Estimation of the Operative Risk of Mitral Valve Replacement by Multivariate Logistic Regression Analysis

The knowledge of factors determining the risk of postoperative myocardial failure (MF) should allow a more rational approach to the timing and the management of mitral valve replacement (MVR). Using multivariate logistic regression analysis the influence of 41 preoperative and perioperative variables on MF was assessed in a training group of 353 consecutive patients undergoing isolated primary MVR between 6/76 and 12/82. Early MF mortality was 4.2%. Strongest independent preoperative predictors of MF were advanced NYHA functional class (p less than 0.001), hepatomegaly (p = 0.001), and reduced body weight (p = 0.01). Amongst preoperative and perioperative variables independent determinants of MF were NYHA functional class (p less than 0.001), hepatomegaly (p = 0.002), hypotension during extracorporeal circulation (ECC) (p = 0.005), body weight (p = 0.007), ECC duration (p = 0.008), female sex (p = 0.061) and the absence of cardioplegia (p = 0.065). From the combination of these determinants estimates of the probability of MF were calculated and adjoined to low or high risk by means of an optimum cutoff point. The sensitivity of this test performed before and after operation was 0.80 and 0.93, the specificity 0.92 and 0.94, respectively. The reliability of this prognostic test was prospectively evaluated on data of 107 consecutive MVR patients between 1/83 and 12/84. The observed diagnostic characteristics of the test group were comparable to those predicted from the training group. Multivariate logistic regression analysis selects independent determinants, estimates the risk of MF or other modes of postoperative events and identifies patients with low or high risk with a definable validity as an objective aid for medical decision-making.