ReviewCurrent emergency and hospital medicine reports2021
Succinct Approach to Delirium in the Emergency Department.
Review in Current emergency and hospital medicine reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- GRADE-Based Clinical Practice Guidelines for Emergency Department Delirium Risk Stratification, Screening, and Brain Imaging in Older Patients With Suspected Delirium.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2026Guideline
- Targeted Delirium Screening in At-risk Older Adults in the Emergency Department Improves Screening Rates.Journal of the American College of Emergency Physicians open · 2026Article
- Pharmacological Management of Delirium in Older Adults in the Emergency Department: Clinical Outcomes.Diseases (Basel, Switzerland) · 2026Article
- An Outcome Comparison Between Geriatric and Nongeriatric Emergency Departments.Annals of emergency medicine · 2023Observational
- A Lethal Combination of Delirium and Overcrowding in the Emergency Department.Journal of clinical medicine · 2023Review
- Evaluating the performance of machine learning methods for risk estimation of delirium in patients hospitalized from the emergency department.Acta psychiatrica Scandinavica · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
purpose of reviewThis study aims to provide a concise delirium review for practicing emergency medicine providers using the Assess, Diagnose, Evaluate, Prevent, and Treat (ADEPT) framework. RECENT
findingsDelirium is a form of acute brain dysfunction that results in significant mortality and morbidity for older emergency department (ED) patients. Delirium is frequently missed by healthcare providers, but monitoring for this syndrome using brief delirium assessments may improve recognition. Once delirium is diagnosed, emergency medicine providers' primary goal is to perform a comprehensive history and physical examination to uncover the underlying etiology for delirium. This includes obtaining history from a collateral historian and obtaining an accurate medication history. If posssible, emergency physicians (EPs) should treat the medical etiology that precipitated the delirium. If agitated, non-pharmacologic interventions such that minimize the use of tethers are preferred. Pharmacologic agents such as antipsychotic medications should be used as a last resort. SUMMARY: Delirium is a common geriatric emergency and requires the EP to assess, diagnose, evaluate, prevent, and treat. Delirium is a key geriatric syndrome that geriatric ED providers should routinely screen for. A strong emphasis is on the widespread use of delirium screening, followed by prevention and treatment efforts.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.