Inpatient Treatment of Severe Disruptive Behaviour Disorders with Risperidone and Milieu Therapy
Bibliographic record
Abstract
OBJECTIVES: To evaluate the therapeutic impact of adding risperidone to milieu therapy of latency-aged inpatients with severe disruptive disorders. METHODS: The charts of 90 latency-aged patients consecutively admitted to a psychiatry ward were reviewed retrospectively. Fifteen of these patients received risperidone treatment, were nonpsychotic, and did not suffer from pervasive developmental disorder (12 male, 3 female; mean age 9.99 years, SD 1.76). Their scores on the Children's Global Assessment Scale (CGAS) were compared at admission, before risperidone treatment, and at discharge. RESULTS: All subjects were diagnosed with a disruptive behavioural disorder. Ten (66.67%) had additional learning difficulties, and 13 (86.7%) had pathological personality traits. The characteristics of the sample suggested borderline pathology or multiple complex developmental disorder. Following a mean of 38 days after admission (SD 22.3), the patients received risperidone for a mean of 46 days (SD 28.2) before being discharged. The mean maintenance dose of risperidone was 1.27 mg daily (SD 0.36). Mean CGAS scores increased from admission (21.9, SD 7.0) to before risperidone treatment (26.8, SD 7.6, P < 0.0001) and to discharge (50.3, SD 5.3, P < 0.0001). Only 2 patients had documented side effects. CONCLUSIONS: Low-dose risperidone used adjunctively to milieu therapy led to statistically and clinically significant additional improvement in the functioning of hospitalized latency-aged children with severe behavioural disorders. Low-dose risperidone is a safe and effective adjunct to milieu therapy for treating this population in inpatient settings. Prospective randomized controlled trials are needed to confirm these findings.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".