Statistical methods
We retrieved the following individual patient data from each database:
age, gender, resting systolic and diastolic blood pressure (SBP and
DBP), heart rate (HR), and use of antihypertensive drugs for
hypertension. The data were subsequently merged into one study
population. Continuous data are shown as mean ± standard deviation,
whereas frequencies are used to describe categorical data. The method of
Kolmogorov and Smirnov was used to check the normality of distributions.
Continuous variables were compared by means of the paired Student’s
t-test. Paired and multiple proportions were compared by means of
Pearson’s chi-square test. Stepwise multiple regression analysis was
used to identify the independent factors predicting TT positivity.
Multivariable logistic regression was adjusted for age, gender, SBP, and
HR, whereas presence of hypertension was adjusted for age, gender and HR
only. Analyses were performed using the Statistical Analysis System
Software (version 9.4; SAS Institute, Cary, NC, USA) and IBM SPSS
Statistics software version 26.0 (SPSS Inc., Chicago, IL, USA).
Statistical significance was set at the 0.05 level and all p-values were
two-sided.