Atrial Fibrillation Is Associated with Increased In-Hospitality Mortality During Chimeric Antigen Receptor T-cell Therapy Hospitalizations: A Retrospective Cohort Study in the United States. 

Atrial Fibrillation Is Associated with Increased In-Hospitality Mortality During Chimeric Antigen Receptor T-cell Therapy Hospitalizations: A Retrospective Cohort Study in the United States. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Atrial Fibrillation Is Associated with Increased In-Hospitality Mortality During Chimeric Antigen Receptor T-cell Therapy Hospitalizations: A Retrospective Cohort Study in the United States. Nischit Baral, Nabin R. Karki, Daniel A. Ladin, Raja Zaghlol, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4931828/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Jul, 2025 Read the published version in Cardio-Oncology → Version 1 posted 9 You are reading this latest preprint version Abstract Background: Chimeric Antigen Receptor (CAR) T-cell therapy (CAR-T) has emerged as a promising treatment for specific hematological malignancies. While some studies suggest an association between CAR-T and atrial fibrillation (AF), more data are needed on the impact of AF on CAR-T outcomes. Methods: This retrospective cohort study utilized the National Inpatient Sample (NIS) 2017-2020 to explore in-hospital outcomes in cancer patients with AF while undergoing CAR-T. Comparisons were drawn between patients with and without AF (occurring at any time), assessing various parameters including mortality rates, length of hospital-stay, and occurrences of acute heart failure, pulmonary edema, and gastrointestinal (GI) bleeding. Results: Of the 236,270 cancer-related hospitalizations, 1,030 cases (0.44%) received CAR-T. The average age of CAR-T recipients was 55.6 years ±18.1 years, and females constituted 40.5% of the total CAR-T recipients. Of the 1030 patients receiving CAR-T, 97 (9.4%) had an associated diagnosis of AF (occurring at any time) during their hospitalization. A multivariable logistic regression analysis, adjusted for age, sex, race, comorbidity, and income, revealed that cancer hospitalizations who underwent CAR-T therapy with AF had increased odds of in-hospital mortality (adjusted odds ratio, aOR: 3.87), acute pulmonary edema (aOR: 3.29), GI bleeding (aOR: 5.46), acute heart failure (aOR: 10.2), and extended hospital stays (Beta coefficient: 0.18) compared to hospitalizations with CAR-T but without AF. Similar results were seen in a sensitivity analysis limited to diffuse large B cell lymphoma patients receiving CAR-T. Conclusions: In cancer patients receiving CAR-T, AF is independently associated with a higher risk of in-hospital mortality, acute pulmonary edema, gastrointestinal bleeding, acute heart failure, and prolonged hospitalization. Chimeric Antigen Receptor T-cell therapy Atrial fibrillation Cohort Study In-hospital Mortality Cardiovascular disease Cancer Figures Figure 1 Figure 2 Background Over the last decade, Chimeric Antigen Receptor (CAR) T-cell therapy (CAR-T) has emerged as a revolutionary tool for cancer treatment. In its original design, a CAR was composed of an antibody-derived single-chain variable fragment (scFv) fused to the T-cell receptor (TCR) signaling domain, intended to redirect T-cells to target solid tumors and human deficiency virus (HIV).( 1 , 2 ) With time, the design of CAR T-cells evolved to include costimulatory domains and improved ex vivo culturing methodologies.( 1 ) The first successful clinical reports of CAR-T were in patients with chronic lymphocytic leukemia (CLL) and non-Hodgkin lymphoma (NHL), using patient-derived autologous CAR T-cells directed against CD19 (CART19).( 3 , 4 ) In 2017, the Food and Drug Administration (FDA) approved tisagenlecleucel and axicabtagene ciloleucel for the treatment of relapsing/refractory diffuse B-ALL (B-acute lymphoblastic leukemia) and diffuse large B-cell lymphoma (DLBCL). Despite its therapeutic promise, CAR-T may have potential life-threatening adverse events, including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). In addition, cardiotoxicity affects up to 26% of cancer patients who undergo CAR-T.( 5 ) Cardiotoxicity may share pathophysiological pathways overlapping with CRS and ICANS. CRS is associated with various cardiovascular manifestations, including arrhythmias, heart failure, cardiogenic shock, and cardiomyopathies.( 6 ) In a recent retrospective study, atrial fibrillation (AF) was the most common arrhythmia in CAR-T recipients.( 7 ) However, there is a paucity of data on whether AF is associated with higher mortality and other adverse clinical outcomes in CAR-T recipients hospitalized in the US. Our study aims to investigate the association between CAR-T and AF in the National Inpatient Sample (NIS), including potential correlations between AF and in-hospital outcomes in this cancer population. Methods This retrospective, population-based cohort observational study drew from all hospitalizations in the NIS from January 1, 2017, to December 31, 2020, the most current data available. NIS is the largest inpatient database in the United States and allows for analyzing rare treatments such as CAR-T. The NIS was developed for the Healthcare Cost and Utilization Project (HCUP; www.hcup-us.ahrq.gov ) and the Agency for Healthcare Research and Quality (AHRQ) to estimate inpatient utilization, access, cost quality and in-hospital outcomes.( 8 ) The publicly available, all-payer, inpatient database contains de-identified data from more than seven million hospital stays annually.( 8 ) For this analysis of the NIS, we followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement for reporting observational studies.( 9 ) The study was exempt from local Institutional Review Board (IRB) review given the de-identified nature of the data. We first identified all NIS hospitalizations containing a cancer diagnosis (including principal as well as secondary diagnoses) with a Food and Drug Administration (FDA) approved indication for CAR-T.( 10 , 11 ) Cancers eligible for inclusion were selected using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and consisted of DLCBL, B-cell precursor acute lymphoblastic leukemia, follicular lymphoma, mantle cell lymphoma, and multiple myeloma ( Supplementary Table 1 ).( 11 ) Among these eligible hospitalizations, ICD-10 procedure codes identified patients undergoing CAR-T ( Supplementary Table 1 ). Eligible patients were further divided by the presence or absence of AF or atrial flutter (principal or secondary diagnosis) at any time by ICD-10-CM codes I48.0, I48.1, I48.2, I48.3, I48.4, I48.91, and I48.92. Notably, the NIS does not include patients receiving CAR-T in clinical trials or outpatient infusion clinics, and these patients were naturally excluded. We collected patient demographics for each hospital stay including age, sex, race, median household income by zip code, hospital region, hospital bed size, and insurance status. Patient comorbidity status was assessed using the Charlson Comorbidity Index (CCI), a point-based system with values of 0, 1, 2 or ≥ 3 representing no, mild, moderate, and severe comorbid burden, respectively.( 12 ) The primary outcome for the study was in-hospital mortality. Secondary outcomes were length of hospital stay as well as the occurrence of in-hospital gastrointestinal bleeding, pulmonary edema, and/or acute heart failure. These outcomes were identified using ICD-10-CM codes found in any principal or secondary diagnosis field.( 8 ) The ICD-10-CM diagnosis and ICD-10 procedure codes used for the study are shown in Supplementary Table 1 . We evaluated differences between CAR-T patients with and without AF using Chi-squared or Fisher's exact tests for categorical variables (e.g., sex, in-hospital mortality, race, comorbidity index categories), and Student’s t-test for the length of stay (LOS). Univariable logistic regression models assessed the association by odds ratio with AF and outcomes (i.e., in-hospital mortality) as well as other baseline socio-demographics and comorbidities that have been associated with in-hospital mortality (e.g., age, sex obtained from medical records as male or female assigned at birth, race, comorbidity index, hospital bed size, hospital region, hospital teaching status, and household income national quartiles). Variables with a p -value of ≤ 0.20 in the unadjusted weighted univariate regressions were subsequently included in a multivariable logistic regression model.( 13 ) Age and sex were included into the multivariable regression model independent of the univariable regression model due to the significance of these variables in our primary and secondary outcomes of interest.( 13 ) Additional multivariable logistic regression models tested the independent association of atrial fibrillation with secondary outcomes using the same covariates. For length of stay (LOS), we used negative binomial regression to assess association (by beta coefficient) of AF with LOS, after an evaluation of the dispersion of LOS variable in the histogram showed over-dispersed data for the LOS in days. We defined survey parameters (weight, strata, and stratum) to account for the NIS complex survey sampling methods.( 8 ) This study addressed the potential for misclassification bias by using ICD-10 codes validated in prior studies as well as codes used in prior published papers.( 14 – 18 ) The multiple imputation method was planned for imputed missing data if more than ten percent of variables were missing.( 19 ) Since differences among cancer types could add variation into study findings, we performed a sensitivity analysis in the subgroup of patients with diffuse large B-cell lymphoma which constituted 70% of the patients receiving CAR-T. For reference, descriptive statistics were employed to report cardiovascular and bleeding diagnoses associated with all hospitalizations, with and without CAR-T, among the patients with cancers with an FDA approved indication for CAR-T. Only descriptive statistics are reported, given potential variations in hospitalization indications. (All CAR T-cell therapy admissions would be expected to be specifically for CAR T-cell therapy, while other hospitalizations may have been for indications unrelated to cancer treatment such as sepsis.) In this analysis, we stressed the precision of the study estimates, focusing on 95% confidence intervals. P -values are presented to aid interpretation. All analyses were performed with STATA 17.0 (Stata-Corp LP, College Station, Texas). Results Among the 236,270 hospitalizations involving CAR-T approved cancer subtypes (DLBCL, multiple myeloma, follicular lymphoma, mantle cell lymphoma, and acute lymphoblastic leukemia), 1,030 (0.44%) hospitalizations involved administration of CAR-T between January 1, 2017, and December 31, 2020 ( Figure 1, Supplementary Table 2 ). These 1030 unweighted hospitalizations represented approximately 4670 records after applying weights for national estimates. CAR-T hospitalizations steadily rose from 2017-2020 ( Figure 2, Supplementary Table 2 ). DLBCL accounted for 70% of patients receiving CAR-T. Among the 1030 unweighted hospitalizations, 43 records were missing race, 45 records were missing income quartiles, and 8 records were missing insurance status. (Multiple imputations were not indicated per the statistical plan, as the total records with missing variables were less than ten percent.) Of the 1030 patients receiving CAR-T (mean age 55.6±18.1 years), 97 (9.4%) had an associated diagnosis of AF during their hospitalization. Compared to CAR-T patients without AF, those with AF were found to be older (mean age 68 vs. 54 years, p <0.001), more likely to be male (42% vs. 22%, p <0.001), more likely to be Caucasian (84% vs. 70%, p <0.001), have Medicare (57% vs. 30%, p <0.001), and have a higher prevalence of 3 or more comorbidities (59% vs. 38%, p <0.001) ( Table 1 ). Compared to the CAR-T without AF, CAR-T with AF was associated with higher prevalence of hypertension (56.7% vs 36.6%, p <0.001), hypotension (35% vs 28%, p =0.157), chronic heart failure (24.7% vs 7%, p <0.001), and coronary artery disease (18.6% vs 5%, p <0.001) as shown in Table 2 . The prevalence of supraventricular arrhythmia, acute heart failure, pulmonary edema, acute myocardial infarction, gastrointestinal bleed, and disseminated intravascular coagulation were also more common in the CAR-T with AF group compared to CART without AF group. However, we were unable to report the number and percentages in these variables due to low frequencies. In the table, frequencies less than 11 are not specifically reported as per the data reporting and publishing policy of HCUP.