Statistical analysis
motor impairment, SD, Dextrain, upper limb motor impairment
SECONDARY
Categorical variables were described as number (%). Data distributions of continuous variables were analyzed using skewness (< − 1 or > 1 = highly skewed data) and Shapiro–Wilk’s test. Normally distributed variables were described as means ± SD and compared with Student t-test, whereas non-normally distributed variables were described as medians (interquartile range [IQR]) and compared with non-parametric tests (Mood median test or Mann–Whitney U test).The effect of training was evaluated using change variables T1-T0 (absolute difference, reflecting immediate training effect) and T2-T0 (3-month follow-up effect), as specified in the statistical analysis protocol established before project start. The Hodges-Lehmann estimator of median of group differences with its 95% ‘exact’ confidence limits (95%CL) was computed as main measure of treatment effect. To limit the number of statistical tests with regards to secondary outcomes, P-values were only calculated for outcomes where the 95%CL of the median of group differences did not include zero. In this case, the Mood median test was used. Six tests were carried out and we did not correct for multiple comparisons given the exploratory nature of this pilot RCT. Given the group difference in age we also analyzed the percent change in BBT using gender and age normalized BBT scores [Finally, to explore the impact of degree of motor impairment on Dextrain training effect we divided patients into moderate and mild motor impairment subgroups using median split of Fmax% and compared BBT-change using Mann–Whitney U Test. Maximal grip force is considered a good overall indicator of upper limb motor impairment [