Browsing by Author "Zeybek, Burak"

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Citation - WoS: 15
Citation - Scopus: 14
Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease
(John Wiley and Sons Ltd, 2014) Fatih Şendaǧ; Burak Zeybek; Ali Osman Akdemir; Banu Ozgurel; Kemal Öztekin; Akdemir, Ali; Ozgurel, Banu; Oztekin, Kemal; Zeybek, Burak; Sendag, Fatih
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±7.6min 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. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 18
Citation - Scopus: 19
Learning Curve Analysis of Intracorporeal Cuff Suturing During Robotic Single-Site Total Hysterectomy
(ELSEVIER SCIENCE INC, 2015) Ali Akdemir; Burak Zeybek; Banu Ozgurel; Mehmet Kemal Oztekin; Fatih Sendag; Akdemir, Ali; Ozgurel, Banu; Zeybek, Burak; Oztekin, Mehmet Kemal; Sendag, Fatih
Study Objective: To analyze the learning curve of intracorporeal cuff suturing during robotic single-site total hysterectomy. Design: Retrospective study (Canadian Task Force classification Setting: University hospital. Patients: Twenty-four patients with benign indications for hysterectomy. Interventions: Twenty-four patients who underwent robotic single-site total hysterectomy to treat benign indications were included in the study. Surgical procedures were performed by a single surgeon with extensive experience in laparoscopy using the single-site platform of the da Vinci Surgical System. All vaginal cuffs were closed intracorporeally using semi-rigid single-site instruments. Measurements and Main Results: An exponential learning curve technique was used to analyze the learning curve. The overall mean (SD) vaginal cuff closure time was 23.2 (7) minutes. Learning curve analysis revealed a decrease in vaginal closure time after 14 procedures. Conclusions: An experienced robotic surgeon requires approximately 14 procedures to achieve proficiency in intracorporeal cuff suturing during robotic single-site total hysterectomy. Novel instruments that create perfect triangulation are needed to overcome the current challenges of suturing and to shorten operative time. (C) 2015 AAGL. All rights reserved.