PREDICTION OF SURVIVAL AND MORBIDITY IN INFANTS OF BIRTH-WEIGHT < 801 g

The dilemmas of providing intensive care for extremely low birth-weight infants stem from high mortality and morbidity rates, and the high cost of survival, both in human and economic terms. Where resources are limited, prediction of outcome early in the course may help in determining priorities. In this study we used multiple logistic regression analysis to determine the variables indicating severity of illness in the first 24 hours of life which made an independent contribution to the prediction of survival to 28 days. The patient material consisted of 106 outborn infants of birthweight < 801 g admitted between 1980 and 1984. At 8 hours of age, birthweight (p=0.041) and FiO2 (p=0.002) were independent variables predicting survival. At 16 and 24 hours of age, body temperature (p=0.002 and 0.004), pH (p=0.002 and 0.047), and presence of spontaneous breaths (p=0.046 and 0.007) independently predicted survival. A statistical model based on the method of maximum likelihood was computed on the basis of these variables. Accuracies of prediction of survival and of death were in the range 77-83 per cent at each of the above ages. All 7 infants whose predicted chances of survival were < 0.5 at 16 hours of age had handicapping sequelae by 3 months of age, or died between 28 days and 3 months of age. Only 3 of 49 infants with chances of survival ≥ 0.5 had these outcomes. It is concluded that 1. Use of measures of severity of illness can give predictions of survival and of death with about 80% accuracy. 2. Survival “against the odds” is associated with severe sequelae of prematurity.