S'abonner

Rapid Electroencephalography and Artificial Intelligence in the Detection and Management of Nonconvulsive Seizures - 18/06/24

Doi : 10.1016/j.annemergmed.2024.04.026 
Chase Richard, MD, MBA , David Schriger, MD, MPH, Daniel Weingrow, DO
 Division of Emergency Medicine, the University of California Los Angeles, CA 

Corresponding Author.
Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Tuesday 18 June 2024
Cet article a été publié dans un numéro de la revue, cliquez ici pour y accéder

Abstract

Study objective

Nonconvulsive status epilepticus is a commonly overlooked cause of altered mental status. This study assessed nonconvulsive status epilepticus prevalence in emergency department (ED) patients with acute neurologic presentations using limited electroencephalogram (EEG) coupled with artificial intelligence (AI)-enhanced seizure detection technology. We then compared the accuracy of the AI EEG interpretations to those performed by an epileptologist.

Methods

In a prospective observational cohort analysis, adult patients with unexplained mental status changes identified by emergency physicians received expedited placement of a limited EEG. Data collected encompassed patient demographics, clinical history, EEG interpretations by the AI algorithm and epileptologists, treatments, and disposition determinations.

Results

There were 134 device applications on 132 patients (2 received the device twice) enrolled in the study, but 16 were missing data critical for identification or analysis and 9 did not meet the selection criteria. Of the 108 limited EEGs interpreted by an epileptologist, 69 were abnormal (diffuse slowing, highly epileptiform patterns, or spikes and sharps), 41 were normal, 5 were uninterpretable, and 3 captured episodes of seizure or status epilepticus. Limited EEG AI interpretation detected >90% seizure burden in 2 of 3 cases of seizure or status epilepticus as well as in 2 abnormal EEGs and 1 normal EEG, providing a sensitivity of 66.7% (95% confidence interval 9.4 to 99.2), a specificity of 97.0% (95% confidence interval 91.5 to 99.4), and a disease prevalence of 2.9%.

Conclusion

Limited AI-enhanced EEG can detect nonconvulsive status epilepticus in the ED; however, the technology tended to overestimate seizure burden in our cohort. This study found a lower nonconvulsive status epilepticus prevalence compared to prior literature reports.

Le texte complet de cet article est disponible en PDF.

Plan


 Please see page XX for the Editor’s Capsule Summary of this article.
 Supervising editor: William J. Meurer, MD, MS. Specific detailed information about possible conflict of interest for individual editors is available at editors.
 Author contributions: CR and DW conceived and designed the study. CR collected the data. The data analysis was performed by CR, DW, and DS. The manuscript was drafted by CR, DW, and DS. CR and DW take responsibility for the paper as a whole.
 Data sharing statement: The entire deidentified data set, data dictionary, and analytic code for this investigation are available on request from the date of article publication by contacting Chase Richard, MD, MBA, by email at crichard@mednet.ucla.edu.
 Authorship: All authors attest to meeting the four ICMJE.org authorship criteria: (1) Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND (2) Drafting the work or revising it critically for important intellectual content; AND (3) Final approval of the version to be published; AND (4) Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
 Funding and support: By Annals’ policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org/). The authors have stated that no such relationships exist. The authors report this article did not receive any outside funding or support.
 Presentation information: Preliminary data were presented as a poster presentation at the Society for Academic Emergency Medicine Conference in New Orleans, Louisiana on May 12, 2022.


© 2024  American College of Emergency Physicians. Publié par Elsevier Masson SAS. Tous droits réservés.
Ajouter à ma bibliothèque Retirer de ma bibliothèque Imprimer
Export

    Export citations

  • Fichier

  • Contenu

Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.

Déjà abonné à cette revue ?

Mon compte


Plateformes Elsevier Masson

Déclaration CNIL

EM-CONSULTE.COM est déclaré à la CNIL, déclaration n° 1286925.

En application de la loi nº78-17 du 6 janvier 1978 relative à l'informatique, aux fichiers et aux libertés, vous disposez des droits d'opposition (art.26 de la loi), d'accès (art.34 à 38 de la loi), et de rectification (art.36 de la loi) des données vous concernant. Ainsi, vous pouvez exiger que soient rectifiées, complétées, clarifiées, mises à jour ou effacées les informations vous concernant qui sont inexactes, incomplètes, équivoques, périmées ou dont la collecte ou l'utilisation ou la conservation est interdite.
Les informations personnelles concernant les visiteurs de notre site, y compris leur identité, sont confidentielles.
Le responsable du site s'engage sur l'honneur à respecter les conditions légales de confidentialité applicables en France et à ne pas divulguer ces informations à des tiers.


Tout le contenu de ce site: Copyright © 2024 Elsevier, ses concédants de licence et ses contributeurs. Tout les droits sont réservés, y compris ceux relatifs à l'exploration de textes et de données, a la formation en IA et aux technologies similaires. Pour tout contenu en libre accès, les conditions de licence Creative Commons s'appliquent.