INTRA-ARTICULAR OZONE OR HYALURONIC ACID INJECTION IN PATIENTS WITH KNEE OSTEOARTHRITIS
Bibliographic record
Abstract
Objective: To compare the effect of ozone and hyaluronic acid for pain relief in patients of knee osteoarthritis. Study Design: Randomized clinical trial Place of study: Study was conducted at Orthopedic department, Sheikh Zayed Hospital, Rahim Yar Khan. Duration of study: study was completed in one year from February 2019 to February 2020. Methodology: A total of 200 patients were included in the study through non-probability consecutive sampling and divided into two groups (A and B) through lottery method. Collected data was entered and analyzed by using SPSS version 24, mean and standard deviation were calculated for numerical data like age, and Visual Analog Scale (VAS scale) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC score). Frequency and numbers were calculated for qualitative data like gender. Paired t-test and chi square test were applied to see significance of data, p-value less than or equal to 0.05 was considered as significant. Results: Mean age, BMI, WOMAC and VAS of ozone therapy’s patients was 55.85±4.56 years, 26.01±1.75 kg/m2, 42.23±7.30 and 7.35±1.90 respectively. Mean VAS, WOMAC pain, WOMAC stiffness, WOMAC function and WOMAC total of the HA therapy’s (before) patients was 6.62±2.25, 8.62±1.89, 1.91±1.08, 27.59±2.64 and 37.67±4.06 respectively. While, the mean VAS, WOMAC pain, WOMAC stiffness, WOMAC function and WOMAC total of the HA therapy’s (after) patients was 3.08±1.68, 2.97±1.21, 1.0±0.48, 13.36±2.39 and 17.40±3.64 respectively. According to paired sample t test, the difference was statistically significant at (p<0.05). Conclusion: Results of our study concluded that ozone oxygen and hyaluronic acid is equally effective for relieve of pain in knee osteoarthritis. There was no significant difference among groups which shows that no drug has superiority on each other. Keywords: Osteoarthritis, Intraarticular, Ozone, Hyaluronic acid, Pain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".