Intra‐Articular Platelet‐Rich Plasma Combined With Hyaluronic Acid Injection for Knee Osteoarthritis Is Superior to Platelet‐Rich Plasma or Hyaluronic Acid Alone in Inhibiting Inflammation and Improving Pain and Function
Bibliographic record
Abstract
PURPOSE: To evaluate the effectiveness and explore the therapeutic mechanisms of platelet-rich plasma (PRP) combined with hyaluronic acid (HA) as a treatment for knee osteoarthritis (KOA). METHODS: In total, 122 knees were randomly divided into HA (34 knees), PRP (40 knees), and PRP+HA (48 knees) groups. Platelet densities in whole blood and PRP were examined using Wright-Giemsa staining. Visual analogue scale, Lequesne, Western Ontario and McMaster Universities Osteoarthritis Index, Lysholm scores, and postoperative complications were evaluated. High-frequency color Doppler imaging was used to observe the synovium and cartilage. Enzyme-linked immunosorbent assays were used to quantify interleukin-1β, tumor necrosis factor-α, matrix metalloproteinase-3, and tissue inhibitor of metalloproteinase-1 levels in synovial fluid. RESULTS: = .000). At 6 and 12 months, synovial hyperplasia in the PRP and PRP+HA groups was improved (P < .05). After 6 and 12 months, the synovial peak systolic velocity, synovial end-diastolic velocity, systolic/diastolic ratio, and resistance index were improved in the PRP+HA group (P < .05). Complications were greatest in the PRP group (P = .008). After 6 and 12 months, interleukin-1β, tumor necrosis factor-α, matrix metalloproteinase-3, and tissue inhibitor of metalloproteinase-1 in the PRP and PRP+HA groups decreased (P < .05), with more apparent inhibition in the PRP+HA group (P < .05). CONCLUSIONS: PRP combined with HA is more effective than PRP or HA alone at inhibiting synovial inflammation and can effectively improve pain and function and reduce adverse reactions. Its mechanism involves changes in the synovium and cytokine content. LEVEL OF EVIDENCE: Level II, Prospective cohort study.
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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 | 0.001 | 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".