Curcumagalactomannoside/Glucosamine Combination Improved Joint Health Among Osteoarthritic Subjects as Compared to Chondroitin Sulfate/Glucosamine: Double-Blinded, Randomized Controlled Study
Bibliographic record
Abstract
Objective: A combination of curcumagalactomannosides (CGM) (400 mg) with glucosamine hydrochloride (GLN) (500 mg) was evaluated against a standard dietary supplement combination chondroitin sulfate (CHN) (415 mg)/GLN (500 mg) for their effectiveness in alleviating the pain and symptoms among osteoarthritic subjects. Design: Randomized, double-blinded and active-controlled study. Settings/Location: The study was conducted in a hospital-based research center in Vadodara, Gujarat, India. Subjects: Eighty subjects (38 males and 42 females), with confirmed osteoarthritis (OA) (Class I–III), were randomized into two parallel groups designated as Group I (CGM-GLN) and Group II (CHN-GLN). Interventions: All the study subjects were supplemented with their corresponding intervention capsules (ether CGM along with GLN or CHN along with GLN), as a single oral dose twice a day, once in the morning 10–15 min before breakfast and again in the evening before dinner, for 84 days. Outcome measures: A validated treadmill uphill walking protocol was used for the study, and the efficiency of supplementation was evaluated using visual analogue scale (VAS) score, Karnofsky Performance Scale (KPS) score, and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire at the baseline, 28th, and 84th day following the treatment. Mechanism of action of CGM-GLN combination was analyzed by measuring the levels of serum inflammatory markers interleukin 1 beta (IL-1β), interleukin 6 (IL-6), and soluble vascular cell adhesion molecule-1 (sVCAM) at the baseline and 84th day. Results: CGM-GLN was found to offer significant beneficial effects to pain, stiffness, and physical function of OA subjects compared with CHN-GLN, which was evident from the improvement in walking performance, VAS score, KPS score, and WOMAC score. The efficiency of CGM-GLN was almost double compared with the CHN-GLN by the end of the study (84th day). A significant reduction of inflammatory serum marker levels was observed among CGM-GLN subjects compared with CHN-GLN subjects. Compared with the baseline, CGM-GLN produced 54.52%, 59.08%, and 22.03% reduction in IL-1β, IL-6, and sVCAM levels, respectively. Whereas CHN-GLN group of subjects expressed only 23.17%, 21.38%, and 6.82% reduction in IL-1β, IL-6, and sVCAM levels, respectively. Conclusions: In conclusion, the present study demonstrated the potential benefits of CGM-GLN supplements in alleviating the symptoms and function of OA subjects compared with the standard CHN-GLN treatment. The augmented efficacy of CGM-GLN combination could be attributed to the enhanced anti-inflammatory effect of CGM.
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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) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".