Objectives: With recent advances in left ventricular assist device (LVAD) technology, the utilization of LVADs has increased while mortality, cost, and length of stay (LOS) have significantly decreased. This study sought to determine the national trends of surgically implanted biventricular assist devices (BiVADs). Methods: This is a retrospective analysis of the National Inpatient Sample (NIS) database for internal BiVADs (n = 538) and external BiVADs (n = 727) from 2009 to 2015. Results: Utilization of all surgically implanted BiVADs decreased (4.8% per year, p < 0.001), and was driven by a decline in utilization of external BiVADs (9.4% per year, p < 0.001). There was no significant change in BiVAD-associated mortality. However, cost and LOS increased significantly, and these trends were isolated to patients who died during their hospitalization. Patients with internal BiVADs incurred higher cost than external BiVAD patients but were more likely to survive. Conclusions: The decline in surgically implanted BiVAD utilization may be due to an improvement in LVAD technology as well as an increase in the availability of percutaneous temporary circulatory support. Future prospective studies are needed to compare various BiVAD configuration strategies and to optimize BiVAD patient selection and perioperative care.

Objective To analyze the incidence, predictors, and cost of 30-day left atrial appendage closure readmissions utilizing the Nationwide Readmissions Database (NRD) and to develop a scoring system to predict readmission risk. Background Determining incidence and predictors of 30-day readmission post-left atrial appendage closure can direct resources towards high-risk patients. Methods International Classification of Diseases, Tenth Revision (ICD-10) codes were used to identify patients. We excluded patients who were discharged or died in December 2016. Influential factors were identified by univariate analysis and clinical suspicion. Continuous variables were compared using the Student’s T-test and categorical variables were compared using chi-square or Fisher’s exact test. A logistic regression model and scoring system were developed and validated. Results 2975 patients were identified and 243 (8.2%) readmitted within 30 days. Non-routine disposition (p<0.0001), chronic pulmonary disease (p=0.0003), renal disease (p<0.0001), and anemia (p=0.009) were significant predictors of readmission. Readmitted patients had longer lengths of stay (2.8 days ± 4.8) and higher charges ($139,869.3 ± 94,574.3). Average length of stay and cost for rehospitalizations were 4.8 days ±4.9 and $62,577± 85,850. Top causes of readmission included atrial fibrillation, atrial flutter, congestive heart failure, sepsis and gastrointestinal bleeding. Mortality during rehospitalization was 1.2%. Our scoring system had a C-statistic of 0.679 (derivation) and 0.633 (validation). Conclusion Readmitted patients have longer and more expensive initial hospital admissions, and chronic cardiac, pulmonary, and renal issues. A simple scoring system may identify patients at risk for readmission