Eliminating the learning curve in robotic mitral valve repair: Results from 1400 patients.

OBJECTIVE

To evaluate learning curves of surgeons performing robotic mitral surgery at an experienced program.

METHODS

A total of 1410 patients undergoing robotic mitral surgery between 2005 and 2023 performed by 4 surgeons (from early to late in their careers) were identified from an institutional registry. Learning curves for the primary outcome of Society of Thoracic Surgeons (STS) risk-adjusted morbidity (stroke, renal failure, cardiac reoperation, reintubation, or prolonged ventilation) and mortality were constructed using cumulative sum analysis.

RESULTS

The median patient age was 63 years (interquartile range [IQR], 54-70 years), 65.3% of the patients were male, and the patients' median STS predicted risk of morbidity and mortality was 5.9% (IQR, 4.3%-8.5%). Etiology was degenerative in 1237 patients (88%), of whom 869 (70%) had isolated P2 prolapse. Overall operative mortality was 0.3% (n = 4), with 3 deaths occurring in the first 1000 cases. Composite morbidity and mortality was 4.4% (n = 62). The degenerative repair rate was 99.5% (n = 1234/1237), with a 95% freedom from moderate or worse mitral regurgitation at 5 years. The program learning curve peaked at case 94, after which risk-adjusted morbidity and mortality was consistently better than predicted. Subsequent surgeons learned robotic mitral surgery with better-than-predicted outcomes from the outset-that is, no learning curve, with progressive improvement in risk-adjusted complications and cardiopulmonary bypass times.

CONCLUSIONS

Surgeons in an experienced program can learn robotic mitral surgery without a learning curve defined by worse-than-predicted clinical outcomes, achieving degenerative mitral repair rates >99% and good durability.