Evidence map›Paper›PMID 24727466›Full record

ArticleEpilepsy & behavior : E&B2014

Diagnostic accuracy of microEEG: a miniature, wireless EEG device.

Arthur C Grant, Samah G Abdel-Baki, Ahmet Omurtag, Richard Sinert, Geetha Chari, Schweta Malhotra, Jeremy Weedon, Andre A Fenton, Shahriar Zehtabchi

Open access · greenAbstract readEvaluation Study
In one paragraph

Article in Epilepsy & behavior : E&B, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

23 citing papers in PubMed, 41 citations in OpenAlex.

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  14. Seizure detection: do current devices work? And when can they be useful?Current neurology and neuroscience reports · 2018
    Review
  15. Cognitive Behavior Classification From Scalp EEG Signals.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018
    Article
  16. Article
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  18. Article
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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 2 institutions in 1 country.

Arthur C GrantDepartment of Neurology, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA; Department of Physiology and Pharmacology, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA. Electronic address: arthur.grant@downstate.edu.
Samah G Abdel-BakiBio-Signal Group Corporation, Brooklyn, NY 11226, USA.
Ahmet OmurtagBio-Signal Group Corporation, Brooklyn, NY 11226, USA.
Richard SinertDepartment of Emergency Medicine, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA.
Geetha ChariDepartment of Neurology, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA.
Schweta MalhotraDepartment of Emergency Medicine, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA.
Jeremy WeedonThe Scientific Computing Center, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA.
Andre A FentonDepartment of Physiology and Pharmacology, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA; Center for Neural Science, New York University, New York, NY 10003, USA.
Shahriar ZehtabchiDepartment of Emergency Medicine, SUNY Downstate Medical Center, Brooklyn, NY 11203, USA.
SUNY Downstate Health Sciences University · USBio Signal Group (United States) · US

Funding

Putting EEG in the Emergency DepartmentRC3NS070658 · NINDS · BIO-SIGNAL GROUP CORPORATION · PI FENTON, ANDRE ANTONIO, OMURTAG, AHMET · 2010 to 2010
$2.9M
NINDS NIH HHS 1RC3NS070658NINDS NIH HHS RC3 NS070658
6 · The paper itself

Abstract

Measuring the diagnostic accuracy (DA) of an EEG device is unconventional and complicated by imperfect interrater reliability. We sought to compare the DA of a miniature, wireless, battery-powered EEG device ("microEEG") to a reference EEG machine in emergency department (ED) patients with altered mental status (AMS). Two hundred twenty-five ED patients with AMS underwent 3 EEGs. Two EEGs, EEG1 (Nicolet Monitor, "reference") and EEG2 (microEEG) were recorded simultaneously with EEG cup electrodes using a signal splitter. The remaining study, EEG3, was recorded with microEEG using an electrode cap immediately before or after EEG1/EEG2. The official EEG1 interpretation was considered the gold standard (EEG1-GS). EEG1, 2, and 3 were de-identified and blindly interpreted by two independent readers. A generalized mixed linear model was used to estimate the sensitivity and specificity of these interpretations relative to EEG1-GS and to compute a diagnostic odds ratio (DOR). Seventy-nine percent of EEG1-GS were abnormal. Neither the DOR nor the κf representing interrater reliabilities differed significantly between EEG1, EEG2, and EEG3. The mean setup time was 27 min for EEG1/EEG2 and 12 min for EEG3. The mean electrode impedance of EEG3 recordings was 12.6 kΩ (SD: 31.9 kΩ). The diagnostic accuracy of microEEG was comparable to that of the reference system and was not reduced when the EEG electrodes had high and unbalanced impedances. A common practice with many scientific instruments, measurement of EEG device DA provides an independent and quantitative assessment of device performance.

Indexed as

ElectroencephalographyFemaleHumansMaleProspective StudiesReproducibility of ResultsSeizuresSensitivity and SpecificityAltered mental statusDiagnostic accuracyEEGSensitivity and specificity

Identifiers

PMID24727466
PMCPMC4056592
OpenAlexW1967792486

What OpenQuestion holds

Textmetadata
LicenceTDM
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.