Alonso, Álvaro

Importance Only modest attention has been paid to the contributions of social determinants of health to atrial fibrillation (AF) risk factors, diagnosis, symptoms, management, and outcomes. The diagnosis of AF provides unique challenges exacerbated by the arrhythmia’s often paroxysmal nature and individuals’ disparate access to health care and technologies that facilitate detection. Social determinants of health affect access to care and management decisions for AF, increasing the likelihood of adverse outcomes among individuals who experience systemic disadvantages. Developing effective approaches to address modifiable social determinants of health requires research to eliminate the substantive inequities in health care delivery and outcomes in AF. Observations The National Heart, Lung, and Blood Institute convened an expert panel to identify major knowledge gaps and research opportunities in the field of social determinants of AF. The workshop addressed the following social determinants: (1) socioeconomic status and access to care; (2) health literacy; (3) race, ethnicity, and racism; (4) sex and gender; (5) shared decision-making in systemically disadvantaged populations; and (6) place, including rurality, neighborhood, and community. Many individuals with AF have multiple adverse social determinants, which may cluster in the individual and in systemically disadvantaged places (eg, rural locations, urban neighborhoods). Cumulative disadvantages may accumulate over the life course and contribute to inequities in the diagnosis, management, and outcomes in AF. Conclusions and Relevance Workshop participants identified multiple critical research questions and approaches to catalyze social determinants of health research that address the distinctive aspects of AF. The long-term aspiration of this work is to eradicate the substantive inequities in AF diagnosis, management, and outcomes across populations.

Background Electronic medical records are increasingly used to identify disease cohorts; however, computable phenotypes using electronic medical record data are often unable to distinguish between prevalent and incident cases. Methods and Results We identified all Olmsted County, Minnesota residents aged ≥18 with a first‐ever International Classification of Diseases, Ninth Revision (ICD‐9) diagnostic code for atrial fibrillation or atrial flutter from 2000 to 2014 (N=6177), and a random sample with an International Classification of Diseases, Tenth Revision (ICD‐10) code from 2016 to 2018 (N=200). Trained nurse abstractors reviewed all medical records to validate the events and ascertain the date of onset (incidence date). Various algorithms based on number and types of codes (inpatient/outpatient), medications, and procedures were evaluated. Positive predictive value (PPV) and sensitivity of the algorithms were calculated. The lowest PPV was observed for 1 code (64.4%), and the highest PPV was observed for 2 codes (any type) >7 days apart but within 1 year (71.6%). Requiring either 1 inpatient or 2 outpatient codes separated by >7 days but within 1 year had the best balance between PPV (69.9%) and sensitivity (95.5%). PPVs were slightly higher using ICD‐10 codes. Requiring an anticoagulant or antiarrhythmic prescription or electrical cardioversion in addition to diagnostic code(s) modestly improved the PPVs at the expense of large reductions in sensitivity. Conclusions We developed simple, exportable, computable phenotypes for atrial fibrillation using structured electronic medical record data. However, use of diagnostic codes to identify incident atrial fibrillation is prone to some misclassification. Further study is warranted to determine whether more complex phenotypes, including unstructured data sources or using machine learning techniques, may improve the accuracy of identifying incident atrial fibrillation.

Background: Women and African Americans with atrial fibrillation (AF) experience higher rates of stroke compared to men and white AF patients, respectively. However, sex and race differences for cardiovascular outcomes other than stroke have not been specifically evaluated in patients with AF. Methods: We studied patients with AF in the Optum Clinformatics database between 2009 and 2015 with at least 6 months of enrollment before AF diagnosis. The Optum Clinformatics database includes medical and pharmacy claims and sociodemographic information on privately insured and Medicare Advantage enrollees throughout the US. Endpoints (hospitalizations for ischemic stroke, heart failure (HF), myocardial infarction (MI)) and covariates were defined using validated algorithms. Multivariable Cox models were used to study the association of race and sex with endpoints of interest. Results: The analysis included 380,636 eligible participants (mean age 73, women 45%). Of them, 82% were white, 9% African American, 7% Hispanic and 2% Asian American. During a mean follow-up of 23 months, 7,235 suffered ischemic stroke, 17,258 HF, and 5,585 MI. Crude rates of ischemic stroke and HF were higher in women than men, while men had higher rates of MI than women (Table). African Americans and Hispanics had higher rates of all studied outcomes than whites and Asian Americans. In models including age, sex, race, education and CHA 2 DS 2 -VASc score, women had higher risk of ischemic stroke and lower risk of HF and MI compared to men. Compared to whites, African Americans had 1.4 times the rate of HF and stroke, and 1.1 times the rate of MI, while Asian Americans had 16% lower rates of HF. No major differences were observed between rates in whites and Hispanics (Table). Conclusion: In a large insured population of patients with AF, we observed differences in rates of selected cardiovascular outcomes by sex and race. Additional research should explore the mechanisms underlying these differences and develop strategies to eliminate them.

