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Browsing by Subject "Diagnostic accuracy"
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Item Estimating the Impact of Verification Bias on Celiac Disease Testing(Wolters Kluwer, 2021) Hujoel, Isabel A.; Jansson-Knodell, Claire L.; Hujoel, Philippe P.; Hujoel, Margaux L.A.; Choung, Rok Seon; Murray, Joseph A.; Rubio-Tapia, Alberto; Medicine, School of MedicineGoal: The goal of this study was to estimate the impact of verification bias on the diagnostic accuracy of immunoglobulin A tissue transglutaminase (IgA tTG) in detecting celiac disease as reported by an authoritative meta-analysis, the 2016 Comparative Effectiveness Review (CER). Background: Verification bias is introduced to diagnostic accuracy studies when screening test results impact the decision to verify disease status. Materials and methods: We adjusted the sensitivity and specificity of IgA tTG reported by the 2016 CER with the proportion of IgA tTG positive and negative individuals who are referred for confirmatory small bowel biopsy. We performed a systematic review from January 1, 2007, to July 19, 2017, to determine these referral rates. Results: The systematic review identified 793 articles of which 9 met inclusion criteria (n=36,477). Overall, 3.6% [95% confidence interval (CI): 1.1%-10.9%] of IgA tTG negative and 79.2.2% (95% CI: 65.0%-88.7%) of IgA tTG positive individuals were referred for biopsy. Adjusting for these referral rates the 2016 CER reported sensitivity of IgA tTG dropped from 92.6% (95% CI: 90.2%-94.5%) to 57.1% (95% CI: 35.4%-76.4%) and the specificity increased from 97.6% (95% CI: 96.3%-98.5%) to 99.6% (95% CI: 98.4%-99.9%). Conclusions: The CER may have largely overestimated the sensitivity of IgA tTG due to a failure to account for verification bias. These findings suggest caution in the interpretation of a negative IgA tTG to rule out celiac disease in clinical practice. More broadly, they highlight the impact of verification bias on diagnostic accuracy estimates and suggest that studies at risk for this bias be excluded from systematic reviews.Item King-Devick Sensitivity and Specificity to Concussion in Collegiate Athletes(Allen Press, 2023) Le, Rachel Khinh; Ortega, Justus; Chrisman, Sara P.; Kontos, Anthony P.; Buckley, Thomas A.; Kaminski, Thomas W.; Meyer, Briana P.; Clugston, James R.; Goldman, Joshua T.; McAllister, Thomas; McCrea, Michael; Broglio, Steven P.; Schmidt, Julianne D.; Psychiatry, School of MedicineContext: The King-Devick (K-D) test is used to identify oculomotor impairment after concussion. However, the diagnostic accuracy of the K-D test over time has not been evaluated. Objectives: To (1) examine the sensitivity and specificity of the K-D test at 0 to 6 hours postinjury, 24 to 48 hours postinjury, the beginning of a return-to-play (RTP) protocol (asymptomatic), unrestricted RTP, and 6 months postconcussion and (2) compare outcomes between athletes with and those without concussion across confounding factors (sex, age, sport contact level, academic year, learning disorder, attention-deficit/hyperactivity disorder, migraine history, concussion history, and test administration mode). Design: Retrospective, cross-sectional design. Setting: Multiple institutions in the Concussion Assessment, Research and Education Consortium. Patients or other participants: A total of 320 athletes with a concussion (162 men, 158 women; age = 19.80 ± 1.41 years) were compared with 1239 total collegiate athletes without a concussion (646 men, 593 women; age = 20.31 ± 1.18 years). Main outcome measure(s): We calculated the K-D test time difference (in seconds) by subtracting the baseline from the most recent time. Receiver operator characteristic (ROC) curve and area under the curve (AUC) analyses were used to determine the diagnostic accuracy across time points. We identified cutoff scores and corresponding specificity at both the 80% and 70% sensitivity levels. We repeated ROC with AUC analyses using confounding factors. Results: The K-D test predicted positive results at the 0- to 6-hour (AUC = 0.724, P < .001), 24- to 48-hour (AUC = 0.701, P < .001), RTP (AUC = 0.640, P < .001), and 6-month postconcussion (AUC = 0.615, P < .001) tim points but not at the asymptomatic time point (AUC = 0.513, P = .497). The 0- to 6-hour and 24- to 48-hour time points yielded 80% sensitivity cutoff scores of -2.6 and -3.2 seconds (ie, faster), respectively, but 46% and 41% specificity, respectively. The K-D test had a better AUC when administered using an iPad (AUC = 0.800, 95% CI = 0.747, 0.854) compared with the spiral-bound card system (AUC = 0.646, 95% CI = 0.600, 0.692; P < .001). Conclusions: The diagnostic accuracy of the K-D test was greatest at 0 to 6 hours and 24 to 48 hours postconcussion but declined across subsequent postconcussion time points. The AUCs did not differentiate between groups across confounding factors. Our negative cutoff scores indicated that practice effects contributed to improved performance, requiring athletes to outperform their baseline scores.