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Quantitative spectral electroencephalography in predicting survival in patients with early Alzheimer disease
J J Claus1, B W Ongerboer de Visser, G J Walstra
1Department of Neurology, Academic Medical Center, Amsterdam, The Netherlands. j.j.claus@amc.uva.nl
Objective:
To determine whether measures of quantitative spectral electroencephalography (EEG) can predict survival in patients with early Alzheimer disease.
Design:
Prospective cohort study; median duration of follow-up was 4.4 years in survivors and 2.6 years in nonsurvivors. Cox proportional hazards models, with adjustment for age and sex were used to estimate relationships between EEG measures and survival. Log relative percentage values of EEG bands were used as predictors.
Setting:
Outpatient university memory clinic.
Participants:
One hundred one consecutively referred patients with early probable Alzheimer disease according to National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association criteria were studied with EEG at the time of diagnosis. The mean age of the patients was 79.2 years, which was higher than in previous EEG studies.
Main Outcome Measure:
Mortality.
Results:
Fifty-one patients (50.5%) died during follow-up, with a median survival time in all patients of 4.1 years. The following EEG variables were significantly associated with increased risk of mortality: from parieto-occipital leads, higher theta (hazard ratio, 2.05; 95% confidence interval, 1.15-3.66; P<.05), lower alpha (hazard ratio, 0.43; 95% confidence interval, 0.25-0.76; P<.01), and lower beta (hazard ratio, 0.38; 95% confidence interval, 0.22-0.68; P<.001) activity; and from frontocentral leads, higher theta activity (hazard ratio, 2.07; 95% confidence interval, 1.17-3.66; P<.05). Stepwise Cox regression analysis showed that loss of parieto-occipital beta (P<.01) and alpha (P<.05) power were independent and significant predictors of mortality. Both beta (12.6-35.4 Hz) and alpha (7.5-12.5 Hz) activity remained significantly associated with mortality after adjustment for education, dementia severity, symptom duration, level of cognitive function, presence of extrapyramidal symptoms or hallucinations, presence of vascular risk factors, and presence of leukoaraiosis or local cortical atrophy.
Conclusions:
Decreases of beta and alpha activity on quantitative spectral EEG are independent predictors of mortality in patients with early Alzheimer disease. In the clinical context, the use of EEG technology for prediction of survival in individual patients remains to be determined.