Abstract
Background
Undetected atrial fibrillation (AF) may be common in the heart failure with persevered ejection fraction (HFpEF) population, and failure to detect this may lead to missed opportunities to prevent associated subclinical cerebral infarcts (SCIs) and cognitive decline.
Objective
To determine whether subjects with HFpEF and no prior AF diagnosis have a similar number of SCIs as those with documented AF (whether with or without CHF).
Methods
We studied 1,527 participants in the Atherosclerosis Risk in Communities (ARIC) Study who underwent echocardiography, brain MRI and detailed cognitive assessment in 2011–2013. The prevalence of SCIs as detected by brain MRI was compared among the following groups: no congestive heart failure (CHF)/no prior AF, no CHF/AF, HFpEF/no AF, HFpEF/AF. Cognitive scores among these groups were also compared.
Results
Prevalence of HFpEF and AF in this sample were 13% and 5% respectively. Participants with HFpEF but no prior diagnosis of AF had a high prevalence of SCI by brain MRI (29.3 %), which was similar to the no CHF/AF (24.5%) and HFpEF/AF (23.5%) groups but higher than the no CHF/no AF subjects (17.3 %). The odds of having SCI in participants with HFpEF/no AF was higher than the no CHF/no AF group even after adjustment for potential confounders (OR 1.60, 95% CI 1.08–2.36). Individuals with HFpEF and SCI had lower cognitive scores than the reference (no CHF/no SCI) and HFpEF/no SCI groups.
Conclusions
SCIs are highly prevalent in the HFpEF population with no prior AF diagnosis and are associated with measurable cognitive deficits. As AF is mechanistically linked to SCI, these data suggest that paroxysmal AF may be underdiagnosed in this population. There may be a role for increased heart rhythm surveillance in patients with HFpEF to prevent this mechanism of cognitive decline.
Keywords: diastolic heart failure, cognitive decline, atrial fibrillation
Introduction
There are currently 6 million Americans with heart failure (HF), and this number is projected to increase to 8.5 million by 2030.(1) Over half of these patients have heart failure with preserved ejection fraction (HFpEF), and the incidence of this disease is increasing rapidly.(2,3) HFpEF has been associated with accelerated cognitive decline; however, the exact mechanism of this decline remains unclear.(4) While atrial fibrillation (AF) is a common co-morbidity in this patient group,(5,6) it is unknown how many patients with HFpEF have undiagnosed paroxysmal AF. Evidence is emerging that AF is associated with cognitive impairment or dementia even in individuals without a history of clinical stroke.(7) In addition, it has been recently demonstrated that by the time AF is diagnosed, subclinical brain infarctions can be detected by MRI along with measureable cognitive deficits.(8) Presence of these infarctions by brain MRI in patients with HFpEF and no prior diagnosis of AF would suggest that AF is being missed.
In this study, we analyzed whether a clinical diagnosis of HFpEF was associated with the presence of subclinical infarcts by brain MRI in individuals with no history of AF. We also assessed whether these subclinical infarcts were associated with cognitive impairment. Our overarching hypothesis is that undetected atrial fibrillation may be common in the HFpEF population, and failure to detect this may be leading to subclinical brain infarcts and cognitive decline.
Methods
Study Population
The Atherosclerosis Risk in Communities (ARIC) study is a predominantly biracial, population-based cohort drawn from four communities in North Carolina, Mississippi, Minnesota, and Maryland. The cohort enrolled 15,792 men and women between the ages of 45 and 64 years during the years of 1987–1989 (visit 1).(9) Four additional visits have subsequently taken place, the last of which was visit 5 (2011–2013). The ARIC study protocol was approved by the institutional review board of each participating center, and informed consent was obtained from each study participant.
