Antipsychotic prescription patterns in the management of delirium symptoms in hospitalized elderly patients
Bibliographic record
Abstract
Objective: The objective of this study was to study the pharmacological management of delirium in elderly hospitalized patients in acute geriatric medical wards. Method: We conducted a one-year retrospective cross-sectional study in patients 65 years of age or older who were admitted to an acute geriatric unit care at a teaching hospital with a delirium diagnosis. Results: A total of 133 subjects were included in the study. Delirium was prevalent in 78% of patients. The average length of delirium was 13 days. Antipsychotics were prescribed to 74% of patients with delirium. Patients with hyperactive, mixed and hypoactive delirium received antipsychotics regularly in a proportion of 68%, 54%, and 34% respectively. The length of antipsychotic prescription was of 11 days. Risperidone was the most commonly prescribed agent given on a regular basis while haloperidol was chosen for the as required prescriptions. Fifty-five percent of demented patients received a daily prescription of antipsychotics compared to 46% in the non-demented population. A shorter length of delirium episodes in subjects with acetylcholinesterase inhibitors was also observed. A higher mortality rate was observed in the group of subjects receiving benzodiazepine during the delirium episode. Conclusion: This study shows that antipsychotic treatment is widely, but not systematically prescribed in demented and non-demented patients in all types of delirium including hypoactive. Efforts should be made to increase appropriate antipsychotic prescription in this vulnerable population.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".