Statistical Analysis
The statistical software package SAS 9.4 (SAS Institute Inc., Cary, North Carolina) was utilized for the analyses, which accounted for the complex survey design and clustering. Since NIS represents a 20% stratified random sample of US hospitals, analyses were performed using hospital-level discharge weights provided by the NIS to obtain national estimates of arrhythmia associated with HIV hospitalizations. For categorical variables such as annual change in HIV hospitalization rate and in-hospital mortality, the modified chi-squared test of trend for proportions (Cochrane Armitage test) was used21. For continuous variable such as LOS and cost of care, simple linear regression was used. Multivariable models for predictors of arrhythmia were performed with independent variables which were either clinically significant or statistically significant in univariate model. Multivariate model included patient-level variables such as age and gender; year of admission, admission type (elective vs non-elective),day of admission (weekdays vs weekend), primary payer (private insurance [including Health Maintenance Organization] and self-pay versus Medicaid/Medicare); co-morbidities such as diabetes mellitus, chronic lung disease, peripheral vascular disease etc.; hospital course requiring ICD implantation, use of vasopressors, cardiac catheterization, endotracheal intubation and CPR; A two-sided p-value < 0.05 was considered statistically significant.