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Improving the clinical prediction of psychosis by combining ultra-high risk criteria and cognitive basic symptoms

Abstract Objective Cognitive impairments are regarded as a core component of schizophrenia. However, the cognitive dimension of psychosis is hardly considered by ultra-high risk (UHR) criteria. Therefore, we studied whether the combination of symptomatic UHR criteria and the basic symptom criterion...

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Bibliographic Details
Published in:Schizophrenia research 2014-04, Vol.154 (1), p.100-106
Main Authors: Schultze-Lutter, Frauke, Klosterkötter, Joachim, Ruhrmann, Stephan
Format: Article
Language:English
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Summary:Abstract Objective Cognitive impairments are regarded as a core component of schizophrenia. However, the cognitive dimension of psychosis is hardly considered by ultra-high risk (UHR) criteria. Therefore, we studied whether the combination of symptomatic UHR criteria and the basic symptom criterion “cognitive disturbances” (COGDIS) is superior in predicting first-episode psychosis. Method In a naturalistic 48-month follow-up study, the conversion rate to first-episode psychosis was studied in 246 outpatients of an early detection of psychosis service (FETZ); thereby, the association between conversion, and the combined and singular use of UHR criteria and COGDIS was compared. Results Patients that met UHR criteria and COGDIS (n = 127) at baseline had a significantly higher risk of conversion (hr = 0.66 at month 48) and a shorter time to conversion than patients that met only UHR criteria (n = 37; hr = 0.28) or only COGDIS (n = 30; hr = 0.23). Furthermore, the risk of conversion was higher for the combined criteria than for UHR criteria (n = 164; hr = 0.56 at month 48) and COGDIS (n = 158; hr = 0.56 at month 48) when considered irrespective of each other. Conclusions Our findings support the merits of considering both COGDIS and UHR criteria in the early detection of persons who are at high risk of developing a first psychotic episode within 48 months. Applying both sets of criteria improves sensitivity and individual risk estimation, and may thereby support the development of stage-targeted interventions. Moreover, since the combined approach enables the identification of considerably more homogeneous at-risk samples, it should support both preventive and basic research.
ISSN:0920-9964
1573-2509
DOI:10.1016/j.schres.2014.02.010