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      Prediction of operative mortality after valve replacement surgery.

      Journal of the American College of Cardiology

      Risk Factors, Aortic Valve, surgery, Coronary Artery Bypass, mortality, Female, Heart Valve Prosthesis Implantation, Aged, Humans, Male, Middle Aged, Mitral Valve, Models, Statistical, Risk Assessment

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          Abstract

          We sought to develop national benchmarks for valve replacement surgery by developing statistical risk models of operative mortality. National risk models for coronary artery bypass graft surgery (CABG) have gained widespread acceptance, but there are no similar models for valve replacement surgery. The Society of Thoracic Surgeons National Cardiac Surgery Database was used to identify risk factors associated with valve surgery from 1994 through 1997. The population was drawn from 49,073 patients undergoing isolated aortic valve replacement (AVR) or mitral valve replacement (MVR) and from 43,463 patients undergoing CABG combined with AVR or MVR. Two multivariable risk models were developed: one for isolated AVR or MVR and one for CABG plus AVR or CABG plus MVR. Operative mortality rates for AVR, MVR, combined CABG/AVR and combined CABG/ MVR were 4.00%, 6.04%, 6.80% and 13.29%, respectively. The strongest independent risk factors were emergency/salvage procedures, recent infarction, reoperations and renal failure. The c-indexes were 0.77 and 0.74 for the isolated valve replacement and combined CABG/valve replacement models, respectively. These models retained their predictive accuracy when applied to a prospective patient population undergoing operation from 1998 to 1999. The Hosmer-Lemeshow goodness-of-fit statistic was 10.6 (p = 0.225) for the isolated valve replacement model and 12.2 (p = 0.141) for the CABG/valve replacement model. Statistical models have been developed to accurately predict operative mortality after valve replacement surgery. These models can be used to enhance quality by providing a national benchmark for valve replacement surgery.

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          11693766

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