There are two versions of the EuroSCORE cardiac surgery risk model for mortality: the logistic regression which provides a predicted probability of death, and an additive score, a simplified approximation to the logistic probability, which can be easily calculated without a computing aid. A recent comparison of these two models' performance concluded that the logistic probability did not offer a distinct advantage over the additive score, and that the additive score was just as accurate as the logistic probability, even in high-risk patients. This conflicts with the conclusion of our previous study of the same issue. Thus, we did further analyses of our original data, following the approach of these authors. The additive and logistic EuroSCORE models were retrospectively applied to predict operative mortality in 23,463 cardiac surgery patients operated from 1997-2004 at Providence Health System hospitals. Both the logistic and additive risk predictions are higher than the observed mortality, and were calibrated downward to reconcile this difference. The observed-to-predicted ratio is relatively constant for the logistic model, but it varies with the risk score for the additive model. Thus, the logistic model can be recalibrated to fit the actual outcome well, but the recalibrated additive model cannot. The (recalibrated) logistic model is more accurate for different patient groups, including the high-risk patients, and should be preferred for clinical use.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1510/icvts.2005.122705 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!