scholarly journals Dilute pilocarpine test for diagnosis of Adie’s tonic pupil

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yung-Ju Yoo ◽  
Jeong-Min Hwang ◽  
Hee Kyung Yang
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Group Versus ◽  
Diagnostic Ability ◽  
Tonic Pupil ◽  
Pupillary Light ◽  
Denervation Supersensitivity ◽  
Pupillary Constriction ◽  
Control Study ◽  
Better Than

AbstractWe have compared the diagnostic ability of different concentrations of 0.125% and 0.0625% dilute pilocarpine for detecting denervation supersensitivity in unilateral Adie’s tonic pupil. This retrospective, observational, case–control study involved 117 subjects, consisting of 56 patients with unilateral Adie’s tonic pupil and 61 controls with other causes of unilateral dilated pupils. Subjects underwent the dilute pilocarpine test with one of the two concentrations, 0.125% or 0.0625%. Pupillary light reflex was recorded with a dynamic pupillometer at baseline and at 30–40 min after instilling one of the two concentrations of dilute pilocarpine. Diagnostic accuracy of two different concentrations of the dilute pilocarpine test, 0.125% group versus 0.0625% group, were compared by area under the receiver operating characteristic curve (AUC). Diagnostic ability of the dilute pilocarpine test for detecting denervation supersensitivity in unilateral Adie’s tonic pupil was significantly better in the 0.0625% group than in the 0.125% group (AUC = 0.954 vs. 0.840, respectively, P = 0.047). In the 0.0625% group, the change in maximal pupil diameter of ≥ 0.5 mm after topical pilocarpine instillation showed 100% sensitivity and 82.8% specificity for detecting Adie’s tonic pupil. This study confirmed that pupillary constriction with 0.0625% pilocarpine is better than 0.125% pilocarpine for detecting denervation supersensitivity in Adie’s tonic pupil. Digital pupillometry is a reliable method for assessing denervation supersensitivity in Adie's tonic pupil.

scholarly journals Predicting experimental success: a retrospective case-control study using the rat intraluminal thread model of stroke

2020 ◽  
Vol 13 (12) ◽  
pp. dmm044651
Author(s):  
Lisa Liebenstund ◽  
Mark Coburn ◽  
Christina Fitzner ◽  
Antje Willuweit ◽  
Karl-Josef Langen ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Disease Model ◽  
Area Under The Curve ◽  
Artery Occlusion ◽  
Retrospective Case ◽  
Stroke Research ◽  
Left And Right ◽  
Cerebral Artery Occlusion ◽  
Control Study

ABSTRACTThe poor translational success rate of preclinical stroke research may partly be due to inaccurate modelling of the disease. We provide data on transient middle cerebral artery occlusion (tMCAO) experiments, including detailed intraoperative monitoring to elaborate predictors indicating experimental success (ischemia without occurrence of confounding pathologies). The tMCAO monitoring data (bilateral cerebral blood flow, CBF; heart rate, HR; and mean arterial pressure, MAP) of 16 animals with an ‘ideal’ outcome (MCA-ischemia), and 48 animals with additional or other pathologies (subdural haematoma or subarachnoid haemorrhage), were checked for their prognostic performance (receiver operating characteristic curve and area under the curve, AUC). Animals showing a decrease in the contralateral CBF at the time of MCA occlusion suffered from unintended pathologies. Implementation of baseline MAP, in addition to baseline HR (AUC, 0.83, 95% c.i. 0.68 to 0.97), increased prognostic relevance (AUC, 0.89, 95% c.i. 0.79 to 0.98). Prediction performance improved when two additional predictors referring to differences in left and right CBF were considered (AUC, 1.00, 95% c.i. 1.0 to 1.0). Our data underline the importance of peri-interventional monitoring to verify a successful experimental performance in order to ensure a disease model as homogeneous as possible.

scholarly journals Comparisons of QPFs Derived from Single- and Multicore Convection-Allowing Ensembles

