Shown are the frequencies of atrial fibrillation symptoms in women and men. The P values are for the differences between women and men.
eAppendix. ORBIT-AF: 55 Candidate Variable List for Multivariable Outcome Models
eTable 1. Baseline Characteristics According to Sex in the Quality of Life Substudy Cohort
eTable 2. Overall AFEQT Scores in Women and Men According to the Type of AF and CHA2DS2-VASc Risk Scores
eTable 3. Sex and Outcomes According to Alternative Adjustment Cox Regression Frailty Models
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Piccini JP, Simon DN, Steinberg BA, et al. Differences in Clinical and Functional Outcomes of Atrial Fibrillation in Women and Men: Two-Year Results From the ORBIT-AF Registry. JAMA Cardiol. 2016;1(3):282–291. doi:10.1001/jamacardio.2016.0529
Copyright 2016 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.This article is published under JAMA Cardiology’s open access model and is free to read on the day of publication.
Despite the frequency of atrial fibrillation (AF) in clinical practice, relatively little is known about sex differences in symptoms and quality of life and how they may affect treatment and outcomes.
To determine whether symptoms, quality of life, treatment, and outcomes differ between women and men with AF.
Design, Setting, and Participants
This observational cohort study included 10 135 patients with AF. The Outcomes Registry for Better Informed Treatment of Atrial Fibrillation is a prospective, nationwide, multicenter outpatient registry of patients with incident and prevalent AF enrolled at 176 sites between June 2010 and August 2011.
Main Outcomes and Measures
Symptoms, quality of life as measured by Atrial Fibrillation Effects on Quality of Life scores, AF treatment, cardiovascular outcomes, stroke or non–central nervous system embolism, and all-cause mortality.
Overall, 4293 of the cohort (42%) were female. Compared with men, women were older (77 years; interquartile range [IQR], 69-83, vs 73 years; IQR, 65-80; P < .001) and had higher median CHA2DS2-VASc scores (5; IQR, 4-6, vs 3; IQR, 2-5; P < .001), but less sleep apnea (578 [13.5%] vs 1264 [21.6%]; P < .001). Only 32.1% of women (n = 1378) were asymptomatic (European Heart Rhythm Association class I) compared with 42.5% of men (n = 2483) in unadjusted analyses (P < .001). Women had lower (more severe) unadjusted baseline overall Atrial Fibrillation Effects on Quality of Life scores (n = 2007; 80; IQR, 62-92 vs 83; IQR, 69-94; P < .001). Women had similar rates of anticoagulation and similar time in therapeutic range. In follow-up, women experienced lower risk-adjusted all-cause mortality (adjusted hazard ratio, 0.57; 95% CI, 0.49-0.67) and cardiovascular death (adjusted hazard ratio, 0.56; 95% CI, 0.44-0.72); however, they had a higher risk for stroke or non–central nervous system embolism (adjusted hazard ratio, 1.39; 95% CI, 1.05-1.84; P = .02) compared with men.
Conclusions and Relevance
Women with AF have more symptoms and worse quality of life. Despite higher risk, women have lower risk-adjusted all-cause and cardiovascular death compared with men, but higher stroke rates. Future studies should focus on how treatment and interventions specifically affect AF-related quality of life and cardiovascular outcomes in women.
clinicaltrials.gov Identifier: NCT01165710
Atrial fibrillation (AF) is a growing and costly public health problem for which most studies have focused on thromboembolic outcomes, although the disease is known to impair patients’ health status: their symptoms, function, and quality of life (QoL).1,2 While there are well-documented sex-based differences in treatment, health status, and other clinical outcomes in other cardiovascular diseases, these have been infrequently described in AF.3-5 If present, such sex-related differences could stimulate new efforts to better manage AF, potentially including antiarrhythmic therapy and radiofrequency ablation, to minimize health status disparities.
The nationwide multicenter Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) provides a unique opportunity to examine this gap in knowledge because the registry prospectively collects information on AF treatment and patients’ health status. Accordingly, we examined whether symptoms, functional capacity, and QoL differed between women and men enrolled in ORBIT-AF. We hypothesized that women with AF would have worse symptoms, lower QoL, and worse clinical outcomes relative to men.
