Efficacy of Juglandis semen complex extract for knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (KOA) is a common disease in elderly individuals. Many medications for KOA have the potential to cause side effects. We used Juglandis semen complex extract (JCE) consisting of 4 herbs derived from Cheong-A-Won, which has been commonly used for KOA treatment. In this study, we will evaluate whether JCE improves symptoms in patients with KOA and will identify the changes in the inflammation factor. METHODS: This study will be a single-center, randomized, double-blind, and placebo-controlled trial. Three groups, JCE 1000 mg, 2000 mg, and placebo, will be randomly allocated. Total duration of the clinical trial will be 12 to 14 weeks. Study participants will be followed up every 6 weeks and the effect and safety will be assessed at the 2, 3, and 4 visit. All participants were asked to maintain a dosage schedule for this protocol. The primary outcomes will be measured using Korean Western Ontario and McMaster Universities Questionnaire and the secondary outcomes will include pain Visual analog scale score, EuroQol Five Dimensions questionnaire, Patient Global Impression of Change, and the changes in the laboratory test parameters of inflammation. Repeated-measure analysis will be used to measure primary efficacy based on full analysis set. DISCUSSION: This study has limited inclusion and exclusion criteria and a well-controlled intervention, and it will be the first randomized controlled trial to assess the efficacy and safety of JCE in patients with KOA. This study provides insights into the mechanisms that explain the therapeutic effects of JCE in KOA and will lay the groundwork for further studies.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".