Chen, Lin Y.

Background: Multiple studies have shown that atrial fibrillation (AF), a common cardiac arrhythmia, is associated with increased mortality and higher incidence of stroke and heart failure. However, evidence for this association in African Americans is lacking. Methods: We studied 4,063 African Americans and 11,280 whites in the Atherosclerosis Risk in Communities (ARIC) Study, a US community-based cohort study, aged 45-64 (55% women) and free of AF at baseline in 1987-89. Three additional follow-up exams were conducted in 1990-92, 1993-95, and 1996-98. AF was ascertained during follow-up with study visit ECGs and hospital surveillance. Mortality and incidence of stroke and heart failure were ascertained according to study protocols. Using multivariable Cox proportional hazards models with time-dependent covariates, we calculated hazard ratios (HR) and 95% confidence intervals (CI) of mortality, stroke and heart failure in those with new-onset AF compared to those without AF by race. Results: During an average follow-up of 18 years, 332 AF cases were ascertained in African Americans and 1407 in whites. Overall, African Americans showed higher all-cause mortality and cardiovascular disease rates than whites ( Table ). AF was associated with increased mortality and risk of incident stroke and heart failure in whites and African Americans, even after adjustment for baseline and time-dependent potential confounders ( Table ). Associations of AF with all-cause mortality and stroke were of similar magnitude in both racial groups. However, the association between AF and heart failure was stronger in whites than in African Americans (HR 3.6, 95% CI 3.1-4.2 in whites, vs. HR 2.2, 95% CI 1.6-3.0 in African Americans). Conclusion: New-onset AF was associated with an increased risk of all-cause mortality, stroke, and heart failure in whites and African Americans independently of other cardiovascular risk factors. Table. Hazard ratios (95% confidence interval) of all-cause mortality, stroke, and heart failure in those with new-onset atrial fibrillation (AF) versus those without AF by race, ARIC, 1987-2008 Blacks Whites P for interaction No AF (n=3731) AF (n=332) No AF (n=9873) AF (n=1407) Mortality Deaths (n) 1144 188 2042 630 Person-years 69,483 1268 200,878 7493 Mortality rate 1 18.6 126.3 10.1 62.3 Model 1 1 (ref.) 5.80 (4.93-6.82) 1 (ref.) 4.58 (4.17-5.04) 0.27 Model 2 1 (ref.) 3.20 (2.71-3.76) 1 (ref.) 2.87 (2.61-3.17) 0.68 Stroke Events (n) 281 23 347 64 Person-years 51,082 867 147,608 5040 Incidence rate 1 6.0 25.0 2.4 11.5 Model 1 1 (ref.) 2.91 (1.81-4.68) 1 (ref.) 2.52 (1.86-3.43) 0.94 Model 2 1 (ref.) 1.83 (1.13-2.96) 1 (ref.) 1.91 (1.39-2.62) 0.82 Heart failure Events 613 71 992 364 Person-years 62,570 721 187,847 4578 Incidence rate 1 10.7 108.1 5.3 76.1 Model 1 1 (ref.) 3.35 (2.41-4.65) 1 (ref.) 4.75 (4.09-5.51) 0.02 Model 2 1 (ref.) 2.18 (1.56-3.04) 1 (ref.) 3.63 (3.12-4.21) 0.0006 1 Age- and sex-standardized, per 1000 person-years; Model 1 : Cox proportional hazards model adjusted for age, sex, and study center, with AF incidence as a time-dependent covariate; Model 2 : As model 1, but additionally adjusting for baseline education, and time-dependent body mass index, smoking, diabetes, hypertension, stroke, heart failure, and myocardial infarction Funding(This research has received full or partial funding support from the American Heart Association, National Center)

