*2.4. Statistical Analysis*

All results for categorical variables were presented as numbers and percentages and, for continuous variables, as mean and standard deviation (SD) or median and quartiles (Q1:25th–Q2:75th percentiles). The Fisher exact test was used for comparison of categorical variables. The differences between continuous variables were tested by Student's t-test (for two independent samples and for paired observation, normally distributed data) or, in the case of irregular distribution, nonparametric Mann–Whitney and paired signed rank tests. A receiver-operating characteristic curve (ROC) analysis was used to assess the cutoff point of the markers for the prediction of events (supplementary Figure S1). The optimal cutoff was defined as the value with the maximal sum of sensitivity and specificity. Event analysis over time was made by using the univariable and multiple Cox proportional-hazards regression model. In order to indicate independent predictors of events, the stepwise variable selection procedure was used. Risk was quantified as a hazard ratio with 95% confidence interval (CI). Survival curves were constructed by the Kaplan–Meier method and compared by the log-rank test. We used two different start points for the time-to-event analysis: from the first cardiologic assessment in our centre and from date of birth to assess life-time risk. In subjects without an event, the follow-up period extended to the most recent evaluation or the date of July 31st, 2019. All hypotheses were two-tailed with a 0.05 type I error. All statistical analyses were performed using SAS statistical software, version 9.4 (SAS Institute, Cary, NC, USA) and Statistica v16.

#### **3. Results**
