Evidence of Chinese herbal medicine Duhuo Jisheng decoction for knee osteoarthritis: a systematic review of randomised clinical trials
Bibliographic record
Abstract
OBJECTIVES: Duhuo Jisheng decoction (DJD) is considered beneficial for controlling knee osteoarthritis (KOA)-related symptoms in some Asian countries. This review compiles the evidence from randomised clinical trials and quantifies the effects of DJD on KOA. DESIGNS: 7 online databases were investigated up to 12 October 2015. Randomised clinical trials investigating treatment of KOA for which DJD was used either as a monotherapy or in combination with conventional therapy compared to no intervention, placebo or conventional therapy, were included. The outcomes included the evaluation of functional activities, pain and adverse effect. The risk of bias was evaluated using the Cochrane Collaboration tool. The estimated mean difference (MD) and SMD was within a 95% CI with respect to interstudy heterogeneity. RESULTS: 12 studies with 982 participants were identified. The quality presented a high risk of bias. Meta-analysis found that DJD combined with glucosamine (MD 4.20 (1.72 to 6.69); p<0.001) or DJD plus meloxicam and glucosamine (MD 3.48 (1.59 to 5.37); p<0.001) had a more significant effect in improving Western Ontario and McMaster Universities Arthritis Index (total WOMAC scores). Also, meta-analysis presented more remarkable pain improvement when DJD plus sodium hyaluronate injection (MD 0.89 (0.26 to 1.53); p=0.006) was used. These studies demonstrated that active treatment of DJD in combination should be practiced for at least 4 weeks. Information on the safety of DJD or comprehensive therapies was insufficient in few studies. CONCLUSIONS: DJD combined with Western medicine or sodium hyaluronate injection appears to have benefits for KOA. However, the effectiveness and safety of DJD is uncertain because of the limited number of trials and low methodological quality. Therefore, practitioners should be cautious when applying DJD in daily practice. Future clinical trials should be well designed; more research is needed.
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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 | 0.018 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".