Acupuncture Vs Streitberger Needle in Knee Osteoarthritis – An Rct
Bibliographic record
Abstract
Aims To determine the effectiveness of acupuncture as a therapy complementary to the pharmacological treatment of osteoarthritis of the knee. Methods Randomised, single blind, placebo controlled trial. Patients with osteoarthritis of the knee were randomly assigned to either 12 sessions of true acupuncture or 12 sessions of placebo acupuncture (Streitberger needle), these sessions taking place once a week. A baseline measurement was carried out, followed by further observations at 4, 8, 12 and 16 weeks. The clinical variables were the WOMAC (Western Ontario and McMaster Universities Osteoarthritis) index, knee pain measured by a visual analogue scale (pain VAS), the weekly consumption of diclofenac and the Profile of the Quality of Life of the Chronically Ill (PQLC). The two groups were compared for each of the clinical variables per protocol and by intention to treat. A multiple linear regression model for the dependent variables was constructed. Results Ninety seven outpatients were selected, with 88 remaining for the per protocol analysis; the analysis of homogeneity concluded that the lost subjects were not significantly different from those that completed the study. The multivariate per protocol model for the relative pain VAS variable showed a difference in improvement of 43.7% (95% CI 29.4% to 58.0%) for acupuncture, compared with the control group. In an intention to treat analysis, the relative improvement was 32.4% (20.3% to 44.4%). In a per protocol analysis, the total WOMAC showed a relative decrease of 52.0% (34.3% to 69.6%) in favour of the acupuncture group, or 37.6% (22.4% to 52.8%) in an intention to treat analysis. Conclusions The group treated with acupuncture showed significantly better effects, both clinically and statistically, in the reduction of pain intensity as measured by pain VAS, on the WOMAC index and in decreased consumption of diclofenac.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".