Predictive Model of Early Spontaneous Ductus Arteriosus Closure Based on Neonatologist Performed Echocardiography in Preterm Infants - Bravo, María Carmen; Sánchez, Rebeca; Blanco, Ana Isabel; Losantos, Itsaso; Pellicer, Adelina (Frontiers in Pediatrics, 2021)
Background. Patent ductus arteriosus (PDA) treatment remains controversial. Modelling on the predictive capacity of early spontaneous PDA closure would help in decision-making. Aim. To design a predictive model of early spontaneous PDA closure. Methods: As part of a trial to assess efficacy and safety of two ibuprofen treatment schemes for PDA, infants below 29 weeks’ gestation were scanned between 18-72 h of birth, and serially if indicated. PDA treatment was decided based on echocardiography signs of lung overflow or systemic hypoperfusion and clinical criteria. A PDA score that included the echocardiographic parameters significantly associated with treatment prescription was retrospectively applied. Perinatal variables and screening score were included in a backwards elimination model to predict early spontaneous closure. Results: Among 87 eligible infants (27 weeks’ gestation; age at screening 45h), 21 received ibuprofen at 69h of life [(screening score=7 (IQR=5-8.5); score at treatment=9 (IQR=8-9)], while 42 infants had conservative management, [screening score=1 (IQR=0-4)]. Twenty four infants were excluded (ibuprofen contraindication, declined consent or incomplete echocardiography). Screening score showed an AUC=0.93 to predict early spontaneous PDA closure, [cut-off value=4.5 (sensitivity=0.90, specificity=0.86)]. The predictive model for early spontaneous PDA closure followed the equation: Log (p/1-p) = -28.41+1.23*gestational age-0.87*PDA screening score Conclusions: A predictive model of early spontaneous PDA closure that includes gestational age and the screening PDA score is proposed to help clinicians in the decision- making for PDA treatment. In addition, this model could be used in future intervention trials aimed to prevent PDA related morbidities to improve the eligibility criteria.