When Time is of the Essence: Preliminary Findings for a Quick Administration of the Dot Counting Test

2019 ◽  
Author(s):  
K Chase Bailey ◽  
Troy A Webber ◽  
Jacob I Phillips ◽  
Lindsay D R Kraemer ◽  
Janice C Marceaux ◽  
...  
Keyword(s):  
Classification Accuracy ◽  
Clinical Sample ◽  
Characteristic Curve ◽  
Cross Sectional Study ◽  
Receiver Operator Characteristic Curve ◽  
Performance Validity ◽  
Free Standing ◽  
Cross Sectional ◽  
Validity Measures ◽  
Sensitivity Specificity

Abstract Objective Performance validity research has emphasized the need for briefer measures and, more recently, abbreviated versions of established free-standing tests to minimize neuropsychological evaluation costs/time burden. This study examined the accuracy of multiple abbreviated versions of the Dot Counting Test (“quick” DCT) for detecting invalid performance in isolation and in combination with the Test of Memory Malingering Trial 1 (TOMMT1). Method Data from a mixed clinical sample of 107 veterans (80 valid/27 invalid per independent validity measures and structured criteria) were included in this cross-sectional study; 47% of valid participants were cognitively impaired. Sensitivities/specificities of various 6- and 4-card DCT combinations were calculated and compared to the full, 12-card DCT. Combined models with the most accurate 6- and 4-card combinations and TOMMT1 were then examined. Results Receiver operator characteristic curve analyses were significant for all 6- and 4-card DCT combinations with areas under the curve of .868–.897. The best 6-card combination (cards, 1-3-5-8-11-12) had 56% sensitivity/90% specificity (E-score cut-off, ≥14.5), and the best 4-card combination (cards, 3-4-8-11) had 63% sensitivity/94% specificity (cut-off, ≥16.75). The full DCT had 70% sensitivity/90% specificity (cut-off, ≥16.00). Logistic regression revealed 95% classification accuracy when 6-card or 4-card “quick” combinations were combined with TOMMT1, with the DCT combinations and TOMMT1 both emerging as significant predictors. Conclusions Abbreviated DCT versions utilizing 6- and 4-card combinations yielded comparable sensitivity/specificity as the full DCT. When these “quick” DCT combinations were further combined with an abbreviated memory-based performance validity test (i.e., TOMMT1), overall classification accuracy for identifying invalid performance was 95%.

scholarly journals A-227 Boston Naming Test as an Embedded Performance Validity Test: A Replication Study

2020 ◽  
Vol 35 (6) ◽  
pp. 1022-1022
Author(s):  
Abramson D ◽  
White D ◽  
Resch Z ◽  
Ovsiew G ◽  
Soble J
Keyword(s):  
Characteristic Curve ◽  
Area Under The Curve ◽  
High Specificity ◽  
Cross Sectional Study ◽  
Receiver Operator Characteristic Curve ◽  
Performance Validity ◽  
Boston Naming Test ◽  
Cross Sectional ◽  
Validity Test ◽  
Naming Test

Abstract Objective The Boston Naming Test (BNT) has recently been proposed as an embedded performance validity test (PVT) with high specificity/low sensitivity; however, this has not been replicated. This study therefore aimed to cross-validate findings in a mixed clinical neuropsychiatric sample. Method This cross-sectional study of 136 primary monolingual English-speaking patients who completed the BNT during outpatient evaluation was 57% female/43% male, 38% Caucasian, 39% African American, 16% Hispanic, and 6% Asian with mean age of 47.7 years (SD = 16.6) and mean education of 14.0 years (SD = 2.7). In total, 109/136 (80%) were classified as valid and 27/136 (20%) as invalid based on 4 independent criterion PVTs. Results Respective mean BNT raw/T-scores were 49.5 (SD = 9.2)/45.3 (SD = 10.9) for the valid group and 45.8 (SD = 8.2)/41.1 (SD = 7.8) for the invalid group. Analyses of variance fell just above significance for both BNT raw F(1, 134) = 3.75, p = .05 and T-scores F(1, 134) = 3.55, p = .06. Receiver operator characteristic curve analysis for the raw score was significant, with an area under the curve (AUC) of .67 (p < .01) and an optimal cutoff of ≤ 35 (4% specificity/90% sensitivity). BNT raw scores remained significant after removing bilingual participants, (AUC = .68; p < .01), with identical psychometric properties. In contrast, analysis of BNT T-scores (AUC = .61; p = .08) were nonsignificant. Conclusions Overall, results showed that the BNT cannot psychometrically distinguish valid versus invalid performance and therefore has questionable utility as a PVT in a mixed clinical setting. Findings contribute to a growing literature base cautioning against the indiscriminate use of measures of actual cognitive ability as validity indicators, particularly in populations with cognitive impairment.

