Evidence map›Paper›PMID 35277128›Full record

ArticleBMC neurology2022

Electroencephalography in delirium assessment: a scoping review.

Tim L T Wiegand, Jan Rémi, Konstantinos Dimitriadis

Registry-linked trialOpen access · goldAbstract readScoping Review
In one paragraph

Article in BMC neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05525702 (Effects of Multi-model Virtual Reality Intervention Method to Reduce the Prevalence of Delirium in ICU Patients With Mechanical Ventilation), which is not on this map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
7.9field-weighted citation impact, top 2% of its field
1 · What the graph read from 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.

2 · The registry

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.

NCT05525702 narecruitingnot on this mapstarted 2023, after this paper: background citation

Effects of Multi-model Virtual Reality Intervention Method to Reduce the Prevalence of Delirium in ICU Patients With Mechanical Ventilation

TypeinterventionalSponsorPeking Union Medical College HospitalRan2023 to 2026Enrolled102ConditionsDeliriumArmsVRFS
3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 54 citations in OpenAlex.

  1. Observational
  2. Video-based Detection of Delirium in Hospitalized Adults.medRxiv : the preprint server for health sciences · 2026
    Article
  3. Article
  4. Observational
  5. Article
  6. Review
  7. Observational
  8. Bedside EEG for rapid diagnosis of delirium.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
    Review
  9. Article
  10. Electrographic Features of Catatonia With or Without Comorbid Delirium.The Journal of neuropsychiatry and clinical neurosciences · 2026
    Article
  11. Review
  12. Observational
  13. Review
  14. Article
  15. Article
  16. Review
  17. Observational
  18. Article
  19. Article
  20. Investigating delirium in stroke with an EEG lens: Focal lesions with global impact?Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Tim L T WiegandcBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany.
Jan RémiDepartment of Neurology, University Hospital, Ludwig Maximilian University, 15 Marchioninistr, 81377, Munich, Germany.
Konstantinos DimitriadisDepartment of Neurology, University Hospital, Ludwig Maximilian University, 15 Marchioninistr, 81377, Munich, Germany. Konstantin.Dimitriadis@med.lmu.de.ORCID https://orcid.org/0000-0003-0417-2267
Ludwig-Maximilians-Universität München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDelirium is a common disorder affecting around 31% of patients in the intensive care unit (ICU). Delirium assessment scores such as the Confusion Assessment Method (CAM) are time-consuming, they cannot differentiate between different types of delirium and their etiologies, and they may have low sensitivities in the clinical setting. While today, electroencephalography (EEG) is increasingly being applied to delirious patients in the ICU, a lack of clear cut EEG signs, leads to inconsistent assessments.

methodsWe therefore conducted a scoping review on EEG findings in delirium. One thousand two hundred thirty-six articles identified through database search on PubMed and Embase were reviewed. Finally, 33 original articles were included in the synthesis.

resultsEEG seems to offer manifold possibilities in diagnosing delirium. All 33 studies showed a certain degree of qualitative or quantitative EEG alterations in delirium. Thus, normal routine (rEEG) and continuous EEG (cEEG) make presence of delirium very unlikely. All 33 studies used different research protocols to at least some extent. These include differences in time points, duration, conditions, and recording methods of EEG, as well as different patient populations, and diagnostic methods for delirium. Thus, a quantitative synthesis and common recommendations are so far elusive.

conclusionFuture studies should compare the different methods of EEG recording and evaluation to identify robust parameters for everyday use. Evidence for quantitative bi-electrode delirium detection based on increased relative delta power and decreased beta power is growing and should be further pursued. Additionally, EEG studies on the evolution of a delirium including patient outcomes are needed.

Indexed as

DeliriumElectroencephalographyHumansIntensive Care UnitsDeliriumDementiaEEGElectrophysiologyEpilepsyIntensive care

Identifiers

PMID35277128
PMCPMC8915483
OpenAlexW4220911244

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.