Details

Autor(en) / Beteiligte

• van Tricht, Mirjam J
• Ruhrmann, Stephan
• Arns, Martijn
• Müller, Ralf
• Bodatsch, Mitja
• Velthorst, Eva
• Koelman, Johannes H.T.M
• Bour, Lo J
• Zurek, Katharina
• Schultze-Lutter, Frauke
• Klosterkötter, Joachim
• Linszen, Don H
• de Haan, Lieuwe
• Brockhaus-Dumke, Anke
• Nieman, Dorien H

Titel

Can quantitative EEG measures predict clinical outcome in subjects at Clinical High Risk for psychosis? A prospective multicenter study

Ist Teil von

• Schizophrenia research, 2014-03, Vol.153 (1), p.42-47

Ort / Verlag

Amsterdam: Elsevier B.V

Erscheinungsjahr

2014

Quelle

MEDLINE

Beschreibungen/Notizen

• Abstract Background Prediction studies in subjects at Clinical High Risk (CHR) for psychosis are hampered by a high proportion of uncertain outcomes. We therefore investigated whether quantitative EEG (QEEG) parameters can contribute to an improved identification of CHR subjects with a later conversion to psychosis. Methods This investigation was a project within the European Prediction of Psychosis Study (EPOS), a prospective multicenter, naturalistic field study with an 18-month follow-up period. QEEG spectral power and alpha peak frequencies (APF) were determined in 113 CHR subjects. The primary outcome measure was conversion to psychosis. Results Cox regression yielded a model including frontal theta (HR = 1.82; [95% CI 1.00–3.32]) and delta (HR = 2.60; [95% CI 1.30–5.20]) power, and occipital–parietal APF (HR = .52; [95% CI .35–.80]) as predictors of conversion to psychosis. The resulting equation enabled the development of a prognostic index with three risk classes (hazard rate 0.057 to 0.81). Conclusions Power in theta and delta ranges and APF contribute to the short-term prediction of psychosis and enable a further stratification of risk in CHR samples. Combined with (other) clinical ratings, EEG parameters may therefore be a useful tool for individualized risk estimation and, consequently, targeted prevention.