Identification of Prenatal Risk Factors for Brachial Plexus Birth Injury

Background: The most common cause of upper extremity paralysis in infants results from a traction injury to the cervical nerve roots of the brachial plexus during childbirth. These brachial plexus birth injuries (BPBI) occur in 1.5 per 1000 live births and often result in impaired upper extremity function and psychosocial and economic stress on children and families. No cure for BPBI exists so it is imperative to understand prenatal risk factors for BPBI to identify those at greatest risk and guide prevention efforts. However only intrapartum and postpartum obstetric factors have been evaluated and no factors are predictive of BPBI. Maternal demographic geographic socioeconomic and health factors that are identifiable prenatally have not been evaluated making prediction of mothers at risk of delivering an affected infant nearly impossible. Improved understanding of prenatal characteristics predisposing to BPBI including maternal and hospital related factors is necessary to identify those at greatest risk and guide targeted interventions to decrease BPBI. Purpose: The purpose of this project is to identify prenatal characteristics associated with BPBI focusing on maternal and hospital factors. Specifically this project evaluates maternal prenatal demographic socioeconomic and health characteristics that have not previously been evaluated. This project evaluates hospital characteristics associated with other perinatal outcomes but have not been assessed in the context of BPBI. Methods: This project uses the state of California's Office of Statewide Health Planning and Development (OSHPD) linked maternal-infant dataset which contains health information on all live births in California (~ 500 000 per year) from 1991 to 2012 (~11 million) and links infant data for their first year of life with their maternal demographic socioeconomic and health information for 9 months prior to childbirth. Hospital characteristics are also available such as obstetric volume hospital location and frequency of obstetric procedures. We will include all maternal-infant pairs in this OSHPD dataset. We will identify prenatally-identifiable risk factors for BPBI by univariate and multivariate logistic regression and develop a risk model quantifying the probability of BPBI given the presence of identified risk factors. We will identify areas of targeted intervention to aid in potential preventative strategies. Hypotheses: Evaluation of a large diverse population of maternal-infant pairs will identify prenatal BPBI risks associated with maternal and hospital factors. Impact: Determination of prenatally identifiable risk factors for BPBI will create a more complete understanding of the etiology and epidemiology of BPBI. This information will be used to improve identification and individual care for high risk mothers and infants and population level targets for primary prevention.