(6, 12) Univariable logistic regression models assessed the associations of in-hospital mortality in CAR-T admissions with age, sex, atrial fibrillation, race, hospital region, hospital bed size, household income, year, Charlson comorbidity, and insurance status ( Table 3 ). Atrial fibrillation and Charlson comorbidity index were both associated with increased in-hospital mortality. A multivariable model ( Table 3 ) analyzed the independent association of AF with hospitalization after adjusting for age, sex, race, household income, and Charlson comorbidity (included in the model given univariable p -values were £ 0.20). The adjusted odds of in-hospital mortality (the primary outcome) were more than three times higher in the group of CAR-T recipients with AF compared to the CAR-T group without AF (aOR: 3.87, 95% CI: 1.61, 9.30, p =0.003) ( Tables 3 and 4 ). Similar multivariable regression models were used for the secondary outcomes with the exception of length of stay, which was evaluated with negative binomial regression. The adjusted odds of pulmonary edema were more than three times higher (aOR: 3.29, 95% CI: 1.34, 8.09, p =0.010), adjusted odds of gastrointestinal bleed were more than five times higher (aOR: 5.46, 95% CI: 1.95, 15.29, p =0.001), and adjusted odds of acute heart failure more than ten times higher (aOR: 10.20, 95% CI: 2.15, 47.95, p =0.003) in CAR-T with AF compared to CAR-T without AF ( Table 4 ). Length of stay was longer in CAR-T with AF versus without AF (mean length of stay 20.5 days vs 7.5 days, p <0.001, adjusted beta co-efficient 0.18, 95% CI: 0.01, 0.36, p =0.045) as also shown in Table 4 . The demographics, cancer types and in-hospital CV and bleeding diagnosis associated with CAR-T vs non-CAR-T in the five FDA approved cancer types are reported for reference. Only descriptive statistics are used given the potential differences in hospitalization indications in patients not receiving CAR-T. Among the 236,270 hospitalizations with cancer subtypes where CAR-T is approved, only 0.4% of hospitalization included the administration of CAR-T. The majority of CAR-T admissions were in patients with DLBCL (70.2%) followed by acute lymphoblastic leukemia (12.3%), multiple myeloma (11.6%) and mantle cell lymphoma (2.2%). ( Supplementary Table 4 ). Compared to patients not receiving CAR-T, patients receiving CAR-T had numerically higher incidence of hypotension (28.6% vs. 8.1%), ventricular tachycardia (3.2% vs. 1.5%), supraventricular tachycardia (3.4% vs. 1.8%), pulmonary edema (3.2% vs. 1.1%), mechanical ventilation requirement (4.4% vs 2.8%) and disseminated intravascular coagulation (3.7% vs. 2.4%). ( Supplementary Table 4 ). Since the ICD 10 diagnostic code for CRS was implemented in October, 2020, CRS could only be assessed after this date. CRS was diagnosed in 141 patients in the study cohort.(16) Among them, 21 patients (0.05%) developed CRS in the AF group compared to 120 patients (0.06%) who developed CRS in the non-AF group, p=0.733. Given the potential impact of cancer type on outcomes, we performed a sensitivity analysis of our AF and CAR-T limited to patients with DLBCL alone, who constituted 70% of CAR-T patients . In a multivariable logistic regression model in the subgroup of DLBCL patients, the results were similar to the entire cohort. The odds of in-hospital mortality (the primary outcome), when adjusted for age, race, sex, Charlson comorbidity, and income were more than five times higher in CAR-T-cell with AF compared to CAR-T without AF (aOR: 5.84, 95% CI: 2.36, 14.47, p <0.001) ( Supplementary Table 5 ). Similarly, the adjusted odds of pulmonary edema were more than two times higher (aOR: 2.73, 95% CI: 0.79, 9.36, p =0.111), the adjusted odds of gastrointestinal bleed were more than four times higher (aOR: 4.87, 95% CI: 1.13, 21.04, p =0.034), and the adjusted odds of acute heart failure more than seven times higher (aOR: 7.99, 95% CI: 1.54, 41.40, p =0.013) in CAR-T with AF compared to CAR-T without AF. While there was a similar trend in length of stay in the CAR-T with AF group compared to CAR-T without AF, the results were not significant (adjusted beta co-efficient 0.15, 95% CI: -0.06, 0.35, p =0.157; Supplementary Table 5 ). Discussion In a large cohort of 1030 hospitalizations for CAR-T in the NIS, representing 4670 unweighted hospitalizations, AF is common and is independent associated with increased in-hospital mortality, gastrointestinal bleeding, acute heart failure, pulmonary edema, and increased length of stay. While prior studies have commented on the frequency and rates of cardiovascular events after CAR-T in smaller cohorts or the pharmacovigilance database, no studies have assessed the impact of comorbid AF on these outcomes in the CAR-T population.( 7 , 22 , 23 ) Thus, our study sheds light on the impact of AF on CAR-T outcomes and highlights the potential importance of reducing AF burden in the CAR-T population. Multiple lines of evidence indicate that AF is a predictor of in-hospital mortality in non-CAR-T patients with metastatic cancers, DLBCL, and multiple myeloma.( 24 , 25 ) In an analysis of the FDA pharmacovigilance database, Goldman et al. reported that hypotension and AF were the most frequent cardiovascular events reported with CAR-T and were thought to be likely secondary to CRS.( 7 ) Limitations of the pharmacovigilance database, however, prevented computing of incidence or odds ratios. Our study thus helps improve our understanding of the incidence of AF with CAR-T and its association with a 3-fold increased risk of in-patient mortality and increased length of stay. In patients receiving CAR-T, AF can occur as part of cytokine release syndrome (CRS) or independently.( 6 ) CRS classically presents with a combination of high fever, severe hypotension, and hypoxia occurring within a few days of CAR T-cell infusion. Studies show that up to 27% of CAR-T patients experience hypotension.( 26 ) As a result, pre- and post-treatment cardiac assessment is critical for evaluating cardiotoxicity in those receiving CAR-T.( 27 ) Pulmonary edema and decreased left ventricular ejection fraction have also been reported in 6% and 10% of CAR-T recipients in the context of high-grade CRS.( 28 , 29 ) These previous findings suggest that the higher incidence of adverse events, such as pulmonary edema and acute heart failure of CAR-T patients with AF observed in our study could be related to CRS. Several case reports have also proposed CRS-independent mechanisms linking CAR-T and cardiotoxicity. Indeed, autopsies in at least two patients who received CAR-T uncovered high concentrations of CAR T-cells in the myocardium and pericardial fluid.( 30 ) This suggests that cardiotoxic CAR T-cells may be a possible culprit in CAR-T recipients who develop cardiopulmonary symptoms and arrhythmia. As such, more extensive studies are needed to determine CRS-dependent and -independent mechanisms in CAR-T patients who develop cardiac dysfunction.( 31 ) In our study, we were not able to fully assess the association of CRS with AF as the ICD-10 code for CRS was not available until near the end of the study period. Out of the 141 patients diagnosed with CRS in our cohort after the code was available, there was no association of CRS with AF, but low patient numbers limit interpretation. While further studies will need to continue to investigate the underlying etiologies of AF (CRS dependent and independent pathways), we are able to show that AF, regardless of the underlying cause, is strongly associated with inpatient mortality and important secondary outcomes. Patients within the CAR-T group with AF were notably older than their counterparts without AF, (68.2 vs. 54.3-year-old, p < 0.001). Age is a well-established independent predictor of mortality and is significantly associated with AF.( 32 ) There is also a strong link between mortality (in both sexes, irrespective of age), bleeding risk, and higher CCI with AF.( 23 , 33 , 34 ) To our knowledge, we are the first to report data involving these metrics in CAR-T patients. Hypertension, chronic heart failure and coronary artery disease were fairly prevalent in the CAR-T AF group, and there certainly may be opportunities for improved cardiovascular optimization prior to CAR-T. Certainly, baseline cardiovascular examinations have been recommended in patients at risk for complications during CAR-T.( 35 ) Importantly, to date no CV comorbidity has been identified as a specific contraindication to CAR-T, but optimization of these risk factors should help reduce risk of events during treatment. Patients with AF were also more likely than CAR-T patients wtihout AF to be diagnosed with acute heart failure, pulmonary edema, acute myocardial infarction, gastrointestinal bleeding, and disseminated intravascular coagulation during their hospitalization. Due to limitations with the NIS, we cannot discern the relative order that these events occurred. However, regardless of the initial driver, the occurrence of atrial fibrillation clearly identifies patients at substantially higher risk of prolonged hospitalization and increased inpatient mortality. Management of atrial fibrillation can be challenging in cancer patients. Thrombocytopenia can limit use of anticoagulation and thus prevent safe cardioversion, while use of anti-arrhythmic therapies can be further complicated by other QT prolonging medications or drug-drug interactions. The general framework for management of atrial fibrillation in cancer patients currently resembles that for the general population,( 36 ) but further studies are needed to address lingering questions. Given the relatively high rate of atrial fibrillation in CAR-T patients, is premedication with anti-arrhythmic warranted? Does the presence of cancer treatment influence the optimal anti-arrhythmic option? As an example, amiodarone is generally not first line in the general population due to long-term toxicity, but it may be a safer option in an acute setting given a lower risk for torsades de pointes.( 37 ) For now these questions remain unanswered, but they are of increased importance given the significant impact atrial fibrillation has in the cancer population, including those receiving CAR-T. Due to limitations with the NIS, we could not differentiate whether AF was present on admission or occurred as a complication from the CAR-T. The results thus reflect associations with AF more broadly, and future research should investigate the impact of AF onset and duration. Our study was limited to inpatient CAR-T administration and did not include patients in outpatient infusion clinics. While there is a trend towards increased outpatient administration of CAR-T, the administration of CAR-T was predominantly inpatient during the study period. Our findings may not be generalizable to the outpatient settings. Data obtained for this study was limited to hospitalizations before December 31, 2020, and only one CAR-T product (Brexucabtagene autoleucel, CART19) was available within this period. Thus, findings from this study may not reflect outcome profiles from other CAR-T products. Additionally, the NIS classifies readmissions as new admissions which introduces the potential for double-counting patients. However, the impact would be minimal for our analysis as every hospitalization included the administration of CAR-T and readministration of CAR-T would be rare during the study period. During the study period, administration of CAR-T was primarily conducted in urban teaching hospitals with large bed numbers (99%) due to high costs and special equipment requirements.( 20 , 21 ) Caucasians represented 71.3% of the study population, limiting our findings' applicability to other patient populations. However, these demographics are consistent with those patients receiving CAR-T. Our data was collected retrospectively, and remaining residual confounders would be expected. The potential for misclassification bias is also a known concern with the use of administrative (ICD-10) codes. We did use previously validated codes to minimize bias and maximize comparability. Finally, our study could not analyze outcomes based on cancer stage or grading of incident CRS. Conclusions The presence of AF in patients undergoing CAR-T is associated with heightened risks of in-hospital mortality, acute pulmonary edema, gastrointestinal bleeding, acute heart failure, and prolonged hospitalization. Further research into AF prevention and treatment has the potential to improve patient outcomes. Abbreviations AF: Atrial Fibrillation, AHRQ: Agency for Healthcare Research and Quality, AMI : Acute Myocardial Infarction, CAR-T: Chimeric Receptor Antigen T-cell Therapy, CAD: Coronary Artery Disease, CCI: Charlson Comorbidity Index, CRS: Cytokine Release Syndrome, DVT: Deep Vein Thrombosis, DIC: Disseminated Intravascular Coagulation, DLBCL: Diffuse Large B-cell Lymphoma, FDA: Food and Drug Administration, GI: Gastro-Intestinal, HCUP: Healthcare Cost and Utilization Project, ICD: International Classification of Disease, STEMI: ST Segment Elevation Myocardial Infarction, N/A: Not Available, NIS: National Inpatient Sample, NHL: Non-Hodgkin Lymphoma, NSTEMI: Non-ST Segment Elevation Myocardial Infarction, OR: Odds Ratio, PE: Pulmonary Embolism, SD: Standard Deviation, SVT: Supra Ventricular Tachycardia, UA: Unstable angina Declarations Acknowledgements: None Funding: Not applicable Corresponding author: Correspondence to Joshua D. Mitchell Ethics Approval declarations: In accordance with the Declaration of Helsinki, our local study NIS research committee deemed local Institutional Review Board (IRB) review was not necessary given the de-identified nature of the data. Human Ethics and Consent of Participate declarations: Not applicable Consent of Participate: Not applicable Clinical trial number: Not applicable Author contribution declaration: N.B.: Conceptualization, Methodology, Data Curation, Writing Original Draft, Formal analysis, wrote the main manuscript text, edited all figures and tables, edited the supplementary materials, N.K.: Writing - Original Draft, Formal analysis, Writing - Original Draft, Writing - Reviewed and edited original manuscript, D.L.: Writing - Review & Editing, prepared supplementary material, R.Z.: - Writing - Review & Editing, prepared tables 3-4, M.I.:- Writing - Original Draft, Writing - Review & Editing with preparing of tables 1-2, A.R.: Writing - Original Draft, prepared figures 1-2, T.E.: Supervision, Writing - Review & Editing, O.M.: Supervision, Writing - Review & Editing, A.K.: Supervision, Project administration, Visualization, J.M.: Conceptualization, Methodology, Supervision, Formal analysis, Writing - Review & Editing, Visualization, Project administration All authors reviewed the manuscript. 