Analysis of the learning curve of robot-assisted laparoscopic aortofemoral bypass
| Autoři | |
|---|---|
| Rok publikování | 2012 |
| Druh | Vyžádané přednášky |
| Fakulta / Pracoviště MU | |
| Citace | |
| Popis | Introduction: Advanced minimally invasive surgery is typically associated with appreciable learning curves. Robotic operating systems are used to facilitate the most complex procedures. Minimally invasive vascular surgery of the aortoiliac region belongs to this group. The objective of our study was to evaluate the learning process of robot-assisted laparoscopic aortofemoral bypass for aortoiliac occlusive disease in a group of 63 patients. Materials/Methods: Between May 2006 and December 2011, 63 patients (48 men, 15 women) at a median age of 58 years (range, 44-75 years), underwent 63 robot-assisted laparoscopic aortofemoral bypass procedures. The process of learning was evaluated by the assessment of learning curves. For continuous variables, they were constructed using the cumulative average-time model and power function regression (operative, aortoiliac segment dissection, clamping and anastomosis time). For the evaluation of conversion rate (binary variable) we used a cumulative summation (CUSUM) technique. Results: We implanted 33 aortobifemoral and 30 aortofemoral bypasses. In 60 cases, we completed the procedure successfully using minimally invasive approach. We had to convert to open surgery three times. The median proximal anastomosis time was 23 minutes (range, 18-50 minutes), median clamping time 65 minutes (range, 40-125 minutes), median aortoiliac segment dissection time 125 minutes (range, 45-315 minutes) and median operative time 270 minutes (range, 180-475 minutes). The 30-day mortality rate was 0%. During the follow-up period (median 31 months; range, 6-72 months), we observed 3 early occlusions (5%) and 1 graft infection (2%). After reoperations, the secondary patency of reconstructions was 100%. Data showed a typical short learning curve for proximal anastomosis creation, confirming the positive contribution of the robotic system. The operative time and aortoiliac segment dissection time learning curves were less steep, demonstrating the complexity of the whole procedure and laparoscopic retroperitoneal dissection as well. The reduction of the aortoiliac segment dissection time contributed the most to the overall procedure time improvement. The learning curve for clamping time was the flattest. Only the proximal anastomosis time contributed to its reduction, as expected. The conventional creation of distal anastomoses in the groin was constant. CUSUM analysis confirmed that we had achieved better a conversion rate than the set 5% after 31 procedures. Conclusions: One of the main difficulties of laparoscopic bypass grafting, anastomosis creation, has been overcome using a robotic operating system and its learning curve is short. Therefore, the acceptable anastomosis and clamping time can be achieved easily even during the learning curve. The whole procedure remains an advanced endoscopic surgery and the retroperitoneal dissection is now its most challenging part. Previous laparoscopic experience and training is crucial for the successful application of this method. Totally robotic retroperitoneal dissection or development of laparoscopic retroperitoneal approach may lead to further operative time reduction. Robot-assisted laparoscopic aortoiliac bypass grafting seems a safe method with a low complication rate. |