Fig 1.
Flowchart of the binary logistic regression model.
Abbreviations: MoCA, Montreal Cognitive Assessment; NIHSS, National Institutes of Health Stroke Scale.
Fig 2.
Flowchart of the study participants.
Abbreviations: MoCA, Montreal Cognitive Assessment.
Table 1.
Comparison between patients included in the study sample and excluded patients.
Table 2.
Characteristics of patients included in the study—Baseline data.
Between-group analyses of patients with impaired (MoCA <26) and intact (MoCA ≥26) cognition at acute stroke units.
Fig 3.
Number of subjective cognitive complaints in the total sample as well stratified based on the cognitive function (screened with the Montreal Cognitive Assessment [MoCA]) at baseline.
Table 3.
Subjective cognitive complaints 3 months after stroke in the total sample as well as stratified based on cognitive function at baseline.
Fig 4.
Correlational analysis between cognitive function screened at stroke units (Montreal Cognitive Assessment [MoCA]), age, sex, education, stroke severity at admission to the hospital (the National Institutes of Health Stroke Scale [NIHSS]), and subjective cognitive complaints (SCCs) three months after stroke.
Statistics: Spearman’s rank-order correlation coefficient for continuous variables, Phi correlation coefficient for nominal variables. ** p < 0.01; *p < 0.05.
Fig 5.
Forest plot with the results of binary logistic regression analyses showing the explanatory value of independent variables for subjective cognitive complaints (SCCs) 3 months after stroke.
MoCA, Montreal Cognitive Assessment; NIHSS, National Institutes of Health Stroke Scale; AUC, area under the curve; CI, confidence interval; ORs, odds ratios.
Table 4.
The results of binary logistic regression analyses showing the explanatory value of cognitive function screened early after stroke for subjective cognitive compliant after 3 months.