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Systematic review of prediction models for gestational hypertension and preeclampsia.

ABSTRACT:

Introduction

Prediction 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.

Methods

Using 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.

Results

We 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.

Conclusions

Most 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.

SUBMITTER: Antwi E

PROVIDER: S-EPMC7173928 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe association of gestational hypertension (GH) and preeclampsia (PE) with offspring adiposity outcomes had controversial results in different studies.ObjectiveWe conducted a systematic review and meta-analysis to evaluate the relationship between maternal GH/PE and offspring adiposity outcomes.Search strategyStudies were identified in PubMed, Embase, and Cochrane databases, with keywords including "gestational hypertension", "preeclampsia", "offspring", "weight", "cohort study", etc., without year restriction. This study was registered with PROSPERO, CRD42022292084.Selection criteriaWe set the selection criteria for six aspects: population, outcome, time frame, study design, and availability. For the studies included in the meta-analysis, we required the potential confounders in these studies have been adjusted.Data collection and analysisTwo reviewers independently evaluated the data from the included studies. The meta-analyses included mean differences, regression coefficients, and corresponding 95% confidence intervals. Results were performed using RevMan software (version 5.4; Cochrane Collaboration). Heterogeneity among the included studies was assessed using the I2 statistic.Main resultsA total of 16 studies were included in our review, 15 of which were evaluated as high quality. In all offspring, during the early life (28 days-36 months), GH/PE exposure was found to be not or inversely associated with offspring obesity, then become positively associated at larger ages (3-19 years old). In offspring with adverse birth outcomes, the maternal GH/PE-exposed group had a lower weight in the short term (28 days to 18 months), but there was a trend of rapid weight gain as they grew older, compared with the non-exposed group. The meta-analysis showed that the BMI of the female offspring in the maternal PE-exposed group was significantly higher than that of the non-exposed offspring (MD=1.04, 95% CI: 0.67~1.42, P < 0.05).ConclusionsThe systematic review suggested that maternal exposure to de novo hypertension disorders of pregnancy (HDP) was associated with obesity in offspring, extending from early childhood to adolescence. The meta-analysis showed that PE was associated with higher BMI in female offspring. More studies are needed to conduct stratified analyses by PE/GH, the severity of HDP, or gender.Systematic review registrationPROSPERO, identifier CRD42022292084.

Project description:In the face of the obesity epidemic around the world, attention should be focused on the role of maternal obesity in the development of pregnancy. The purpose of this analysis was to evaluate the prediction of preeclampsia (PE) and isolated gestational hypertension (GH) for a number of maternal factors, in order to investigate the importance of pre-pregnancy obesity (body mass index, BMI ≥ 30 kg/m2), compared to other risk factors (e.g., prior PE, pregnancy weight gain (GWG), infertility treatment, interpregnancy interval, family history, the lack of vitamin supplementation, urogenital infection, and socioeconomic factors). In total, 912 women without chronic diseases were examined in a Polish prospective cohort of women with a single pregnancy (recruited in 2015-2016). Separate analyses were performed for the women who developed GH (n = 113) vs. 775 women who remained normotensive, as well as for those who developed PE (n = 24) vs. 775 controls. The probability of each disease was assessed for the base prediction model (age + primiparity) and for the model extended by one (test) variable, using logistic regression. Three measures were used to assess the prediction: area under curve (AUC) of the base and extended model, integrated discrimination improvement (IDI) (the index shows the difference between the value of the mean change in the predicted probability between the group of sick and healthy women when a new factor is added to the model), and net reclassification improvement (NRI) (the index focuses on the reclassification table describing the number of women in whom an upward or downward shift in the disease probability value occurred after a new factor had been added, including results for healthy and sick women). In the GH prediction, AUC increased most strongly when we added BMI (kg/m2) as a continuous variable (AUC = 0.716, p < 0.001) to the base model. The highest IDI index was obtained for prior GH/PE (IDI = 0.068, p < 0.001). The addition of BMI as a continuous variable or BMI ≥ 25 kg/m2 improved the classification for healthy and sick women the most (NRI = 0.571, p < 0.001). In the PE prediction, AUC increased most strongly when we added BMI categories (AUC = 0.726, p < 0.001) to the base model. The highest IDI index was obtained for prior GH/PE (IDI = 0.050, p = 0.080). The addition of BMI categories improved the classification for healthy and sick women the most (NRI = 0.688; p = 0.001). After summing up the results of three indexes, the probability of hypertension in pregnancy was most strongly improved by BMI, including BMI ≥ 25 kg/m2 for the GH prediction, and BMI ≥ 30 kg/m2 for the PE prediction. Main conclusions: Pre-pregnancy BMI was the most likely factor to increase the probability of developing hypertension in pregnancy, compared to other risk factors. Hierarchies of PE and GH risk factors may suggest different (or common) mechanisms of their development.