Adverse events in children and adolescents treated with quetiapine
Bibliographic record
Abstract
Quetiapine is a low-affinity dopamine D2 receptor antagonist, approved for the treatment of bipolar disorder and schizophrenia in children and adolescents by the Food and Drug Administration, but not by European Medicine Agency. Although knowledge of adverse drug reactions in children and adolescents is scarce, quetiapine is increasingly being used for youth in Denmark. The aim of this case study is to discuss adverse drug events (ADEs) spontaneously reported to the Danish Medicines Agency on quetiapine used in the pediatric population in relation to adversive drug reactions (ADRs) reported in the European Summary of Product Characteristics (SPCs). The ADE report database at Danish Medicines Agency was searched for all quetiapine ADRs involving individuals (<18 years) in the period 1997-2015. Fifteen ADE case reports were retrieved, scrutinized, and categorized. The average age was 14.8 years (range 10-17 years) and six patients were boys. The main reported ADEs were (i) endocrine, for example, hyperprolactinemia and hyperthyroidism, (ii) cardiac, for example, tachycardia and QT prolongation, (iii) neurological, for example, seizures and cerebral hemorrhage, and (iv) psychiatric, for example, hallucinations. As some of the reported ADEs are life threatening and not listed as ADRs in the SPCs, off-label use of quetiapine in children and adolescents gives rise to safety concerns.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".