LAUSR

Abstract This study evaluated the diagnostic performance of a new clinical approach based on decision tree (DT) analysis in adult patients with equivocal computed tomography (CT) findings of acute appendicitis (AA) compared with previous scoring systems. This retrospective study of 244 adult patients with equivocal CT findings included appendicitis (AG, n = 80) and non-appendicitis (NAG, n = 164) groups. The chi-squared automatic interaction detection algorithm was for AA prediction. A receiver operating characteristic curve analysis and area under the curve (AUC) were used to compare the DT analysis with Alvarado, Eskelinen score, and adult appendicitis scores (AAS). The following factors were selected for AA prediction: rebound tenderness severity, migration, urinalysis, symptom duration, leukocytosis, neutrophil count, and C-reactive protein levels. The DT comprised 11 final nodes with the following AA probabilities: node 1, 100% (16/16); node 2, 90% (9/10); node 3, 80% (8/10); node 4, 60.9% (14/23); node 5, 50% (3/6); node 6, 43.8% (7/16); node 7, 22.6% (12/53); node 8, 13% (10/77); node 9, 5.6% (1/18); node 10, 0% (0/12); and node 11, 0% (0/3). The AUC of the DT was higher (0.850 [95% confidence interval {CI}; 0.799–0.893]) than the Alvarado score (0.695 [95% CI; 0.633–0.752]), AAS (0.749 [95% CI; 0.690–0.802]), and the Eskelinen score (0.715 [95% CI; 0.654–0.770]). The results were statistically significant when compared with the AUCs of the Alvarado score, Eskelinen score, and AAS (P < .001, P < .001, P = .003, respectively). The DT-based approach facilitated AA diagnosis and determination of clinical status in patients with equivocal preoperative CT findings and ambiguous results.