Inclusion criteria
As part of visit 5, participants were invited to undergo a transthoracic echocardiogram and extensive cognitive assessment, as part of the ARIC Neurocognitive Study (ARIC-NCS). A subset of visit 5 participants was further invited to undergo a brain MRI. Participants with cognitive impairment and those with previous brain MRI were oversampled. For the present analysis, we included cohort participants with the following data obtained at visit 5: echocardiogram, brain MRI and cognitive testing. Individuals also had to have complete data regarding incident heart failure and previous or current atrial fibrillation up to and including visit 5.
Exclusion criteria
Exclusion criteria included the following: 1) a diagnosis of Alzheimer’s disease prior to visit 5 as these subjects have a different mechanism for cognitive deficit (n= 212); 2) prevalent stroke defined as any adjudicated stroke prior to visit 5 (n= 71)(10); 3) prior open heart surgery given a different mechanism for SCIs via cardiopulmonary bypass (n=22); 4) end-stage renal disease (defined as an estimated glomerular filtration rate of less than 15mL/min/m2 at visit 5) as HFpEF cannot be diagnosed in this setting (n=7); 5) history of a permanent pacemaker as these patients would not have undiagnosed atrial fibrillation (n=1); 6) individuals who were of a racial/ethnic group other than white or black and nonwhites in the Minneapolis and Washington County field centers (n=13); 7) missing covariate data (n= 3); or 8) heart failure with reduced ejection fraction (n=14).
Variable definitions
HFpEF
HFpEF was defined as a prior history of HF hospitalization or self-reported physician diagnosis of HF or HF medication use at visit 5 and a left ventricular ejection fraction ≥ 50% by visit 5 echocardiogram.(11,12)
Atrial fibrillation
Presence of AF at visit 5 was defined by either a hospital discharge record during follow-up showing an ICD–9-CM code for AF (427.31 or 427.32) or from AF as detected by an ECG performed during any ARIC study visit including visit 5.(13)
Subclinical infarcts
Brain MRIs were performed at each site on 3 Tesla Siemens (various models) scanners using a common set of sequences that included 3-dimensional volumetric magnetization prepared gradient echo and fluid-attenuated inversion recovery sequences. Brain infarcts were identified, counted, and measured by a trained imaging technician and confirmed by radiologists as previously described.(14) SCIs were defined as focal, non-mass lesions ≥ 3 mm that were bright on T2 and proton density and dark on T1 images.(15)
Neurocognitive function
All ARIC cognitive assessments were administered by trained examiners in a standard order. Detailed descriptions of each test have been described previously.(16) For each individual test, standardized z scores were calculated. A list of the cognitive tests used in this analysis is included in supplemental Table 1.
Table 1.
Participants’ characteristics according to heart failure and atrial fibrillation status, ARIC, 2011–2013
| No CHF, No AF | No CHF, AF | HFpEF, no AF | HFpEF, AF | |
|---|---|---|---|---|
| N | 1273 | 53 | 167 | 34 |
| Age, years | 76.0 (5.3) | 78.5 (5.3) | 76.6 (5.1) | 80.4 (4.5) |
| Male sex | 472 (37.1%) | 28 (52.8%) | 67 (40.1%) | 16 (47.1%) |
| Black race | 359 (28.2%) | 5 (9.4%) | 68 (40.7%) | 7 (20.6%) |
| High school graduate | 1120 (88.0%) | 47 (88.7%) | 126 (75.5%) | 29 (85.3%) |
| Current smoking | 69 (5.4%) | 1 (1.9%) | 7 (4.2%) | 3 (8.8%) |
| BMI, kg/m2 | 28.3 (5.5) | 28.3 (4.6) | 29.9 (7.3) | 27.8 (4.7) |
| Diabetes | 383 (30.1%) | 18 (34.0%) | 76 (45.5%) | 10 (29.4%) |
| Hypertension | 925 (72.7%) | 40 (75.5%) | 140 (83.8%) | 26 (76.5%) |
| Total cholesterol, mg/dL | 186.8 (41.0) | 179.5 (42.4) | 168.4 (43.3) | 170.3 (40.3) |
| Prevalent CHD | 28 (2.2%) | 5 (9.4%) | 27 (16.2%) | 9 (26.5%) |
