Prolactin Levels During Long-Term Risperidone Treatment in Children and Adolescents
Bibliographic record
Abstract
BACKGROUND: This analysis was designed to investigate prolactin levels in children and adolescents on long-term risperidone treatment and explore any relationship with side effects hypothetically attributable to prolactin (SHAP). METHOD: Data from 5 clinical trials (total N = 700) were pooled for this post hoc analysis. Children and adolescents aged 5 to 15 years with subaverage intelligence quotients and conduct or other disruptive behavior disorders received risperidone treatment (0.02-0.06 mg/kg/day) for up to 55 weeks. Outcome measures analyzed included serum prolactin levels, reported adverse events, and the conduct problem subscore of the Nisonger Child Behavior Rating Form. RESULTS: Mean prolactin levels rose from 7.8 ng/mL at baseline to a peak of 29.4 ng/mL at weeks 4 to 7 of active treatment, then progressively decreased to 16.1 ng/mL at weeks 40 to 48 (N = 358) and 13.0 ng/mL at weeks 52 to 55 (N = 42). There was no relationship between pro-lactin levels and age. Females returned to a mean value within the normal range (</= 30 ng/mL) by weeks 8 to 12, and males were close to normal values (</= 18 ng/mL) by weeks 16 to 24. At least 1 SHAP was reported by 13 (2.2%) of 592 children. There was no direct correlation between prolactin elevation and SHAP. CONCLUSION: With long-term risperidone treatment in children and adolescents, serum prolactin levels tended to rise and peak within the first 1 to 2 months and then steadily decline to values within or very close to the normal range by 3 to 5 months.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".