Zhang L, et al. - Given that socioeconomic status (SES) has been linked to adverse outcomes following cardiac surgery, researchers assessed whether aortic valve replacement (AVR) risk prediction models might be improved by inclusion of SES. For this purpose, they examined all patients undergoing AVR at a single institution from 2005 to 2015. Using models published by the Society for Thoracic Surgeons, they generated risk scores for mortality, complications and increased length of stay. They found that the area under the curve for mortality, for any complications and for prolonged length of stay (PLOS) in the multivariable models, was increased as a result of the inclusion of SES covariates. The inclusion of census-tract-level socioeconomic factors into the STS risk predication models was found to be a potentially useful approach to improve risk prediction for outcomes following cardiac surgery. This study not only introduced this novel approach but also potentially represents an improvement in risk prediction model.