Original Article Blood-nourishing and Hard-softening Capsule Costs Less in the Management of Osteoarthritic Knee Pain: A Randomized Controlled
Bibliographic record
Abstract
The blood-nourishing and hard-softening (BNHS) capsule is a traditional Chinese formula used in the symptomatic treatment of inflammation and pain. We conducted this randomized controlled trial to compare the efficacy of BNHS with other commonly prescribed drugs. We recruited 120 patients from two teaching hospitals; 30 patients in each hospital were randomly assigned to receive BNHS. In one hospital, the 30 controls were given another traditional Chinese drug; whereas a Western medicine (chondroprotection drug/Viartril-s) was used as the control in the other hospital. Intervention was carried out over a period of 4 weeks. Primary outcome measures included self-reported pain level, and changes in stiffness and functional ability as measured by the Western Ontario McMaster Universities Osteoarthritis (WOMAC) index. Mixed models were used for statistical analysis. Substantial improvements in disease-specific symptoms were observed, after 4 weeks of treatment, in patients taking BNHS capsules. As assessed by the WOMAC index, pain level of the BNHS group decreased by 57 % [95 % confidence interval (CI) 50, 63], stiffness by 63 % (95 % CI 55, 71) and functional ability increased by 56% (95 % CI 50, 63). No significant differences were found in any of the outcome measures between the BNHS group and either of the comparison groups. No severe adverse effects were reported. However, this study lacked a placebo group; therefore, we conclude that BNHS appears to be as effective as commonly prescribed medicines for the relief of pain and dysfunction in knee osteoarthritis patients, but costs a lot less than other Western and herbal drugs in the study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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) | 0.015 | 0.001 |
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".