scholarly journals A-233 Incremental Utility of the Montreal Cognitive Assessment (MoCA) Memory Index Score (MIS) for Detection of Cognitive Impairment

2020 ◽  
Vol 35 (6) ◽  
pp. 1028-1028
Author(s):  
Bain K ◽  
Marceaux J ◽  
Kruzelock A
Keyword(s):  
Cognitive Impairment ◽  
Classification Accuracy ◽  
Clinical Sample ◽  
Cross Sectional Study ◽  
Index Score ◽  
Neurocognitive Disorder ◽  
Chi Square ◽  
Cross Sectional ◽  
Neuropsychological Evaluations ◽  
Chi Square Analysis

Abstract Objective To investigate the incremental utility of the optional MoCA Memory Index Score (MIS) for detection of cognitive impairment. Method This cross-sectional study utilized data collected from a mixed clinical sample of 153 veterans referred for clinical neuropsychological evaluations at a VA hospital. The sample was 87% male (n = 133), with an average age of 63.23 years (range 20–91) and average education level of 13.6 years (range 6–20). All participants completed the MoCA, including the MIS items. Participants meeting criteria for mild (n = 66) or major neurocognitive disorder (n = 24) were classified as cognitively impaired (CI). Sixty-three participants who did not meet criteria for a neurocognitive disorder were classified as having no cognitive impairment (NCI). Chi square analysis and logistic regression were utilized to determine the sensitivity of the MoCA total score for detection of cognitive impairment, and to determine whether the MIS significantly improved classification accuracy. Results The MoCA total score was a significant predictor of cognitive impairment status (X2 = 40.92, p < .001), with 73% sensitivity, 67% specificity, and 71% classification accuracy. When the MIS was added, the model retained significance (X2 = 41.13, p < .001), but overall sensitivity, specificity, and classification accuracy were unchanged; MIS was not a significant predictor in the combined model. Conclusions The optional MIS score did not significantly improve the sensitivity of the MoCA for detection of cognitive impairment.

Ratio of height to thyromental distance: a comparison with Mallampati and Upper lip Bite test for predicting difficult intubation in Pakistani population

2021 ◽  
pp. 1-15
Author(s):  
Saman Tauheed Ali ◽  
Khalid Samad ◽  
Syed Amir Raza ◽  
Muhammad Qamarul Hoda
Keyword(s):  
Predictive Value ◽  
Characteristic Curve ◽  
Cross Sectional Study ◽  
Difficult Laryngoscopy ◽  
University Hospital ◽  
Upper Lip ◽  
Cross Sectional ◽  
Elective Surgical Procedures ◽  
Lehane Grade ◽  
Sensitivity Specificity

Objectives: We conducted this study to compare the accuracy of three diagnostic tests; ratio of height to thyromental distance (RHTMD), Modified Mallampati Test (MMT) and Upper Lip Bite Test (ULBT) in predicting difficult laryngoscopy using Cormack and Lehane grade as gold standard.Methods: This study was conducted in Aga Khan University Hospital, Karachi. Based on calculated sample size, 383 patients who required endotracheal intubation for elective surgical procedures were enrolled with consecutive sampling techniques during August 2014 to August 2015 for this cross-sectional study. Primary investigator used RHTMD, ULBT, and MMT for assessing the airway and correlated with laryngoscopic view.Results: A total of 383 patients were incorporated in this research, out of which 59(15.4%) classified as difficult laryngoscopy based on Cormack and Lehane (CL) grading. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of RHTMD (84.7%, 90.1%, 60.9%, 97%, 89.3%) and ULBT (83.1%, 89.2%, 58.3%, 96.7%, 88.3%) values were highest as compared to MMT (30.5%, 84.3%, 26.1%, 86.9%, 79.9%). The area under a receiver-operating characteristic curve (AUC of ROC curve) for ULBT and RHTMD was significantly more than for MMT (P<0.01). RHTMD and ULBT both are acceptable alternatives for prediction of difficult laryngoscopy as a simple, single bed-side test. Continuous...

