BIRTH-WEIGHT AND ILLNESS SEVERITY - INDEPENDENT PREDICTORS OF NEONATAL-MORTALITY

Background. Low birth weight is a major determinant of neonatal mortal ity. Yet birth weight, even in conjunction with other demographic mark ers, is inadequate to explain the large variations in neonatal mortali ty between intensive care units. This variation probably reflects diff erences in admission severity. The authors have recently developed the Score for Neonatal Acute Physiology (SNAP), an illness severity index specific for neonatal intensive care, and demonstrated illness severi ty to be a major determinant of neonatal mortality. Objective. To defi ne the relative contributions of birth weight and illness severity to the risk of neonatal mortality and to identify other significant indep endent risk factors. Methods. Logistic regression was used to analyze data from a cohort of 1621 consecutive admissions to three neonatal in tensive care units (92 deaths), to test six alternative predictive mod els. The best logistic model was then used to develop a simple additiv e clinical score, the SNAP Perinatal Extension (SNAP-PE). Results. The se analyses demonstrated that birth weight and illness severity are po werful independent predictors across a broad range of birth weights an d that their effects are additive. Below 750 g, there is an interactio n between birth weight and SNAP. Other factors that showed independent predictive power were low Apgar score at 5 minutes and small size for gestational age. Separate derivation and test samples were used to de monstrate that the SNAP-PE is comparable to the best logistic model an d has a sensitivity and specificity superior to either birth weight or SNAP alone (receiver-operator characteristic area .92 +/- .02) as wel l as excellent goodness of fit. Conclusion. This simplified clinical s core provides accurate mortality risk estimates for application in a b road array of clinical and research settings.