A retrospective, exploratory, secondary analysis of the association between antipsychotic use and mortality in elderly patients with delirium
Bibliographic record
Abstract
BACKGROUND: Delirium, an acute altered level of cognition, is a frequent complication of medical illness in the elderly. Antipsychotic medications (APs) are often used to treat agitation and psychosis in delirium. The goal of this study is to compare mortality in delirious elderly medical inpatients treated with APs with those who did not receive APs. METHOD: 326 elderly hospitalized patients were identified with delirium at an acute care community hospital. A nested case-control analysis was conducted on this cohort. Cases consisted of all patients who died in hospital within eight weeks of admission. Each case was matched for age and severity of illness to patients (controls) alive on the same day post-admission. Conditional logistic regression was used to assess the impact of exposure to AP on mortality. Covariates used for adjustment were the Charlson comorbidity score and the acute physiology score. Odds ratio (OR) and 95% confidence intervals were calculated from the regression coefficients. RESULTS: 111 patients received an AP. A total of 62 patients died, 16 of whom were exposed to an AP. The OR of association between AP use and death was 1.53 (95% C.I, 0.83-2.80) in univariate and 1.61 (95% C.I, 0.88-2.96) in multivariate analysis. CONCLUSION: In elderly medical inpatients with delirium, administration of APs was not associated with a statistically significant increased risk of mortality. Larger studies are needed to clarify the safety of AP medication in elderly patients with delirium.
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 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 | 0.000 | 0.002 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".