OBJECTIVE: We investigated the ability of quantitative electroencephalography (QEEG) measures in sub-acute stroke to assist monitoring or prognostication of stroke evolution. QEEG indices and National Institutes of Health Stroke Scale (NIHSS) scores were compared. METHODS: Ischaemic cortical stroke patients were studied. Resting, 62-channel EEG and NIHSS score were acquired at 49+/-3h post-symptom onset, and NIHSS administered at 30+/-2 days post-stroke. Mean power was calculated for delta (1-4 Hz), theta (4.1-8 Hz), alpha (8.1-12.5 Hz) and beta (12.6-30 Hz) frequency bands, using a 62-channel electrode array and a 19-channel subset. RESULTS: Thirteen patients (6 male, median age 66, range 54-86 years) were studied. Sub-acute delta:alpha power ratio (DAR; r=0.91, P<0.001), relative alpha power (r=-0.82, P<0.01), and NIHSS score (r=0.92, P<0.001) each were significantly correlated with 30-day NIHSS score. The former two significant correlations were upheld in 19-channel EEG data. QEEG measures involving theta or beta power were not significantly correlated with NIHSS scores. CONCLUSIONS: QEEG measures such as DAR demonstrate potential to augment bedside assessment of cerebral pathophysiology and prognostication of stroke evolution. A standard, 19-channel array seems adequate for these purposes. Future studies in larger samples should investigate the potential effects on these measures of sleep state and possible causes of artefacts. SIGNIFICANCE: QEEG measures from a standard number of electrodes, if available rapidly and robust to potential artefacts, may inform future management of stroke patients.
OBJECTIVE: We investigated the ability of quantitative electroencephalography (QEEG) measures in sub-acute stroke to assist monitoring or prognostication of stroke evolution. QEEG indices and National Institutes of Health Stroke Scale (NIHSS) scores were compared. METHODS: Ischaemic cortical strokepatients were studied. Resting, 62-channel EEG and NIHSS score were acquired at 49+/-3h post-symptom onset, and NIHSS administered at 30+/-2 days post-stroke. Mean power was calculated for delta (1-4 Hz), theta (4.1-8 Hz), alpha (8.1-12.5 Hz) and beta (12.6-30 Hz) frequency bands, using a 62-channel electrode array and a 19-channel subset. RESULTS: Thirteen patients (6 male, median age 66, range 54-86 years) were studied. Sub-acute delta:alpha power ratio (DAR; r=0.91, P<0.001), relative alpha power (r=-0.82, P<0.01), and NIHSS score (r=0.92, P<0.001) each were significantly correlated with 30-day NIHSS score. The former two significant correlations were upheld in 19-channel EEG data. QEEG measures involving theta or beta power were not significantly correlated with NIHSS scores. CONCLUSIONS: QEEG measures such as DAR demonstrate potential to augment bedside assessment of cerebral pathophysiology and prognostication of stroke evolution. A standard, 19-channel array seems adequate for these purposes. Future studies in larger samples should investigate the potential effects on these measures of sleep state and possible causes of artefacts. SIGNIFICANCE: QEEG measures from a standard number of electrodes, if available rapidly and robust to potential artefacts, may inform future management of strokepatients.
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