Combined intra-articular injection of corticosteroid and hyaluronic acid reduces pain compared to hyaluronic acid alone in the treatment of knee osteoarthritis
Bibliographic record
Abstract
Intra-articular injections of corticosteroid (CS) and hyaluronic acid (HA) have individually demonstrated efficacy for knee osteoarthritis (OA); however, both treatments are limited by the trajectory of symptom relief. The combination of CS and HA in the management of knee OA may provide improved symptomatic relief for patients who are candidates for intra-articular therapies. Electronic databases Medline, EMBASE and Cochrane Library were used to identify relevant publications. Randomized controlled trials (RCT) that evaluated intra-articular injections of combined CS and HA in comparison to HA alone were included. Outcomes eligible for meta-analysis were WOMAC pain, WOMAC total, OMERACT-OARSI responder rate, and treatment-related adverse events. Standardized mean differences (SMD) were calculated for continuous outcomes using an inverse variance method and a random-effects model. Odds ratios (OR) were calculated for dichotomous outcomes using the Mantel–Haenszel method and a random-effects model. Heterogeneity was assessed using the I 2 statistic. Eight trials ( n = 751 patients) were included. Reduction in WOMAC pain scores at 2–4 weeks favoured the combined CS and HA group compared to HA alone [SMD 0.60, 95% CI (0.23, 0.97); p = 0.002, I 2 = 75%]. Longer term improvements at 24–26 and 52 weeks WOMAC pain scores also favoured the combined CS and HA group {[SMD 0.25, 95% CI (0.09, 0.41); p = 0.002, I 2 = 0%] and [SMD 0.39, 95% CI (0.01, 0.77); p = 0.05, I 2 = 0%]} compared to HA alone, respectively. There were no significant differences in WOMAC total scores, OMERACT-OARSI responder rate, or treatment-related adverse events. Combined intra-articular injections of CS and HA led to reductions in pain at 2–4, 24–26 and 52 weeks compared to HA injections alone. Level II—meta-analysis.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.015 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".