Statistical analysis
Categorical variables summarized as frequency and percentage. Continuous variables were evaluated for normal distribution using histograms and Q-Q plots and reported as median and interquartile range. Independent samples T-test and Mann-Whitney test were applied to compare between patients with and without new arrhythmia. Chi-square test and Fisher’s exact test were used to compare categorical variables. Multi variate Logistic regression using forward stepwise (likelihood ratio) selection method (p<0.05 was used as criteria for inclusion) was used to explore variables associated with new arrhythmia. Variables available for inclusion were: age, gender, BMI, history of HTN, DM, IHD, CHF, valvular heart disease, lung disease, presentation with syncope or palpitations, past arrhythmia, and COVID-19 illness severity. Classification trees were applied to identify subgroup of patients that are in increased risk for arrhythmia. Classification and Regression Tree (CART) and Chi-square Automatic Interaction Detection (CHAID) growing algorithms were used. The following variables were available for the classification trees: age, gender, previous history of HTN, DM, IHD, CHF, valvular heart disease, lung disease, presentation with syncope or palpitations, past arrhythmia, and COVID-19 illness severity. A second model included also hsTnI and CRP levels. All statistical tests were 2 sided and p< 0.05 was considered statistically significant. SPSS software was used for all statistical analyses (IBM SPSS statistics for windows, version 24, IBM cooperation, Armonk, NY, USA, 2016).
The study was approved by the hospital ethical committee.