[Intra-articular injection of compound betamethasone and hyaluronic acid for the treatment of moderate-severe knee osteoarthritis:a randomized controlled trial].
Bibliographic record
Abstract
OBJECTIVE: To compare clinical effects of compound betamethasone and compound betamethasone with hyaluronic acid in treating moderate-severe knee osteoarthritis (KOA). METHODS: A prospective randomized controlled study was conducted in 116 patients with unilateral moderate-severe KOA patients from February 2017 to November 2017 and divided into observation group and control group, 58 patients in each group. In observation group, there were 15 males and 43 females aged from 45 to 80 years old with an average of (66.45±6.31) years old;according to Kellgren-Lawrence(K-L) classification, 42 patients were type Ⅲ and 16 patients were type Ⅳ;the courses of disease ranged from 4 to 8 years with an average of (5.25±2.21) years;the patients were treated by injecting 1 ml compound betamethasone into knee joint. In control group, there were 13 males and 45 females aged from 45 to 80 years old with an average of (64.89±6.41) years old;according to K-L classification, 43 patients were type Ⅲ and 15 patients were type Ⅳ;the courses of disease ranged from 4 to 10 years with an average of (5.41±2.35) years;the patients were treated by knee joint injection of 4 ml hyaluronic acid and 1 ml compound betamethasone. Visual analog scale (VAS), Western Ontario and McMaster University Osteoarthritis Index (WOMAC) were used to evaluate clinical effects before treatment and 1 week, 1, month, 3 and 6 months after treatment. RESULTS: >0.05). CONCLUSION: For patients with moderate-severe KOA, there is no significant difference in therapeutic effect between compound betamethasone injection and compound betamethasone combined with hyaluronic acid injection, and long-term effect of two methods is not good.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".