ArticleFrontiers in nutrition2026
Predictive value of sarcopenia-related clinical indices for early disease progression in acute pancreatitis: a multicenter retrospective cohort study.
Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Early identification of patients at risk for severe Acute Pancreatitis (AP) remains a critical clinical challenge. Although sarcopenia reflects nutritional status and physiological reserve, its predictive value for disease progression in AP remains unclear. This study aimed to evaluate the association between sarcopenia, quantified by the psoas muscle index (PMI), and progression to moderately severe or severe AP, and to develop a practical risk-stratification tool. Methods: We retrospectively analyzed 470 patients with AP. Sarcopenic status was assessed by measuring the psoas major muscle area at the L3 level on admission CT scans. Multivariate Cox regression was employed to identify independent risk factors for progression to moderately severe or severe AP (MSAP/SAP). A predictive nomogram was constructed and validated using C-index, time-dependent ROC curves, and decision curve analysis (DCA). Results: Decreased PMI and Albumin (Alb), alongside elevated Systemic Immune-Inflammation index (SII) and Alanine Aminotransferase (ALT), were independent predictors of disease progression. The nomogram demonstrated moderate discriminatory ability, with C-indices of 0.68 and 0.63 in the training and validation sets, respectively. The 7-day Area Under the Curve (AUC) reached 0.69 (training) and 0.65 (validation). Survival analysis demonstrated significantly higher progression rates in the high-risk group ( Conclusion: Sarcopenia, characterized by a low PMI, is an independent predictor of early progression to moderately severe or severe AP. The developed nomogram, integrating PMI with routine laboratory markers (SII, ALT, Alb), may serve as a potentially useful tool for early risk stratification and personalized management.
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