Articles: outcome-assessment-health-care.
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J. Clin. Periodontol. · May 1995
ReviewA survey of endpoint characteristics in periodontal clinical trials published 1988-1992, and implications for future studies.
Endpoints are conditions or events that are associated with individual study subjects and that are used to assess treatment efficacy. 2 types of endpoints can be distinguished: "true" endpoints (reflect unequivocal evidence of tangible benefit to the patient) and "surrogate" endpoints (usually a measure of disease process). The purpose of this study was to survey four aspects of endpoint usage in randomized controlled trials (RCT's) on the treatment of periodontitis: (1) the typical number of endpoints per RCT, (2) the proportion of RCTs using the same endpoint, (3) the proportion of RCTs using true endpoints, and (4) whether treatment choice influenced endpoint choice. 92 publications (1988-1992) reporting on 82 RCT's were identified. The typical number of endpoints per RCT was 6 (range: 1-28). ⋯ If a need for definitive randomized controlled trials is perceived, then the use of (multiple) surrogate endpoints as primary outcomes should be questioned. Surrogate endpoint usage has led to both false positive and false negative conclusions in other chronic disease studies. Endpoint selection and validation in RCTs may be an important element in resolving controversies about periodontal treatments.
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There are now two validated time points for predicting hospital mortality of ICU patients--at admission and at 24 hours. The best purposes include evaluation of high clinical performance ICUs and for patients being enrolled in clinical trials. For the latter purpose, the model must be calibrated in the individual hospital to ensure that the model is applicable. ⋯ The mathematical link between physiology score and estimation of hospital mortality is established only for the time point of 24 hours after ICU admission. Calibration and discrimination of the admission and 24-hour models also must be performed within each hospital in which individual probabilities are presented to families. It may be possible to customize a probability model such as MPM to achieve a high level of calibration at the individual hospital level.
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Meeting the challenges of allocating critical care resources in the fairest way possible depends upon the development of a standardized strategy for apportioning ICU services in times of limited supply. Two main approaches are emerging to handle these challenges. ⋯ The second approach involves improving the efficiencies of the care giving system itself. Either approach requires the establishment of a standard of care that reduces the potential for personal biases into the decision making process.