Elevated Systemic Inflammatory Response Index Is Associated With Increased Risk of Severe Acute Pancreatitis: A...

Acute pancreatitis (AP) is a common gastrointestinal emergency with a significant proportion of patients progressing to severe acute pancreatitis (SAP), which carries substantial morbidity and mortality. A comprehensive search of the literature was performed in PubMed, Scopus, Web of Science, Embase, Cochrane Library, and Google Scholar, covering all records from database inception through February 2026. Eligible studies were those providing quantitative evidence on the association between the Systemic Inflammatory Response Index (SIRI) and the severity of acute pancreatitis (AP) in adult populations. Methodological rigor was evaluated using the Newcastle-Ottawa Scale, and statistical synthesis was conducted with a random-effects approach using RevMan software. A total of nine studies satisfied the inclusion criteria and were incorporated into the meta-analysis. The aggregated results indicated that higher SIRI values were significantly correlated with a greater likelihood of severe acute pancreatitis (odds ratio or OR: 1.99; 95% confidence interval or CI: 1.46-2.72). Furthermore, patients with severe AP exhibited markedly elevated mean SIRI levels compared with those with mild disease (mean difference or MD: 4.30; 95% CI: 0.41-8.19). Substantial heterogeneity was detected among the included studies (I² = 92% for the OR analysis and I² = 89% for the mean difference analysis). Publication bias was not assessed as the number of included studies was less than 10. The findings of this meta-analysis suggest that elevated SIRI at admission is associated with an increased risk of severe acute pancreatitis, with patients presenting with severe disease demonstrating higher SIRI values compared to those with mild pancreatitis. These results are hypothesis-generating and should be interpreted as preliminary evidence rather than definitive proof of clinical utility. Large-scale prospective studies are warranted to establish optimal cut-off values and validate their incremental utility over existing severity scores.