Impact of a restrictive drug access program on the risk of cardiovascular encounters in children exposed to ADHD medications.
Bibliographic record
Abstract
BACKGROUND: ADHD medications increase clinical encounters for cardiovascular symptoms. Uncertain are the roles of differences in ADHD medications and restrictive practices by drug programs. METHODS: We conducted two nested case-control studies. The first was nested within a cohort of children de novo users of methylphenidate, amphetamines or atomoxetine and the second case-control study was nested within a subcohort of de novo amphetamine or atomoxetine users with no cardiovascular events prior to the first dispensing of either drug. The outcome for both studies was the composite of physician visits, emergency room visits or hospitalizations for cardiovascular reasons. Cases were matched on sex, age and date of entry within the cohorts, with up to 10 controls. Patients with an active dispensation of ADHD medications at the index date (and up to 90 days previously) were considered exposed. Conditional logistic regression was used to calculate odd ratios (OR). RESULTS: The full cohort comprised 38,495 patients. Among these patients, 3595 (9.3%) had no prior cardiovascular events (the subcohort). In the full cohort, an association was demonstrated with exposure to amphetamine and atomoxetine (but not methylphenidate) and the cardiovascular encounter outcomes. When the sub-cohort was analyzed the associations with amphetamine or atomoxetine were no longer evident. CONCLUSION: Reimbursement policies need to be considered when conducting observational studies. Had the analysis been conducted without consideration of these policies the results would have incorrectly identified amphetamine and atomoxetine as important risk factors for cardiovascular encounters.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".