BACKGROUND: Robotic partial nephrectomy (RPN) is emerging as an alternative to traditional laparoscopic partial nephrectomy (LPN). Despite the potential advantages of the robotic approach, renorrhaphy remains a challenging portion of the procedure. OBJECTIVE: To present our technique and outcomes for RPN, including sliding-clip renorrhaphy. DESIGN, SETTING, AND PARTICIPANTS: Between 2007 and 2008, 50 patients underwent RPN performed by a single attending surgeon. SURGICAL PROCEDURE: In this paper, we describe our technique for RPN, including a sliding-clip renorrhaphy, which is distinguished by the use of Weck Hem-O-Lock clips that are slid into place under complete control of the surgeon seated at the console and secured with a LapraTy clip. For the first 13 procedures, traditional tied-suture or assistant-placed clip closures were performed; sliding-clip renorrhaphy was performed in the remaining 37 cases. RESULTS AND LIMITATIONS: Mean tumor size was 2.5 cm. Mean operative time was 145.3 min, and mean overall warm ischemia time was 17.8 min. Mean estimated blood loss was 140.3 ml. The learning curve for overall operative time was 19 cases; the learning curve for portions of the case performed under warm ischemia (including tumor resection and renorrhaphy) was 26 cases. The introduction of a sliding-clip renorrhaphy produced significant reductions in overall operative time and warm ischemia time, while blood loss and hospital stay remained stable over our experience. Limitations of RPN include cost and increased reliance on the bedside assistant. CONCLUSIONS: Sliding-clip renorrhaphy provides an efficient and effective repair that is under nearly complete control of the surgeon. This technique appears to contribute to significantly shorter overall operative times and, perhaps most critically, to shorter warm ischemia times. The learning curve for RPN using this technique appears to be foreshortened compared with LPN.
BACKGROUND: Robotic partial nephrectomy (RPN) is emerging as an alternative to traditional laparoscopic partial nephrectomy (LPN). Despite the potential advantages of the robotic approach, renorrhaphy remains a challenging portion of the procedure. OBJECTIVE: To present our technique and outcomes for RPN, including sliding-clip renorrhaphy. DESIGN, SETTING, AND PARTICIPANTS: Between 2007 and 2008, 50 patients underwent RPN performed by a single attending surgeon. SURGICAL PROCEDURE: In this paper, we describe our technique for RPN, including a sliding-clip renorrhaphy, which is distinguished by the use of Weck Hem-O-Lock clips that are slid into place under complete control of the surgeon seated at the console and secured with a LapraTy clip. For the first 13 procedures, traditional tied-suture or assistant-placed clip closures were performed; sliding-clip renorrhaphy was performed in the remaining 37 cases. RESULTS AND LIMITATIONS: Mean tumor size was 2.5 cm. Mean operative time was 145.3 min, and mean overall warm ischemia time was 17.8 min. Mean estimated blood loss was 140.3 ml. The learning curve for overall operative time was 19 cases; the learning curve for portions of the case performed under warm ischemia (including tumor resection and renorrhaphy) was 26 cases. The introduction of a sliding-clip renorrhaphy produced significant reductions in overall operative time and warm ischemia time, while blood loss and hospital stay remained stable over our experience. Limitations of RPN include cost and increased reliance on the bedside assistant. CONCLUSIONS: Sliding-clip renorrhaphy provides an efficient and effective repair that is under nearly complete control of the surgeon. This technique appears to contribute to significantly shorter overall operative times and, perhaps most critically, to shorter warm ischemia times. The learning curve for RPN using this technique appears to be foreshortened compared with LPN.
Authors: Jonathan D Harper; Anup Shah; Stuart B Mitchell; Yak-Nam Wang; Frank Starr; Michael R Bailey; Lawrence A Crum Journal: J Endourol Date: 2012-09-10 Impact factor: 2.942
Authors: Scott Tobis; Sriram Venigalla; Joy K Knopf; Emelian Scosyrev; Erdal N Erturk; Dragan J Golijanin; Jean V Joseph; Hani Rashid; Guan Wu Journal: J Robot Surg Date: 2011-06-10