Table 2.
Multivariable linear regression analyses showing the associations for baseline characteristics and biomarkers to cognitive function (ie, total BNIS score) 7 years after index ischemic stroke
| Baseline characteristics | Whole sample, n = 268 | Stroke <50 years, n = 67 | ||
|---|---|---|---|---|
| βstd | 95% CI for βstd | βstd | 95% CI for βstd | |
| Age | −0.12 | −0.24, 0.00 | 0.04 | −0.15, 0.23 |
| <65 years | −0.16 | −0.28, −0.05 | NA | NA |
| SSS | 0.35 | 0.25, 0.44 | 0.58 | 0.39, 0.76 |
| Education | 0.31 | 0.21, 0.40 | 0.26 | 0.09, 0.44 |
| Years from last stroke | 0.17 | 0.07, 0.27 | 0.08 | −0.10, 0.25 |
| Diabetes | −0.10 | −0.20, 0.00 | −0.16 | −0.35, 0.03 |
| Hypertension | −0.02 | −0.12, 0.08 | 0.01 | −0.18, 0.19 |
| Biomarkers | ||||
| Fibrinogen | −0.09 | −0.20, 0.01 | −0.27 | −0.47, −0.07 |
| VWF antigen | −0.07 | −0.17, 0.04 | −0.03 | −0.23, 0.18 |
| t‐PA antigen | −0.03 | −0.14, 0.07 | −0.05 | −0.26, 0.17 |
BNIS, Barrow Neurological Institute Screen for Higher Cerebral Functions; SSS, Scandinavian Stroke Scale; VWF, von Willebrand factor; t‐PA, tissue‐type plasminogen activator; βstd, standardized beta; CI, confidence interval. Multivariable linear regression models were used for calculation of βstd for total BNIS score. The betas represent an estimate of how many standard deviations the BNIS score will change per standard deviation increase in the predictor variable. Variables included were baseline characteristics and, for the biomarkers, each biomarker at a time. Units for the predictor variables are given in Table 1. The analyses were based on log transformed biomarker concentrations. For fibrinogen one standard deviation increase represents a biomarker concentration increase of approximately 30% and for t‐PA and VWF the corresponding figure is approximately 50%. Please note that a high SSS score represents a low stroke severity.