Spss version 23.0 statistical package

Normal distribution of continuous data was assessed using a one-sample Kolmogorov-Smirnov test. Normally distributed variables were reported as mean and standard deviation, whereas non-normally distributed variables were described as median and interquartile range (IQR). Pearson’s chi-square test or Fisher’s exact test were used to compare proportions between groups, as appropriate. The Student’s t-test and the Mann-Whitney U test were employed to determine the differences between normally distributed and non-normally distributed variables, respectively. A logistic regression analysis was performed to estimate the odds ratio (OR) and 95% confidence interval (95% CI) of the likelihood of zinc deficiency. A twosided P-value of less than 0.05 was considered statistically significant. Statistical analysis was performed using SPSS version 23.0 statistical package (SPSS, Chicago, IL, USA).

Continuous variables were presented as means and standard deviations. Comparison of continuous variables was performed using an independent t test or, in case of a non‐normal distribution, the Mann–Whitney test. Categorical variables were represented with numbers and percentages using the Chi‐square test of Fisher exact test. Incidence rates were estimated using the total number of study outcomes during the follow‐up period divided by person‐years at risk. The risk for clinical outcomes for study groups were obtained using survival analysis (Kaplan–Meier method and log‐rank test for univariate analysis and Cox proportional hazards regression for multivariate analysis). Cox proportional hazards regression was used to estimate the unadjusted and adjusted hazard ratio for the association between label adherence of NOAC dosing and clinical outcomes. To control for confounding, we added age, sex, chronic kidney disease, dyslipidemia, and other risk factors included in CHA₂DS₂‐VASc risk score factors (heart failure, hypertension, diabetes mellitus, stroke or transient ischemic attack, and vascular disease) to our multivariable models. Statistical significance was indicated by a P<0.05. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC) and SPSS version 23.0 statistical package (SPSS Inc., Chicago, IL, USA).

A one-sample Kolmogorov–Smirnov test was used to assess whether the variables were normally distributed. Normally distributed variables were described as means and standard deviations; nonnormally distributed variables were presented as medians and interquartile ranges. The Pearson's Chi-square or Fisher's exact test was used to compare proportions between groups, as appropriate. The Student's t-test and Mann–Whitney U-test were used to verify the differences of normally distributed and nonnormally distributed variables, respectively. The change in serum zinc levels from baseline was assessed by a paired t-test and presented as mean and 95% confidence interval (CI). P < 0.05 was considered as statistically significant. Data were analyzed using SPSS version 23.0 statistical package (SPSS, Chicago, IL, USA).