ADHD medications use and risk of mortality and unintentional injuries: a population-based cohort study
Bibliographic record
Abstract
We assessed the association between the use of medications for attention-deficit/hyperactivity disorder (ADHD) and the risk of all-cause mortality and unintentional injuries leading to emergency department (ED) or hospital admission in individuals aged ≤24 years with ADHD. We conducted a population-based retrospective cohort study between 2000 and 2021 using Quebec health administrative data. Individuals were followed from the first ADHD diagnosis or ADHD medication claim until turning 25, death, or study end. Exposure was defined as mutually exclusive episodes of ADHD medication use and/or coverage under the public provincial drug plan (PDP): 1) covered and not treated with ADHD medication; 2) covered and treated with ADHD medication; and 3) not covered under the PDP. The risk of all-cause mortality and unintentional injuries associated with exposure episodes was estimated using multivariable survival analyses. The cohort included n = 217 192 individuals aged 1-24 years with a male to female ratio of close to 2:1. Compared to non-medication use, episodes of ADHD medication use, overall, were associated with reduced all-cause mortality (adjusted hazard ratio, aHR 0.61, 95% CI 0.48-0.76) and unintentional injury leading to ED (0.75, 0.74-0.77) or hospitalisation (0.71, 0.68-0.75). Episodes of stimulants were associated with a lower risk of all-cause mortality and reduced risk of unintentional injuries, while episodes with non-stimulants and with both stimulants and non-stimulants concomitantly were associated with reduced risk of unintentional injuries, but not of all-cause mortality. Although residual confounding cannot be excluded, stimulants may have a protective effect in terms of risk of all-cause mortality and both stimulants and non-stimulants for ADHD may reduce the risk of unintentional injuries. The findings of the current study should inform clinical decision making on the choice of starting a pharmacological treatment for ADHD, when a balance needs to be struck between expected benefits and possible risks.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".