A Pilot Study to Compare Two Different Hyaluronic Acid Compounds for Treatment and Knee Osteoarthritis
Bibliographic record
Abstract
Osteoarthritis is characterized by progressive articular cartilage degeneration, changes in subchondral bone and synovial inflammation, leading to pain and disability. Viscosupplementation with hyaluronic acid has been widely investigated due to the viscoelastic properties of this compound to manage pain improving the ability to perform daily activities in patients affected by osteoarthritis. In the present study we investigated the clinical effectiveness of viscosupplementation with a new highly cross-linked hyaluronic acid, Variofill, in patients affected by bilateral knee osteoarthritis in comparison with the widely used Synvisc. A total of 20 patients, aged between 24-74 years and affected by bilateral knee osteoarthritis, participated in this pilot randomized triple-blind clinical study. They received two injections (2 ml each) of Synvisc in their left knee and 2 injections (2 ml each) of Variofill in their right knee spaced 15 days apart. Visual Analogue Scale and Western Ontario McMaster Universities Osteoarthritis Index score were used to evaluate the efficacy of hyaluronic acid injections before and 3 and 6 months after treatment. Both treatment regimens resulted in a significant improvement vs baseline in all endpoints at 3 and 6 months (p less than 0.001). Treatment with Variofill resulted in a high percentage improvement in Visual Analogue Scale pain, Western Ontario McMaster universities Osteoarthritis Index score pain and physical activity, when compared to Synvisc viscosupplementation, at 6 months (p less than 0.05). These results are encouraging for larger clinical trials with Variofill in larger cohorts of patients affected by osteoarthritis of the knee.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.007 | 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".