Tong SX, Li RS, Wang D, Xie XM, Ruan Y, Huang L. Artificial intelligence technology and ultrasound-guided nerve block for analgesia in total knee arthroplasty. World J Clin Cases 2023; 11(29): 7026-7033 [PMID: 37946775 DOI: 10.12998/wjcc.v11.i29.7026]
Corresponding Author of This Article
Lin Huang, MD, Doctor, Department of Orthopaedics, Huanggang Central Hospital, No. 6 Qi’an Avenue, Huangzhou District, Huanggang 438000, Hubei Province, China. lhuang0727@sina.com
Research Domain of This Article
Orthopedics
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. Oct 16, 2023; 11(29): 7026-7033 Published online Oct 16, 2023. doi: 10.12998/wjcc.v11.i29.7026
Artificial intelligence technology and ultrasound-guided nerve block for analgesia in total knee arthroplasty
Sheng-Xiong Tong, Ren-Song Li, Dan Wang, Xiao-Meng Xie, Yuan Ruan, Lin Huang
Sheng-Xiong Tong, Department of Pain Management, Wuhan First Hospital, Wuhan 430033, Hubei Province, China
Ren-Song Li, Department of Orthopaedics, Wuhan Wuchang Hospital, Wuhan 430063, Hubei Province, China
Dan Wang, Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, Hubei Province, China
Xiao-Meng Xie, Department of Nursing, Huanggang Central Hospital, Huanggang 438000, Hubei Province, China
Yuan Ruan, Lin Huang, Department of Orthopaedics, Huanggang Central Hospital, Huanggang 438000, Hubei Province, China
Author contributions: Tong SX and Li RS contributed equally to this work; Tong SX and Huang L contributed to the conceptualization, methodology, software of the study; Tong SX and Li RS contributed to the data curation and the drafted the manuscript; Wang D, Xie XM, Li RS and Ruan Y contributed the validation of the study, and the writing, reviewing and editing of the manuscript.
Institutional review board statement: Ethics approval was provided by the ethical committee of Wuhan First Hospital.
Informed consent statement: Written informed consent was obtained from all participants.
Conflict-of-interest statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Lin Huang, MD, Doctor, Department of Orthopaedics, Huanggang Central Hospital, No. 6 Qi’an Avenue, Huangzhou District, Huanggang 438000, Hubei Province, China. lhuang0727@sina.com
Received: August 15, 2023 Peer-review started: August 15, 2023 First decision: August 31, 2023 Revised: September 14, 2023 Accepted: September 22, 2023 Article in press: September 22, 2023 Published online: October 16, 2023 Processing time: 59 Days and 4.4 Hours
ARTICLE HIGHLIGHTS
Research background
Knee joint disease, as one of the common diseases of middle-aged and elderly people, has increased greatly with the aging population. Conventional total knee arthroplasty (TKA) has a high risk of postoperative pain.
Research motivation
Artificial intelligence (AI) combined with ultrasound-guided nerve block anesthesia has achieved ideal results in TKA, effectively reducing the incidence of postoperative complications.
Research objectives
This study aimed to explore the clinical analgesic effect of artificial intelligence and ultrasound-guided nerve block in TKA, and to provide expected clinical guidance for TKA.
Research methods
Patients were randomly divided into two groups: combined spinal-epidural anesthesia and AI combined with ultrasound-guided nerve block anesthesia. The different clinical effects of the two groups were compared.
Research results
Ultrasound-guided nerve block in TKA has longer duration of sensory block and longer duration of motor block in the research group, better postoperative complications and better clinical effect.
Research conclusions
The combination of AI technology and ultrasound-guided nerve block is effective in the treatment of knee lesions in the elderly, with few postoperative complications and significantly analgesic effect, which is worth popularizing and applying.
Research perspectives
The combination of AI technology and ultrasound-guided nerve block is an effective clinical practice method, which provides a certain clinical guidance for postoperative analgesia of knee diseases in middle-aged and elderly people.
