Anti-diabetic drug use and the risk of motor vehicle crash in the elderly.
Bibliographic record
Abstract
BACKGROUND: Studies of the risk of motor vehicle crash associated with diabetes have produced conflicting results. OBJECTIVES: To assess whether the use of anti-diabetic drugs among the elderly increases the risk of motor vehicle crash. METHODS: The computerized databases of the various universal insurance programs of Québec were linked to form a cohort of all 224,734 elderly drivers that was followed from 1990-1993. Using a nested case-control approach, all 5,579 drivers involved in an injurious crash (cases) and a random sample of 13,300 control subjects were identified. Exposure to anti-diabetic drugs was assessed in the year preceding the index date, namely the date of the crash for the cases and a randomly selected date during follow-up for the controls. RESULTS: The adjusted rate ratio of an injurious crash was 1.4 (95% CI: 1.0-2.0) for current users of insulin monotherapy relative to non-users and 1.3 (95% CI: 1.0-1.7) for sulfonylurea and metformin combined. Monotherapy, using either a sulfonylurea or metformin, was not associated with an increased risk. There was a dose-response effect in subjects using high doses of combined oral therapy (RR 1.4; 95% CI: 1.0-2.0). For users of insulin monotherapy or of high doses of combined oral therapy, the increase corresponds to an excess rate of 32 crashes per 10,000 elderly drivers per year. CONCLUSIONS: L Elderly drivers treated with insulin monotherapy or a combination of sulfonylurea and metformin, especially at high doses, have a small increased risk of injurious crashes. There is no increased risk associated with any regimen of oral monotherapy.
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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 | 0.002 | 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".