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Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol

Silent cerebrovascular disease (SCD), which is a common disease in the elderly, leads to cognitive decline, gait disorders, depression and urination dysfunction, and increases the risk of cerebrovascular events. Our study aims to compare the accuracy of the diagnosis of SCD-related gait disorders be...

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Autores principales: Fei, Beini, Zhao, Jin, Li, Xin, Tang, Yanmin, Qin, Guoyou, Zhang, Wei, Ding, Jing, Hu, Min, Wang, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948402/
https://www.ncbi.nlm.nih.gov/pubmed/35332042
http://dx.doi.org/10.1136/bmjopen-2021-055880
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author Fei, Beini
Zhao, Jin
Li, Xin
Tang, Yanmin
Qin, Guoyou
Zhang, Wei
Ding, Jing
Hu, Min
Wang, Xin
author_facet Fei, Beini
Zhao, Jin
Li, Xin
Tang, Yanmin
Qin, Guoyou
Zhang, Wei
Ding, Jing
Hu, Min
Wang, Xin
author_sort Fei, Beini
collection PubMed
description Silent cerebrovascular disease (SCD), which is a common disease in the elderly, leads to cognitive decline, gait disorders, depression and urination dysfunction, and increases the risk of cerebrovascular events. Our study aims to compare the accuracy of the diagnosis of SCD-related gait disorders between the intelligent system and the clinician. Our team have developed an intelligent evaluation system for gait. This study will evaluate whether the intelligent system can help doctors make clinical decisions and predictions, which aids the early prevention and treatment of SCD. METHODS AND ANALYSIS: This study is a multi-centred, prospective, randomised and controlled trial. SCD subjects aged 60–85 years in Shanghai and Guizhou will be recruited continuously. All subjects will randomly be divided into a doctor with intelligence assistance group or a doctor group, at a 1:1 ratio. The doctor and intelligent assistant group will accept the intelligent system evaluation. The intelligent system obtains gait parameters by an Red-Green-Blue-depth camera and computer vision algorithm. The doctor group will accept the clinicians’ routine treatment procedures. Meanwhile, all subjects will accept the panel’s gait assessment and recognition rating scale as the gold standard. The primary outcome is the sensitivity of the intelligent system and clinicians to screen for gait disorders. The secondary outcomes include the healthcare costs and the incremental cost effectiveness ratio of intelligent systems and clinicians to screen for gait disorders. ETHICS AND DISSEMINATION: Approval was granted by the Ethics Committee of Zhongshan Hospital affiliated with Fudan University on 26 November 2019. The approval number is B2019-027(2) R. All subjects will sign an informed consent form before enrolment. Serious adverse events will be reported to the main researchers and ethics committees. The subjects’ data will be kept strictly confidential. The results will be disseminated in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04457908
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spelling pubmed-89484022022-04-08 Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol Fei, Beini Zhao, Jin Li, Xin Tang, Yanmin Qin, Guoyou Zhang, Wei Ding, Jing Hu, Min Wang, Xin BMJ Open Neurology Silent cerebrovascular disease (SCD), which is a common disease in the elderly, leads to cognitive decline, gait disorders, depression and urination dysfunction, and increases the risk of cerebrovascular events. Our study aims to compare the accuracy of the diagnosis of SCD-related gait disorders between the intelligent system and the clinician. Our team have developed an intelligent evaluation system for gait. This study will evaluate whether the intelligent system can help doctors make clinical decisions and predictions, which aids the early prevention and treatment of SCD. METHODS AND ANALYSIS: This study is a multi-centred, prospective, randomised and controlled trial. SCD subjects aged 60–85 years in Shanghai and Guizhou will be recruited continuously. All subjects will randomly be divided into a doctor with intelligence assistance group or a doctor group, at a 1:1 ratio. The doctor and intelligent assistant group will accept the intelligent system evaluation. The intelligent system obtains gait parameters by an Red-Green-Blue-depth camera and computer vision algorithm. The doctor group will accept the clinicians’ routine treatment procedures. Meanwhile, all subjects will accept the panel’s gait assessment and recognition rating scale as the gold standard. The primary outcome is the sensitivity of the intelligent system and clinicians to screen for gait disorders. The secondary outcomes include the healthcare costs and the incremental cost effectiveness ratio of intelligent systems and clinicians to screen for gait disorders. ETHICS AND DISSEMINATION: Approval was granted by the Ethics Committee of Zhongshan Hospital affiliated with Fudan University on 26 November 2019. The approval number is B2019-027(2) R. All subjects will sign an informed consent form before enrolment. Serious adverse events will be reported to the main researchers and ethics committees. The subjects’ data will be kept strictly confidential. The results will be disseminated in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04457908 BMJ Publishing Group 2022-03-23 /pmc/articles/PMC8948402/ /pubmed/35332042 http://dx.doi.org/10.1136/bmjopen-2021-055880 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article 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, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Neurology
Fei, Beini
Zhao, Jin
Li, Xin
Tang, Yanmin
Qin, Guoyou
Zhang, Wei
Ding, Jing
Hu, Min
Wang, Xin
Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol
title Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol
title_full Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol
title_fullStr Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol
title_full_unstemmed Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol
title_short Randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (ACCURATE-1): study protocol
title_sort randomised parallel trial on the effectiveness and cost-effectiveness in screening gait disorder of silent cerebrovascular disease assisted by artificial intelligent system versus clinical doctors (accurate-1): study protocol
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948402/
https://www.ncbi.nlm.nih.gov/pubmed/35332042
http://dx.doi.org/10.1136/bmjopen-2021-055880
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