Cross-sectional and longitudinal associations between statin use and bone density: the Manitoba BMD registry
Bibliographic record
Abstract
Statins are among the most widely prescribed medications in older individuals. Inconsistent data in humans suggest that statin medications may be associated with greater BMD and lower risk for osteoporosis. We identified 22 393 individuals aged 40 yr and older undergoing initial (Visit 1) and repeat (Visit 2) TH BMD measurement within 1-10 yr total from DXA through the Manitoba BMD Program (February 28, 1999 to March 29, 2018). Linked medication records showed that 4119 (18.3%) of the study population were statin users at Visit 1 and 6667 (29.8%) were statin users at Visit 2. There was inconsistent and largely negative evidence for prior statin use affecting initial TH BMD measurement or BMD change during follow-up. Even among those with the greatest exposure (mean 5.1 yr of prior statin use with high adherence), the observed effects on covariate-adjusted initial TH BMD or annualized change in TH BMD change did not show clinically significant differences. In summary, this large observational analysis, which included both cross-sectional and longitudinal components, failed to detect a clinically meaningful benefit of statin exposure on bone density, even when taken with high adherence over several years.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".