Observational studyBMC pregnancy and childbirth2025
Establishment and validation of a nomogram for predicting preterm birth in intrahepatic cholestasis during pregnancy: a retrospective study.
Observational study in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Early Precise Prediction and Severe Risk Stratification of Intrahepatic Cholestasis of Pregnancy: Advances and Future Directions in Clinical Translation from Traditional Models to Artificial Intelligence and Multi-Omics Technologies.Journal of clinical medicine · 2026Review
- A nomogram integrating dynamic total bile acid monitoring, medication history, and curative effect for preterm birth prediction in twin pregnancies with intrahepatic cholestasis of pregnancy.BMC pregnancy and childbirth · 2026Article
- Observational
- Early Metabolic Profile in Neonates with Maternal Intrahepatic Cholestasis of Pregnancy.Children (Basel, Switzerland) · 2025Article
- Correction: Establishment and validation of a nomogram for predicting preterm birth in intrahepatic cholestasis during pregnancy: a retrospective study.BMC pregnancy and childbirth · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to develop and evaluate a nomogram for predicting preterm birth in patients with intrahepatic cholestasis of pregnancy (ICP), with a view to assisting clinical management and intervention.
methodsThis retrospective observational study included 257 pregnant women with ICP from Sichuan Provincial People's Hospital between January 1, 2022 and July 30, 2024. The routine clinical and laboratory information of these patients were also collected. We used the least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analysis to investigate the association between clinical and laboratory data and preterm birth in ICP patients. A nomogram was developed to predict the likelihood of preterm birth in ICP patients. The prediction accuracy of the model was evaluated by consistency index (C-index), receiver operating characteristic (ROC) curve, area under the curve (AUC), and calibration curve. Decision curve analysis (DCA) was used to evaluate its applicability in clinical practice.
resultsAmong the 257 ICP patients, 56 (21.79%) were diagnosed with preterm birth. Cases were randomly divided into a training set (154 cases) and a test set (103 cases). A nomogram was developed to predict preterm birth in ICP patients based on height, twin pregnancy (TP), gestational age at diagnosis (GA at diagnosis), and total bile acid level (TBA) at diagnosis. The calibration curve of the training set was close to the diagonal (C-index = 0.864), and the calibration curve of the test set was also close to the diagonal (C-index = 0.835). These results indicate that the model has a good consistency. The AUC of the training group and the test group were 0.864 and 0.836, respectively, indicating the good accuracy of the model. The DCA reveals that this nomogram could be applied to clinical practice.
conclusionThe combination of TBA level, TP, height and GA at diagnosis is an effective model for identifying preterm birth in ICP patients. These results will help guide the clinical management and treatment of patients with ICP, thereby reducing maternal and infant safety issues caused by preterm birth.
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