Effect of Weekly Alendronate on Knee Symptoms in Patients with Osteoporosis and Knee Osteoarthritis Coexistence - Original Investigation
Bibliographic record
Abstract
Aim: The aim of this study was to examine the effect of alendronate 70 mg weekly on knee symptoms in elderly women with osteoporosis and knee OA coexistence. Material and Methods: Elderly women who diagnosed as osteoporosis between 60-75 years old, underwent radiography of the knee if they reported symptoms of knee OA. Radiographs were read for Kellgren and Lawrence grade and individual features of OA. Osteoporotic patients with Knee OA treated with 70 mg alendronate once weekly for one year. Knee symptoms were assessed by interview before the treatment and 6 and 12 months after the treatment, and knee pain severity was evaluated using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Lequense index, VAS at rest and at movement. Results: Alendronate 70 mg once weekly use was associated with less severity of knee pain as assessed by WOMAC scores, Lequense index, VAS at rest and at movement at 6th and 12th month assessments. Conclusion: This current study has shown that Alendronate 70 mg once weekly use was associated with less severity of knee symptoms in elderly women with osteoporosis and knee OA coexistence. Additional long-term randomised, placebo controlled clinical trials are needed to confirm this effect of weekly Alendronate. (From the World of Osteoporosis 2010;16:17-21)
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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 | 0.001 |
| 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 | 0.000 |
| 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".