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Linette GP, Stadtmauer EA, Maus MV, Rapoport AP, Levine BL, Emery L, et al.Cardiovascular toxicity and titin cross-reactivity of affinity-enhanced T cells in myeloma and melanoma. Blood. 2013;122(6):863-71. Grigor EJM, Fergusson D, Kekre N, Montroy J, Atkins H, Seftel MD, et al.Risks and Benefits of Chimeric Antigen Receptor T-Cell (CAR-T) Therapy in Cancer: A Systematic Review and Meta-Analysis. Transfus Med Rev. 2019;33(2):98-110. Staerk L, Sherer JA, Ko D, Benjamin EJ, Helm RH . Atrial Fibrillation: Epidemiology, Pathophysiology, and Clinical Outcomes. Circ Res. 2017;120(9):1501-17. Proietti M, Esteve-Pastor MA, Rivera-Caravaca JM, Roldán V, Roldán Rabadán I, Muñiz J, et al.Relationship between multimorbidity and outcomes in atrial fibrillation. Exp Gerontol. 2021;153:111482. Benjamin EJ, Wolf PA, D'Agostino RB, Silbershatz H, Kannel WB, Levy D . Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. Circulation. 1998;98(10):946-52. 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Tables Table 1: Baseline Socio-demographics and Comorbidity Index of CAR-T patients with and without Atrial Fibrillation Baseline Demographics and Comorbidities Variables Total Study n =1030 CAR-T with AF n =97 (9.4%) CAR-T without AF n =933 (90.6%) P -value Age (years) ±SD - 55.6±18.1 68.2±9.4 54.3±18.3 <0.001 Gender, n (%) Male 613 (59.5) 75 (78) 538 (57.6) <0.001 Female 417 (40.5) 21 (22) 396 (42.4) Race, n (%) Caucasian 704 (71) 79 (84) 625 (70) <0.001 Black 63 (6.4) N/A 59 (6.6) Hispanic 125 (12.7) N/A 124 (13.9) Asian 40 (4) N/A 39 (4.4) Insurance, n (%) Medicare 335 (32.6) 55 (57) 280 (30) <0.001 Medicaid 105 (10.2) N/A 102 (11) Private 524 (51.0) 33 (34) 491 (52.7) Self-pay 27 (2.6) N/A 25 (2.7) Region, n (%) Northeast 283 (27.5) 24 (25) 259 (27.7) 0.255 Midwest 245 (23.8) 22 (23) 223 (24) South 268 (26.0) 33 (34) 235 (25) West 234 (22.7) 17 (17.7) 217 (23) Setting/location, n (%) Rural N/A N/A N/A 1.00 Urban non-teaching N/A N/A N/A Urban teaching 1023 (99.3) 96 (100) 927 (99.3) Bed size, n (%) Small 129 (12.5) 14 (14.6) 115 (12.3) 0.055 Medium 143 (13.9) N/A 137 (14.7) Large 758 (73.6) 76 (79) 682 (73) Charlson comorbidity index, n (%) 0 N/A N/A N/A <0.001 1 N/A N/A N/A 2 614 (59.6) 38 (40) 576 (61.7) 3 or higher 413 (40.1) 57 (59) 356 (38) Annual income (US $ per year), n (%) 1-45,999 175 (17.8) 16 (17) 159 (18) 0.229 46K–58,999 205 (20.8) 18 (19) 187 (21) 59K-78,999 276 (28) 20 (21) 256 (28.7) 79K or more 329 (33.4) 40 (42.6) 289 (32) Comparison of baseline socio-demographics and Charlson Comorbidity Index in patients admitted for CAR-T with and without atrial fibrillation. Data reflects all hospitalizations from the National Inpatient Sample between 2017-2020 with an FDA approved indication for CAR-T. Cancer types included are diffuse large B cell lymphoma, B-cell precursor acute lymphoblastic leukemia, follicular lymphoma, mantle cell lymphoma, and multiple myeloma. Frequencies less than 11 are marked as “N/A” due to Healthcare Cost and Utilization Project (HCUP) guidelines. The Student t-test assessed differences in continuous variables while Chi-squared assessed differences in categorical variables. Abbreviations: AF: Atrial fibrillation, N/A: Non-applicable. As per National inpatient sample we cannot report numbers less than or equal to 11 so in such cases N/A has been used. CAR-T: Chimeric Receptor Antigen T-cell therapy, FDA: Food and Drug Administration, US: United States, SD: Standard Deviation Table 2. In-hospital Cardiovascular and Bleeding Diagnoses Associated with CAR-T with and without AF Total Study n=1030 CAR-T with AF n =97 (9.4%) CAR-T without AF n =933 (90.6%) P -value Cardiovascular Risk Factors Hypertension 396 (38.4) 55 (56.7) 341 (36.6) <0.001 Obesity 70 (6.8) 5 (5) 65 (7) 0.671 Cardiovascular Disease CAD 65 (6.3) 18 (18.6) 47 (5) <0.001 Pericardial disease including pericarditis 15 (1.5) 2 (2) 13 (1.4) 0.645 Arrhythmias Supraventricular tachycardia 35 (3.4) 10 (10.3) 25 (2.7) 0.001 Ventricular arrhythmias 44 (4.3) 8 (8.3) 36 (3.9) 0.059 Heart failure Chronic Heart Failure 89 (8.6) 24 (24.7) 65 (7) <0.001 Acute Heart Failure 12 (1.2) 6 (6.2) 6 (0.6) <0.001 Pulmonary Edema 33 8 (8.3) 25 (2.7) 0.009 Acute myocardial infarction (AMI) AMI 29 6 (6.2) 23 (2.5) 0.048 Thromboembolism Acute DVT and PE 20 2 (2) 18 (2) 0.712 Hypotension and Critical Care Hypotension 295 34 (35) 261 (28) 0.157 Mechanical ventilation requirement 45 8 (8.3) 37 (4) 0.063 Bleeding Complications GI Bleed 18 5 (5.2) 13 (1.4) 0.021 DIC 38 9 (9.3) 29 (3.1) 0.006 Comparison of inpatient cardiovascular and bleeding diagnoses in patients admitted for CAR-T with and without atrial fibrillation. Data reflects all hospitalizations from the National Inpatient Sample between 2017-2020 with an FDA approved indication for CAR-T. Cancer types included are diffuse large B cell lymphoma, B-cell precursor acute lymphoblastic leukemia, follicular lymphoma, mantle cell lymphoma, and multiple myeloma. Acute and chronic heart failure, pulmonary edema, supraventricular tachycardia, acute myocardial infarction, hypertension, coronary artery disease, gastrointestinal bleeding, and disseminated intravascular coagulation were more common in atrial fibrillation patients. Variables with a frequency less than 11 are marked as “N/A” due to Healthcare Cost and Utilization Project (HCUP) policy on reporting low numbers. (N/A marks both the cell in question and the corresponding cell to prevent computation of the missing cell count). Abbreviations: CAR-T: Chimeric Receptor Antigen T-cell Therapy, CAD: Coronary Artery Disease, CCI: Charlson Comorbidity Index, DVT: Deep Vein Thrombosis, DIC: Disseminated Intravascular Coagulation, FDA: Food and Drug Administration, GI: Gastro-Intestinal AMI : Acute Myocardial Infarction includes (STEMI: ST Segment Elevation Myocardial Infarction, N/A: Not Available, NSTEMI: Non-ST Segment Elevation Myocardial Infarction, and UA: Unstable angina), PE: Pulmonary Embolism, SD: Standard Deviation, SVT: Supra Ventricular Tachycardia Table 3. Unadjusted and Adjusted Odds Ratios for In-Hospital Mortality During CAR-T Hospitalization in the NIS 2017-2020 Variables Univariable Logistic Regression Multivariable Logistic Regression OR 95% CI P- value aOR 95% CI P- value Age 0.99 0.97-1.01 0.181 0.98 0.96–1.01 0.017 Atrial fibrillation 3.12 1.43-6.80 0.004 3.87 1.61-9.30 0.002 Female Sex 0.82 0.42-1.60 0.554 0.99 0.51-1.93 0.975 Race Ref: Caucasian 0.069 <0.001 African American 2.01 0.66-6.07 1.8 0.63-5.10 Hispanic 0.98 0.34-2.85 0.77 0.21-2.85 Asian 1.56 0.37-6.60 1.75 0.38-8.07 Region 0.859 - Bed size 0.417 - Annual income (US$ per year) Ref: 1-45,999 0.071 <0.001 46K–58,999 0.36 0.89-1.42 0.37 0.09-1.57 59K-78,999 0.62 0.26-1.51 0.69 0.28-1.74 79K or more 1.39 0.53-3.62 1.59 0.55-4.67 Year 0.377 - Charlson Comorbidity 1.99 1.10-3.67 0.028 1.86 0.92-3.73 0.083 Insurance 0.774 - Univariable and multivariable logistic regression assessed the association of baseline socio-demographics, charlson-comorbidity index and atrial fibrillation with in-hospital mortality. Variables were included in the multivariable model if the unadjusted p-value was £ 0.20. Abbreviations: NIS: National Inpatient Sample, CAR-T: Chimeric Receptor Antigen T-cell Therapy, LL: lower limit, UP: upper limit, N/A: Not application in multivariate regression OR: Odds ratio USD: United States Dollar Table 4: Adjusted odds ratio (effect) of various in-hospital outcomes in CAR-T AF group compared to CAR-T non-AF group. In-hospital outcomes Adjusted OR 95% CI P -value In-hospital mortality 3.87 1.61–9.30 0.002 Pulmonary edema 3.29 1.34-8.09 0.01 Gastrointestinal bleed 5.46 1.95–15.29 0.001 Acute Heart Failure 10.2 2.15–47.95 0.003 Beta Coefficient 95% CI P -value Length of stay 0.18 0.01–0.36 0.045 Adjusted odds ratios and beta coefficient after multivariable logistic regression and negative binomial regression in primary and secondary outcomes adjusted for age, sex, race, comorbidity, and income. The median length of stay in CAR-T with AF was 23 days compared to 20 days in the CAR-T group without AF. Abbreviations: AF: Atrial Fibrillation, CAR-T: Chimeric Antigen Receptor T-cell therapy, CI: Confidence Interval, OR: Odds Ratio, LL: Lower limit, UL: Upper Limit Additional Declarations No competing interests reported. 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Ladin","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"A.","lastName":"Ladin","suffix":""},{"id":354797681,"identity":"67878112-502f-4951-b922-4b0a08afcef2","order_by":3,"name":"Raja Zaghlol","email":"","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":false,"prefix":"","firstName":"Raja","middleName":"","lastName":"Zaghlol","suffix":""},{"id":354797682,"identity":"99655538-caff-44ce-b68f-ad36cf56c0fe","order_by":4,"name":"Mahmoud Ibrahim","email":"","orcid":"","institution":"McLaren Health Care","correspondingAuthor":false,"prefix":"","firstName":"Mahmoud","middleName":"","lastName":"Ibrahim","suffix":""},{"id":354797683,"identity":"a0f86c04-991a-49f6-a031-35ecd32947a8","order_by":5,"name":"Alexander Rabadi","email":"","orcid":"","institution":"McLaren Health Care","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Rabadi","suffix":""},{"id":354797684,"identity":"07e0016a-9a76-4449-9ea9-4259fae509f3","order_by":6,"name":"Tarec K. 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Mitchell","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACxoYEhgMMQMTHznwAJCADxAaEtRwAamFjZksAqeYhqIWBIQFkB0gLjwFxWpjbsxMPf6i5IwfU8k2a588fHgb25m0SeB3W83bDgQPHnhmzMfNuk+ZtA9rCc6wMv5YZuRsOHGw4nNgG1HKbtwGoRSLHjCgt9W3MPM9u8/wBapF/Q5yWBKBf2G7zsIFs4SGgBeSXM8cOG7Yxs5n/nNtmzMPGk1ZsgU+LYXvu5g8VNYfl+dmbHxu8+SMnx89+eOMNvFoa0EXY8CkHAXlCCkbBKBgFo2AUMAAAmhFKMhQPOWAAAAAASUVORK5CYII=","orcid":"","institution":"Washington University in St. Louis","correspondingAuthor":true,"prefix":"","firstName":"Joshua","middleName":"D.","lastName":"Mitchell","suffix":""}],"badges":[],"createdAt":"2024-08-18 04:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4931828/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4931828/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40959-025-00334-5","type":"published","date":"2025-07-03T15:58:06+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66632806,"identity":"f4b6bc83-17b5-4892-933e-4bb0120df73e","added_by":"auto","created_at":"2024-10-15 05:01:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":956156,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of study population selection with information on inclusion observations\u003c/p\u003e\n\u003cp\u003eAbbreviations: CART: Chimeric Antigen Receptor T-cell\u003c/p\u003e","description":"","filename":"Figure1CART8.19.24.png","url":"https://assets-eu.researchsquare.com/files/rs-4931828/v1/40e5f317f72f1943296d9b72.png"},{"id":66634664,"identity":"4b39d652-2c08-46b2-9cbe-261e734c6868","added_by":"auto","created_at":"2024-10-15 05:09:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":629556,"visible":true,"origin":"","legend":"\u003cp\u003eTrend of Chimeric Antigen Receptor T-cell Therapy (CART) hospitalizations\u003c/p\u003e","description":"","filename":"Figure2CART8.19.24.png","url":"https://assets-eu.researchsquare.com/files/rs-4931828/v1/a1ebd1054b73082136539cd1.png"},{"id":86180167,"identity":"07a5ae31-fa6e-49e5-9aad-1e8263867578","added_by":"auto","created_at":"2025-07-07 16:21:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2911231,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4931828/v1/4776aea4-3fe0-465f-8183-e7ac3dbfcab6.pdf"},{"id":66632805,"identity":"8edb05f0-8fb5-444d-959a-2d7283196453","added_by":"auto","created_at":"2024-10-15 05:01:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16071,"visible":true,"origin":"","legend":"","description":"","filename":"HIGHLIGHTSCARTAF.docx","url":"https://assets-eu.researchsquare.com/files/rs-4931828/v1/8cae5d4ca0134a265106c414.docx"},{"id":66632807,"identity":"886183c6-92f1-423e-bd48-e9dca5cfaf45","added_by":"auto","created_at":"2024-10-15 05:01:17","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":37267,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryfileCARTcell8172024.docx","url":"https://assets-eu.researchsquare.com/files/rs-4931828/v1/0a719af115acf5c12f8a7d70.