Prediction of operative mortality after valve replacement surgery

OBJECTIVES We sought to develop national benchmarks for valve replacement s urgery by developing statistical risk models of operative mortality. BACKGROUND National risk models for coronary artery bypass graft surgery (C ABG) have gained widespread acceptance, but there are no similar models for valve replacement surgery. METHODS The Society of Thoracic Surgeons National Cardiac Surgery Database was used to identify risk factors associated with valve surgery from 1994 t hrough 1997. The population was drawn from 49,073 patients undergoing isola ted aortic valve replacement (AVR) or mitral valve replacement (MVR) and fr om 43,463 patients undergoing CABG combined with AVR or MVR. Two multivaria ble risk models were developed: one for isolated AVR or MVR and one for CAB G plus AVR or CABG plus MVR. RESULTS Operative mortality rates for AVR, MVR, combined CABG/AVR and combi ned CABG/ MVR were 4.00%, 6.04%, 6.80% and 13.29%, respectively. The strong est independent risk factors were emergency/salvage procedures, recent infa rction, reoperations and renal failure. The c-indexes were 0.77 and 0.74 fo r the isolated valve replacement and combined CABG/valve replacement models , respectively. These models retained their predictive accuracy when applie d to a prospective patient population undergoing operation from 1998 to 199 9. The Hosmer-Lemeshow goodness-of-fit statistic was 10.6 (p = 0.225) for t he isolated valve replacement model and 12.2 (p = 0.141) for the CABG/valve replacement model. CONCLUSIONS Statistical models have been developed to accurately predict op erative mortality after valve replacement surgery. These models can be used to enhance quality by providing a national benchmark for valve replacement surgery. (J Am Coil Cardiol 2001;37:885-92) (C) 2001 by the American Colle ge of Cardiology.