Robotic-Assisted vs. Standard Laparoscopic Surgery for Rectal Cancer Resection: A Systematic Review and Meta-Analysis of 19,731 Patients.
Kamil SafiejkoRadoslaw TarkowskiMaciej KoselakMarcin JuchimiukAleksander TarasikFrancesco ChiricoJacek SmerekaAgnieszka SzarpakPublished in: Cancers (2021)
Robotic-assisted surgery is expected to have advantages over standard laparoscopic approach in patients undergoing curative surgery for rectal cancer. PubMed, Cochrane Library, Web of Science, Scopus and Google Scholar were searched from database inception to 10 November 2021, for both RCTs and observational studies comparing robotic-assisted versus standard laparoscopic surgery for rectal cancer resection. Where possible, data were pooled using random effects meta-analysis. Forty-Two were considered eligible for the meta-analysis. Survival to hospital discharge or 30-day overall survival rate was 99.6% for RG and 98.8% for LG (OR = 2.10; 95% CI: 1.00 to 4.43; p = 0.05). Time to first flatus in the RG group was 2.5 ± 1.4 days and was statistically significantly shorter than in LG group (2.9 ± 2.0 days; MD = -0.34; 95%CI: -0.65 to 0.03; p = 0.03). In the case of time to a liquid diet, solid diet and bowel movement, the analysis showed no statistically significant differences ( p > 0.05). Length of hospital stay in the RG vs. LG group varied and amounted to 8.0 ± 5.3 vs. 9.5 ± 10.0 days (MD = -2.01; 95%CI: -2.90 to -1.11; p < 0.001). Overall, 30-days complications in the RG and LG groups were 27.2% and 19.0% (OR = 1.11; 95%CI: 0.80 to 1.55; p = 0.53), respectively. In summary, robotic-assisted techniques provide several advantages over laparoscopic techniques in reducing operative time, significantly lowering conversion of the procedure to open surgery, shortening the duration of hospital stay, lowering the risk of urinary retention, improving survival to hospital discharge or 30-day overall survival rate.
Keyphrases
- rectal cancer
- minimally invasive
- laparoscopic surgery
- systematic review
- locally advanced
- coronary artery bypass
- robot assisted
- patients undergoing
- physical activity
- free survival
- healthcare
- weight loss
- end stage renal disease
- ejection fraction
- public health
- molecular dynamics
- prognostic factors
- surgical site infection
- meta analyses
- randomized controlled trial
- newly diagnosed
- risk factors
- acute coronary syndrome
- radiation therapy
- machine learning
- coronary artery disease
- big data
- emergency department
- electronic health record
- artificial intelligence
- deep learning
- patient reported