Question Are symptoms, quality of life, and outcomes different in women and men with atrial fibrillation (AF)?
Findings In this observational cohort study of 10 135 patients with AF, only 32.1% of women were asymptomatic vs 42.5% of men. Women had worse adjusted AF-related quality of life. While women experienced lower risk-adjusted all-cause mortality, they had a higher risk for thromboembolism compared with men.
Meaning Patient experience and subsequent outcomes are different in women and men with AF. Women with AF experience more symptoms, worse quality of life, and higher risk for stroke, but better overall survival.
The ORBIT-AF study is a prospective, multicenter nationwide, outpatient registry of patients with incident and prevalent AF. Patients were enrolled at 176 sites between June 2010 and August 2011 by a diverse group of health care professionals including internists, cardiologists, and electrophysiologists. The rationale, design, and methods of the ORBIT-AF registry have been reported previously.6 The study and all its analyses are approved under a continuous institutional review board at Duke University (the coordinating center) and each participating center obtained local institutional review board approval; all participants provided informed consent. Eligible patients were required to have electrocardiographic AF and be 18 years of age or older, able to provide consent, and adhere with local follow-up. Patients with solitary atrial flutter without AF, a life expectancy of less than 6 months, or AF secondary to an easily reversible condition were excluded. Patients were followed up at 6-month intervals. Outcomes assessed in follow-up included all-cause mortality, cardiovascular death, hospitalization, stroke or non–central nervous system (CNS) systemic embolism, new-onset heart failure, and bleeding.
The ORBIT-AF registry included a health-related QoL substudy, which was conducted at 99 of the 176 total study sites. Patients in the substudy underwent assessment of AF-related QoL using the validated Atrial Fibrillation Effects on Quality of Life questionnaire (AFEQT; http://www.afeqt.org) at baseline (n = 2007), 12 months (n = 1346), and 24 months (n = 988). The development and validation of the AFEQT have been previously described.7 The AFEQT is a 20-item survey using 7-point Likert response scales that was developed through serial iterations with patients, factor-level analysis, and psychometric testing, which measures AF-specific health status. It quantifies 4 domains of patients’ health status: symptoms, daily activities, treatment concern, and treatment satisfaction, with the first 3 being used to generate an overall summary score. The AFEQT scores range from 0 to 100, with 100 representing the best possible health status (no impairment) and 0 representing the worst.
For the purpose of this analysis, the ORBIT-AF cohort population was stratified and analyzed by sex overall (N = 10 135; 176 sites) and for the patient-reported outcomes cohort (n = 2007; 99 sites). Patients were included regardless of AF type or management strategy (rate or rhythm control). Baseline characteristics were compared between women and men, including demographics, general medical history, cardiovascular history, AF history, prior procedures, prior and current medical therapies, vital signs, echocardiographic data (left ventricular ejection fraction and left atrial diameter), and laboratory studies. An inventory of AF-related symptoms and data regarding AF-functional limitation were also collected. Risk scores for stroke (eg, cardiac failure or dysfunction, hypertension, age ≥75 years [doubled], diabetes, stroke [doubled]–vascular disease, age 65-74 years, and sex category [female] [CHA2DS2-VASc]) were calculated and compared. Data are reported as frequencies and percentages for categorical variables and medians (interquartile ranges [IQRs]) for continuous variables. The χ2 test for categorical variables and the Wilcoxon rank-sum test for continuous variables were used for univariate comparisons.
The AFEQT is bounded between 0 and 100 and is not normally distributed. Therefore, to determine the association between female sex and QoL at baseline, a multivariable binomial regression model was used to model the proportion of AFEQT points achieved out of 100.8,9 An empirical variance was used to account for the fact that AFEQT is a proportion, but not a sum of independent Bernoulli trials. Additionally, site was included as a random effect to account for site variability. Backward selection with a retention criterion of α = .05 with the covariates listed in the eAppendix in the Supplement as potential candidate variables was used to build the model. Additionally, continuous covariates were evaluated for linearity with overall AFEQT score at baseline and nonlinearity was addressed with piecewise splines. Adjusted associations were displayed as odds ratios (95% CIs).
