1. Pre-conception clinical risk factors differ between spontaneous and indicated preterm birth in a densely phenotyped EHR cohort
- Author
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Costello, Jean M, Takasuka, Hannah, Roger, Jacquelyn, Yin, Ophelia, Tang, Alice, Oskotsky, Tomiko, Sirota, Marina, and Capra, John A
- Subjects
Reproductive Medicine ,Midwifery ,Biomedical and Clinical Sciences ,Health Sciences ,Clinical Research ,Prevention ,Women's Health ,Pregnancy ,Maternal Health ,Cardiovascular ,Health Disparities ,Preterm ,Low Birth Weight and Health of the Newborn ,Pediatric ,Patient Safety ,Perinatal Period - Conditions Originating in Perinatal Period ,2.1 Biological and endogenous factors ,4.1 Discovery and preclinical testing of markers and technologies ,Reproductive health and childbirth ,Good Health and Well Being ,Humans ,Female ,Premature Birth ,Electronic Health Records ,Risk Factors ,Adult ,Cohort Studies ,Infant ,Newborn ,Young Adult ,Maternal Age ,Diagnosis associations ,Electronic health records ,Indicated preterm birth ,Spontaneous preterm birth ,Nursing ,Paediatrics and Reproductive Medicine ,Public Health and Health Services ,Obstetrics & Reproductive Medicine ,Reproductive medicine - Abstract
BackgroundPreterm birth (PTB) is the leading cause of infant mortality. Risk for PTB is influenced by multiple biological pathways, many of which are poorly understood. Some PTBs result from medically indicated labor following complications from hypertension and/or diabetes, while many others are spontaneous with unknown causes. Previously, investigation of potential risk factors has been limited by a lack of data on maternal medical history and the difficulty of classifying PTBs as indicated or spontaneous. Here, we leverage electronic health record (EHR) data (patient health information including demographics, diagnoses, and medications) and a supplemental curated pregnancy database to overcome these limitations. Novel associations may provide new insight into the pathophysiology of PTB as well as help identify individuals who would be at risk of PTB.MethodsWe quantified associations between maternal diagnoses and preterm birth both with and without controlling for maternal age and socioeconomic factors within a University of California, San Francisco (UCSF), EHR cohort with 10,643 births (nterm = 9692, nspontaneous_preterm = 449, nindicated_preterm = 418) and maternal pre-conception diagnoses derived from International Classification of Diseases (ICD) 9 and 10 codes.ResultsThirty diagnoses significantly and robustly (False Discovery Rate (FDR)
- Published
- 2025