setting.

PubMed

Jespersen, James J; Hellstein, John; Williamson, Anne; Johnson, William T; Qian, Fang

2014-03-01

The goal of this project was to evaluate the performance of dental pulp sensibility testing with Endo Ice (1,1,1,2-tetrafluoroethane) and an electric pulp tester (EPT) and to determine the effect of several variables on the reliability of these tests. Data were collected from 656 patients seen in the University of Iowa College of Dentistry Endodontic graduate clinic. The results of pulpal sensibility tests, along with the tooth number, age, sex, number of restored surfaces, presence or absence of clinical or radiographic caries, and reported recent use of analgesic medications, were recorded. The presence of vital tissue within the pulp chamber was used to verify the diagnosis. The Endo Ice results showed accuracy, 0.904; sensitivity, 0.916; specificity, 0.896; positive predictive value, 0.862; and negative predictive value, 0.937. The EPT results showed accuracy, 0.75; sensitivity, 0.84; specificity, 0.74; positive predictive value, 0.58; and negative predictive value, 0.90. Patients aged 21-50 years exhibited a more accurate response to cold testing (P = .0043). Vital teeth with caries responded more accurately to cold testing (P = .0077). There was no statistically significant difference noted with any other variable examined. Pulpal sensibility testing with Endo Ice and EPT are accurate and reliable methods of determining pulpal vitality. Patients aged 21-50 exhibited a more accurate response to cold. Sex, tooth type, number of restored surfaces, presence of caries, and recent analgesic use did not significantly alter the results of pulpal sensibility testing in this study. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Diagnostic accuracy of quantitative real-time PCR assay versus clinical and Gram stain identification of bacterial vaginosis.

PubMed

Menard, J-P; Mazouni, C; Fenollar, F; Raoult, D; Boubli, L; Bretelle, F

2010-12-01

The purpose of this investigation was to determine the diagnostic accuracy of quantitative real-time polymerase chain reaction (PCR) assay in diagnosing bacterial vaginosis versus the standard methods, the Amsel criteria and the Nugent score. The Amsel criteria, the Nugent score, and results from the molecular tool were obtained independently from vaginal samples of 163 pregnant women who reported abnormal vaginal symptoms before 20 weeks gestation. To determine the performance of the molecular tool, we calculated the kappa value, sensitivity, specificity, and positive and negative predictive values. Either or both of the Amsel criteria (≥3 criteria) and the Nugent score (score ≥7) indicated that 25 women (15%) had bacterial vaginosis, and the remaining 138 women did not. DNA levels of Gardnerella vaginalis or Atopobium vaginae exceeded 10(9) copies/mL or 10(8) copies/mL, respectively, in 34 (21%) of the 163 samples. Complete agreement between both reference methods and high concentrations of G. vaginalis and A. vaginae was found in 94.5% of women (154/163 samples, kappa value = 0.81, 95% confidence interval 0.70-0.81). The nine samples with discordant results were categorized as intermediate flora by the Nugent score. The molecular tool predicted bacterial vaginosis with a sensitivity of 100%, a specificity of 93%, a positive predictive value of 73%, and a negative predictive value of 100%. The quantitative real-time PCR assay shows excellent agreement with the results of both reference methods for the diagnosis of bacterial vaginosis.

Common polygenic variation enhances risk prediction for Alzheimer's disease.

PubMed

Escott-Price, Valentina; Sims, Rebecca; Bannister, Christian; Harold, Denise; Vronskaya, Maria; Majounie, Elisa; Badarinarayan, Nandini; Morgan, Kevin; Passmore, Peter; Holmes, Clive; Powell, John; Brayne, Carol; Gill, Michael; Mead, Simon; Goate, Alison; Cruchaga, Carlos; Lambert, Jean-Charles; van Duijn, Cornelia; Maier, Wolfgang; Ramirez, Alfredo; Holmans, Peter; Jones, Lesley; Hardy, John; Seshadri, Sudha; Schellenberg, Gerard D; Amouyel, Philippe; Williams, Julie

2015-12-01

The identification of subjects at high risk for Alzheimer's disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer's disease and the accuracy of Alzheimer's disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer's Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer's disease (P = 4.9 × 10(-26)). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10(-19)). The best prediction accuracy AUC = 78.2% (95% confidence interval 77-80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer's disease has a significant polygenic component, which has predictive utility for Alzheimer's disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Anatomic features of the neck as predictive markers of difficult direct laryngoscopy in men and women: A prospective study

