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Acta Neurológica Colombiana

Print version ISSN 0120-8748On-line version ISSN 2422-4022

Abstract

MANCILLA, Edwin Ebrat et al. Electroencephalographic findings compatible with encephalopathy in patients admitted for COVID-19. Acta Neurol Colomb. [online]. 2022, vol.38, n.3, pp.113-123.  Epub Oct 21, 2022. ISSN 0120-8748.  https://doi.org/10.22379/24224022416.

INTRODUCTION:

COVID-19 mainly affects the respiratory system; however, both direct and indirect involvement of the central and peripheral nervous system has also been described, causing a wide variety of neurological manifestations, with encephalopathy being one of the most frequently observed neurological manifestations.

OBJECTIVE:

With this article we intend to show the usefulness of vEEG in the diagnosis of encephalopathy in patients referred for COVID-19 who develop this neurological complication, as well as its value in determining the prognosis of these patients.

METHODS:

Retrospective observational study with 76 video-electroencephalograms of 41 patients with confirmed COVID-19 infection. The studies were performed during the months of March 2020 through June 2021. Disease severity, clinical and neurological features, pharmacological treatment and electroencephalographic indings were studied according to the degree of encephalopathy dysfunction these patients developed.

RESULTS:

Of the 41 patients, 12 (29 %) presented electroencephalographic signs of mild cerebral dysfunction, 15 (37 %) moderate cerebral dysfunction, and 14 (34 %) severe cerebral dysfunction, which were associated with higher mortality.

CONCLUSIONS:

In the 76 vEEG performed in the 41 patients admitted with encephalopathies associated with COVID-19 infection, no pattern different from that described in encephalopathies of other etiologies was observed. The vEEG was useful to confirm the clinical suspicion of brain dysfunction in patients with encephalopathies associated with COVID-19 infection and to assign a degree of severity, confirming its benefit as a diagnostic and prognostic biomarker.

Keywords : COVID-19; Electroencephalography (EEG); Encephalopathy (MeSH).

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