Frontiers in medicine · 2026
Development and validation of a 24-h predictive model for hypertriglyceridemic moderately severe acute pancreatitis: a single-center retrospective study.
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Yang Songlong, Li Chaoqun, Zeng Kaiping, Zhang Minguang, Wang Wenrong
Аннотация
OBJECTIVE: To develop and validate a risk prediction model for identifying patients with hypertriglyceridemia-induced acute pancreatitis who are at risk of progressing to moderately severe acute pancreatitis (MSAP) within 24 h after admission, thereby providing decision support for early clinical intervention.
METHODS: A single-center retrospective study was conducted, enrolling 146 patients with HTG-AP admitted between January 2018 and December 2023. The patients were randomly divided into a training set and a validation set at a ratio of 7:3. Predictive factors were screened using univariate analysis and multivariate logistic regression, To address the quasi-complete separation observed in the SIRS variables, a Firth penalized likelihood logistic regression model was employed to develop the prediction model. Model discrimination was assessed using the area under the receiver operating characteristic curve (ROC-AUC). Calibration performance was evaluated using the Hosmer-Lemeshow goodness-of-fit test, calibration plots, Brier score, and calibration slope. Clinical utility was assessed through decision curve analysis (DCA). Comparative performance against the BISAP score was conducted using DeLong's test. Internal validation was performed using 1,000 bootstrap resamples to estimate and adjust for optimism bias.
RESULTS: Multivariable analysis based on Firth's penalized likelihood logistic regression showed that systemic inflammatory response syndrome (SIRS) (OR = 202.469, p < 0.001) and elevated triglyceride (TG) levels (OR = 1.066, p = 0.013) within 24 h after admission were independent risk factors for predicting moderately severe disease. In the validation cohort, the area under the ROC curve (AUC) of the prediction model was 0.909, with a sensitivity of 86.2% and a specificity of 90.9%. In comparison, the AUC of the 24-h TG level alone (cut-off value: 18.41 mmol/L) was 0.690, with a sensitivity of 58.62% and a specificity of 81.82%.
CONCLUSION: SIRS and elevated TG levels within 24 h after admission are independent predictors of progression to moderately severe disease in patients with HTG-AP. The prediction model based on these variables demonstrates good predictive performance. A 24-h TG level below 18.41 mmol/L indicates a relatively lower risk of progression to moderately severe disease; however, prediction based on combined biochemical indicators is recommended. Further studies are required to validate the effectiveness of this model.
METHODS: A single-center retrospective study was conducted, enrolling 146 patients with HTG-AP admitted between January 2018 and December 2023. The patients were randomly divided into a training set and a validation set at a ratio of 7:3. Predictive factors were screened using univariate analysis and multivariate logistic regression, To address the quasi-complete separation observed in the SIRS variables, a Firth penalized likelihood logistic regression model was employed to develop the prediction model. Model discrimination was assessed using the area under the receiver operating characteristic curve (ROC-AUC). Calibration performance was evaluated using the Hosmer-Lemeshow goodness-of-fit test, calibration plots, Brier score, and calibration slope. Clinical utility was assessed through decision curve analysis (DCA). Comparative performance against the BISAP score was conducted using DeLong's test. Internal validation was performed using 1,000 bootstrap resamples to estimate and adjust for optimism bias.
RESULTS: Multivariable analysis based on Firth's penalized likelihood logistic regression showed that systemic inflammatory response syndrome (SIRS) (OR = 202.469, p < 0.001) and elevated triglyceride (TG) levels (OR = 1.066, p = 0.013) within 24 h after admission were independent risk factors for predicting moderately severe disease. In the validation cohort, the area under the ROC curve (AUC) of the prediction model was 0.909, with a sensitivity of 86.2% and a specificity of 90.9%. In comparison, the AUC of the 24-h TG level alone (cut-off value: 18.41 mmol/L) was 0.690, with a sensitivity of 58.62% and a specificity of 81.82%.
CONCLUSION: SIRS and elevated TG levels within 24 h after admission are independent predictors of progression to moderately severe disease in patients with HTG-AP. The prediction model based on these variables demonstrates good predictive performance. A 24-h TG level below 18.41 mmol/L indicates a relatively lower risk of progression to moderately severe disease; however, prediction based on combined biochemical indicators is recommended. Further studies are required to validate the effectiveness of this model.