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Neuropsychological Clustering in Bipolar and Major Depressive Disorder

Published online by Cambridge University Press:  15 June 2017

Charles Cotrena
Affiliation:
Department of Psychology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
Laura Damiani Branco*
Affiliation:
Department of Psychology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
André Ponsoni
Affiliation:
Department of Psychology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
Flávio Milman Shansis
Affiliation:
Program for the Study and Research of Mood Disorders (PROPESTH), São Pedro Psychiatric Hospital, Porto Alegre, Brazil
Rochele Paz Fonseca
Affiliation:
Department of Psychology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
*
Correspondence and reprint requests to: Laura Damiani Branco, Av. Ipiranga, 6681, Building 11, Room 932, Porto Alegre, RS, Brazil. 90619-900. E-mail: [email protected]

Abstract

Objectives: Cognitive dysfunction is a key feature of major depressive (MDD) and bipolar (BD) disorders. However, rather than a single cognitive profile corresponding to each diagnostic categories, recent studies have identified significant intra- and cross-diagnostic variability in patterns of cognitive impairment. The goal of this study was to contribute to the literature on cognitive heterogeneity in mood disorders by identifying cognitive subprofiles in a population of patients with MDD, BD type I, BD type II, and healthy adults. Methods: Participants completed a neuropsychological battery; scores were converted into Z-scores using normative data and submitted to hierarchical cluster analysis. Results: Three distinct neuropsychological clusters were identified: (1) a large cluster containing mostly control participants, as well as some patients with BD and MDD, who performed at above-average levels on all neuropsychological domains; (2) a cluster containing some patients from all diagnostic groups, as well as healthy controls, who performed worse than cluster 1 on most tasks, and showed impairments in motor inhibition and verbal fluency; (3) a cluster containing mostly patients with mood disorders with severe impairments in verbal inhibition and cognitive flexibility. Conclusions: These findings revealed multiple cognitive profiles within diagnostic categories, as well as significant cross-diagnostic overlap, highlighting the importance of developing more specific treatment approaches which consider patients’ demographic and cognitive profiles in addition to their diagnosis. (JINS, 2017, 23, 584–593)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2017 

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References

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