Background/aims: Most studies of poststroke cognitive impairment (PSCI) have analyzed cognitive levels at specific time points rather than their changes over time. Furthermore, they seldom consider correlations between cognitive domains. We aimed to investigate the effects of these methodological considerations on determining significant PSCI predictors in a longitudinal stroke cohort.
Methods: In patients who underwent neuropsychological tests at least twice after stroke, we adopted a multilevel hierarchical mixed-effects model with domain-specific cognitive changes and a multivariate model for multiple outcomes to reflect their correlations.
Results: We enrolled 375 patients (median follow-up of 34.1 months). Known predictors of PSCI were generally associated with cognitive levels; however, most of the statistical significances disappeared when cognitive changes were set as outcomes, except age for memory, prior stroke and baseline cognition for executive/attention domain, and baseline cognition for visuospatial function. The multivariate analysis which considered multiple outcomes simultaneously further altered these associations.
Conclusions: This study shows that defining outcomes as changes over time and reflecting correlations between outcomes may affect the identification of predictors of PSCI.
Keywords: Longitudinal study; Mixed model; Multivariate analysis; Poststroke cognitive impairment; Vascular causes of cognitive impairment; Vascular cognitive impairment.
© 2018 S. Karger AG, Basel.