Effects of a periodized circuit training protocol delivered by telerehabilitation compared to face-to-face method for knee osteoarthritis: a protocol for a non-inferiority randomized controlled trial
Bibliographic record
Abstract
Background: Regular exercise is an effective method for reducing pain and disability in patients with knee osteoarthritis (OA), as well as improving body composition. Thus, a combination of both resistance and aerobic training (circuit training) has shown to be promising for this population. However, access to physical therapy is limited by physical distance, social isolation, and/or treatment costs. Remote rehabilitation seems to be an effective way to minimize these barriers, but the benefits are dependent on the participants’ adherence to the interventions provided at a distance. The objectives of this protocol are to compare the effects of a periodized circuit training applied via telerehabilitation with the same protocol applied in the face-to-face model for individuals with knee OA. Methods: This study presents a single-blinded protocol for a non-inferiority randomized controlled trial. One hundred participants diagnosed with knee OA (grades II and III Kellgren and Lawrence system), aged 40 years or more, and BMI < 30 kg/m2 will be randomly divided into two groups: telerehabilitation (TR) and face-to-face (FtF) circuit training. The FtF group will perform a 14-week periodized circuit training protocol supervised by a physical therapist, 3 times a week. The TR group will perform the same exercise protocol at home, at least 3 times a week. In addition, the TR group will be able to follow the execution and orientations of the exercises by DVD, a website, and online file sharing tools, and they will receive periodic phone calls in order to motivate, clarify, and inform some aspects of knee OA. The primary outcomes are changes in self-reported pain intensity (visual analog scale (VAS)) and physical function (Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)), with a primary end-point of 14 weeks and a secondary end-point of 26 weeks. Secondary outcomes include changes in other clinical outcomes, in morphological characteristics, adherence, acceptability, and treatment perspective. Discussion: A circuit training through telerehabilitation may contribute to developing early intervention in the causative and potentiating factors of the knee OA, verifying the effects of a low-cost, non-pharmacological and non-invasive treatment.
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How this classification was reachedexpand
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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".