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Related Experiment Video

Updated: Nov 8, 2025

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
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Alpha power decrease in quantitative EEG detects development of cerebral infarction after subarachnoid hemorrhage

Tamara M Mueller1, Stephanie Gollwitzer1, Rüdiger Hopfengärtner1

  • 1Department of Neurology, University Hospital Erlangen, Schwabachanlage 6, 91054 Erlangen, Germany.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology
|April 19, 2021
PubMed
Summary
This summary is machine-generated.

Quantitative electroencephalography (qEEG) effectively identifies patients at risk of cerebral infarction following subarachnoid hemorrhage. This non-invasive tool shows promise in predicting delayed cerebral ischemia better than transcranial Doppler/color-coded-duplex sonography (TCD/TCCS).

Keywords:
Delayed cerebral ischemiaQuantitative EEGSubarachnoid hemorrhageVasospasm

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Area of Science:

  • Neuroscience
  • Neurology
  • Medical Imaging

Background:

  • Subarachnoid hemorrhage (SAH) poses a risk for delayed cerebral ischemia (DCI).
  • Transcranial Doppler/color-coded-duplex sonography (TCD/TCCS) is a standard method for DCI detection.
  • Quantitative electroencephalography (qEEG) has also shown potential in predicting DCI.

Purpose of the Study:

  • To compare the efficacy of qEEG and TCD/TCCS in early identification of patients who will develop cerebral infarction after SAH.
  • To analyze the predictive capabilities of qEEG and TCD/TCCS for imminent DCI.

Main Methods:

  • Analysis of data from two previous qEEG studies involving continuous six-channel-EEG.
  • Definition of significant EEG events based on alpha power decline (≥40% for ≥5 hours).
  • Diagnosis of vasospasm using TCD/TCCS, measuring maximum frequency and duration.

Main Results:

  • A moderate correlation was found between TCD/TCCS frequencies and qEEG alpha power reduction (r=0.43, p=0.015).
  • qEEG parameters significantly differentiated patients with cerebral infarction from those without (p<0.05).
  • TCD/TCCS parameters did not show significant differences between patients with and without infarction.

Conclusions:

  • qEEG is a superior tool for differentiating patients with and without cerebral infarction post-SAH.
  • qEEG offers a non-invasive, continuous method for identifying patients at risk of cerebral infarction.
  • The findings suggest qEEG's utility in managing SAH patients to prevent cerebral infarction.