Adverse events in children and adolescents treated with antipsychotic medications
Bibliographic record
Abstract
OBJECTIVE: To report the odds of developing adverse events associated with antipsychotic treatment among children and adolescents. METHOD: A retrospective cohort design evaluating medical and pharmacy claims from one state Medicaid program was used to compare incidence rates for six categories of adverse events of antipsychotic use in 4140 children and adolescents newly prescribed one of six atypical or two conventional antipsychotic medications, January, 1998 to December, 2005 with prevalence rates of these conditions in a random sample of 4500 children not treated with psychotropic medications. RESULTS: The odds of developing obesity/excessive weight gain, Type II diabetes and dyslipidemia, digestive/urogenital problems, and neurological/sensory symptoms were higher for females and those prescribed multiple antipsychotic medications. The odds of developing cardiovascular conditions were higher for those prescribed multiple antipsychotic medications and haloperidol. The odds of developing somatic conditions were higher for females, children 12 and under, and those prescribed multiple antipsychotics. Those with lengthy exposure to antipsychotics were at higher risk of developing incident neurological/sensory symptoms. Those treated with concomitant antipsychotic agents were at higher risk of developing somatic problems, and digestive/urogenital conditions. CONCLUSION: Pediatric exposure to antipsychotic polypharmacotherapy confers a higher risk of developing adverse events than monotherapy, especially for females.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".