Risk Assessment of Cognitive Impairment at 2 Years of Age in Infants Born Extremely Preterm Using the INTERGROWTH-21st Growth Standards

J Pediatr. 2024 Aug 19:275:114239. doi: 10.1016/j.jpeds.2024.114239. Online ahead of print.

Abstract

Objective: To assess the risk of cognitive impairment among infants born extremely preterm using the INTERGROWTH-21st standards.

Study design: We analyzed anthropometric data at birth and 36 weeks postmenstrual age (PMA) from infants born extremely preterm (24-26 weeks of gestation) admitted to US neonatal units between 2008 and 2018. To determine INTERGROWTH-21st z-score values that indicate an increased risk of cognitive impairment at 2 years of age (Bayley cognitive score <85), we employed classification and regression trees and redefined growth failure (weight, length, and head circumference z-scores at 36 weeks PMA) and growth faltering (weight, length, and head circumference z-score declines from birth to 36 weeks PMA).

Results: Among 5393 infants with a mean gestational age of 25 weeks, growth failure defined as a weight z-score of -1.8 or below at 36 weeks PMA and growth faltering defined as a weight z-score decline of 1.1 or greater from birth to 36 weeks PMA indicated a higher likelihood of cognitive impairment. A length z-score less than -1 at 36 weeks PMA had the highest sensitivity to detect cognitive impairment at 2 years (80%). A head circumference z-score decline of 2.43 or greater from birth to 36 weeks PMA had the highest specificity (86%). Standard definitions had fair to low sensitivity and specificity for risk detection of cognitive impairment.

Conclusions: Length and head circumference z-scores had the highest sensitivity and specificity for risk detection of cognitive impairment. Monitoring these growth parameters could guide earlier individualized interventions with potential to reduce cognitive impairment.

Clinical trial registration: ClinicalTrials.gov ID Generic Database: NCT00063063.

Keywords: anthropometric measurements; neurodevelopmental impairment; prediction model; premature newborns.

Associated data

  • ClinicalTrials.gov/NCT00063063