To examine the association between female sex and change in QoL, a multivariable hierarchical linear regression model was constructed for change in overall AFEQT score within 1 year using backward selection with a stay criterion of α = .05 with the covariates listed in the eAppendix in the Supplement. Change in overall AFEQT score within 1 year was defined as overall AFEQT score at 12 months minus overall AFEQT score at baseline. Therefore, a positive change signifies improved QoL and a negative change indicates reduced QoL. The overall estimate represents the difference in mean change score between women and men, holding other covariates constant. Adjusted associations were displayed as regression estimates (95% CIs).
Subsequently, to determine whether female sex was independently associated with outcomes, Cox frailty models (which account for clustered patients within a site by adding a random effect for site) were used to examine the association of female sex and time from enrollment with outcomes in follow-up (all-cause death, cardiovascular death, noncardiovascular death, sudden cardiac death, revascularization, myocardial infarction, new-onset heart failure diagnosis, stroke or non-CNS embolism, all-cause hospitalization, cardiovascular hospitalization, bleeding-cause hospitalization, all-other-cause hospitalization, major bleeding, catheter ablation, atrioventricular node [AVN]/His bundle ablation) among 9743 patients (392 patients were excluded owing to no follow-up data). Missing data were less than 1.2% for cardiovascular death, noncardiovascular death, and sudden cardiac death. All other outcomes had complete data. Models were adjusted for all covariates listed in the eAppendix in the Supplement that were previously identified as statistically significant for each outcome based on backward selection with a retention criterion of α = .05. Adjusted associations for outcomes were displayed as hazard ratios (HRs) (95% CIs).
All candidate variables had less than 2% missingness except for level of education (4%), estimated glomerular filtration rate (8%), hematocrit level (11%), left ventricular ejection fraction (11%), and left atrial diameter (14%). To account for missing data, multiple imputation was used. Five imputed data sets were created with values imputed for all variables included in the modeling. Imputed values were obtained by the Markov chain Monte Carlo method or regression methods. The results from each model were then combined to produce statistical valid inferences when imputed data sets are used. All analyses were performed using SAS software (version 9.3; SAS Institute).
We evaluated 4293 women (42%) and 5842 (58%) men with AF from 176 US practices. The baseline characteristics of the cohort according to sex are shown in Table 1. Compared with men, women with AF were older (77 years; IQR, 69- 83 years, vs 73 years; IQR, 65-80 years; P < .001), but had lower frequencies of obstructive sleep apnea (578 [13.5%] vs 1264 [21.6%]; P < .001) and coronary artery disease (1175 [27.4%] vs 2470 [42.3%]; P < .001). Women more often had a left ventricular ejection fraction of 50% or greater (3300 [76.9%] vs 3813 [65.3%]; P < .001) but had worse renal function (median estimated glomerular filtration rate, 63 mL/min/1.73 m2; IQR, 50-76 mL/min/1.73 m2 vs 70 mL/min/1.73 m2; IQR, 56-86 mL/min/1.73 m2; P < .001). Heart rates at baseline were similar between men and women. Finally, women had higher median CHA2DS2-VASc scores (5; IQR, 4-6 vs 3; IQR, 2-5; P < .001).
In the overall ORBIT-AF cohort, women had greater functional impairment as reflected by higher European Heart Rhythm Association scores (Table 1). Only 32.1% of women (n = 1378) were asymptomatic compared with 42.5% of men (n = 2483) (P < .001). Across the AF symptom checklist, women often reported more symptoms than men (Figure). Forty percent of women (1727/4293) experienced palpitations compared with 27% of men (1576/5842), and women more frequently reported lightheadedness/dizziness (23%, 974/4293 vs 19%, 1110/5842; P < .001) and fatigue (28%, 1216/4293 vs 25%, 1454/5842; P < .001). While orthostasis is often associated with antihypertensive medication use, dizziness/lightheadedness was not more common in women with hypertension compared with women without hypertension (29%, 212/730 vs 35%, 48/136; P = .14). However, dizziness/lightheadedness was more common in women taking antiarrhythmic drugs than in women not taking antiarrhythmic drugs (35%, 85/242 vs 28%, 175/624; P = .04).