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Atrial Fibrillation Is Associated with Increased In-Hospitality Mortality During Chimeric Antigen Receptor T-cell Therapy Hospitalizations: A Retrospective Cohort Study in the United States. ","fulltext":[{"header":"Background","content":"\u003cp\u003eOver the last decade, Chimeric Antigen Receptor (CAR) T-cell therapy (CAR-T) has emerged as a revolutionary tool for cancer treatment. In its original design, a CAR was composed of an antibody-derived single-chain variable fragment (scFv) fused to the T-cell receptor (TCR) signaling domain, intended to redirect T-cells to target solid tumors and human deficiency virus (HIV).(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) With time, the design of CAR T-cells evolved to include costimulatory domains and improved \u003cem\u003eex vivo\u003c/em\u003e culturing methodologies.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The first successful clinical reports of CAR-T were in patients with chronic lymphocytic leukemia (CLL) and non-Hodgkin lymphoma (NHL), using patient-derived autologous CAR T-cells directed against CD19 (CART19).(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) In 2017, the Food and Drug Administration (FDA) approved tisagenlecleucel and axicabtagene ciloleucel for the treatment of relapsing/refractory diffuse B-ALL (B-acute lymphoblastic leukemia) and diffuse large B-cell lymphoma (DLBCL).\u003c/p\u003e \u003cp\u003eDespite its therapeutic promise, CAR-T may have potential life-threatening adverse events, including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). In addition, cardiotoxicity affects up to 26% of cancer patients who undergo CAR-T.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Cardiotoxicity may share pathophysiological pathways overlapping with CRS and ICANS. CRS is associated with various cardiovascular manifestations, including arrhythmias, heart failure, cardiogenic shock, and cardiomyopathies.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) In a recent retrospective study, atrial fibrillation (AF) was the most common arrhythmia in CAR-T recipients.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) However, there is a paucity of data on whether AF is associated with higher mortality and other adverse clinical outcomes in CAR-T recipients hospitalized in the US. Our study aims to investigate the association between CAR-T and AF in the National Inpatient Sample (NIS), including potential correlations between AF and in-hospital outcomes in this cancer population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis retrospective, population-based cohort observational study drew from all hospitalizations in the NIS from January 1, 2017, to December 31, 2020, the most current data available. NIS is the largest inpatient database in the United States and allows for analyzing rare treatments such as CAR-T. The NIS was developed for the Healthcare Cost and Utilization Project (HCUP; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.hcup-us.ahrq.gov\u003c/span\u003e\u003cspan address=\"http://www.hcup-us.ahrq.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the Agency for Healthcare Research and Quality (AHRQ) to estimate inpatient utilization, access, cost quality and in-hospital outcomes.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) The publicly available, all-payer, inpatient database contains de-identified data from more than seven million hospital stays annually.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) For this analysis of the NIS, we followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement for reporting observational studies.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) The study was exempt from local Institutional Review Board (IRB) review given the de-identified nature of the data.\u003c/p\u003e \u003cp\u003eWe first identified all NIS hospitalizations containing a cancer diagnosis (including principal as well as secondary diagnoses) with a Food and Drug Administration (FDA) approved indication for CAR-T.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Cancers eligible for inclusion were selected using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and consisted of DLCBL, B-cell precursor acute lymphoblastic leukemia, follicular lymphoma, mantle cell lymphoma, and multiple myeloma (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e).(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Among these eligible hospitalizations, ICD-10 procedure codes identified patients undergoing CAR-T (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). Eligible patients were further divided by the presence or absence of AF or atrial flutter (principal or secondary diagnosis) at any time by ICD-10-CM codes I48.0, I48.1, I48.2, I48.3, I48.4, I48.91, and I48.92. Notably, the NIS does not include patients receiving CAR-T in clinical trials or outpatient infusion clinics, and these patients were naturally excluded.\u003c/p\u003e \u003cp\u003eWe collected patient demographics for each hospital stay including age, sex, race, median household income by zip code, hospital region, hospital bed size, and insurance status. Patient comorbidity status was assessed using the Charlson Comorbidity Index (CCI), a point-based system with values of 0, 1, 2 or \u0026ge;\u0026thinsp;3 representing no, mild, moderate, and severe comorbid burden, respectively.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) The primary outcome for the study was in-hospital mortality. Secondary outcomes were length of hospital stay as well as the occurrence of in-hospital gastrointestinal bleeding, pulmonary edema, and/or acute heart failure. These outcomes were identified using ICD-10-CM codes found in any principal or secondary diagnosis field.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) The ICD-10-CM diagnosis and ICD-10 procedure codes used for the study are shown in \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eWe evaluated differences between CAR-T patients with and without AF using Chi-squared or Fisher's exact tests for categorical variables (e.g., sex, in-hospital mortality, race, comorbidity index categories), and Student\u0026rsquo;s t-test for the length of stay (LOS). Univariable logistic regression models assessed the association by odds ratio with AF and outcomes (i.e., in-hospital mortality) as well as other baseline socio-demographics and comorbidities that have been associated with in-hospital mortality (e.g., age, sex obtained from medical records as male or female assigned at birth, race, comorbidity index, hospital bed size, hospital region, hospital teaching status, and household income national quartiles). Variables with a \u003cem\u003ep\u003c/em\u003e-value of \u0026le; 0.20 in the unadjusted weighted univariate regressions were subsequently included in a multivariable logistic regression model.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) Age and sex were included into the multivariable regression model independent of the univariable regression model due to the significance of these variables in our primary and secondary outcomes of interest.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) Additional multivariable logistic regression models tested the independent association of atrial fibrillation with secondary outcomes using the same covariates. For length of stay (LOS), we used negative binomial regression to assess association (by beta coefficient) of AF with LOS, after an evaluation of the dispersion of LOS variable in the histogram showed over-dispersed data for the LOS in days.\u003c/p\u003e \u003cp\u003eWe defined survey parameters (weight, strata, and stratum) to account for the NIS complex survey sampling methods.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) This study addressed the potential for misclassification bias by using ICD-10 codes validated in prior studies as well as codes used in prior published papers.(\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) The multiple imputation method was planned for imputed missing data if more than ten percent of variables were missing.(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSince differences among cancer types could add variation into study findings, we performed a sensitivity analysis in the subgroup of patients with diffuse large B-cell lymphoma which constituted 70% of the patients receiving CAR-T.\u003c/p\u003e \u003cp\u003eFor reference, descriptive statistics were employed to report cardiovascular and bleeding diagnoses associated with all hospitalizations, with and without CAR-T, among the patients with cancers with an FDA approved indication for CAR-T. Only descriptive statistics are reported, given potential variations in hospitalization indications. (All CAR T-cell therapy admissions would be expected to be specifically for CAR T-cell therapy, while other hospitalizations may have been for indications unrelated to cancer treatment such as sepsis.)\u003c/p\u003e \u003cp\u003eIn this analysis, we stressed the precision of the study estimates, focusing on 95% confidence intervals. \u003cem\u003eP\u003c/em\u003e-values are presented to aid interpretation. All analyses were performed with STATA 17.0 (Stata-Corp LP, College Station, Texas).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAmong the 236,270 hospitalizations involving CAR-T approved cancer subtypes (DLBCL, multiple myeloma, follicular lymphoma, mantle cell lymphoma, and acute lymphoblastic leukemia), 1,030 (0.44%) hospitalizations involved administration of CAR-T between January 1, 2017, and December 31, 2020 (\u003cstrong\u003eFigure 1, Supplementary Table 2\u003c/strong\u003e). These 1030 unweighted hospitalizations represented approximately 4670 records after applying weights for national estimates. CAR-T hospitalizations steadily rose from 2017-2020 (\u003cstrong\u003eFigure 2, Supplementary Table 2\u003c/strong\u003e). DLBCL accounted for 70% of patients receiving CAR-T.\u003c/p\u003e\n\u003cp\u003eAmong the 1030 unweighted hospitalizations, 43 records were missing race, 45 records were missing income quartiles, and 8 records were missing insurance status. (Multiple imputations were not indicated per the statistical plan, as the total records with missing variables were less than ten percent.)\u003c/p\u003e\n\u003cp\u003eOf the 1030 patients receiving CAR-T (mean age 55.6±18.1 years), 97 (9.4%) had an associated diagnosis of AF during their hospitalization. Compared to CAR-T patients without AF, those with AF were found to be older (mean age 68 vs. 54 years, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), more likely to be male (42% vs. 22%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), more likely to be Caucasian (84% vs. 70%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), have Medicare (57% vs. 30%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), and have a higher prevalence of 3 or more comorbidities (59% vs. 38%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001) (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eCompared to the CAR-T without AF, CAR-T with AF was associated with higher prevalence of hypertension (56.7% vs 36.6%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), hypotension (35% vs 28%, \u003cem\u003ep\u003c/em\u003e=0.157), chronic heart failure (24.7% vs 7%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), and coronary artery disease (18.6% vs 5%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001) as shown in \u003cstrong\u003eTable 2\u003c/strong\u003e. The prevalence of supraventricular arrhythmia, acute heart failure, pulmonary edema, acute myocardial infarction, gastrointestinal bleed, and disseminated intravascular coagulation were also more common in the CAR-T with AF group compared to CART without AF group. However, we were unable to report the number and percentages in these variables due to low frequencies. In the table, frequencies less than 11 are not specifically reported as per the data reporting and publishing policy of HCUP.(6, 12)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnivariable logistic regression models assessed the associations of in-hospital mortality in CAR-T admissions with age, sex, atrial fibrillation, race, hospital region, hospital bed size, household income, year, Charlson comorbidity, and insurance status (\u003cstrong\u003eTable 3\u003c/strong\u003e). Atrial fibrillation and Charlson comorbidity index were both associated with increased in-hospital mortality. A multivariable model (\u003cstrong\u003eTable 3\u003c/strong\u003e) analyzed the independent association of AF with hospitalization after adjusting for age, sex, race, household income, and Charlson comorbidity (included in the model given univariable \u003cem\u003ep\u003c/em\u003e-values were\u0026nbsp;£\u0026nbsp;0.20). The adjusted odds of in-hospital mortality (the primary outcome) were more than three times higher in the group of CAR-T recipients with AF compared to the CAR-T group without AF (aOR: 3.87, 95% CI: 1.61, 9.30,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e=0.003) (\u003cstrong\u003eTables 3 and 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eSimilar multivariable regression models were used for the secondary outcomes with the exception of length of stay, which was evaluated with negative binomial regression. The adjusted odds of pulmonary edema were more than three times higher (aOR: 3.29, 95% CI: 1.34, 8.09,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e=0.010), adjusted odds of gastrointestinal bleed were more than five times higher (aOR: 5.46, 95% CI: 1.95, 15.29,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e=0.001), and adjusted odds of acute heart failure more than ten times higher (aOR: 10.20, 95% CI: 2.15, 47.95,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e=0.003) in CAR-T with AF compared to CAR-T without AF (\u003cstrong\u003eTable 4\u003c/strong\u003e). Length of stay was longer in CAR-T with AF versus without AF (mean length of stay 20.5 days vs 7.5 days, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, adjusted beta co-efficient 0.18, 95% CI: 0.01, 0.36, \u003cem\u003ep\u003c/em\u003e=0.045) as also shown in \u003cstrong\u003eTable 4\u003c/strong\u003e. