Assessing the effectiveness and NSAIDs sparing effect of celery seeds and Boswellia serrata in osteoarthritis management
Bibliographic record
Abstract
: This study examines the anti-inflammatory and analgesic properties of Celery seed and extracts as potential alternatives for OA treatment, focusing on their effectiveness in reducing pain and improving joint functionality. Osteoarthritis (OA), a prevalent joint disorder, particularly affects the knees and hips. Current management primarily involves NSAIDs, which can lead to severe side effects, especially in older adults with comorbidities. A multicentre observational study enrolled 394 participants clinically diagnosed with knee osteoarthritis. They continued their usual treatment while taking Celery seeds and extract tablet twice daily for three months. Primary outcomes included Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores and changes in painkiller and NSAID usage. Secondary outcomes included visual analogue scale (VAS) pain scores. The study demonstrated significant improvements in primary outcome measures: WOMAC score improved by 17.07% (p<0.001), WOMAC pain score by 75.00% (p<0.001), WOMAC stiffness score by 72.05% (p<0.001) and WOMAC physical function score by 78.93% (p<0.001). Secondary outcomes showed VAS score reductions at rest by 67.17% (p<0.001) and during movement by 64.28% (p<0.001). There was a notable decrease in NSAID usage from baseline 70.09% to 31.89% (p<0.001). Celery seeds and extract demonstrate promising efficacy as a safer and effective adjunctive therapy for knee osteoarthritis, offering pain relief, enhanced joint functionality and potential reduction in NSAID usage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.001 |
| 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".