Efficacy and Safety of Risperidone in Patients With Delirium
Bibliographic record
Abstract
BACKGROUND: The cornerstone treatment of delirium is to assess and treat its underlying causes and prevent further complications. Drug therapy may be necessary to control agitation and behavioral symptoms associated with delirium. The aim of this pilot study was to evaluate the feasibility of a randomized placebo controlled trial to evaluate the efficacy and safety of risperidone in the treatment of delirium. METHODS: This was a randomized double-blinded placebo-controlled trial. Patients were enrolled in the study if they were hospitalized and 65 years or older and had a diagnosis of delirium. Delirium Rating Scale revised 98 was used to determine delirium and motor agitation. RESULTS: A total of 14 participants with 57% being men and having a mean age of 86 years were included. There were no statistically significant differences between the risperidone and placebo group for the Delirium Rating Scale revised 98 score. There were no severe adverse reactions reported in the study, and no patients discontinued the study for adverse reactions. CONCLUSIONS: Risperidone at low doses (1 mg daily or less) was well tolerated for the treatment of delirium. Future large-scale trials are needed to evaluate the safety and efficacy of risperidone in the treatment of delirium. This pilot study taught us that the phase 2 RIsperDone DELirium trial will need a multicenter design with more research personnel to increase the number of participants enrolled.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".