WIP 55 - Identifying Factors That Potentially Predict Medical Therapy Resolution of Patent Ductus Arteriosus (PDA) in Preterm Infants

Poster Number: WIP 55
Publication Number: WIP 55.817

Background: Preterm infants born less than 32 0/7 weeks are at high risk for a hemodynamically significant patent ductus arteriosus (PDA). The presence of a PDA increases the risk for other prematurity-related morbidities, such as bronchopulmonary dysplasia and intraventricular hemorrhage.
The persistence of a PDA is closely related to PGE levels. Cyclooxygenase (COX) is an enzyme necessary for the synthesis of PGE, and thus, nonselective COX inhibitors, such as indomethacin, acetaminophen, and ibuprofen, have been used to medically treat a PDA. These medications, although efficacious, have numerous side effects and may be unsuccessful in some infants. To improve individual management of PDA and avoid unnecessary exposure to medications, it is necessary to determine the predictors of successful medical closure of PDA.

Objective: The primary objective of this study is to identify possible factors that could predict successful PDA closure with medical treatment, preventing the need for surgical treatment.

Design/Methods: This is a single-center, retrospective cross-sectional study of preterm infants born less than 32 0/7 weeks admitted to the UMass Memorial Medical Center (UMMMC) neonatal intensive care unit (NICU) from January 2016 to July 2023 for whom a hemodynamically significant PDA was diagnosed by echocardiogram (ECHO) prior to 36 0/7 weeks. The study was approved by the UMass Chan IRB. Infants were identified through the Vermont Oxford Network database. Demographic variables, such as race and ethnicity, will be collected. Maternal exposures and clinical variables related to the infant’s NICU course (CRIB II score, surfactant administration, enteral feeding, phototherapy, comorbidities) will be abstracted. Clinical status at the time of medication, ECHO findings, and the type, time, and duration of medications given will be noted. Bivariate analyses will be performed to determine the association of each aforementioned parameter to successful medical treatment. Data collection will be complete by December 31, 2023, and statistical analysis will be complete by April 1, 2024.