ArticleFrontiers in cardiovascular medicine2022
Predictors of Maternal Death Among Women With Pulmonary Hypertension in China From 2012 to 2020: A Retrospective Single-Center Study.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Predictive efficacy of PASP combined with NT-proBNP for outcomes in pregnant women with severe cardiovascular disease: a single-centre retrospective observational study.BMC pregnancy and childbirth · 2026Observational
- Trends in maternal mortality in China and Hainan Province: an analysis based on GBD 2023 and Hainan surveillance data.Frontiers in global women's health · 2026Article
- Risk stratification and multidisciplinary management strategies for pregnancy complicated by pulmonary arterial hypertension: a narrative review.Frontiers in endocrinology · 2026Review
- A nomogram model for predicting maternal cardiovascular complications and neonatal adverse outcomes in pregnant patients with pulmonary arterial hypertension.Annals of medicine · 2025Article
- The Obstetric Comorbidity Index (OB-CMI) and its association with ICU admission and length of hospital stay in pregnant patients with pulmonary hypertension: a retrospective cohort study (1996-2025).International journal of obstetric anesthesia · 2025Article
- An early screening model for preeclampsia: utilizing zero-cost maternal predictors exclusively.Hypertension research : official journal of the Japanese Society of Hypertension · 2024Article
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11 authors.
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Abstract
Background: Previous studies have suggested that pregnant women with pulmonary hypertension (PH) have high maternal mortality. However, indexes or factors that can predict maternal death are lacking. Methods: We retrospectively reviewed pregnant women with PH admitted for delivery from 2012 to 2020 and followed them for over 6 months. The patients were divided into two groups according to 10-day survival status after delivery. Predictive models and predictors for maternal death were identified using four machine learning algorithms: naïve Bayes, random forest, gradient boosting decision tree (GBDT), and support vector machine. Results: A total of 299 patients were included. The most frequent PH classifications were Group 1 PH (73.9%) and Group 2 PH (23.7%). The mortality within 10 days after delivery was 9.4% and higher in Group 1 PH than in the other PH groups (11.7 vs. 2.6%, Conclusion: Mortality remained high, particularly in Group 1 PH. Our study shows that NT-proBNP, PASP, and albumin are the most important predictors of maternal death in the GBDT model. These findings may help clinicians provide better advice regarding fertility for women with PH.
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