Hypertriglyceridemic acute pancreatitis with diabetes mellitus: Investigation of factors and predictive models for severity progression

Abstract

BACKGROUND

In recent years, the incidence of acute pancreatitis (AP) caused by hypertriglyceridemia has been on the rise. In China, it has surpassed alcohol to become the second leading cause of AP. Patients with hypertriglyceridemia-induced AP combined with diabetes mellitus (HTG-AP-DM) have a higher probability of developing severe disease.

AIM

To investigate the risk factors for progression to severe disease in HTG-AP-DM and to develop and validate a predictive model.

METHODS

This retrospective study, with a sample size of 133 patients, analyzed clinical data from patients with HTG-AP-DM admitted to the First Hospital of Jilin University between January 2019 and December 2024. Disease severity was classified according to the Revised Atlanta Classification, with mild and moderately severe cases categorized as the non-severe group and severe cases as the severe group. Potential predictors were initially screened using univariate logistic regression, followed by multivariate logistic regression to identify independent risk factors for progression to severe disease in patients with HTG-AP-DM. A predictive model was subsequently developed based on these factors. Model performance was evaluated using receiver operating characteristic curve analysis to quantify discriminative ability using the area under the curve (AUC), calibration curves to visualize agreement between predicted probabilities and observed outcomes, and decision curve analysis to assess clinical utility by calculating net benefit across threshold probabilities.

RESULTS

A retrospective analysis of 133 patients with HTG-AP-DM identified several independent risk factors for disease progression through univariate and multivariate logistic regression: Heart rate [odds ratio (OR) = 1.03, 95% confidence interval (CI): 1.01-1.05, P = 0.027], albumin (OR = 0.91, 95%CI: 0.84-0.98, P = 0.019), platelets (OR = 0.99, 95%CI: 0.98-0.99, P < 0.001), serum lipase (OR = 1.01, 95%CI: 1.01-1.01, P = 0.014), random plasma glucose (OR = 1.22, 95%CI: 1.07-1.39, P = 0.003), and pleural effusion (OR = 3.83, 95%CI: 1.30-11.25, P = 0.015). The predictive model incorporating these variables demonstrated excellent discriminative power (AUC = 0.894, 95%CI: 0.840-0.949) and good calibration between predicted and observed probabilities, whereas decision curve analysis confirmed its clinical utility across a wide range of probability thresholds, suggesting robust potential for clinical application.

CONCLUSION

Heart rate, serum lipase, random plasma glucose, and pleural effusion were identified as independent risk factors for disease progression to a severe stage, whereas albumin and platelets were independent protective factors. The predictive model developed based on these variables can rapidly assess whether a patient will progress to severe illness within 24 hours of admission, with an AUC of 0.894, demonstrating excellent prognostic performance.

Keywords: Hypertriglyceridemic acute pancreatitis; Diabetes mellitus; Severity; Clinical prediction model; Hyperlipidemia; Albumin and platelets; Protective factors

Core Tip: In a retrospective cohort of 133 patients with hypertriglyceridemic acute pancreatitis combined with diabetes mellitus, multivariate analysis revealed that heart rate, serum lipase, random plasma glucose, and pleural effusion were independent risk factors for severe disease, while albumin and platelets were protective. The predictive model incorporating these variables exhibited excellent discrimination (area under the curve = 0.894), good calibration, and net clinical benefit, aiding early risk stratification.