Origin and Efficacy of Hyaluronan Injections in Knee Osteoarthritis: Randomized, Double-Blind Trial
Bibliographic record
Abstract
BACKGROUND Several hyaluronan preparations are available that have different dosage forms, origins, and concentrations. The objective of the study was to compare the efficacy of intra-articular chemically cross-linked hyaluronan (CCH) and avian-derived hyaluronan (ADH) injections in knee osteoarthritis (KOA) patients. MATERIAL AND METHODS In total, 258 patients were randomized into 2 groups of 129 each: patients who received CCH injection (CCH group) and patients who received ADH injection (ADH group). Radiographic Kellgren-Lawrence score, visual analog scale (VAS) pain score, Lequesne index score, the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index, single-limb stance (SLS) test, and timed "Up-and-Go" (TUG) test were performed. The Mann-Whitney U test or independent t-test following Bonferroni adjustment was performed for statistical analysis at 95% of confidence level. RESULTS The CCH group had improved VAS pain score (P<0.0001, q=54.803), total WOMAC score (P<0.0001, q=4.753), Lequesne index score (P<0.0001, q=3.208), and SLS time (P<0.0001, q=8.76) at the end of 6 months as compared to those in the ADH group. After 6 months of follow-up, the ADH group had improved TUG time (P=0.0148, q=3.385) as compared to baseline. Both groups of patients had the similar improvement in Kellgren-Lawrence score and mild to moderate adverse effects after 6 months. CONCLUSIONS CCH injection was superior to ADH injection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".