{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T17:16:12Z","timestamp":1788542172899,"version":"build-2803163510"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007277","name":"The Icahn School of Medicine at Mount Sinai","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007277","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Postpartum hemorrhage (PPH) remains a leading cause of preventable maternal mortality in the United States. We sought to develop a novel risk assessment tool and compare its accuracy to tools used in current practice.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>We used a PPH digital phenotype that we developed and validated previously to identify 6639 PPH deliveries from our delivery cohort (N\u2009=\u200970\u2009948). Using a vast array of known and potential risk factors extracted from electronic medical records available prior to delivery, we trained a gradient boosting model in a subset of our cohort. In a held-out test sample, we compared performance of our model with 3 clinical risk-assessment tools and 1 previously published model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Our 24-feature model achieved an area under the receiver-operating characteristic curve (AUROC) of 0.71 (95% confidence interval [CI], 0.69-0.72), higher than all other tools (research-based AUROC, 0.67 [95% CI, 0.66-0.69]; clinical AUROCs, 0.55 [95% CI, 0.54-0.56] to 0.61 [95% CI, 0.59-0.62]). Five features were novel, including red blood cell indices and infection markers measured upon admission. Additionally, we identified inflection points for vital signs and labs where risk rose substantially. Most notably, patients with median intrapartum systolic blood pressure above 132\u2009mm Hg had an 11% (95% CI, 8%-13%) median increase in relative risk for PPH.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We developed a novel approach for predicting PPH and identified clinical feature thresholds that can guide intrapartum monitoring for PPH risk. These results suggest that our model is an excellent candidate for prospective evaluation and could ultimately reduce PPH morbidity and mortality through early detection and prevention.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/jamia\/ocab161","type":"journal-article","created":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T15:12:29Z","timestamp":1627312349000},"page":"296-305","source":"Crossref","is-referenced-by-count":38,"title":["Improving postpartum hemorrhage risk prediction using longitudinal electronic medical records"],"prefix":"10.1093","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6987-1435","authenticated-orcid":false,"given":"Amanda B","family":"Zheutlin","sequence":"first","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luciana","family":"Vieira","sequence":"additional","affiliation":[{"name":"Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan A","family":"Shewcraft","sequence":"additional","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shilong","family":"Li","sequence":"additional","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zichen","family":"Wang","sequence":"additional","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emilio","family":"Schadt","sequence":"additional","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan","family":"Gross","sequence":"additional","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"},{"name":"Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siobhan M","family":"Dolan","sequence":"additional","affiliation":[{"name":"Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA"},{"name":"Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joanne","family":"Stone","sequence":"additional","affiliation":[{"name":"Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric","family":"Schadt","sequence":"additional","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"},{"name":"Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6746-4297","authenticated-orcid":false,"given":"Li","family":"Li","sequence":"additional","affiliation":[{"name":"Sema4, Stamford, Connecticut, USA"},{"name":"Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"issue":"6","key":"2022011313562367000_ocab161-B1","doi-asserted-by":"crossref","first-page":"e323","DOI":"10.1016\/S2214-109X(14)70227-X","article-title":"Global causes of maternal death: a WHO systematic analysis","volume":"2","author":"Say","year":"2014","journal-title":"Lancet Glob 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