Key result
Model combining CRP, age, and lymphocyte percentage rules in perforated appendicitis with ~95% specificity.
Why the study?
Accurately predicting perforated appendicitis preoperatively remains challenging.
Does a predictive model incorporating CRP, age, and lymphocyte percentage accurately identify perforated appendicitis preoperatively in patients with acute appendicitis?
Cohort (n=770)
Does a predictive model incorporating CRP, age, and lymphocyte percentage accurately identify perforated appendicitis preoperatively in patients with acute appendicitis?
Effect estimate: AUC 0.78
A predictive model using CRP, age, and lymphocyte percentage provides a highly specific tool for ruling in perforated appendicitis preoperatively, which may aid in prioritizing surgical urgency.
May aid prioritization of urgent surgery when positive; extends biomarker models but leaves open prospective validation before adoption.
BackgroundAccurately predicting perforated appendicitis (PA) preoperatively remains challenging.MethodsWe retrospectively studied appendectomy patients with histopathologically confirmed acute appendicitis (2022-2023) to identify predictors of perforation. The primary outcome was histopathologically confirmed perforated appendicitis. Bayesian univariate analysis and Bayesian logistic regression were performed to estimate risk probabilities, with frequentist analyses conducted for confirmation. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity.ResultsOf 770 patients with histologically confirmed appendicitis, 155 (20%) had PA. Bayesian univariate analysis demonstrated decisive evidence (BF₁₀ > 100) for several predictors, with C-reactive protein (CRP) (BF₁₀ = 251 079), age (BF₁₀ = 828), and lymphocyte percentage (BF₁₀ = 352) showing the strongest associations. Multivariate Bayesian modeling identified a parsimonious three-variable model comprising CRP, age, and lymphocyte percentage. This model demonstrated good discrimination (AUC 0.78) with high specificity (95.4%) and modest sensitivity (29%). Frequentist analyses confirmed these findings.ConclusionA predictive model incorporating CRP, age, and lymphocyte percentage provides a highly specific tool for ruling in perforated appendicitis. This approach may aid in prioritizing surgical urgency and optimizing perioperative management. Prospective validation is warranted.
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Akpinar et al. (2026) conducted a cohort in Acute appendicitis (n=770). Predictive model (CRP, age, lymphocyte percentage) was evaluated on Histopathologically confirmed perforated appendicitis (AUC 0.78). A predictive model incorporating CRP, age, and lymphocyte percentage demonstrated good discrimination (AUC 0.78) and high specificity (95.4%) for ruling in perforated appendicitis.
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