Predictive Factors of Acute Complicated Appendicitis: A Retrospective Study
Abstract Background: Complicated appendicitis is an indication for emergency surgery. Therefore, the predictive factors for appendicitis based on the patient background needs identification. Previously, factors predicting non-complicated and complicated appendicitis were reported. However, most of those reports were deemed unsuitable as a standard for emergency use, since those comprised too many items as predictors. We previously reported three items that preoperatively predicted complicated appendicitis (body temperature, C-reactive protein, and fluid retention around the appendix). In this study, we re-evaluated different cases to confirm the usefulness of these three items can for accurately predicting complicated appendicitis preoperatively. In addition, we compared the effectiveness of these predictor items with those reported by other researchers.Methods: We retrospectively evaluated 417 adult patients who underwent surgery for acute appendicitis between January 2013 and December 2019, and compared our predictor items with those used in previous reports on the preoperative prediction of complicated appendicitis (criteria A consisting of eight predictor items and criteria B consisting of seven predictor items). Results: The area under the receiver operating characteristic curve (AUC) for the sensitivity to diagnose complicated appendicitis according to our criteria, criteria A, and criteria B were 0.823, 0.839, and 0.856, respectively. The AUC of our criteria and criteria A were similar (P = 0.356); those of criteria A and B were also similar (P = 0.352). However, the AUC of criteria B was statistically higher than that of our criteria (P < 0.05).Conclusion: Diagnostic criteria B were statistically the best predictor items for characterizing complicated and uncomplicated appendicitis. However, like criteria A and B, the AUC of our criteria exceeded 0.8, and only involved three predictor items; therefore, they can be considered useful predictors.