A comparative study of the results of conservative therapy, intra-articular steroid injection therapy and intra-articular hyaluronic acid injection therapy in primary osteoarthritis of knee: A prospective study in Eastern Indian population
Bibliographic record
Abstract
Background:To compare the results of intra articular steroid, intra articular hyaluronic acid and conservative therapy, in primary osteoarthritis of knee. There are many literature comparing the efficacy between hyaluronic acid and steroids, however to compare the three variables we are not aware of any studies available. Materials & Methods: 45 patients attending were selected and randomized 15 each in each group (A, B and C). The patients treated with hyaluronic acid (A) received one course of three weekly injections. The patients treated with the steroid (B) received one injection at the time of enrollment in the study. In group C, physical therapy in the form of heat and physiotherapy were taught to patients. Western Ontario and McMaster University Osteoarthritis Index and Lequesne were used to assessed the patients. Results: All the three groups were followed at 2, 4, and 6 months. In group A on first visit WOMAC average score is 70.8 which improves to 68, 61.06 and then to 64 (p- 0.00001). In group B average score before injection is 71.2; the follow up average score 60.4, 66.93, 73.86(p-0.00001). In group C patients WOMAC score in first visit is 72. the follow up average score 68.53, 74.8, 79 (p
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".