Statistical Analysis
REGRESSION
The first author (J.D.) was conducting statistical analyses and was not involved in performing the physical tests or collecting the VISA-P scores. Statistical analyses under intention to treat were performed. Normality tests were performed by visual check using histograms or normal Q-Q plots and also assessed by the Shapiro-Wilk test. Estimated means and standard deviations were reported for continuous variables with normal distribution. Otherwise, medians and interquartile ranges were used. We performed a 2-sample We used a linear mixed-effect model to evaluate the change in clinical symptoms (VISA-P score) and physical test results in both groups over 24 weeks. The fixed-effect included time, study arms, baseline clinical characteristics (symptom duration and sports activity [Cincinnati Sports Activity Scale]),Linear regression models were used to assess the association between the change in physical test results and the change in VISA-P score over 24 weeks. In addition, we further dichotomized the change in VISA-P score into clinical responsiveness (≥14 points) and nonresponsiveness (<14 points) by MCID, and logistic regression analyses were further used to assess whether these physical changes were associated with the occurrence of clinical responsiveness. All models were adjusted with the aforementioned baseline clinical predictors and additional baseline VISA-P score. In case of missing data in VISA-P scores or physical test results >5%, prediction linear mixed-effect models were used to impute missing values (Residuals were tested to investigate the assumptions of models. Collinearity and outliers were also tested for the linear regression model. In case of multiple testing, a Bonferroni correction method was used.