A randomised, double-blind, controlled trial comparing two intra-articular hyaluronic acid preparations differing by their molecular weight in symptomatic knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: To compare the effects of an intermediate molecular weight (MW) intra-articular hyaluronic acid (HA) with a low MW product on knee osteoarthritis (OA) symptoms. METHODS: Patients with symptomatic knee OA were enrolled inarandomised, controlled, double-blind, parallel-group, non-inferiority trial with the possibility to shift to superiority. Patients were randomised to GO-ON(MW 800-1500 kD, 25 mg/2.5 ml) or Hyalgan(MW 500-730 kD, 20 mg/2 ml) injected at 3-weekly intervals. The primary outcome was 6-month change in the WOMAC pain subscale (0-100 mm). Sample size was calculated on a non-inferiority margin of 9 mm, lower than the minimum perceptible clinical improvement. Secondary endpoints included OARSI-OMERACT responder rates RESULTS: The intention-to-treat (ITT) and per-protocol (PP) populations consisted of 217 and 209 patients and 171 and 172 patients in the GO-ON and Hyalgan groups, respectively. ITT WOMAC pain of 47.5±1.0(SE) and 48.8±1.0 mm decreased by 22.9±1.4 mm with GO-ON and 18.4±1.5 mm with Hyalgan after 6 months. The primary analysis was conducted in the PP population followed by the ITT population.Mean (95% CI) differences in WOMAC pain change were 5.2 (0.9 to 9.6)mm and 4.5 (0.5 to 8.5)mm, respectively,favouring GO-ON, satisfying the claim for non-inferiority (lower limit>-9 mm) and for statistical superiority (95% CI all>0, p=0.021). Ahigher proportion of OARSI/OMERACT responders was observed with GO-ONthan with Hyalgan (73.3% vs58.4%, p=0.001). Both preparations were well tolerated. CONCLUSIONS: Treatment with 3-weekly injections of intermediate MW HA may be superior to low MW HA on knee OA symptoms over 6 months, with similar safety.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".