Hyaluronic acid injections for knee osteoarthritis. Systematic review of the literature.
Bibliographic record
Abstract
OBJECTIVE: To determine whether viscosupplementation with intra-articular hyaluronic acid (HA) injections improves pain and function in patients with osteoarthritis (OA) in their knees. DATA SOURCES: We searched MEDLINE, Pre-MEDLINE, and Cochrane databases using the MeSH headings and key words osteoarthritis (knee) and hyaluronic acid. STUDY SELECTION: English-language case series and randomized controlled trials (RCTs) were selected. Studies with biologic, histologic, or arthroscopic outcomes were excluded. SYNTHESIS: Five case series and 13 RCTs were critically appraised. Data from three case series and three RCTs using injections of high-molecular-weight HA (Synvisc) demonstrated significant improvement in pain, activity levels, and function. The beneficial effect started as early as 12 weeks. Studies using low-molecular-weight HA had conflicting results. CONCLUSION: Viscosupplementation with high-molecular-weight HA is an effective treatment for patients with knee OA who have ongoing pain or are unable to tolerate conservative treatment or joint replacement. Viscosupplementation appears to have a slower onset of action than intra-articular steroids, but the effect seems to last longer.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".