Background: Preeclampsia is a severe, multisystem complication that affects 2%-5% of pregnancies, and is a leading cause of fetal and maternal morbidity and mortality worldwide. Preeclampsia may have devastating results on maternal health and may affect offspring's immediate and long-term health. Previous studies have examined the impact of maternal preeclampsia on the long-term health outcomes of offspring, many of these studies have been limited by confounding factors that could bias the results. The classic way of analyzing the relationship between maternal preeclampsia and long-term infectious morbidity of the offspring, which typically involves comparing the rates of infectious disease hospitalization between the exposed and unexposed groups, may not be sufficient due to the potential influence of unmeasured confounding factors.
Objective: To study the association between maternal preeclampsia and long-term offspring infectious morbidity, while employing sibling-matched analysis to maximize confounder control.
Study Design: A retrospective cohort was conducted, including parous women, who were diagnosed with preeclampsia in one pregnancy. A sibling-matched analysis was performed, so that one sibling was, and the other was not, prenatally exposed to maternal preeclampsia. Incidence of the offspring hospitalization with infectious morbidities were compared between the siblings, as well as the time to first hospitalization with such a diagnosis. Multivariable survival analysis was performed to adjust for confounding variables.
Results: Offspring of mothers with preeclampsia (n = 4272) were significantly (p < 0.001) at a higher risk for long-term infectious hospitalization compared to offspring of mothers without preeclampsia (n = 4272), with a hazard ratio of 1.324 (95% CI 1.168-1.503) after adjusting for maternal age, gestational age, and mode of delivery.
Conclusions: Offspring born following pregnancies complicated with preeclampsia are at increased risk for infectious morbidity, even while rigorously adjusting for confounders in a sibling analysis.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11722688 | PMC |
http://dx.doi.org/10.1111/aji.70041 | DOI Listing |
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