Clinical data predict neurodevelopmental outcome better than head ultrasound in extremely low birth weight infants

J Pediatr. 2007 Nov;151(5):500-5, 505.e1-2. doi: 10.1016/j.jpeds.2007.04.013. Epub 2007 Jul 12.

Abstract

Objective: To determine the relative contribution of clinical data versus head ultrasound scanning (HUS) in predicting neurodevelopmental impairment (NDI) in extremely low birth weight infants.

Study design: A total of 2103 extremely low birth weight infants (<1000 g) admitted to a National Institute of Child Health and Human Development Neonatal Research Network center who underwent HUS within the first 28 days, a repeat one around 36 weeks' postmenstrual age, and neurodevelopmental assessment at 18 to 22 months corrected age were selected. Multivariate logistic regression models were developed with clinical or HUS variables. The primary outcome was the predictive abilities of the HUS performed before 28 days after birth and closer to 36 weeks postmenstrual age, either alone or in combination with "Early" and "Late" clinical variables.

Results: Models with clinical variables alone predicted NDI better than models with only HUS variables at both 28 days and 36 weeks (both P < .001), and the addition of the HUS data did not improve prediction. NDI was absent in 30% and 28% of the infants with grade IV intracranial hemorrhage or periventricular leukomalacia, respectively, but was present in 39% of the infants with a normal HUS result.

Conclusions: Clinical models were better than HUS models in predicting neurodevelopment.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Cohort Studies
  • Developmental Disabilities / epidemiology*
  • Echoencephalography*
  • Female
  • Gestational Age
  • Humans
  • Infant
  • Infant, Extremely Low Birth Weight*
  • Infant, Newborn
  • Infant, Premature, Diseases*
  • Intracranial Hemorrhages / diagnostic imaging*
  • Leukomalacia, Periventricular / diagnostic imaging*
  • Logistic Models
  • Male
  • Neurologic Examination
  • Retrospective Studies
  • United States / epidemiology