High-Rosmarinic Acid Spearmint Tea in the Management of Knee Osteoarthritis Symptoms
Bibliographic record
Abstract
UNLABELLED: Individuals with medically diagnosed knee osteoarthritis (OA) participated in a randomized, double-blind study to investigate the effects of a high-rosmarinic acid (rosA) spearmint tea. Sixty-two participants were randomized by sex and screening pain score to consume tea brewed from a high-rosA spearmint variety or a commercially available spearmint twice daily for 16 weeks. Pain, quality of life (QoL), and physical function at baseline and week 16 were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Short-Form 36-item Health Survey (SF-36), 6-minute walk test (6MWT), and stair climb test (SCT). Data from 46 participants (mean age=60.7; BMI=32.9 kg/m(2)) were analyzed. Pain score significantly decreased from week 0 to 16 for the high-rosA group but not for the control group and scores for stiffness and physical disability significantly decreased from week 0 to 16 for both groups. Increased QoL score on the bodily pain index in the SF-36 was observed at week 16 within the high-rosA group only, although no significant differences were observed between the groups. A nonsignificant improvement was observed in the 6MWT at week 16 in the high-rosA group only. There were no changes in the SCT for either group. Therefore, 16-week daily consumption of the high-rosA and commercial spearmint teas significantly improved stiffness and physical disability scores in adults with knee OA, but only the high-rosA tea significantly decreased pain. Consumption of high-rosA tea warrants further consideration as a potential complementary therapy to reduce pain in OA. CLINICAL TRIAL REGISTRATION NUMBER: NCT01380015.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".