Author information
1Grey Walter Dept of Clinical Neurophysiology, North Bristol NHS Trust, Bristol, UK.
2Johns Hopkins Bayview Medical Center, Baltimore, Maryland, USA.
3Grey Walter Dept of Clinical Neurophysiology, North Bristol NHS Trust, Westbury on Trym, UK nick.Kane@nbt.nhs.uk.
Abstract
Electroencephalography (EEG) is a useful adjunct to clinical neurological examination, particularly as it may detect subtle or subclinical disturbance of cerebral function and it allows monitoring of cerebral activity over time. Continuous EEG combined with quantitative analysis and machine learning may help identify changes in real time, before the emergence of clinical signs and response to interventions. EEG is rarely pathognomonic in encephalopathy/encephalitis but when interpreted correctly and within the clinical context, certain phenotypes may indicate a specific pathophysiology (eg, lateralised periodic discharges in HSV-1, generalised periodic discharges in sporadic Creutzfeldt-Jakob disease, and extreme delta brushes in anti-n-methyl-D-aspartate receptor autoimmune encephalitis). EEG is included in some specialist guidelines for disease assessment, monitoring and prognostication (ie, hepatic, cancer immunotherapy, viral, prion, autoimmune encephalitis and hypoxic ischaemic encephalopathy). EEG is invaluable for confirming or excluding non-convulsive seizures or status epilepticus, particularly in critically ill patients, and in understanding new concepts such as epileptic encephalopathy and the ictal-interictal continuum.