The relationship of antiresorptive drug use to structural findings and symptoms of knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To examine the cross-sectional association between use of medications that have a bone antiresorptive effect (estrogen, raloxifene, and alendronate) and both the structural features of knee osteoarthritis (OA), assessed by magnetic resonance imaging (MRI) and radiography, and the symptoms of knee OA in elderly women. METHODS: Women in the Health, Aging and Body Composition Study underwent MRI and radiography of the knee if they reported symptoms of knee OA, and women without significant knee symptoms were selected as controls. MR images of the knee were assessed for multiple features of OA using the Whole-Organ MRI scoring method, and radiographs were read for Kellgren and Lawrence grade and individual features of OA. Concurrent medication use and knee symptoms were assessed by interview, and knee pain severity was evaluated using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). RESULTS: There were 818 postmenopausal women from whom we obtained MR images of the knee and data on medication use. Among these women, 214 (26.2%) were receiving antiresorptive drugs. We found no significant association between overall use of antiresorptive drugs and the presence of knee pain and radiographic changes of OA of the knee. Use of alendronate, but not estrogen, was associated with less severity of knee pain as assessed by WOMAC scores. Both alendronate use and estrogen use were associated with significantly less subchondral bone attrition and bone marrow edema-like abnormalities in the knee as assessed by MRI, as compared with women who had not received these medications. CONCLUSION: Elderly women being treated with alendronate and estrogen had a significantly decreased prevalence of knee OA-related subchondral bone lesions compared with those reporting no use of these medications. Alendronate use was also associated with a reduction in knee pain according to the WOMAC scores.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".