The Impact of Excluding Patients with End-Stage Knee Disease in Intra-Articular Hyaluronic Acid Trials: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: The Kellgren-Lawrence (K-L) grade is the most commonly used measure of radiographic disease severity in knee osteoarthritis (OA). Studies suggest that intra-articular hyaluronic acid (IA-HA) should only be considered in cases of early stage knee OA. The purpose of this review was to determine if trials administering IA-HA in early-moderate knee OA patients demonstrated greater pain relief than studies that also included patients with end-stage disease. METHODS: We conducted a systematic search of the literature to identify randomized controlled trials (RCT) comparing IA-HA with saline injections and that diagnosed disease severity using the K-L grade criteria. The primary outcome was mean change in pain from baseline at 4-13 weeks and 22-27 weeks. Safety was evaluated on the total number of participants experiencing a treatment-related adverse event (AE). RESULTS: Twenty RCTs were included. In the early-moderate OA subgroup, the mean change in pain scores was statistically significant favoring IA-HA from baseline to 4-13 weeks [SMD = - 0.30, 95% CI - 0.44 to - 0.15, p < 0.0001] and within 22-27 weeks [SMD = - 0.27, 95% CI - 0.39 to - 0.16, p < 0.00001]. No significant differences were observed in the late OA subgroup. IA-HA was associated with a significantly greater risk of treatment-related AEs relative to saline in the late OA subgroup [RR = 1.76, 95% CI 1.16-2.67, p = 0.008]. CONCLUSION: IA-HA provides significant pain relief compared to saline for patients with early-moderate knee OA, compared to cohorts including patients with end-stage OA (KL grade 4), with no increase in the risk of treatment-related AEs, up to 6 months. Patients with end-stage disease had lower levels of pain relief and may be diluting study results if included in the treatment cohort. FUNDING: Ferring Pharmaceuticals.
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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 | 0.035 | 0.070 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.046 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".