Association between allopurinol and cardiovascular outcomes and all‐cause mortality in diabetes: A retrospective, population‐based cohort study
Bibliographic record
Abstract
AIM: To assess the association between allopurinol and mortality and cardiovascular outcomes in an allopurinol-treated diabetes cohort. MATERIALS AND METHODS: We conducted a population-based retrospective cohort study in Ontario, Canada. Eligible subjects were ≥ 66 years old with diabetes and a first prescription for allopurinol between 1 April, 2002 and 31 March, 2012 and were followed until 31 March, 2016. The primary outcome was a composite: all-cause mortality, non-fatal cardiovascular event (myocardial infarction, revascularization procedure, or stroke) or congestive heart failure (CHF). Secondary outcomes were components of the primary outcome and pneumonia as a negative tracer. Allopurinol was modelled as time-varying exposed versus unexposed, daily dose category and cumulative dose using sex-specific multivariable Cox proportional hazards models. RESULTS: Over a median follow-up of 4.65 years (interquartile range 1.79-7.81), 16 266/23 103 males and 10 571/15 313 females experienced the primary outcome. Allopurinol was associated with a reduction in the primary outcome [adjusted hazard ratios (aHR) 0.77 (95% confidence interval 0.75-0.80) and 0.81 (0.78-0.84) for males and females, respectively], driven by marked reductions in all-cause mortality and modest reductions in cardiovascular events/CHF. There was no effect of cumulative allopurinol dose on any outcome, and allopurinol was also associated with reduced risk of pneumonia in males [aHR 0.88 (0.83, 0.93)]. CONCLUSIONS: Allopurinol was associated with reduced mortality and cardiovascular outcomes. However, lack of cumulative dose effect and a positive tracer outcome in males suggests residual bias. Future research assessing whether allopurinol prevents vascular complications in diabetes requires a clinical trial.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".