2019 ◽  
Vol 34 (6) ◽  
pp. 1955-1964
Author(s):  
Adam J. Clark
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Skill Score ◽  
Ensemble Forecast ◽  
Grid Spacing ◽  
Forecast System ◽  
Relative Operating Characteristic ◽  
Core System ◽  
Testing And Evaluation ◽  
Better Than

Abstract This study compares ensemble precipitation forecasts from 10-member, 3-km grid-spacing, CONUS domain single- and multicore ensembles that were a part of the 2016 Community Leveraged Unified Ensemble (CLUE) that was run for the 2016 NOAA Hazardous Weather Testbed Spring Forecasting Experiment. The main results are that a 10-member ARW ensemble was significantly more skillful than a 10-member NMMB ensemble, and a 10-member MIX ensemble (5 ARW and 5 NMMB members) performed about the same as the 10-member ARW ensemble. Skill was measured by area under the relative operating characteristic curve (AUC) and fractions skill score (FSS). Rank histograms in the ARW ensemble were flatter than the NMMB ensemble indicating that the envelope of ensemble members better encompassed observations (i.e., better reliability) in the ARW. Rank histograms in the MIX ensemble were similar to the ARW ensemble. In the context of NOAA’s plans for a Unified Forecast System featuring a CAM ensemble with a single core, the results are positive and indicate that it should be possible to develop a single-core system that performs as well as or better than the current operational CAM ensemble, which is known as the High-Resolution Ensemble Forecast System (HREF). However, as new modeling applications are developed and incremental changes that move HREF toward a single-core system are made possible, more thorough testing and evaluation should be conducted.

scholarly journals Are Body Composition Parameters Better than Conventional Anthropometric Measures in Predicting Pediatric Hypertension?

2020 ◽  
Vol 17 (16) ◽  
pp. 5771
Author(s):  
Chih-Yu Hsu ◽  
Rong-Ho Lin ◽  
Yu-Ching Lin ◽  
Jau-Yuan Chen ◽  
Wen-Cheng Li ◽  
...  
Keyword(s):  
Body Composition ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Fat Free Mass ◽  
Z Score ◽  
Pediatric Hypertension ◽  
Anthropometric Measures ◽  
Operating Characteristic Curve ◽  
Better Than

Body composition (BC) parameters are associated with cardiometabolic diseases in children; however, the importance of BC parameters for predicting pediatric hypertension is inconclusive. This cross-sectional study aimed to compare the difference in predictive values of BC parameters and conventional anthropometric measures for pediatric hypertension in school-aged children. A total of 340 children (177 girls and 163 boys) with a mean age of 8.8 ± 1.7 years and mean body mass index (BMI) z-score of 0.50 ± 1.24 were enrolled (102 hypertensive children and 238 normotensive children). Significantly higher values of anthropometric measures (BMI, BMI z-score, BMI percentile, waist-to-height ratio) and BC parameters (body-fat percentage, muscle weight, fat mass, fat-free mass) were observed among the hypertensive subgroup compared to their normotensive counterparts. A prediction model combining fat mass ≥ 3.65 kg and fat-free mass ≥ 34.65 kg (area under the receiver operating characteristic curve = 0.688; sensitivity = 66.7%; specificity = 89.9%) performed better than BMI alone (area under the receiver operating characteristic curve = 0.649; sensitivity = 55.9%; specificity = 73.9%) in predicting hypertension. In conclusion, BC parameters are better than anthropometric measures in predicting pediatric hypertension. BC measuring is a reasonable approach for risk stratification in pediatric hypertension.

scholarly journals IoT information theft prediction using ensemble feature selection

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Joffrey L. Leevy ◽  
John Hancock ◽  
Taghi M. Khoshgoftaar ◽  
Jared M. Peterson
Keyword(s):  
Feature Selection ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Classification Performance ◽  
Feature Reduction ◽  
Security Risk ◽  
Precision Recall Curve ◽  
Iot Devices ◽  
Feature Selection Techniques ◽  
Better Than

