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Systemic Inflammation Indices as Early Predictors of Severity in Acute Pancreatitis
José Francisco Araiza-Rodríguez1, Brandon Bautista-Becerril2, Alejandra Núñez-Venzor1
1Hospital General "Dr. Manuel Gea González", Mexico City 14080, Mexico.
None:
Background/Objectives: Acute pancreatitis (AP) is a highly variable inflammatory condition that can lead to severe complications and high mortality, particularly in its severe forms. Early risk stratification is essential; however, the delayed availability of traditional scoring systems often limits its effectiveness. This study aimed to evaluate the clinical utility of systemic inflammation indices as early predictors of severity in patients with acute pancreatitis. Methods: A retrospective, observational study was conducted among patients diagnosed with acute pancreatitis, classified according to the revised Atlanta criteria. Upon admission, systemic inflammation indices were calculated from complete blood count parameters, including neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI). Severity was assessed using the APACHE II score. Statistical analysis involved Kruskal-Wallis tests, Dunn's post hoc comparisons, ROC curve analysis, logistic regression for odds ratios (ORs), and Spearman correlations. Results: SII, NLR, MLR, SIRI, and AISI showed statistically significant associations with AP severity (p < 0.05). MLR and SIRI exhibited the highest predictive performance (AUC = 0.74). ORs for severe pancreatitis were: MLR = 19.10, SIRI = 7.50, NLR = 7.33, AISI = 5.12, and SII = 4.10. All four indices also demonstrated moderate positive correlations with APACHE II scores. Conclusions: Systemic inflammation indices are simple, cost-effective, and accessible tools that can aid in the early identification of patients at high risk for severe acute pancreatitis. Their integration into clinical practice may enhance early decision-making and improve patient outcomes.
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