ArticleBMC gastroenterology2025
Development of a novel nomogram to predict the prognosis of acute pancreatitis in pregnancy.
Article in BMC gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Acute Pancreatitis in Pregnancy and the Early Postpartum Period: An Anaesthesiology and Critical Care Perspective.Journal of clinical medicine · 2026Article
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11 authors.
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Abstract
backgroundAcute pancreatitis is a rare but serious complication for pregnant women. Early identification of severity of acute pancreatitis in pregnancy (APIP) is of great significance to the treatment. The aim of this study was to investigate the risk factors and develop a novel model for predicting the prognosis of APIP patients.
methodsA retrospective study was conducted from December 2005 to June 2024. Univariate and multivariate analyses were used to identify the risk factors of APIP. LASSO regression and logistic regression were employed to develop prognosis model of APIP patients and nomogram was plotted. The performance of the predictive model was evaluated using the receiver operating characteristic curve, calibration curve and decision curve analysis.
resultsA total of 45 patients with APIP were enrolled in this study. Univariate and multivariate logistic regression analysis determined that albumin (OR = 0.72, 95%CI: 0.51-0.90, P = 0.019) and blood urea nitrogen (OR = 1.45, 95%CI: 1.11-2.14, P = 0.021) measured within 24 h of admission were independent risk factors of severity in APIP. Additionally, a prognostic model consisting of albumin and blood urea nitrogen was developed based on LASSO and logistic regression models. Nomogram was established and visualized. The nomogram achieved a higher AUC value of 0.920 than BISAP score (AUC = 0.875) and SIRS score (AUC = 0.728). Besides, The AUC of nomogram to predict ICU admission in APIP patients was 0.819. Calibration curve indicated that the prediction model has good calibration performance, while decision curve confirmed its clinical utility.
conclusionThis study developed a novel and simple nomogram to predict the severity and ICU admission of APIP patients, which is of great value in guiding APIP management.
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