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Preparing a Mice Model of Severe Acute Pancreatitis via a Combination of Caerulein and Lipopolysaccharide Intraperitoneal Injection
Published on: May 10, 2024
Intra-abdominal pressure and procalcitonin for prognosis in patients with severe acute pancreatitis: An
Jin-Feng Zhao1, Guo-Xing Jin2, Yao Wang3
1Department of General Surgery, Huzhou Wuxing District People's Hospital, Wuxing District Maternal and Child Health Hospital of Huzhou City, Huzhou 313000, Zhejiang Province, China.
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.
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