Intermittent blood flow restriction with low-load resistance training for older adults with knee osteoarthritis: a randomized, controlled, non-inferiority trial protocol
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (KOA) is a chronic musculoskeletal disorder characterized by pain and functional impairment. Blood flow restriction (BFR) with low-load resistance training (LLRT) demonstrates a similar improvement in clinical outcomes to high-load resistance training (HLRT) in treating KOA. It has not been established whether intermittent blood flow restriction (iBFR) with LLRT can lead to clinical outcomes that are comparable to those produced by continuous blood flow restriction (cBFR) with LLRT and HLRT. The aim of the proposed study is to evaluate the efficacy of iBFR with LLRT on pain, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), muscle strength, muscle mass, physical function, perceptions of discomfort and effort, and adherence in KOA patients. METHODS: This is a three-arm, non-inferiority, randomized controlled trial utilizing blinded assessors. Two hundred thirteen participants will be randomly allocated to one of the following three groups: iBFR group-receiving 4 months of LLRT with iBFR, twice weekly (n = 71); cBFR group-receiving 4 months of LLRT with cBFR, twice weekly (n = 71); or HLRT group-receiving 4 months of HLRT without BFR, twice weekly (n = 71). The primary outcome is pain. The secondary outcomes include the WOMAC, muscle strength, muscle mass, physical function, perceptions of discomfort and effort, and adherence. Pain and WOMAC will be measured at the baseline and 4 and 12 months after randomizations. Muscle strength, muscle mass, and physical function will be measured at the baseline and 4 months after randomizations. The perceptions of discomfort and effort will be measured during the first and final sessions. DISCUSSION: BFR with LLRT has a similar improvement in clinical outcomes as HLRT. However, cBFR may cause elevated ratings of perceived exertion and local discomfort, compromising patient tolerability and treatment adherence. If iBFR with LLRT could produce improvement in clinical outcomes analogous to those of HLRT and iBFR with LLRT, it could be considered an alternative approach for treating patients with KOA. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2300072820. Registered on June 26, 2023.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 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".