Factors Associated With Delirium Severity Among Older Persons With Dementia
Bibliographic record
Abstract
Delirium is a common cause of functional and cognitive decline, morbidity, and mortality among hospitalized elderly individuals. Several studies reveal that the prognosis of delirium is worse among elderly individuals with severe delirium. In light of these findings, it is important to identify which factors are associated with delirium severity: individual (predisposing) or environmental (precipitating) factors. This study wanted to investigate individual and environmental factors associated with delirium severity among older persons with delirium superimposed on dementia. This study is a secondary analysis of a cross-sectional study (N = 71) on delirium carried out in three long-term care facilities and one long-term care unit of a large regional hospital. Of the 29 potential risk factors considered, researchers found 6 to be significantly associated with delirium severity in univariate analysis: marital status (being married), severity of dementia, lower functional autonomy, less medication consumption, presence of behavioral problems, and inadequacy of the physical environment. In multivariate analysis, only marital status (being married) and severity of dementia remained statistically associated with delirium severity. Results of this study provide further evidence that the weakened brain functions of persons with dementia increases not only the risk of delirium but also its severity. Given the poor outcomes associated with delirium severity, nurses need to pay closer attention to the predisposing and precipitating factors of delirium severity.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".