Internet of Things-based pulsed electromagnetic field combined with exercise therapy in patients with knee osteoarthritis: randomized, controlled, noninferiority trial protocol
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (KOA) is a chronic musculoskeletal condition that affects the entire joint structure. Although pulsed magnetic therapy is widely recommended to alleviate KOA symptoms and telerehabilitation is increasingly utilized for its management, there is a lack of research comparing Internet of Things-based pulsed electromagnetic field combined with exercise (IOT-BPEMFE) methods to traditional outpatient therapy (OT). This study aims to evaluate and compare the effects of IOT-BPEMFE on pain reduction, functional recovery, quality of life, and participant adherence in a community setting, relative to outpatient therapy. METHODS: This study adopts a single-blind randomized controlled design. One-hundred and twelve patients with KOA (≥ 40 years) will be recruited and randomly assigned to either the IOT-BPEMFE or the OT groups. The intervention will last for 4 weeks. Outcome measures will be assessed at baseline (T0) and at 2 weeks (T1), 4 weeks (T2), and 12 weeks (T3) after the randomization. The primary outcome will be measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Secondary outcomes will include the Numerical Rating Scale (NRS), 36-Item Short Form health Survey (SF-36), Instrumental Activity of Daily Living (IADL), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Timed "Up and Go" test (TUG), manual muscle test (MMT), range of motion (ROM), Knee Society Score (KSS), Knee Injury and Osteoarthritis Outcome Score (KOOS), patient satisfaction with the treatment, and any adverse events. DISCUSSION: The findings of this study will help establish the feasibility and effectiveness of IOT-BPEMFE for patients with KOA in the community. By highlighting this study's methodological strengths and limitations, the results may guide the implementation and optimization of IOT-BPEMFE in community-based KOA telerehabilitation. STRENGTH AND LIMITATIONS: This study will be the first to demonstrate that combining electromagnetic field therapy with exercise via the Internet of Things (IoT) can effectively reduce pain, improve physical function, and enhance quality of life in community-dwelling patients with knee osteoarthritis. We will use self-report tools for measurement, which may lead to social desirability bias. Additionally, due to time and budget constraints, the study will not include follow-up beyond the 12-week post-randomization. TRIAL REGISTRATION: The study protocol has been registered with the Chinese Clinical Trial Registry (ChiCTR 2300071181; Registration time: May 6, 2023) and approved by the Ethics Committee on Biomedical Research of the Fourth Medical Center of PLA General Hospital.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.006 |
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".