In the health-related QoL substudy (n = 2007; eTable 1 in the Supplement), women had lower overall AFEQT scores compared with men: 80; IQR, 62-92 vs 83; IQR, 69-94; P < .001 (Table 2). Overall, patients with recent AF diagnosis (diagnosed as having AF ≤3 months) had worse QoL (77; IQR, 57-91 vs 82; IQR, 68-94; P < .001). As shown in Table 2, women had consistently lower AFEQT domain scores including symptoms, daily activities, and treatment concern. These sex differences persisted when restricting the analysis to those aged 75 years or older (Table 2). The AFEQT scores were also lower in women compared with men in those with paroxysmal and persistent AF and were lower in women with CHA2DS2-VASc scores of 2 and greater (eTable 2 in the Supplement).
After adjustment for baseline characteristics, female sex was associated with lower QoL (OR, 0.67; 95% CI, 0.60-0.75; P < .001). After controlling for baseline characteristics and all AF-related symptoms in the regression for AFEQT, female sex remained associated with lower QoL (OR, 0.76; 95% CI, 0.68-0.84; P < .001). As shown in Table 3, when follow-up QoL at 1 year was investigated among 1346 patients, women continued to have lower QoL with no significant improvement in follow-up vs men (adjusted change in AFEQT, −0.55; 95% CI, −2.34 to 1.24; P = .55) and this persisted out to 2 years (adjusted change in AFEQT, 0.03; 95% CI, −1.99 to 2.05; P = .98).
More than half the cohort had paroxysmal AF (51%), while only 5% had first-detected AF. The distribution of AF type was similar between women and men, although women were less frequently in permanent AF (1109 [25.8%] vs 1721 [29.5%]%; P < .001; Table 1). Compared with men, women were more commonly in sinus rhythm at enrollment (1573 [36.6%] vs 1819 [31.1%]; P < .001). Rates of prior treatment with antiarrhythmic drugs (P = .88) were similar between women and men; however, women were less likely to have a history of cardioversion (1144 [26.7%] vs 1895 [32.4%]; P < .001) or AF ablation (210 [4.9%] vs 342 [5.9%]; P = .04). Women more frequently had a history of AVN ablation (124 [2.9%] vs 97 [1.7%]; P < .001), were less likely to be taking a β-blocker (2662 [62.0]% vs 3827 [65.5%]; P < .001), and slightly more likely to be taking digoxin (1057 [24.6%] vs 131 [22.6%]; P = .02). Current antiarrhythmic therapy was similar in men and women (1244 [28.9%] vs 1669 [28.6%]; P = .65). Warfarin therapy was also similar between men and women with a CHADS2 (congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, and stroke [doubled]) score greater than 1 (2621 [79.6%] vs 3209 [80.5%]; P = .36), although concomitant aspirin (oral anticoagulation and aspirin) was used less frequently in women (921 [21.5%] vs 1803 [30.9%]; P < .001). The median time in therapeutic range was relatively similar between women and men (67%; IQR, 50-78 vs 68%; IQR, 53-81; P < .001) as was the median time with supratherapeutic international normalized ratio greater than 3 (Table 1). In follow-up, there were no differences in adjusted rates of catheter ablation between men and women. Although rates of AVN ablation were very low overall, after adjustment, female sex was associated with a higher risk for AVN ablation (HR, 1.97; 95% CI, 1.30-2.97; P = .001).
