Acupuncture as an adjunctive therapy to pharmacological treatment in patients with chronic pain due to osteoarthritis of the knee: A 3-armed, randomized, placebo-controlled trial
Bibliographic record
Abstract
The efficacy of acupuncture as an adjunctive therapy to pharmacological treatment of chronic pain due to knee osteoarthritis was studied with a 3-armed, single-blind, randomized, sham-controlled trial; it compared acupuncture combined with pharmacological treatment, sham acupuncture including pharmacological treatment, and pharmacological treatment alone. A total of 120 patients with knee osteoarthritis were randomly allocated to 3 groups: group I was treated with acupuncture and etoricoxib, group II with sham acupuncture and etoricoxib, and group III with etoricoxib. The primary efficacy variable was the Western Ontario and McMaster Universities (WOMAC) index and its subscales at the end of treatment at week 8. Secondary efficacy variables included the WOMAC index at the end of weeks 4 and 12, a visual analogue scale (VAS) at the end of weeks 4, 8, and 12, and the Short Form 36 version 2 (SF-36v2) health survey at the end of week 8. An algometer was used to determine changes in a predetermined unique fixed trigger point for every patient at the end of weeks 4, 8, and 12. Group I exhibited statistically significant improvements in primary and secondary outcome measures, except for Short Form mental component, compared with the other treatment groups. We conclude that acupuncture with etoricoxib is more effective than sham acupuncture with etoricoxib, or etoricoxib alone for the treatment of knee osteoarthritis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".