Impact of atrial fibrillation on patients hospitalized for acute myocarditis: Insights from a nationally‐representative United States cohort

Atrial fibrillation (AF) is associated with increased all‐cause mortality in the general population. However, the impact of AF on the in‐hospital outcomes of acute myocarditis (AM) patients is not well characterized.


| INTRODUCTION
Atrial fibrillation (AF) is the most common cardiac rhythm disorder in clinical practice affecting 2.3% to 3.4% of the adult population worldwide. 1,2 Furthermore, the prevalence and incidence of AF are expected to increase exponentially in the future. 1,2 While several studies have concluded that AF is associated with increased all-cause mortality in the general population, 3,4 very little is known regarding the impact of AF on the prognosis of the patients hospitalized with acute myocarditis (AM). Since AF prevalence is increasing, 1,2 a negative prognostic impact of AF on the natural course of AM has imperative clinical implications. The aim of this study was to describe the outcomes of patients with myocarditis complicated by AF in a large nationally-representative database.

| Data source
Our study was conducted using the National Inpatient Sample (NIS) database, which is part of the Healthcare Cost and Utilization Project sponsored by Agency for Healthcare Research and Quality (AHRQ). 5 NIS is the largest all-payer inpatient stays database in the United States. It represents a 20% stratified sample of all discharges from community hospitals in the United States with approximately 8 million discharges per year. 5 Each patient discharge record in the NIS database includes a single primary diagnosis, and up to 24 secondary diagnoses along with the demographic characteristics, length of stay (LOS), procedures performed, comorbidities, and complications identified during the index admission. 5  diagnostic investigation) and is usually derived after reviewing the patient admission record according to the AHRQ. 6 The approach of identifying AM hospitalizations according to ICD-9-CM codes have been used in prior work examining the NIS. 7 The included myocarditis patients were then stratified into two major groups. The first group was myocarditis patients with AF. The second group constituted the control (no-AF) group. The presence of AF was based on ICD-9-CM code 427.31, which has been previously validated. 8,9 The primary outcome was the impact of AF on inpatient mortality. Secondary outcomes were the impact of AF on inpatient complications like cardiogenic shock, cardiac tamponade, respiratory complications, ischemic strokes, deep venous thrombosis/pulmonary embolism, sepsis, acute kidney injury, and the requirement for a new pacemaker.
We also evaluated the length of hospital stay, discharge pattern, and hospitalization costs. The ICD codes used to identify these complications are available in Table S1, Supporting Information.

| Statistical analysis
We used the hospital trend/discharge weight provided by AHRQ to generate national estimates including sum, rates, and averages. χ 2 test for categorical variable or t test for continuous variable were used to compare baseline characteristics between patient with and without AF. To compare clinical outcomes between patients with and without AF, we created 1:1 matched groups based on propensity score analysis using nearest neighbor matching with a caliper of 0.1 ( Table 2). 10 The propensity score was estimated using a multivariable logistic  without AF (P < 0.001). AM patients with AF were more commonly white (83.6% vs 69.8%, P < 0.001) and more likely to have an Elixhauser score ≥ 4 (33.5% vs 17.5%, P < 0.001). Concerning comorbidity, AM patients with AF were more likely to have peripheral vascular disease, hypertension, diabetes, anemia, congestive heart failure (, chronic obstructive pulmonary disease, renal failure, and coagulation disorder compared to those without AF; and less likely to have obesity, liver failure, and malignancy. Baseline clinical characteristics between the two groups before propensity matching are depicted in Table 1.

