SynthesisPloS one2020
Systematic review of prediction models for gestational hypertension and preeclampsia.
Synthesis in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 4 of them syntheses that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
52 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- 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
- Evaluation of reporting quality of cohort studies using real-world data based on RECORD: systematic review.BMC medical research methodology · 2023Pooled it
- American College of Cardiology and American Heart Association blood pressure categories-a systematic review of the relationship with adverse pregnancy outcomes in the first half of pregnancy.American journal of obstetrics and gynecology · 2023Pooled it
- The prognostic utility of soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PIGF) biomarkers for predicting preeclampsia: a secondary analysis of data from the INSPIRE trial.BMC pregnancy and childbirth · 2022Trial
- Effects of Low-Dose Aspirin Combined with Vitamin E on the Incidence of Intrauterine Growth Restriction and Hemorheological Indexes of Pregnant Women in Patients with Gestational Hypertension.Computational and mathematical methods in medicine · 2022Trial
- 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
- Periodontitis Prediction Model Using Linked Electronic Health and Dental Records.JDR clinical and translational research · 2026Article
- A First-Trimester Serum Proteomic Signature for Early Prediction of Preeclampsia: Integrated Untargeted and Targeted Mass Spectrometry with Machine Learning.Life (Basel, Switzerland) · 2026Article
- Extracellular vesicles in pregnancy-related disorders: from mechanisms to clinical implications.Science China. Life sciences · 2026Review
- Machine Learning and Blood-Targeted Proteomics Enable Early Prediction and Etiological Discrimination of Hypertensive Pregnancy Disorders.International journal of molecular sciences · 2026Article
- Development and validation of a lasso-logistic regression-based risk prediction model for retinopathy in patients with hypertensive disorders of pregnancy.Frontiers in cardiovascular medicine · 2026Article
- Diagnostic Gap in Rural Maternal Health: Initial Validation of a Parsimonious Clinical Model for Hypertensive Disorders of Pregnancy in a Honduran Hospital.Diagnostics (Basel, Switzerland) · 2026Article
- PRESHA - Preventing severe hypertensive adverse events in pregnancy and childbirth: a study protocol for establishing a prospective cohort study and biobank in urban Tanzania.Frontiers in global women's health · 2026Article
- Machine learning-based management of hypertensive disorders in pregnancy: analysis of differences in key risk factors between gestational hypertension and pre-eclampsia and construction of a pre-eclampsia prediction model.European journal of medical research · 2025Article
- Liensinine attenuates inflammatory response and oxidative stress by activation of Nrf2/HO- 1 signaling in L-NAME-induced gestational hypertension.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Development and validation of a predictive model for preeclampsia: a retrospective cohort study.Archives of gynecology and obstetrics · 2025Article
- Predicting complications in hypertensive disorders of pregnancy: external validation of a prognostic model for adverse perinatal outcomes.AJOG global reports · 2025Article
- First trimester circulating miR-208b-3p and miR-26a-1-3p are relevant to the prediction of gestational hypertension.BMC pregnancy and childbirth · 2025Article
- Changes of maternal carotid artery elasticity in patients with pregnancy concurred with hypertension.Archives of gynecology and obstetrics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPrediction models for gestational hypertension and preeclampsia have been developed with data and assumptions from developed countries. Their suitability and application for low resource settings have not been tested. This review aimed to identify and assess the methodological quality of prediction models for gestational hypertension and pre-eclampsia with reference to their application in low resource settings.
methodsUsing combinations of keywords for gestational hypertension, preeclampsia and prediction models seven databases were searched to identify prediction models developed with maternal data obtained before 20 weeks of pregnancy and including at least three predictors (Prospero registration CRD 42017078786). Prediction model characteristics and performance measures were extracted using the CHARMS, STROBE and TRIPOD checklists. The National Institute of Health quality assessment tools for observational cohort and cross-sectional studies were used for study quality appraisal.
resultsWe retrieved 8,309 articles out of which 40 articles were eligible for review. Seventy-seven percent of all the prediction models combined biomarkers with maternal clinical characteristics. Biomarkers used as predictors in most models were pregnancy associated plasma protein-A (PAPP-A) and placental growth factor (PlGF). Only five studies were conducted in a low-and middle income country.
conclusionsMost of the studies evaluated did not completely follow the CHARMS, TRIPOD and STROBE guidelines in prediction model development and reporting. Adherence to these guidelines will improve prediction modelling studies and subsequent application of prediction models in clinical practice. Prediction models using maternal characteristics, with good discrimination and calibration, should be externally validated for use in low and middle income countries where biomarker assays are not routinely available.
Indexed as
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.