ArticleBMC neurology2023
Electroencephalography in young onset dementia.
Article in BMC neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- The neurophysiology of healthy and pathological aging: a comprehensive systematic review.Brain structure & function · 2025Pooled it
- Knowledge-Guided Deep Learning with Clinical EEG Biomarkers for Automated Dementia Detection and Staging.Diagnostics (Basel, Switzerland) · 2026Article
- Dementia classification using two-channel electroencephalography features.Scientific reports · 2025Article
- Expanding SPG18 clinical spectrum: autosomal dominant mutation causes complicated hereditary spastic paraplegia in a large family.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- Neurophysiological markers of early cognitive decline in older adults: a mini-review of electroencephalography studies for precursors of dementia.Frontiers in aging neuroscience · 2024Review
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3 authors at 1 institution in 1 country.
Funding
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Abstract
backgroundYoung onset dementia (YOD) is a major diagnostic and management problem.
methodsWe set out to explore if electroencephalography (EEG) might be useful in the diagnosis of young onset Alzheimer's disease (YOAD) and young onset frontotemporal dementia (YOFTD). The ARTEMIS project is a 25-year prospective study of YOD based in Perth, Western Australia. 231 participants were included: YOAD: n = 103, YOFTD: n = 28, controls: n = 100. EEGs were performed prospectively, with 30-minute recording time for each subject, without knowledge of diagnosis or other diagnostic data.
results80.9% of patients with YOD had abnormal EEGs (P < 0.00001). Slow wave changes were more frequent in YOAD that YOFTD (P < 0.00001), but no difference in the frequency of epileptiform activity (P = 0.32), with 38.8% of YOAD and 28.6% of YOFTD patients having epileptiform activity. Slow wave changes were more generalized in YOAD (P = 0.001). Slow wave changes and epileptiform activity were not sensitive to the diagnosis of YOD, but highly specific (97-99%). The absence of slow wave changes and epileptiform activity had a 100% negative predictive value and likelihood radio 0.14 and 0.62 respectively, meaning that those without slow wave changes or epileptiform activity had low probability of having YOD. No relationship was established between EEG findings and the patient's presenting problem. Eleven patients with YOAD developed seizures during the study, and only one with YOFTD.
conclusionsThe EEG is highly specific for the diagnosis of YOD with the absence of slow wave changes and epileptiform phenomena making the diagnosis unlikely, with 100% negative predictive value and with low probability for the dementia diagnosis.
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