Table 1.
Author (YOP) | Country | Robot | Design | FU (mo) | Age | Sample | Gender (M/F) | ||||
---|---|---|---|---|---|---|---|---|---|---|---|
RA | FH | RA | FH | Total | RA | FH | |||||
Cao (2017) [33] | China | Universal Robots | RCS | 14.7 | 44.7 | 47.9 | 20 | 36 | 56 | 10/10 | 19/17 |
Chen (2023) [17] | China | TiRobot | RCS | 31.4 | 43.6 (13.7) | 45.7 (12.7) | 32 | 36 | 68 | 18/14 | 17/19 |
Duan (2019) [12] | China | TiRobot | RCS | 13.6 | 61.7 (5.2) | 62.1 (4.1) | 26 | 23 | 49 | 11/15 | 9/14 |
He (2019) [13] | China | Bi-planar robot | RCS | 24 | 56 (11.1) | 56.2 (9.13) | 30 | 30 | 60 | 11/19 | 12/18 |
Huang (2017) [34] | China | Bi-planar robot | RCS | 19.6 | 59.4 (5.6) | 59.1 (4.9) | 32 | 32 | 64 | 10/22 | 12/20 |
Huang (2023) [44] | China | TiRobot Advance | RCS | 22.2 | 48.2 (11.9) | 48.5 (9.8) | 25 | 28 | 53 | 11/14 | 12/16 |
Jiang (2024) [18] | China | TiRobot | RCS | 15.6 | 53.61 (5.45) | 55.23 (4.64) | 16 | 20 | 36 | 7/9 | 8/12 |
Jing (2022) [35] | China | TiRobot | RCS | 7 | 55.2 | 55 | 31 | 43 | 74 | 11/20 | 14/29 |
Lei (2021) [36] | China | TiRobot | RCS | 6 | 51.86 (4.89) | 51.33 (4.3) | 21 | 21 | 42 | 12/9 | 14/7 |
Liao (2022) [37] | China | TiRobot | RCS | 8 | 44.1 (8.7) | 48.8 (8) | 14 | 14 | 28 | 6/8 | 7/7 |
Liu (2015) [38] | China | GD-2000 | RCS | 12.5 | 65.2 (4.2) | 60.5 (5.1) | 21 | 25 | 46 | 8/13 | 11/14 |
Liu (2023) [39] | China | TiRobot | RCS | 24 | 71.3 | 73.2 | 21 | 20 | 41 | 10/11 | 8/12 |
Liu (2024) [19] | China | TiRobot | RCS | 12 | 51.92 (6.41) | 50.08 (8.41) | 26 | 26 | 52 | 17-Sep | 11/15 |
Lou (2024) [20] | China | Tianji Robot | RCS | 13 | 46.2 (9.3) | 48.2 (7.8) | 28 | 32 | 60 | 12/16 | 15/17 |
Nie (2023) [21] | China | TiRobot | RCS | 14.9 | 56 (4.22) | 54.87 (4.81) | 18 | 23 | 41 | 8/10 | 10/13 |
Tong (2016) [14] | China | TiRobot | RCS | 18 | 47.5 | 51.5 | 20 | 18 | 38 | 12/8 | 11/7 |
Wan (2021) [40] | China | Tianji Robot | RCT | 6 | 51.86 (4.89) | 51.33 (4.3) | 21 | 21 | 42 | 12/9 | 14/7 |
Wang (2011) [15] | China | Bi-planar robot | RCS | - | - | - | 6 | 6 | 12 | - | - |
Wang (2019) [16] | China | TiRobot | RCS | 12 | 49.03 (8.23) | 49.8 (7.68) | 63 | 65 | 128 | 30/33 | 31/34 |
Wang (2023) [22] | China | TiRobot | RCS | 12 | 59.5 (8.7) | 60.1 (8.2) | 56 | 56 | 112 | 32/34 | 30/36 |
Wang (2024) [23] | China | TiRobot | RCS | 6 | 41.95 (5.39) | 40.8 (5.08) | 30 | 32 | 62 | - | - |
Yi (2022) [41] | China | TINAVI | RCT | 18 | 58.5 (6.3) | 57.5 (5.3) | 32 | 36 | 68 | 19/13 | 16/20 |
Zhao (2024) [43] | China | TiRobot | RCS | 12 | 53.87 (5.28) | 52.36 (5.05) | 37 | 35 | 72 | 16/21 | 13/22 |
Zhu (2021) [42] | China | TiRobot | RCS | 38.8 | 47.9 (13.5) | 47.7 (12.6) | 50 | 83 | 133 | 26/24 | 47/36 |
RCS: retrospective cohort study; RCT: randomized controlled trial; YOP: year of publication; FU: follow-up; mo: month; RA: robot-assisted; FH: freehand; M/F: male/female. Age data are presented as mean (standard deviation).