Role and Effectiveness of Intra-Articular Injection of Hyaluronic Acid in the Treatment of Knee Osteoarthritis: A Prospective Study
Bibliographic record
Abstract
Background: Intra-articular injection of hyaluronic acid (IAHA) is a widely utilized therapeutic approach for knee osteoarthritis, although its efficacy remains a topic of debate. Aim and Objective: This prospective study aimed to evaluate the effectiveness and safety of IAHA therapy in patients with knee osteoarthritis. Materials and Methods: Thirty patients with knee osteoarthritis were treated with three IAHA injections over one year. Pain severity was assessed using the Visual Analog Scale (VAS), while knee function was evaluated using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). A radiographic evaluation was performed to monitor disease progression. Adverse events were documented throughout the study period. Subgroup analyses were conducted based on demographic and clinical characteristics. Results: Following IAHA therapy, a significant reduction in knee pain severity was observed, with the mean VAS score decreasing from 7.2 ± 1.5 at baseline to 3.4 ± 1.2 at six months post-treatment (p < 0.001). Similarly, knee function improved significantly, as evidenced by a decrease in the mean WOMAC score from 45.6 ± 9.8 to 22.3 ± 6.7 (p < 0.001). Radiographic evaluation revealed no significant disease progression. Transient local reactions at the injection site were reported in 16.7% of patients, but no serious adverse events were documented. Subgroup analyses did not identify significant variations in treatment response based on age, gender, disease severity, or comorbidity profiles. Conclusion: Intra-articular injection of hyaluronic acid effectively reduced pain and improved knee function in patients with knee osteoarthritis, with a favorable safety profile and no evidence of disease progression on radiographic evaluation. These findings support the continued use of IAHA therapy as a viable treatment option for knee osteoarthritis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".