Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease

Autor: Kemal Öztekin, Burak Zeybek, Fatih Sendag, Ali Akdemir, Banu Ozgurel
Rok vydání: 2013
Předmět:
Zdroj: The International Journal of Medical Robotics and Computer Assisted Surgery. 10:275-279
ISSN: 1478-5951
DOI: 10.1002/rcs.1567
Popis: Background The objective was to evaluate the learning curve for performing a robotic hysterectomy to treat benign gynaecological disease. Methods Thirty-six patients underwent robotic hysterectomy for benign indications. A systematic chart review of consecutive cases was conducted. The collected data included age, BMI, operating time, set-up time, docking time, uterine weight, blood loss, intraoperative complications, postoperative complications, conversions to laparotomy and length of hospital stay. Results The mean operating, set-up and docking times were 169 ± 54.5, 52.9 ± 12.4 and 7.8 ± 7.6 min, respectively. The learning curve analysis revealed a decrease in both docking and operating times, with both curves plateauing after case 9. Conclusions The learning curve analysis revealed a decrease in docking time and operating time after case 9, suggesting that there might be a fast, learning curve for experienced laparoscopic surgeons to master robotic hysterectomy, and that the docking process does not have a significant negative influence on the overall operating time. Copyright © 2013 John Wiley & Sons, Ltd.
Databáze: OpenAIRE