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A risk factor-based predictive model for new-onset hypertension during pregnancy in Chinese Han women

Yamin Hou1,2, Lin Yun3, Lihua Zhang3

  • 1Department of Cardiology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, 250014, P.R. China.

BMC Cardiovascular Disorders
|April 5, 2020
PubMed

Insights

This study developed a prediction model for new-onset hypertension during pregnancy. The model effectively identifies high-risk pregnancies, enabling early intervention for better maternal and neonatal outcomes.

Area of Science:

  • Obstetrics and Gynecology
  • Cardiovascular Disease in Pregnancy
  • Biomarker Research

Background:

  • Hypertensive disorders of pregnancy (HDP) are a major cause of maternal and neonatal mortality.
  • HDP increases the long-term risk of cardiovascular diseases.
  • Preeclampsia and gestational hypertension are key components of HDP.

Purpose of the Study:

  • To establish a prediction model for pregnant women with new-onset hypertension (de novo hypertension) after 20 weeks of gestation.
  • To guide clinical prediction and treatment strategies for de novo hypertension.
  • To enable early intervention for high-risk pregnancies.

Main Methods:

  • A case-control study involving 117 pregnant women with de novo hypertension and 199 healthy controls.
  • Collection of maternal clinical parameters and biomarkers (homocysteine, cystatin C, uric acid, etc.) between 16-20 weeks gestation.
  • Logistic regression analysis to establish a prediction model.

Main Results:

  • Eleven indicators showed statistically significant differences between groups (P < 0.05).
  • A logistic regression model identified 7 independent predictors for de novo hypertension.
  • The model achieved an area under the curve of 0.884, with 88.0% sensitivity and 75.0% specificity.
  • A scoring system was developed to classify pregnancies into low-risk (≤15.5) and high-risk (>15.5) groups.

Conclusions:

  • The developed regression equation offers a feasible and reliable method for predicting de novo hypertension in pregnancy.
  • Risk stratification allows for targeted early treatment interventions in high-risk populations.
  • This approach can improve maternal and neonatal outcomes by facilitating timely management of hypertension during pregnancy.
Abstract

Keywords:
HomocysteineHypertension, pregnancy inducedPrediction modelRisk factors

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