Evidence map›Paper›PMID 41994213›Full record

ArticleResuscitation plus2026

Changes in diagnostic and care trajectories following use of continuous EEG monitoring for neuroprognostication after out of hospital cardiac arrest - a before-and-after study.

Luuk Wieske, Jeroen Hoogland, Ineke van de Pol, Anna J Court, Vera Lagerburg, Laurien L Teunissen, Mirjam Datema, Jolande van Helden, Hazra S Moeniralam, Lea M Dijksman and 3 more

Abstract read
In one paragraph

Article in Resuscitation plus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Luuk WieskeDepartment of Clinical Neurophysiology, St. Antonius Hospital, Nieuwegein, the Netherlands.
Jeroen HooglandDepartment of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
Ineke van de PolDepartment of Intensive Care, St. Antonius Hospital, Nieuwegein, the Netherlands.
Anna J CourtDepartment of Clinical Neurophysiology, St. Antonius Hospital, Nieuwegein, the Netherlands.
Vera LagerburgDepartment of Medical Physics and Instrumentation, St. Antonius Hospital, Nieuwegein, the Netherlands.
Laurien L TeunissenDepartment of Clinical Neurophysiology, St. Antonius Hospital, Nieuwegein, the Netherlands.
Mirjam DatemaDepartment of Clinical Neurophysiology, St. Antonius Hospital, Nieuwegein, the Netherlands.
Jolande van HeldenDepartment of Intensive Care, St. Antonius Hospital, Nieuwegein, the Netherlands.
Hazra S MoeniralamDepartment of Intensive Care, St. Antonius Hospital, Nieuwegein, the Netherlands.
Lea M DijksmanDepartment of Value Based Health Care, St. Antonius Hospital, Nieuwegein, the Netherlands.
Erik ScholtenDepartment of Intensive Care, St. Antonius Hospital, Nieuwegein, the Netherlands.
Antje A SeeberDepartment of Clinical Neurophysiology, St. Antonius Hospital, Nieuwegein, the Netherlands.
Mariska M G LeeflangDepartment of Neurology and Clinical Neurophysiology, Amsterdam University Medical Centers, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Continuous electro-encephalography (cEEG) has been added to multimodal protocols to improve neurological prognostication in patients after cardiac arrest. Our aim was to investigate the impact of adding cEEG on diagnostic and care trajectories in clinical practice. Methods: Before-and-after study of patients after out of hospital cardiac arrest admitted in 2013-2024 to the intensive care unit in the Netherlands. Data on diagnostic and care trajectories and costs associated with prognostication were compared between patients admitted from 2013 to 2019, when cEEG was not used to predict the neurological prognosis, and patients admitted from 2019 to 2024, when cEEG was used. Results: 581 patients were included; 355 when cEEG was not used for neuroprognostication and 226 when cEEG was used. cEEG patterns associated with a poor prognosis were found in 18% of patients; cEEG patterns associated with a good prognosis in 24%. When cEEG was used, the neurologic outcome (either good or poor) could be predicted in an additional 23% of patients (95% CI: 16-31%). ICU length of stay did not change when cEEG was used (adjusted estimate: 1% increase in days; 95% CI: -23% to 32%) nor did overall survival (adjusted hazard ratio: 0.93; 95% CI: 0.68-1.27). Overall costs did not differ (estimated difference €1040; 95% CI: -4672 to 7078). Conclusion: Use of cEEG increased the number of patients in whom the neurological prognosis after out of hospital cardiac arrest could be predicted correctly. We did not observe changes in subsequent care trajectories although this may have been influenced by self-fulfilling prophecies and/or incorporation bias.

Indexed as

Cardiac arrestDiagnostic accuracyEEGNeurological prognosis

Identifiers

PMID41994213
PMCPMC13080491

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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.