[Treatment of Knee Osteoarthritis by Tendons of Minimally Invasive Therapy Combined Drug Ther- apy: a Clinical Observation of Sixty Cases].
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy of tendons of minimally invasive therapy (TMIT) combined drug therapy by comparing it with treatment by drug therapy alone on patients with knee osteoarthritis (KOA). METHODS: Totally 60 KOA patients were assigned to the treatment group and the control group according to random digit table, 30 in each group. Patients in the control group took Hydrochloric Acid Glucosamine Capsule and Celecoxib Capsule. Patients in the treatment group additionally received TMIT. The treatment course for all was 4 weeks. Scores for visual analogue scale (VAS) and the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index were observed and recorded at week 1 and 4 after treatment by acupotomology mirror. RESULTS: Compared with before treatment, improvement was shown in VAS score, pain and stiffness degrees, activities and functions, and WOMAC scores at week 1 and 4 after treatment in all patients with statistical difference (P < 0.05). Besides, better effect was shown in the treatment group (P < 0.05). CONCLUSIONS: TMIT combined drug therapy could relieve KOA patients' pain, stiffness and joint activities, elevate the overall efficacy. TMIT was easily operated with less injury.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".