| Warfarin | 19 (1.5%) | 15 (28.3%) | 8 (4.8%) | 22 (64.7%) |
| Statin | 611 (48.0%) | 32 (60.4%) | 97 (58.1%) | 17 (50.0%) |
| Aspirin | 843 (66.2%) | 38 (71.7%) | 118 (70.7%) | 18 (52.9%) |
Values are n(%) or mean (SD)
AF: atrial fibrillation; BMI: body mass index; CHD: coronary heart disease; HFpEF: heart failure with preserved ejection fraction
Covariates
Pre-specified potential confounders of the relationship between HFpEF and SCI were measured at visit 5 and were included in the models. These ARIC variables have established definitions which were also used for this analysis.(17) Briefly, we included the following: age, sex, race, education, and smoking status. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or use of blood pressure lowering medications. Diabetes was defined as a fasting glucose level ≥126 mg/dL or a non-fasting glucose ≥ 200 mg/dL, a self-reported physician diagnosis of diabetes, or use of diabetes medications. Blood samples were collected following a fast of at least eight hours, and total cholesterol was determined by enzymatic methods. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Coronary heart disease (CHD) prior to visit 1 was defined as physician-diagnosed CHD or the presence of a previous myocardial infarction by ECG. Patients were also classified as having CHD if an adjudicated coronary event occurred after visit 1. Anticoagulant use, as defined as warfarin, direct thrombin inhibitor use or factor Xa inhibitor use, was obtained by self-report of medication intake during last two weeks and by reviewing medications brought by the participants to their visit.
Statistical analysis
All analyses were performed with SAS version 9.3 (SAS Inc, Cary, NC).
To determine the association between HFpEF and SCI prevalence independently of AF diagnosis, we divided the sample in four groups: no CHF/no AF, no CHF/AF, HFpEF/no AF, and HFpEF/AF. The number of SCI by brain MRI was compared among these four groups as were baseline characteristics.
Logistic regression was used to assess the odds ratios of SCIs in each participant group against the reference group (no CHF/no AF), and also to assess the association of SCIs with HFpEF. A series of nested models were fit. Model 1 was adjusted for age, sex and race. Model 2 included model 1 covariates plus enrolling center, education (did not complete high school vs. completed high school), hypertension, diabetes, smoking status (current smoker vs. not a current smoker), BMI, and total cholesterol. Model 3 included model 2 covariates plus prevalent coronary heart disease. Anticoagulant use was then incorporated into the final model and was also tested for interaction with HFpEF on the odds of having SCI.
Among the HFpEF/no AF group, logistic regression was used to identify clinical variables that conferred increased odds of SCI. We looked at the univariate associations, and then used a multivariable model adjusting for variables with a p value for the association < 0.10 after applying a backwards stepwise covariate selection approach.
Next, linear regression was used to compare cognitive z-scores from each test among the four participant groups, using no HF/no AF again as the reference group. In this analysis, model 1 adjusted for age, sex and race. Model 2 included model 1 plus center, education, hypertension, diabetes, smoking, BMI, total cholesterol, prevalent CHD, anticoagulant use, and prevalent AF. All models comparing cognitive scores were weighted to account for the sampling approach used to select subjects for brain MRI.
For all measures of association, a p value of less than 0.05 was considered statistically significant.
Results
Of the initial ARIC cohort, 6,538 participants completed visit 5. Of these, 1,870 had complete cognitive scores as well as brain MRI and echocardiogram data, and the final cohort based on all inclusion and exclusion criteria was 1,527 subjects.
