Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders

Eleanor P. Thong, Drishti P. Ghelani, Pamada Manoleehakul, Anika Yesmin, Kaylee Slater, Rachael Taylor, Clare Collins, Melinda Hutchesson, Siew S. Lim, Helena J. Teede, Cheryce L. Harrison, Lisa Moran, Joanne Enticott

Research output: Contribution to journalReview ArticleResearchpeer-review

17 Citations (Scopus)

Abstract

Cardiovascular disease, especially coronary heart disease and cerebrovascular disease, is a leading cause of mortality and morbidity in women globally. The development of cardiometabolic conditions in pregnancy, such as gestational diabetes mellitus and hypertensive disorders of preg-nancy, portend an increased risk of future cardiovascular disease in women. Pregnancy therefore represents a unique opportunity to detect and manage risk factors, prior to the development of cardiovascular sequelae. Risk prediction models for gestational diabetes mellitus and hypertensive disorders of pregnancy can help identify at-risk women in early pregnancy, allowing timely intervention to mitigate both short-and long-term adverse outcomes. In this narrative review, we outline the shared pathophysiological pathways for gestational diabetes mellitus and hypertensive disorders of pregnancy, summarise contemporary risk prediction models and candidate predictors for these conditions, and discuss the utility of these models in clinical application.

Original languageEnglish
Article number55
Number of pages18
JournalJournal of Cardiovascular Development and Disease
Volume9
Issue number2
DOIs
Publication statusPublished - Feb 2022

Keywords

  • Cardiovascular
  • Gestational diabetes
  • Hypertensive disorders of pregnancy
  • Preeclampsia
  • Pregnancy
  • Risk prediction

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