Statistical Analysis
As recommended by the Agency for Healthcare Research and Quality, weighted data were used for all statistical analyses. Temporal trends in LVAD utilization as well as post-LVAD mortality were assessed using the average annual growth rate formula. Baseline characteristics and post-LVAD outcomes were compared using the Pearson Chi-Squared (χ2) tests for categorical variables, independent samples T-test for parametric continuous variables, and Mann-Whitney U test for non-parametric continuous variables. We considered statistical significance when p value was below 0.001. Categorical variables of interest included hypertension (HTN), diabetes mellitus (DM), malnutrition, coronary artery disease (CAD), atrial tachyarrhythmias (Atach) which include atrial fibrillation and atrial flutter, peripheral arterial disease (PAD), chronic kidney disease (CKD), history tobacco use, history of stroke, dyslipidemia, and chronic liver disease (CLD). Continuous variables of interest included mean age, total cost of hospitalization, and hospital length of stay. NIS provides median household income for patient’s ZIP code divided by percentile. High-income patients were considered between the 51stto 100th percentile and low-income individuals were considered between 0 to 50th percentile. The association between income and post-LVAD mortality was analyzed using multivariable logistic regression. All multivariable regression models were created using generalized estimating equations. Missing data for race were handled using multiple imputation as recommended by Healthcare Cost and Utilization Project. Missing primary payer status in patients 65 years old or older was imputed to Medicare, whereas missing data for all other variables were imputed to the dominant category (See supplemental material). All statistical analyses were performed using SPSS (IBM SPSS Statistics for Mac, Version 23.0. Armonk, NY: IBM Corp.).