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Feng J, Yan Z, Li M, Zhang Z, Chen X, Du Z, Yang K. Handheld robotic needle holder training: slower but better. Surg Endosc 2020; 35:1667-1674. [PMID: 32514830 DOI: 10.1007/s00464-020-07550-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 04/04/2020] [Indexed: 12/24/2022]
Abstract
BACKGROUND Handheld robotic laparoscopic instruments fill the gap between robotic and conventional instruments, combining the advantages of degrees of freedom and low price. The difficulty and value in learning these new instruments require detailed investigation. METHODS Forty novice surgeons with no laparoscopic experience were randomly assigned to two groups: conventional instrument group (Group Conv) and robotic instrument group (Group Rob). The same training protocol was used in both groups: after viewing a standard operation film, laparoscopic suture training was administered using the corresponding instruments. After each training period, surgeons were tested using a force-sensing test platform. Maximum force (MF) and impulse (IMP) of operators through each ring were recorded. Learning curves based on MF and IMP for both instruments were compared. Institutional review board approval is not needed for this study. RESULTS MF and IMP of both groups decreased with increased training time; the learning curve of Group Conv decreased faster than that of Group Rob. When training time reached 13 h, the MF of Group Rob was significantly lower than that of Group Conv (P < 0.05), while IMP showed no significant difference between the two groups. CONCLUSIONS Effective training reduces operator MF and IMP, possibly decreasing damage to tissues with both conventional and handheld robotic needle holders. Group Rob took longer to reach a plateau, but subsequently had lower suture tension than did Group Conv. MF is more sensitive than IMP for measuring performance progress.
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Affiliation(s)
- Jing Feng
- Department of Urology, ZhongNan Hospital, Wuhan University, No. 169 Donghu Road, Wuhan, 430071, Hubei, China.,Medicine - Remote Mapping Associated Laboratory, ZhongNan Hospital, Wuhan University, Wuhan, China
| | - Zhiyuan Yan
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, No. 92, Xidazhi Street, Nangang District, Harbin, 150000, China
| | - Man Li
- Department of Urology, ZhongNan Hospital, Wuhan University, No. 169 Donghu Road, Wuhan, 430071, Hubei, China.,Medicine - Remote Mapping Associated Laboratory, ZhongNan Hospital, Wuhan University, Wuhan, China
| | - Zhang Zhang
- Department of Urology, ZhongNan Hospital, Wuhan University, No. 169 Donghu Road, Wuhan, 430071, Hubei, China.,Medicine - Remote Mapping Associated Laboratory, ZhongNan Hospital, Wuhan University, Wuhan, China
| | - XiaoJia Chen
- Department of Urology, ZhongNan Hospital, Wuhan University, No. 169 Donghu Road, Wuhan, 430071, Hubei, China.,Medicine - Remote Mapping Associated Laboratory, ZhongNan Hospital, Wuhan University, Wuhan, China
| | - Zhijiang Du
- State Key Laboratory of Robotics and System, Harbin Institute of Technology, No. 92, Xidazhi Street, Nangang District, Harbin, 150000, China.
| | - Kun Yang
- Department of Urology, ZhongNan Hospital, Wuhan University, No. 169 Donghu Road, Wuhan, 430071, Hubei, China. .,Medicine - Remote Mapping Associated Laboratory, ZhongNan Hospital, Wuhan University, Wuhan, China.
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