Statistical analysis

Assuming an 80% prevalence of ED in the hypomagnesemia group and 65% prevalence in the normomagnesemia group, we found that a sample size of 368 (184 per group) patients would be required to detect a statistically significant difference with power of 90% (α=0.05). The primary study end point was the prevalence of ED. Secondary end points included severity and risk factors of ED. Comparisons of continuous variables between groups were made using Student’s t-test for normally distributed data and the Mann–Whitney U-test for non-normally distributed data. Within-subject comparisons of continuous variables were made using a paired t-test or the Wilcoxon signed-rank test for normally and non-normally distributed data, respectively. Categorical variables were analyzed using the chi-square test or alternatively Fisher’s exact test. We performed logistic regression with the presence of ED as the dependent variable and the following 11 parameters as potential covariates: presence of hypomagnesemia, age ≥70 years, hypertension, smoking, high urine P/C ratio (≥500 mg/dL), high CRP (>5 mg/L), abdominal obesity, metabolic syndrome, eGFR ≤30 mL/min/1.73 m², low HDL-C (<40 mg/dL), and serum albumin levels. Variables that were statistically significant on univariate analysis were included in the multivariate model to identify predictors of ED. A two-sided 95% confidence interval (CI) was constructed around the point estimate of the relative risk (RR). Receiver operating characteristic (ROC) curve analyses of serum magnesium levels for the prediction of ED and the positive and negative predictive values of magnesium were performed. All tests were two-sided, and a P-value of <0.05 was considered to be statistically significant. Continuous data are reported as mean ± standard deviation. Categorical data are presented as absolute values and percentages. Analyses were performed using IBM SPSS Statistics Version 20.0 (IBM Corporation, Armonk, NY, USA).