Electrocardiographic markers of atrial cardiomyopathy and risk of heart failure in the multi-ethnic study of atherosclerosis (MESA) cohort.

BackgroundHeart failure with preserved ejection fraction (HFpEF) accounts for about 50% of heart failure patients (pts) and atrial cardiomyopathy is common in those pts. The latter is associated with more severe pulmonary vascular disease, right ventricular dysfunction, stroke and an increased risk of incident atrial fibrillation (AF). There is a lack of data concerning the extent of electrical remodeling in HFpEF and ACM pts seen in 12-lead-electrocardiograms (ECG).PurposeThis study aims to elucidate the prevalence of atrial cardiomyopathy based on p-wave morphology parameters in pts with HFpEF with known and without previously known AF.MethodsWe analyzed 152 pts from the German HFpEF registry. Clinical, functional, ECG, and echocardiographic data were collected. To define atrial cardiomyopathy based on ECG parameters (eACM) we used 4 ECG parameters in sinus rhythm (SR) ECGs (n=99): p-wave terminal force in V1 (PTFV1) > (-) 4 ms*mV, p-wave duration (PWD) >120ms, pathological p-vector (P-Vec), and biphasic p-waves in lead II,III+aVF. To confirm eACM diagnosis ≥2 criteria had to be met. We compared ECG parameters in pts with a diagnosis of clinical AF and without previously known AF. Furthermore, it was hypothesized that clinical parameters do not predict the prevalence of eACM.ResultsOf the 152 HFpEF 91 (60%) had clinical AF (37 pts with paroxysmal AF (41%), 45 pts with persistent (pers) or permanent AF (49%), while 61 pts (40.1%) did not have AF diagnosis. Clinical parameters are depicted in table 1. 30 pts (20%) were in pers AF and 9 (6%) in atrial tachycardias at the time of enrollment in the registry, 14 (9%) showed atrial pacing while in N=99 pts (65%) with SR ECGs p wave morphologies were analyzed (table 2). 40 (40.4%) of these met our diagnostic criterium for eACM (figure 1A). ECG parameters for all HFpEF pts and the subgroups AF/no AF are shown in table 2. Nineteen of the eACM pts (47.5%) had a clinical AF diagnosis while 21 patients (52.5%) did not. The presence of AF did not correlate with the diagnosis of eACM in pts with HFpEF (p=0.738). Except for the CHA2DSV2A score (p=0.020), all clinical parameters were comparable between patients with eACM and those without eACM. The same applies to the left atrial size (p=0.5), 6-min walking test (p=0.6) and NT-ProBNP (p=0.5). CHA2DS2VA score correlated with eACM diagnosis, even though 22.6% (N=7 of 31) of pts with CHA2DSV2A score ≤3 showed eACM (figure 1B). There was no significant difference regarding clinical parameters such as type 2 diabetes (p>0.9), arterial hypertension (p=0.2) and cerebral vascular disease (p=0.2). In addition, there was no significant difference in an anticoagulation requiring (p=0.226).ConclusioneACM is prevalent in patients with HFpEF, regardless of whether they have a prior diagnosis of AF. This finding may influence recommendations for systematic atrial fibrillation screening in HFpEF pts with eACM and could contribute to a reduction in stroke risk.Tabels Figures

Early Identification of Asymptomatic Subjects at Increased Risk of Heart Failure and Cardiovascular Events: Progress and Future Directions

Relationship Between Physical Activity, Body Mass Index, and Risk of Heart Failure

Introduction: Breast cancer (BC) survivors (BCS) are at increased risk for incident heart failure (HF). In this population, the risk for HF with preserved ejection fraction (HFpEF) has been understudied compared to HF with reduced EF (HFrEF). The purpose of this study was to estimate 1) the incidence of HFpEF and HFrEF, and 2) the phenotypic profiles conferring risk for incident HFpEF and HFrEF in BCS. Methods: This Women’s Health Initiative analysis was conducted in women with invasive BC stages I-IV in the Medical Records Cohort (MRC). Those with pre-existing HF were excluded. Exposures of interest were lifestyle factors [e.g. body mass index (BMI)], comorbidities [e.g. hypertension, diabetes, and myocardial infarction (MI)], and BC treatment. Lifestyle factors and comorbidities most proximal and prior to BC diagnosis were assessed. In the MRC, BC and HF as well as left ventricular EF (LVEF) were ascertained through chart review and physician-adjudication. LVEF ≥50% was classified as HFpEF; and <50% for HFrEF per AHA/ACC guidelines. Cox proportional hazards models estimated risks of HFpEF and HFrEF. Follow up time began at BC diagnosis and HF events were recorded through March 1, 2019. All models adjusted for age at BC diagnosis. Results: In 2,250 BCS, 153 developed HF after BC during a median follow-up of 7.3 years. Of those, 49 had HFrEF and 75 had HFpEF. The cumulative incidences of HFrEF and HFpEF over follow-up were 7.3% and 4.6%, respectively. Diabetes and MI were associated with both HFpEF and HFrEF (Table). Smoking, BMI ≥30, and hypertension were associated with HFpEF. Anthracycline use was associated with HFrEF but not HFpEF (p=0.03). Conclusions: In BCS, lifestyle factors were associated with incident HFpEF, whereas anthracycline use was associated with a higher risk for HFrEF. Understanding risk factors associated with incident HFpEF and HFrEF in BCS is important to guide the implementation of risk profile-specific preventative measures and interventions.

