Metabolic side effects of atypical antipsychotics in children: a literature review
Bibliographic record
Abstract
The objective of this review is to summarize the data about metabolic side effects of atypical antipsychotics in children. Original research articles about side effects of atypical antipsychotics used in children were reviewed. The data was obtained mainly through Medline searches, identifying articles focusing on the use of atypical antipsychotics in children. Forty studies that addressed the issue of metabolic side effects were selected. The use of atypical antipsychotics in children has been consistently associated with weight gain and moderate prolactin elevation, while only a few case reports address the issue of glucose dysregulation and dyslipidaemia. The risk of weight gain and hyperprolactinaemia might be higher in younger children. Other risk factors have also been associated with antipsychotic-induced metabolic disturbances. These changes seem to be reversible, at least in some cases. Metabolic side effects of atypical antipsychotics could lead to serious complications in children who are prescribed these medications. Serious considerations should be given before initiating treatment and consistent clinical monitoring is essential. More research is needed, especially regarding glucose dysregulation and dyslipidaemia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".