Intra-articular hyaluronic acid and platelet-rich plasma as monotherapy or combination therapy in knee osteoarthritis?
Bibliographic record
Abstract
Aim To systematically identify best current evidence on intra-articular combination therapy with hyaluronic acid (HA) and platelet-rich plasma (PRP), compared to monotherapy in knee osteoarthritis.Methods Using the McMaster University and National Health Service five-step systematic approach, we conducted a bottom-up literature search of all existing evidence through Ovid Medline, Ovid Embase, and Cochrane (Central – Wiley) from January 2021 to June 2024.Results Of 258 articles retrieved, we systematically narrowed best current evidence to one meta-analysis when evaluating combination therapy versus HA alone. This demonstrated superior outcomes with combination therapy against HA only at 3, 6, and 12 months on the visual acuity scale (VAS, p < 0.001), and with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at 12 months in areas of stiffness and physical function (p < 0.001). For combination therapy versus PRP alone, one randomized controlled trial qualified as best current evidence. This demonstrated superior VAS outcomes with combination therapy compared to PRP monotherapy at 6 months (p < 0.02).Conclusion Best current evidence indicates that intra-articular HA and PRP as combination therapy has superior short and long term symptom control over HA or PRP as monotherapy. Due to the extensive heterogeneity in the studies, results should be interpreted with caution.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".