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe demographics, cancer types and in-hospital CV and bleeding diagnosis associated with CAR-T vs non-CAR-T in the five FDA approved cancer types are reported for reference. Only descriptive statistics are used given the potential differences in hospitalization indications in patients not receiving CAR-T. Among the 236,270 hospitalizations with cancer subtypes where CAR-T is approved, only 0.4% of hospitalization included the administration of CAR-T. The majority of CAR-T admissions were in patients with DLBCL (70.2%) followed by acute lymphoblastic leukemia (12.3%), multiple myeloma (11.6%) and mantle cell lymphoma (2.2%). (\u003cstrong\u003eSupplementary Table 4\u003c/strong\u003e). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompared to patients not receiving CAR-T, patients receiving CAR-T had numerically higher incidence of hypotension (28.6% vs. 8.1%), ventricular tachycardia (3.2% vs. 1.5%), supraventricular tachycardia (3.4% vs. 1.8%), pulmonary edema (3.2% vs. 1.1%), mechanical ventilation requirement (4.4% vs 2.8%) and disseminated intravascular coagulation (3.7% vs. 2.4%). (\u003cstrong\u003eSupplementary Table 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eSince the ICD 10 diagnostic code for CRS was implemented in October, 2020, CRS could only be assessed after this date. CRS was diagnosed in 141 patients in the study cohort.(16)\u0026nbsp;Among them, 21 patients (0.05%) developed CRS in the AF group compared to 120 patients (0.06%) who developed CRS in the non-AF group, p=0.733.\u003c/p\u003e\n\u003cp\u003eGiven the potential impact of cancer type on outcomes, we performed a sensitivity analysis of our AF and CAR-T limited to patients with DLBCL alone, who constituted 70% of CAR-T patients\u003cstrong\u003e.\u003c/strong\u003e In a multivariable logistic regression model in the subgroup of DLBCL patients, the results were similar to the entire cohort. The odds of in-hospital mortality (the primary outcome), when adjusted for age, race, sex, Charlson comorbidity, and income were more than five times higher in CAR-T-cell with AF compared to CAR-T without AF (aOR: 5.84, 95% CI: 2.36, 14.47,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e\u0026lt;0.001) (\u003cstrong\u003eSupplementary Table 5\u003c/strong\u003e). Similarly, the adjusted odds of pulmonary edema were more than two times higher (aOR: 2.73, 95% CI: 0.79, 9.36,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e=0.111), the adjusted odds of gastrointestinal bleed were more than four times higher (aOR: 4.87, 95% CI: 1.13, 21.04,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e=0.034), and the adjusted odds of acute heart failure more than seven times higher (aOR: 7.99, 95% CI: 1.54, 41.40,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e=0.013) in CAR-T with AF compared to CAR-T without AF. While there was a similar trend in length of stay in the CAR-T with AF group compared to CAR-T without AF, the results were not significant (adjusted beta co-efficient 0.15, 95% CI: -0.06, 0.35, \u003cem\u003ep\u003c/em\u003e=0.157; \u003cstrong\u003eSupplementary Table 5\u003c/strong\u003e). \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn a large cohort of 1030 hospitalizations for CAR-T in the NIS, representing 4670 unweighted hospitalizations, AF is common and is independent associated with increased in-hospital mortality, gastrointestinal bleeding, acute heart failure, pulmonary edema, and increased length of stay. While prior studies have commented on the frequency and rates of cardiovascular events after CAR-T in smaller cohorts or the pharmacovigilance database, no studies have assessed the impact of comorbid AF on these outcomes in the CAR-T population.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) Thus, our study sheds light on the impact of AF on CAR-T outcomes and highlights the potential importance of reducing AF burden in the CAR-T population.\u003c/p\u003e \u003cp\u003eMultiple lines of evidence indicate that AF is a predictor of in-hospital mortality in non-CAR-T patients with metastatic cancers, DLBCL, and multiple myeloma.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) In an analysis of the FDA pharmacovigilance database, Goldman et al. reported that hypotension and AF were the most frequent cardiovascular events reported with CAR-T and were thought to be likely secondary to CRS.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Limitations of the pharmacovigilance database, however, prevented computing of incidence or odds ratios. Our study thus helps improve our understanding of the incidence of AF with CAR-T and its association with a 3-fold increased risk of in-patient mortality and increased length of stay.\u003c/p\u003e \u003cp\u003eIn patients receiving CAR-T, AF can occur as part of cytokine release syndrome (CRS) or independently.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) CRS classically presents with a combination of high fever, severe hypotension, and hypoxia occurring within a few days of CAR T-cell infusion. Studies show that up to 27% of CAR-T patients experience hypotension.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) As a result, pre- and post-treatment cardiac assessment is critical for evaluating cardiotoxicity in those receiving CAR-T.(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003cp\u003ePulmonary edema and decreased left ventricular ejection fraction have also been reported in 6% and 10% of CAR-T recipients in the context of high-grade CRS.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) These previous findings suggest that the higher incidence of adverse events, such as pulmonary edema and acute heart failure of CAR-T patients with AF observed in our study could be related to CRS. Several case reports have also proposed CRS-independent mechanisms linking CAR-T and cardiotoxicity. Indeed, autopsies in at least two patients who received CAR-T uncovered high concentrations of CAR T-cells in the myocardium and pericardial fluid.(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) This suggests that cardiotoxic CAR T-cells may be a possible culprit in CAR-T recipients who develop cardiopulmonary symptoms and arrhythmia. As such, more extensive studies are needed to determine CRS-dependent and -independent mechanisms in CAR-T patients who develop cardiac dysfunction.(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn our study, we were not able to fully assess the association of CRS with AF as the ICD-10 code for CRS was not available until near the end of the study period. Out of the 141 patients diagnosed with CRS in our cohort after the code was available, there was no association of CRS with AF, but low patient numbers limit interpretation. While further studies will need to continue to investigate the underlying etiologies of AF (CRS dependent and independent pathways), we are able to show that AF, regardless of the underlying cause, is strongly associated with inpatient mortality and important secondary outcomes.\u003c/p\u003e \u003cp\u003ePatients within the CAR-T group with AF were notably older than their counterparts without AF, (68.2 vs. 54.3-year-old, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Age is a well-established independent predictor of mortality and is significantly associated with AF.(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) There is also a strong link between mortality (in both sexes, irrespective of age), bleeding risk, and higher CCI with AF.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) To our knowledge, we are the first to report data involving these metrics in CAR-T patients.\u003c/p\u003e \u003cp\u003eHypertension, chronic heart failure and coronary artery disease were fairly prevalent in the CAR-T AF group, and there certainly may be opportunities for improved cardiovascular optimization prior to CAR-T. Certainly, baseline cardiovascular examinations have been recommended in patients at risk for complications during CAR-T.(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) Importantly, to date no CV comorbidity has been identified as a specific contraindication to CAR-T, but optimization of these risk factors should help reduce risk of events during treatment.\u003c/p\u003e \u003cp\u003ePatients with AF were also more likely than CAR-T patients wtihout AF to be diagnosed with acute heart failure, pulmonary edema, acute myocardial infarction, gastrointestinal bleeding, and disseminated intravascular coagulation during their hospitalization. Due to limitations with the NIS, we cannot discern the relative order that these events occurred. However, regardless of the initial driver, the occurrence of atrial fibrillation clearly identifies patients at substantially higher risk of prolonged hospitalization and increased inpatient mortality.\u003c/p\u003e \u003cp\u003eManagement of atrial fibrillation can be challenging in cancer patients. Thrombocytopenia can limit use of anticoagulation and thus prevent safe cardioversion, while use of anti-arrhythmic therapies can be further complicated by other QT prolonging medications or drug-drug interactions. The general framework for management of atrial fibrillation in cancer patients currently resembles that for the general population,(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) but further studies are needed to address lingering questions. Given the relatively high rate of atrial fibrillation in CAR-T patients, is premedication with anti-arrhythmic warranted? Does the presence of cancer treatment influence the optimal anti-arrhythmic option? As an example, amiodarone is generally not first line in the general population due to long-term toxicity, but it may be a safer option in an acute setting given a lower risk for torsades de pointes.(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) For now these questions remain unanswered, but they are of increased importance given the significant impact atrial fibrillation has in the cancer population, including those receiving CAR-T.\u003c/p\u003e \u003cp\u003eDue to limitations with the NIS, we could not differentiate whether AF was present on admission or occurred as a complication from the CAR-T. The results thus reflect associations with AF more broadly, and future research should investigate the impact of AF onset and duration.\u003c/p\u003e \u003cp\u003eOur study was limited to inpatient CAR-T administration and did not include patients in outpatient infusion clinics. While there is a trend towards increased outpatient administration of CAR-T, the administration of CAR-T was predominantly inpatient during the study period. Our findings may not be generalizable to the outpatient settings. Data obtained for this study was limited to hospitalizations before December 31, 2020, and only one CAR-T product (Brexucabtagene autoleucel, CART19) was available within this period. Thus, findings from this study may not reflect outcome profiles from other CAR-T products. Additionally, the NIS classifies readmissions as new admissions which introduces the potential for double-counting patients. However, the impact would be minimal for our analysis as every hospitalization included the administration of CAR-T and readministration of CAR-T would be rare during the study period. During the study period, administration of CAR-T was primarily conducted in urban teaching hospitals with large bed numbers (99%) due to high costs and special equipment requirements.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) Caucasians represented 71.3% of the study population, limiting our findings' applicability to other patient populations. However, these demographics are consistent with those patients receiving CAR-T. Our data was collected retrospectively, and remaining residual confounders would be expected. The potential for misclassification bias is also a known concern with the use of administrative (ICD-10) codes. We did use previously validated codes to minimize bias and maximize comparability. Finally, our study could not analyze outcomes based on cancer stage or grading of incident CRS.