Curcuma longa and Boswellia serrata for Improving Functional Status in Osteoarthritis Patients: From Bench to Bedside Evidences
Bibliographic record
Abstract
Background: The management of osteoarthritis (OA) represents a real challenge. Curcumin is a highly pleiotropic molecule with an excellent safety profile.Some previous studies showed the extract of Curcuma longa and Boswellia Serrata(CB extract) is a promising potential as therapeutic interventions against OA. Aims and Objective: This study aimed to measure the effectiveness and safety of CB extract for improving functional status in patients with OA. Materials and Methods: A randomized controlled trial (RCT) in OA patients. The treatment used in this trial were CB extract (350 mg of Curcuma longa and 150 mg Boswellia Serrata) and NSAID (400 mg ibuprofen or 50 mg diclofenac sodium). Subjects were randomized to 3 different group (Group 1: CB extract and NSAID; group 2: CB extract; group 3: NSAID). Each subject would be followed up 3 times: baseline (visit I), 2 weeks after baseline (visit II), and 4 weeks after baseline (visit III). The measurement of functional status with WOMAC (Western Ontario and McMaster Universities Osteoarthitis Index). Results: There were 105 osteoarthritis patients. Seven subjects were lost to follow up and three subjects were excluded from the study due to medication side effect. Ninety-five subjects (group 1: 36; group 2: 29, group 3: 30) remained for complete analysis. Delta (Δ) WOMAC score defined as the result of subtraction between WOMAC score at visit I and WOMAC score at visit III. Group 1 showed the greatest reduction of WOMAC score after 4 weeks of treatment (ΔWOMAC = 12.08 ± 18.6). Group 3 has the least WOMAC score reduction (ΔWOMAC = 6.9 ± 16). There was no statistically different of ΔWOMAC score between groups (p = 0.367). There were no statistically different of the prevalence of AE between groups at the visit II (p: 0.119) and at the visit III (p: 0.767). Conclusion: CB extract is effective and safe for improving functional status in OA patients.
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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 | 0.000 | 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".