Abstract Background: Women with atrial fibrillation (AF) experience greater symptomatology, worse quality of life, and have a higher risk of stroke as compared to men, but are less likely to receive rhythm control treatment. Whether these differences exist in elderly patients with AF, and whether sex modifies the effectiveness of rhythm versus rate control therapy has not been assessed.Methods: We studied 135,850 men and 139,767 women aged ≥75 years diagnosed with AF in the MarketScan Medicare database between 2007-2015. Anticoagulant use was defined as use of warfarin or a direct oral anticoagulant. Rate control was defined as use of rate control medication or atrioventricular node ablation. Rhythm control was defined by use of anti-arrhythmic medication, catheter ablation or cardioversion. We used multivariable Poisson and Cox regression models to estimate the association of sex with treatment strategy and to determine whether the association of treatment strategy with adverse outcomes (bleeding, heart failure and stroke) differed by sex. Results: At the time of AF, women were on average (SD) 83.8 (5.6) years old and men 82.5 (5.2) years, respectively. Compared to men, women were less likely to receive an anticoagulant or rhythm control treatment. Rhythm control (vs. rate) was associated with a greater risk for heart failure with a significantly stronger association in women (HR women = 1.41, 95%CI 1.34-1.49; HR men= 1.21, 95%CI 1.15-1.28, p <0.0001 for interaction). No sex differences were observed for the association of treatment strategy with the risk of bleeding or stroke. Conclusion: Sex differences exist in the treatment of AF among patients aged 75 years and older. Women are less likely to receive an anticoagulant and rhythm control treatment. Women were also at a greater risk of experiencing heart failure as compared to men, when treated with rhythm control strategies for AF. Efforts are needed to enhance use AF therapies among women. Future studies will need to delve into the mechanisms underlying these differences.

There has been sustained focus on the secondary prevention of coronary heart disease and heart failure; yet, apart from stroke prevention, the evidence base for the secondary prevention of atrial fibrillation (AF) recurrence, AF progression, and AF‐related complications is modest. Although there are multiple observational studies, there are few large, robust, randomized trials providing definitive effective approaches for the secondary prevention of AF. Given the increasing incidence and prevalence of AF nationally and internationally, the AF field needs transformative research and a commitment to evidenced‐based secondary prevention strategies. We report on a National Heart, Lung, and Blood Institute virtual workshop directed at identifying knowledge gaps and research opportunities in the secondary prevention of AF. Once AF has been detected, lifestyle changes and novel models of care delivery may contribute to the prevention of AF recurrence, AF progression, and AF‐related complications. Although benefits seen in small subgroups, cohort studies, and selected randomized trials are impressive, the widespread effectiveness of AF secondary prevention strategies remains unknown, calling for development of scalable interventions suitable for diverse populations and for identification of subpopulations who may particularly benefit from intensive management. We identified critical research questions for 6 topics relevant to the secondary prevention of AF: (1) weight loss; (2) alcohol intake, smoking cessation, and diet; (3) cardiac rehabilitation; (4) approaches to sleep disorders; (5) integrated, team‐based care; and (6) nonanticoagulant pharmacotherapy. Our goal is to stimulate innovative research that will accelerate the generation of the evidence to effectively pursue the secondary prevention of AF.

Background: Midlife obesity is associated with dementia in later life, but how the metabolic syndrome (MetS) relates to cognitive change is less understood. We hypothesized that MetS would be more predictive of 6-year cognitive decline than its individual components in a large biethnic cohort (the ARIC study) and that combinations of risk factors would further increase likelihood of change. Methods: The MetS was defined in 1987-89 on 10,687 participants with two cognitive assessments at two time points. In subjects aged 44 to 66, obesity measures included body mass index (BMI) and waist-to-hip ratio (WTHR). The main outcome measure was change in 1990-92 to 96-99 of three cognitive tests: Delayed Word Recall (DWR), Digit Symbol Substitution Test (DSST), and Word Fluency Test (WFT). Linear and logistic regressions were all adjusted for age, combined race-center, sex, education, smoking, drinking, coronary artery disease and prior stroke. Change was measured as the difference divided by the number of years between visits. Results: At baseline, the prevalence of MetS was 22% (mean age 54 years, 27% black, 55% female, and 28% BMI>30 kg/m2). Subjects with MetS performed in the lowest test quintile (adjusted ORs: DWR 1.3 95% CI 1.1-1.4) in 1996-99, and much of this effect size was explained by an elevated WTHR (DWR OR 1.3 CI 1.1-1.5) and diabetes (DWR OR 1.4 CI 1.2-1.7). MetS was not associated with annual cognitive change, and diabetes was the only significant component associated with change (adjusted beta: DWR 0.03 p=.01, DSST 0.2 p<.001, WFT 0.09 p=.01). Conclusion: MetS at ages 44 to 66 was associated with worse cognitive function at follow-up, but not with annual cognitive decline over several years. Elevated WTHR and diabetes explained most of the association of MetS with cognitive function measures, and diabetes with cognitive decline. Until we have a definition of the MetS more based on pathophysiology, the components of the MetS should be the focus of analysis in future studies.