Among the 1,527 cohort participants, 201 (13.2%) had HFpEF. Eighty one subjects (5.3 %) had prior or current diagnosis of AF and 290 subjects (19.0 %) had SCI present. The mean (standard deviation) age of the study cohort at visit 5 was 76 (5.3) years. Descriptive statistics according to HF and AF status are presented in Table 1. Individuals in the HFpEF/no AF group were less likely to be on warfarin than those with a diagnosis of AF (4.8 % vs. 32 % for the no CHF/AF group and 67.8 % for the HFpEF/AF group) and were also more likely to be diabetic and African American.
High Prevalence of SCI in the HFpEF/no AF population
Cohort participants with HFpEF but no prior diagnosis of AF had a high prevalence of SCI by brain MRI (29.3 %), which was similar to no CHF/AF (24.5%) and HFpEF/AF (23.5%) but higher than the no CHF/no AF reference population (17.3%). The odds of having SCI in subjects with HFpEF/no AF was higher than the non-heart failure cohort even after adjustment for other potential confounders (minimally adjusted OR 1.92 95% CI 1.33–2.77, fully-adjusted OR 1.60, 95% CI 1.08 - 2.36, Table 2).
Table 2.
Odds ratios and 95% confidence intervals of subclinical cerebral infarcts according to heart failure and atrial fibrillation status, ARIC, 2011–2013
| No CHF, No AF | No CHF, AF | HFpEF, no AF | HFpEF, AF | |
|---|---|---|---|---|
| N | 1273 | 53 | 167 | 34 |
| Subclinical infarct present (n=290) | 220 (17.3%) | 13 (24.5%) | 49 (29.3%) | 9 (23.5%) |
| OR (95% CI),Subclinical infarct present | ||||
| Model 1 | Ref | 1.36 (0.71–2.62) | 1.92 (1.33–2.77) | 1.24 (0.55–2.81) |
| Model 2 | Ref | 1.30 (0.67–2.50) | 1.76 (1.20–2.56) | 1.26 (0.55–2.86) |
| Model 3 | Ref | 1.24 (0.64–2.40) | 1.60 (1.08–2.36) | 1.06 (0.46–2.46) |
AF: atrial fibrillation; CI: confidence interval; HFpEF: heart failure with preserved ejection fraction; OR: odds ratio
Model 1 was adjusted for age, sex and race.
Model 2 included model 1 plus enrolling center, education, hypertension, diabetes, smoking status, body mass index, and total cholesterol.
Model 3 included model 2 plus prevalent coronary heart disease.
The odds of having SCI were higher in the HFpEF population vs. the non HFpEF population (adjusted model OR 1.49, 95% CI 1.03 – 2.17), even after adjustment for potential confounders (model 3, plus adjustment for anticoagulant use and AF). The presence of AF did not modify the relationship between HFpEF and SCI (p-interaction = 0.28).
Left atrial enlargement is a risk factor for SCI in the HFpEF/no AF population
Among the HFpEF population without an AF diagnosis, only male sex and a larger left atrium (LA) were associated with increased odds of having SCI after using backwards selection of variables (Table 3). In the adjusted model, for each standard deviation increase in the LA volume index, the odds of SCI were increased by 41 % (OR 1.41, 95 % CI 1.00–2.00). Male sex was also associated with increased odds of SCI (OR 2.26, 95 % CI 1.12 - 4.58, Table 3). Increased left ventricular mass index was associated with increased odds of SCI in the univariate model but did not remain significant after adjustment in this small HFpEF/no AF population.
Table 3.