Overall, the median follow-up was 2.3 years (IQR, 1.8-2.9 years). Outcomes in full follow-up in women compared with men are shown in Table 4. The observed rates for mortality, cardiovascular death, and noncardiovascular death were similar between women and men. After accounting for baseline risk, women had a lower adjusted risk for most adverse outcomes, including all-cause mortality (adjusted HR, 0.57; 95% CI, 0.49-0.67; P < .001), cardiovascular death (adjusted HR, 0.56; 95% CI, 0.44-0.72; P < .001), and noncardiovascular death (adjusted HR, 0.74; 95% CI, 0.62-0.88; P < .001). However, the incidence of new-onset heart failure, myocardial infarction, revascularization, major bleeding, all-cause hospitalization, and sudden cardiac death were similar between women and men, even after risk adjustment. Women had a higher risk for stroke or non-CNS embolism in both unadjusted and adjusted data, with an adjusted HR of 1.39 (95% CI, 1.05-1.84; P = .02) compared with men. Sensitivity analyses were performed with alternative methods of adjustment, including inclusion of CHA2DS2-VASc score components only, and use of a nonparsimonious common list of covariates led to similar results (eTable 3 in the Supplement).
In this nationwide analysis of sex differences in patients with AF, there were 4 main findings. First, women have more symptoms, more functional impairment, and worse QoL despite less persistent forms of AF. Second, after adjustment, women were more likely to undergo AVN ablation. Third, women experienced a higher risk for stroke or systemic embolism. Finally, in terms of overall outcomes, despite worse QoL and a higher risk for stroke, women had higher risk-adjusted survival and lower risk-adjusted cardiovascular death.
Prior investigations in large registries, including the Registry on Cardiac Rhythm Disorders Assessing the Control of Atrial Fibrillation (RECORD AF)10 and Eurobservational Research Programme–Atrial Fibrillation General Registry Pilot Phase,11 have described the burden of symptoms in AF; however, to our knowledge, few analyses have focused on sex differences in symptoms and health-related QoL. An analysis of sex differences in rhythm-control therapy in persistent AF from the Rate Control vs Electrical Cardioversion Study found that women reported more palpitations, dyspnea, and fatigue and had worse QoL but comparable cardiovascular outcomes.12 While this study focused on sex differences, it was limited by a small sample size (n = 192), exclusion of paroxysmal and permanent AF, and the selection bias associated with a randomized interventional trial. Data from the larger Euro Heart Survey on Atrial Fibrillation found that women with AF had lower general QoL as measured by EuroQol scores (EuroQol 5 Dimensions questionnaire and EuroQol visual analogue scale); however, several reported symptoms were similar between men and women (dyspnea and fatigue) and there was no AF-specific QoL measurement.13
In our large, nationwide, observational cohort, women reported more frequent symptoms, including palpitations, fatigue, lightheadedness, and chest discomfort. These differences in symptoms were significant and occurred despite the fact that women were more frequently in sinus rhythm at the time of evaluation relative to men. Following adjustment for important patient characteristics (including demographics, comorbidities, prior treatment, imaging results, and laboratory evaluations), adjusted QoL was 24% lower in women. Furthermore, analysis of the component domains of the AFEQT demonstrated that women had worse symptoms, more limitation in daily activities, and more concern over their treatment. Thus, the lower QoL in women with AF may be a consequence of both physical and mental consequences of their AF. Although symptoms have been reported to have different patterns in paroxysmal vs persistent AF in the Atrial Fibrillation: Focus on Effective Clinical Treatment Strategies Registry,14 this cannot account for the differences reported in our current ORBIT study because there was no major significant difference in paroxysmal or persistent AF frequencies by sex in ORBIT-AF.
Given the overall prevalence of AF, the evaluation and management of women with AF is commonly encountered in both primary care and specialty cardiovascular care. Clinical decision making is often aided by risk stratification. Many patients in this registry reported symptoms and reduced QoL. Health status instruments, such as AFEQT, may be a valuable resource for identifying patients who might benefit from more aggressive or more specific treatment. More importantly, our data suggest that women are at increased risk for more severe symptom burden and lower QoL compared with men, underscoring the benefits of directly measuring patient-reported health status as a means for minimizing differences in AF management. Clinicians evaluating women with AF should be aware of these differences and ensure that symptom burden and QoL are carefully evaluated before selecting a treatment strategy.
