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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8874392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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