Methylphenidate as Treatment for Clozapine-Induced Sedation in Patients with Treatment-Resistant Schizophrenia
Bibliographic record
Abstract
BACKGROUND: Treatment-resistant schizophrenia patients frequently need to be managed with clozapine. However, noncompliance is in-part due to complaints of sedation, fatigue, and low energy. There is little literature reporting on the effectiveness and safety of using stimulants to treat clozapine-induced sedation. We report three cases of treatment-resistant schizophrenia where methylphenidate was used to address these common side-effects. METHODS: To evaluate the effectiveness and safety of psychostimulants in treatment-resistant schizophrenia, we reviewed 3 extensively documented cases of clozapine-induced sedation treated with methylphenidate for over 2 years, in addition to reviewing the literature on this topic. RESULTS: All 3 patients reported improvements in energy and fatigue, along with decreased sedation, while treated with methylphenidate for 27, 30, and 32 months respectively. Clozapine doses ranged between 325mg and 500mg daily; methylphenidate doses ranged between 2.5mg of the immediate-release and 72mg daily of the extended-release formulation. There was no reported or observed increase in psychotic symptoms resulting from treatment with methylphenidate. CONCLUSION: Methylphenidate may be safe and effective in the management of clozapine-induced sedation in treatment-resistant schizophrenia. Large scale, placebo-controlled, double-blind trials are needed to further validate the safety and efficacy of methylphenidate as treatment for clozapine-induced sedation.
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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 | 0.001 |
| 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 | 0.001 | 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".