Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity
Abstract 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 h...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/ba60975536f744a687e4c7987c2fe597 |
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| Sumario: | Abstract 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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