Header

UZH-Logo

Maintenance Infos

Neurocognition in help-seeking individuals at risk for psychosis: Prediction of outcome after 24 months


Metzler, Sibylle; Dvorsky, Diane; Wyss, Christine; Nordt, Carlos; Walitza, Susanne; Heekeren, Karsten; Rössler, Wulf; Theodoridou, Anastasia (2016). Neurocognition in help-seeking individuals at risk for psychosis: Prediction of outcome after 24 months. Psychiatry Research, 246:188-194.

Abstract

An important aim in schizophrenia research is to optimize the prediction of psychosis and to improve strategies for early intervention. The objectives of this study were to explore neurocognitive performance in individuals at risk for psychosis and to optimize predictions through a combination of neurocognitive and psychopathological variables. Information on clinical outcomes after 24 months was available from 118 subjects who had completed an extensive assessment at baseline. Subjects who had converted to psychosis were compared with subjects who had not. Multivariate Cox regression analyses were used to determine which baseline measure best predicted a conversion to psychosis. The premorbid IQ and the neurocognitive domains of processing speed, learning/memory, working memory and verbal fluency significantly discriminated between converters and non-converters. When entered into multivariate regression analyses, the combination of PANSS positive/negative symptom severity and IQ best predicted the clinical outcomes. Our results confirm previous evidence suggesting moderate premorbid cognitive deficits in individuals developing full-blown psychosis. Overall, clinical symptoms appeared to be a more sensitive predictor than cognitive performance. Nevertheless, the two might serve as complementary predictors when assessing the risk for psychosis.

Abstract

An important aim in schizophrenia research is to optimize the prediction of psychosis and to improve strategies for early intervention. The objectives of this study were to explore neurocognitive performance in individuals at risk for psychosis and to optimize predictions through a combination of neurocognitive and psychopathological variables. Information on clinical outcomes after 24 months was available from 118 subjects who had completed an extensive assessment at baseline. Subjects who had converted to psychosis were compared with subjects who had not. Multivariate Cox regression analyses were used to determine which baseline measure best predicted a conversion to psychosis. The premorbid IQ and the neurocognitive domains of processing speed, learning/memory, working memory and verbal fluency significantly discriminated between converters and non-converters. When entered into multivariate regression analyses, the combination of PANSS positive/negative symptom severity and IQ best predicted the clinical outcomes. Our results confirm previous evidence suggesting moderate premorbid cognitive deficits in individuals developing full-blown psychosis. Overall, clinical symptoms appeared to be a more sensitive predictor than cognitive performance. Nevertheless, the two might serve as complementary predictors when assessing the risk for psychosis.

Statistics

Citations

2 citations in Web of Science®
1 citation in Scopus®
Google Scholar™

Altmetrics

Downloads

1 download since deposited on 19 Oct 2016
1 download since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Psychiatric University Hospital Zurich > Clinic for Psychiatry, Psychotherapy, and Psychosomatics
04 Faculty of Medicine > Psychiatric University Hospital Zurich > Center for Child and Adolescent Psychiatry
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:30 September 2016
Deposited On:19 Oct 2016 13:11
Last Modified:19 Oct 2016 13:12
Publisher:Elsevier
ISSN:0165-1781
Publisher DOI:https://doi.org/10.1016/j.psychres.2016.08.065
PubMed ID:27718468

Download

Preview Icon on Download
Content: Published Version
Filetype: PDF - Registered users only
Size: 299kB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations