Introduction
Materials and methods
Search strategy
Inclusion and exclusion criteria
Data extraction
Risk of bias assessment
Data and statistical analyses
Results
Systematic review
Overall characteristics of included studies
Author | Country | Study design | Study arms | Sample size | Time period | Follow-up |
---|---|---|---|---|---|---|
Billfeldt et al. (2018) [16] | Sweden | Database | Robotic | 1015 | 2009–2015 | 1 year |
Lap | 1539 | |||||
Vaginal | 3767 | |||||
Open | 7485 | |||||
Brunes et al. (2021) [17] | Sweden | Database | Robotic | 249 | Jan. 1, 2015–Dec. 31, 2017 | 1 year |
Lap | 317 | |||||
Vaginal | 218 | |||||
Open | 751 | |||||
Carbonnel et al. (2013) [18] | France | Pro Compare | Robotic | 60 | Mar. 2010–Mar. 2012 | 2 months |
Vaginal | 34 | |||||
Cohen et al. (2014) [19] | USA | Database | Robotic Benign | 18,836 | 2009 | Discharge |
Lap Benign | 84,569 | |||||
Vaginal Benign | 77,940 | |||||
Open Benign | 232,633 | |||||
Dandolu et al. (2018) [20]a | USA | Database | Robotic | 12,029 | 2008–2012 | 90 days |
Lap | 15,971 | |||||
Vaginal | 43,936 | |||||
Open | 145,047 | |||||
Deimling et al. (2017) [21] | USA | RCT | Robotic | 72 | Apr. 23–Oct. 20, 2014 | 3 months |
Lap | 72 | |||||
Dubeshter et al. (2013) [22]b | USA | Database | Robotic | 1192 | 2011 | Discharge |
Lap | 2557 | |||||
Vaginal | 2200 | |||||
Open | 7926 | |||||
Elessawy et al. (2020) [23] | Germany | Pro Compare | Robotic | 56 | Jan. 1, 2013–Dec. 31, 2017 | 20 weeks |
Lap | 99 | |||||
Friedman et al. (2016) [24] | USA | Database | Inpatient Matched | 2011 | 1 month | |
Robotic | 7056 | |||||
Non-Robotic | 7056 | |||||
Outpatient Matched | ||||||
Robotic | 7199 | |||||
Non-Robotic | 7199 | |||||
Inpatient Matched | ||||||
Hart et al. (2013) [25]c | USA | Database | Robotic | 3971 | Jan. 1, 2009–Jun. 30, 2011 | Discharge |
Lap | 4363 | |||||
Endo Stitch | 974 | |||||
Herrinton et al. (2020) [26] | USA | Database | Robotic | 560 | Jan. 1, 2011–Sept. 30, 2015 | 90 days |
Lap | 6785 | |||||
Lim et al. (2016) [27] Risk | USA | Database | Robotic | 4528 | Jan. 1, 2013–Jul. 2, 2014 | 1 month |
Lap | 2464 | |||||
Lim et al. (2016) [28] Multi | USA | Database | Robotic | 2300 | Jan. 1, 2010–Sept. 30, 2013 | 1 month |
Lap | 11,952 | |||||
Vaginal | 8121 | |||||
Open | 9745 | |||||
Lonnerfors et al. (2015) [29]d | Sweden | RCT | Robotic | 61 | Jan. 2010–Jun. 2013 | 4 months |
Lap | 36 | |||||
Vaginal | 25 | |||||
Luciano et al. (2016) [30] | USA | Database | Robotic | 20,781 | Jan. 2005–Dec. 2010 | 1 month |
Lap | 78,148 | |||||
Vaginal | 52,635 | |||||
