Multivariable prediction of in-hospital mortality associated with aortic and mitral valve surgery in Northern New England.

BACKGROUND: Predicting risk for aortic and mitral valve surgery is important both for informed consent of patients and objective review of surgical outcomes. Development of reliable prediction rules requires large data sets with appropriate risk factors that are available before surgery. METHODS: Data from eight Northern New England Medical Centers in the period January 1991 through December 2001 were analyzed on 8943 heart valve surgery patients aged 30 years and older. There were 5793 cases of aortic valve replacement and 3150 cases of mitral valve surgery (repair or replacement). Logistic regression was used to examine the relationship between risk factors and in-hospital mortality. RESULTS: In the multivariable analysis, 11 variables in the aortic model (older age, lower body surface area, prior cardiac operation, elevated creatinine, prior stroke, New York Heart Association [NYHA] class IV, congestive heart failure [CHF], atrial fibrillation, acuity, year of surgery, and concomitant coronary artery bypass grafting) and 10 variables in the mitral model (female sex, older age, diabetes, coronary artery disease, prior cerebrovascular accident, elevated creatinine, NYHA class IV, CHF, acuity, and valve replacement) remained independent predictors of the outcome. The mathematical models were highly significant predictors of the outcome, in-hospital mortality, and the results are in general agreement with those of others. The area under the receiver operating characteristic curve for the aortic model was 0.75 (95% confidence interval [CI], 0.72 to 0.77), and for the mitral model, 0.79 (95% CI, 0.76 to 0.81). The goodness-of-fit statistic for the aortic model was chi(2) [8 df] = 11.88, p = 0.157, and for the mitral model it was chi(2) [8 df] = 5.45, p = 0.708. CONCLUSIONS: We present results and methods for use in day-to-day practice to calculate patient-specific in-hospital mortality after aortic and mitral valve surgery, by the logistic equation for each model or a simple scoring system with a look-up table for mortality rate.

Mitral valve repair and replacement in northern New England.

BACKGROUND: The etiology of mitral valvular disease has changed in the last 20 years, and new techniques for the diagnosis and repair of mitral valves have been advanced. A retrospective regional study was conducted to identify changes in patient and disease characteristics and in population-based rates for mitral valve repair and replacement in northern New England. METHODS: Data from 1648 patients were collected from 5 clinical centers in Maine, New Hampshire, and Vermont between January 1, 1990, and December 31, 1999. U.S. Census data were used to calculate population-based rates. RESULTS: Total mitral valve procedures increased 2.4 times, from 8.7 to 20.6 cases/100,000/year (p(trend) = 0.004). Primary procedures increased from 6.7 to 16.9 cases/100,000/year (p(trend) = 0.014). Primary mitral valve repair procedures increased 3.7 times, from 2.4 to 8.9 cases/100,000/year (p(trend) = 0.012), whereas mitral valve replacement increased only 1.9 times, from 4.3 to 8.0 cases/100,000/year (p(trend) = 0.016). Repeat mitral valve operations did not change significantly (p(trend) = 0.810). During this period, there was a significant increase of the percentage of octogenarians (p(trend) = 0.016) and of patients with ejection fractions <40% (p(trend) = 0.012). There was a decrease in the percentage of patients with mitral stenosis (p(trend) = 0.024). CONCLUSION: In an era of a change in the etiology of mitral valvular disease and new techniques for diagnosis and repair of mitral valvular disease, regional data demonstrate substantial increased rates of mitral repair and replacement and expanded indications of older age and poorer left ventricular function.