AbstractThe recent years have seen a proliferation of Internet of Things (IoT) devices and an associated security risk from an increasing volume of malicious traffic worldwide. For this reason, datasets such as Bot-IoT were created to train machine learning classifiers to identify attack traffic in IoT networks. In this study, we build predictive models with Bot-IoT to detect attacks represented by dataset instances from the Information Theft category, as well as dataset instances from the data exfiltration and keylogging subcategories. Our contribution is centered on the evaluation of ensemble feature selection techniques (FSTs) on classification performance for these specific attack instances. A group or ensemble of FSTs will often perform better than the best individual technique. The classifiers that we use are a diverse set of four ensemble learners (Light GBM, CatBoost, XGBoost, and random forest (RF)) and four non-ensemble learners (logistic regression (LR), decision tree (DT), Naive Bayes (NB), and a multi-layer perceptron (MLP)). The metrics used for evaluating classification performance are area under the receiver operating characteristic curve (AUC) and Area Under the precision-recall curve (AUPRC). For the most part, we determined that our ensemble FSTs do not affect classification performance but are beneficial because feature reduction eases computational burden and provides insight through improved data visualization.

DETECTION OF BLOOD VESSELS IN RETINAL IMAGES

2010 ◽  
Vol 10 (01) ◽  
pp. 57-72 ◽  
Author(s):  
HEJER JLASSI ◽  
KAMEL HAMROUNI
Keyword(s):  
Blood Vessels ◽  
Anisotropic Diffusion ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Retinal Images ◽  
Linear Filter ◽  
Vascular Tree ◽  
Morphological Reconstruction ◽  
Processing Steps ◽  
Better Than

This paper presents a method to segment blood vessels in retinal images. It is based on mathematical morphology and the anisotropic diffusion and is composed of four steps: image processing by using linear filter and morphological ones, details extraction by using top-hat transform, morphological reconstruction of vascular tree and post processing steps using anisotropic diffusion. Our method is tested on red-free retinal images, taken from two public database. Our results on both public databases were comparable in performance with other authors. The method achieves a good result by mean of the "receiver operating characteristic curve" (ROC). The results show that our method is significantly better than other rule-based methods.

scholarly journals Accuracy of new Corvis ST parameters for detecting subclinical and clinical keratoconus eyes in a Chinese population

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shengwei Ren ◽  
Liyan Xu ◽  
Qi Fan ◽  
Yuwei Gu ◽  
Kaili Yang
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Chinese Population ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Youden Index ◽  
Diagnostic Efficiency ◽  
Stiffness Parameter ◽  
Diagnostic Ability ◽  
Corvis St ◽  
Operating Characteristic Curve

AbstractThis study aimed to compare the values of new corneal visualization Scheimpflug technology (Corvis ST) parameters in normal, subclinical keratoconus (SKC) and keratoconus (KC) eyes, and evaluate the diagnostic ability to distinguish SKC and KC eyes from normal eyes. One-hundred normal, 100 SKC and 100 KC eyes were included in the study. Corvis ST parameters containing dynamic corneal response parameters were measured by one ophthalmologist. The receiver operating characteristic curve was used to evaluate the diagnostic ability of new Corvis ST parameters. The new Corvis ST parameters in KC eyes were different from those in the control and SKC eyes after adjusting for IOP and CCT, and stiffness parameter at the first applanation (SP-A1) and Corvis biomechanical index (CBI) were significantly different between the control and SKC eyes (all P < 0.05). The parameter with the highest diagnostic efficiency was SP-A1 (Youden index = 0.40, AUC = 0.753), followed by CBI (Youden index = 0.38, AUC = 0.703), and Integrated Radius (Youden index = 0.33, AUC = 0.668) in diagnosing SKC from control eyes. New Corvis ST parameters in SKC eyes were significantly different from normal control and KC eyes, and could be considered to distinguish SKC and KC eyes from normal eyes.

scholarly journals Diagnostic sensitivity of arginase, alpha-1 antitrypsin and alpha-fetoprotein in hepatitis patients

