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Updated: Jul 4, 2025

Preparing a Mice Model of Severe Acute Pancreatitis via a Combination of Caerulein and Lipopolysaccharide Intraperitoneal Injection
Published on: May 10, 2024
An inflammation-based model for identifying severe acute pancreatitis: a single-center retrospective study
Xiaotong Li1,2, Yiyan Zhang1,2, Weiwei Wang1,3
1Department of Gastroenterology, General Hospital of Northern Theater Command, No. 83 Wenhua Road, Shenyang, 110840, Liaoning Province, China.
Background And Aims:
Severe acute pancreatitis (SAP) is potentially lethal. Considering the role of inflammation in the progression of acute pancreatitis (AP), this study aims to develop a model based on inflammatory indexes for identifying the presence of SAP.
Methods:
Overall, 253 patients with AP who were consecutively admitted between July 2018 and November 2020 were screened, of whom 60 had SAP. Systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), neutrophil-to-platelet ratio (NPR), systemic inflammation response index (SIRI), platelet-to-albumin ratio (PAR), C-reactive protein-to-albumin ratio (CAR), C-reactive protein-to-lymphocyte ratio (CLR), and triglyceride glucose (TyG) index were calculated. Multivariate logistic regression analyses were performed to identify independent risk factors of SAP. Then, inflammation-based models were established. Receiver operating characteristics (ROC) curve analyses were performed. Area under ROC curve (AUROC) was calculated.
Results:
Diabetes mellitus, fatty liver, high white blood cell count (WBC), C-reactive protein (CRP), red blood cell distribution width (RDW), procalcitonin (PCT), SII, NLR, NPR, CAR, CLR, and TyG index, and a low LMR were significantly associated with SAP. Considering the collinearity among these variables, 10 multivariate logistic regression analyses were separately performed. Finally, four independent inflammation-based models were established. Of them, the best one, which was calculated as follows: 1.204*fatty liver (yes = 1; no = 0) + 0.419*PCT + 0.005*CLR - 2.629, had an AUROC of 0.795 with a specificity of 73.4% and a sensitivity of 71.7%.
Conclusion:
The inflammation-based model consisting of fatty liver, PCT, and CLR has a good diagnostic performance for SAP.
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