Association of predictors of subclinical infarcts in those with HFpEF and no atrial fibrillation, ARIC, 2011–2013
| Odds ratios (95% confidence interval) | ||
|---|---|---|
| N with HFpEF=167 N with subclinical infarcts=49 |
Univariate association with SCIs | Significant variables in the multivariate model* |
| Age (per year) | 1.05 (0.98–1.12) | |
| Male | 2.39 (1.21–4.72) | 2.26 (1.12–4.58) |
| Black race | 1.01 (0.51–1.98) | |
| SBP (per 1 SD) | 0.98 (0.70–1.37) | |
| DBP (per 1 SD) | 1.04 (0.74–1.45) | |
| Hypertension meds | 0.66 (0.28–1.56) | |
| Anticoagulant use | 1.47 (0.34–6.42) | |
| LA volume index (per 1 SD) | 1.46 (1.04–2.04) | 1.41 (1.00–2.00) |
| BNP (per 1 SD) | 1.18 (0.86–1.63) | |
| LV mass index (per 1 SD) | 1.52 (1.08–2.14) | |
after backwards stepwise regression, leaving in variables with p < 0.10
SBP = systolic blood pressure; DBP = diastolic blood pressure; HFpEF: heart failure with preserved ejection fraction; LA = left atrium; BNP = brain natriuretic peptide; LV = left ventricle
SCI in the HFpEF population is associated with lower cognitive performance
Presence of SCI in the HFpEF population was associated with lower cognitive scores in several tests compared to the reference (no CHF/no SCI) (Table 4). In the final multivariable model, subjects with HFpEF but no SCI had cognitive scores that were similar to the no HFpEF/no AF group, suggesting that the SCI, and not HFpEF alone, may have been the mechanism of the cognitive impairment.
Table 4.
Weighted association of cognitive test scores according to presence of HFpEF and sub-clinical infarcts, ARIC, 2011–2013.
| No CHF | HFpEF | ||||
|---|---|---|---|---|---|
| No SCI | SCI | No SCI | SCI | ||
| N | 1093 | 233 | 144 | 57 | |
| DWR | Model 1 | REF | −0.23 (−0.48 to −0.08) | −0.13 (−0.31 to 0.05) | −0.23 (−0.48 to 0.03) |
| Model 2 | REF | −0.20 (−0.34 to −0.06) | −0.04 (−0.22 to 0.14) | −0.10 (−0.35 to 0.14) | |
| DSS | Model 1 | REF | −0.26 (−0.39 to −0.12) | −0.22 (−0.39 to −0.04) | −0.49 (−0.79 to −0.20) |
| Model 2 | REF | −0.17 (−0.29 to −0.05) | −0.08 (−0.25 to 0.09) | −0.31 (−0.60 to −0.02) | |
| WF | Model 1 | REF | −0.12 (−0.29 to 0.05) | −0.13 (−0.31 to 0.05) | −0.49 (−0.76 to −0.23) |
| Model 2 | REF | −0.08 (−0.23 to 0.08) | −0.04 (−0.21 to 0.15) | −0.35 (−0.59 to −0.11) | |
| MME | Model 1 | REF | −0.19 (−0.32 to −0.05) | −0.09 (−0.25 to 0.06) | −0.35 (−0.60 to −0.10) |
| Model 2 | REF | −0.12 (−0.25 to 0.004) | 0.03 (−0.11 to 0.18) | −0.23 (−0.46 to 0.01) | |
| TMTa | Model 1 | REF | −0.23 (−0.37 to −0.09) | −0.11 (−0.29 to 0.08) | −0.36 (−0.64 to −0.07) |
| Model 2 | REF | −0.17 (−0.31 to −0.03) | −0.02 (−0.21 to 0.17) | −0.26 (−0.57 to 0.06) | |
| TMTb | Model 1 | REF | −0.24 (−0.38 to −0.11) | −0.13 (−0.35 to 0.09) | −0.53 (−0.78 to −0.28) |
| Model 2 | REF | −0.17 (−0.30 to −0.05) | −0.02 (−0.23 to 0.19) | −0.36 (−0.68 to −0.04) | |
| DSB | Model 1 | REF | −0.14 (−0.29 to 0.02) | −0.03 (−0.24 to 0.18) | −0.32 (−0.58 to −0.06) |
