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Predicting Death


Despite various models developed to predict mortality, the evidence suggests that physicians perform poorly in this area.

One of the toughest jobs a physician has is imparting bad news, and it is crucial for a physician to be able to predict death accurately when informing a patient. Despite various models developed to predict mortality, the evidence suggests that physicians perform poorly in this area, according to an evaluation in the Archive of Internal Medicine.

The study’s authors — George C. M. Siontis, MD;

Ioanna Tzoulaki, PhD


John P. A. Ioannidis, MD, DSc

— assessed how accurately and consistently models for predicting death performed. What they discovered was that the tools in their analysis were “not sufficiently accurate for wide use in clinical practice.” In order for these predictive tools to be useful, the authors identified several prerequisites.

The tool must be validated in populations other than the one in which it was developed; it should be reproducible; and it should have good accuracy and calibration,” the report reads. “Such a predictive tool can make accurate predictions in diverse settings across the range of both low- and high-risk patients.”

The researchers studied 110 models and eight different predictors to discover that the median accuracy

based on the area under the receiver operating characteristic curve (AUC) was 0.77. However, the values ranged from as low as 0.43 to as high as 0.98.

Overall 95 models

— 40% of the models assessed —

were considered accurate enough to have very good discrimination, but only 10% of the models were valued with excellent discrimination.

The area where models were most accurate were among pediatric populations. Also, tools trying to predict death for the highest-risk patients performed better.

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