Early prediction of poor outcome in extremely low birth weight infants by classification tree analysis

Academic Article

Abstract

  • Objective: To predict death or neurodevelopmental impairment (NDI) in extremely low birth weight infants by classification trees with recursive partitioning and automatic selection of optimal cut points of variables. Study design: Data from the Trial of Indomethacin Prophylaxis in Preterms were randomly divided into development (n = 784) and validation sets (n = 262). Three models were developed for the combined outcome of death (8 days to 18 months) or NDI (cerebral palsy, cognitive delay, deafness, or blindness at 18 months corrected age): antenatal: antenatal data; early neonatal: antenatal + first 3 days data; and first week: antenatal, first 3 days, and 4th to 8th days data. Decision trees were tested on the validation set. Results: Variables associated with death/NDI in each model were: Antenatal: Gestation ≤25.5 weeks and antenatal steroids <7 days. Early neonatal: Birth weight ≤787 g and fluid intake >101 mL/kg/d. First week: Birth weight ≤787 g: transfusion >3 mL/kg/d. Birth weight >787 g: cranial echodense intraparenchymal lesion and transfusion >11 mL/kg/d. Correct classification rates were 61% to 62% for all models. Conclusions: The ability to predict long-term morbidity/death in extremely low birth weight infants does not improve significantly over the first week of life. Effects of different variables depend on age. © 2006 Elsevier Inc. All rights reserved.
  • Digital Object Identifier (doi)

    Author List

  • Ambalavanan N; Baibergenova A; Carlo WA; Saigal S; Schmidt B; Thorpe KE
  • Volume

  • 148
  • Issue

  • 4