On 30 Cases of Knee Osteoarthritis Treated with Duhuo Jisheng Decoction Combined with Moxibustion
Bibliographic record
Abstract
Objective:To observe the curative effects of Duhuo Jisheng Decoction combined with moxibustion in the treatment of knee osteoarthritis.Methods:60 cases of knee osteoarthritis were randomly and equally divided into the treatment group and the control group.The treatment group were given orally Duhuo Jisheng Decoction combined with moxibustion treatment,and the control group were given orally Celecoxib Capsules,two groups being treated for 20 days.The Visual Analogue Scale(VAS) and the Western Ontario and McMaster Universities Arthritis Index(WOMAC) were used as the observation index.Results:5 cases of the treatment group were clinically cured,17 cases being markedly effective,5 cases effective,and 3 cases invalid,and the effective rate being 90%; 6 cases of the control group were cured clinically,13 cases being markedly effective,9 cases effective,2 cases invalid,and the effective rate being 93.30%.The difference between the two groups was not?statistically?significant(P 0.05).After treatment,the VAS score and WOMAC score of the two groups were significantly?decreased?compared?with?those?before?treatment,the?difference?being?statistically?significant(P 0.01), and the decrease of the WOMAC score of the treatment group was better than that of the control group(P 0.05). Conclusion:Duhuo Jisheng Decoction combined with moxibustion has a better curative effect on the treatment of knee osteoarthritis than that of Celecoxib Capsules,being safer.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".