Viscosupplementation with Intra-Articular Hyaluronic Acid for Treatment of Osteoarthritis in the Elderly
Bibliographic record
Abstract
Osteoarthritis (OA) is very disabling condition in the elderly. The current therapeutic approaches (analgesics, NSAIDs, COX-2 inhibitors, steroids) do not delay the OA progression or reverse joint damage. Moreover, they may cause relevant systemic side effects. Hyaluronic acid (HA) is a physiologic component of the synovial fluid and is reduced in OA joints. Therefore, intra-articular injection of HA, due to its viscoelastic properties and protective effect on articular cartilage and soft tissue surfaces of joints, can restore the normal articular homoeostasis. These effects are evident when HA is properly administered into the articular space; therefore, the use of "image-guided" infiltration techniques is mandatory. Viscosupplementation (VS), with different HA preparations (Low and High molecular weight), can be considered when the patient has not found pain relief from other therapies or is intolerant to analgesics or NSAIDs. A 3-5 doses regimen is usually recommended with 1 week interval between each injection. Several studies have shown the efficacy of HA for the treatment of knee OA, with positive effects on pain, articular function (Western Ontario and Mc Master Universities Osteoarthritis Index [WOMAC], Lequesne Index [LI], Range of Motion [ROM]), subjective global assessment and reduction in NSAIDs consumption. In general, the benefit is evident within 3 months and persists in the following 6-12 months. Encouraging but inconclusive results have also been observed for the treatment of shoulder, carpo-metacarpal, hip and ankle OA. However there is the need of better designed studies to prove the effectiveness of these medications, in order to rule out a placebo effect. The therapy is well tolerated with absence of systemic side effects and only with limited local discomfort.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".