Cognitive validation of cross-diagnostic cognitive subgroups on the schizophrenia-bipolar spectrum

James A. Karantonis, Susan L. Rossell, Sean P. Carruthers, Philip Sumner, Matthew Hughes, Melissa J. Green, Christos Pantelis, Katherine E. Burdick, Vanessa Cropley, Tamsyn E. Van Rheenen

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Background: Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs. Method: Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline. Results: A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups. Limitations: For clustering analysis, sample size was relatively small. Conclusions: The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.

Original languageEnglish
Pages (from-to)710-721
Number of pages12
JournalJournal of Affective Disorders
Volume266
DOIs
StatePublished - 1 Apr 2020
Externally publishedYes

Keywords

  • Bipolar disorder
  • Clustering
  • Cognition
  • Heterogeneity
  • Neuropsychology
  • Schizophrenia

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