349. Distressed Communities Are Associated with Worse Outcomes After Coronary Artery Bypass Surgery: Nationwide Analysis from the STS Database
J. Hunter Mehaffey1, Robert B. Hawkins1, Eric J. Charles1, Dylan Thibault2, Matthew L. Williams3, Matthew Brennen2, *Vinay Badhwar4, *Gorav Ailawadi1
1University of Virginia, Charlottesville, VA;2Duke Clinical Research Institute, Durham, NC;3University of Pennsylvania, Philadelphia, VA;4West Virginia University, Morgantown, WV
Invited Discussant: *Thomas V. Bilfinger
Objective: While low socioeconomic status has been associated with increased risk of complications after cardiac surgery, analyses have typically focused on insurance status, race or median income. We sought to determine if the Distressed Communities Index (DCI), a composite socioeconomic ranking by zip code, could predict operative mortality following coronary artery bypass grafting (CABG).
Methods: All patients who underwent isolated CABG (2011-2018) in the national Society of Thoracic Surgeons (STS) adult cardiac surgery database were analyzed. Clinical data were paired with the DCI, which accounts for unemployment, education level, poverty rate, median income, business growth, and housing vacancies. Developed by the Economic Innovation Group, DCI scores range from 0 (no distress) to 100 (severe distress). Patients were stratified into distressed (DCI≥75) or not (DCI<75). Hierarchical logistic regression modeled the association between DCI and outcomes adjusting for STS risk. Net Reclassification Improvement (NRI) was used to assess the impact of DCI on the STS risk model.
Results: Of the 575,900 CABG patients had a DCI score; the median age was 65 years. The operative mortality rate was 2.0%, and composite morbidity or mortality rate was 11.5%. Higher DCI scores were associated with increasing STS predicted risk of mortality (Distressed 1.97% vs 1.85%, p<0.0001), and risk of composite morbidity or mortality (Distressed 12.8% vs 11.7%, p<0.0001). Importantly, after risk adjustment for STS predicted risk Distressed Community remained significantly associated with mortality (OR 1.12 95% CI 1.07, 1.17, p<0.0001) and composite morbidity and mortality (OR 1.03, 95%CI 1.01, 1.05, p<0.0001), suggesting unmeasured factors by traditional risk scores. NRI demonstrated addition of Distressed Community to the STS mortality model correctly reclassified 46% of events and 52% of non-events (p=0.002) while addition to the composite morbidity or mortality model correctly reclassified 48% of events and 53% of non-events (p=0.002).
Conclusions: Increasing Distressed Communities Index, an established composite metric for community level socioeconomic distress, is independently associated with morbidity and mortality in CABG patients. Patients from distressed communities have greater risk than traditional risk calculators would predict. The DCI may provide a more holistic assessment of socioeconomic status and should be considered when building risk models, evaluating resource utilization and comparing hospitals.