Title

Predictors of Cognitive Improvement Following Treatment for Late-Life Depression

Document Type

Article

Abstract

Objective: Cognitive impairment is frequently comorbid with late-life depression (LLD) and often persists despite remission of mood symptoms with antidepressant treatment. Increasing understanding of factors that predict improvement of cognitive symptoms in LLD is useful to inform treatment recommendations. Methods: We used data from 2 randomized clinical trials of geriatric depression to examine the relationships between sociodemographic factors (resilience, quality of life) and clinical factors (age of depression onset, severity of depression, apathy) with subsequent cognitive outcomes. One hundred sixty-five older adults with major depression who had completed one of 2 clinical trials were included: (1) methylphenidate plus placebo, citalopram plus placebo, and citalopram plus methylphenidate or (2) citalopram combined with Tai Chi or health education. A comprehensive neuropsychiatric battery was administered; 2 measures of cognitive improvement were examined, one defined as an increase in general cognitive performance score of at least 1 standard deviation and the other 0.5 standard deviation pre–post treatment. Results: At posttreatment, 59% of participants had remitted, but less than a third of those who remitted showed cognitive improvement (29%). Cognitive improvement was observed in 18% of nonremitters. Lower baseline depression severity, greater social functioning, and depression onset prior to 60 years of age were significantly associated with cognitive improvement. None of the other measures, including baseline apathy, resilience, and depression remission status, were significantly associated with cognitive improvement. Conclusions: Lower severity of depression, earlier onset, and greater social functioning may predict improvement in cognitive functioning with treatment for depression in LLD.

Publication Date

3-1-2021

Publication Title

Journal of Geriatric Psychiatry and Neurology

ISSN

08919887

E-ISSN

15525708

Volume

34

Issue

2

First Page

162

Last Page

168

PubMed ID

32208884

Digital Object Identifier (DOI)

10.1177/0891988720915515

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