Clinical characteristics associated with the onset of delirium among long-term nursing home residents
Bibliographic record
Abstract
Abstract Background Nursing home residents are frail, have multiple medical comorbidities, and are at high risk for delirium. Most of the existing evidence base on delirium is derived from studies in the acute in-patient population. We examine the association between clinical characteristics and medication use with the incidence of delirium during the nursing home stay. Methods This is a retrospective cohort study of 1571 residents from 12 nursing homes operated by a single care provider in Ontario, Canada. Residents were over the age of 55 and admitted between February 2010 and December 2015 with no baseline delirium and a minimum stay of 180 days. Residents with moderate or worse cognitive impairment at baseline were excluded. The baseline and follow-up characteristics of residents were collected from the Resident Assessment Instrument-Minimal Data Set 2.0 completed at admission and repeated quarterly until death or discharge. Multivariate logistic regression was used to identify characteristics and medication use associated with the onset of delirium. Results The incidence of delirium was 40.4% over the nursing home stay (mean LOS: 32 months). A diagnosis of dementia (OR: 2.54, p < .001), the presence of pain (OR: 1.64, p < .001), and the use of antipsychotics (OR: 1.87, p < .001) were significantly associated with the onset of delirium. Compared to residents who did not develop delirium, residents who developed a delirium had a greater increase in the use of antipsychotics and antidepressants over the nursing home stay. Conclusions Dementia, the presence of pain, and the use of antipsychotics were associated with the onset of delirium. Pain monitoring and treatment may be important to decrease delirium in nursing homes. Future studies are necessary to examine the prescribing patterns in nursing homes and their association with delirium.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.160 | 0.001 |
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".