Intra-abdominal pressure and procalcitonin for prognosis in patients with severe acute pancreatitis: An etiology-based analysis
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND Early risk stratification in severe acute pancreatitis (SAP) remains challenging with traditional scoring systems overlooking etiological heterogeneity, particularly in hypertriglyceridemic acute pancreatitis (HTG-AP). AIM To develop and evaluate a machine learning (ML) model combining intra-abdominal pressure (IAP) and procalcitonin (PCT) for SAP prognosis and evaluate its clinical impact across different etiologies. METHODS We retrospectively analyzed 245 patients with pancreatitis (98 patients with SAP). An ML model using 24-h peak IAP and PCT levels was used to predict 28-day mortality. Propensity score matching was used to compare IAP-PCT-guided management with conventional management. RESULTS The ML-IAP-PCT model outperformed the Acute Physiology and Chronic Health Evaluation II score (area under the curve: 0.853 vs 0.801, P = 0.044) and Bedside Index of Severity in Acute Pancreatitis score. IAP-PCT-guided management was associated with lower mortality (15.8% vs 25.0%, P = 0.043) and multiple organ dysfunction syndrome (48.7% vs 61.8%, P = 0.027) rates. Patients with HTG-AP showed the greatest benefit (multiple organ dysfunction syndrome: 39.3% vs 60.7%, P = 0.018). CONCLUSION ML-optimized IAP-PCT monitoring provides superior prognostic accuracy and guides management associated with improved outcomes, especially in patients with HTG-AP. Prospective validation is needed to establish causality for this etiology-stratified approach.
Institution: Huzhou Women and Children's Hospital
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Awards: G1287959399, G2005892256
OpenAlex ID: W7117243391