| Model 2 | REF | −0.10 (−0.25 to 0.04) | 0.02 (−0.19 to 0.22) | −0.26 (−0.54 to 0.02) | |
| LMTa | Model 1 | REF | −0.08 (−0.24 to 0.09) | −0.05 (−0.23 to 0.14) | −0.38 (−0.65 to −0.10) |
| Model 2 | REF | −0.06 (−0.22 to 0.09) | −0.02 (−0.21 to 0.18) | −0.32 (−0.62 to −0.02) | |
| LMTb | Model 1 | REF | −0.08 (−0.24 to 0.09) | −0.07 (−0.24 to 0.11) | −0.28 (−0.55 to −0.01) |
| Model 2 | REF | −0.07 (−0.23 to 0.09) | −0.04 (−0.22 to 0.14) | −0.22 (−0.51 to 0.06) | |
| IL | Model 1 | REF | −0.09 (−0.25 to 0.07) | −0.12 (−0.33 to 0.09) | −0.24 (−0.52 to 0.04) |
| Model 2 | REF | −0.06 (−0.22 to 0.10) | −0.06 (−0.28 to 0.17) | −0.18 (−0.48 to 0.12) | |
| CTP | Model 1 | REF | −0.13 (−0.26 to 0.002) | −0.06 (−0.21 to 0.09) | −0.14 (−0.41 to 0.12) |
| Model 2 | REF | −0.11 (−0.24 to 0.02) | −0.02 (−0.24 to 0.13) | −0.07 (−0.35 to 0.22) | |
| AN | Model 1 | REF | −0.08 (−0.25 to 0.08) | −0.14 (−0.31 to 0.03) | −0.34 (−0.65 to −0.02) |
| Model 2 | REF | −0.05 (−0.21 to 0.12) | −0.10 (−0.27 to 0.08) | −0.27 (−0.56 to 0.02) | |
| BNT | Model 1 | REF | −0.06 (−0.17 to 0.04) | 0.03 (−0.11 to 0.16) | −0.07 (−0.30 to 0.15) |
| Model 2 | REF | −0.02 (−0.12 to 0.07) | 0.11 (−0.03 to 0.24) | 0.01 (−0.19 to 0.20) | |
Model 1: General linear model adjusted for age, sex and race, and weighted for the sampling mechanism used to select subjects for brain MRI and cognitive testing.
Model 2: General linear model adjusted for age, sex, race, center, education, hypertension, diabetes, smoking, BMI, total cholesterol, prevalent coronary heart disease, anticoagulant use, prevalent AF and weighted for selection bias to brain MRI.
DWR: Delayed Word Recall; DSS: Digit Symbol Substitution; WF: Word Fluency; MME: Mini-Mental State Exam; TMTa: Trail Making Tet, part A; TMTb: Trail Making Test, part B; DSB: Digit Span Backward; LMTa: Logical Memory Test, part A; LMTb: Logical Memory Test, part B; IL: Incidental Learning, digit-symbol pairs; CTP: Clock Time Perception; AN: Animal Naming; BNT: Boston Naming Test.
Discussion
This analysis of the ARIC cohort demonstrates that individuals with HFpEF but no prior AF diagnosis had a high prevalence of SCI as detected by brain MRI. The odds of having SCI in this group were higher than the no CHF/no AF population even after multivariable adjustment, and was similar to groups with a known history of AF. Risk factors for having SCI in the HFpEF/no AF group included left atrial enlargement, which is highly associated with AF and(18,19) AF is a known to be a risk factor for SCI.(20–22) Lower cognitive scores were observed in the HFpEF population and these appear to have been mediated through the SCI rather than the HFpEF alone. Collectively these data suggest that AF may be underdiagnosed in this high risk population. The presence of cognitive deficits which may be attributable to these small infarcts also underscores their clinical importance.
