ArticleInternational journal of general medicine2024
Development and Validation of a Multivariable Predictive Model for the Risk of Histologic Chorioamnionitis in Patients with Premature Rupture of Membranes in the Late Preterm and Term.
Article in International journal of general medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Development and Validation of a Nomogram Model for Predicting Chorioamnionitis in Patients with Term Premature Rupture of Membranes.International journal of women's health · 2026Article
- Initial and Longitudinal Trajectories in Hemoglobin Levels Predict the Prognosis of Patients With Premature Rupture of Membranes.American journal of reproductive immunology (New York, N.Y. : 1989) · 2025Article
- Association Analysis Between Maternal Neutrophil Ratio and the Risk of Histological Chorioamnionitis in Pregnant Women with Premature Rupture of Membranes in Late Pregnancy.International journal of general medicine · 2024Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aimed to develop and validate a model to predict histologic chorioamnionitis (HCA) risk in late preterm and term premature rupture of membranes (PROM) patients using clinical and laboratory parameters. Methods: We conducted a retrospective study on 116 late preterm and term PROM cases, divided into a training (n=81) and a validation set (n=35). A multivariable logistic regression model was developed using the training set. Performance was assessed via the area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI). Decision curve analysis (DCA) evaluated the model's clinical utility. Additionally, nomograms and a web version of the model were developed. Results: In the training set, the combined model constructed using maternal BMI, gravidity, amniotic fluid characteristics, and prenatal white blood cell (WBC) count showed significantly higher AUC than WBC alone (0.859 vs 0.710, P=0.010), with improved accuracy and sensitivity. In the validation set, the AUC of the combined model remained higher than that of WBC, but the difference was not statistically significant (0.728 vs 0.584, P=0.173). NRI analysis indicated that the combined model improved the correct classification of HCA by 25.0% (P=0.012) compared to that of WBC alone. DCA demonstrated that the combined model had a higher net benefit than WBC in most cases. The nomograms and web version of the model provided convenient tools for clinicians to predict the risk of HCA. Conclusion: This study successfully developed and validated a clinically feasible multivariable model to predict the risk of HCA in women with late preterm and term PROM.
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Registered trials
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