Agitation management strategies for older adults in the emergency department or with emergency medical services: A scoping review
Bibliographic record
Abstract
BACKGROUND: Agitation is common in the emergency department (ED) and with emergency medical services (EMS), which can pose significant challenges to safety and patient care. In older adults, agitation is a common symptom of dementia or delirium. RATIONALE: Managing agitation in older adults is challenging in emergency care environments. A scoping review of literature for agitation management approaches for older adults in ED/EMS environments was completed. METHODS: We searched Medline, Embase, and APA PsycINFO, combining key words and subject headings for 3 concepts: "older adults, aged 65 and older," "agitation/dementia/delirium," and "ED/EMS." Studies which explored management strategies for older adults with agitation, dementia, or delirium in the ED or EMS were included. Studies with younger populations (<65 years old) and/or lacking patient data specifically from the ED or EMS were excluded. RESULTS: A total of 7113 studies were screened, of which 22 were included in this review: pharmacological (n = 8), non-pharmacological (n = 5), multi-component (n = 3) treatments, and recommendations (n = 6). Most were in the ED, and 5038 older adults were included across all studies. Antipsychotics and benzodiazepines to manage agitation were common. Non-pharmacological and multi-component interventions were less commonly evaluated and lacked exploration of patient outcomes. Recommendations stressed caution with pharmacological medications rather than prioritizing non-restraint strategies. DISCUSSION: Most studies identified use of pharmacological treatment for agitation amongst older adults in ED/EMS settings, however, are not found to be overly effective and are associated with patient harm. There is a significant gap in evidence specific to EMS settings and evaluation of effectiveness of non-pharmacological interventions, highlighting the need for further research.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".