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia in current clinical practice. Yet, contemporary community data on adverse outcomes, such as ischemic stroke (IS) and heart failure (HF), are scarce. Methods: We assembled a community-based cohort of incident AF among Olmsted County, MN residents ≥18 years of age from 2000-2010. IS, transient ischemic attack (TIA), and incident HF occurring through 12/31/2012 were identified using diagnosis codes and were manually validated. Cox proportional hazards regression was used to determine age- and sex-adjusted predictors of IS/TIA and HF, as well as the association of year of AF diagnosis with these outcomes after adjustment for demographics and comorbidities. Results: Among 3315 incident AF (mean age 72.6 years, 52% male), 346 (10%) developed a subsequent IS (n=230) or TIA (n=116) over a mean follow-up of 4.2 years. In the 2807 AF patients without prior HF, 782 (28%) developed HF over a mean of 3.9 years. Differences in the predictors of subsequent IS/TIA and HF were observed (Figure). Increasing age, female sex, and prior IS/TIA were associated with an increased risk of IS/TIA, whereas increasing age, obesity, smoking, prior myocardial infarction, diabetes, chronic obstructive pulmonary disease, peripheral vascular disease, prior IS/TIA, and renal disease predicted the development of HF after AF. The risk of subsequent IS/TIA or HF did not differ by year of AF diagnosis. Compared to those diagnosed with AF in 2000-2003, the adjusted hazard ratios (HR) (95% CI) for ischemic IS/TIA were 0.84 (0.65-1.08) and 1.02 (0.76-1.36) for those diagnosed with AF in 2004-2007 and 2008-2010, respectively (P time trend =0.58); similar results were observed for IS alone. The corresponding HRs for HF were 0.99 (0.83-1.16) and 0.93 (0.76-1.13) for those diagnosed with AF in 2004-2007 and 2008-2010 compared to 2000-2003 (P time trend =0.43). Conclusions: In the community, adverse outcomes are frequent after AF, and HF occurs more frequently than IS/TIA. Risk factors differed for IS/TIA and HF, suggesting that pathways to the occurrence of these outcomes, as well as prevention strategies, may differ. Finally, the occurrence of these outcomes did not decline over the last decade, highlighting the importance of continued rigorous surveillance of adverse outcomes in AF.

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.

Introduction: Understanding the role of risk factors associated with accelerated cognitive decline has important public health relevance for the aging US population. To test hypotheses that mid-life cardiovascular (CV) risk factors increase risk of dementia in old age, the Atherosclerosis Risk in Communities (ARIC) cohort was evaluated for dementia in 2011-2013. Anticipating challenges of complete dementia ascertainment in an elderly population, supplementary data sources were collected to aid analysis accounting for potentially informative attrition. Methods: ARIC enrolled 15,792 participants 45-64 years old at baseline (1987-1989) from four US communities and collected baseline CV exposure data. A complete neurocognitive battery including informant interview was completed 2011-2013, yielding an algorithmic diagnosis of dementia, mild cognitive impairment (MCI) or normal cognition. Cognitively impaired and a random sample of cognitively normal were selected for further clinical evaluation. Syndromic diagnoses (dementia/MCI/normal) and etiologic diagnoses were made by a panel of experts using standardized criteria. Standardized protocols, timely reports of reviewer reliability, ongoing training of reviewers and a web-based data management system were developed to ensure reliability, consistency and efficiency of data collection and review. Living participants not attending the visit were asked to complete the Telephone Interview for Cognitive Status (TICS). Based on dementia discharge codes and death codes identified during cohort surveillance, interviewer impression of hearing loss or cognitive impairment or need for a proxy during semi-annual calls, or random sampling, participants refusing the TICS are eligible for proxy dementia interview. Medicare claims are being examined to identify missed dementia discharge codes. Results: Of 11,017 participants alive as of 2011, 6495 (59%) completed the neurocognitive battery; 2937 of these (45%) were selected for, and completed, additional clinical assessments and classification by committee (algorithmic or reviewer diagnosis: dementia 5%, MCI 21%). Of the 4522 participants who did not undergo the neurocognitive battery, 1463 (32%) completed the TICS (dementia 7%), while 1627 of the remaining participants were eligible for proxy calls (903 completed to date, dementia 58%). Conclusions: Participants who were not examined were more likely to be cognitively impaired, highlighting the importance of collecting supplementary data to support analyses of midlife CV risk factors accounting for informative attrition. Collection of exam data in an elderly cohort is difficult and requires a multi-pronged approach, especially for an outcome highly correlated with attrition. The strategy described here could be applied in other settings.