TY - JOUR
T1 - Cognitive impairment in euthymic patients with bipolar disorder
T2 - Prevalence estimation and model selection for predictors of cognitive performance
AU - Tsapekos, Dimosthenis
AU - Strawbridge, Rebecca
AU - Cella, Matteo
AU - Wykes, Til
AU - Young, Allan H
N1 - Funding Information:
This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. DT would like to acknowledge that this scientific paper was supported by the Onassis Foundation-Scholarship ID: F ZO077-1/2018-2019. AHY and TW would like to acknowledge their NIHR Senior Investigator award.
Funding Information:
We are grateful to all CRiB study participants, service user representatives, and all students and researchers from Centre for Affective Disorders who contributed to the CRiB study. We also thank King's College Hospital Clinical Research Facility (CRF) and King's College Clinical Trials Unit, OPTIMA mood disorders service and SLaM Affective Disorders Service. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All procedures involving human patients were approved by the City Road & Hampstead NHS Research Ethics Committee (reference 15/LO/1557).
Publisher Copyright:
© 2021 The Author(s)
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/11/1
Y1 - 2021/11/1
N2 - Objectives Although cognitive dysfunction is a prominent feature of bipolar disorder (BD), previous research presents limitations in estimating the proportion of euthymic patients experiencing clinically relevant deficits and identifying predictors of cognitive difficulties. We explored the relevance of recommended definitions of clinically significant cognitive impairment for functional outcomes, estimated its prevalence, and identified patient characteristics associated with cognition. Methods We assessed cognitive performance across four domains in 80 euthymic participants with BD. Participants were categorized based on two criteria for clinically significant cognitive impairment and we assessed the ability of these criteria to differentiate participant performance on established functional outcomes. Variable selection with elastic net regression was used to identify sociodemographic and clinical factors associated with cognitive performance. Selected variables were examined as predictors of clinically significant cognitive impairment with logistic regression. Results According to the selected criterion, 34% presented with clinically significant cognitive impairment. Poorer current cognitive performance was associated with older age, lower estimated premorbid IQ, more currently prescribed psychotropic medications, fewer previous psychological therapies, and current use of antipsychotics. A model with premorbid IQ, psychotropic medications and previous psychological therapies as predictors of cognitive impairment correctly classified 75% of the participants. Conclusions This is one of the first studies to use a model selection approach to identify factors associated with cognitive difficulties in BD. Our findings offer the initial steps towards a predictive model for cognitive impairment. This could improve treatment decisions and prioritization for euthymic patients with BD, particularly the implementation of cognitive interventions.
AB - Objectives Although cognitive dysfunction is a prominent feature of bipolar disorder (BD), previous research presents limitations in estimating the proportion of euthymic patients experiencing clinically relevant deficits and identifying predictors of cognitive difficulties. We explored the relevance of recommended definitions of clinically significant cognitive impairment for functional outcomes, estimated its prevalence, and identified patient characteristics associated with cognition. Methods We assessed cognitive performance across four domains in 80 euthymic participants with BD. Participants were categorized based on two criteria for clinically significant cognitive impairment and we assessed the ability of these criteria to differentiate participant performance on established functional outcomes. Variable selection with elastic net regression was used to identify sociodemographic and clinical factors associated with cognitive performance. Selected variables were examined as predictors of clinically significant cognitive impairment with logistic regression. Results According to the selected criterion, 34% presented with clinically significant cognitive impairment. Poorer current cognitive performance was associated with older age, lower estimated premorbid IQ, more currently prescribed psychotropic medications, fewer previous psychological therapies, and current use of antipsychotics. A model with premorbid IQ, psychotropic medications and previous psychological therapies as predictors of cognitive impairment correctly classified 75% of the participants. Conclusions This is one of the first studies to use a model selection approach to identify factors associated with cognitive difficulties in BD. Our findings offer the initial steps towards a predictive model for cognitive impairment. This could improve treatment decisions and prioritization for euthymic patients with BD, particularly the implementation of cognitive interventions.
KW - Bipolar disorder
KW - Cognitive impairment
KW - Euthymia
KW - Model selection
KW - Predictors
KW - Prevalence
UR - http://www.scopus.com/inward/record.url?scp=85111204312&partnerID=8YFLogxK
U2 - 10.1016/j.jad.2021.07.036
DO - 10.1016/j.jad.2021.07.036
M3 - Article
C2 - 34330045
AN - SCOPUS:85111204312
SN - 0165-0327
VL - 294
SP - 497
EP - 504
JO - Journal of Affective Disorders
JF - Journal of Affective Disorders
ER -
