The impact of blood flow restriction training combined with low-load resistance training on the risk of falls in patients with knee osteoarthritis in China: a single-centre, two-arm, single-blind, parallel randomised controlled trial protocol
Bibliographic record
Abstract
INTRODUCTION: Patients with knee osteoarthritis are at a higher risk of falls compared to healthy individuals, thereby increasing the likelihood of accidental injury. Resistance training is an important strategy for managing knee osteoarthritis. Although some studies suggest that blood flow restriction training combined with low-load resistance training (LL-BFRT) is a beneficial treatment approach, its effect on fall risk and balance function in patients with knee osteoarthritis remains unclear. We aim to conduct a randomised controlled trial to assess the effectiveness of combined training in reducing fall risk and improving function in patients with knee osteoarthritis. METHODS AND ANALYSIS: We will conduct a single-blind pilot randomised controlled trial involving patients with knee osteoarthritis. 98 patients will be randomly assigned to either the LL-BFRT group or the low-load resistance training (LL-RT) group, with a 1:1 allocation ratio. Both groups will undergo a 4-week intervention. Follow-up assessments will be conducted at baseline, 4 weeks, 16 weeks, 28 weeks and 52 weeks. The primary outcome will be the measurement of the fall risk stability index and overall stability index using the Biodex Balance System. Secondary outcomes include the Numerical Rating Scale, the Western Ontario and McMaster Universities Osteoarthritis Index, the 30 s Chair Stand Test, proprioception testing, the Timed Up and Go Test, the Short Form-36 scores, compliance and adverse events. Intention-to-treat principles will be applied in data analysis. ETHICS AND DISSEMINATION: This study has been approved by the Ethics Review Committee of the First Hospital of Quanzhou Affiliated Fujian Medical University (2024-K161). The results of the study will be disseminated through peer-reviewed publications. TRIAL REGISTRATION NUMBER: ChiCTR2400087829.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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".