Validation and refinement of mortality risk models for heart valve surgery.
BACKGROUND: The Northern New England Cardiovascular Disease Study Group ( NNE) recently published risk models for hospital mortality after heart valve surgery. The Providence Health System Cardiovascular Study Group ( PHS) has been collecting similar heart valve data for 8 years, providing an ideal opportunity to both validate the NNE risk models and attempt to produce an improved model, by using some different modeling techniques. METHODS: From 1997 to 2004, 3,324 patients aged 30 to 95 years underwent aortic valve replacement (AVR), and 1,596 underwent mitral valve replacement or repair (MVRR) at one of nine PHS medical centers. We used area under the receiver operating characteristic curve (c-index) to measure model discrimination, and Hosmer-Lemeshow statistic (H-L) to measure calibration. We modified the NNE models by ungrouping continuous variables, seeking optimal transformations of continuous variables, and imputing missing values by multiple regression. RESULTS: The prevalence and the lethality of risk factors were similar in PHS and NNE patients. The NNE models fit PHS patients well: c-index (95% confidence interval) = 0.75 (0.70 to 0.80) for AVR and 0.81 (0.76 to 0.86) for MVRR; H-L = 3.95 (p = 0.861) for AVR and 7.10 (p = 0.526) for MVRR. A single PHS model performed slightly better for both positions: c-index = 0.79 (0.75 to 0.83) for AVR and 0.84 (0.80 to 0.88) for MVRR; H-L = 2.75 (p = 0.949) for AVR and 12.21 (p = 0.142) for MVRR. CONCLUSIONS: The NNE models for aortic and mitral valve surgery were successfully validated using PHS patients. Using some different statistical approaches to modeling, we produced a new, unified model for both positions.[1]References
- Validation and refinement of mortality risk models for heart valve surgery. Jin, R., Grunkemeier, G.L., Starr, A. Ann. Thorac. Surg. (2005) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg
