Statistical analysis
paresis
REGRESSION, PARESIS, SECONDARY
Descriptive statistical analysis will be carried out to evaluate randomization groups in terms of demographic, and initial clinical and kinematic characteristics, including PFP cause, delay since injury, side of paresis, previous drug treatments, and comorbidities. Quantitative data will be described using means (± SD) or medians (with IQR), depending on the normality of distributions, and qualitative data will be reported as numbers or percentages.Changes in the Sunnybrook Composite score between D1 and D180 will be evaluated by Student’s Comparative analysis of binary parameters will be run through Chi-square or Fisher’s exact tests, depending on conditions. Multivariable analysis will be generated through logistic regression models. Intra- and inter-rater reliability studies will use frequencies of agreement, intraclass correlation coefficients, Cohen and Fleiss kappa coefficients and coefficients of variation. Spearman or Pearson coefficients will be calculated between scores on the various scales, depending on conditions. Complementary analyses on the primary outcome and all analyses regarding secondary outcomes will be performed in both ITT and per protocol (PP) populations to describe the excluded patients of the PP population and to evaluate the robustness of the results.All missing or invalid data will be systematically sought for verification in patient charts. In addition to the analysis performed on complete cases without missing data for the primary outcome, sensitivity analysis will be performed using various methods of replacement of missing data, including the LOCF method (Last Observation Carry Forward), the worst-case assumption, and multiple account assignment by chained equations (MICE). Participants who terminate the study prematurely will not be replaced. All analyzes will be performed with Stata software v14.1 (StataCorp, College Station, TX, USA).