Abstract 4143095: Rural-Urban Disparities in Heart Transplant Outcomes for Heart Failure Patients: An Analysis of the National Inpatient Sample Dataset

Background: Disparities in healthcare outcomes between rural and urban populations are well-documented, yet limited research specifically addresses differences in heart transplant outcomes for heart failure patients. Methods: We conducted a retrospective cohort study using the NIS dataset (2017-2020), analyzing 11,025 heart failure patients who received heart transplants. The cohort included 565 rural and 10,460 urban patients. We examined variables such as age, gender, hospital bed size, race, insurance status, and comorbidities. Primary outcomes included in-hospital mortality, mechanical ventilation requirement, length of stay, hospital charges, and vasopressor requirement. Multivariate logistic regression was performed to identify independent predictors of in-hospital mortality. Results: Age was found to be a significant predictor, with each additional year increasing the risk of mortality (OR 1.026, 95% CI 1.017-1.034, p < 0.0001). Hospital bed size also played a critical role; patients in small hospitals had a significantly higher risk of mortality compared to those in large hospitals (OR 3.309, 95% CI 2.101-5.212, p < 0.0001), whereas patients in medium-sized hospitals had a lower risk (OR 0.374, 95% CI 0.236-0.592, p < 0.0001). While rural residency was associated with a higher mortality risk compared to urban residency, this association was not statistically significant (OR 1.40, 95% CI 0.95-2.07, p = 0.0860). Other factors, including the adjusted odds of vasopressor requirement (OR 1.13, 95% CI 0.92-1.39, p = 0.2524), need for mechanical ventilation (OR 1.12, 95% CI 0.87-1.43, p = 0.3741), length of stay (difference -0.005, 95% CI -8.57-1.33, p = 0.1709), and pacemaker insertion (OR 0.81, 95% CI 0.65-1.01, p = 0.062), did not show significant differences between groups. Conclusion: This study reveals that clinical outcomes post-heart transplant are comparable between patients in rural and urban settings. However, age and hospital bed size significantly influence mortality risk, with older age and treatment in smaller hospitals associated with higher mortality rates.