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Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity

Obstetric hemorrhage is one of the leading preventable causes of maternal mortality in the United States. Although hemorrhage risk-prediction models exist, there remains a gap in literature describing if these risk-prediction tools can identify composite maternal morbidity. We investigate how well a...

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Autores principales: Colalillo, Emer L., Sparks, Andrew D., Phillips, Jaclyn M., Onyilofor, Chinelo L., Ahmadzia, Homa K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289851/
https://www.ncbi.nlm.nih.gov/pubmed/34282160
http://dx.doi.org/10.1038/s41598-021-93413-3
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author Colalillo, Emer L.
Sparks, Andrew D.
Phillips, Jaclyn M.
Onyilofor, Chinelo L.
Ahmadzia, Homa K.
author_facet Colalillo, Emer L.
Sparks, Andrew D.
Phillips, Jaclyn M.
Onyilofor, Chinelo L.
Ahmadzia, Homa K.
author_sort Colalillo, Emer L.
collection PubMed
description Obstetric hemorrhage is one of the leading preventable causes of maternal mortality in the United States. Although hemorrhage risk-prediction models exist, there remains a gap in literature describing if these risk-prediction tools can identify composite maternal morbidity. We investigate how well an established obstetric hemorrhage risk-assessment tool predicts composite hemorrhage-associated morbidity. We conducted a retrospective cohort analysis of a multicenter database including women admitted to Labor and Delivery from 2016 to 2018, at centers implementing the Association of Women’s Health, Obstetric, and Neonatal Nurses risk assessment tool on admission. A composite morbidity score incorporated factors including obstetric hemorrhage (estimated blood loss ≥ 1000 mL), blood transfusion, or ICU admission. Out of 56,903 women, 14,803 (26%) were categorized as low-risk, 26,163 (46%) as medium-risk and 15,937 (28%) as high-risk for obstetric hemorrhage. Composite morbidity occurred at a rate of 2.2%, 8.0% and 11.9% within these groups, respectively. Medium- and high-risk groups had an increased combined risk of composite morbidity (diagnostic OR 4.58; 4.09–5.13) compared to the low-risk group. This established hemorrhage risk-assessment tool predicts clinically-relevant composite morbidity. Future randomized trials in obstetric hemorrhage can incorporate these tools for screening patients at highest risk for composite morbidity.
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spelling pubmed-82898512021-07-21 Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity Colalillo, Emer L. Sparks, Andrew D. Phillips, Jaclyn M. Onyilofor, Chinelo L. Ahmadzia, Homa K. Sci Rep Article Obstetric hemorrhage is one of the leading preventable causes of maternal mortality in the United States. Although hemorrhage risk-prediction models exist, there remains a gap in literature describing if these risk-prediction tools can identify composite maternal morbidity. We investigate how well an established obstetric hemorrhage risk-assessment tool predicts composite hemorrhage-associated morbidity. We conducted a retrospective cohort analysis of a multicenter database including women admitted to Labor and Delivery from 2016 to 2018, at centers implementing the Association of Women’s Health, Obstetric, and Neonatal Nurses risk assessment tool on admission. A composite morbidity score incorporated factors including obstetric hemorrhage (estimated blood loss ≥ 1000 mL), blood transfusion, or ICU admission. Out of 56,903 women, 14,803 (26%) were categorized as low-risk, 26,163 (46%) as medium-risk and 15,937 (28%) as high-risk for obstetric hemorrhage. Composite morbidity occurred at a rate of 2.2%, 8.0% and 11.9% within these groups, respectively. Medium- and high-risk groups had an increased combined risk of composite morbidity (diagnostic OR 4.58; 4.09–5.13) compared to the low-risk group. This established hemorrhage risk-assessment tool predicts clinically-relevant composite morbidity. Future randomized trials in obstetric hemorrhage can incorporate these tools for screening patients at highest risk for composite morbidity. Nature Publishing Group UK 2021-07-19 /pmc/articles/PMC8289851/ /pubmed/34282160 http://dx.doi.org/10.1038/s41598-021-93413-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Colalillo, Emer L.
Sparks, Andrew D.
Phillips, Jaclyn M.
Onyilofor, Chinelo L.
Ahmadzia, Homa K.
Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
title Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
title_full Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
title_fullStr Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
title_full_unstemmed Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
title_short Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
title_sort obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289851/
https://www.ncbi.nlm.nih.gov/pubmed/34282160
http://dx.doi.org/10.1038/s41598-021-93413-3
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