Statistical analysis
DM, adrenal incidentalomas, hypertension
ADRENAL INCIDENTALOMA, CORONARY HEART DISEASE, REGRESSION, HYPERTENSION, DYSLIPIDEMIA
Results are summarized as means ± SD for continuous variables and percentages for categorical variables. Statistical significance was a probability value of < 0.05. The comparison of continuous variables was conducted using ANOVA with Tukey’s post hoc test. The comparison of categorical variables between groups was conducted using a chi-square test. The associations between variables were assessed by using Spearman’s correlation coefficients. Changes in parameters after administration of 1 mg dexamethasone were evaluated using the paired t-test. To create a matched cohort of patients with NFA who had hypertension and/or DM and patients without adrenal incidentalomas with hypertension and/or DM in protocol 1, a propensity score was computed for each patient by using logistic regression analysis to determine the probability of baseline clinical variables including age, sex, body mass index, hypertension, dyslipidemia, DM, current smokers, and precious coronary heart disease. To create a matched cohort of patients with NFA and patients without adrenal incidentalomas in protocol 2, a propensity score was computed for each patient by using logistic regression analysis to determine the probability of baseline clinical variables including age, sex, body mass index, hypertension, dyslipidemia, DM, current smokers and precious coronary heart disease. One-to-one propensity-score matching analyses were used to create matched pairs to investigate the associations of NFA with vascular function. With these propensity scores, two well-matched groups based on clinical characteristics were created with a caliper size specification (0.25 × SD of propensity score) for comparison of vascular function. Propensity-score matching analyses were used to reduce the effects of selection bias. To detect a 2.0% difference before and after administration of 1 mg dexamethasone with α of 0.05 and power 0.90, the total sample size requirement would exceed 14. We performed multiple imputations for incomplete data, since multiple imputations of missing data have been recommended to avoid potential bias in full case analysis due to missing values. The data were processed using JMP pro version 15 (SAS Institute. Cary, NC).