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.