Management of Agitation in Dementia and Effects on Inpatient Length of Stay
Bibliographic record
Abstract
Background Agitation associated with dementia impacts delivery of medical care and is a major reason for institutionalization in dementia patients. This study examines the association of medication use and other clinical factors with patients’ ‘dischargeability’ (i.e., amount of time until a patient is considered dischargeable from an inpatient unit). Methods This study was a retrospective chart review examining 200 patients with dementia and agitation, hospitalized at a Canadian acute care geriatric ward between November 2007 and November 2018. The main outcome measure was time until a patient was deemed dischargeable. Univariate linear regression analyses, followed by multiple linear regression analyses, were used. Results Risperidone and quetiapine were the most commonly prescribed medications, but were not associated with time until dischargeable. Olanzapine (40.9 vs. 16.2 days until dischargeable, β = 0.23, p = .001), regular benzodiazepine (32.7 vs. 16.5 days until dischargeable, β = 0.15, p = .027), and as-needed (‘PRN’) benzodiazepine use (31.7 vs. 15.9 days until dischargeable, β =0.19, p = .006) were independently associated with prolonging time until dischargeable. Conclusions Olanzapine, benzodiazepine, and PRN benzodiazepine use were associated with longer time until patients with dementia and agitation were considered ready for discharge. This raises the question as to whether the risks of these medications outweigh the benefits in a 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 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".