Quality of life in patients who undergo conventional or robotic-assisted total laparoscopic hysterectomy

Abstract

Abstract Background: Hysterectomy for benign gynecologic diseases, especially dysfunctional uterine bleeding, is one of the most common gynecologic interventions. The uterus can be removed using abdominal, vaginal, laparoscopic, or robotic-assisted laparoscopic hysterectomy. In a robotic-assisted procedure, the surgeon directs the robot while seated at a console in the operating room. This differs from laparoscopic hysterectomy because a “robot” performs the operation, while the surgeon watches a monitor. This systematic review will compare quality of life (QOL) in patients who undergo total robotic-assisted laparoscopic hysterectomy for benign indications and those who undergo conventional laparoscopic surgery. Methods: We will perform a systematic review according to the Cochrane Methodology for randomized controlled trials. The review will include studies reporting use of QOL metrics to assess patients who undergo total hysterectomy for benign indications using robotic-assisted technique or conventional laparoscopic surgery. QOL will be the primary outcome and will be measured using validated instruments. An overall search strategy will be developed and adapted for Embase, MEDLINE, LILACS, and CENTRAL databases. Two reviewers will independently select the eligible studies, assess the risk of bias, and extract the data from included studies. Similar outcomes measured in at least 2 trials will be plotted in the meta-analysis using Review Manager 5.3. The quality of evidence will be determined using the GRADE approach. Results: This systematic review is designed to provide high quality evidence on QOL in patients undergoing total hysterectomy for benign indications using either robotic-assisted or conventional laparoscopic surgery. Conclusion: It is expected that high-quality evidence on QOL can be used to guide decision-making by institutions and clinicians to improve health care; the evidence can also be used in future studies. PROSPERO registration number: PROSPERO CRD 42019129913