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Post-stroke Depressive Symptoms and Cognitive Performances: A Network Analysis.
Shi, Yun; Lenze, Eric J; Mohr, David C; Lee, Jin-Moo; Hu, Lu; Metts, Christopher L; Fong, Mandy W M; Wong, Alex W K.
Afiliação
  • Shi Y; Center for Healthful Behavior Change, Institute for Excellence in Health Equity, NYU Langone Health, New York, NY; Department of Population Health, New York University Grossman School of Medicine, New York, NY.
  • Lenze EJ; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO.
  • Mohr DC; Center for Behavioral Intervention Technologies, Northwestern University Feinberg School of Medicine, Chicago, IL; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
  • Lee JM; Department of Neurology, Washington University School of Medicine, St. Louis, MO.
  • Hu L; Center for Healthful Behavior Change, Institute for Excellence in Health Equity, NYU Langone Health, New York, NY; Department of Population Health, New York University Grossman School of Medicine, New York, NY.
  • Metts CL; Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, SC.
  • Fong MWM; Department of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, IL; Michigan Avenue Neuropsychologists, Chicago, IL.
  • Wong AWK; Department of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, IL; Center for Rehabilitation Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL; Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago
Article em En | MEDLINE | ID: mdl-37884084
ABSTRACT

OBJECTIVE:

To examine the relationships between post-stroke depression and cognition using network analysis. In particular, we identified central depressive symptoms, central cognitive performances, and bridge components that connect these 2 constructs.

DESIGN:

An observational study. We applied network analysis to analyze baseline data to visualize and quantify the relationships between depression and cognition.

SETTING:

Home and Community.

PARTICIPANTS:

202 participants with mild-to-moderate stroke (N=202; mean age 59.7 years; 55% men; 55% Whites; 90% ischemic stroke). INTERVENTION Not applicable. MAIN OUTCOME

MEASURES:

Patient Health Questionnaire (PHQ-8) for depressive symptoms and the NIH Toolbox Cognitive Battery for cognitive performances.

RESULTS:

Depressive symptoms were positively intercorrelated with the network, with symptoms from similar domains clustered together. Mood (expected influence=1.58), concentration (expected influence=0.67), and guilt (expected influence=0.63) were the top 3 central depressive symptoms. Cognitive performances also showed similar network patterns, with executive function (expected influence=0.89), expressive language (expected influence=0.68), and processing speed (expected influence=0.48) identified as the top 3 central cognitive performances. Psychomotor functioning (bridge expected influence=2.49) and attention (bridge expected influence=1.10) were the components connecting depression and cognition.

CONCLUSIONS:

The central and bridge components identified in this study might serve as targets for interventions against these deficits. Future trials are needed to compare the effectiveness of interventions targeting the central and bridge components vs general interventions treating depression and cognitive impairment as a homogenous clinical syndrome.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article