The Effect of Combination of Turmeric and Black Pepper Extracts in Osteoarthritis of the Knee
Bibliographic record
Abstract
The management of osteoarthritis (OA) remains a challenge. Curcumin is basically a spice that is known for its anti-inflammatory properties. In vitro studies suggest that curcumin could be beneficial for cartilage in OA. Piperine, derived from black pepper, is added to Curcumin to increase its bioavailability. The aim of this randomized, double blind trial was to evaluate the effects of combination curcumin plus piperine in knee OA patients.A total of 43patients were randomly assigned to receive the fixed dose combination (curcumin 500 mg plus piperine 5 mg) or placebo twice daily for three months and was evaluated using a Western Ontario MacMaster (WOMAC) score. Results revealed the serum levels of High Sensitivity C - reactive protein (HS-CRP)and Human Cross Linked C-Telopeptide of Type II Collagen (CTX-II) were changedafter 3 months of treatment. In conclusions: The treatment with curcumin was globally well tolerated. It significantly decreased the WOMAC score and NSAIDS uses. Serum level of CTXII significantly reduced (p<0.001) and tended to decrease serum HS-CRP. In addition, curcumin significantly reduced body mass index,this may point toward that curcuminoids has role in weight reduction,and hence, lower risk of OA
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".