Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.


Journal

Stroke
ISSN: 1524-4628
Titre abrégé: Stroke
Pays: United States
ID NLM: 0235266

Informations de publication

Date de publication:
11 2020
Historique:
pubmed: 19 9 2020
medline: 17 2 2021
entrez: 18 9 2020
Statut: ppublish

Résumé

Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility of electroencephalography for acute stroke/transient ischemic attack (TIA) and for LVO. Patients (n=100) with suspected acute stroke in an emergency department underwent clinical exam then electroencephalography using a dry-electrode system. Four models classified patients, first as acute stroke/TIA or not, then as acute stroke with LVO or not: (1) clinical data, (2) electroencephalography data, (3) clinical+electroencephalography data using logistic regression, and (4) clinical+electroencephalography data using a deep learning neural network. Each model used a training set of 60 randomly selected patients, then was validated in an independent cohort of 40 new patients. Of 100 patients, 63 had a stroke (43 ischemic/7 hemorrhagic) or TIA (13). For classifying patients as stroke/TIA or not, the clinical data model had area under the curve=62.3, whereas clinical+electroencephalography using deep learning neural network model had area under the curve=87.8. Results were comparable for classifying patients as stroke with LVO or not. Adding electroencephalography data to clinical measures improves diagnosis of acute stroke/TIA and of acute stroke with LVO. Rapid acquisition of dry-lead electroencephalography is feasible in the emergency department and merits prehospital evaluation.

Sections du résumé

BACKGROUND AND PURPOSE
Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility of electroencephalography for acute stroke/transient ischemic attack (TIA) and for LVO.
METHODS
Patients (n=100) with suspected acute stroke in an emergency department underwent clinical exam then electroencephalography using a dry-electrode system. Four models classified patients, first as acute stroke/TIA or not, then as acute stroke with LVO or not: (1) clinical data, (2) electroencephalography data, (3) clinical+electroencephalography data using logistic regression, and (4) clinical+electroencephalography data using a deep learning neural network. Each model used a training set of 60 randomly selected patients, then was validated in an independent cohort of 40 new patients.
RESULTS
Of 100 patients, 63 had a stroke (43 ischemic/7 hemorrhagic) or TIA (13). For classifying patients as stroke/TIA or not, the clinical data model had area under the curve=62.3, whereas clinical+electroencephalography using deep learning neural network model had area under the curve=87.8. Results were comparable for classifying patients as stroke with LVO or not.
CONCLUSIONS
Adding electroencephalography data to clinical measures improves diagnosis of acute stroke/TIA and of acute stroke with LVO. Rapid acquisition of dry-lead electroencephalography is feasible in the emergency department and merits prehospital evaluation.

Identifiants

pubmed: 32942967
doi: 10.1161/STROKEAHA.120.030150
pmc: PMC7606743
mid: NIHMS1625521
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

3361-3365

Subventions

Organisme : NCATS NIH HHS
ID : UL1 TR001414
Pays : United States

Références

Stroke. 1977 Jan-Feb;8(1):51-7
pubmed: 13521
Int J Stroke. 2019 Jul;14(5):530-539
pubmed: 30209989
Stroke. 2018 Mar;49(3):e111-e122
pubmed: 29367333
J Neural Eng. 2019 Sep 19;16(5):054001
pubmed: 31096191
Prehosp Emerg Care. 2018 Mar-Apr;22(2):180-188
pubmed: 29023166
Stroke. 2016 Jul;47(7):1772-6
pubmed: 27272487
Stat Med. 1997 Feb 28;16(4):385-95
pubmed: 9044528
Prehosp Emerg Care. 2019 Sep-Oct;23(5):612-618
pubmed: 30668202

Auteurs

Fareshte Erani (F)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Nadezhda Zolotova (N)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Benjamin Vanderschelden (B)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Nima Khoshab (N)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Hagop Sarian (H)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Laila Nazarzai (L)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Jennifer Wu (J)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Bharath Chakravarthy (B)

Department of Emergency Medicine (B.C., W.H.), UC Irvine, CA.

Wirachin Hoonpongsimanont (W)

Department of Emergency Medicine (B.C., W.H.), UC Irvine, CA.

Wengui Yu (W)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Babak Shahbaba (B)

Department of Statistics (B.S.), UC Irvine, CA.

Ramesh Srinivasan (R)

Department of Cognitive Science (R.S.), UC Irvine, CA.
Department of Biomedical Engineering (R.S.), UC Irvine, CA.

Steven C Cramer (SC)

Department of Neurology (F.E., N.Z., B.V., N.K., H.S., L.N., J.W., W.Y., S.C.C.), UC Irvine, CA.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH