OA09.02. Observation on effects of 10.6µm laser moxibustion in patients with knee osteoarthritis: a double-blind, randomized, controlled study
Bibliographic record
Abstract
172 patients with knee osteoarthritis were randomly divided into real and sham laser moxibustion groups, with 10.6μm laser moxibustion and sham laser moxibustion treatment on ST-35 respectively. Patients in both groups received 20 minutes of treatment, thrice a week and 4 weeks in total. Effects of treatment were assessed mainly by changes in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC VA 3.1) before, in the middle (after 2 weeks), at the end (after 4 weeks) and 4 weeks after the end of the treatment. Completion time of 50 yards walking was evaluated as a secondary measurement. There was no statistical difference in WOMAC pain, stiffness and function scores between the two groups before treatment. Patients in the real treatment group experienced greater improvement in WOMAC pain, stiffness and function scores in the middle, at the end and 4 weeks after the end of the treatment (p < 0.05). No significant difference was shown in completion time of 50 yards walking before, in the middle and at the end of the treatment. Patients in the real treatment group were superior to those in the sham group in completion time of 50 yards’ walking 4 weeks after the treatment. Compared with sham treatment, 10.6μm laser moxibustion can significantly reduce pain and improve knee joint stiffness and function in patients with knee osteoarthritis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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) | 0.008 | 0.002 |
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".