Strontium ranolate effect on knee osteoarthritis
Bibliographic record
Abstract
Osteoarthritis (OA) is a joint disease that most commonly accompanied with pain and joint deformity which eventually leads to disability. Burden of OA will be accounted second in women and fourth in men in Iran. Most therapies of knee osteoarthritis are symptomatic treatment. Recently, strontium ranolate are used as a new agent for handling of post menopausal osteoporosis and provided reduces in hip and vertebral fractures risks. Beneficial effects of this treatment are showed in spine OA as well. This study was designed to evaluate short-term effects of strontium ranolate on treating of knee OA in Iran. Study was performed as a randomized double blind clinical trial. Symptomatic knee OA cases at Kellgren – Lawrence based stages I, II and III were enrolled in study following exclusion of systemic disease as well as joint disease. These patients randomly divided into 2 groups and each group was treated with placebo and Strontium ranolate at the dose of 2 mg per day. Then cases were followed for 12 weeks via Visual Analog Scale (VAS) and Western Ontario and McMaster universities (WOMAC) questionnaires associated with subsequent statistically analyzes. Statistically significant differences in the rate decline of pain, stiffness, functionality and eventually total scores as well as VAS scores were revealed between strontium ranolate and placebo therapy. Given the proven positive effects, strontium ranolate recommended as one of treatment bases in association with weight loss and muscles physiotherapy as well as healthy use of joints.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".