Clinical Benefits of <i>Boswellia Serrata</i> (BOSMAX®) in Early Knee Osteoarthritis: A Randomized, Placebo-Controlled, Double-Blind Study
Bibliographic record
Abstract
Osteoarthritis (OA) is a major cause of pain and reduced mobility in older adults, with few effective treatments currently available. This randomized, double-blind, placebo-controlled trial evaluated the efficacy and safety of Boswellia serrata extract (BOSMAX®), a botanical anti-inflammatory agent, in participants with non/mild OA. A total of 150 adults aged 40–75 were randomized to receive either BOSMAX® or a placebo daily for 90 days. Primary outcome measures included WOMAC scores, visual analog scale (VAS) for pain, and Lequesne Functional Index; secondary endpoints were SF-36 scores, tumor necrosis factor-alpha (TNF-α), and high-sensitivity C-reactive protein (hs-CRP). Significant improvements were observed in the BOSMAX® group compared with the placebo. The mean total Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores decreased significantly at days 30 (−6.28), 60 (−15.24), and 90 (−24.55; P < .05). WOMAC sub-scores (pain, stiffness, and function) and VAS pain scores also showed significant reductions at days 60 and 90. Lequesne Index scores improved progressively (−1.37, −2.93, and −4.53 at days 30, 60, and 90, respectively; P < .05). TNF-α and hs-CRP levels decreased significantly (−104.75 ng/L and −5.67 ng/mL, respectively; P < .05) at day 90. However, no significant changes were observed in SF-36 scores. Both treatments exhibited good tolerability, with only one mild and unrelated adverse event reported. Vital signs, physical exams, and laboratory parameters remained clinically unchanged. BOSMAX® significantly improved knee-joint symptoms and inflammatory markers over 90 days in individuals with non/mild OA, supporting its potential as a safe therapeutic option.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".