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. 2003 Sep;76(3):749-53.
doi: 10.1016/s0003-4975(03)00680-5.

Analysis of the learning curve in telerobotic, beating heart coronary artery bypass grafting: a 90 patient experience

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Analysis of the learning curve in telerobotic, beating heart coronary artery bypass grafting: a 90 patient experience

Richard J Novick et al. Ann Thorac Surg. 2003 Sep.

Abstract

Background: Recent articles have commented on the "learning curve" in robotic-assisted coronary artery bypass grafting. We systematically studied this phenomenon using standard statistical and cumulative sum (CUSUM) failure methods.

Methods: Ninety patients underwent internal thoracic artery (ITA) takedown and an attempt at ITA to coronary bypass on the beating heart using the Zeus telerobotic system from September 1999 to December 2001. The rates of mortality and 11 predefined major complications were compared in five quintiles of 18 consecutive patients each and a CUSUM curve was generated for the entire cohort.

Results: All patients but one underwent successful endoscopic ITA takedown. Thirteen patients had a totally endoscopic anastomosis, whereas in 61 a small mini-thoracotomy or mini-sternotomy was used. Sixteen patients (17.8%) were converted electively to a sternotomy: 11 patients underwent off-pump and 5 patients on-pump surgery. There were no deaths; 13 patients (14.4%) incurred one or more of the 11 major complication(s), including 5, 1, 2, 3, and 2 in each of the five quintiles (p = 0.39). Standard statistical analyses identified a significant decrease in operating room time (p < 0.0001), as well as a decrease in the incidence of an occluded graft or wrong vessel grafted from quintiles 1 to 5 (p = 0.03). On CUSUM analysis, the failure curve was steep for the first 18 to 20 patients, before moderating its slope for the remainder of the experience.

Conclusions: Robotic ITA to coronary bypass on the beating heart has a moderately steep learning curve, which is mitigated by further experience. CUSUM analysis complimented standard statistical methods in detecting a cluster of suboptimal results during the early experience with this procedure.

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