Estimate of Patients With Missed Seizures Because of Delay in Conventional EEG.


Journal

Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society
ISSN: 1537-1603
Titre abrégé: J Clin Neurophysiol
Pays: United States
ID NLM: 8506708

Informations de publication

Date de publication:
01 Mar 2024
Historique:
medline: 4 3 2024
pubmed: 4 3 2024
entrez: 4 3 2024
Statut: ppublish

Résumé

There is frequent delay between ordering and placement of conventional EEG. Here we estimate how many patients had seizures during this delay. Two hundred fifty consecutive adult patients who underwent conventional EEG monitoring at the University of Wisconsin Hospital were retrospectively chart reviewed for demographics, time of EEG order, clinical and other EEG-related information. Patients were stratified by use of anti-seizure medications before EEG and into low-risk, medium-risk, and high-risk groups based on 2HELPS2B score (0, 1, or >1). Monte Carlo simulations (500 trials) were performed to estimate seizures during delay. The median delay from EEG order to performing EEG was 2.00 hours (range of 0.5-8.00 hours) in the total cohort. For EEGs ordered after-hours, it was 2.00 hours (range 0.5-8.00 hours), and during business hours, it was 2.00 hours (range 0.5-6.00 hours). The place of EEG, intensive care unit, emergency department, and general floor, did not show significant difference (P = 0.84). Anti-seizure medication did not affect time to first seizure in the low-risk (P = 0.37), medium-risk (P = 0.44), or high-risk (P = 0.12) groups. The estimated % of patients who had a seizure in the delay period for low-risk group (2HELPS2B = 0) was 0.8%, for the medium-risk group (2HELPS2B = 1) was 10.3%, and for the high-risk group (2HELPS2B > 1) was 17.6%, and overall risk was 7.2%. The University of Wisconsin Hospital with 24-hour in-house EEG technologists has a median delay of 2 hours from order to start of EEG, shorter than published reports from other centers. Nonetheless, seizures were likely missed in about 7.2% of patients.

Identifiants

pubmed: 38436390
doi: 10.1097/WNP.0000000000000957
pii: 00004691-202403000-00007
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

230-235

Informations de copyright

Copyright © 2022 by the American Clinical Neurophysiology Society.

Déclaration de conflit d'intérêts

The authors have no conflicts of interest to disclose.

Références

Ruiz AR, Vlachy J, Lee JW, et al. Association of periodic and rhythmic electroencephalographic patterns with seizures in critically ill patients. JAMA Neurol 2017;74:181–188.
Claassen J, Mayer SA, Kowalski RG, Emerson RG, Hirsch LJ. Detection of electrographic seizures with continuous EEG monitoring in critically ill patients. Neurology 2004;62:1743–1748.
Hill CE, Blank LJ, Thibault D, et al. Continuous EEG is associated with favorable hospitalization outcomes for critically ill patients. Neurology 2019;92:e9–18.
Treiman DM, Meyers PD, Walton NY, et al. A comparison of four treatments for generalized convulsive status epilepticus. NEJM 1998;339:792–798.
De Marchis GM, Pugin D, Meyers E, et al. Seizure burden in subarachnoid hemorrhage associated with functional and cognitive outcome. Neurology 2016;86:253–260.
Payne ET, Zhao XY, Frndova H, et al. Seizure burden is independently associated with short term outcome in critically ill children. Brain 2014;137:1429–1438.
Kull LL, Emerson RG. Continuous EEG monitoring in the intensive care unit: technical and staffing considerations. J Clin Neurophysiol 2005;22:107–118.
Westover MB, Shafi MM, Bianchi MT, et al. The probability of seizures during EEG monitoring in critically ill adults. Clin Neurophysiol 2015;126:463–471.
Sánchez Fernández I, Sansevere AJ, Guerriero RM, et al. Time to electroencephalography is independently associated with outcome in critically ill neonates and children. Epilepsia 2017;58:420–428.
Struck AF, Ustun B, Ruiz AR, et al. Association of an electroencephalography-based risk score with seizure probability in hospitalized patients. JAMA Neurol 2017;74:1419–1424.
Therneau TM, Lumley T. Package survival: survival analysis. Cham: CRAN; 2014. Available at: https://cran.r-project.org/web/packages/survival/survival.pdf.
Borgan Ø. Modeling survival data: Extending the cox model. Therneau TM, Grambsch PM. New York, NY: Springer‐Verlag, 2000. ISBN 0‐387‐98784‐3.
Fay MP, Shaw PA. Exact and asymptotic weighted logrank tests for interval censored data: the interval R package. J Stat Softw 2010;36:i02.
Yazbeck M, Sra P, Parvizi J. Rapid response electroencephalography for urgent evaluation of patients in community hospital intensive care practice. J Neurosci Nurs 2019;51:308–312.
Gururangan K, Razavi B, Parvizi J. Utility of electroencephalography: experience from a US tertiary care medical center. Clin Neurophysiol 2016;127:3335–3340.
Vespa PM, Olson DM, John S, et al. Evaluating the clinical impact of rapid response electroencephalography: the DECIDE multicenter prospective observational clinical study. Crit Care Med 2020;48:1249.
Hocker S, Nagarajan E, Rabinstein AA, Hanson D, Britton JW. Progressive brain atrophy in super-refractory status epilepticus. JAMA Neurol 2016;73:1201–1207.
Zafar SF, Postma EN, Biswal S, et al. Effect of epileptiform abnormality burden on neurologic outcome and antiepileptic drug management after subarachnoid hemorrhage. Clin Neurophysiol 2018;129:2219–2227.
Hirsch LJ, LaRoche SM, Gaspard N, et al. American clinical neurophysiology society's standardized critical care EEG terminology: 2012 version. J Clin Neurophysiol 2013;30:1–27.
Gaspard N, Hirsch LJ, LaRoche SM, Hahn CD, Westover MB. Critical care EEG monitoring research consortium. Interrater agreement for critical care EEG terminology. Epilepsia 2014;55:1366–1373.

Auteurs

Safoora Fatima (S)

Department of Neurology, University of Wisconsin-Madison, Wisconsin, U.S.A.; and.

Parimala Velpula Krishnamurthy (PV)

Department of Neurology, University of Wisconsin-Madison, Wisconsin, U.S.A.; and.

Mengzhen Sun (M)

Department of Neurology, University of Wisconsin-Madison, Wisconsin, U.S.A.; and.

Mariel Kalkach Aparicio (MK)

Department of Neurology, University of Wisconsin-Madison, Wisconsin, U.S.A.; and.

Klevest Gjini (K)

Department of Neurology, University of Wisconsin-Madison, Wisconsin, U.S.A.; and.

Aaron F Struck (AF)

Department of Neurology, University of Wisconsin-Madison, Wisconsin, U.S.A.; and.
William S Middleton Veterans Hospital, Madison, Wisconsin, U.S.A.

Classifications MeSH