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- W1448833783 abstract "AbstractAn index for severity of illness that may be used as a prediction of outcome was developed retrospectively by a multivariate analysis of cardiorespiratory data from 113 critically ill postoperative general surgical patients and was tested prospectively in a new series of 105 patients. The severity (predictive) index was heuristically developed using an algorithm that generates a severity score from the observed value for each cardiorespiratory variable and the frequency distributions of survivors' and nonsurvivors' values of that variable at each stage of postoperative shock. An overall or global severity index was developed from the sum of the severity scores of each variable weighted according to their capacity to predict outcome. The difference in the mean values of the predictive index for survivors and nonsurvivors was statistically significant (P<.001) during each stage of shock. In a prospective study of 105 new patients, there was 93% accuracy for the values of the last available data set. The usefulness of this index was demonstrated by tracking the clinical course of the critical illness of the prospective series. We conclude that the severity (predictive) index aids in evaluation of monitored cardiorespiratory variables, facilitates interpretation of physiologic alterations, and facilitates clinical decision-making at the bedside." @default.
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- W1448833783 date "1980-11-05" @default.
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- W1448833783 title "Clinical Trials of a Computerized Algorithm for Measurement of the Severity of Illness and Prediction of Outcome in Postoperative Shock" @default.
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