Comparision of therapertic effect of different acupuncture methods for knee osteoarthritis
Bibliographic record
Abstract
Objective To compare the clinical efficacy of acupuncture, electroacupuncture(EA) and moxibustion in the treatment of knee osteoarthritis(KOA). Methods A total of eight-four patients with KOA were randomly and equally divided into acupuncture group, EA group and moxibustion group. Neixiyan(EX-LE40), Dubi(ST35), Heding(EX-LE2), Liangqiu(ST34), Xuehai(SP10), Zusanli(ST36) and Ashi-point on the affected side of the body were punctured with filiform needles or EA(2 Hz/100 Hz) for 30 min. In the moxibustion group, moxibustion was applied to the surrounding area of the affected joint for 60 min. The treatment was conducted once every other day for 4 weeks. The pain degree was assessed by using numerical rating scale(NRS) and the Western Ontario McMaster Universities Osteoarthritis Index(WOMAC) scale(0-240 points) was used to evaluate the severity of KOA. The "Minimal Clinically Important Improvement(MCII)" was used to assess the therapeutic effect after the treatment. Results After the treatment, the scores of NRS, and the pain, stiffness, motor function and total scores of WOMAC were significantly decreased in the three groups compared with their own pre-treatment(P<0.05), and were obviously lower in the EA and moxibustion groups than in the acupuncture group(P<0.05), and those of the moxibustion group was notably lower than those of the acupuncture group(P<0.05). Of the 28 cases in the acupuncture, EA and moxibustion groups, 11, 17 and 22 were effective, with the effective rate being 39.29%, 60.71% and 78.57%, respectively. The comprehensive therapeutic effect of the moxibustion group was significantly superior to that of the acupuncture and EA groups(P<0.05). Conclusion All the three different kinds of acupuncture and moxibustion methods have positively regulatory effect on KOA, and moxibustion is the best for reducing the joint pain and stiffness, and improving the motor function.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".