Cardiac risk assessment before the use of stimulant medications in children and youth
Bibliographic record
Abstract
Regulatory decisions and scientific statements regarding the management of attention-deficit hyperactivity disorder (ADHD) raise questions about the safety of medications and the appropriate pretreatment evaluation to determine suitability for treatment with medication. This is particularly true in the setting of known structural or functional heart disease. The present paper reviews the available data, including peer-reviewed literature, data from the United States Food and Drug Administration Web site on reported adverse reactions in children using stimulant medication, and Health Canada data on the same problem. A consensus-based guideline on appropriate assessment is provided, based on input from members of the Canadian Paediatric Society, the Canadian Cardiovascular Society and the Canadian Academy of Child and Adolescent Psychiatry, with specific expertise and knowledge in the areas of both ADHD and paediatric cardiology. The present statement advocates a thorough history and physical examination before starting stimulant medications, with an emphasis on the identification of risk factors for sudden death, but does not routinely recommend electrocardiographic screening or cardiac sub-specialist consultation unless indicated by history or physical examination findings. A checklist for identifying children who are potentially at risk of sudden death (independent of ADHD or medications used to treat it) is provided. Although recommendations are based on the best evidence currently available, the committee further agrees that more research on this subject is necessary to optimize the approach to this common clinical scenario.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".