A randomized comparative study of safety and efficacy of immediate release glucosamine HCL and glucosamine HCL sustained release formulation in the treatment of knee osteoarthritis: A proof of concept study
Bibliographic record
Abstract
OBJECTIVES: To compare the safety and efficacy of glucosamine HCl- sustained release (GLU-SR) with that of Glucosamine HCl- immediate release (GLU-IR) in patients with knee osteoarthritis (OA). MATERIALS AND METHODS: This study involved 59 patients with knee OA, randomised to receive single oral dose of 1,500 mg, GLU-SR and GLU-IR for 60 days with 31 and 28 patients, respectively. The primary efficacy (pain and function) was assessed using visual analogue scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores. Intention-to-treat principle, repeated measure of ANOVA and mixed model analysis were used. RESULTS: The patients baseline, demographic and clinical characteristics were comparable between groups with female preponderance (71.20%). There was a significant reduction in algofunctional indices as primary outcome measure in both the groups across time (P < 0.001) and 29% lesser adverse events (AEs) in GLU-SR group, with no difference in the use of rescue medications. CONCLUSIONS: The study showed equal efficacy of the glucosamine formulations on algofunctional indices in reducing pain in patients with knee OA with less number of AEs in GLU-SR.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".