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe presence of AF in patients undergoing CAR-T is associated with heightened risks of in-hospital mortality, acute pulmonary edema, gastrointestinal bleeding, acute heart failure, and prolonged hospitalization. Further research into AF prevention and treatment has the potential to improve patient outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAF: Atrial Fibrillation, AHRQ: Agency for Healthcare Research and Quality, AMI : Acute Myocardial Infarction, CAR-T: Chimeric Receptor Antigen T-cell Therapy, CAD: Coronary Artery Disease, CCI: Charlson Comorbidity Index, CRS: Cytokine Release Syndrome, DVT: Deep Vein Thrombosis, DIC: Disseminated Intravascular Coagulation, DLBCL: Diffuse Large B-cell Lymphoma, FDA: Food and Drug Administration, GI: Gastro-Intestinal, HCUP: Healthcare Cost and Utilization Project, ICD: International Classification of Disease, \u0026nbsp;STEMI: ST Segment Elevation Myocardial Infarction, N/A: Not Available, NIS: National Inpatient Sample, NHL: Non-Hodgkin Lymphoma, NSTEMI: Non-ST Segment Elevation Myocardial Infarction, OR: Odds Ratio, PE: Pulmonary Embolism, SD: Standard Deviation, SVT: Supra Ventricular Tachycardia, UA: Unstable angina\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements: None\u003c/p\u003e\n\u003cp\u003eFunding: Not applicable\u003c/p\u003e\n\u003cp\u003eCorresponding author: Correspondence to Joshua D. Mitchell\u003c/p\u003e\n\u003cp\u003eEthics Approval declarations: In accordance with the Declaration of Helsinki, our local study NIS research committee deemed local Institutional Review Board (IRB) review was not necessary given the de-identified nature of the data.\u003c/p\u003e\n\u003cp\u003eHuman Ethics and Consent of Participate declarations: Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent of Participate: Not applicable\u003c/p\u003e\n\u003cp\u003eClinical trial number: Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor contribution declaration: N.B.: Conceptualization, Methodology, Data Curation, Writing Original Draft, Formal analysis, wrote the main manuscript text, edited all figures and tables, edited the supplementary materials, N.K.: Writing - Original Draft, Formal analysis, Writing - Original Draft, Writing - Reviewed and edited original manuscript, D.L.: Writing - Review \u0026amp; Editing, prepared supplementary material, R.Z.: - Writing - Review \u0026amp; Editing, prepared tables 3-4, M.I.:- Writing - Original Draft, Writing - Review \u0026amp; Editing with preparing of tables 1-2, A.R.: Writing - Original Draft, prepared figures 1-2, T.E.: Supervision, Writing - Review \u0026amp; Editing, O.M.: Supervision, Writing - Review \u0026amp; Editing, A.K.: Supervision, Project administration, Visualization, J.M.: Conceptualization, Methodology, Supervision, Formal analysis, Writing - Review \u0026amp; Editing, Visualization, Project administration All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis retrospective, population-based cohort observational study used database from all hospitalizations in the National inpatient sample (NIS) from January 1, 2017, to December 31, 2020. NIS is the largest inpatient database in the United States. The NIS was developed for the Healthcare Cost and Utilization Project (HCUP) and the database is publicly available at www.hcup-us.ahrq.gov for purchase from the Agency for Healthcare Research and Quality (AHRQ).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBraendstrup P, Levine BL, Ruella M\u003cstrong\u003e. \u003c/strong\u003eThe long road to the first FDA-approved gene therapy: chimeric antigen receptor T cells targeting CD19. Cytotherapy. 2020;22(2):57-69.\u003c/li\u003e\n\u003cli\u003eGross G, Waks T, Eshhar Z\u003cstrong\u003e. \u003c/strong\u003eExpression of immunoglobulin-T-cell receptor chimeric molecules as functional receptors with antibody-type specificity. Proc Natl Acad Sci U S A. 1989;86(24):10024-8.\u003c/li\u003e\n\u003cli\u003eStein-Merlob AF, Rothberg MV, Holman P, Yang EH\u003cstrong\u003e. \u003c/strong\u003eImmunotherapy-Associated Cardiotoxicity of Immune Checkpoint Inhibitors and Chimeric Antigen Receptor T Cell Therapy: Diagnostic and Management Challenges and Strategies. Curr Cardiol Rep. 2021;23(3):11.\u003c/li\u003e\n\u003cli\u003eSimbaqueba CC, Aponte MP, Kim P, Deswal A, Palaskas NL, Iliescu C, et al.Cardiovascular Complications of Chimeric Antigen Receptor T-Cell Therapy: The Cytokine Release Syndrome and Associated Arrhythmias. J Immunother Precis Oncol. 2020;3(3):113-20.\u003c/li\u003e\n\u003cli\u003eGoldman A, Maor E, Bomze D, Liu JE, Herrmann J, Fein J, et al.Adverse Cardiovascular and Pulmonary Events Associated With Chimeric Antigen Receptor T-Cell Therapy. J Am Coll Cardiol. 2021;78(18):1800-13.\u003c/li\u003e\n\u003cli\u003eHCUP\u003cstrong\u003e.\u003c/strong\u003e HCUP National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). 2021. Agency for Healthcare Research and Quality, Rockville, MD. 2021.\u003c/li\u003e\n\u003cli\u003evon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP\u003cstrong\u003e. \u003c/strong\u003eThe Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344-9.\u003c/li\u003e\n\u003cli\u003eJain T, Bar M, Kansagra AJ, Chong EA, Hashmi SK, Neelapu SS, et al.Use of Chimeric Antigen Receptor T Cell Therapy in Clinical Practice for Relapsed/Refractory Aggressive B Cell Non-Hodgkin Lymphoma: An Expert Panel Opinion from the American Society for Transplantation and Cellular Therapy. Biol Blood Marrow Transplant. 2019;25(12):2305-21.\u003c/li\u003e\n\u003cli\u003eInstitute NC 2022;Pageshttps://www.cancer.gov/about-cancer/treatment/research/car-t-cells on 11/25/2022 2022.\u003c/li\u003e\n\u003cli\u003eRoffman CE, Buchanan J, Allison GT\u003cstrong\u003e. \u003c/strong\u003eCharlson Comorbidities Index. J Physiother. 2016;62(3):171.\u003c/li\u003e\n\u003cli\u003eHosmer Jr DW, Lemeshow S, Sturdivant RX\u003cstrong\u003e.\u003c/strong\u003e Applied logistic regression: John Wiley \u0026amp; Sons; 2013.\u003c/li\u003e\n\u003cli\u003eElisabeth Kato MD, M.R.P., Quyen Ngo-Metzger, M.D., M.P.H., Kathryn R. Fingar, Ph.D., M.P.H., Kimberly W. McDermott, Ph.D., and Anne Elixhauser, Ph.D.;Pageswww.hcup-us.ahrq.gov/reports/statbriefs/sb236-Atrial-Fibrillation-Hospital-Stays-Trends.jsp.\u003c/li\u003e\n\u003cli\u003eEmole J, Lawal O, Lupak O, Dias A, Shune L, Yusuf K\u003cstrong\u003e. \u003c/strong\u003eDemographic differences among patients treated with chimeric antigen receptor T-cell therapy in the United States. Cancer Med. 2022;11(23):4440-8.\u003c/li\u003e\n\u003cli\u003eBaral N, Mitchell JD, Aggarwal NT, Paul TK, Seri A, Arida AK, et al.Sex-based disparities and in-hospital outcomes of patients hospitalized with atrial fibrillation with and without dementia. Am Heart J Plus. 2023;26:100266.\u003c/li\u003e\n\u003cli\u003eChamberlain AM, Roger VL, Noseworthy PA, Chen LY, Weston SA, Jiang R, et al.Identification of Incident Atrial Fibrillation From Electronic Medical Records. J Am Heart Assoc. 2022;11(7):e023237.\u003c/li\u003e\n\u003cli\u003ePatel R, Patel M, Laxmidhar F, Lakhatariya K, Patel D, Patel Z, et al.Cytokine Release Syndrome in Patients Treated With Chimeric Antigen Receptor T-cell Therapy: A Retrospective Study Analyzing Risks, Outcomes, and Healthcare Burden. Cureus. 2023;15(11):e49452.\u003c/li\u003e\n\u003cli\u003eHe Y\u003cstrong\u003e. \u003c/strong\u003eMissing data analysis using multiple imputation: getting to the heart of the matter. Circ Cardiovasc Qual Outcomes. 2010;3(1):98-105.\u003c/li\u003e\n\u003cli\u003eAlvi RM, Frigault MJ, Fradley MG, Jain MD, Mahmood SS, Awadalla M, et al.Cardiovascular Events Among Adults Treated With Chimeric Antigen Receptor T-Cells (CAR-T). J Am Coll Cardiol. 2019;74(25):3099-108.\u003c/li\u003e\n\u003cli\u003eLefebvre B, Kang Y, Smith AM, Frey NV, Carver JR, Scherrer-Crosbie M\u003cstrong\u003e. \u003c/strong\u003eCardiovascular Effects of CAR T Cell Therapy: A Retrospective Study. JACC CardioOncol. 2020;2(2):193-203.\u003c/li\u003e\n\u003cli\u003eHan H, Chen L, Lin Z, Wei X, Guo W, Yu Y, et al.Prevalence, trends, and outcomes of atrial fibrillation in hospitalized patients with metastatic cancer: findings from a national sample. Cancer Med. 2021;10(16):5661-70.\u003c/li\u003e\n\u003cli\u003eJackson I, Oyenubi O, Etuk A, Jackson N\u003cstrong\u003e. \u003c/strong\u003eARRHYTHMIA BURDEN AND FACTORS PREDICTING MORTALITY AMONG HOSPITALIZED PATIENTS WITH DIFFUSE LARGE B-CELL LYMPHOMA. Journal of the American College of Cardiology. 2022;79(9_Supplement):1907-.\u003c/li\u003e\n\u003cli\u003eLee DW, Santomasso BD, Locke FL, Ghobadi A, Turtle CJ, Brudno JN, et al.ASTCT Consensus Grading for Cytokine Release Syndrome and Neurologic Toxicity Associated with Immune Effector Cells. Biol Blood Marrow Transplant. 2019;25(4):625-38.\u003c/li\u003e\n\u003cli\u003eGanatra S, Carver JR, Hayek SS, Ky B, Leja MJ, Lenihan DJ, et al.Chimeric Antigen Receptor T-Cell Therapy for Cancer and Heart: JACC Council Perspectives. J Am Coll Cardiol. 2019;74(25):3153-63.\u003c/li\u003e\n\u003cli\u003eMaude SL, Laetsch TW, Buechner J, Rives S, Boyer M, Bittencourt H, et al.Tisagenlecleucel in Children and Young Adults with B-Cell Lymphoblastic Leukemia. N Engl J Med. 2018;378(5):439-48.\u003c/li\u003e\n\u003cli\u003eGanatra S, Redd R, Hayek SS, Parikh R, Azam T, Yanik GA, et al.Chimeric Antigen Receptor T-Cell Therapy-Associated Cardiomyopathy in Patients With Refractory or Relapsed Non-Hodgkin Lymphoma. Circulation. 2020;142(17):1687-90.\u003c/li\u003e\n\u003cli\u003eLinette GP, Stadtmauer EA, Maus MV, Rapoport AP, Levine BL, Emery L, et al.Cardiovascular toxicity and titin cross-reactivity of affinity-enhanced T cells in myeloma and melanoma. Blood. 2013;122(6):863-71.\u003c/li\u003e\n\u003cli\u003eGrigor EJM, Fergusson D, Kekre N, Montroy J, Atkins H, Seftel MD, et al.Risks and Benefits of Chimeric Antigen Receptor T-Cell (CAR-T) Therapy in Cancer: A Systematic Review and Meta-Analysis. Transfus Med Rev. 2019;33(2):98-110.\u003c/li\u003e\n\u003cli\u003eStaerk L, Sherer JA, Ko D, Benjamin EJ, Helm RH\u003cstrong\u003e. \u003c/strong\u003eAtrial Fibrillation: Epidemiology, Pathophysiology, and Clinical Outcomes. Circ Res. 2017;120(9):1501-17.\u003c/li\u003e\n\u003cli\u003eProietti M, Esteve-Pastor MA, Rivera-Caravaca JM, Rold\u0026aacute;n V, Rold\u0026aacute;n Rabad\u0026aacute;n I, Mu\u0026ntilde;iz J, et al.Relationship between multimorbidity and outcomes in atrial fibrillation. Exp Gerontol. 2021;153:111482.\u003c/li\u003e\n\u003cli\u003eBenjamin EJ, Wolf PA, D\u0026apos;Agostino RB, Silbershatz H, Kannel WB, Levy D\u003cstrong\u003e. \u003c/strong\u003eImpact of atrial fibrillation on the risk of death: the Framingham Heart Study. Circulation. 1998;98(10):946-52.\u003c/li\u003e\n\u003cli\u003eGutierrez C, Neilan TG, Grover NS\u003cstrong\u003e. \u003c/strong\u003eHow I approach optimization of patients at risk of cardiac and pulmonary complications after CAR T-cell therapy. Blood. 2023;141(20):2452-9.\u003c/li\u003e\n\u003cli\u003eFradley MG, Beckie TM, Brown SA, Cheng RK, Dent SF, Nohria A, et al.Recognition, Prevention, and Management of Arrhythmias and Autonomic Disorders in Cardio-Oncology: A Scientific Statement From the American Heart Association. Circulation. 2021;144(3):e41-e55.\u003c/li\u003e\n\u003cli\u003eFriedman A, Miles J, Liebelt J, Christia P, Engstrom K, Thachil R, et al.QT Dispersion and Drug-Induced Torsade de Pointes. Cureus. 2021;13(1):e12895.\u003c/li\u003e\n\u003cli\u003eCummings Joyner AK, Snider JT, Wade SW, Wang ST, Buessing MG, Johnson S, et al.Cost-Effectiveness of Chimeric Antigen Receptor T Cell Therapy in Patients with Relapsed or Refractory Large B Cell Lymphoma: No Impact of Site of Care. Adv Ther. 2022;39(8):3560-77.\u003c/li\u003e\n\u003cli\u003eLin JK, Muffly LS, Spinner MA, Barnes JI, Owens DK, Goldhaber-Fiebert JD\u003cstrong\u003e. \u003c/strong\u003eCost Effectiveness of Chimeric Antigen Receptor T-Cell Therapy in Multiply Relapsed or Refractory Adult Large B-Cell Lymphoma. J Clin Oncol. 2019;37(24):2105-19.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Baseline Socio-demographics and Comorbidity Index of CAR-T patients with and without Atrial Fibrillation\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"676\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline Demographics and Comorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Study\u003cbr\u003e \u003cem\u003en\u003c/em\u003e=1030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" valign=\"top\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAR-T with AF \u003cem\u003en\u003c/em\u003e=97 (9.4%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" valign=\"top\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAR-T without AF \u003cem\u003en\u003c/em\u003e=933 (90.6%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years) \u0026plusmn;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003e55.6\u0026plusmn;18.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e68.2\u0026plusmn;9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e54.3\u0026plusmn;18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, \u003cem\u003en\u003c/em\u003e (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003e613 (59.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e75 (78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e538 (57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e417 (40.