The Effect of Ozone (O<sub>3</sub>) versus Hyaluronic Acid on Pain and Function in Patients with Knee Osteoarthritis: A Systematic Review and Meta-Analysis.
Bibliographic record
Abstract
BACKGROUND: Of the pharmacological modalities for knee osteoarthritis (OA), intra-articular injections including ozone (O3) and hyaluronic acid (HA) are commonly used for reducing pain and improving function. In this systematic review and meta-analysis, we aimed to compare the effect of O3 versus HA in reducing pain and increasing function in patients with knee OA. METHODS: After searching databases, we included 6 randomized controlled trials on patients with knee OA that compared the effects of intra-articular injection of ozone versus HA. The primary outcome was visual analogue scale (VAS) of pain. The secondary outcome was Western Ontario and McMaster Universities Arthritis Index (WOMAC) score. RESULTS: There was a total of 237 patients in the HA group and 230 patients in the Ozone group. Of 6 studies, 4 were in English, 1 was in Persian, and 1 was in German language. The overall Standardized Mean Difference (SMD) for VAS pain did not show a significant difference between the groups although it favored HA injection (1.27 [95%CI: (-0.12)-2.66]). Total WOMAC score showed a significant difference over the time favoring HA injection (4.5 [95%CI: 1.1-8]). However, no single time point showed any significant difference between groups. CONCLUSION: This meta-analysis showed no significant difference between HA and ozone in reducing pain and improving function in patients with knee OA, although the overall results favored HA over ozone. Since previous studies have shown comparable results between HA and placebo, ozone seems to fall in the same category with more placebo effect rather than a real disease-modifier.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".