While subclinical infarcts have been mechanistically linked to AF, other sources of emboli are also possible. Patients with HFpEF have a high burden of atherosclerosis which may explain some of these small ischemic events.(23) While with this study design we cannot prove that undiagnosed AF was the cause of all of brain MRI findings, these data are suggestive and fit into what is known both regarding mechanism of SCI and also with what is known about the burden of AF in high risk populations when surveillance increases.(24,25)
Despite the prevalence of AF among those with HFpEF being similar to previously published studies(23,26) we did not find a statistical increase in the odds of SCI in those with AF after multivariable adjustment. This may be due to the low number of participants in these subgroups and potentially due to the higher anticoagulant use in these groups.
Evidence is emerging that AF is associated with cognitive impairment or dementia even in individuals without a history of clinical stroke.(7) In addition, it has been recently demonstrated that by the time AF is diagnosed, subclinical brain infarctions can be detected by MRI along with measureable cognitive deficits.(8) This work builds on these previously published studies and suggests that SCI may be occurring prior to an AF diagnosis.
Cognitive impairment negatively impacts quality of life and can lead to a loss of independence, both of which are of extreme importance to the aging population.(27) As the epidemic of HFpEF continues to develop, it will be increasingly important to prevent any loss of cognitive function from occurring. Our results suggest that increased cardiac rhythm monitoring in this population might have a role in the prevention of stroke and cognitive impairment.
Limitations
Given the relatively healthy population that participated in the ARIC visit 5, the number of patients with a diagnosis of HFpEF or AF was relatively small. Despite this we found a statistically significant association with SCI even after adjustment, and the prevalence rates of HFpEF in this study were similar to rates in the United States.(28,29) Sub-clinical infarcts were defined as focal, non-mass lesions ≥ 3 mm that were bright on T2 and proton density and dark on T1 images. Therefore, participants with SCIs < 3 mm might have been misclassified, although lesions of this size are usually considered to be enlarged perivascular spaces. This was a cross-sectional analysis which limits our ability to interpret causality and we do not know definitively that AF was the direct mechanism of SCI.
Conclusions
Subclinical brain infarcts are highly prevalent in the HFpEF population with no prior AF diagnosis and are associated with measurable cognitive deficits. As AF is mechanistically linked to SCI, these data suggest that paroxysmal AF may be underdiagnosed in this population. There may be a role for increased heart rhythm surveillance in patients with HFpEF to identify patients at high risk for SCI and for potential anticoagulation therapy to prevent this mechanism of cognitive decline.
Perspective.
Competency in Medical Knowledge
Subclinical cerebral infarcts (SCI) are present by brain MRI by the time atrial fibrillation is diagnosed and are associated with measurable cognitive decline. Patients with HFpEF are known to be at high risk for the development of atrial fibrillation.
Translational outlook
While we demonstrate in this study that subclinical cerebral infarcts are prevalent in the HFpEF population without a previous diagnosis of atrial fibrillation, additional studies will be need to confirm that that asymptomatic atrial fibrillation is linked to the development of SCI in HFpEF.
Translational outlook
If SCIs are occurring in HFpEF due to atrial fibrillation then there may be a case in the future towards increase cardiac monitoring in this high risk group with the goal of an earlier anticoagulation strategy.
Acknowledgments
The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C). Neurocognitive data is collected by U01 HL096812, HL096814, HL096899, HL096902, HL096917 from the NHLBI and the National Institute of Neurological Disorders and Stroke, and with previous brain MRI examinations funded by R01-HL70825 from the NHLBI. The authors thank the staff and participants of the ARIC study for their important contributions.
Funding sources: ARIC-NCS funding (U01 HL096902)
List of abbreviations
- AF
atrial fibrillation
- HF
heart failure
- HFpEF
heart failure with preserved ejection fraction
- LA
left atrium
- SCI
subclinical cerebral infarcts
Footnotes
Financial relationships:
The authors have no financial relationships with industry related to this work. Among the authors, Amil Shah does receive research support from Novartis, Gilead, and Actelion.
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