[Not Available].
Bibliographic record
Abstract
BACKGROUND: Second-generation antipsychotics are commonly associated with metabolic complications. These medications are being used more frequently for the treatment of mental health disorders in children, which has stimulated the need for creating formal guidelines on monitoring their safety and effectiveness. Previous guidelines have been developed for monitoring metabolic and neurological complications. To assist practitioners who perform these monitoring procedures, a complementary set of treatment recommendations have been created for situations in which abnormal measurements or results are encountered. OBJECTIVE: To create evidence-based recommendations to assist in managing metabolic complications in children being treated with second-generation antipsychotics. METHODS: A systematic review of the literature on metabolic complications of second-generation antipsychotic medications in children was conducted. Members of the consensus group evaluated the information gathered from the systematic review of the literature and used a nominal group process to reach a consensus on treatment recommendations. Wherever possible, references were made to existing guidelines on the evaluation and treatment of metabolic abnormalities in children. RESULTS: Evidence-based recommendations are presented to assist in managing metabolic complications including weight gain; increased waist circumference; elevation in prolactin, cholesterol, triglyceride and glucose levels; abnormal liver function tests; and abnormal thyroid studies. CONCLUSION: The use of second-generation antipsychotics requires proper monitoring procedures. The present treatment guideline provides guidance to clinicians on the clinical management of metabolic complications if they occur.
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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 | 0.003 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.640 | 0.266 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".