Impact of pre-existing cardiovascular disease on inpatient arrhythmias following autologous stem cell transplantation in multiple myeloma: A national inpatient sample database analysis

Abstract Introduction: Autologous stem cell transplantation (ASCT) continues to be a cornerstone in the treatment of eligible patients with multiple myeloma (MM). Cardiac safety of ASCT in real-world populations continues to be a concern, especially in older and frail populations. Cardiotoxicity from melphalan conditioning, volume shifts, and stress-induced myocardial events may occur in vulnerable and frail patients. The goal of this study is to evaluate the impact of pre-existing cardiovascular disease (CVD) on inpatient outcomes following ASCT in MM. Methods We conducted a retrospective analysis using the National Inpatient Sample (NIS) database from 2016 to 2022 to identify adult patients with MM who underwent ASCT and had pre-existing CVD. Pre-existing CVD was identified using ICD-10 codes, encompassing congestive heart failure (CHF), coronary artery disease (CAD), atrial fibrillation (AFib), valvular heart disease, conduction disorders, and cardiac arrest. Patients with missing key demographic data were excluded from the analysis. The patients were stratified based on the presence or absence of pre-existing cardiac comorbidities. The primary outcome was the development of any new cardiac event. Firth's penalized logistic regression addressed small-sample bias, and Lasso regression was applied to validate model selection using 10-fold cross-validation. Secondary outcomes included length of stay (LOS), total hospitalization cost, and discharge disposition. Multivariable linear regression models were adjusted using robust and bootstrapped standard errors. Results A total of 58 MM patients who met the inclusion criteria were identified. The mean age was higher among those with cardiac comorbidities (63.3 ± 5.1) than those without (56.2 ± 10.8). The cohort was predominantly White (70.7%), followed by Black (20.7%) and Hispanic (5.2%). Pre-existing cardiac comorbidities were identified in 21% of patients (n=12), 66% of this group were male. Among patients with prior cardiac disease, atrial fibrillation (13.8%) and coronary artery disease (CAD) (6.9%) were the predominant cardiac conditions, followed by valvular heart disease and conduction disorders. No cases of CHF or cardiac arrest were recorded. The presence of any cardiac comorbidity was strongly associated with an increase in in-hospital arrhythmias (66.7% vs. 2.2%, p < 0.001). In the multivariate Firth logistic regression model, a composite cardiac diagnosis was associated with markedly higher odds of arrhythmia (OR 53.9, 95% CI 5.7–509.5; p= 0.001). Specifically, CAD alone was associated with an increased odds of arrhythmia (OR 24.0, 95% CI 2.1–269.1; p= 0.010). Female sex was associated with a borderline p-value (0.053), indicating a potential trend toward increased arrhythmia risk in males. Age and race were not independently associated with arrhythmia. Despite this risk, cardiac comorbidities were not associated with a longer LOS (15.6 vs. 16.0 days; p = 0.385) or higher hospitalization costs. Interestingly, patients with cardiac comorbidities had lower average charges and lower variability ($185,637 ± 87,044 vs. $224,968 ± 158,260). All patients with cardiac disease were discharged home (100%) compared to 93% in the non-cardiac group. Of note, no deaths related to new cardiac events were reported. All patients were treated in a metropolitan teaching hospital, of which 70% were treated at large institutions. Conclusion Our study shows that although pre-existing cardiac comorbidities, particularly AFib and CAD, were associated with a significantly higher risk of inpatient arrhythmias (66.7% vs. 2.2%), these adverse cardiac events did not translate to an increased LOS, cost of care, or non-home discharge. This may suggest that current patient selection for transplant eligibility effectively mitigates poor outcomes, even in this high-risk population. A key limitation was our small cohort size, which may have led to inflated estimates despite using a large national database. Nevertheless, using Firth and Lasso regression improves confidence in our model selection. These findings may suggest the use of individualized pre-ASCT cardiac risk stratification over categorical exclusion for older patients with pre-existing CVD. Future prospective studies in larger, multicenter populations are needed to validate these findings.