Bayesian comparative model of CT scan and ultrasonography in the assessment of acute appendicitis: results from the Acute Care Diagnostic Collaboration project

Abstract

The objective of this study was to develop a comparative diagnostic model for computed tomography (CT) and ultrasound (US) in the assessment of acute appendicitis using Alvarado risk score as a predictor of pretest probability and Bayesian statistical model as a tool to calculate posttest probabilities for both diagnostic test.Stratification was made by applying the Alvarado score for the prediction of acute appendicitis. Likelihood ratios were calculated using sensitivity and specificity of both CT and US from a Meta-analysis. Posttest probabilities were obtained after inserting Alvarado score and likelihood ratios into Bayesian nomogram. Absolute and relative gains were calculated. ANOVA was used to assess statistical association.4341 patients from 31 studies yielded a pooled sensitivity and specificity US of 83% (95% CI, 78%-87%) and 93% (95% CI, 90%-96%) and 94% (95% CI, 92%-95%) and 94% (95% CI, 94%-96%), respectively, for CT studies. Positive likelihood ratios (LR) for US were 12 and negative LR was 0.18; for CT +LR was 16 and –LR 0.06. Bayesian statistical modeling posttest probabilities for +LR and low Alvarado risk results yielded a posttest probability for US of 83.72% and 87.27% for CT, intermediate risk gave 95.88% and 96.88%, high risk 99.37% and 99.53 respectively. No statistical differences were found between Ultrasound and CT.This Bayesian analysis demonstrated slight superiority of CT scan over US low-risk patients, whereas no significant advantage was seen when evaluating intermediate and high risk patients. This study also favored elevated accuracy of the Alvarado score.