{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T18:10:11Z","timestamp":1755886211721,"version":"3.44.0"},"reference-count":50,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00c3fico e Tecnol\u00c3\u00b3gico","doi-asserted-by":"publisher","award":["445881\/2020-8"],"award-info":[{"award-number":["445881\/2020-8"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006182","name":"Funda\u00c3\u00a7\u00c3\u00a3o de Amparo \u00c3\u00a0 Pesquisa e Inova\u00c3\u00a7\u00c3\u00a3o do Esp\u00c3rito Santo","doi-asserted-by":"publisher","award":["007\/2021"],"award-info":[{"award-number":["007\/2021"]}],"id":[{"id":"10.13039\/501100006182","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["INV-027961"],"award-info":[{"award-number":["INV-027961"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Objective<\/jats:title>\n<jats:p>To predict the actual number of COVID-19 cases in Brazilian pregnant and postpartum women diagnosed with Severe Acute Respiratory Syndrome using a predictive model created based on data from Brazilian database.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>This is a cross-sectional study with pregnant and postpartum women diagnosed with Severe Acute Respiratory Syndrome (SARS) between January 2016 and November 2021 in Brazil. Patients were divided into two groups (COVID-19 and non-COVID-19) for comparative analysis, and a predictive model was constructed to classify cases without a defined causative agent.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Main outcome measures<\/jats:title>\n<jats:p>Estimated number of COVID cases in obstetric patients with SARS and no defined agent.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Results<\/jats:title>\n<jats:p>38,774 pregnant and postpartum women diagnosed with SARS were identified and categorized by date and causative agent. Women in the COVID-19 group (19.138) were older (29.86\u2009\u00b1\u20097.20 years), self-reported more frequently as non-white race (50.9%), and more often had educational status marked as blank or ignored (29.6% and 26.9%, respectively) compared to the Other confirmed agents\u2019 group (2.233). The groups differed in all presented variables, and patients in the COVID-19 group were diagnosed more often in the third trimester of pregnancy or in the postpartum period. Using the XGBoost model, 13,978 cases of SARS with undefined etiology from 2020 and 2021 were reclassified: 13,799 (98.7%) as predicted COVID-19 and 179 (1.3%) as predicted non-COVID-19.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec005\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>The number of COVID-19 cases and deaths in the obstetric population were even higher than reported by authorities, indicating a significant impact on the maternal mortality ratio during this period.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0330375","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:28:04Z","timestamp":1755883684000},"page":"e0330375","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unveiling the hidden burden of COVID-19 in Brazil\u2019s obstetric population with severe acute respiratory syndrome: A machine learning model"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2150-6612","authenticated-orcid":true,"given":"Veridiana Freire","family":"Franco","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tatiana Assun\u00e7\u00e3o","family":"Zaccara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ornella Scardua","family":"Ferreira","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafaela Alkmin","family":"da Costa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Agatha Sacramento","family":"Rodrigues","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rossana Pulcinelli","family":"Francisco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"pone.0330375.ref001","doi-asserted-by":"crossref","DOI":"10.1590\/0102-311X00126013","article-title":"Assist\u00eancia pr\u00e9-natal no Brasil","volume":"30","author":"EF Viellas","year":"2014","journal-title":"Cad Saude Publica"},{"key":"pone.0330375.ref002","unstructured":"Hist\u00f3rico da pandemia de COVID-19. 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