Evidence map›Paper›PMID 32034656›Full record

ArticleNeurocritical care2020

Diagnostic Value of Electroencephalography with Ten Electrodes in Critically Ill Patients.

M Brandon Westover, Kapil Gururangan, Matthew S Markert, Benjamin N Blond, Saien Lai, Shawna Benard, Stephan Bickel, Lawrence J Hirsch, Josef Parvizi

Open access · hybridAbstract read
In one paragraph

Article in Neurocritical care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 5% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Nurses: The Missing Link in Continuous EEG Monitoring?Neurology. Clinical practice · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Detecting Seizures and Epileptiform Abnormalities in Acute Brain Injury.Current neurology and neuroscience reports · 2020
    Review
  17. Article
  18. Article
  19. 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

9 authors at 8 institutions in 1 country.

M Brandon WestoverDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA. mwestover@mgh.harvard.edu.
Kapil GururanganThe Mount Sinai Hospital, New York, NY, USA.
Matthew S MarkertStanford University Medical Center, Stanford, CA, USA.
Benjamin N BlondStony Brook University Hospital, Stony Brook, NY, USA.
Saien LaiKaiser Permanente Medical Center, Panorama City, CA, USA.
Shawna BenardKeck Hospital of University of Southern California, Los Angeles, CA, USA.
Stephan BickelZucker School of Medicine at Hofstra/Northwell, Long Island, NY, USA.
Lawrence J HirschYale-New Haven Hospital, New Haven, CT, USA.
Josef ParviziStanford University Medical Center, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-8520-7948
Stanford Medicine · USHofstra University · USKaiser Permanente · USMassachusetts General Hospital · USMount Sinai Hospital · USStony Brook University Hospital · USUniversity of Southern California · USYale New Haven Hospital · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Investigation of Sleep in the Intensive Care Unit (ICU-SLEEP)R01NS102190 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$3.2M
Big Data and Deep Learning for the Interictal-Ictal-Injury ContiuumR01NS107291 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$2.8M
NCATS NIH HHS UL1 TR001863NINDS NIH HHS R01 NS102190NINDS NIH HHS R01 NS107291
6 · The paper itself

Abstract

backgroundIn critical care settings, electroencephalography (EEG) with reduced number of electrodes (reduced montage EEG, rm-EEG) might be a timely alternative to the conventional full montage EEG (fm-EEG). However, past studies have reported variable accuracies for detecting seizures using rm-EEG. We hypothesized that the past studies did not distinguish between differences in sensitivity from differences in classification of EEG patterns by different readers. The goal of the present study was to revisit the diagnostic value of rm-EEG when confounding issues are accounted for.

methodsWe retrospectively collected 212 adult EEGs recorded at Massachusetts General Hospital and reviewed by two epileptologists with access to clinical, trending, and video information. In Phase I of the study, we re-configured the first 4 h of the EEGs in lateral circumferential montage with ten electrodes and asked new readers to interpret the EEGs without access to any other ancillary information. We compared their rating to the reading of hospital clinicians with access to ancillary information. In Phase II, we measured the accuracy of the same raters reading representative samples of the discordant EEGs in full and reduced configurations presented randomly by comparing their performance to majority consensus as the gold standard.

resultsOf the 95 EEGs without seizures in the selected fm-EEG, readers of rm-EEG identified 92 cases (97%) as having no seizure activity. Of 117 EEGs with "seizures" identified in the selected fm-EEG, none of the cases was labeled as normal on rm-EEG. Readers of rm-EEG reported pathological activity in 100% of cases, but labeled them as seizures (N = 77), rhythmic or periodic patterns (N = 24), epileptiform spikes (N = 7), or burst suppression (N = 6). When the same raters read representative epochs of the discordant EEG cases (N = 43) in both fm-EEG and rm-EEG configurations, we found high concordance (95%) and intra-rater agreement (93%) between fm-EEG and rm-EEG diagnoses.

conclusionsReduced EEG with ten electrodes in circumferential configuration preserves key features of the traditional EEG system. Discrepancies between rm-EEG and fm-EEG as reported in some of the past studies can be in part due to methodological factors such as choice of gold standard diagnosis, asymmetric access to ancillary clinical information, and inter-rater variability rather than detection failure of rm-EEG as a result of electrode reduction per se.

Indexed as

Critical IllnessElectroencephalographyAdultElectrodesHumansRetrospective StudiesSeizuresAbbreviated EEGContinuous EEG monitoringElectroencephalography (EEG)NeuroemergenciesNon-convulsive status epilepticusSeizure prediction

Identifiers

PMID32034656
PMCPMC7416437
OpenAlexW3004912526

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.