Relationship between delirium and behavioral symptoms of dementia
Bibliographic record
Abstract
BACKGROUND: Persons with dementia frequently present behavioral and psychological symptoms as well as delirium. However, the association between these has received little attention from researchers and current knowledge in this area is limited. The purpose of this study was to examine the relation between delirium and behavioral symptoms of dementia (BSD). METHODS: Participants were 155 persons with a diagnosis of dementia, 109 (70.3%) of whom were found delirious according to the Confusion Assessment Method. BSD were assessed using the Nursing Home Behavior Problem Scale. RESULTS: Participants with delirium presented significantly more BSD than participants without delirium. More specifically, they presented more wandering/trying to leave, sleep problems, and irrational behavior after controlling for cognitive problems and use of antipsychotics and benzodiazepines. Most relationships between participant characteristics and BSD did not differ according to the presence or absence of delirium, but some variables, notably sleep problems, were more strongly associated to BSD in persons with delirium. CONCLUSIONS: Although correlates of BSD in persons with delirium superimposed on dementia are generally similar to those in persons with dementia alone, delirium is associated with a higher level of BSD. Results of this study have practical implications for the detection of delirium superimposed on dementia, the management of behavioral disturbances in patients with delirium, and caregiver burden.
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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 | 0.007 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".