Geographically Derived Socioeconomic Factors to Improve Risk Prediction in Patients Having Aortic Valve Replacement

Socioeconomic status (SES) has been associated with adverse outcomes after cardiac surgery, but is not included in commonly applied risk adjustment models. This study evaluates whether inclusion of SES improves aortic valve replacement (AVR) risk prediction models, as this is the most common elective operation performed at our institution during the study period. All patients who underwent AVR at a single institution from 2005 to 2015 were evaluated. SES measures included unemployment, poverty, household income, home value, educational attainment, housing density, and a validated SES index score. The risk scores for mortality, complications, and increased length of stay were generated using models published by the Society for Thoracic Surgeons. Univariate models were fitted for each SES covariate and multivariable models for mortality, any complication, and prolonged length of stay (PLOS). A total of 1,386 patients underwent AVR with a 2.7% mortality, 15.1% complication rate, and 9.7% PLOS. In univariate models, higher education was associated with decreased mortality (odds ratio [OR] 0.96, p = 0.04) and complications (OR 0.97, p