214 - Postnatal Growth as Stand-Alone Predictor of Cognition at 2 Years of Age in Extremely Preterm Infants

Poster Number: 214
Publication Number: 214.144

Ariel A.. Salas, University of Alabama School of Medicine, Birmingham, AL, United States; Waldemar A. Carlo, University of Alabama School of Medicine, Birmingham, AL, United States; Carla Bann, RTI International, Apex, NC, United States; Edward F.. Bell, University of Iowa, Iowa City, IA, United States; Tarah T. Colaizy, University of Iowa Stead Family Children's Hospital, Iowa City, IA, United States; Noelle Younge, Duke University School of Medicine, Durham, NC, United States; Myriam Peralta-Carcelen, University of Alabama at Birmingham, Birmingham, AL, United States; Namasivayam Ambalavanan, University of Alabama School of Medicine, Birmingham, AL, United States; Brenda Poindexter, Children’s Healthcare of Atlanta and Emory University, Atlanta, GA, United States; NICHD Neonatal Research Network, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, United States

Background: INTERGROWTH-21st growth curves generated with longitudinal data collected prospectively have more accurate measurements than traditional growth curves generated with cross-sectional data collected retrospectively.

Objective: To determine if adverse growth outcomes defined with z-scores calculated using the INTERGROWTH-21^st growth curves can accurately predict the risk of cognitive delay in extremely preterm infants born at ≤26 weeks’ gestation.

Design/Methods: Extremely preterm infants of 24 to 26 weeks' gestation admitted to NICHD Neonatal Research Network neonatal intensive care units from 2008 to 2018 and assessed for cognitive outcomes at 2 years of age were included. Z-scores for weight, length, and head circumference were calculated using the INTERGROWTH-21 standards. The final sample was randomly split into development and testing samples. Classification and regression trees (CART) were used to identify the most appropriate cut-offs for weight z-score at 36 weeks postmenstrual age (PMA) and for decline in weight z-score from birth to 36 weeks PMA to predict risk of cognitive delay (defined as Bayley-III cognitive composite score < 85).

Results: A final analytic sample of 5,393 infants was randomly split into development (n=2,696) and testing (n=2,697) samples.  A weight z-score at 36 weeks PMA of ≤ -1.8 and a weight z-score decline from birth to 36 weeks PMA of ≤ -1.1 were identified as the optimal cut-offs that indicate a greater likelihood of having a cognitive delay. Both cut-offs were significantly associated with a higher risk of cognitive delay in analyses adjusted for year, center, in-hospital morbidities, and maternal/neonatal demographics (aRR: 1.33 [95% CI: 1.15, 1.54] and aRR: 1.18 [95% CI: 1.03, 1.35], respectively). Both cut-offs were associated with lower length and head circumference z-scores. A weight z-score at 36 weeks PMA of ≤ -1.8 had the highest specificity for cognitive delay at 2 years of age (82%).  A weight z-score decline from birth to 36 weeks PMA of ≤ 1.1 had the highest sensitivity (40%) (Figure).

Conclusion(s): As a diagnostic test derived from INTERGROWTH-21st standards, weight z-score at 36 weeks PMA has the highest specificity (82%) to predict cognitive delay. Weight z-score decline from birth to 36 weeks PMA has the highest sensitivity (40%) to predict cognitive delay, but may be too low to guide clinical practice as a stand-alone predictor. Since both growth outcomes are associated with a higher risk of cognitive delay, they could be added to predictive equations aimed at determining the probability of cognitive delay in extremely preterm infants.