Robot-assisted partial nephrectomy: Evaluation of learning curve for an experienced renal surgeon

Mohammed Haseebuddin, Brian M. Benway, Jose M. Cabello, Sam B. Bhayani

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

Abstract

Purpose: The learning curve for robot-assisted partial nephrectomy (RAPN) has not been extensively studied. We therefore evaluated the learning curve of RAPN for a fellowship-trained laparoscopic surgeon with extensive prior experience with laparoscopic partial nephrectomy (LPN). We also examined the potential effect of tumor size on the learning curve. Patients and Methods: We prospectively evaluated 38 consecutive patients undergoing RAPN by a single surgeon (S.B.B.). Sixteen patients had tumors <2 cm, and 22 patients had tumors >2 cm. Warm ischemia times and overall operative times were recorded as indices of learning progression. Results: Average operative time for tumors <2 cm was 131.9 minutes (115.3-148.5 minutes) and for tumors >2 cm was 145.8 minutes (131.1-160.5 minutes). The difference between the operative times for tumors <2 and >2 cm was not statistically significant (p = 0.23). Average warm ischemia time for tumors <2 cm was 21 minutes (16.9-25.1 minutes) and for tumors >2 cm was 24.7 minutes (21.3-28.1 minutes). This difference was also not statistically significant (p = 0.20). Defined by the overall operative time, the learning curve for RAPN was 16 cases, and by ischemic time, the learning curve was 26 cases. Tumor size did not have an effect on the learning curve. Conclusions: The learning curve for RAPN is short for surgeons already experienced with LPN. The learning curve for portions performed under warm ischemia is slightly longer, implying that the critical portions of the procedure require more experience to become facile. Tumor size does not appear to have a significant impact on the learning curve for surgeons experienced with LPN.

Original languageEnglish
Pages (from-to)57-61
Number of pages5
JournalJournal of Endourology
Volume24
Issue number1
DOIs
StatePublished - Jan 1 2010

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