Efficacy of a computer vision-based system for exercise management in patients with knee osteoarthritis: a study protocol for a randomised controlled pilot trial
Bibliographic record
Abstract
INTRODUCTION: This study aims to evaluate the efficacy of a computer vision system in guiding exercise management for patients with knee osteoarthritis (OA) by comparing functional improvement between a tele-rehabilitation versus an outpatient intervention program. METHODS AND ANALYSIS: This is a prospective, single-blind, randomised controlled trial of 60 patients with knee OA who will be randomly assigned to exercise therapy (n=30) or control (n=30) . Both groups will receive treatment two times per week for 12 weeks. The primary outcome of the study will be assessed using the University of Western Ontario and McMaster University Osteoarthritis Index (WOMAC). The Knee Injury and Osteoarthritis Outcome Score will be assessed, as well as the visual analogue scale, quality of life score and physical fitness score. All observations will be collected at baseline and at weeks 4, 8 and 12 during the intervention period, as well as at weeks 4, 8, 12 and 24 during the follow-up visits after the end of the intervention. ETHICS AND DISSEMINATION: This evaluator-blinded, prospective, randomised controlled study was approved by the Biomedical Ethics Review Committee of West China Hospital of Sichuan University. TRIAL REGISTRATION NUMBER: ChiCTR2300070319.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.031 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.051 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".