Simplified age-weight mortality risk classification for very low birth weight infants in low-resource settings

J Pediatr. 2008 Oct;153(4):519-24. doi: 10.1016/j.jpeds.2008.04.051. Epub 2008 Jun 9.


Objective: To identify a valid neonatal mortality risk prediction score feasible for use in developing countries.

Study design: Retrospective study of 467 neonates, < or =1500 g, enrolled in trials during 1998 to 2005 at tertiary care children's hospitals in Dhaka, Bangladesh, and Cairo, Egypt, and a community field site in Sarlahi District, Nepal. We derived simplified mortality risk scores and compared their predictive accuracy with the modified Clinical Risk Index for Babies (CRIB) II. Outcome was death during hospital stay (Dhaka and Cairo) or end of the neonatal period (Nepal).

Results: The area under the curve receiver operating characteristic was 0.62, 0.71, 0.68, and 0.69 on the basis of the (a) CRIB II applied to the Dhaka-Cairo dataset; (b) an 18-category, simplified age, weight, sex score; (c) a binary-risk simplified age-weight (SAW) classification derived from the Dhaka-Cairo dataset; and (d) external validation of the binary-risk SAW classification in the Nepal dataset, respectively. Mortality risk prediction with the SAW classification on the basis of gestational age (< or =29 weeks) or weight (<1000 g) was improved (P = .048) compared with CRIB II.

Conclusions: The SAW classification is a markedly simplified mortality risk prediction score for use in identifying high-risk, very low birth weight neonates in developing country settings for whom urgent referral is indicated.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Area Under Curve
  • Developing Countries / statistics & numerical data*
  • Humans
  • Infant Mortality*
  • Infant, Newborn
  • Infant, Very Low Birth Weight*
  • ROC Curve
  • Referral and Consultation
  • Regression Analysis
  • Risk Assessment / classification*
  • Severity of Illness Index