Tenghuang Jiangu tablet in knee osteoarthritis therapy: A prospective multicenter registry study in China
Bibliographic record
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE: Chinese patent medicine Tenghuang Jiangu tablet (THJGT) is frequently used to treat knee osteoarthritis (KOA). AIM: This prospective multicenter registry study investigated the effectiveness and safety of THJGT in treating KOA. MATERIALS AND METHODS: Patients with KOA aged 50-75 years were preferentially treated with THJGT, other nonsurgical conventional treatments (CTs), or both. The treatment duration was 8 weeks, with follow-ups at weeks 4 and 8. The visual analog scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were the efficacy assessments. Adverse events and drug reactions were evaluated to assess the safety of THJGT. Propensity score matching (PSM) was used for the subgroup analysis. RESULTS: From September 2019 to January 2021, a total of 2995 participants were included, with 1471 in THJGT group, 490 in CT group and 1034 in THJGT + CT group. After treatment, the VAS and WOMAC scores in the three groups improved significantly (P < 0.001). At week 8, the VAS scores in the THJGT group significantly improved, were lower than those in the CT group (P < 0.01), and were comparable to those in the THJGT + CT group (P = 0.623). The WOMAC scores significantly improved (P < 0.001), with no differences between groups (P > 0.05). The WOMAC pain and stiffness scores were better in the THJGT + CT than in the THJGT and CT groups. PSM revealed that the WOMAC pain and stiffness scores were significantly lower in the THJGT than in the nonsteroidal anti-inflammatory drugs (NSAID) group (P < 0.01 and 0.001). Adverse events were higher in the CT and THJGT + CT groups (P < 0.001). CONCLUSION: THJGT is effective and safe for treating KOA, particularly in improving stiffness symptoms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".