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Subjects with bipolar disorder (BD) show heterogeneous cognitive profile and that not necessarily the disease will lead to unfavorable clinical outcomes. We aimed to identify clinical markers of severity among cognitive clusters in individuals with BD through data-driven methods.
We recruited 167 outpatients with BD and 100 unaffected volunteers from Brazil and Spain that underwent a neuropsychological assessment. Cognitive functions assessed were inhibitory control, processing speed, cognitive flexibility, verbal fluency, working memory, short- and long-term verbal memory. We performed hierarchical cluster analysis and discriminant function analysis to determine and confirm cognitive clusters, respectively. Then, we used classification and regression tree (CART) algorithm to determine clinical and sociodemographic variables of the previously defined cognitive clusters.
We identified three neuropsychological subgroups in individuals with BD: intact (35.3%), selectively impaired (34.7%), and severely impaired individuals (29.9%). The most important predictors of cognitive subgroups were years of education, the number of hospitalizations, and age, respectively. The model with CART algorithm showed sensitivity 45.8%, specificity 78.4%, balanced accuracy 62.1%, and the area under the ROC curve was 0.61. Of 10 attributes included in the model, only three variables were able to separate cognitive clusters in BD individuals: years of education, number of hospitalizations, and age.
These results corroborate with recent findings of neuropsychological heterogeneity in BD, and suggest an overlapping between premorbid and morbid aspects that influence distinct cognitive courses of the disease.
Functional impairment is a defining feature of psychotic disorders. A range of factors has been shown to influence functioning, including negative symptoms, cognitive performance and cognitive reserve (CR). However, it is not clear how these variables may affect functioning in first-episode psychosis (FEP) patients. This 2-year follow-up study aimed to explore the possible mediating effects of CR on the relationship between cognitive performance or specific clinical symptoms and functional outcome.
A prospective study of non-affective FEP patients was performed (211 at baseline and 139 at follow-up). CR was entered in a path analysis model as potential mediators between cognitive domains or clinical symptoms and functioning.
At baseline, the relationship between clinical variables or cognitive performance and functioning was not mediated by CR. At follow-up, the effect of attention (p = 0.003) and negative symptoms (p = 0.012) assessed at baseline on functioning was partially mediated by CR (p = 0.032 and 0.016), whereas the relationship between verbal memory (p = 0.057) and functioning was mediated by CR (p = 0.014). Verbal memory and positive and total subscales of PANSS assessed at follow-up were partially mediated by CR and the effect of working memory on functioning was totally mediated by CR.
Our results showed the influence of CR in mediating the relationship between cognitive domains or clinical symptoms and functioning in FEP. In particular, CR partially mediated the relationship between some cognitive domains or clinical symptoms and functioning at follow-up. Therefore, CR could improve our understanding of the long-term functioning of patients with a non-affective FEP.
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