{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:29:25Z","timestamp":1767659365785,"version":"3.48.0"},"reference-count":4,"publisher":"Georg Thieme Verlag KG","issue":"02","funder":[{"name":"National Institutes of Health T32 Training Grant in Perinatal Epidemiology at the University of Pennsylvania","award":["T32HD007440"],"award-info":[{"award-number":["T32HD007440"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Am J Perinatol"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The clinically-modified obstetric comorbidity index (OB-CMI) is a comorbidity-based scoring system that has been validated to predict severe maternal morbidity (SMM) in a single tertiary, academic hospital using an internal SMM definition. We aimed to validate the OB-CMI for the prediction of SMM as defined by the CDC during delivery admissions across a diverse health system.<\/jats:p>\n                  <jats:p>This is a retrospective cohort study evaluating all deliveries in a large health system encompassing academic and community hospitals. Data from 2019 to 2021 were extracted from the electronic health record (EHR) and validated with chart review. An OB-CMI score was calculated for each patient using established diagnosis codes and EHR data. The primary outcome was nontransfusion SMM (defined by the CDC) during the delivery admission. Patient characteristics were evaluated by the hospital, and hospital-specific receiver-operator characteristic (ROC) curves were constructed and compared.<\/jats:p>\n                  <jats:p>In total, 42,130 deliveries were included with significant differences in all demographic, clinical, and obstetric characteristics across the hospitals including age, BMI, race\/ethnicity, insurance type, preterm birth, and preeclampsia rates. Median OB-CMI score and rate of elevated OB-CMI score (\u22656) were also significantly different. ROC curves for OB-CMI and SMM for each hospital are noted in the figure with an area under the curve range from 0.77 to 0.83, and no significant differences across hospitals (p\u2009=\u20090.32).<\/jats:p>\n                  <jats:p>In a large cohort of patients delivering across a diverse hospital system, the clinical OB-CMI score similarly predicted SMM despite differences in demographic and clinical characteristics among the hospitals. This validation of the OB-CMI supports the use of this scoring system in variegated clinical settings, which can inform widescale uptake and clinical integration of OB-CMI scoring to improve obstetric risk stratification.<\/jats:p>","DOI":"10.1055\/a-2572-1727","type":"journal-article","created":{"date-parts":[[2025,4,2]],"date-time":"2025-04-02T19:50:20Z","timestamp":1743623420000},"page":"279-282","source":"Crossref","is-referenced-by-count":0,"title":["External Validation of the Clinical Obstetric Comorbidity Index across a Diverse Health System"],"prefix":"10.1055","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7932-1987","authenticated-orcid":false,"given":"Adina R.","family":"Kern-Goldberger","sequence":"additional","affiliation":[{"name":"Cleveland Clinic Foundation, Ob\/Gyn and Women's Health Institute, Cleveland, Ohio"},{"name":"Department of Quantitative Health Sciences, Cleveland Clinic Lerner Research Institute, Cleveland, Ohio"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sindhu K.","family":"Srinivas","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, Pregnancy and Perinatal Research Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania"},{"name":"Leonard Davis Institute, University of Pennsylvania, Philadelphia, Pennsylvania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael O.","family":"Harhay","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lisa D.","family":"Levine","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, Pregnancy and Perinatal Research Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania"},{"name":"Leonard Davis Institute, University of Pennsylvania, Philadelphia, Pennsylvania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"194","published-online":{"date-parts":[[2025,5,6]]},"reference":[{"issue":"03","key":"ref1","doi-asserted-by":"crossref","first-page":"271.e1","DOI":"10.1016\/j.ajog.2019.06.025","article-title":"A comorbidity-based screening tool to predict severe maternal morbidity at the time of delivery","volume":"221","author":"S R Easter","year":"2019","journal-title":"Am J Obstet Gynecol"},{"issue":"03","key":"ref3","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1097\/AOG.0000000000004022","article-title":"An expanded obstetric comorbidity scoring system for predicting severe maternal morbidity","volume":"136","author":"S A Leonard","year":"2020","journal-title":"Obstet Gynecol"},{"issue":"03","key":"ref4","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","volume":"44","author":"E R DeLong","year":"1988","journal-title":"Biometrics"},{"issue":"10","key":"ref5","doi-asserted-by":"crossref","first-page":"e2234924","DOI":"10.1001\/jamanetworkopen.2022.34924","article-title":"Comparison of natural language processing of clinical notes with a validated risk-stratification tool to predict severe maternal morbidity","volume":"5","author":"M A Clapp","year":"2022","journal-title":"JAMA Netw Open"}],"container-title":["American Journal of Perinatology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2572-1727.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T23:41:34Z","timestamp":1767656494000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2572-1727"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,2]]},"references-count":4,"journal-issue":{"issue":"02","published-online":{"date-parts":[[2026,1,5]]},"published-print":{"date-parts":[[2026,1]]}},"URL":"https:\/\/doi.org\/10.1055\/a-2572-1727","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["0735-1631","1098-8785"],"issn-type":[{"type":"print","value":"0735-1631"},{"type":"electronic","value":"1098-8785"}],"subject":[],"published-other":{"date-parts":[[2025,4,2]]},"published":{"date-parts":[[2025,4,2]]}}}