The occurrence and timing of delirium in acute care hospitalizations in the last year of life: A population-based retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Delirium is a distressing neurocognitive disorder that is common among terminally ill individuals, although few studies have described its occurrence in the acute care setting among this population. AIM: To describe the prevalence of delirium in patients admitted to acute care hospitals in Ontario, Canada, in their last year of life and identify factors associated with delirium. DESIGN: Population-based retrospective cohort study using linked health administrative data. Delirium was identified through diagnosis codes on hospitalization records. SETTING/PARTICIPANTS: Ontario decedents (1 January 2014 to 31 December 2016) admitted to an acute care hospital in their last year of life, excluding individuals age of <18 years or >105 years at admission, those not eligible for the provincial health insurance plan between their hospitalization and death dates, and non-Ontario residents. RESULTS: Delirium was recorded as a diagnosis in 8.2% of hospitalizations. The frequency of delirium-related hospitalizations increased as death approached. Delirium prevalence was higher in patients with dementia (prevalence ratio: 1.43; 95% confidence interval: 1.36-1.50), frailty (prevalence ratio: 1.67; 95% confidence interval: 1.56-1.80), or organ failure-related cause of death (prevalence ratio: 1.23; 95% confidence interval: 1.16-1.31) and an opioid prescription (prevalence ratio: 1.17; 95% confidence interval: 1.12-1.21). Prevalence also varied by age, sex, chronic conditions, antipsychotic use, receipt of long-term care or home care, and hospitalization characteristics. CONCLUSION: This study described the occurrence and timing of delirium in acute care hospitals in the last year of life and identified factors associated with delirium. These findings can be used to support delirium prevention and early detection in the hospital setting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".