ArticleFrontiers in public health2022
Development and Validation of Multi-Stage Prediction Models for Pre-eclampsia: A Retrospective Cohort Study on Chinese Women.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- First-Trimester Prediction Models Based on Maternal Characteristics for Adverse Pregnancy Outcomes: A Systematic Review and Meta-Analysis.BJOG : an international journal of obstetrics and gynaecology · 2025Pooled it
- Machine Learning Algorithms Versus Classical Regression Models in Pre-Eclampsia Prediction: A Systematic Review.Current hypertension reports · 2024Pooled it
- 3D Placental Bed Perfusion Ultrasound: Development and Internal Validation of Trimester-Specific Prediction Models for Early- and Late-Onset Preeclampsia.Reproductive sciences (Thousand Oaks, Calif.) · 2026Article
- First-trimester biochemical inflammatory markers (NHR and NLR) as predictors of preeclampsia risk.Journal of medical biochemistry · 2026Article
- Clinical Deployment of Interpretable AI: Bridging Routine Clinical Tests and Proteomic Signatures for Preeclampsia Risk Stratification.Current drug targets · 2026Article
- Uric Acid and Preeclampsia: Pathophysiological Interactions and the Emerging Role of Inflammasome Activation.Antioxidants (Basel, Switzerland) · 2025Review
- Article
- Serum uric acid as a diagnostic biomarker for preeclampsia: comparison with renal indices and cerebroplacental ratio.Frontiers in endocrinology · 2025Article
- Role of First Trimester Screening Biochemical Markers to Predict Hypertensive Pregnancy Disorders and SGA Neonates-A Narrative Review.Healthcare (Basel, Switzerland) · 2023Review
- Incremental predictive value of platelet parameters for preeclampsia: results from a large prospective cohort study.BMC pregnancy and childbirth · 2023Article
- Identification of key genes in the pathogenesis of preeclampsia via bioinformatic analysis and experimental verification.Frontiers in endocrinology · 2023Article
- Development and validation of the prediction models for preeclampsia: a retrospective, single-center, case-control study.Annals of translational medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The aim of this study is to develop multistage prediction models for pre-eclampsia (PE) covering almost the entire pregnancy period based on routine antenatal measurements and to propose a risk screening strategy. Methods: This was a retrospective cohort study that included 20582 singleton pregnant women with the last menstruation between January 1, 2013 and December 31, 2019. Of the 20582 women, 717 (3.48%) developed pre-eclampsia, including 46 (0.22%) with early-onset pre-eclampsia and 119 (0.58%) preterm pre-eclampsia. We randomly divided the dataset into the training set ( Results: We found that uric acid tested from 5-10 weeks of gestation, platelets tested at 18-23 and 24-31 weeks of gestation, and alkaline phosphatase tested at 28-31, 32-35 and 36-39 weeks of gestation can further improve the prediction performance of models. The AUROC of the optimal prediction models on the test set gradually increased from 0.71 at 5-10 weeks to 0.80 at 24-27 weeks, and then gradually increased to 0.95 at 36-39 weeks of gestation. At sensitivity level of 0.98, our screening strategy can identify about 94.8% of women who will develop pre-eclampsia and reduce about 40% of the healthy women to be screened by 28-31 weeks of pregnancy. Conclusion: We developed multistage prediction models and a risk screening strategy, biomarkers of which were part of routine test items and did not need extra costs. The prediction window has been advanced to 5-10 weeks, which has allowed time for aspirin intervention and other means for PE high-risk groups.
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