Evidence map›Paper›PMID 35332042›Full record

ArticleBMJ open2022

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.

Beini Fei, Jin Zhao, Xin Li, Yanmin Tang, Guoyou Qin, Wei Zhang, Jing Ding, Min Hu, Xin Wang

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04457908 (the Effectiveness and Cost Effectiveness in Screening Gait Disorder of Silent Cerebrovascular Disease Assisted by Artificial Intelligent System and Clinical Doctors - A Randomized Parallel-controlled Study), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 44% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04457908 naunknown statusnot on this map

the Effectiveness and Cost Effectiveness in Screening Gait Disorder of Silent Cerebrovascular Disease Assisted by Artificial Intelligent System and Clinical Doctors - A Randomized Parallel-controlled Study

TypeinterventionalSponsorShanghai Zhongshan HospitalRan2020 to 2020Enrolled1,000ConditionsSilent StrokeArmsintelligent assessment
3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Beini FeiDepartment of Neurology, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China.
Jin ZhaoDepartment of Health Economics, Fudan University, Shanghai, China.
Xin LiDepartment of Neurology, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China.
Yanmin TangDepartment of Neurology, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China.
Guoyou QinDepartment of Biostatistics, Fudan University, Shanghai, China.
Wei ZhangDepartment of Biostatistics, Fudan University, Shanghai, China.
Jing DingDepartment of Neurology, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China.ORCID 0000-0001-5135-4210
Min HuDepartment of Health Economics, Fudan University, Shanghai, China.
Xin WangDepartment of Neurology, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China wang.xin@zs-hospital.sh.cn.
Sun Yat-sen University · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionSilent 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.

Indexed as

Cerebrovascular DisordersGaitAgedChinaCost-Benefit AnalysisHumansMulticenter Studies as TopicProspective StudiesRandomized Controlled Trials as Topicadult neurologyhealth economicsstroke

Identifiers

PMID35332042
PMCPMC8948402
OpenAlexW4220857793

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.