Background: Atrial fibrillation (AF) is associated with increased risk of hospitalization. However, little is known about the impact of AF on non-inpatient healthcare utilization or about sex or race differences in AF-related utilization. We examined rates of inpatient and outpatient utilization by AF status in the Atherosclerosis Risk in Communities (ARIC) study. Methods and Results: ARIC cohort participants with incident AF enrolled in fee-for-service Medicare, Parts A and B, for at least 12 continuous months between 1991 and 2009 were matched on age, sex, race and center to up to three participants without AF. Healthcare utilization was ascertained from inpatient and outpatient Medicare claims and classified based on primary ICD-9 code. The analysis included 944 AF and 2,761 non-AF participants. The average number of days hospitalized per year was 13.1 (95% confidence interval [CI]: 11.5-15.0) and 2.8 (95% CI: 2.5-3.1) for those with and without AF, respectively. The corresponding number of outpatient claims per year was 53.2 (95% CI: 50.4-56.1) and 23.0 (95% CI: 22.2-23.8) for those with and without AF, respectively (Table). Most utilization in AF patients was attributable to non-AF conditions, particularly other-cardiovascular disease (CVD)-related reasons; the adjusted rate ratio for days hospitalized per year for other-CVD-related reasons was 4.76 (95% CI: 3.51 - 6.44) for those with compared to those without AF. There was suggestive evidence that sex modified the association between AF and inpatient utilization, with AF related to greater utilization in women than men. The association between AF and healthcare utilization was similar in whites and blacks. Conclusions: This study highlights the considerably greater healthcare utilization (inpatient and outpatient) among those with AF; the differential in utilization due to other-CVD-related reasons was substantial. In addition to recommended heart rate or rhythm treatment, accompanying cardiovascular comorbidities should be evaluated and managed.

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice, causes substantial morbidity, and is associated with an excess risk of mortality. However, information on contemporary time trends in survival after AF is lacking. Thus, we aimed to determine whether survival after incident AF has changed over the last decade in a community-based cohort of 3413 individuals with incident AF between 2000 and 2010. Methods: Olmsted County, MN residents 18 years of age and older with a first-ever AF or atrial flutter event between 2000 and 2010 were identified using inpatient and outpatient diagnostic codes and electrocardiograms. Deaths from any cause were ascertained through August 31, 2012 and time trends in survival after AF were examined using Kaplan-Meier curves and Cox proportional hazards regression. Results: Among 3413 individuals with incident AF (52% men, age range 18-104) between 2000 and 2010, 1561 deaths were observed over a median follow-up of 3.4 years. Survival did not differ by year of AF diagnosis (figure). In addition, the proportion of cardiovascular disease-related deaths compared to non-cardiovascular deaths did not differ over time. After adjustment for age, sex, and Charlson comorbidity index, the hazard ratios for all-cause mortality were 1.09 (95% CI 0.97-1.23) for those diagnosed with AF in 2004-2007 vs. 2000-2003 and 1.04 (95% CI 0.90-1.12) for 2008-2010 vs. 2000-2003. Furthermore, the risk of death did not differ by sex after adjustment for age and comorbidity (HR 1.00, 95% CI 0.90-1.11 for men vs. women). Conclusions: In the community, survival after AF has remained constant over the last decade despite substantial changes in the recommendations for treatment of AF. This underscores the importance of identification of prognostic factors and continued surveillance of outcomes in AF, as well as a better understanding of how to optimize the management of AF to improve outcomes in these patients.

Background: Current guidelines recommend oral anticoagulation for the prevention of stroke in most patients with atrial fibrillation (AF). Direct oral anticoagulants (DOACs) are associated with lower risk of ischemic stroke and intracranial bleeding than warfarin and, therefore, may reduce risk of dementia among patients with AF. Hypothesis: AF patients initiating DOACs for stroke prevention will have lower risk of dementia than patients initiating warfarin. Methods: We used data from two US healthcare claim databases, MarketScan (2007-2015) and Optum Clinformatics (2009-2015). Using validated algorithms, we identified patients with AF who initiated oral anticoagulation. Dementia was defined as having an International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code of 290.xx, 294.xx, or 331.0. Comorbidities and use of other medications were defined based on inpatient, outpatient, and pharmacy claims. We performed a series of head-to-head comparisons of different oral anticoagulants (warfarin, dabigatran, rivaroxaban, and apixaban) in propensity score-matched cohorts. In each database, multivariable-adjusted Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident dementia for each comparison of propensity score-matched cohorts, adjusting for age, sex, comorbidities, use of other medications, and markers of socioeconomic status (in the Optum database only). We meta-analyzed database-specific results using a random-effects model. Results: The analysis included 307,099 AF patients from the MarketScan database and 161,346 from the Optum database, of which 6,572 and 4,391 respectively had a diagnosis of incident dementia. Mean follow up ranged between 0.7 to 2.3 years and incident of diagnosed dementia between 7 to 14 cases per 1000 person-years across different oral anticoagulant initiator groups. Patients initiating DOACs had a lower risk of incident dementia than those initiating warfarin (dabigatran: HR 0.85, 95%CI 0.71, 1.01; rivaroxaban: HR 0.85, 95%CI 0.76, 0.94; apixaban: HR 0.80, 95%CI 0.65, 0.97). There were no differences in risk of incident dementia comparing DOAC user groups (dabigatran vs. rivaroxaban: HR 1.02, 95%CI 0.79, 1.32; dabigatran vs. apixaban: HR 0.92, 95%CI 0.63, 1.36; apixaban vs. rivaroxaban: HR 1.01, 95%CI 0.86, 1.19). Conclusions: Patients with AF initiating DOACs experienced lower rates of incident dementia than warfarin users. No obvious benefit was observed for any particular DOAC in relation to dementia rates.

