Establishment and validation of clinical prediction models for preterm birth in patients with intrahepatic cholestasis of pregnancy: Single-center retrospective observational study

This study aimed to develop and validate a prediction model for preterm birth in patients with intrahepatic cholestasis of pregnancy. A retrospective analysis was conducted using demographic and clinical data from 370 patients with intrahepatic cholestasis of pregnancy. Multivariate logistic regression was used to screen predictive factors and construct the prediction model. The model's discriminative ability, calibration, and clinical utility were evaluated. Six relevant independent predictors were identified: employment status, placental grading, pharmacotherapy status, lymphocyte count, neutrophil count, and serum total bile acid level. The constructed model demonstrated excellent discriminative ability and calibration in the training set, with an area under the curve of 0.85 (95% CI: 0.78-0.91) and a P value of 0.147 in the Hosmer-Lemeshow test. Decision curve analysis in the training set showed that the model provided clinical net benefit across a risk threshold range of 4% to 45%. This study established the first preterm birth prediction tool for intrahepatic cholestasis of pregnancy integrating multidimensional indicators. It provides an objective basis for early clinical identification of high-risk patients and has significant clinical value.

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Journal
Medicine
Published
2025-12-26
DOI
https://doi.org/10.1097/md.0000000000046848
Primary Topic
Drug Transport and Resistance Mechanisms
Type
article
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article

Establishment and validation of clinical prediction models for preterm birth in patients with intrahepatic cholestasis of pregnancy: Single-center retrospective observational study

Min Wen, Wenfei Zheng, Mengmeng Yu
Medicine
Drug Transport and Resistance Mechanisms
article

Establishment and validation of clinical prediction models for preterm birth in patients with intrahepatic cholestasis of pregnancy: Single-center retrospective observational study

Min Wen, Wenfei Zheng, Mengmeng Yu
article en

Abstract

This study aimed to develop and validate a prediction model for preterm birth in patients with intrahepatic cholestasis of pregnancy. A retrospective analysis was conducted using demographic and clinical data from 370 patients with intrahepatic cholestasis of pregnancy. Multivariate logistic regression was used to screen predictive factors and construct the prediction model. The model's discriminative ability, calibration, and clinical utility were evaluated. Six relevant independent predictors were identified: employment status, placental grading, pharmacotherapy status, lymphocyte count, neutrophil count, and serum total bile acid level. The constructed model demonstrated excellent discriminative ability and calibration in the training set, with an area under the curve of 0.85 (95% CI: 0.78-0.91) and a P value of 0.147 in the Hosmer-Lemeshow test. Decision curve analysis in the training set showed that the model provided clinical net benefit across a risk threshold range of 4% to 45%. This study established the first preterm birth prediction tool for intrahepatic cholestasis of pregnancy integrating multidimensional indicators. It provides an objective basis for early clinical identification of high-risk patients and has significant clinical value.

MedicineVol. 104(52)
Yichang Central People's Hospital (CN)
Reduced inequalities
Openalex Percentile: Top 31%
Drug Transport and Resistance Mechanisms
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