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

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 pregnancy, portend a...

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Autores principales: Thong, Eleanor P., Ghelani, Drishti P., Manoleehakul, Pamada, Yesmin, Anika, Slater, Kaylee, Taylor, Rachael, Collins, Clare, Hutchesson, Melinda, Lim, Siew S., Teede, Helena J., Harrison, Cheryce L., Moran, Lisa, Enticott, Joanne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874392/
https://www.ncbi.nlm.nih.gov/pubmed/35200708
http://dx.doi.org/10.3390/jcdd9020055
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author Thong, Eleanor P.
Ghelani, Drishti P.
Manoleehakul, Pamada
Yesmin, Anika
Slater, Kaylee
Taylor, Rachael
Collins, Clare
Hutchesson, Melinda
Lim, Siew S.
Teede, Helena J.
Harrison, Cheryce L.
Moran, Lisa
Enticott, Joanne
author_facet Thong, Eleanor P.
Ghelani, Drishti P.
Manoleehakul, Pamada
Yesmin, Anika
Slater, Kaylee
Taylor, Rachael
Collins, Clare
Hutchesson, Melinda
Lim, Siew S.
Teede, Helena J.
Harrison, Cheryce L.
Moran, Lisa
Enticott, Joanne
author_sort Thong, Eleanor P.
collection PubMed
description 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 pregnancy, 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.
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spelling pubmed-88743922022-02-26 Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders Thong, Eleanor P. Ghelani, Drishti P. Manoleehakul, Pamada Yesmin, Anika Slater, Kaylee Taylor, Rachael Collins, Clare Hutchesson, Melinda Lim, Siew S. Teede, Helena J. Harrison, Cheryce L. Moran, Lisa Enticott, Joanne J Cardiovasc Dev Dis Review 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 pregnancy, 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. MDPI 2022-02-10 /pmc/articles/PMC8874392/ /pubmed/35200708 http://dx.doi.org/10.3390/jcdd9020055 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Thong, Eleanor P.
Ghelani, Drishti P.
Manoleehakul, Pamada
Yesmin, Anika
Slater, Kaylee
Taylor, Rachael
Collins, Clare
Hutchesson, Melinda
Lim, Siew S.
Teede, Helena J.
Harrison, Cheryce L.
Moran, Lisa
Enticott, Joanne
Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders
title Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders
title_full Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders
title_fullStr Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders
title_full_unstemmed Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders
title_short Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders
title_sort optimising cardiometabolic risk factors in pregnancy: a review of risk prediction models targeting gestational diabetes and hypertensive disorders
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874392/
https://www.ncbi.nlm.nih.gov/pubmed/35200708
http://dx.doi.org/10.3390/jcdd9020055
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