Background: Oral anticoagulants (OACs) are recommended for AF patients for the prevention of thromboembolic events, including stroke. Stroke risk stratification scores (e.g., CHA 2 DS 2 -VASc) are used to tailor therapeutic recommendations for patients in different risk groups. However, these were derived before the advent of direct OACs. At present, there is no tool that estimates a patient’s stroke risk, given their individual characteristics, by type of OAC. Methods: We used healthcare utilization data from two independent US databases (MarketScan and Optum) to construct and validate a predictive model of ischemic stroke in patients with AF initiating OACs. Patients with non-valvular AF initiating OACs were identified from the MarketScan data for years 2007-2015. Using bootstrapping methods and backward selection of 44 candidate variables, we developed a model which selected variables predicting stroke. The final model was validated in patients with non-valvular AF in the Optum Clinformatics database in the period 2009-2015. Results: Among 135,523 patients with AF initiating OAC in the MarketScan dataset, 2,028 experienced an ischemic stroke after anticoagulant initiation. The stepwise model identified 15 variables (including type of OAC) associated with ischemic stroke (Table). The discrimination (c-statistic) of the model was adequate [0.68, 95% confidence interval (CI) 0.66-0.70], showing excellent calibration (χ 2 = 7.7 p=0.57). The model was then applied to the 84,549 AF patients in the Optum data set (1408 stroke events). The model showed similar discrimination (c-statistic 0.67, 95%CI 0.65-0.70) and calibration (χ 2 = 12.8 p=0.17). However, previously-developed predicted models had similar discriminative ability (CHA 2 DS 2 -VASc 0.67, 95%CI 0.65-0.68; ATRIA 0.67, 95%CI 0.65-0.68) Conclusion: A novel model using extensive administrative healthcare data for the identification of patients at higher risk of ischemic stroke by type of anticoagulant did not perform better than established simple models.

Introduction: We recently reported that abnormal P-wave indices (PWI)—ECG markers of atrial cardiomyopathy (AC)—are associated with an increased risk of dementia, independent of atrial fibrillation (AF) and clinical ischemic stroke. The mechanisms, however, remain unclear, but may include silent ischemia. Hypothesis: Abnormal PWI are associated with higher prevalence of cortical infarcts on MRI, suggesting cardioembolism as a potential mechanism. Methods: ARIC-NCS participants (mean age, 72.2±5.3 years; 60% women; 29% black) who underwent 3T brain MRI scans in 2011-2013 were included. Abnormal PWI included P-wave terminal force in lead V1 [(PTFV1) defined as ≥4000 μV*ms] and P-wave duration [(PWD) defined as >120 ms], which were measured from standard 12-lead ECGs. Brain MRI outcomes included cortical infarcts, cerebral microbleeds (CMB), and markers of small vessel disease [white matter hyperintensities (WMH) and lacunar infarcts]. We used weighted multivariable logistic and linear regression analyses. Results: Of the 1,850 participants, 464 had abnormal PTFV1 and 415 had prolonged PWD. After multivariable adjustment including AF, abnormal PTFV1 and PWD were significantly associated with 26-44% increased odds of cortical and lacunar infarcts (Table) . Although PWD was associated with CMB in Model 1, the association was no longer significant after multivariable adjustment. Finally, abnormal PWIs were not associated with WMH after adjusting for stroke and AF (P >0.5). Conclusions: Abnormal PWI are associated with higher prevalence of cortical infarcts, suggesting cardioembolism with silent ischemia as a possible mechanism underlying the association of AC with dementia. More research is needed to evaluate other mechanisms such as cerebral small vessel disease.

Clinically recognized atrial fibrillation (AF) is associated with higher risk of complications, including ischemic stroke, cognitive decline, heart failure, myocardial infarction, and death. It is increasingly recognized that AF frequently is undetected until complications such as stroke or heart failure occur. Hence, the public and clinicians have an intense interest in detecting AF earlier. However, the most appropriate strategies to detect undiagnosed AF (sometimes referred to as subclinical AF) and the prognostic and therapeutic implications of AF detected by screening are uncertain. Our report summarizes the National Heart, Lung, and Blood Institute’s virtual workshop focused on identifying key research priorities related to AF screening. Global experts reviewed major knowledge gaps and identified critical research priorities in the following areas: (1) role of opportunistic screening; (2) AF as a risk factor, risk marker, or both; (3) relationship between AF burden detected with long-term monitoring and outcomes/treatments; (4) designs of potential randomized trials of systematic AF screening with clinically relevant outcomes; and (5) role of AF screening after ischemic stroke. Our report aims to inform and catalyze AF screening research that will advance innovative, resource-efficient, and clinically relevant studies in diverse populations to improve the diagnosis, management, and prognosis of patients with undiagnosed AF.

