Treatment recommendations for extrapyramidal side effects associated with second-generation antipsychotic use in children and youth
Bibliographic record
Abstract
Antipsychotic use in children is increasing. The purpose of the present article was to provide guidance to clinicians on the clinical management of extrapyramidal side effects of second-generation antipsychotics. Published literature, key informant interviews, and discussions with panel members and stakeholder partners were used to identify key clinical areas of guidance and preferences on format for the present recommendations. Draft recommendations were presented to a guideline panel. Members of the guideline panel evaluated the information gathered from the systematic review of the literature and used a nominal group process to reach a consensus on treatment recommendations. A description of the neurological abnormalities commonly seen with antipsychotic medications is provided, as well as recommendations on how to examine and quantify these abnormalities. A stepwise approach to the management of neurological abnormalities is provided. Several different types of extrapyramidal symptoms can be seen secondary to antipsychotic use in children including neuroleptic-induced acute dystonia, neuroleptic-induced akathisia, neuroleptic-induced parkinsonism, neuroleptic-induced tardive dyskinesia, tardive dystonia and tardive akathisia, and withdrawal dyskinesias. The overwhelming majority of evidence on the treatment of antipsychotic-induced movement disorders comes from adult patients with schizophrenia. Given the scarcity of paediatric data, recommendations were made with reference to both the adult and paediatric literature. Given the limitations in the generalizability of data from adult subjects to children, these recommendations should be considered on the basis of expert opinion, rather than evidence based. Clinicians must be aware of the potential of second-generation antipsychotics to induce neurological side effects, and should exercise a high degree of vigilance when prescribing these medications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".