Acupuncture of different treatment frequency in knee osteoarthritis: a protocol for a pilot randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: This study aims to determine whether 3 sessions per week of acupuncture treatment is superior to 1 session per week of acupuncture treatment for symptomatic outcomes in knee osteoarthritis. METHODS/DESIGN: This is a two parallel-group, assessor-blinded, randomized controlled trial. Sixty patients with knee osteoarthritis (Kellgren-Lawrence grade II or III) will be recruited and randomly allocated to receive 24 or 8 sessions (group M or group L) of acupuncture treatment in a 1:1 ratio. Patients in group M will receive 3 sessions per week of acupuncture for 8 weeks. Patients in group L will receive acupuncture once per week for 8 weeks. The primary outcome is the response rate-the percentage of patients achieving a decrease ≥ 2 points on a numerical rating pain scale and a decrease ≥ 6 points in the Western Ontario and McMaster Universities Osteoarthritis Index function score at 8 weeks compared with baseline. Secondary outcomes include pain, function, overall effect, quality of life, and treatment credibility and expectancy. DISCUSSION: Three sessions per week of acupuncture treatment may be superior to 1 session per week of acupuncture treatment for symptomatic outcomes in knee osteoarthritis. Results of the study will be of great importance for the guidelines of clinical therapy. TRIAL REGISTRATION: Clinicaltrials.gov, NCT03359603 . Registered on 1 December 2017.
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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 | 0.044 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.060 | 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, 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".