Sulphonylureas versus metformin and the risk of ventricular arrhythmias among people with type 2 diabetes: A population‐based cohort study
Bibliographic record
Abstract
AIM: To determine whether the use of sulphonylurea monotherapy, compared with metformin monotherapy, is associated with an increased risk of ventricular arrhythmia (VA) among patients initiating pharmacotherapy for type 2 diabetes. RESEARCH DESIGN AND METHODS: We conducted a population-based cohort study using electronic health data extracted from the UK's Clinical Practice Research Datalink Aurum. Using the active comparator, new-user cohort design, we compared rates of VA among patients aged 18 years or older using sulphonylurea monotherapy with those using metformin monotherapy as their initial pharmacological treatment for type 2 diabetes from April 1998 to December 2019. We used a Cox proportional hazards model with inverse probability of treatment weighting by propensity score to estimate the adjusted hazard ratio (aHR) and a corresponding bootstrap 95% confidence interval (CI) for VA with sulphonylurea monotherapy versus metformin monotherapy. RESULTS: The cohort included 92 638 new users of sulphonylurea and 506 882 new users of metformin. A total of 279 VA events occurred among sulphonylurea users (rate per 10 000 person-years: 25.5, 95% CI: 22.7 to 28.7) and 1537 VA events occurred among metformin users (rate per 10 000 person-years: 18.5, 95% CI: 17.6 to 19.5). Compared with metformin, sulphonylureas were associated with an increased risk of VA (aHR: 1.42, 95% CI: 1.18 to 1.69). CONCLUSIONS: Sulphonylureas are associated with an increased risk of VA when used as first-line therapy for type 2 diabetes relative to metformin use. This increased risk should be considered when prescribing sulphonylureas as an initial treatment for type 2 diabetes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".