ArticleHypertension research : official journal of the Japanese Society of Hypertension2021
Development and validation of a nomogram for the early prediction of preeclampsia in pregnant Chinese women.
Article in Hypertension research : official journal of the Japanese Society of Hypertension, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Assisted Reproductive Technology as Predictor for Preeclampsia: A Systematic Review of Current Clinical Prediction Models.Reproductive sciences (Thousand Oaks, Calif.) · 2026Pooled 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
- Maternal red blood cell folate and vitamin B metabolism with pregnancy outcomes: a retrospective study.BMC pregnancy and childbirth · 2025Article
- Cohort-based nomogram for forensic prediction of SCD: a single-center pilot study.Forensic science, medicine, and pathology · 2025Article
- A prediction model of superimposed preeclampsia in women with chronic hypertension.Frontiers in cardiovascular medicine · 2025Article
- Combined assessment of placental growth factor, uterine artery pulsation index, and mean arterial pressure for predicting preeclampsia.American journal of translational research · 2025Article
- Article
- Preeclampsia up to date-What's going on?Hypertension research : official journal of the Japanese Society of Hypertension · 2023Review
- Systematic review and meta-analysis protocol for development and validation of a prediction model for gestational hypertension in Africa.SAGE open medicine · 2023Article
- Development of a prediction model on preeclampsia using machine learning-based method: a retrospective cohort study in China.Frontiers in physiology · 2022Article
- Development and Validation of Multi-Stage Prediction Models for Pre-eclampsia: A Retrospective Cohort Study on Chinese Women.Frontiers in public health · 2022Article
- Development of a nomogram for predicting clinical outcome in patients with angiogram-negative subarachnoid hemorrhage.CNS neuroscience & therapeutics · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To make early predictions of preeclampsia before diagnosis, we developed and validated a new nomogram for the early prediction of preeclampsia in pregnant Chinese women. A stepwise regression model was used for feature selection. Multivariable logistic regression analysis was used to develop the prediction model. We incorporated BMI, blood pressure, uterine artery ultrasound parameters, and serological indicator risk factors, and this was presented with a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Internal validation was assessed. The signature, which consisted of 11 selected features, was associated with preeclampsia status (P < 0.1) for the development dataset. Predictors contained in the individualized prediction nomogram included BMI, blood pressure, uterine artery ultrasound parameters, and serological indicator levels. The model showed good discrimination, with an area under the ROC curve of 0.8563 (95% CI: 0.8364-0.8761) and good calibration. The nomogram still had good discrimination and good calibration when applied to the validation dataset (area under ROC curve of 0.8324, 95% CI: 0.7873-0.8775). Decision curve analysis demonstrated that the nomogram was clinically useful. The nomogram presented in this study incorporates BMI, blood pressure, uterine artery ultrasound parameters, and serological indicators and can be conveniently used to facilitate the individualized prediction of preeclampsia.
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