Introduction While patients with acute uncomplicated appendicitis may be treated conservatively, those who suffer from complicated appendicitis require surgery. We describe a logistic regression equation to calculate the likelihood of acute uncomplicated appendicitis and complicated appendicitis in patients presenting to the emergency department with suspected acute appendicitis. Materials and methods A cohort of 895 patients who underwent appendicectomy were analysed retrospectively. Depending on the final histology, patients were divided into three groups; normal appendix, acute uncomplicated appendicitis and complicated appendicitis. Normal appendix was considered the reference category, while acute uncomplicated appendicitis and complicated appendicitis were the nominal categories. Multivariate and univariate regression models were undertaken to detect independent variables with significant odds ratio that can predict acute uncomplicated appendicitis and complicated appendicitis. Subsequently, a logistic regression equation was generated to produce the likelihood acute uncomplicated appendicitis and complicated appendicitis. Results Pathological diagnosis of normal appendix, acute uncomplicated appendicitis and complicated appendicitis was identified in 188 (21%), 525 (59%) and 182 patients (20%), respectively. The odds ratio from a univariate analysis to predict complicated appendicitis for age, female gender, log2 white cell count, log2 C-reactive protein and log2 bilirubin were 1.02 (95% confidence interval, CI, 1.01, 1.04), 2.37 (95% CI 1.51, 3.70), 9.74 (95% CI 5.41, 17.5), 1.57 (95% CI 1.40, 1.74), 2.08 (95% CI 1.56, 2.76), respectively. For the same variable, similar odds ratios were demonstrated in a multivariate analysis to predict complicated appendicitis and univariate and multivariate analysis to predict acute uncomplicated appendicitis. Conclusions The likelihood of acute uncomplicated appendicitis and complicated appendicitis can be calculated by using the reported predictive equations integrated into a web application at www.appendistat.com. This will enable clinicians to determine the probability of appendicitis and the need for urgent surgery in case of complicated appendicitis.
Application of logistic regression equation analysis using derivatives for optimal cutoff discriminative criterion estimation