scholarly journals Corneal Segmentation Analysis Increases Glaucoma Diagnostic Ability of Optic Nerve Head Examination, Heidelberg Retina Tomograph’s Moorfield’s Regression Analysis, and Glaucoma Probability Score

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
F. Saenz-Frances ◽  
L. Jañez ◽  
C. Berrozpe-Villabona ◽  
L. Borrego-Sanz ◽  
L. Morales-Fernández ◽  
...  
Keyword(s):  
Optic Nerve ◽  
Optic Nerve Head ◽  
Open Angle Glaucoma ◽  
Characteristic Curve ◽  
Corneal Thickness ◽  
Cross Sectional Study ◽  
Receiver Operator Characteristic Curve ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Segmentation Analysis

Purpose. To study whether a corneal thickness segmentation model, consisting in a central circular zone of 1 mm radius centered at the corneal apex (zone I) and five concentric rings of 1 mm width (moving outwards: zones II to VI), could boost the diagnostic accuracy of Heidelberg Retina Tomograph’s (HRT’s) MRA and GPS.Material and Methods. Cross-sectional study. 121 healthy volunteers and 125 patients with primary open-angle glaucoma. Six binary multivariate logistic regression models were constructed (MOD-A1, MOD-A2, MOD-B1, MOD-B2, MOD-C1, and MOD-C2). The dependent variable was the presence of glaucoma. In MOD-A1, the predictor was the result (presence of glaucoma) of the analysis of the stereophotography of the optic nerve head (ONH). In MOD-B1 and MOD-C1, the predictor was the result of the MRA and GPS, respectively. In MOD-B2 and MOD-C2, the predictors were the same along with corneal variables: central, overall, and zones I to VI thicknesses. This scheme was reproduced for model MOD-A2 (stereophotography along with corneal variables). Models were compared using the area under the receiver operator characteristic curve (AUC).Results. MOD-A1-AUC: 0.771; MOD-A2-AUC: 0.88; MOD-B1-AUC: 0.736; MOD-B2-AUC: 0.845; MOD-C1-AUC: 0.712; MOD-C2-AUC: 0.838.Conclusion. Corneal thickness variables enhance ONH assessment and HRT’s MRA and GPS diagnostic capacity.

Comparing the accuracy of lay diagnosis of childhood malaria and pneumonia with that of the revised IMCI guidelines in Nigeria

2020 ◽  
Author(s):  
K O Elimian ◽  
P R Myles ◽  
R Phalkey ◽  
A Sadoh ◽  
C Pritchard
Keyword(s):  
Health Workers ◽  
Characteristic Curve ◽  
Cross Sectional Study ◽  
Childhood Diseases ◽  
Cross Sectional ◽  
Predictive Values ◽  
Benin City ◽  
Sensitivity Specificity ◽  
Childhood Malaria ◽  
Pneumonia Diagnosis

