Robotic versus laparoscopic gastrectomy for gastric cancer in patients with obesity: systematic review and meta-analysis
Xianzhe Yu, Lingling Zhu, Yan Zhang, Qingbo Feng
- 发表年份
- 2023
- 引用次数
- 10
- 访问权限
- 开放获取
摘要
Introduction: The number of overweight patients with gastric cancer (GC) is increasing, and no previous study has compared laparoscopic gastrectomy (LG) and robotic gastrectomy (RG) in obese patients with GC. To investigate the perioperative and oncologic outcomes of RG and LG in obese GC patients, we performed a meta-analysis of propensity matched scores and retrospective studies to compare the perioperative parameters, oncologic findings, and short-term postoperative outcomes between the two groups. Methods: This study was performed according to the PRISMA guidelines. A search was performed on PubMed, Web of Science, EMBASE, and Cochrane Central Register to identify eligible propensity matched scores and retrospective studies conducted and published before December 2022. Data on perioperative and oncological outcomes were included in the meta-analysis. Results: Overall, we identified 1 propensity score match study and 5 randomized control trials of RG and LG, enrolling a total of 718 patients (197 and 521 patients received RG and LG, respectively). No significant differences were observed between the two groups in terms of complications, bleeding, or lymph node dissection. Of note, RG had a longer procedure time (P = 0.03), earlier oral intake (P = 0.0010), shorter hospital stay (P = 0.0002), and shorter time to defecation (P < 0.00001). Conclusions: This meta-analysis concluded that patients in the RG group had shorter hospital stays, earlier postoperative feeding, and earlier postoperative ventilation; however, no differences were found in blood loss, number of lymph nodes removed, or overall complications. RG is an effective, safe, and promising treatment for obese patients with GC, compensating for the shortcomings of laparoscopy and allowing for less trauma and faster recovery. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022298967.
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