The Association Between Inflammatory Indices and Acute Pancreatitis Severity: A Retrospective Cohort Study

Huicong Ma¹Na Li¹Huaisheng Zhang²Zepeng Shen²Jie Yang²Qiaojie Bi^1*Xiaoxiao Miao^3*

• ¹Institute of Emergency and Critical Care Medicine, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, China
• ²The First Affiliated Hospital of Bengbu Medical University, Bengbu, China
• ³Qingdao Traditional Chinese Medicine Hospital, Qingdao Hiser Hospital Affiliated of Qingdao University, Qingdao, China

Background: Acute pancreatitis (AP) is a heterogeneous inflammatory disease, with ~20% of patients progressing to moderate-to-severe (MSAP) or severe AP (SAP), conditions associated with high mortality. Early risk stratification is therefore critical. This study systematically evaluated and compared 12 inflammatory biomarkers for predicting AP severity. Methods: This retrospective cohort included 1,981 hospitalized AP patients (January 2018-December 2023). According to the revised Atlanta criteria, patients were classified into mild AP (MAP, n=1,058) and MSAP/SAP (n=923) groups. Twelve inflammatory indices—monocyte-to-lymphocyte ratio (MLR), lymphocyte-to-monocyte ratio (LMR), C-reactive protein-to-albumin ratio (CAR), C-reactive protein-albumin-lymphocyte index (CALLY), C-reactive protein-to-calcium ratio (CCR), C-reactive protein-to-lymphocyte ratio (CLR), red cell distribution width-to-albumin ratio (RDW/Alb), neutrophil-to-albumin ratio (NAR), systemic inflammatory response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII)—were calculated. A multivariate logistic regression model adjusted for 28 covariates. ROC curves assessed predictive performance; restricted cubic splines (RCS) explored nonlinear relationships; and threshold effect analysis was conducted for the highest-performing biomarker. Results: In the fully adjusted model, nine biomarkers were significantly associated with MSAP/SAP risk: MLR (OR=1.29, 95%CI: 1.15-1.45), LMR (OR=0.75, 95%CI: 0.66-0.85), CAR (OR=3.82, 95%CI: 3.18-4.64), CALLY (OR=0.56, 95%CI: 0.49-0.64), CCR (OR=4.84, 95%CI: 3.98-5.96), CLR (OR=2.12, 95%CI: 1.84-2.46), RDW/Alb (OR=1.74, 95%CI: 1.54-1.99), NAR (OR=1.44, 95%CI: 1.27-1.64), and SIRI (OR=1.29, 95%CI: 1.15-1.46). CCR demonstrated the highest observed accuracy (AUC=0.761, 95%CI: 0.739-0.783). Threshold effect analysis revealed a nonlinear association, with an inflection point at 15: no significant association was observed below this threshold (OR=1.015, P=0.558), whereas risk significantly increased above it (OR=1.212, P<0.001). Conclusion: Among 12 inflammatory biomarkers, CCR showed the strongest predictive value for MSAP/SAP, with a critical threshold of 15. As an easily obtainable marker, CCR may serve as a practical early warning tool to guide clinical management and risk stratification in AP.