Clinical therapy of hyaluronic acid combined with platelet‑rich plasma for the treatment of knee osteoarthritis
Bibliographic record
Abstract
Knee osteoarthritis is the most common degenerative disease of the joints caused by articular cartilage injury, degradation of the joint edge and subchondral bone hyperplasia. Various treatments are used to alleviate the symptoms of patients with knee osteoarthritis, including analgesics and intra-articular injections. Platelet-rich plasma (PRP) is an autologous and multifunctional platelet concentrate of the blood, which stimulates the cartilage healing process and improves the damage caused by articular disease. Hyaluronic acid (HA) is an effective treatment for patients with knee osteoarthritis. In the current study, the effectiveness of PRP and HA combination therapy administered via intra-articular injections for patients with knee osteoarthritis was analyzed. A total of 360 patients with knee osteoarthritis were randomized into four different treatment groups as follows: Double-blind treatment with PRP (2-14 ml); double-blind treatment with HA (0.1-0.3 mg); combination therapy of PRP and HA; and placebo groups. Following treatment, all patients were evaluated using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Common Toxicity Criteria. The most common treatment-emergent adverse events were hypertension and proteinuria. The current study demonstrated that PRP and HA treatment significantly improved arthralgia, and PRP treatment was determined to be significantly more effective than HA treatment using the WOMAC pain score (P<0.05). PRP and HA combination treatment significantly improved arthralgia, reduced humoral and cellular immune responses and promoted angiogenesis, which improved the patients' histological parameters compared with PRP or HA treatment alone. These results suggested that PRP and HA combination treatment may be a potential treatment option for patients with knee osteoarthritis in the future.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".