Prediction of death for extremely premature infants in a population-based cohort.

OBJECTIVE: Although gestational age (GA) is often used as the primary basis for counseling and decision-making for extremely premature infants, a study of tertiary care centers showed that additional factors could improve prediction of outcomes. Our objective was to determine how such a model could improve predictions for a population-based cohort.

METHODS: From 2005 to 2008, data were collected prospectively for the California Perinatal Quality Care Collaborative, which encompasses 90% of NICUs in California. For infants born at GAs of 22 to 25 weeks, we assessed the ability of the Eunice Kennedy Shriver National Institute of Child Health and Human Development 5-factor model to predict survival rates, compared with a model using GA alone.

RESULTS: In the study cohort of 4527 infants, 3647 received intensive care. Survival rates were 53% for the whole cohort and 66% for infants who received intensive care. In multivariate analyses of data for infants who received intensive care, prenatal steroid exposure, female sex, singleton birth, and higher birth weight (per 100-g increment) were each associated with a reduction in the risk of death before discharge similar to that for a 1-week increase in GA. The multivariate model increased the ability to group infants in the highest and lowest risk categories (mortality rates of >80% and