Open | 138,311 | |||||
Martinez-Maestre et al. (2014) [31] | Spain | Pro Compare | Robotic | 51 | Jan. 2008–Dec. 2009 | 1 month |
Lap | 54 | |||||
Ngan et al. (2018) [32] | Canada | Database | Robotic | 10,677 | 2008–2012 | Discharge |
Lap | 33,088 | |||||
Paraiso et al. (2013) [33] | USA | RCT | Robotic | 26 | June.2007–Mar. 2011 | 6 months |
Lap | 26 | |||||
Pellegrino et al. (2017) [34] | Italy | Pro Compare | Robotic | 64 | Sept. 2014–Sept. 2015 | 3 months |
Lap | 130 | |||||
Open | 74 | |||||
Rosero et al. (2013) [35] | USA | Database | Robotic | 7788 | 2009–2010 | Discharge |
Lap | 7788 | |||||
Sarlos et al. (2012) [36] | Switzerland | RCT | Robotic | 47 | 2008–2011 | 2 months |
Lap | 48 | |||||
Swenson et al. (2016) [37]e | USA | Database | Robotic | 1338 | Jan. 1, 2013–Jul. 1, 2014 | 1 month |
Lap | 539 | |||||
Vaginal | 361 | |||||
Ulubay et al. (2016) [38] | Turkey | Pro Compare | Robotic | 20 | Jan. 2011–Jan. 2015 | 6 months |
Open | 20 | |||||
Wright et al. (2013) [39]f | USA | Database | Robotic | 4971 | 2007–2010 | 1 month |
Lap | 4971 | |||||
Robotic | 5359 | |||||
Open | 5359 |
Risk of bias assessment
Baseline patient characteristics
Meta-analysis | Heterogeneity | |||||||
---|---|---|---|---|---|---|---|---|
Outcome | # Studies | Robot n | Comparator n | Effect size [95% CI] | p-value | Model | I2 | p-value |
Robotic vs. Laparoscopic | ||||||||
Age (year) | 14 | 56,406 | 190,162 | MD: 0.95 [0.18, 1.71] | 0.01 | RE | 98% | < 0.00001 |
BMI | 8 | 1715 | 1803 | MD: 0.25 [– 0.64, 1.14] | 0.58 | RE | 67% | 0.003 |
Uterine weight (g) | 6 | 1579 | 802 | MD: – 23.6 [– 33.45, – 13.91] | < 0.0001 | FE | 0% | 0.88 |
# Large uterus | 3 | 2842 | 18,362 | OR: 1.10 [1.00, 1.22] | 0.06 | FE | 30% | 0.24 |
Prior surgery | 7 | 2623 | 3214 | OR: 0.97 [0.74, 1.25] | 0.79 | RE | 61% | 0.02 |
Robotic vs. Open | ||||||||
Age | 7 | 71,887 | 554,020 | MD: 0.77 [0.20, 1.33] | 0.008 | RE | 99% | < 0.00001 |
BMI | 2 | 84 | 94 | MD: – 1.14 [– 5.05, 2.77] | 0.57 | RE | 91% | 0.0007 |
# Large uterus | 2 | 3315 | 17,230 | OR: 1.47 [0.14, 15.45] | 0.75 | RE | 100% | < 0.00001 |
Prior surgery | 2 | 84 | 94 | OR: 0.37 [0.03, 5.39] | 0.47 | RE | 81% | 0.02 |
Robotic vs. Vaginal | ||||||||
Age (year) | 6 | 71,863 | 192,719 | MD: – 1.74 [– 3.64, 0.16] | 0.07 | RE | 100% | < 0.00001 |
Uterine weight (g) | 3 | 1459 | 420 | MD: 0.70 [– 126.49, 127.90] | 0.99 | RE | 99% | < 0.00001 |
# Large uterus | 2 | 3315 | 11,888 | OR: 1.87 [1.13, 3.11] | 0.02 | RE | 95% | < 0.00001 |
Prior surgery | 2 | 1075 | 3801 | OR: 1.79 [1.56, 2.05] | < 0.00001 | FE | 0% | 0.75 |