Ozone or hyaluronic acid in the intra-articular treatment of knee osteoarthritis?
Bibliographic record
Abstract
Aim: Both intra-articular ozone and hyaluronic acid injections are commonly used for treatment of knee osteoarthritis (KOA). It was aimed to evaluate and compare the effectiveness of intra-articular ozone and hyaluronic acid (HA) injections on pain and functional limitations of participants with KOA.Methods: One hundred and eight consecutive patients (eighty-four women, twenty-four men) aged 40-75 years visited to outpatient clinic with knee pain for longer than 3 months. HA injections were performed as a single dose, and ozone injections were administered once a week as three doses in total. The Visual Analog Scale (VAS) and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) were performed before treatment, one and three months after treatment.Results: Seventy-six participants were included in the study. The randomization was done as Hyaluronic Acid (n=39) and Ozone (n=37) groups. No significant difference was found in terms of WOMAC-total, WOMAC-pain, and VAS (p>0.05) at all stages among groups. WOMAC-stiffness score was found significantly different between first month and third month follow-ups (p=0.011). Also, there was a significant change in WOMAC-function scores between before treatment and first month follow-ups (p=0.008), and before treatment and third month follow-ups (p=0.002) in inter-group analysis.Conclusion: Both ozone and HA injections were effective treatment methods for KOA. However, intraarticular HA injection had a longer-lasting effect on pain and function than ozone injection.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".