A nomogram to predict meconium-stained amniotic fluid in patients during labor: a retrospective cohort study

Meconium-stained amniotic fluid (MSAF) carries an increased risk of maternal-fetal mortality and morbidity. This study aimed to develop and internally validate a nomogram for predicting the occurrence of MSAF in full-term pregnant women during trial of labor. We retrospectively screened cases of MSAF in patients during labor in our hospital. Potential risk factors were screened through univariate analysis, followed by feature selection using least absolute shrinkage and selection operator (LASSO) regression. A multivariate logistic regression model was constructed and visualized as a nomogram. The model underwent internal validation and was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA). This cohort study included 2260 women, comprising 354 cases with MSAF and 1906 controls. All enrolled patients were randomly divided into training set (n = 1582) and validation set (n = 678). A clinical nomogram was developed incorporating nine independent predictors, including primiparous women, gestational age ≥ 41 weeks, premature rupture of membranes, C-reactive protein level, intrahepatic cholestasis of pregnancy, catheter balloon insertion, intrapartum fever, pathological fetal heart rate patterns, and duration of latent phase (> 16 h). The area under the curves (AUCs) of the training and validation set were 0.891 and 0.883, respectively. The calibration curve indicated excellent agreement between the predicted probabilities and the actual observed outcomes and the DCA showed significantly good net benefit in the predictive model. The proposed nomogram may help clinicians identify high-risk MSAF patients during labor and optimize perinatal management.

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Publication Details

Journal
BMC Pregnancy and Childbirth
Published
2026-02-04
DOI
https://doi.org/10.1186/s12884-026-08748-4
Primary Topic
Neonatal Respiratory Health Research
Type
article
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article

A nomogram to predict meconium-stained amniotic fluid in patients during labor: a retrospective cohort study

Xuepiao Zhao, Peiran B Yang, Yongfei Yue, Zhiyi Yang et al.
BMC Pregnancy and Childbirth
Neonatal Respiratory Health Research
article

A nomogram to predict meconium-stained amniotic fluid in patients during labor: a retrospective cohort study

Xuepiao Zhao, Peiran B Yang, Yongfei Yue, Zhiyi Yang, Jun Yan, Yanxia Chu
article en

Abstract

Meconium-stained amniotic fluid (MSAF) carries an increased risk of maternal-fetal mortality and morbidity. This study aimed to develop and internally validate a nomogram for predicting the occurrence of MSAF in full-term pregnant women during trial of labor. We retrospectively screened cases of MSAF in patients during labor in our hospital. Potential risk factors were screened through univariate analysis, followed by feature selection using least absolute shrinkage and selection operator (LASSO) regression. A multivariate logistic regression model was constructed and visualized as a nomogram. The model underwent internal validation and was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA). This cohort study included 2260 women, comprising 354 cases with MSAF and 1906 controls. All enrolled patients were randomly divided into training set (n = 1582) and validation set (n = 678). A clinical nomogram was developed incorporating nine independent predictors, including primiparous women, gestational age ≥ 41 weeks, premature rupture of membranes, C-reactive protein level, intrahepatic cholestasis of pregnancy, catheter balloon insertion, intrapartum fever, pathological fetal heart rate patterns, and duration of latent phase (> 16 h). The area under the curves (AUCs) of the training and validation set were 0.891 and 0.883, respectively. The calibration curve indicated excellent agreement between the predicted probabilities and the actual observed outcomes and the DCA showed significantly good net benefit in the predictive model. The proposed nomogram may help clinicians identify high-risk MSAF patients during labor and optimize perinatal management.

BMC Pregnancy and ChildbirthVol. 26(1)
Suzhou Municipal Hospital (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 68%
Neonatal Respiratory Health Research
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