Intra-articular injection of hyaluronic acid for treatment of osteoarthritis knee: comparative study to intra-articular corticosteroids
Bibliographic record
Abstract
Osteoarthritis (OA) is a chronic degenerative joint disease characterized by pain and progressive functional limitation. Although both corticosteroid and hyaluronic acid (HA) injections are widely used to palliate the symptoms of knee OA, few researches involving a comparison of two interventions have been conducted. The objective of the study was to compare the efficacy and safety of HA to corticosteroid injections for the treatment of knee OA. We enrolled 60 patients with knee OA who were randomized to receive intra-articular injection of either HA or the corticosteroid. The therapy was followed for 6 months. The patients treated with HA received one course of injections per week for 3 weeks and the other group received single injection of corticosteroid. The two groups were compared as regards pain and functional improvement using the Western Ontario and McMaster University Osteoarthritis Index and visual analog scale. The study included 60 patients, with age ranging from 36 to 65 years with a mean of 51.8 years. All of them were diagnosed with knee OA using ACR clinical classification criteria. Patients were recruited between May and December 2015. After 6 months of the treatment, both groups showed functional improvement. HA group showed significant improvement compared with the corticosteroid group as regards the Western Ontario and McMaster University Osteoarthritis Index and visual analog scale (P=0.01). Both HA and corticosteroid groups showed improvement in pain and knee function, but the intra-articular HA was superior to corticosteroid on long-term follow-up. This supports the potential rate of intra-articular HA as an effective long-term therapeutic option for patients with OA of the knee.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".