A propensity matched analysis of robotic, minimally invasive, and conventional mitral valve surgery.

OBJECTIVES: Institutional studies suggest robotic mitral surgery may be associated with superior outcomes. The objective of this study was to compare the outcomes of robotic, minimally invasive (mini), and conventional mitral surgery. METHODS: A total of 2300 patients undergoing non-emergent isolated mitral valve operations from 2011 to 2016 were extracted from a regional Society of Thoracic Surgeons database. Patients were stratified by approach: robotic (n=372), mini (n=576) and conventional sternotomy (n=1352). To account for preoperative differences, robotic cases were propensity score matched (1:1) to both conventional and mini approaches. RESULTS: The robotic cases were well matched to the conventional (n=314) and mini (n=295) cases with no significant baseline differences. Rates of mitral repair were high in the robotic and mini cohorts (91%), but significantly lower with conventional (76%, P<0.0001) despite similar rates of degenerative disease. All procedural times were longest in the robotic cohort, including operative time (224 vs 168 min conventional, 222 vs 180 min mini; all P<0.0001). The robotic approach had comparable outcomes to the conventional approach except there were fewer discharges to a facility (7% vs 15%, P=0.001) and 1 less day in the hospital (P<0.0001). However, compared with the mini approach, the robotic approach had more transfusions (15% vs 5%, P<0.0001), higher atrial fibrillation rates (26% vs 18%, P=0.01), and 1 day longer average hospital stay (P=0.02). CONCLUSION: Despite longer procedural times, robotic and mini patients had similar complication rates with higher repair rates and shorter length of stay metrics compared with conventional surgery. However, the robotic approach was associated with higher atrial fibrillation rates, more transfusions and longer postoperative stays compared with minimally invasive approach.

Conditional long-term survival following minimally invasive robotic mitral valve repair: a health services perspective.

BACKGROUND: Conditional survival is defined as the probability of surviving an additional number of years beyond that already survived. The aim of this study was to compute conditional survival in patients who received a robotically assisted, minimally invasive mitral valve repair procedure (RMVP). METHODS: Patients who received RMVP with annuloplasty band from May 2000 through April 2011 were included. A 5- and 10-year conditional survival model was computed using a multivariable product-limit method. RESULTS: Non-smoking men (≤65 years) who presented in sinus rhythm had a 96% probability of surviving at least 10 years if they survived their first year following surgery. In contrast, recent female smokers (>65 years) with preoperative atrial fibrillation only had an 11% probability of surviving beyond 10 years if alive after one year post-surgery. CONCLUSIONS: In the context of an increasingly managed healthcare environment, conditional survival provides useful information for patients needing to make important treatment decisions, physicians seeking to select patients most likely to benefit long-term following RMVP, and hospital administrators needing to comparatively assess the life-course economic value of high-tech surgical procedures.

Robotically assisted minimally invasive mitral valve surgery.

Increased recognition of advantages, over the last decade, of minimizing surgical trauma by operating through smaller incisions and its direct impact on reduced postoperative pain, quicker recovery, improved cosmesis and earlier return to work has spurred the minimally invasive cardiac surgical revolution. This transition began in the early 1990s with advancements in endoscopic instruments, video & fiberoptic technology and improvements in perfusion systems for establishing cardiopulmonary bypass (CPB) via peripheral cannulation. Society of Thoracic Surgeons data documents that 20% of all mitral valve surgeries are performed using minimally invasive techniques, with half being robotically assisted. This article reviews the current status of robotically assisted mitral valve surgery, its advantages and technical modifications for optimizing clinical outcomes.

Learning curve analysis of mitral valve repair using telemanipulative technology.

OBJECTIVE: To determine if the time required to perform mitral valve repairs using telemanipulation technology decreases with experience and how that decrease is influenced by patient and procedure variables. METHODS: A single-center retrospective review was conducted using perioperative and outcomes data collected contemporaneously on 458 mitral valve repair surgeries using telemanipulative technology. A regression model was constructed to assess learning with this technology and predict total robot time using multiple predictive variables. Statistical analysis was used to determine if models were significantly useful, to rule out correlation between predictor variables, and to identify terms that did not contribute to the prediction of total robot time. RESULTS: We found a statistically significant learning curve (P < .01). The institutional learning percentage∗ derived from total robot times† for the first 458 recorded cases of mitral valve repair using telemanipulative technology is 95% (R(2) = .40). More than one third of the variability in total robot time can be explained through our model using the following variables: type of repair (chordal procedures, ablations, and leaflet resections), band size, use of clips alone in band implantation, and the presence of a fellow at bedside (P < .01). CONCLUSIONS: Learning in mitral valve repair surgery using telemanipulative technology occurs at the East Carolina Heart Institute according to a logarithmic curve, with a learning percentage of 95%. From our regression output, we can make an approximate prediction of total robot time using an additive model. These metrics can be used by programs for benchmarking to manage the implementation of this new technology, as well as for capacity planning, scheduling, and capital budget analysis.