Abstract Background Improving caregivers’ recognition of childhood malaria and pneumonia is crucial to early treatment and improving outcomes. The objective of this study was to assess the accuracy and reliability of caregivers’ recognition of malaria and pneumonia (lay diagnosis) as compared to the revised IMCI guidelines. Methods A cross-sectional study design was used to recruit 903 children aged 2–59 months who were assessed for malaria and pneumonia by health workers at five primary healthcare centres in Benin City, Nigeria. Accuracy of lay diagnosis as compared to the revised IMCI guidelines was assessed using sensitivity, specificity, positive and negative predictive values and area under the receiver operating characteristic curve (AUROC) values. Results The accuracy of caregivers’ ability to recognise malaria (AUROC: 0.60; 95% CI: 0.57–0.64) and pneumonia (AUROC: 0.54; 95% CI: 0.50–0.58) was, respectively, moderate and poor as compared to the IMCI guidelines. Caregivers were better able to identify children without than those with malaria and pneumonia. Agreement between caregivers and the IMCI guidelines for malaria and pneumonia diagnosis was poor (k = 0.14, 95% CI: 0.09–0.19; P = 0.0001). Conclusion Caregivers’ ability to recognise these childhood diseases as compared to the IMCI guidelines was poor overall, which was partly due to the approach used to ascertain lay diagnosis.

scholarly journals Automated detection of early-stage ROP using a deep convolutional neural network

2020 ◽  
pp. bjophthalmol-2020-316526
Author(s):  
Yo-Ping Huang ◽  
Haobijam Basanta ◽  
Eugene Yu-Chuan Kang ◽  
Kuan-Jen Chen ◽  
Yih-Shiou Hwang ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Early Stage ◽  
Characteristic Curve ◽  
Cross Sectional Study ◽  
Deep Convolutional Neural Network ◽  
Cross Sectional ◽  
Early Stages ◽  
Sensitivity Specificity ◽  
Stage 1

Background/AimTo automatically detect and classify the early stages of retinopathy of prematurity (ROP) using a deep convolutional neural network (CNN).MethodsThis retrospective cross-sectional study was conducted in a referral medical centre in Taiwan. Only premature infants with no ROP, stage 1 ROP or stage 2 ROP were enrolled. Overall, 11 372 retinal fundus images were compiled and split into 10 235 images (90%) for training, 1137 (10%) for validation and 244 for testing. A deep CNN was implemented to classify images according to the ROP stage. Data were collected from December 17, 2013 to May 24, 2019 and analysed from December 2018 to January 2020. The metrics of sensitivity, specificity and area under the receiver operating characteristic curve were adopted to evaluate the performance of the algorithm relative to the reference standard diagnosis.ResultsThe model was trained using fivefold cross-validation, yielding an average accuracy of 99.93%±0.03 during training and 92.23%±1.39 during testing. The sensitivity and specificity scores of the model were 96.14%±0.87 and 95.95%±0.48, 91.82%±2.03 and 94.50%±0.71, and 89.81%±1.82 and 98.99%±0.40 when predicting no ROP versus ROP, stage 1 ROP versus no ROP and stage 2 ROP, and stage 2 ROP versus no ROP and stage 1 ROP, respectively.ConclusionsThe proposed system can accurately differentiate among ROP early stages and has the potential to help ophthalmologists classify ROP at an early stage.

scholarly journals Association between Hemoglobin Glycation Index and NAFLD in Chinese Nondiabetic Individuals

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Di-Shuang Hu ◽  
Sheng-Hao Zhu ◽  
Xu Li ◽  
Qin-Fen Chen ◽  
Chun-Jing Lin ◽  
...  
Keyword(s):  
Risk Score ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Positive Association ◽  
Cross Sectional Study ◽  
Receiver Operator Characteristic Curve ◽  
Abdominal Ultrasonography ◽  
Cross Sectional ◽  
Nonalcoholic Fatty Liver ◽  
Hemoglobin Glycation

Purpose. Limited studies have preliminarily identified a positive association between nonalcoholic fatty liver disease (NAFLD) and hemoglobin glycation index (HGI). However, this association has not been fully established. We aim to investigate the association between NAFLD and HGI in Chinese nondiabetic individuals and to construct a risk score based on HGI to predict a person’s risk of NAFLD. Methods. After strict exclusion criteria, 5,903 individuals were included in this retrospective cross-sectional study. We randomly selected 1,967 subjects in the enrollment to obtain an equation of linear regression, which was used to calculate predicted HbA1c and drive HGI. The other subjects were classified into four categories according to HGI level (≤−0.22, −0.21∼0.02, 0.03∼0.28, and ≥0.29). All subjects retrospectively reviewed the baseline characteristics, laboratory examinations, and abdominal ultrasonography. Results. The prevalence of NAFLD in this population was 20.7%, which increases along with the growth of HGI levels (P<0.001). Adjusted to multiple factors, this trend still remained significant (OR: 1.172 (95% CI, 1.074–1.279)). The combined NAFLD risk score based on HGI resulted in an area under the receiver operator characteristic curve (AUROC) of 0.85 provided sensitivity, specificity, positive predictive value, and a negative predictive value for NAFLD of 84.4%, 71.3%, 65.0%, and 88.0%, respectively. Conclusions. NAFLD is independently associated with HGI levels in Chinese nondiabetic individuals. And, NAFLD risk score may be used as one of the risk predictors of NAFLD in nondiabetic population.

