Evaluation of efficacy and safety of Collashot C2 plus capsule in osteoarthritis patients
Bibliographic record
Abstract
Background: Osteoarthritis (OA), the most prevalent joint disease, is marked by chronic joint pain and debilitating symptoms. Many drugs are available in the market for treating osteo arthritis symptoms but there is still need for drugs with least adverse effects. So, in this study, an attempt has been done with Collashot C2 plus capsule, a nutraceutical for treating OA symptoms. Methods: This is an outcome, quasi-experimental study where patients with OA were included. Patients were given capsule Collashot C2 plus daily for 3 months. A total of 30 male and female patients were included in the study. Changes from baseline to 12 weeks in knee pain intensity measured by pain visual analogue scale (VAS) and in Western Ontario and McMaster universities OA index (WOMAC) pain subscale, laboratory parameters, participant's global assessment of improvement of OA were assessed. Adverse drug reactions were also observed during the study period. Results: There was a statistically significant improvement in the VAS pain scale, WOMAC pain score and in participant's global assessment of improvement of OA at week 4, week 8, and week 12 compared to baseline (p<0.001) was observed. Conclusions: Collashot C2 plus capsule has proved to be very safe and effective in the management of OA Participants by reducing inflammation, providing adequate pain relief without causing any major side effects.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".