Comparative effectiveness of cardioprotective drugs in elderly individuals with type 2 diabetes
Bibliographic record
Abstract
AIMS: Although many elderly individuals suffer from type 2 diabetes, the effectiveness of cardioprotective drugs in primary prevention of cardiovascular events in clinical practice in this population has rarely been evaluated. We aimed to assess the effectiveness of, (i) angiotensin converting enzyme inhibitors or angiotensin receptor blockers, (ii) statins, (iii) antiplatelet drugs and (iv) the combination of these three drugs, in the prevention of myocardial infarction (MI) and stroke in elderly individuals with type 2 diabetes. METHODS: Using Quebec administrative databases, we conducted nested case-control analyses among a cohort of 17,384 individuals without a history of cardiovascular disease. Individuals were aged ≥ 66 years, newly treated with oral antidiabetes drugs and had not used any of the three above classes of cardioprotective drugs in the year before cohort entry. For each case (MI/stroke during follow-up), five controls were matched for age, year of cohort entry and sex. Use of each drug and of their combination was defined as current, past or no use. We calculated adjusted odds ratios (AOR) of MI/stroke. RESULTS: We observed no reduction in the MI/stroke risk for users of ACEI/ARB nor for users of the three drugs combination. Longer exposure to statins was associated with a lower risk (AOR for every 30 days of therapy: 0.97; 95% CI: 0.96-0.99). By contrast, current use of antiplatelet drugs was associated with an increased risk of MI/stroke (1.40; 1.12-1.75). CONCLUSION: The benefit of cardioprotective drugs in primary prevention was not clear in this cohort of elderly individuals with type 2 diabetes. A short duration of exposure to these drugs might explain the lack of benefit.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".