(Circulation. 1996;94:2124-2130.)
© 1996 American Heart Association, Inc.
Articles |
Immediate Results of Percutaneous Mitral Commissurotomy
A Predictive Model on a Series of 1514 Patients
the Cardiology Department, Tenon Hospital, and INSERM U258, Broussais Hospital (P.D.), Paris, France.
Correspondence to Dr Bernard Iung, Service de Cardiologie, Hopital Tenon, 4, rue de la Chine, 75020 Paris, France. E-mail vahan001@msn.com.
Background The wide use of percutaneous mitral commissurotomy (PMC) underlines the need to identify the predictive factors of the results. Using a large series allowed us to develop a multivariate model that can be applied to improve patient selection.
Methods and Results Between 1986 and 1995, PMC was undertaken in 1514 patients. Mean age was 45±15 years. Echocardiography showed that 245 patients (16%) had pliable valves and mild chordal thickening (group 1), 886 (59%) had extensive subvalvular disease (group 2), and 383 (25%) had calcified valves (group 3). PMC failed in 22 patients; it was performed with a single balloon in 30 patients, a double balloon in 586, and the Inoue balloon in 876. Good immediate results were defined as a valve area 
1.5 cm2 with mitral regurgitation Sellers' grade 
2 and were obtained in 1348 patients (89%). A logistic model developed from the first 1088 cases identified the following predictors of immediate results: age (P=.004), echocardiographic group (P<.0001), valve area (P<.0001), and effective balloon dilating area (EBDA) (P=.03). Two interactions were significant: age at previous commissurotomy (P=.013) and EBDA by initial mitral regurgitation (P=.034). The type of balloon was of borderline significance (P=.09). The model was validated on an independent sample comprising the subsequent 426 procedures. For a threshold of probability of good results of .75, sensitivity was 92%, specificity 25%, and predictive accuracy 87%.
Conclusions Prediction of the immediate results of PMC is multifactorial. The predictive model developed and validated can be contributive in decision making for individual patients.
Key Words: mitral valve • valvuloplasty • stenosis • statistics
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