Clinical value of BISAP score combined with low-density lipoprotein cholesterol and ascites in early prediction of hypertriglyceridemic severe acute pancreatitis
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background and aims: An immediate diagnosis and accurate severity assessment of hypertriglyceridemic acute pancreatitis (HTG-AP) are essential. However, risk scoring system specific to HTG-AP has not yet been established. The study aims to identify the potential early predictors of severe cases and explore a novel predictive model for its early identification. Methods: A retrospective analysis was conducted on 189 patients with HTG-AP. According to the revised Atlanta classification, patients were categorized into severe (HTG-SAP, N = 25) and no severe (HTG-NSAP, N = 164) groups. Independent predictors of HTG-SAP were identified through univariate and multivariate logistic regression analyses, with predictive abilities estimated by receiver operating characteristic curves. Results: < 0.05). According to multivariate logistic regression, the BISAP score, low LDL-C level, and the presence of ascites were identified as independent risk factors for HTG-SAP, with the area under the curve (AUC) values of 0.840, 0.702, and 0.742, respectively. The AUC for the model combined BISAP with LDL-C and ascites was 0.900. Decision curve analysis demonstrated that implementing clinical interventions for cases identified by the model as being at risk of developing HTG-SAP could yield significant clinical benefits. Conclusions: The BISAP score combined with LDL-C and ascites might have a potential early predictive value for HTG-SAP, and additional multicenter studies involving larger samples are needed to confirm these results.
Source: Frontiers in Endocrinology
Authors: Xiaofen Xu, Tao Xu, Ye Wang, Lei Li
Institutions: Capital Medical University, Beijing Jishuitan Hospital
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4417145015
