A simplified risk-scoring system for prematurity.
Prematurity, the major cause of perinatal morbidity and mortality, results from a multifactorial interaction of medical, historic, and psychosocial conditions. Although the literature contains several reports of prematurity risk-scoring systems, the relative importance of specific risk factors may depend on the population studied. This report represents the first prematurity risk-scoring system designed specifically for a predominantly Hispanic population in the United States. Retrospective analysis of 8240 births occurring at Harbor/UCLA Medical Center from July, 1979 to December, 1982 identified maternal prenatal risk factors that were found to be statistically related to prematurity. A linear logistic regression model was then employed to derive a composite risk score. Using the logistic risk scores, we developed a simplified model for identifying women at risk for preterm birth. The methodology and analyses provide a system for the development of population-specific risk scoring.
D000704:Analysis of Variance; D002140:California; D006630:Hispanic or Latino; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D010500:Perinatology / Q000379:methods*; D012044:Regression Analysis; D012189:Retrospective Studies; D012306:Risk; D013223:Statistics as Topic