Establishment and Validation of Early Prediction Model for Hypertriglyceridemic Severe Acute Pancreatitis

作者：Shuanglian Yi, Huiling Zeng, Xunting Lin, Yi‐Fang Deng, Yufen Lin, Shanshan Xie, Li-Juan Si, Yunpeng Liu · 发表于：Research Square · 年份：2023 · DOI：10.21203/rs.3.rs-3390665/v1 · 研究领域：Pancreatitis Pathology and Treatment、Pancreatic and Hepatic Oncology Research、Lipid metabolism and disorders

Abstract Background The prevalence of hypertriglyceridaemia-induced acute pancreatitis (HTG-AP) is increasing due to improvements in living standards and dietary changes. However, at present, there is no clinical multifactor scoring system specific to HTG-AP. This study aimed to screen the predictors of hypertriglyceridemia severe acute pancreatitis (HTG-SAP) and combined several indicators to establish and verify a visual model for the early prediction of HTG-SAP. Methods The clinical data of 266 patients with HTG-SAP were analysed. Patients were classified into severe (n = 42) and non-severe (n = 224) groups according to the Atlanta classification criteria. Several statistical analyses, including one-way analysis, least absolute shrinkage with selection operator (LASSO) regression model and binary logistic regression analysis were used to evaluate the data. Result The univariate analysis found that several factors showed no statistically significant differences, including number of episodes of pancreatitis, abdominal pain score and several blood diagnostic markers, such as lactate dehydrogenase (LDH), serum calcium (Ca 2+ ), C-reactive protein (CRP) and the incidence of pleural effusion, between the two groups (P < 0.000). LASSO regression analysis identified six candidate predictors: CRP, LDH, Ca 2+ , procalcitonin (PCT), ascites and Balthazar computed tomography (CT) grade. Binary logistic regression multivariate analysis showed that CRP, LDH, Ca 2+ , and ascites were ...