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Specific EEG Encephalopathy Pattern in SARS-CoV-2 Patients.

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Quantified electroencephalography (qEEG) identified distinct brainwave patterns in COVID-19 patients with encephalopathy. These findings aid in diagnosing this neurological condition in post-ICU survivors.

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Area of Science:

  • Neuroscience
  • Critical Care Medicine
  • Medical Imaging

Background:

  • Severe COVID-19 illness can lead to encephalopathy, a brain dysfunction.
  • Objective diagnostic markers for COVID-19-associated encephalopathy are needed.
  • Quantified electroencephalography (qEEG) offers a potential method for characterizing neurological changes.

Purpose of the Study:

  • To define the specific electroencephalography (EEG) features of encephalopathy in patients recovering from severe COVID-19.
  • To compare EEG findings in COVID-19 patients with those experiencing infectious toxic encephalopathy (ENC) or post-cardiorespiratory arrest (CRA) encephalopathy.
  • To identify objective EEG markers for diagnosing COVID-19-related encephalopathy.

Main Methods:

  • Utilized quantified electroencephalography (qEEG) on artifact-free EEG recordings from post-ICU COVID-19 patients.
  • Analyzed EEG data by calculating power spectrum for delta, theta, alpha, and beta bands across different brain lobes.
  • Computed Shannon's spectral entropy (SSE) and hemispheric connectivity using Pearson's correlation coefficient for comparison with ENC and CRA groups.

Main Results:

  • Visual EEG inspection of COVID-19 patients revealed near-physiological patterns with few anomalies.
  • EEG band distributions differed among COVID-19, ENC, and CRA groups, with COVID-19 findings falling between the other two.
  • COVID-19 patients exhibited distinct EEG band distributions in temporal lobes, higher SSE, and lower hemispheric connectivity compared to controls.

Conclusions:

  • Objective numerical EEG features were identified in severely ill COVID-19 patients.
  • These qEEG findings can aid in the positive diagnosis of COVID-19-associated encephalopathy.
  • The study provides a basis for utilizing qEEG in understanding and diagnosing neurological complications of COVID-19.