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A Methodological Perspective on the Longitudinal Cognitive Change after Stroke.

Jae-Sung Lim1, Maengseok Noh2, Beom Joon Kim3

  • 1Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea.

Dementia and Geriatric Cognitive Disorders
|February 3, 2018
PubMed
Summary
This summary is machine-generated.

Predictors for poststroke cognitive impairment (PSCI) differ when cognitive changes over time and domain correlations are considered. Analyzing cognitive changes is crucial for accurate PSCI predictor identification.

Keywords:
Longitudinal studyMixed modelMultivariate analysisPoststroke cognitive impairmentVascular causes of cognitive impairmentVascular cognitive impairment

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Area of Science:

  • Neuroscience
  • Clinical Neurology
  • Psychology

Background:

  • Most poststroke cognitive impairment (PSCI) studies assess cognition at single time points, not changes over time.
  • Correlations between different cognitive domains are often overlooked in PSCI research.
  • Existing methodologies may inaccurately identify predictors of cognitive decline after stroke.

Purpose of the Study:

  • To investigate how analyzing cognitive changes over time and accounting for domain correlations impacts the identification of PSCI predictors.
  • To re-evaluate known PSCI predictors using advanced longitudinal and multivariate statistical models.

Main Methods:

  • Utilized a longitudinal cohort of 375 stroke patients with at least two neuropsychological tests.
  • Employed multilevel hierarchical mixed-effects models to analyze domain-specific cognitive changes.
  • Applied multivariate models to account for correlations between multiple cognitive outcomes.

Main Results:

  • Known PSCI predictors were associated with cognitive levels but often lost significance when cognitive changes were the outcome.
  • Age predicted memory changes; prior stroke and baseline cognition predicted executive/attention changes; baseline cognition predicted visuospatial changes.
  • Multivariate analysis considering outcome correlations further modified the identified associations.

Conclusions:

  • Defining outcomes as cognitive changes over time is critical for accurate PSCI predictor identification.
  • Incorporating correlations between cognitive domains refines the understanding of factors influencing cognitive trajectories poststroke.
  • Methodological choices significantly influence the identification and interpretation of PSCI predictors.