Use of selective serotonin reuptake inhibitors in pregnancy and cardiac malformations: a propensity-score matched cohort in CPRD

Abstract

Purpose: Research on the association of maternal selective serotonin reuptake inhibitor (SSRI) use and cardiac malformations in the offspring has yielded conflicting findings. We therefore sought to further investigate the association using data from a large population-based cohort in the UK.

Methods: The study population consisted of 149 464 pregnancies ending in a live birth between January/1996 and November/2010 from the Clinical Practice Research Datalink's Mother Baby Link. We created propensity-score matched cohorts of first-trimester SSRI users who did not use other antidepressants in the same gestational period ('SSRI users', n=3046) and non-antidepressant users (no use from the 3 months before pregnancy through the second trimester of pregnancy, 'non-users'; n=8991). Weighted logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI) of cardiac malformations overall and septal defects diagnosed in the first year of life, or in the first 6 years of life.

Results: Sixteen infants with cardiac malformations were identified among SSRI users; 10 of them were septal defects. Among non-users, there were 48 infants with cardiac malformations, 26 of whom had septal defects. The OR (95% CI) for cardiac malformations was 1.00 (0.50; 2.00), and for septal defects was 1.15 (0.46; 2.87). Results were similar for cardiac malformations diagnosed in the first 6 years of life, and in several sensitivity analyses that were also implemented.

Conclusions: The results of this study are most compatible with no association between maternal use of SSRIs in early pregnancy and cardiac malformations or septal defects in the offspring. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Keywords: SSRIS; congenital abnormalities; heart defects; mother-baby link; pharmacoepidemiology; propensity score; weighted logistic regression.