Yang Wenxiao, Zeng Hai, Jin Yueling
Business School, University of Shanghai for Science & Technology, Shanghai, China.
The First Affiliated Hospital of Jinan University, Guangzhou, China.
BMJ Open. 2024 Jul 17;14(7):e080605. doi: 10.1136/bmjopen-2023-080605.
The prevalence of overweight or obesity among patients undergoing pancreaticoduodenectomy is on the rise. The utilisation of robotic assistance has the potential to enhance the feasibility of performing minimally invasive pancreaticoduodenectomy in this particular group of patients who are at a higher risk. The objective of this meta-analysis is to assess the safety and effectiveness of robotic pancreaticoduodenectomy in individuals with overweight or obesity.
This investigation will systematically search for randomised controlled trials (RCTs) and non-randomised comparative studies that compare robotic pancreaticoduodenectomy with open or laparoscopic pancreaticoduodenectomy in patients with overweight or obesity, using PubMed, Embase and the Cochrane Library databases. The methodological quality of studies will be evaluated using the Cochrane risk of bias tool for RCTs and the Newcastle-Ottawa Scale for observational studies. RevMan software (V.5.4.1) will be used for statistical analysis. The OR and weighted mean differences will be calculated separately for dichotomous and continuous data. The selection of a fixed-effects or random-effects model will depend on the level of heterogeneity observed among the included studies.
This study will be conducted based on data in the published literature from publicly available databases. Therefore, ethics approval is not applicable. The results will be disseminated in a peer-reviewed journal.
CRD42023462321.
接受胰十二指肠切除术的患者中超重或肥胖的患病率正在上升。对于这一高风险的特定患者群体，使用机器人辅助有可能提高实施微创胰十二指肠切除术的可行性。本荟萃分析的目的是评估机器人胰十二指肠切除术在超重或肥胖个体中的安全性和有效性。
本研究将使用PubMed、Embase和Cochrane图书馆数据库，系统检索比较机器人胰十二指肠切除术与开放或腹腔镜胰十二指肠切除术在超重或肥胖患者中的随机对照试验（RCT）和非随机对照研究。将使用Cochrane偏倚风险工具评估RCT的研究方法质量，使用纽卡斯尔-渥太华量表评估观察性研究的质量。将使用RevMan软件（V.5.4.1）进行统计分析。将分别计算二分法和连续数据的比值比（OR）和加权平均差。固定效应模型或随机效应模型的选择将取决于纳入研究中观察到的异质性水平。
本研究将基于公开可用数据库中已发表文献的数据进行。因此，无需伦理批准。研究结果将在同行评审期刊上发表。
PROSPERO注册号：CRD42023462321。
