Learning curve and period of experience required for the competent diagnosis of acute appendicitis using abdominal computed tomography: a prospective observational study

Abstract

Objective To assess the learning curve of novice residents in diagnosing acute appendicitis using abdominal computed tomography (CT) scans. Methods This prospective observational study was conducted within a 4-month period from March 1 to June 30, 2015. After CT scans for right lower quadrant pain or similar acute abdomen were evaluated, postgraduate year 1 (PGY-1) residents completed an interpretation checklist. The primary outcome was evaluation of the learning curve for competent CT scan interpretation under suspicion of acute appendicitis. Secondary outcomes were cumulative numbers of accurate abdominal CT interpretations regardless of initial clinical impression and training period. Results PGY-1 residents recorded a total of 230 interpretation checklists. There were 53, 51, 46, 44, and 36 checklists recorded by individual residents and 92, 92, 91, 91, and 61 respective training days in the emergency department, excluding rotation periods in other departments. After 16 to 20 interpretations of abdominal CT scans performed under suspicion of acute appendicitis, the residents could diagnose acute appendicitis with more than 95% accuracy. Overall, the sensitivity and specificity for diagnosing acute appendicitis were 97% (95% confidence interval, 94 to 100) and 83% (95% confidence interval, 80 to 87), respectively. After 61 to 80 abdominal CT interpretations regardless of suspicion of acute appendicitis and after 41 to 50 days in training, PGY-1 emergency department residents could diagnose acute appendicitis with more than 95% accuracy. Conclusion PGY-1 residents require 16 to 20 checklist interpretations to acquire acceptable abdominal CT interpretation. After performing 61 to 80 CT scans regardless of suspicion of acute appendicitis, they could diagnose acute appendicitis with acceptable accuracy.

Keywords

• acute appendicitis
• computed tomography
• learning curve
• interpretation