Your browser doesn't support javascript.
COVID-19 Vaccination during Pregnancy: A Structured Electronic Medical Record Data Study
Value in Health ; 26(6 Supplement):S201, 2023.
Article Dans Anglais | EMBASE | ID: covidwho-20238573
ABSTRACT

Objectives:

To compare pregnancy loss rates, preterm birth rates and gestational age at delivery in women vaccinated against COVID-19 during pregnancy vs. those unvaccinated. Method(s) Data were captured from Dorsata Prenatal, an electronic medical record (EMR) system that captures obstetrical data for tens of thousands of pregnancies annually. Patients who delivered between February 11, 2021-June 2, 2022, were included. The vaccinated group included women who had at least one COVID-19 vaccination documented in their EMR between 30 days prior to pregnancy and delivery. The unvaccinated group included women without a COVID-19 vaccination documented. The primary outcome measure was gestational age (GA) at delivery. We analyzed the data using chi-square tests, with significance set at p<0.01. Result(s) A total of 51,994 pregnant women were identified-7,947 (15.3%) in the vaccinated group and 44,047 (84.7%) in the unvaccinated group. Vaccination rate varied by race (Asian 19.7%;White 17.3%;Black 11.2%, P<0.001), ethnicity (Latino 8.6%;Not-Latino 18.7%;P<0.001), marital status (Married 19.2%;Single 8.8%;P<0.001), mother's age (>=35 years 20.0%;<35 years 14.2%;P<0.001), and region (Northeast 19.2%;South 15.2%;West 9.1%;P<0.001). The vaccinated group had significantly lower rate of preterm delivery (Gestational Age [GA]<37 weeks;vaccinated 7.8% vs. unvaccinated 9.6%;P<0.001), and significantly lower rates of pregnancy loss (GA<20 weeks;vaccinated 1.1% vs. unvaccinated 4.1%;P<0.001). Conclusion(s) This is one of the largest real-world studies to date in women who received the COVID-19 vaccination during pregnancy. Vaccination rates varied significantly across race/ethnicity. Vaccinated patients had lower preterm delivery and pregnancy loss rates compared with unvaccinated patients.Copyright © 2023
Mots clés

Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: EMBASE Type d'étude: Étude pronostique Les sujets: Vaccins langue: Anglais Revue: Value in Health Année: 2023 Type de document: Article

Documents relatifs à ce sujet

MEDLINE

...
LILACS

LIS


Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: EMBASE Type d'étude: Étude pronostique Les sujets: Vaccins langue: Anglais Revue: Value in Health Année: 2023 Type de document: Article