Abstract
Acute pancreatitis is an inflammatory condition that starts as a mild illness but can progress to become fatal through multi-organ failure with high death rates. The APACHE II and BISAP scoring systems help identify patient risks, but their ability to forecast early deterioration remains limited during the initial hours following admission when critical decisions need to be made. This review examines the mechanisms linking pancreatic injury to systemic inflammation and organ failure, outlining the distinction between early sterile organ failure and later sepsis-related failure. Clinical patterns of organ dysfunction correlate strongly with the inflammatory response, and early indicators such as systemic inflammatory response syndrome duration, rising blood urea nitrogen, hemoconcentration, and increasing CRP provide useful predictors of disease severity. Emerging biomarkers, including IL-6, IL-8, circulating histones, angiopoietin-2, arterial lactate, and albumin-based ratios, show promise for forecasting persistent organ failure. Integrating these markers with machine learning algorithms and multi-cytokine panels enhances predictive accuracy for patient risk assessment and early intensive care unit admission. Although promising, most of these biomarkers and AI-based tools remain investigational and require further multicenter validation. Future research should prioritize standardized assay methods and prospective evaluation of combined clinical-biomarker-AI models to determine their true impact on early diagnosis, triage, and patient outcomes.