Optimal gestational age and birth-weight cutoffs to predict neonatal morbidity.

Journal Article (Academic Article)

BACKGROUND: Gestational age (GA) and birth weight (BW) criteria are used to identify newborns at risk for neonatal morbidity. Currently, preterm is GA less than 37 weeks; low birth weight is BW less than 2,500 grams; and small for gestational age (SGA) is BW less than the tenth percentile weight for the infant's GA. The optimal classification system balances the misclassification cost of false negatives against the cost of false positives. OBJECTIVE: To calculate the relative misclassification costs implied by the current 37-week and 2,500-gram cutoffs, and to test the validity of the current definition of SGA as a predictor of term morbidities. METHODS: GA, BW, and morbidity information were collected for 22,606 infants born between July 1981 and December 1992. Using this dataset, logistic regression coefficients were obtained modeling GA or BW as predictors of morbidities associated with prematurity. For a subset of 18,813 infants with GAs between 37 and 41 weeks, coefficients were obtained modeling both GA and BW as independent predictors of term morbidities. The logistic regression coefficients were used to calculate optimal birth weight, gestational age, and birth-weight-for-gestational-age cutoffs. RESULTS: The current definitions of low birth weight and preterm imply that it is 18 to 28 times more costly to misclassify a sick infant as low-risk than to misclassify a well infant as high-risk. CONCLUSIONS: Gestational age alone is better than birth weight alone at predicting preterm morbidities. No birth-weight cutoff can adequately predict term morbidities. A single weight-percentile cutoff for all gestational ages should not be used to identify newborns at high risk for neonatal morbidity.

Duke Authors

Cited Authors

  • Kohn, MA; Vosti, CL; Lezotte, D; Jones, RH

Published Date

  • 2000

Published In

Volume / Issue

  • 20 / 4

Start / End Page

  • 369 - 376

International Standard Serial Number (ISSN)

  • 0272-989X

Conference Location

  • united states