Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease
Makaleler > Tam Makale · 2013
Yazarlar: Fatih ŞENDAĞ, Burak ZEYBEK, Ali AKDEMİR, Banu Ozgurel, Kemal OZTEKIN
The International Journal of Medical Robotics and Computer Assisted Surgery, SCI Expanded İndekslerine Giren Dergi, Uluslararası, Wos, 2013, cilt 10, ss 275-279
DOI: 10.1002/rcs.1567
Özet
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.