Antipsychotics in the Treatment of Delirium
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Antipsychotics are frequently used in the management of delirium, although there is limited information regarding the safety and efficacy of antipsychotics in treating delirium. The purpose of this study was to systematically evaluate the evidence for the efficacy and safety of antipsychotics in treating delirium. SOURCES: MEDLINE (July 1980 to July 2005) and Cochrane databases were searched for English language articles using keywords. STUDY SELECTION: Prospective studies with standardized criteria for diagnosing delirium and evaluating its severity. DATA SYNTHESIS: In total, 14 studies (9 single agent studies and 5 comparison trials) met inclusion criteria. Study medications included haloperidol, chlorpromazine, olanzapine, risperidone, and quetiapine. Improvements in delirium severity were reported with all of these antipsychotic medications. No study included a placebo comparison to account for spontaneous improvements in delirium. Other methodological limitations included inadequate blinding, randomization, and handling of participant withdrawals. The improvements in delirium tended to occur soon after initiation of treatment, and most of the studies examined used relatively low doses of antipsychotic medication. Serious adverse events attributable to antipsychotic medication were uncommon in studies, although side effects were not evaluated systematically in most studies. CONCLUSION: To date, there are no published double-blind, randomized, placebo-controlled trials to establish the efficacy or safety of any antipsychotic medication in the management of delirium. There is limited evidence from uncontrolled studies that supports the use of low-dose, short-term treatment of delirium with some antipsychotics. Further study with well-designed clinical trials is required in this area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it