| DISCUSSION
Our study revealed two important findings. First, there was a higher risk of in-hospital mortality in hospitalized AM patients with AF. Second, when they concurrently occur, AM and AF synergistically confer a poor prognosis and higher risk of in-hospital complications compared to AM patients without AF. Prevalent AF among AM patients was associated with advanced age, white race, and a high burden of comorbidity (as quantified by Elixhauser score). The previous observation parallels the AF distribution in the general population. 2 Although AF-AM cohort had a high burden of comorbidity, it appears that AF had a major influence on the in-hospital outcomes given the worse outcome among AF-AM group even after rigorous control of confounding factors through propensity matching. Our findings among AM patients with AF are in contrast with findings from previous studies that showed no increased mortality in AM patients with new-onset AF. [12][13][14][15] In the study by Magnani et al. which included 112 patients with biopsy-confirmed myocarditis, presentation with new-onset atrial arrhythmias (AF or flutter) did not predict mortality or the need for cardiac transplantation. 12 However, previous studies lacked national representation and/or sufficient power limiting inferences that could be drawn about the influence of AF on inhospital outcomes. [12][13][14][15] Higher mortality among patients with AF underscores the burden of this complication in patients with AM. AF can induce several neurohormonal, biochemical, and electrophysiological changes at the cellular and extracellular matrix level with subsequent worsening of the myocardial dysfunction. 16,17 Thus, it is expected to find higher rates of mortality and morbidity including cardiogenic shock and acute kidney injury in patients with AF than in patients without AF.
In our study, patients with AF were more likely to develop cardiac tamponade. The reason for a higher proportion of cardiac tamponade among AF-AM patients, however, is unclear and needs to be studied further. AF was associated with longer LOS. Factors like hemodynamic instability (eg, due to rapid ventricular response), higher complications rate (cardiogenic shock, cardiac tamponade, and acute kidney injury) and the use of Vitamin K antagonists impelling international normalized ratio monitoring before discharge may account for the previous findings. However, our study lacks information on rate control and the pattern of anticoagulant agent use.
Therefore, the precise reason underlying this association is not entirely apparent. Given the observed increased LOS, the association of AF with an increased cost of hospitalization was expected.
We found that AF was associated with an increased median cost of approximately $10 163 per hospitalization after adjustment of confounders. Our study also showed an increased risk of nonroutine discharge, including home with home health care, short-and longterm care facilities in the AF cohort, further adding to the overall cost.

| LIMITATIONS
Our study has some limitations that deserve to be emphasized. First, in the NIS database variables are identified using a coding system that is subject to coding errors and documentation disparities. 18 However, the use of ICD-9-CM codes to identify AM or AF has been implemented and validated in previous studies with a reasonable diagnostic performance. [7][8][9]19 Second, our database lacked information on AF subtypes (paroxysmal or permanent), rate control, the pattern of anticoagulation, antiarrhythmic drugs, steroids, and echocardiographic parameters (eg, ejection fraction). Therefore, the impact of the antecedent variables on outcomes cannot be determined, and our ability to precisely identify opportunities to reduce adverse outcomes are limited. Despite lacking this granularity, analysis of large administrative databases is a useful resource for hypothesis-generation which was the primary goal of our study. 20 Third, despite the rigorously adjusted baseline characteristics using propensity score analysis, there is the risk of unmeasured residual confounding in the registry-based retrospective data analysis, for example, AF can be a marker of AM that is complicated at the time of hospitalization. Similarly, in the multicenter Lombardy registry on myocarditis, the patients with severe myocarditis were more likely to present with arrhythmias and more likely to have adverse outcomes. 21 Lastly, our study is limited to the in-hospital outcomes; follow-up data were not reported. However, strengths of this study included the nationallyrepresentative large sample size which involves multiple centers and populations across the United States. The NIS database design has been validated 19 and is commonly used to examine patterns in the US health system among a range of subpopulations including AM. 7 Furthermore, we matched the study patients using propensity score to control for the discrepancies in baseline characteristics.

| CONCLUSION
AF is a frequently encountered arrhythmia in patients admitted to the hospital with acute myocarditis, and it confers an increased risk of in-hospital mortality and complications. Rigorous studies to identify strategies to improve outcomes for this vulnerable subpopulation are warranted.