Exploring intra-individual cognitive variability phenotypes after stroke using ecological momentary assessment

Thursday, November 10, 2022

12:31 PM – 12:36 PM

Location: Station 2

Presenting Author(s)

Elizabeth Munsell, PhD, OTR/L

Post-doctoral Research Fellow
Shirley Ryan AbilityLab; Feinberg School of Medicine, Northwestern University, United States

Non-presenting Author(s)

Quoc Bui

Staff
Washington University School of Medicine in St. Louis
Maryland Heights, Missouri, United States
KK

Katherine Kaufman

Research Assistant
Shirley Ryan Abilitylab, United States
EL

Eric Lenze, MD

Wallace and Lucille K. Renard Professor of Psychiatry
Washington University School of Medicine at St. Louis
Saint Louis, Missouri, United States
JL

Jin-Moo Lee, MD, PhD

Norman J. Stupp Professor of Neurology
Washington University School of Medicine, St. Louis, Missouri
St. Louis, Missouri, United States
DM

David C. Mohr, PhD

Professor
Northwestern University
Chicago, Illinois, United States
MF

Mandy W. M. Fong, PhD

Assistant Professor
Dept. of Neurology, Washington University School of Medicine
St. Louis, Missouri, United States
CM

Christopher L. Metts, MD

Associate Professor
Medical University of South Carolina, Pathology and Laboratory Medicine
Charleston, North Carolina, United States
ST

Stephanie Tomazin, B.S., MPH

Project Coordinator
Shirley Ryan AbilityLab
Chicago, Illinois, United States
VP

Vy T. Pham

Statistical Data Analyst
Washington University School of Medicine in St. Louis
Maryland Heights, Missouri, United States
Alex W.K Wong, PhD, DPhil

Research Scientist & Research Associate Professor
Shirley Ryan AbilityLab & Northwestern University
Chicago, Illinois, United States

Research Objectives: To describe variability in cognitive complaints and associations with functional outcomes in individuals with stroke.

Design: Longitudinal observational study using ecological momentary assessment (EMA) to assess cognitive complaints. PROMIS and NeuroQoL short forms, including participation and satisfaction with social roles, depression, anxiety, and pain interference and intensity, were also completed in a lab setting. We used Latent class analysis (LCA) to determine phenotypic profiles of cognitive variability (CV) and ANOVA to test associations between functional outcomes and variability profiles.

Setting: Home and community.

Participants: Individuals (N = 201) with mild-moderate stroke and greater than three months post-stroke were recruited.

Interventions: Not applicable.

Main Outcome Measures: Participants responded EMA surveys five times a day for 14 days. We derived five variability indicators to quantify the patterns of cognitive complaints experienced by each participant.

Results: The LCA converged on a three-profile model (BIC= 1398, entropy = 0.994, VLMR p = .177, k − 1 LRT= 367.89, p < .001). Inspection of the profiles revealed a low, moderate, and high CV profile. The moderate and high CV group demonstrated significantly greater functional challenges than the low CV group (all domains p < .05). The high CV group had the worst performance in all domains. Further, over 65% of the participants with moderate CV reported meaningfully worse pain interference and participation in and satisfaction with social roles.

Conclusions: Findings suggest that EMA assessment of intra-individual variability may be a useful tool to identify a subgroup of at-risk stroke survivors with cognitive issues impacting daily function in natural environments. This tool offers real-world monitoring and screening for post-stroke health after transitioning to home and community settings.

Author(s) Disclosures: None.

Learning Objectives:

Describe the importance of assessing intra-individual variability in cognitive complaints post-stroke.
Describe the functional challenges experienced by individuals with cognitive variability post-stroke.
Describe the benefits of EMA as an assessment tool for home and community settings.