WIP 57 - CPAP Use in the Delivery Room on Term Infants and Association with Hospital Length of Stay

Poster Number: WIP 57
Publication Number: WIP 57.2555

Background: In 2011, the Neonatal Resuscitation Program (NRP) algorithm was revised to include use of CPAP in the delivery room (DR-CPAP) for infants with labored breathing or persistent cyanosis, regardless of their gestational age. The International Committee on Resuscitation (ILCOR) systematically reviewed DR-CPAP use in term infants and found insufficient evidence for or against its use. However, the availability of DR-CPAP often urges its use. In term infants, this may have serious adverse outcomes leading to prolonged hospital length of stay (LOS) and contribution to the perinatal core measure-06 (PC-06) as an unexpected healthy pregnancy outcome.

Objective: To determine if use of DR-CPAP is associated with prolonged LOS in term infants born between 37 to 42 weeks.

Design/Methods: The Stony Brook University Hospital institutional review board approved this retrospective cohort study. Inclusion criteria are infants born between 37 to 42 weeks in 2020 and 2021 who received DR-CPAP. Exclusion criteria are gestational age < 37 weeks, congenital malformations, genetic diseases, and infants with in-utero opioid exposure. Assuming mean LOS is 2 days for vaginal births and 4 days for cesarean births, a total sample size of 128 neonates (64 exposed and 64 controls) was required for a power of 80% to detect any significant difference (alpha 0.05) in LOS (sigma 2). Each group was further divided by mode of delivery. The primary outcome was hospital length of stay in days. Secondary outcomes included air leak syndrome, need for mechanical ventilation, antibiotic exposure, x-ray exposure, breastfeeding, time to full feeds, need for intravenous access, and electrolyte imbalances. Data was extracted via retrospective review of electronic medical records.

STATA software will be utilized for statistical analysis. Logistic regression will account for independent variables. Student T-Test will compare the continuous variables. Data analysis will be completed by December 2023.