Despite worse QoL, women were no more likely to receive rhythm control. Recent data have suggested that women are less likely to undergo catheter ablation of AF; however, after risk adjustment, we observed similar rates of AF ablation between women and men.15 However, women were more likely to undergo AVN ablation. Although rates of AVN ablation were very low overall, after adjustment, female sex was associated with a 2-fold higher risk for AVN ablation. Atrioventricular nodal ablation is largely considered a treatment of last resort for medically refractory and symptomatic AF. The higher rate of AVN ablation in women is surprising as permanent AF was less common in women (26% vs 30%). Women were older and more likely to have frailty, and this may have contributed to the higher use of AVN ablation in women. The reasons for differences in AVN ablation require further investigation.
Similar to international data from the Prospective Global Anticoagulant Registry in the FIELD,16 we found that oral anticoagulation was similar in women and men in the United States. Female sex is an established, yet controversial, risk factor for stroke in patients with nonvalvular AF.17-19 As expected, women in our study had higher CHA2DS2-VASc scores given the nature of the CHA2DS2-VASc score and the older age of the women relative to men. Our data extend and confirm the results from other studies that demonstrate increased risk for stroke in women. After adjustment, the risk for stroke or systemic embolism was approximately 40% higher in women compared with only 20% in the Swedish Atrial Fibrillation Cohort Study.20 Thus, our nationwide data support the association between female sex and stroke. Interestingly, while the adjusted risk for stroke was 40% higher in women, women experienced lower adjusted overall and cardiovascular-related death rates than men. The reasons for this stroke-survival paradox are not clear; however, the paradox highlights the need for studies focused on how treatment and interventions specifically affect cardiovascular outcomes in women and men with AF. The differences in therapies and response may shed light on important factors associated with disease progression and modification of risk. For example, it is possible that rate and rhythm-control therapies affect disease progression and subsequent QoL differently in men and women. Such differences may help plan studies to guide individualized therapy selection that incorporates sex in addition to other patient characteristics.
There are limitations that need to be considered when evaluating these data. First, the ORBIT-AF registry relied on voluntary participation from sites and patients. Thus, the patients enrolled may not be entirely representative. The median age of the ORBIT-AF cohort is older than has been observed in other registries, with a higher proportion of patients with lone AF but younger than cohorts from Medicare. Thus, the age and comorbidity profile are likely influenced by the older patients with AF encountered in clinical practice.21-23 Despite our use of a large number of characteristics to adjust for potential confounding, residual or unmeasured confounding cannot be excluded. The major differences in unadjusted and adjusted outcomes suggest that confounding may be influencing the observed outcomes, which is not unexpected given the baseline differences between the sexes. Recent data have raised the hypothesis that depression is associated with increased AF symptom burden.24 Whether sex differences in AF symptoms and QoL are influenced by depression requires further study. Finally, palpitations and other symptoms of AF are not always caused by AF and are often experienced in sinus rhythm,25,26 thus, the extent to which these symptoms reflect true arrhythmia in women vs men is also unknown. Nonetheless, the point estimate for the reduction of QoL associated with sex and the differences in cardiovascular outcomes were robust in adjusted analyses. In addition, health status data were available in only a subset of patients. Follow-up was for a median of 2.3 years and with longer-term follow-up different findings may emerge. We did not measure overall QoL, the QoL data used an AF-specific instrument that has been validated.7 Finally, we cannot exclude the possibility that lack of changes in AFEQT scores could be because patients who were experiencing declines did not return for follow-up.
Compared with men, women with AF have more symptoms, more functional limitation, and worse QoL. This impairment in QoL reflects increased symptoms, reduced capacity to engage in daily activities, and more concern regarding treatment. Despite a higher risk for stroke, women had improved risk-adjusted all-cause survival and lower risk-adjusted cardiovascular death compared with men. The reasons for this stroke-survival paradox may have important implications for AF-directed therapies in women and men.
Corresponding Author: Jonathan P. Piccini, MD, MHS, Electrophysiology Section, Duke Center for Atrial Fibrillation, Duke Clinical Research Institute, Duke University Medical Center, PO Box 17969, Durham, NC 27710 (email@example.com).
