Diguisto Caroline, Ancel Pierre-Yves, Seco Aurélien, Baunot Nathalie, Caze Cecile, Crenn-Hébert Catherine, Dupont Corinne, Garabedian Charles, Lebeaux Cécile, Le Ray Camille, Letouzey Mathilde, Lorthe Elsa, Marrer Emilie, Rouger Valérie, Vayssière Christophe, Vauloup Fellous Christelle, Bonnet Marie-Pierre, Deneux-Tharaux Catherine
Obstetrical, Perinatal and Pediatric Life Course Epidemiology (OPPALE Team), Centre de Recherche Epidémiologie et StatistiqueS (CRESS), INSERM, INRAE, Université Paris Cité and Université Sorbonne Paris Nord, Paris, France.
Department of Obstetrics, Centre Hospitalier Régional Universitaire et Faculté de Médecine de Tours, Tours, France.
Paediatr Perinat Epidemiol. 2025 Jul;39(5):477-494. doi: 10.1111/ppe.70028. Epub 2025 May 21.
Population-based data are needed to reliably assess the impact of SARS-CoV-2 infection during pregnancy.
To estimate the population-based incidence of SARS-CoV-2 infection and its severe forms in the obstetric population, identify risk factors of severe SARS-CoV-2 infection (severe COVID-19) and describe delivery, maternal and neonatal outcomes by disease severity, using a definition of severity based on organ dysfunction.
A prospective population-based study conducted over the three first pandemic waves between March 2020 and April 2021 in 281 maternity hospitals in six French regions included all women with SARS-CoV-2 infection during pregnancy or within 7 days post-partum, whether symptomatic or not, hospitalised or not. Severe COVID-19 forms were defined a priori using clinical, biological and management criteria of organ dysfunction. We calculated infection and severe infection rates and studied associations between sociodemographic, medical and pregnancy characteristics and severe COVID-19 by univariate and multivariate modified Poisson regression modelling.
From a population of 385,214 deliveries in the participating regions, 6015 women with SARS-CoV-2 infection were identified, including 337 severe cases. The rates of severe COVID-19 were 1.1, 0.9 and 3.6 per 1000 deliveries during the first, second and third pandemic waves, respectively, and the proportions of severe COVID-19 were 8.6%, 3.4% and 9.3%, respectively. On multivariate analysis, the risk of severe COVID-19 was associated with younger and older age, migrant status, living with > 4 people, overweight or obesity, chronic hypertension or diabetes and infection ≥ 22 weeks of gestation rather than earlier in pregnancy. Neonatal morbidity occurred mostly with severe maternal infection.
Using an organ-based definition of severity and population-based data, rates of severe COVID-19 appeared lower than in previous studies. A permanent perinatal surveillance system is needed to assess efficiently and rapidly the impact of future pandemics.
需要基于人群的数据来可靠评估孕期感染严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的影响。
估计产科人群中SARS-CoV-2感染及其严重形式的基于人群的发病率,确定严重SARS-CoV-2感染(重症冠状病毒病19,即重症COVID-19)的危险因素,并根据基于器官功能障碍的严重程度定义,按疾病严重程度描述分娩情况、孕产妇和新生儿结局。
2020年3月至2021年4月期间,在法国六个地区的281家妇产医院进行了一项基于人群的前瞻性研究,纳入了所有在孕期或产后7天内感染SARS-CoV-2的妇女,无论有无症状、是否住院。重症COVID-19形式根据器官功能障碍的临床、生物学和管理标准预先定义。我们计算了感染率和严重感染率,并通过单变量和多变量修正泊松回归模型研究了社会人口统计学、医学和妊娠特征与重症COVID-19之间的关联。
在参与研究的地区的385214例分娩人群中,确定了6015例感染SARS-CoV-2的妇女,其中包括337例重症病例。在第一、第二和第三波疫情期间,重症COVID-19的发病率分别为每1000例分娩1.1例、0.9例和3.6例,重症COVID-19的比例分别为8.6%、3.4%和9.3%。多变量分析显示,重症COVID-19的风险与年龄较小和较大、移民身份、与超过4人同住、超重或肥胖、慢性高血压或糖尿病以及妊娠≥22周时感染而非孕期较早感染有关。新生儿发病主要发生在孕产妇严重感染的情况下。
使用基于器官的严重程度定义和基于人群的数据,重症COVID-19的发病率似乎低于先前的研究。需要一个永久性的围产期监测系统来有效、快速地评估未来大流行的影响。