Higher potency statins and the risk of new diabetes: multicentre, observational study of administrative databases
Bibliographic record
Abstract
OBJECTIVE: To evaluate the incremental increase in new onset diabetes from higher potency statins compared with lower potency statins when used for secondary prevention. DESIGN: Eight population based cohort studies and a meta-analysis. SETTING: Six Canadian provinces and two international databases from the UK and US. PARTICIPANTS: 136,966 patients aged ≥ 40 years newly treated with statins between 1 January 1997 and 31 March 2011. METHODS: Within each cohort of patients newly prescribed a statin after hospitalisation for a major cardiovascular event or procedure, we performed as-treated, nested case-control analyses to compare diabetes incidence in users of higher potency statins with incidence in users of lower potency statins. Rate ratios of new diabetes events were estimated using conditional logistic regression on different lengths of exposure to higher potency versus lower potency statins; adjustment for confounding was achieved using high dimensional propensity scores. Meta-analytic methods were used to estimate overall effects across sites. MAIN OUTCOME MEASURES: Hospitalisation for new onset diabetes, or a prescription for insulin or an oral antidiabetic drug. RESULTS: In the first two years of regular statin use, we observed a significant increase in the risk of new onset diabetes with higher potency statins compared with lower potency agents (rate ratio 1.15, 95% confidence interval 1.05 to 1.26). The risk increase seemed to be highest in the first four months of use (rate ratio 1.26, 1.07 to 1.47). CONCLUSIONS: Higher potency statin use is associated with a moderate increase in the risk of new onset diabetes compared with lower potency statins in patients treated for secondary prevention of cardiovascular disease. Clinicians should consider this risk when prescribing higher potency statins in secondary prevention patients.
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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 | 0.001 | 0.001 |
| 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".