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S-2 QEEG and Brain Imaging Techniques for a New Treatment Strategy in Pharmacopsychiatry (ACNP Invited Symposium)

Monday, 19 October 1992

Prediction of the evolution of cognitive deterioration in the elderly using QEEG

Prichep, L.S. 1'2, John, E.R. 1'2, Almas, M. l, Ferris, S. t and Reisberg, B. 1 INew York University Medical Center, New York, NY, U.S.A. 2Nathan S. Kline Research Institute, Orangeburg, NY, U.S.A.

Normal elderly subjects (n = 18), elderly patients with mild cognitive impairment (n = 43) and patients presenting with a continuum of primary cognitive deterioration from mild (n = 22) to severe (n = 68), compatible with dementia of the Alzheimer's type (DAT), were extensively studied with neuropsychological, medical, psychiatric and electrophysiological evaluations. Neurometric QEEG features were extracted from artifact-free data, transformed to obtain Gaussianity and age- regressed. All measures were than expressed as Z scores, indicating the probability that the patient's obtained values are within the range expected for a normal individual his/her age. This population was then followed up 3 to 10 years later at which time they were again evaluated clinically. Using the neurometric profile at baseline, we were able to predict with high accuracy those who remain unchanged and those who go on to show deterioration, with global deterioration scale scores (GDS) changes of 1 to 4 points. Of particular interest and importance were the 60 subjects who initially were normal and those who initially showed only subjective evidence of cognitive decline. Accurate prediction of decline in these groups over the follow-up period suggests the utility of QEEG in the early detection of dementia and raising the possibility of early pharmacological intervention.

Prediction of the response to t r ea tment in OCD and panic d isorder pat ients using cluster analysis of QEEG variables

Mas, F. 1, Goldstein, S. 2 and Prichep, L.S. 1 1New York University Medical Center, Brain Research Labs

2Columbia University, Department of Psychiatry, New York, NY, U.S.A.

In order to study the treatment outcome predictive value of quantitative EEG, baseline measure have been performed in 26 patients with DSMIIIR diagnosed obsessive compulsive disorder and 13 patients with a well defined DSMIIIR diagnosis of panic disorder. In both groups, QEEG findings at baseline showed many deviations from expected age appropriate normal values which clustered in two rather well defined subgroups. A clear relationship between clustering and response to treatment could be seen in OCD patients. This was less obvious in panic disorder patients. In both instances, however, results suggested the existence of different pathophysiological subtypes sharing a common clinical expression.