Evidence map›Paper›PMID 39380108›Full record

ArticleJournal of orthopaedic surgery and research2024

ChatGPT-4 and wearable device assisted Intelligent Exercise Therapy for co-existing Sarcopenia and Osteoarthritis (GAISO): a feasibility study and design for a randomized controlled PROBE non-inferiority trial.

Mingke You, Xi Chen, Di Liu, Ye Lin, Gang Chen, Jian Li

Abstract readClinical Trial Protocol
In one paragraph

Article in Journal of orthopaedic surgery and research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Observational
  5. Review
  6. Article
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

6 authors.

Mingke You *Sports Medicine Center, West China Hospital, Sichuan University, 37 Guoxue Lane, Wuhou District, Chengdu, Sichuan Province, China.
Xi Chen *Sports Medicine Center, West China Hospital, Sichuan University, 37 Guoxue Lane, Wuhou District, Chengdu, Sichuan Province, China.
Di LiuUniversity of Chicago, Chicago, USA.
Ye LinUniversity of Chicago, Chicago, USA.
Gang ChenSports Medicine Center, West China Hospital, Sichuan University, 37 Guoxue Lane, Wuhou District, Chengdu, Sichuan Province, China. 7422979@qq.com.
Jian LiSports Medicine Center, West China Hospital, Sichuan University, 37 Guoxue Lane, Wuhou District, Chengdu, Sichuan Province, China. lijian_sportsmed@163.com.

Funding

Sichuan Province Science and Technology Support Program 2022YFS0372West China Hospital, Sichuan University ZYGD21005
6 · The paper itself

Abstract

backgroundSarcopenia and osteoarthritis are prevalent age-related diseases that mutually exacerbate each other, creating a vicious cycle that worsens both conditions. Exercise is key to breaking this detrimental cycle. Facing increasing demand for rehabilitation services within this patient demographic, ChatGPT-4 and wearable device may increase the availability, efficiency and personalization of such health care.

aimTo evaluate the clinical efficacy and cost-effectiveness of a rehabilitation system implemented on mobile platforms, utilizing the integration of ChatGPT-4 and wearable devices.

methodsThe study design is a prospective randomized open blinded end-point (PROBE) non-inferiority trial. 278 patients diagnosed with osteoarthritis and sarcopenia will be recruited and randomly assigned to the intervention group and the control group. In the intervention group patients receive mobile phone-based rehabilitation service where ChatGPT-4 generates personalized exercise therapy, and wearable device guides and monitor the patient to implement the exercise therapy. Traditional clinic based face-to-face exercise therapy will be prescribed and implemented in the control group. All patients will receive three-months exercise therapies following the frequency, intensity, type, time, volume and progression (FITT-VP) principle. The patients will be assessed at baseline, one month, three months, and six months after initiation. Outcome measures will include ROM, gait patterns, Visual Analogue Scale (VAS) for pain assessment, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Knee Injury and Osteoarthritis Outcome Score (KOOS) for functional assessment, Short-Form Health Survey 12 (SF-12) for quality of life, Minimal Clinically Important Difference (MCID), Patient Acceptable Symptom State (PASS), and Substantial Clinical Benefit (SCB) for clinically significant measures. DISCUSSION: A rehabilitation system combining the capabilities of ChatGPT-4 and wearable devices potentially enhance the availability and efficiency of professional rehabilitation services, thus enhancing the therapeutic outcomes for a substantial population concurrently afflicted with sarcopenia and osteoarthritis.

Indexed as

Exercise TherapyOsteoarthritisSarcopeniaWearable Electronic DevicesAgedCell PhoneEquivalence Trials as TopicFeasibility StudiesFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedProspective StudiesQuality of LifeTreatment OutcomeArtificial intelligenceChatGPT-4OsteoarthritisRehabilitationSarcopeniaWearable device

Identifiers

PMID39380108
PMCPMC11463084

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.