Sulfonylureas as initial treatment for type 2 diabetes and the risk of adverse cardiovascular events: A population‐based cohort study
Bibliographic record
Abstract
AIMS: Sulfonylureas are recommended as second-line treatment in the management of type 2 diabetes. However, they are still commonly used also as first-line treatment instead of metformin. Given the controversial cardiovascular safety of sulfonylureas, we aimed to determine if their use as first-line treatment is associated with adverse cardiovascular events among patients with newly treated type 2 diabetes compared with metformin. METHODS: We conducted a population-based cohort study of patients with newly treated type 2 diabetes using the UK's Clinical Practice Research Datalink. Initiators of metformin and sulfonylurea monotherapy were matched on high-dimensional propensity score, and Cox proportional hazards models were used to compare the rate of cardiovascular events (myocardial infarction, ischaemic stroke, cardiovascular death, and all-cause mortality) with sulfonylureas vs metformin. RESULTS: Our cohort included 94 750 patients initiating treatment for type 2 diabetes, 17 612 on a sulfonylurea and 77 138 on metformin. After matching, sulfonylurea monotherapy, compared with metformin monotherapy, was not associated with an increased risk of myocardial infarction (hazard ratio [HR]: 1.04, 95% confidence interval [CI]: 0.85-1.25) but was associated with increased risks of ischaemic stroke (HR: 1.25, 95% CI: 1.002-1.56), cardiovascular death (HR: 1.25, 95% CI: 1.06-1.47), and all-cause mortality (HR: 1.60, 95% CI: 1.45-1.76). This represents an additional 2.0 ischaemic strokes, 3.5 cardiovascular deaths, and 21.4 all-cause deaths per 1,000 patients per year with sulfonylureas. CONCLUSIONS: Initiating treatment of type 2 diabetes with a sulfonylurea rather than metformin is associated with higher rates of ischaemic stroke, cardiovascular death, and all-cause mortality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".