Abstract 4361269: Predictors of Mortality Among Hospitalized Patients with Repaired Congenital Heart Defects Following Catheter Ablation Procedures

Abstract

Background: Repaired congenital heart defects poses an increased risk of mortality in patients undergoing catheter ablation. However, there is limited data on the factors associated with mortality in these patient population. We examined the predictors of mortality among hospitalized patients with repaired congenital heart defects following catheter ablation procedures. Objective: To examine the predictors of mortality among hospitalized patients with repaired congenital heart defects following catheter ablation procedures. Methods: Retrospective cohort analyses were conducted using data from the National Inpatient Sample (NIS) collected between 2016 and 2020. Multivariate logistic and linear regression modelling was used to examine the factors associated with mortality among hospitalized patients with associated repaired congenital heart defects following catheter ablation procedure. Results: In the adjusted analyses, age 65 years and above (AOR: 1.60; 95% Cl: 1.20-2.58) was associated with higher odds of mortality compared to being less than 65. Participants with longer hospital stay (AOR: 2.80; 95% Cl: 1.40-3.90) and higher comorbidity scores (AOR: 2.80; 95% Cl: 1.50-4.80) were more likely to die relative to those with shorter hospital stay and lower comorbidity scores respectively. Conversely, females (AOR: 0.65; 95% Cl: 0.32-0.95) admitted electively (AOR: 0.40; 95% Cl: 0.20-0.90) had lower risk of death than males admitted non-electively. Finally, being non-Hispanic black (AOR: 2.50; 95% Cl: 1.80-3.40) and Hispanic (AOR: 2.40; 95% Cl: 1.20-3.60) were associated with higher odds of mortality compared to non- Hispanic Whites. Conclusion: Patient and hospital-related factors associated with higher odds of mortality among hospitalized patients with repaired congenital heart defects following catheter ablation were highlighted in this study. These identified predictors of mortality will assist clinicians in identifying high risk patients.