scholarly journals Revising BMI Cut-Off Points for Obesity in a Weight Management Setting in Lebanon

2020 ◽  
Vol 17 (11) ◽  
pp. 3832
Author(s):  
Leila Itani ◽  
Dima Kreidieh ◽  
Dana El Masri ◽  
Hana Tannir ◽  
Leila Chehade ◽  
...  
Keyword(s):  
Weight Management ◽  
Clinical Sample ◽  
Characteristic Curve ◽  
Cross Sectional Study ◽  
Normal Weight ◽  
World Health ◽  
Fat Percentage ◽  
Cross Sectional ◽  
Total Body ◽  
Health Organization

Obesity is defined by the World Health Organization (WHO) as a body mass index (BMI) ≥ 30 Kg/m2. This study aimed to test the validity of this BMI cut-off point for adiposity in a weight management clinical setting in Lebanon. This cross-sectional study of 442 adults of mixed gender, categorized by the WHO BMI classification, included: 66 individuals of normal weight, 110 who were overweight and 266 with obesity. The clinical sample was referred to the Outpatient Clinic in the Department of Nutrition and Dietetics at Beirut Arab University (BAU) in Lebanon. All participants underwent anthropometric evaluation. The gold standard for defining obesity was based on the National Institutes of Health (NIH)/WHO guidelines for total body fat percentage (BF%). The best sensitivity and specificity were attained to predict obesity, according to the receiver operating characteristic curve (ROC) analysis. The BMI cut-off point for predicting obesity in the clinical sample was nearly 31.5 Kg/m2, and more than 90% of individuals with obesity and cardiometabolic disease were above this cut-off point. In conclusion, this new BMI cut-off point, an obesity definition higher than suggested in Western populations, was demonstrated to have clinical usefulness. Obesity guidelines in Lebanon, therefore, need revising.

Validation of the Advanced Clinical Solutions Word Choice Test (WCT) in a Mixed Clinical Sample: Establishing Classification Accuracy, Sensitivity/Specificity, and Cutoff Scores

Assessment ◽  
2017 ◽  
Vol 26 (7) ◽  
pp. 1320-1328 ◽  
Author(s):  
Kathleen M. Bain ◽  
Jason R. Soble
Keyword(s):  
Classification Accuracy ◽  
Clinical Sample ◽  
Choice Test ◽  
Word Choice ◽  
Performance Validity ◽  
Cut Scores ◽  
Word Memory Test ◽  
Word Memory ◽  
Good Classification ◽  
Sensitivity Specificity

This study examined the Word Choice Test’s (WCT) utility as a performance validity test in a mixed clinical sample of veterans referred for neuropsychological evaluation. Participants completed Green’s Word Memory Test (WMT), WCT, and Test of Memory Malingering (TOMM) Trial 1. Using the WMT as the criterion for valid performance, logistic regressions examined the WCT and TOMM’s classification accuracy for those with and without cognitive impairment (CI). Receiver operating characteristic curves were used to establish cut scores which maximized the sensitivity/specificity of each measure. In those without CI, both tests showed good classification accuracy (86.7% and 85.0%, respectively). Among those with CI, the TOMM retained good classification accuracy (82.3%), while the WCT’s decreased considerably (69.4%). Optimal WCT cut scores differed based on impairment status, with a higher sensitivity/specificity trade-off among those with CI. Successful performance on the WCT appeared to rely more heavily on cognitive processes unrelated to performance validity.

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