Evidence mapPaperPMID 41998712Full record

ReviewCritical care (London, England)2026

EEG for bedside monitoring: the intensivist's point of view.

Fabio Silvio Taccone, Taylan Ozkaya, Marta Baggiani, Frank A Rasulo

Abstract readReview
In one paragraph

Review in Critical care (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Fabio Silvio TacconeDepartment of Intensive Care, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles (ULB), Route de Lennik, 808, Brussels, 1070, Belgium. fabio.taccone@ulb.be.
Taylan OzkayaDepartment of Intensive Care, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles (ULB), Route de Lennik, 808, Brussels, 1070, Belgium.
Marta BaggianiAnesthesiology and Intensive Therapy, San Gerardo Hospital, Monza, Italy.
Frank A RasuloDepartment of Anesthesiology and Intensive Care, University of Brescia, Brescia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electroencephalography (EEG) is a powerful tool that can provide unique and real time insight into cerebral functioning in the context of acute brain injury in the intensive care unit (ICU), ranging from focal deficits to seizures and coma. Despite being a safe, relatively inexpensive, non-invasive and meaningful tool, EEG has not yet transitioned into a true bedside monitoring system in the ICU, as continuous EEG monitoring cannot realistically be provided to all ICU patients, and EEG implementation and interpretation remains heavily dependent on specialized personnel. In order to integrate EEG into routine ICU monitoring, two conditions must be fulfilled: first, the EEG montage should be adjusted to answer the specific clinical question; second, the presentation of EEG-derived information must be stratified and adapted to the healthcare professional interpreting it, from the inexperienced nurses and junior physicians to the experienced neurophysiologist. Integrating the EEG into the multimodal monitoring of critically ill patients would allow earlier detection of reversible brain insults, it would promote brain monitoring across different levels of expertise, and it could potentially expand EEG use with rapid data acquisition that could facilitate early identification and treatment of acute brain events, even outside the ICU.

Indexed as

ElectroencephalographyPoint-of-Care SystemsBrain InjuriesHumansIntensive Care UnitsMonitoring, PhysiologicBrain injuryEEGIntensive CareNeuromonitoringNon-invasive

Identifiers

PMID41998712
PMCPMC13097847

What Socratic holds

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LicenceCC BY-NC-ND
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 Socratic graph.