Intra-abdominal pressure and procalcitonin for prognosis in patients with severe acute pancreatitis: An etiology-based analysis

Figure 4 Prediction model performance analysis. A: Receiver operating characteristic curves comparing prediction models. The machine learning-intra-abdominal pressure-procalcitonin (area under the curve = 0.837) outperformed single-marker models and the Acute Physiology and Chronic Health Evaluation II score (all P < 0.05); B: Decision curve analysis showed optimal clinical utility at thresholds of 0.10-0.40; C: Calibration plot (Hosmer–Lemeshow test, P = 0.783); D: Feature importance analysis confirmed intra-abdominal pressure and procalcitonin as leading predictors. APACHE II: Acute Physiology and Chronic Health Evaluation II; AUC: Area under the curve; CRP: C-reactive protein; IAP: Intra-abdominal pressure; LR: Logistic regression; ML: Machine learning; PCT: Procalcitonin; ROC: Receiver operating characteristic; CI: Confidence interval.