Franco Veridiana Freire, Zaccara Tatiana Assunção, Ferreira Ornella Scardua, da Costa Rafaela Alkmin, Rodrigues Agatha Sacramento, Francisco Rossana Pulcinelli
Departamento de Obstetricia e Ginecologia da Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, Brazil.
Divisão de Clínica Obstétrica do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, Brazil.
PLoS One. 2025 Aug 22;20(8):e0330375. doi: 10.1371/journal.pone.0330375. eCollection 2025.
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.
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.
Estimated number of COVID cases in obstetric patients with SARS and no defined agent.
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 ± 7.20 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' 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.
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.
利用基于巴西数据库数据创建的预测模型，预测巴西诊断为严重急性呼吸综合征的孕妇和产后妇女中新型冠状病毒肺炎（COVID-19）的实际病例数。
这是一项横断面研究，研究对象为2016年1月至2021年11月在巴西诊断为严重急性呼吸综合征（SARS）的孕妇和产后妇女。将患者分为两组（COVID-19组和非COVID-19组）进行比较分析，并构建预测模型对病因未明的病例进行分类。
SARS且病因未明的产科患者中COVID病例的估计数。
共识别出38774例诊断为SARS的孕妇和产后妇女，并按日期和病原体进行分类。与其他确诊病原体组（2233例）相比，COVID-19组（19138例）的女性年龄更大（29.86±7.20岁），自我报告为非白人种族的频率更高（50.9%），教育状况标记为空白或被忽略的情况更常见（分别为29.6%和26.9%）。两组在所有呈现的变量上均存在差异，COVID-19组的患者更多在妊娠晚期或产后被诊断。使用XGBoost模型，对2020年和2021年病因未明的13978例SARS病例进行重新分类：13799例（98.7%）被预测为COVID-19，179例（1.3%）被预测为非COVID-19。
产科人群中COVID-19的病例数和死亡数甚至高于当局报告的数字，表明在此期间对孕产妇死亡率有重大影响。
