Statistical approaches to development and validation of predictive instruments.
Concepts underlying the development of prediction models for intensive care unit (ICU) outcome are outlined, special emphasis is placed on multivariate logistic regression analysis. A short exposition to experimental study designs and techniques for predictor validation is given. Two statistical procedures for assessing the degree of agreement between predicted and observed mortality risks are discussed. The use of receiver operating characteristic (ROC) analysis is thoroughly reviewed as a major tool for describing and comparing, graphically and statistically, the accuracy of predictors for classifying patients prospectively into survivors and nonsurvivors.
Ruttimann
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Laboratory of Clinical Studies, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD.
D003661:Decision Support Techniques; D005544:Forecasting; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration; D016015:Logistic Models; D017063:Outcome Assessment, Health Care / Q000458:organization & administration*; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D015996:Survival Rate