2021 ◽  
Author(s):  
Hala A. Abdelgaid ◽  
Mohamed A. El-Desouky ◽  
Khairy A. Ibrahim ◽  
Abdelgawad A. Fahmi ◽  
Ahmed I. Amin
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
High Sensitivity ◽  
Alpha Fetoprotein ◽  
Diagnostic Sensitivity ◽  
Significant Elevation ◽  
Diagnostic Ability ◽  
Alpha 1 Antitrypsin ◽  
Linear Regressions

Chronic hepatitis C virus (HCV) and hepatocellular carcinoma (HCC) are common liver diseases that lead to death in Egypt, especially in men. The current study aimed to evaluate the diagnostic sensitivity of arginase (ARG) activity, alpha-1 antitrypsin (AAT), and alpha-fetoprotein (AFP) in the sera of patients with HCV (with & without viremia) and HCC. A total of 190 men classified as 40 healthy used as control (G1), 100 infected with HCV (subdivided into 50 with viremia (G2) and 50 without viremia (G3), and 50 with HCC (G4). The activity of ARG significantly decreased in HCV and HCC groups along with significant elevation in the level of AAT and AFP as compared with the control. Although a non-significant variation was scored in AST/ALT, significant differences were observed among AST/ARG and ARG/ALT in the pathogenic groups as compared with the healthy group. Moreover, significant variations in ARG, AAT, AFP, AST/ARG, and ARG/ALT were observed between viremia and non-viremia. Although AFP scored significant change among the viremia and HCC, the rest parameters scored non-significant changes between both groups. Furthermore, a receiver operating characteristic curve (ROC) showed the diagnostic ability for the selected parameters with high sensitivity and multiple linear regressions exhibited good associations between those parameters. These findings suggest the using possibility of ARG, AAT, and AFP in the diagnosis and/or follow-up of patients with HCV or HCC.

scholarly journals Conventional Laboratory Blood Indicators Are Valuable for Early Diagnosis of Colorectal Cancer

2021 ◽  
Author(s):  
Xia Gan ◽  
Zhi-Yong Chen ◽  
Zi-Hua Li ◽  
Jian-Ming Zhou ◽  
Ying Sun ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Early Diagnosis ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
Diagnostic Value ◽  
Imaging Data ◽  
Operating Characteristic Curve ◽  
Better Than

Abstract Objective: Some conventional laboratory indicators have been found to be of value for the diagnosis of colorectal cancer (CRC). The present study aimed to systematically analyze the diagnostic value of conventional laboratory blood indicators for CRC, especially for early CRC. Methods: A total of 505 patients with CRC (n=210), colorectal adenoma (CRA) (n=167) or polyp (CRP) (n=128) were retrospectively collected. Clinical, laboratory and imaging data available before treatment were extracted. The diagnostic performances of laboratory blood indicators for discriminating total and early CRCs from CRA and CRP (CRA&P) were evaluated.Results: Fifty-three of 76 (69.7%) laboratory blood indicators were significant for discriminating CRC from CRA&P with areas under the receiver operating characteristic curve (AUC) ranging within 0.554-0.819, of these indicators, 17 had AUC > 0.7, three had AUC > 0.8, and five had AUCs greater than that for carcinoembryonic antigen (CEA). Fifteen indicators had overall sensitivities comparable to CEA for the diagnosis of CRC (35.7-55.4% vs. 47.7%, all P>0.05) at a specificity of 90%, and they were not or weakly correlated with CEA (absolute r = 0.058-0.333). For differentiating early CRC (TNM stage I+II, n=102) from CRA&P, the sensitivities for the 15 indicators ranged within 30.4%-55.5% at a specificity of 90% and similar to stage III+IV CRC.Conclusion: Conventional laboratory blood indicators are valuable for early CRC diagnosis, and are comparable to or better than CEA.

