Effects of Moxibustion Combined with Ultrashort Wave on Pain and Oxidative Stress in Elderly Patients with Knee Osteoarthritis
Post-publication record
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Bibliographic record
Abstract
Objective. To explore the effect of moxibustion instrument combined with ultrashort wave on pain and oxidative stress in elderly patients with knee osteoarthritis (KOA). Method. 84 elderly patients with knee osteoarthritis treated in our hospital from May 2020 to June 2021 were randomly divided into observation group ( n = 42 ) and control group ( n = 42 ). The observation group was treated with moxibustion instrument combined with ultrashort wave, while the control group was treated with moxibustion instrument. The clinical efficacy of the two groups was compared, and the pain of the two groups was evaluated by visual analogue scale (VAS). Lysholm knee joint score scale and osteoarthritis index (WOMAC) scale of Western Ontario and McMaster University were used to evaluate the knee joint function of the two groups, and the levels of interleukin-1β (IL-1β), tumor necrosis factor α (TNF-α), serum superoxide dismutase (SOD), serum malondialdehyde (MDA), serum miR-155, and NLRP3 were detected in the two groups, and the comprehensive quality of life assessment questionnaire-74 was used, and the adverse reactions were compared between the two groups. Results. The total effective rate of observation group (90.48%) was higher than that of control group (69.05%) ( P < 0.05 ). After treatment, VAS, Lysholm knee joint, WOMAC, quality of life scores, IL-1β, TNF-α, SOD, MDA, miR-155, and NLRP3 in the observation group were better than those in the control group, and the differences were statistically significant ( P < 0.05 ). There were no obvious adverse reactions in both groups. Conclusion. Moxibustion instrument combined with ultrashort wave can effectively improve knee joint pain, knee joint function, inflammatory reaction, oxidative stress reaction, and quality of life in elderly KOA patients, and the therapeutic effect is good.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".