Using graph learning to understand adverse pregnancy outcomes and stress pathways
Autoři:
Octavio Mesner aff001; Alex Davis aff001; Elizabeth Casman aff001; Hyagriv Simhan aff003; Cosma Shalizi aff002; Lauren Keenan-Devlin aff004; Ann Borders aff004; Tamar Krishnamurti aff001
Působiště autorů:
Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, United States of America
aff001; Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, United States of America
aff002; Magee-Women’s Research Institute, Pittsburgh, PA, United States of America
aff003; Northshore University Health System, Evanston, Illinois, United States of America
aff004; Department of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
aff005
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223319
Souhrn
To identify pathways between stress indicators and adverse pregnancy outcomes, we applied a nonparametric graph-learning algorithm, PC-KCI, to data from an observational prospective cohort study. The Measurement of Maternal Stress study (MOMS) followed 744 women with a singleton intrauterine pregnancy recruited between June 2013 and May 2015. Infant adverse pregnancy outcomes were prematurity (<37 weeks' gestation), infant days spent in hospital after birth, and being small for gestational age (percentile gestational weight at birth). Maternal adverse pregnancy outcomes were pre-eclampsia, gestational diabetes, and gestational hypertension. PC-KCI replicated well-established pathways, such as the relationship between gestational weeks and preterm premature rupture of membranes. PC-KCI also identified previously unobserved pathways to adverse pregnancy outcomes, including 1) a link between hair cortisol levels (at 12–21 weeks of pregnancy) and pre-eclampsia; 2) two pathways to preterm birth depending on race, with one linking Hispanic race, pre-gestational diabetes and gestational weeks, and a second pathway linking black race, hair cortisol, preeclampsia, and gestational weeks; and 3) a relationship between maternal childhood trauma, perceived social stress in adulthood, and low weight for gestational age. Our approach confirmed previous findings and identified previously unobserved pathways to adverse pregnancy outcomes. It presents a method for a global assessment of a clinical problem for further study of possible causal pathways.
Klíčová slova:
Hypertensive disorders in pregnancy – Infants – Preeclampsia – Pregnancy – Preterm birth – Psychological stress
Zdroje
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PLOS One
2019 Číslo 9
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