{"doi":"10.1038/s41598-021-93413-3","title":"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 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.","journal":"Scientific Reports","year":2021,"id":176541,"datarank":0.8191128510479018,"base_score":3.091042453358316,"endowment":3.091042453358316,"self_citation_contribution":0.4636563680037475,"citation_network_contribution":0.3554564830441543,"self_endowment_contribution":0.4636563680037475,"citer_contribution":0.3554564830441543,"corpus_percentile":null,"corpus_rank":null,"citation_count":21,"citer_count":19,"citers_with_citation_signal":11,"citers_with_endowment":11,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9561,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":419834,"name":"Andrew Sparks","orcid":"0000-0001-8668-4105","position":1,"is_corresponding":false},{"id":719199,"name":"Jaclyn M. Phillips","orcid":"0000-0002-2439-0686","position":2,"is_corresponding":false},{"id":719942,"name":"Chinelo Onyilofor","orcid":null,"position":3,"is_corresponding":false},{"id":419837,"name":"Homa K. Ahmadzia","orcid":"0000-0003-0341-1086","position":4,"is_corresponding":false},{"id":719941,"name":"Emer L. Colalillo","orcid":null,"position":0,"is_corresponding":true}],"reference_count":29,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:47:23.605867Z","pmid":"34282160","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}