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

Table 3 Performance comparison of different models for predicting 28-day mortality

Prediction models	Area under the curve (95%CI)	Sensitivity (%)	Specificity (%)	Positive predictive value (%)	Negative predictive value (%)	P value
IAP model alone	0.772 (0.686-0.858)	71.7	73.8	47.3	88.9	0.008a
PCT model alone	0.765 (0.679-0.851)	68.9	72.6	46.1	87.3	0.005a
Acute Physiology and Chronic Health Evaluation II score	0.796 (0.718-0.874)	75.1	70.3	46.8	89.1	0.041a
Logistic regression IAP-PCT model	0.813 (0.738-0.888)	76.8	74.2	50.3	90.3	0.087
ML-IAP-PCT model	0.837 (0.765-0.909)	78.6	76.5	53.1	91.4	Reference
ML-comprehensive model1	0.842 (0.772-0.912)	79.3	77.2	54.5	91.7	0.386

¹Machine learning-comprehensive model included intra-abdominal pressure, procalcitonin, and nine clinical variables.

^aP < 0.05 vs the machine learning-intra-abdominal pressure-procalcitonin model according to the DeLong test.

IAP: Intra-abdominal pressure; ML: Machine learning; PCT: Procalcitonin; CI: Confidence interval.