PubMed Central

Chara, Liaskou; Eleftherios, Vouzounerakis; Maria, Moirasgenti; Anastasia, Trikoupi; Chryssoula, Staikou

2014-01-01

Background and Aims: Difficult airway assessment is based on various anatomic parameters of upper airway, much of it being concentrated on oral cavity and the pharyngeal structures. The diagnostic value of tests based on neck anatomy in predicting difficult laryngoscopy was assessed in this prospective, open cohort study. Methods: We studied 341 adult patients scheduled to receive general anaesthesia. Thyromental distance (TMD), sternomental distance (STMD), ratio of height to thyromental distance (RHTMD) and neck circumference (NC) were measured pre-operatively. The laryngoscopic view was classified according to the Cormack–Lehane Grade (1-4). Difficult laryngoscopy was defined as Cormack–Lehane Grade 3 or 4. The optimal cut-off points for each variable were identified by using receiver operating characteristic analysis. Sensitivity, specificity and positive predictive value and negative predictive value (NPV) were calculated for each test. Multivariate analysis with logistic regression, including all variables, was used to create a predictive model. Comparisons between genders were also performed. Results: Laryngoscopy was difficult in 12.6% of the patients. The cut-off values were: TMD ≤7 cm, STMD ≤15 cm, RHTMD >18.4 and NC >37.5 cm. The RHTMD had the highest sensitivity (88.4%) and NPV (95.2%), while TMD had the highest specificity (83.9%). The area under curve (AUC) for the TMD, STMD, RHTMD and NC was 0.63, 0.64, 0.62 and 0.54, respectively. The predictive model exhibited a higher and statistically significant diagnostic accuracy (AUC: 0.68, P < 0.001). Gender-specific cut-off points improved the predictive accuracy of NC in women (AUC: 0.65). Conclusions: The TMD, STMD, RHTMD and NC were found to be poor single predictors of difficult laryngoscopy, while a model including all four variables had a significant predictive accuracy. Among the studied tests, gender-specific cut-off points should be used for NC. PMID:24963183

Anatomic features of the neck as predictive markers of difficult direct laryngoscopy in men and women: A prospective study.

PubMed

Liaskou, Chara; Chara, Liaskou; Vouzounerakis, Eleftherios; Eleftherios, Vouzounerakis; Moirasgenti, Maria; Maria, Moirasgenti; Trikoupi, Anastasia; Anastasia, Trikoupi; Staikou, Chryssoula; Chryssoula, Staikou

2014-03-01

Difficult airway assessment is based on various anatomic parameters of upper airway, much of it being concentrated on oral cavity and the pharyngeal structures. The diagnostic value of tests based on neck anatomy in predicting difficult laryngoscopy was assessed in this prospective, open cohort study. We studied 341 adult patients scheduled to receive general anaesthesia. Thyromental distance (TMD), sternomental distance (STMD), ratio of height to thyromental distance (RHTMD) and neck circumference (NC) were measured pre-operatively. The laryngoscopic view was classified according to the Cormack-Lehane Grade (1-4). Difficult laryngoscopy was defined as Cormack-Lehane Grade 3 or 4. The optimal cut-off points for each variable were identified by using receiver operating characteristic analysis. Sensitivity, specificity and positive predictive value and negative predictive value (NPV) were calculated for each test. Multivariate analysis with logistic regression, including all variables, was used to create a predictive model. Comparisons between genders were also performed. Laryngoscopy was difficult in 12.6% of the patients. The cut-off values were: TMD ≤7 cm, STMD ≤15 cm, RHTMD >18.4 and NC >37.5 cm. The RHTMD had the highest sensitivity (88.4%) and NPV (95.2%), while TMD had the highest specificity (83.9%). The area under curve (AUC) for the TMD, STMD, RHTMD and NC was 0.63, 0.64, 0.62 and 0.54, respectively. The predictive model exhibited a higher and statistically significant diagnostic accuracy (AUC: 0.68, P < 0.001). Gender-specific cut-off points improved the predictive accuracy of NC in women (AUC: 0.65). The TMD, STMD, RHTMD and NC were found to be poor single predictors of difficult laryngoscopy, while a model including all four variables had a significant predictive accuracy. Among the studied tests, gender-specific cut-off points should be used for NC.

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

PubMed Central

Bandeira e Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-01-01

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. PMID:28455415

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

PubMed

Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-06-07

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.