Abstract

Three discriminant functions were used to determine which were the most effective in discriminating between death and survival of an infant, and to assess the importance of each independent variable in the analyses. Model A contained 28 variables which had been found significant or borderline in previous regression analyses upon birth weight, gestation, or crown-heel length. Model B consisted only of birth weight, gestation, and crown-heel length, while Model C contained the 25 variables of Model A not included in Model B.Model A was judged to be the most effective in discrimination. Model B, with only three variables, was almost as powerful. Model C, with 25 variables, was the least effective by far.The three variables of Model B were further analyzed to determine which of these three indices of prematurity, and which combinations of them were most important in discriminating between death and survival. Birth weight was the most powerful, gestation was next, and crown-heel length the least important. Considering the variables in pairs, birth weight and gestation was the most effective pair, followed by birth weight and crown-heel length. Gestation and crown-heel length was the least effective. Birth weight alone was a better discriminator than gestation and length combined. Furthermore, the addition of a third index to any given pair significantly increased the discriminating power of the function.Individual variables, other than the three discussed above, found significant in discrimination included race, sex, prepregnancy weight of the mother, obstetric complications, placenta and cord conditions, and congenital malformations.

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