Why the study?
Does computer-assisted EEG monitoring improve the objective identification of pathological EEGs compared to visual analysis during carotid endarterectomy?
Does computer-assisted EEG monitoring improve the objective identification of pathological EEGs compared to visual analysis during carotid endarterectomy?
Computer-assisted EEG analysis provides objective spectral indexes that support visual analysis during carotid endarterectomy without additional costs.
Objective spectral metrics may complement visual EEG review in CEA; leaves open whether routine adoption improves outcomes.
The purpose of this study was to develop a reliable method of EEG analysis during carotid endarterectomy. EEGs of 104 patients under general anesthesia were processed by three different methods: a) "on-line" visual analysis during surgery, b) "off-line" visual analysis in laboratory, and c) computer analysis. To identify pathological EEGs, variability and asymmetry indexes of the 0.5-3.5 Hz and 8-15 Hz bands, absolute power and variability indexes of spectral edge frequency (SEF), and main dominant frequency were evaluated. On-line visual analysis showed clamp-related modifications in 29 EEGs (27.9%). Off-line visual analysis detected 24 pathological EEGs (23.1%): 18 with major changes and 6 with moderate changes. Computer analysis showed 21 EEGs (20.19%) with at least one altered index and 7 (6.7%) with altered variability for both SEF and 8-15 Hz power. The statistical analysis was significant for SEF variability and for 8-15 Hz power variability and asymmetry (P < 0.0001, analysis of variance test). While SEF and 8-15 Hz power variability did not appear influenced by anesthesia and single electrode artifacts, 8-15 Hz power asymmetry index was confounded by the presence of contralateral internal carotid occlusion. The data show that the use of these spectral indexes adds objective information to visual analysis, supporting and making easier intraoperative strategies. Their routine clinical use does not involve additional costs remaining technical requirements unchanged compared to traditional recording.
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Minicucci et al. (2000) studied this question.
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