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e21 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e396 (42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace, \u003cem\u003en\u003c/em\u003e (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003eCaucasian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003e704 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e79 (84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e625 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e63 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e59 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e125 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e124 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e40 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e39 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsurance, \u003cem\u003en\u0026nbsp;\u003c/em\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003e335 (32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e55 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e280 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e105 (10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e102 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e524 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e33 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e491 (52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e27 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e25 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion, \u003cem\u003en\u0026nbsp;\u003c/em\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003e283 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e24 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e259 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"4\"\u003e\n \u003cp\u003e0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eMidwest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e245 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e22 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e223 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e268 (26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e33 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e235 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e234 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e17 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e217 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSetting/location, \u003cem\u003en\u003c/em\u003e (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"3\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eUrban non-teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eUrban teaching\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e1023 (99.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e96 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e927 (99.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed size, \u003cem\u003en\u0026nbsp;\u003c/em\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003eSmall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003e129 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e14 (14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e115 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e143 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e137 (14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e758 (73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\" style=\"width: 12.6364%;\"\u003e\n \u003cp\u003e76 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\" style=\"width: 17.5411%;\"\u003e\n \u003cp\u003e682 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson comorbidity index, \u003cem\u003en\u0026nbsp;\u003c/em\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e614 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\"\u003e\n \u003cp\u003e38 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\"\u003e\n \u003cp\u003e576 (61.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003e3 or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e413 (40.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\"\u003e\n \u003cp\u003e57 (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\"\u003e\n \u003cp\u003e356 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.11242603550296%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnual income (US $ per year), \u003cem\u003en\u003c/em\u003e (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34319526627219%\"\u003e\n \u003cp\u003e1-45,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.349112426035504%\"\u003e\n \u003cp\u003e175 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.715976331360945%\"\u003e\n \u003cp\u003e16 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.976331360946746%\"\u003e\n \u003cp\u003e159 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.502958579881657%\" rowspan=\"4\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003e46K\u0026ndash;58,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e205 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\"\u003e\n \u003cp\u003e18 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\"\u003e\n \u003cp\u003e187 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003e59K-78,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e276 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\"\u003e\n \u003cp\u003e20 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\"\u003e\n \u003cp\u003e256 (28.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.054298642533936%\"\u003e\n \u003cp\u003e79K or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.945701357466064%\"\u003e\n \u003cp\u003e329 (33.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.56561085972851%\"\u003e\n \u003cp\u003e40 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.43438914027149%\"\u003e\n \u003cp\u003e289 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eComparison of baseline socio-demographics and Charlson Comorbidity Index in patients admitted for CAR-T with and without atrial fibrillation. Data reflects all hospitalizations from the National Inpatient Sample between 2017-2020 with an FDA approved indication for CAR-T. Cancer types included are diffuse large B cell lymphoma, B-cell precursor acute lymphoblastic leukemia, follicular lymphoma, mantle cell lymphoma, and multiple myeloma. Frequencies less than 11 are marked as \u0026ldquo;N/A\u0026rdquo; due to Healthcare Cost and Utilization Project (HCUP) guidelines. The Student t-test assessed differences in continuous variables while Chi-squared assessed differences in categorical variables.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations:\u003c/p\u003e\n\u003cp\u003eAF: Atrial fibrillation, N/A: Non-applicable. As per National inpatient sample we cannot report numbers less than or equal to 11 so in such cases N/A has been used.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAR-T: Chimeric Receptor Antigen T-cell therapy, FDA: Food and Drug Administration, US: United States, SD: Standard Deviation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. In-hospital Cardiovascular and Bleeding Diagnoses Associated with CAR-T with and without AF\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"771\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Study\u003cbr\u003e\u0026nbsp;n=1030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAR-T with AF \u003cem\u003en\u003c/em\u003e=97 (9.4%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCAR-T without AF \u003cem\u003en\u003c/em\u003e=933 (90.6%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiovascular Risk Factors\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e396 (38.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e55 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e341 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.93103448275862%\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.06896551724138%\"\u003e\n \u003cp\u003e70 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.862068965517242%\"\u003e\n \u003cp\u003e5 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.82758620689655%\"\u003e\n \u003cp\u003e65 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.310344827586206%\"\u003e\n \u003cp\u003e0.671\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiovascular Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eCAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e65 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e18 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e47 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.93103448275862%\"\u003e\n \u003cp\u003ePericardial disease including pericarditis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.06896551724138%\"\u003e\n \u003cp\u003e15 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.862068965517242%\"\u003e\n \u003cp\u003e2 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.82758620689655%\"\u003e\n \u003cp\u003e13 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.310344827586206%\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eArrhythmias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eSupraventricular tachycardia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e35 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e10 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e25 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.93103448275862%\"\u003e\n \u003cp\u003eVentricular arrhythmias\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.06896551724138%\"\u003e\n \u003cp\u003e44 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.862068965517242%\"\u003e\n \u003cp\u003e8 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.82758620689655%\"\u003e\n \u003cp\u003e36 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.310344827586206%\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart failure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eChronic Heart Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e89 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e24 (24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e65 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.93103448275862%\"\u003e\n \u003cp\u003eAcute Heart Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.06896551724138%\"\u003e\n \u003cp\u003e12 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.862068965517242%\"\u003e\n \u003cp\u003e6 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.82758620689655%\"\u003e\n \u003cp\u003e6 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.310344827586206%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.93103448275862%\"\u003e\n \u003cp\u003ePulmonary Edema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.06896551724138%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.862068965517242%\"\u003e\n \u003cp\u003e8 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.82758620689655%\"\u003e\n \u003cp\u003e25 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.310344827586206%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcute myocardial infarction (AMI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eAMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e6 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e23 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eThromboembolism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eAcute DVT and PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e2 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e18 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypotension and Critical Care\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eHypotension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e34 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e261 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.93103448275862%\"\u003e\n \u003cp\u003eMechanical ventilation requirement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.06896551724138%\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.862068965517242%\"\u003e\n \u003cp\u003e8 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.82758620689655%\"\u003e\n \u003cp\u003e37 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.310344827586206%\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.77302204928664%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBleeding Complications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.250324254215304%\"\u003e\n \u003cp\u003eGI Bleed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.84046692607004%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.693904020752269%\"\u003e\n \u003cp\u003e5 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.67704280155642%\"\u003e\n \u003cp\u003e13 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.765239948119326%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.93103448275862%\"\u003e\n \u003cp\u003eDIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.06896551724138%\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.862068965517242%\"\u003e\n \u003cp\u003e9 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.82758620689655%\"\u003e\n \u003cp\u003e29 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.310344827586206%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eComparison of inpatient cardiovascular and bleeding diagnoses in patients admitted for CAR-T with and without atrial fibrillation. Data reflects all hospitalizations from the National Inpatient Sample between 2017-2020 with an FDA approved indication for CAR-T. Cancer types included are diffuse large B cell lymphoma, B-cell precursor acute lymphoblastic leukemia, follicular lymphoma, mantle cell lymphoma, and multiple myeloma. Acute and chronic heart failure, pulmonary edema, supraventricular tachycardia, acute myocardial infarction, hypertension, \u0026nbsp;coronary artery disease, gastrointestinal bleeding, and disseminated intravascular coagulation were more common in atrial fibrillation patients. Variables with a frequency less than 11 are marked as \u0026ldquo;N/A\u0026rdquo; due to Healthcare Cost and Utilization Project (HCUP) policy on reporting low numbers. (N/A marks both the cell in question and the corresponding cell to prevent computation of the missing cell count).