Electroencephalographic findings in schizophreniform and affective disorders. (2nd July 2016)

• Record Type: Journal Article
• Authors: Endres, Dominique; Perlov, Evgeniy; Feige, Bernd; Fleck, Max; Bartels, Susanne; Altenmüller, Dirk-Matthias; Tebartz van Elst, Ludger
• Is Part Of: International journal of psychiatry in clinical practice. Volume 20:Number 3(2016)
• Page Start: 157
• Page End: 164
• Publication Date: 2016-07-02
• Subjects: EEG -- IRDA -- IRTA -- local area network inhibition -- schizophrenia; Mental illness -- Periodicals; Older people -- Mental health -- Periodicals; Psychiatry -- Periodicals; 616.89005
• DOI: 10.1080/13651501.2016.1181184
• Languages: English
• ISSNs: 1365-1501

Abstract

Abstract: Objective: Pathological findings in electroencephalography (EEG) are discussed as a possible marker of organic mental disorders and a therapeutic response to anticonvulsive medication under these conditions. Methods: We compared the prevalence of EEG abnormalities in 100 patients with schizophrenia, 100 patients with schizoaffective disorder, 51 patients with acute polymorphic psychotic disorder, 100 patients with bipolar disorder, 100 patients with unipolar major depression and 76 healthy control subjects with the findings of a previous study using well-diagnosed, large control samples (13, 658 pilots and aircrew personnel). Results: We detected an increased number of pathological EEG findings with intermittent rhythmic delta or theta activity in 7% of patients with schizophrenia, 7% of patients with schizoaffective disorder, 5.9% of patients with acute polymorphic psychosis, 6% of patients with bipolar disorder, 4% of unipolar depressed patients and 3.9% of the own control group, compared to 1% of strictly controlled healthy subjects. One-sided logistic regression revealed an association between pathological EEGs and the diagnosis of schizophrenia (Wald W = 3.466, p = 0.0315), schizoaffective disorder ( W = 3.466, p = 0.0315) and bipolar disorder ( W = 2.862, p = 0.0455). Conclusions: We suggest that the previously developed local area network inhibition model for a potential paraepileptic pathomechanism can explain the relevance of such findings in different psychiatric disorders.