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Division of Cardiothoracic Surgery, Shands Jacksonville, University of Florida, 653-2 W 8th St, Jacksonville, FL 32209-6511
(Email: fhe{at}comcast.net).
This work [1] seeks to determine whether the EuroSCORE model performs better than the New York state valve surgery models in predicting operative mortality. The study shows that for isolated valve surgery, the NewYork state model had significantly better c-index values and Hosmer-Lemeshow scores than the EuroSCORE model. There was essentially no difference between model results for valve plus coronary artery bypass graft procedures.
In this work, the test population is (1) relatively small, (2) from one institution, and (3) from Rotterdam, which may or may not represent the general practice of cardiac surgery. From this article, based on a population from a single center in Rotterdam, it can be concluded that the New York model performs better than the EuroSCORE model in isolated valve surgery.
This is useful information, but it does not fully answer the question posed in the article: "Do we need separate risk stratification models for hospital mortality after heart valve surgery?" This important question highlights a broader issue that centers around the clinical scope and specificity of contemporary risk models.
Clearly, risk adjustment has become a well-recognized and essential element for meaningful outcomes analysis in cardiac surgery. Given the unprecedented national emphasis on physician accountability and the application of performance metrics to measure quality, we must ensure that our risk models perform well. The authors have provided one instance in which a generalized model does not perform as well as a more selective model. How selective must a model be to reach optimal performance? Should there be a separate model for aortic valve surgery and another for mitral surgery? Should there be a separate model for mitral valve replacement and another for mitral valve repair? Should there be separate models for these procedures when combined with coronary artery bypass grafting, or should a more general model population be used?
These are questions central to contemporary model development. The answers require statistical expertise, clinical judgment, and an appreciation for the way in which the models will be used.
Risk models are no longer used exclusively at the local level to assess outcomes in relation to other benchmarks. Today we have seen that risk adjustment will be used by government agencies and commercial health insurance entities as well. It is clearly our charge to ensure that models used to measure quality are fair, accurate, and meaningful. This task will inevitably require objective answers to the questions previously presented. The authors have presented us with a valuable example of an objective way to approach this task.
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