The field of cardiac electrophysiology has been on the cutting edge of advanced digital technologies for many years. More recently, medical device development through traditional clinical trials has been supplemented by direct to consumer products with advancement of wearables and health care apps. The rapid growth of innovation along with the mega-data generated has created challenges and opportunities. This review summarizes the regulatory landscape, applications to clinical practice, opportunities for virtual clinical trials, the use of artificial intelligence to streamline and interpret data, and integration into the electronic medical records and medical practice. Preparation of the new generation of physicians, guidance and promotion by professional societies, and advancement of research in the interpretation and application of big data and the impact of digital technologies on health outcomes will help to advance the adoption and the future of digital health care.

Background Polypharmacy is highly prevalent in elderly people with chronic conditions, including atrial fibrillation ( AF ). The impact of polypharmacy on adverse outcomes and on treatment effectiveness in elderly patients with AF remains unaddressed. Methods and Results We studied 338 810 AF patients ≥75 years of age enrolled in the MarketScan Medicare Supplemental database in 2007–2015. Polypharmacy was defined as ≥5 active prescriptions at AF diagnosis (defined by the presence of International Classification of Diseases, Ninth Revision, Clinical Modification [ ICD‐9‐CM ] codes) based on outpatient pharmacy claims. AF treatments (oral anticoagulation, rhythm and rate control) and cardiovascular end points (ischemic stroke, bleeding, heart failure) were defined based on inpatient, outpatient, and pharmacy claims. Multivariable Cox models were used to estimate associations of polypharmacy with cardiovascular end points and the interaction between polypharmacy and AF treatments in relation to cardiovascular end points. Prevalence of polypharmacy was 52%. Patients with polypharmacy had increased risk of major bleeding (hazard ratio [ HR ], 1.16; 95% CI, 1.12–1.20) and heart failure ( HR , 1.33; 95% CI , 1.29–1.36) but not ischemic stroke ( HR , 0.96; 95% CI , 0.92–1.00), compared with those not receiving polypharmacy. Polypharmacy status did not consistently modify the effectiveness of oral anticoagulants. Rhythm control (versus rate control) was more effective in preventing heart failure hospitalization in patients not receiving polypharmacy ( HR , 0.87; 95% CI , 0.76–0.99) than among those with polypharmacy ( HR , 0.98; 95% CI , 0.91–1.07; P =0.02 for interaction). Conclusion Polypharmacy is common among patients ≥75 with AF , is associated with adverse outcomes, and may modify the effectiveness of AF treatments. Optimizing management of polypharmacy in AF patients ≥75 may lead to improved outcomes.

Background Social determinants of health are relevant to cardiovascular outcomes but have had limited examination in atrial fibrillation (AF). Objectives The purpose of this study was to examine the association of annual household income and cardiovascular outcomes in individuals with AF. Methods We analysed administrative claims for individuals with AF from 2009 to 2015 captured by a health claims database. We categorised estimates of annual household income as <$40 000; $40–$59 999; $60–$74 999; $75–$99 999; and ≥$100 000. Covariates included demographics, education, cardiovascular disease risk factors, comorbid conditions and anticoagulation. We examined event rates by income category and in multivariable-adjusted models in reference to the highest income category (≥$100 000). Results Our analysis included 336 736 individuals (age 72.7±11.9 years; 44.5% women; 82.6% white, 8.4% black, 7.0% Hispanic and 2.1% Asian) with AF followed for median (25th and 75th percentile) of 1.5 (95% CI 0.6 to 3.0) years. We observed an inverse association between income and heart failure and myocardial infarction (MI) with evidence of progressive risk across decreased income categories. Individuals with household income <$40 000 had the greatest risk for heart failure (HR 1.17; 95% CI 1.05 to 1.30) and MI (HR 1.18; 95% CI 0.98 to 1.41) compared with those with income ≥$100 000. Conclusions We identified an association between lower household income and adverse outcomes in a large cohort of individuals with AF. Our findings support consideration of income in the evaluation of cardiovascular risk in individuals with AF.