scholarly journals Cerebellar Arteriovenous Malformations

Neurosurgery ◽  
2012 ◽  
Vol 71 (6) ◽  
pp. 1111-1124 ◽  
Author(s):  
◽  
Ana Rodríguez-Hernández ◽  
Helen Kim ◽  
Tony Pourmohamad ◽  
William L. Young ◽  
...  
Keyword(s):  
Arteriovenous Malformations ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Characteristic Curve ◽  
Venous Drainage ◽  
Martin Grade ◽  
Operating Characteristic Curve ◽  
Cerebral Avms ◽  
Cerebellar Anatomy ◽  
Better Than

ABSTRACT BACKGROUND: Anatomic diversity among cerebellar arteriovenous malformations (AVMs) calls for a classification that is intuitive and surgically informative. Selection tools like the Spetzler-Martin grading system are designed to work best with cerebral AVMs but have shortcomings with cerebellar AVMs. OBJECTIVE: To define subtypes of cerebellar AVMs that clarify anatomy and surgical management, to determine results according to subtypes, and to compare predictive accuracies of the Spetzler-Martin and supplementary systems. METHODS: From a consecutive surgical series of 500 patients, 60 had cerebellar AVMs, 39 had brainstem AVMs and were excluded, and 401 had cerebral AVMs. RESULTS: Cerebellar AVM subtypes were as follows: 18 vermian, 13 suboccipital, 12 tentorial, 12 petrosal, and 5 tonsillar. Patients with tonsillar and tentorial AVMs fared best. Cerebellar AVMs presented with hemorrhage more than cerebral AVMs (P &lt; .001). Cerebellar AVMs were more likely to drain deep (P = .04) and less likely to be eloquent (P &lt; .001). The predictive accuracy of the supplementary grade was better than that of the Spetzler-Martin grade with cerebellar AVMs (areas under the receiver-operating characteristic curve, 0.74 and 0.59, respectively). The predictive accuracy of the supplementary system was consistent for cerebral and cerebellar AVMs, whereas that of the Spetzler-Martin system was greater with cerebral AVMs. CONCLUSION: Patients with cerebellar AVMs present with hemorrhage more often than patients with cerebral AVMs, justifying an aggressive treatment posture. The supplementary system is better than the Spetzler-Martin system at predicting outcomes after cerebellar AVM resection. Key components of the Spetzler-Martin system such as venous drainage and eloquence are distorted by cerebellar anatomy in ways that components of the supplementary system are not.

Effect of Implementing Quantitative Blood Loss Assessment at the Time of Delivery

2019 ◽  
Vol 36 (13) ◽  
pp. 1332-1336
Author(s):  
Elizabeth Coviello ◽  
Sara Iqbal ◽  
Tetsuya Kawakita ◽  
Rebecca Chornock ◽  
Megan Cheney ◽  
...  
Keyword(s):  
Blood Transfusion ◽  
Blood Loss ◽  
Chart Review ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Vital Signs ◽  
Retrospective Chart Review ◽  
Loss Assessment ◽  
Estimated Blood Loss ◽  
Better Than

Objective To evaluate the ability of estimated blood loss (EBL) and quantitative blood loss (qBL) to predict need for blood transfusion in women with postpartum hemorrhage (PPH). Study Design This is a retrospective chart review that identified women with PPH (>1,000 mL for vaginal or cesarean delivery) between September 2014 and August 2015, reported by EBL (n = 92), and October 2015 and September 2016, reported by qBL (n = 374). The primary metric was the area under the receiver-operating characteristic curve for blood transfusion. Results The rate of PPH by EBL and qBL was 2.8 and 10.8%, respectively (p < 0.01). The rate of transfusion for women meeting criteria for PPH by EBL and QBL were 2% (66/3,307) and 2.7% (93/3,453), respectively (p = 0.06). Postpartum transfusion was predicted by an EBL of 1,450 mL with AUC 0.826 and qBL 1,519 mL with AUC 0.764, for all modes of delivery. Postpartum vital signs and change in pre- and postdelivery hematocrit were poor predictors for transfusion. Conclusion The rates of PPH increased with the implementation of qBL. Overall, qBL did not perform better than EBL in predicting the need for blood transfusion.

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