Why the study?
Previous learning curve analyses of minimally invasive MV repair focused largely on early safety outcomes without detailed repair quality outcomes.
Does increased surgeon experience improve technical and clinical outcomes in patients undergoing minimally invasive mitral valve repair?
Does increased surgeon experience improve technical and clinical outcomes in patients undergoing minimally invasive mitral valve repair?
The learning curve for achieving optimal technical and clinical outcomes in minimally invasive mitral valve repair is approximately 60 to 85 operations.
OBJECTIVE: Previous learning curve analyses of minimally invasive mitral valve (MV) repair have focused largely on early safety outcomes without including detailed mitral repair quality outcomes. This study investigates the learning curve of minimally invasive MV repair over a 15-year experience, focused on clinical outcomes and evidence-based technical failure endpoints. METHODS: All MV repair operations were performed by a single surgeon between May 2008 and February 2023. Patient data were stratified into 3 groups of tertiles. Failure endpoints were defined as postrepair residual mitral regurgitation ≥ mild and a 30-day composite outcome. Cumulative log-likelihood curves were constructed for minimally invasive MV repair using the primary outcomes as technical failure endpoints. Control limits were determined using previous analyses of the Society of Thoracic Surgeons database. RESULTS: = 0.005). Learning curve analysis demonstrated crossing of the lower threshold at ~60 patients for postrepair mitral regurgitation ≥ mild and ~85 patients for the 30-day composite outcome. The mean adjusted risk scores for both primary outcomes based on a multivariable logistic model demonstrated no significant differences across tertiles. CONCLUSIONS: The estimated number of operations to achieve optimal repair outcomes and durability is ~60 to 85 patients. These data can improve the design of surgical training competencies, beyond avoidance of complications, and instead focus the learning curve on what is necessary to achieve optimal mitral repair outcomes.
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Malik et al. (2025) studied this question.
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