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbbreviations: CAR-T: Chimeric Receptor Antigen T-cell Therapy, CAD: Coronary Artery Disease, CCI: Charlson Comorbidity Index, DVT: Deep Vein Thrombosis, DIC: Disseminated Intravascular Coagulation, FDA: Food and Drug Administration, GI: Gastro-Intestinal AMI : Acute Myocardial Infarction includes (STEMI: ST Segment Elevation Myocardial Infarction, N/A: Not Available, NSTEMI: Non-ST Segment Elevation Myocardial Infarction, and UA: Unstable angina), PE: Pulmonary Embolism, SD: Standard Deviation, SVT: Supra Ventricular Tachycardia\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Unadjusted and Adjusted Odds Ratios for In-Hospital Mortality During CAR-T Hospitalization in the NIS 2017-2020\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"683\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.62811127379209%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.478770131771597%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariable Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.89311859443631%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.62811127379209%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.97-1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.96\u0026ndash;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtrial fibrillation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e1.43-6.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e1.61-9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale Sex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.42-1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.51-1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003eRef: Caucasian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003eAfrican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.66-6.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.63-5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.34-2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.21-2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.37-6.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.38-8.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnual income\u0026nbsp;\u003cbr\u003e\u0026nbsp;(US$ per year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003eRef: 1-45,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003e46K\u0026ndash;58,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.89-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.09-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003e59K-78,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.26-1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.28-1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003e79K or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e0.53-3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.55-4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson Comorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e1.10-3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e0.92-3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.569546120058565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.05856515373353%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.052708638360176%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.030746705710103%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.395314787701318%\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.224011713030746%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.71303074670571%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.956076134699854%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Univariable and multivariable logistic regression assessed the association of baseline socio-demographics, charlson-comorbidity index and atrial fibrillation with in-hospital mortality. Variables were included in the multivariable model if the unadjusted p-value was \u0026pound; 0.20. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbbreviations: NIS: National Inpatient Sample, CAR-T: Chimeric Receptor Antigen T-cell Therapy, LL: lower limit, UP: upper limit, N/A: Not application in multivariate regression \u0026nbsp;OR: Odds ratio USD: United States Dollar\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u003c/strong\u003e Adjusted odds ratio (effect) of various in-hospital outcomes in CAR-T AF group compared to CAR-T non-AF group.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"472\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.46088794926004%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn-hospital outcomes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.061310782241016%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.084566596194502%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39323467230444%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.46088794926004%\"\u003e\n \u003cp\u003eIn-hospital mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.061310782241016%\"\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.084566596194502%\"\u003e\n \u003cp\u003e1.61\u0026ndash;9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39323467230444%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.46088794926004%\"\u003e\n \u003cp\u003ePulmonary edema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.061310782241016%\"\u003e\n \u003cp\u003e3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.084566596194502%\"\u003e\n \u003cp\u003e1.34-8.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39323467230444%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.46088794926004%\"\u003e\n \u003cp\u003eGastrointestinal bleed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.061310782241016%\"\u003e\n \u003cp\u003e5.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.084566596194502%\"\u003e\n \u003cp\u003e1.95\u0026ndash;15.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39323467230444%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.46088794926004%\"\u003e\n \u003cp\u003eAcute Heart Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.061310782241016%\"\u003e\n \u003cp\u003e10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.084566596194502%\"\u003e\n \u003cp\u003e2.15\u0026ndash;47.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39323467230444%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.46088794926004%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.061310782241016%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta Coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.084566596194502%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39323467230444%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.46088794926004%\"\u003e\n \u003cp\u003eLength of stay\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.061310782241016%\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.084566596194502%\"\u003e\n \u003cp\u003e0.01\u0026ndash;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39323467230444%\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAdjusted odds ratios and beta coefficient after multivariable logistic regression and negative binomial regression in primary and secondary outcomes adjusted for age, sex, race, comorbidity, and income. The median length of stay in CAR-T with AF was 23 days compared to 20 days in the CAR-T group without AF.\u003c/p\u003e\n\u003cp\u003eAbbreviations: AF: Atrial Fibrillation, CAR-T: Chimeric Antigen Receptor T-cell therapy, CI: Confidence Interval, OR: Odds Ratio, LL: Lower limit, UL: Upper Limit\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cardio-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caon","sideBox":"Learn more about [Cardio-Oncology](http://cardiooncologyjournal.biomedcentral.com)","snPcode":"40959","submissionUrl":"https://submission.nature.com/new-submission/40959/3","title":"Cardio-Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chimeric Antigen Receptor T-cell therapy, Atrial fibrillation, Cohort Study, In-hospital Mortality, Cardiovascular disease, Cancer","lastPublishedDoi":"10.21203/rs.3.rs-4931828/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4931828/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eChimeric Antigen Receptor (CAR) T-cell therapy (CAR-T) has emerged as a promising treatment for specific hematological malignancies. While some studies suggest an association between CAR-T and atrial fibrillation (AF), more data are needed on the impact of AF on CAR-T outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis retrospective cohort study utilized the National Inpatient Sample (NIS) 2017-2020 to explore in-hospital outcomes in cancer patients with AF while undergoing CAR-T. Comparisons were drawn between patients with and without AF (occurring at any time), assessing various parameters including mortality rates, length of hospital-stay, and occurrences of acute heart failure, pulmonary edema, and gastrointestinal (GI) bleeding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOf the 236,270 cancer-related hospitalizations, 1,030 cases (0.44%) received CAR-T. The average age of CAR-T recipients was 55.6 years ±18.1 years, and females constituted 40.5% of the total CAR-T recipients. Of the 1030 patients receiving CAR-T, 97 (9.4%) had an associated diagnosis of AF (occurring at any time) during their hospitalization. A multivariable logistic regression analysis, adjusted for age, sex, race, comorbidity, and income, revealed that cancer hospitalizations who underwent CAR-T therapy with AF had increased odds of in-hospital mortality (adjusted odds ratio, aOR: 3.87), acute pulmonary edema (aOR: 3.29), GI bleeding (aOR: 5.46), acute heart failure (aOR: 10.2), and extended hospital stays (Beta coefficient: 0.18) compared to hospitalizations with CAR-T but without AF. Similar results were seen in a sensitivity analysis limited to diffuse large B cell lymphoma patients receiving CAR-T.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e In cancer patients receiving CAR-T, AF is independently associated with a higher risk of in-hospital mortality, acute pulmonary edema, gastrointestinal bleeding, acute heart failure, and prolonged hospitalization.\u003c/p\u003e","manuscriptTitle":"Atrial Fibrillation Is Associated with Increased In-Hospitality Mortality During Chimeric Antigen Receptor T-cell Therapy Hospitalizations: A Retrospective Cohort Study in the United States. ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-15 05:01:11","doi":"10.21203/rs.3.rs-4931828/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-23T13:52:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-22T17:05:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-16T16:01:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"114532256126638461715580003933861125022","date":"2024-09-13T03:57:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298579326287209000038038448561610176597","date":"2024-09-08T23:44:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-03T18:27:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-22T16:53:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-20T07:01:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardio-Oncology","date":"2024-08-18T04:26:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cardio-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caon","sideBox":"Learn more about [Cardio-Oncology](http://cardiooncologyjournal.biomedcentral.com)","snPcode":"40959","submissionUrl":"https://submission.nature.com/new-submission/40959/3","title":"Cardio-Oncology","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3a7f1c35-1db6-4a78-87c7-126770cc8182","owner":[],"postedDate":"October 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-07T16:15:55+00:00","versionOfRecord":{"articleIdentity":"rs-4931828","link":"https://doi.org/10.1186/s40959-025-00334-5","journal":{"identity":"cardio-oncology","isVorOnly":false,"title":"Cardio-Oncology"},"publishedOn":"2025-07-03 15:58:06","publishedOnDateReadable":"July 3rd, 2025"},"versionCreatedAt":"2024-10-15 05:01:11","video":"","vorDoi":"10.1186/s40959-025-00334-5","vorDoiUrl":"https://doi.org/10.1186/s40959-025-00334-5","workflowStages":[]},"version":"v1","identity":"rs-4931828","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4931828","identity":"rs-4931828","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}