Statistical Analysis
TIA, death, cognitive impairment, stroke, white matter hyperintensities, infarct, diabetes
STROKE, WHITE MATTER HYPERINTENSITIES, REGRESSION, HYPERTENSION, INFARCT, TIA, DIABETES
We performed statistical analyses according to the published statistical analysis plan (Data are reported as the number (percentage), median (IQR), or mean (SD). Analyses used binary logistic regression (presented as adjusted odds ratios [aORs]), Cox proportional hazards regression (adjusted hazard ratios [aHRs]), ordinal logistic regression (aORs), or multiple linear regression (adjusted mean difference [aMDs]) and are presented with 95% CIs. Analyses were adjusted for minimization variables (baseline age, sex, NIHSS, mRS, systolic blood pressure, smoking status, time after stroke, and years of education); cognitive outcomes were additionally adjusted for baseline MoCA scores.The primary outcome (feasibility) was depicted graphically and numerically. The safety outcome (death) at 12 months was analyzed using binary logistic regression. The efficacy outcome (composite of stroke or TIA, MI, death, any vs no cognitive impairment on 7-level score, dependence, and death) at 12 months was analyzed using Cox proportional hazards regression. The composite required patients with data for all included variables. We assessed individual recurrent stroke and functional and cognitive outcomes using all available data.We used the Wei-Lachin testSensitivity analyses assessed all participants, including those with missing data for required variables (composite) and prespecified subgroups (minimization variables, hypertension, diabetes, prior stroke or TIA, index infarct on imaging, white matter hyperintensities, or cSVD score) adjusted for cilostazol in ISMN models and for ISMN in cilostazol models.Throughout the analysis, the threshold for statistical significance was a 2-tailed 