Accepted for Publication: February 28, 2016.
Published Online: May 18, 2016. doi:10.1001/jamacardio.2016.0529.
Open Access: This article is published under JAMA Cardiology’s open access model and is free to read on the day of publication.
Author Contributions: Drs Piccini and Thomas had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Piccini, Steinberg, Fonarow, Hylek, Kowey, Reiffel, Naccarelli.
Acquisition, analysis, or interpretation of data: Piccini, Simon, Steinberg, Thomas, Allen, Fonarow, Gersh, Hylek, Reiffel, Chan, Spertus, Peterson.
Drafting of the manuscript: Piccini, Gersh.
Critical revision of the manuscript for important intellectual content: Piccini, Simon, Steinberg, Thomas, Allen, Fonarow, Hylek, Kowey, Reiffel, Naccarelli, Chan, Spertus, Peterson.
Statistical analysis: Simon, Steinberg, Thomas.
Obtained funding: Piccini.
Administrative, technical, or material support: Piccini, Steinberg, Allen.
Study supervision: Piccini, Kowey, Naccarelli, Peterson.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Piccini reported receiving a grant from Janssen Pharmaceuticals; consulting fees from Bristol-Myers Squibb/Pfizer and Johnson & Johnson; research support from ARCA Biopharma, Boston Scientific, GE Healthcare, and Johnson & Johnson/Janssen Scientific Affairs; and consultancy fees from Forest Laboratories, Janssen Scientific Affairs, Pfizer/Bristol-Myers Squibb, Spectranetics, and Medtronic. Dr Allen has received personal fees from Janssen and Novartis. Dr Fonarow’s institution has received consultancy fees from Janssen and Medtronic. Dr Gersh has received personal fees from Mount Sinai–St Luke’s, Boston Scientific Corp, Teva Pharmaceuticals, Janssen Scientific Affairs, St Jude Medical, Baxter Healthcare Corp, Cardiovascular Research Foundation, Medtronic, Xenon Pharmaceuticals, Cipla Ltd, Thrombosis Research Institute, and Armetheon Inc. Dr Hylek has received personal fees from Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi Sankyo, Janssen, Medtronic, Pfizer, and Portola. Dr Kowey has received personal fees from Johnson & Johnson. Dr Reiffel has received a grant from Janssen Pharmaceuticals; research support from Boehringer Ingelheim Pharmaceuticals Inc and GlaxoSmithKline; consultancies with Sanofi, Gilead Sciences Inc, CV Therapeutics, GlaxoSmithKline, Merck & Co Inc, Cardiome Pharma Corp, Boehringer Ingelheim Pharmaceuticals Inc, and Medtronic Inc, and significant speakers’ bureau income from Sanofi and Boehringer Ingelheim Pharmaceuticals Inc. Dr Naccarelli has received personal fees from Janssen Pharmaceuticals; grants for clinical research from Wyeth, Reliant, Medtronic, Boston Scientific, Sanofi, and Boehringer Ingelheim; and significant consultancy fees from Wyeth, Reliant, Medtronic, Boston Scientific, Sanofi, Boehringer Ingelheim, Xention, Pfizer, Novartis, GlaxoSmithKline, and St Jude Medical. Dr Chan is an employee of Janssen and has received consultancy fees from Optum Rx and Johnson & Johnson. Dr Spertus has received grants from Eli Lilly and American College of Cardiology Foundation; personal fees from Amgen, Novartis, and Regeneron; has a patent Seattle Angina Questionnaire, Kansas City Cardiomyopathy Questionnaire, and Peripheral Artery Questionnaire licensed; and has a Health Outcomes Sciences patent pending. Dr Peterson has received personal fees from Boehringer Ingelheim, Sanofi, AstraZeneca, Valeant, and Bayer; grants and personal fees from Janssen; and research support from Eli Lilly & Co and Janssen Scientific Affairs. No other disclosures were reported.
