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Sci Rep ; 11(1): 14709, 2021 07 19.
Article in English | MEDLINE | ID: mdl-34282160

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.


Subject(s)
Models, Statistical , Postpartum Hemorrhage/diagnosis , Postpartum Hemorrhage/epidemiology , Blood Transfusion/statistics & numerical data , Cohort Studies , Databases, Factual/statistics & numerical data , Delivery, Obstetric/adverse effects , Female , Humans , Morbidity , Obstetric Labor Complications/diagnosis , Obstetric Labor Complications/epidemiology , Postpartum Hemorrhage/therapy , Pregnancy , Prognosis , Puerperal Disorders/diagnosis , Puerperal Disorders/epidemiology , Research Design , Retrospective Studies , Risk Assessment , Risk Factors , United States/epidemiology
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