Evidence map›Paper›PMID 41445613›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Surface EEG to identify cognitive motor dissociation after acute brain injury PREPRINT.

Satoshi Egawa, Nicole Casson, Joel Neves Briard, Qi Shen, Vedant Kansara, Itamar Niesvizky-Kogan, Elizabeth Carroll, Jerina C Carmona, You Lim Song, Alex J Klein and 8 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. 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

5 · Who and what money

Authors and funding

18 authors.

Satoshi EgawaDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Nicole CassonDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Joel Neves BriardDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.ORCID 0000-0002-1576-5669
Qi ShenDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Vedant KansaraDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Itamar Niesvizky-KoganDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Elizabeth CarrollDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Jerina C CarmonaDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
You Lim SongDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Alex J KleinDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.ORCID 0000-0002-4194-1996
Angela VelazquezDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Wells AndresDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.
Shivani GhoshalDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.ORCID 0000-0002-8283-197X
David RohDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.ORCID 0000-0003-1927-7686
Sachin AgarwalDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.ORCID 0000-0003-0559-9326
Soojin ParkDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.ORCID 0000-0002-3688-7307
E Sander ConnollyNewYork-Presbyterian Hospital, New York, NY, USA.ORCID 0000-0002-6877-3371
Jan ClaassenDepartment of Neurology, Columbia University Medical Center, New York, NY, USA.ORCID 0000-0002-5893-8531

Funding

RECONFIG - REcovery of CONsciousness Following Intracerebral hemorrhaGeR01NS106014 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CLAASSEN, JAN · 2019 to 2023
$3.6M
BAsIC - Brain-computer-interface practical Application in the Intensive Care unit: a pilot studyR03NS112760 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CLAASSEN, JAN · 2019 to 2020
$162k
NINDS NIH HHS R01 NS106014NINDS NIH HHS R03 NS112760
6 · The paper itself

Abstract

Objective: Cognitive motor dissociation (CMD) is associated with long-term recovery in acute brain injury, but CMD testing is only available in few centers. Our objective was to identify surface EEG patterns with high sensitivity or positive predictive value (PPV) for CMD in patients with acute disorders of consciousness to refine allocation of this resource-intensive test. Methods: In this observational cohort study, we enrolled clinically unresponsive, acutely brain injured patients who underwent continuous surface EEG and CMD assessments. CMD was detected by applying a machine learning algorithm to EEG acquired during a motor command paradigm presentation.Electroencephalographers blinded to CMD test results applied standardized ACNS criteria to the EEGs acquired during CMD assessments. We calculated accuracy measures of surface EEG findings for CMD test results using generalized estimating equations, with an exchangeable matrix and accounting for repeated measures per patient. Results: We included 185 patients (mean age: 62 ± 17; 85 [46%] female) and 282 CMD assessments. CMD testing was positive in 39 (14%) assessments. Sensitivity and PPV of normal background voltage, symmetry and continuity were respectively 77% (95%-CI: 60-88%) and 19% (95%-CI: 13-26%), 74% (95%-CI: 58-86%) and 14% (95%-CI: 10-20%), and 74% (95%-CI: 58-86%) and 14% (95%-CI: 9-19%). All EEGs with burst suppression, suppression, sporadic epileptiform discharges, lateralized periodic discharges, bilateral independent periodic discharges, electrographic seizures and brief potentially ictal rhythmic discharges had negative CMD tests. Interpretation: Surface EEG findings are not reliable to screen for CMD or to identify patterns conferring higher CMD pretest probability.

Indexed as

ACNS criteriaCMDcognitive motor dissociationcomacovert consciousnessEEG

Identifiers

PMID41445613
PMCPMC12723767

What OpenQuestion holds

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Registered trials

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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.