Funding/Support: This project was supported in part by cooperative agreement 1U19 HS021092 from the Agency of Healthcare Research and Quality. The Outcomes Registry for Better Informed Treatment of Atrial Fibrillation is sponsored by Janssen Scientific Affairs LLC. Dr Piccini has received grants from the Agency for Healthcare Research and Quality. Dr Allen has received grants from the National Institutes of Health and the Patient-Centered Outcomes Research Institute. Dr Chan has received grants from the National Heart, Lung, and Blood Institute.
Role of the Funder/Sponsor: With the exception of Janssen Scientific Affairs LLC, the funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Group Information: The Outcomes Registry for Better Informed Treatment of Atrial Fibrillation Investigators and Patients members include the following: R. Mendelson, A. Nahhas, J. Neutel, B. Padanilam, D. Pan, J. Poock, J. Raffetto, R. Greengold, P. Roan, F. Saba, M. Sackett, R. Schneider, Z. Seymour, J. Shanes, J. Shoemaker, V. Simms, N. Smiley, D. Smith, C. Snipes, R. Sotolongo, C. Staniloae, S. Stoltz, D. P. Suresh, T. Tak, A. Tannenbaum, S. Turk, K. Vora, P. Randhawa, J. Zebrack, E. Silva, E. Riley, D. Weinstein, T. Vasiliauskas, S. Goldbarg, D. Hayward, C. Yarlagadda, D. Laurion, A. Osunkoya, R. Burns, T. Castor, D. Spiller, C. Luttman, S. Anton, J. McGarvey, R. Guthrie, G. Deriso, R. Flood, L. Fleischer, J. S. Fierstein, R. Aggarwal, G. Jacobs, N. Adjei, A. Akyea-Djamson, A. Alfieri, J. Bacon, N. Bedwell, P. Berger, J. Berry, R. Bhagwat, S. Bloom, F. Boccalandro, J. Capo, S. Kapadia, R. Casanova, J. E. Morriss III, T. Christensen, J. Elsen, R. Farsad, D. Fox, B. Frandsen, M. Gelernt, S. Gill, S. Grubb, C. Hall, H. Harris, D. Hotchkiss, J. Ip, N. Jaffrani, A. Jones, J. Kazmierski, F. Waxman, G. L. Kneller, A. Labroo, B. Jaffe, M. Lebenthal, D. Lee, M. Lillestol, K. LeClerc, P. Maccaro, N. Mayer, J. Kozlowski, S. Benjamin, R. Detweiler, P. Igic, T. Jackson, J. Pappas, R. Littlefield, A. Frey, R. Vranian, W. Long, P. Grena, A. Arouni, J. Quinn, K. Browne, S. Forman, M. Ebinger, R. Blonder, H. Snyder, S. Slabic, D. Williams, R. Stein, S. Kirkland, K. Cohen, W. Walthall, K. Davis, B. Snoddy, O. Alvarado, C. Leach, S. Rothman, A. Sharma, A. Olatidoye, S. AlMahameed, S. Rosenthal, G. Sutter, W. Reiter, T. Thompson, S. Thew, J. Kobayashi, M. Williams, J. Kramer, S. A. Latif, B. Rhee, A. Adler, D. Ruiz-Serrano, S. Stringam, K. Wolok, A. Focil, S. Butman, H. Ingersoll, R. Borge, Y. Al-Saghir, P. Coats, N. Farris, K. Shore, M. B. Schwartz, C. Gornick, P. Eilat, E. Quinlan, Y. Paliwal, R. Mitra, A. Jingo, A. A. Aslam, L. Allen, R. Watson, S. Voyce, M. Turakhia, D. Goytia-Leos, M. Lurie, G. Mallis, B. Atwater, J. Strobel, J. Murray, D. Fisher, M. Atieh, R. Landes, A. Drabick, E. Harman, B. Ashcraft, M. Krista, A. Videlefsky, E. Rivera-Zayas, and A. E. Tan.
Disclaimer: Dr Fonarow is an Associate Editor for JAMA Cardiology but was not involved in the editorial review or decision to accept the manuscript for publication.
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