Statin Use is Associated With Insulin Resistance in Participants of the Canadian Multicentre Osteoporosis Study
Bibliographic record
Abstract
Abstract Context Statins have been linked to the development of diabetes and atherosclerotic plaque calcification in patients with cardiac disease. Objective To determine the association between statin use and statin characteristics and insulin resistance and abdominal aortic calcification (AAC) in participants of the Canadian Multicentre Osteoporosis Study (CaMos). Design Observational study. Setting General community. Participants Nondiabetic participants of the Kingston CaMos site Intervention Insulin resistance and AAC in statin users and nonstatin users were compared with and without the inclusion of a propensity score (PS) to be on a statin. The covariates of hypertension, sex, body mass index, smoking, kidney stones, and age that were included in the PS were selected based on clinical judgment confirmed by the statistical analysis of a difference between statin users and nonstatin users. Main Outcome Measures Insulin resistance measured by the homeostasis model assessment (HOMA-IR) and AAC assessed on lateral spine radiographs using the Framingham methodology. Results Using a general linear model, statin use was associated with higher levels of HOMA-IR after stratified PS adjustment (β = 1.52, [1.18–1.95], P < 0.01). Hydrophilic statin users (n = 9) and lipophilic statins users (n = 30) had higher HOMA-IR compared to nonstatin users (n = 125) ([β = 2.29, (1.43–3.68), P < 0.001] and [β = 1.36, (1.04–1.78), P < 0.05]), respectively, in general linear models after stratified PS adjustment. Statin use was associated with AAC without stratifying by PS in the Wilcoxon test, but was no longer significant when stratified by PS. Conclusions Statins, widely prescribed drugs to lower cholesterol, may have unintended consequences related to glucose homeostasis that could be relevant in healthy aging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".