Double-blind trial of solid lipid <i>Boswellia serrata</i> particles (SLBSP) vs. standardized <i>Boswellia serrata</i> gum extract (BSE) for osteoarthritis of knee
Bibliographic record
Abstract
Objectives The present study was planned to investigate the efficacy of SLBSP vs. standardized BSE for symptomatic knee osteoarthritis (OA) treatment. Methods It was a prospective, randomized, double-blind, double-dummy, placebo-controlled, and single-centre clinical trial for symptomatic osteoarthritis of knee. Subjects were randomized to receive SLBSP capsule+BSE Placebo or BSE tablet+SLBSP placebo for two months. Patients were allowed to take rescue analgesics (Acelofenac 100 mg). Improvement in pain and function was assessed utilizing WOMAC, VAS. Level of CTX-II in urine and serum levels of inflammatory cytokines including IL-2, IL-4, IL-6, TNF-α, and IFN-γ was measured initially and at end of treatment. Results and conclusions Western Ontario and McMaster Universities osteoarthritis index (WOMAC) and Visual Analog Scale score improved markedly in SLBSP as well as in BSE arm (p < 0.05). Difference in VAS and WOMAC scores between the two arms was not statistically significant. Most significant effect was observed in the need for rescue analgesics. SLBSP caused marked lowering of pro-inflammatory cytokines levels whereas a several fold increase was noted in the BSE arm (p < 0.05). Both groups showed marked improvement in pain, SLBSP being superior to BSE with respect to reducing the need for rescue analgesics in addition to modulating inflammatory cytokines.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".