Evidence map›Paper›PMID 30026951›Full record

ReviewJournal of intensive care2018

Continuous EEG monitoring in ICU.

Yuichi Kubota, Hidetoshi Nakamoto, Satoshi Egawa, Takakazu Kawamata

Open access · goldAbstract readReview
In one paragraph

Review in Journal of intensive care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
5.9field-weighted citation impact, top 3% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 68 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Using artificial intelligence to optimize anti-seizure treatment and EEG-guided decisions in severe brain injury.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025
    Review
  7. Review
  8. Article
  9. Continuous electroencephalography in the intensive care unit: A critical review and position statement from an Australian and New Zealand perspective.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Big data in status epilepticus.Epilepsy & behavior : E&B · 2019
    Review
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

4 authors at 2 institutions in 1 country.

Yuichi KubotaStroke and Epilepsy Center, TMG Asaka Medical Center, 1-1340 Mizonuma, Asaka, Saitama 351-8551 Japan.
Hidetoshi NakamotoStroke and Epilepsy Center, TMG Asaka Medical Center, 1-1340 Mizonuma, Asaka, Saitama 351-8551 Japan.
Satoshi EgawaNeurocritical Care Unit, TMG Asaka Medical Center, 1-1340 Mizonuma, Asaka, Saitama 351-8551 Japan.
Takakazu Kawamata3Department of Neurosurgery, Tokyo Women's Medical University, 8-1 Kawada cho, Shinjiku Tokyo, 162-8666 Japan.
Saitama Medical University · JPTokyo Women's Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundContinuous electroencephalogram (CEEG) monitoring is increasingly being used for brain monitoring in neurocritical care setting. This is because of the proven effectiveness of CEEG in diagnosing nonconvulsive status epilepticus (NCSE) as a cause of unexplained consciousness disorder. CEEG has been demonstrated to be effective in determining the response to, and outcome of, NCSE treatment. MAIN BODY: In this review article, the authors described the indication and methods of CEEG and diagnosis based on EEG pattern. As a condition characterized by unexplained consciousness disorder, NCSE is frequently encountered in the neurocritical care setting and is only accompanied by an altered EEG change without any clinically apparent manifestation, such as convulsion. Thus, it is considered a form of status epilepticus manifesting mainly with consciousness disorder. This is a diagnostic challenge but should not be overlooked as NCSE is a curable condition. However, CEEG is required for the correct diagnosis of NCSE, which is difficult to perform in daily clinical practice. There also are several challenges regarding urgent EEG monitoring in the intensive care unit setting, including system-related problems, such as the preparation of mobile EEG devices and collodion-applied electrodes; human resource-related problems, such as staffing of EEG technicians and physicians who can respond flexibly to unscheduled needs; and EEG-specific difficulties in interpretation/diagnosis. These issues preclude the wide spread of CEEG in daily practice.

conclusionRecently, importance of CEEG was well accepted; however, no definitive diagnostic criteria exist for identifying EEG patterns suggestive of NCSE, especially the ambiguous significance of periodic discharges (PDs) further complicates the diagnosis of NCSE. Thus, analyzing the change in EEG patterns over time is important for the correct diagnosis of NCSE. Further studies are needed to collect sufficient CEEG data and assess the outcome of patients who have undergone therapeutic interventions.

Indexed as

Continuous EEGNonconvulsive status epilepticus (NCSE)Periodic discharges (PDs)

Identifiers

PMID30026951
PMCPMC6050674
OpenAlexW2883991276

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.