BackgroundHigher fibroblast growth factor‐23 (FGF‐23) levels are associated with incident heart failure (HF) in MESA (the Multiethnic Study of Atherosclerosis). FGF‐23 is also associated with left ventricular hypertrophy. Whether the FGF‐23 association with HF is similar for heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF) is not well established.Methods and ResultsWe studied 6542 participants (mean age 62±10 years, 53% women, mean estimated glomerular filtration rate of 81±18 mL/min per 73 m2) from MESA who were free of cardiovascular disease at baseline (2000–2002). HF events were ascertained by an adjudication committee for a median follow‐up of 12.1 years. We classified HF events as HFrEF (ejection fraction [EF] <50%) or HFpEF [EF] ≥50%) at the time of diagnosis. Cox proportional hazard regression was used to compute hazard ratios and 95% confidence intervals for the association between baseline serum FGF‐23 and incident HFrEF and HFpEF. A total of 134 events were classified as HFpEF, 151 HFrEF, and 49 unknown EF. Following imputation, 149 were classified as HFpEF, 176 HFrEF, and 291 participants had HF (34 participants had HFpEF then HFrEF). In the fully adjusted model, higher FGF‐23 levels were associated with incident HFpEF but not with HFrEF (hazard ratio 1.29, 95% confidence interval, 1.08–1.54) versus (hazard ratio 1.04, 95% confidence interval, 0.84–1.29) for each 20 pg/mL higher serum FGF‐23 concentration.ConclusionsFGF‐23 association with HF is driven by the association with HFpEF but not with HFrEF in a population‐based cohort. Further studies are needed to determine the pathological mechanisms mediating this association.

Background Atrial structural abnormalities linked to the risk of atrial fibrillation (AF), as indicated by P-wave indices on surface ECG, are associated with the fibrotic transformation of the atrial myocardium. To what extent incident AF can be predicted by ECG characteristics in patients with advanced atrial structural remodeling, such as patients with heart failure (HF), is less well studied. Purpose To evaluate the association between P-wave indices and biomarkers implicated in cardiac fibrosis, and incident AF in patients with HF. Methods Patients with new-onset or worsening of HF were prospectively recruited in a observational study (n=501) and followed-up for 5 years. Blood samples were collected for analysis using proximity extension assay that included a subset of biomarkers that were associated with fibrosis development (TIMP-2, MMP-2, MMP-3, MMP-9, ST-2, GDF-15, Gal-3). All ECGs ever recorded in the hospital catchment area were exported in digital format and processed using Glasgow algorithm for calculation of the P-wave indices (P-wave duration [PWD], P-wave terminal force in V1 [PTFV1] and P-wave axis [Paxis]) and rhythm identification. AF diagnosis was ascertained by manual ECG review. Only patients who did not have AF reported or ECG documented at enrolment were included in the analysis. Of those subjects, 121 patients also had biomarkers of fibrosis analyzed. Cox-regression analyses were used to assess biomarkers’ and p-wave indices’ associations with incident AF. Results After exclusion of patients with prevalent AF (n=317), 184 patients comprised the study group (mean age of 71 years, 33.2% women, 121 patients with biomarker data available). During follow-up, incident AF was observed in 39 patients. At enrolment, PWD&amp;gt;120 ms was observed in 38.7%, abnormal PTFV1&amp;gt;40 mm*ms in 24.5% and Paxis&amp;lt;0° in 5.4%. Among the seven biomarkers assessed, five demonstrated significant associations with incident AF in adjusted analyses: TIMP4 (HR 1.78; 95%CI 1.03-3.05; p=0.037); MMP2 (HR 1.97; 95%CI 1.03-3.80; p=0.042), MMP3 (HR 1.39; 95%CI 1.03-1.88; p=0.031); ST2 (HR 1.91; 95%CI 1.29-2.83; p=0.001) and GDF-15 (HR 2.56; 95%CI 1.50-4.35; p=0.001) (Figure 1). However, none of the tested P-wave variables (P-wave duration, P-wave terminal force, and P-wave axis) were associated to incident AF. Conclusions In this prospective long-term follow-up study of patients admitted for acute HF, biomarkers with proven associations to fibrosis were strongly associated with incident AF. P-wave indices used for prediction of AF in epidemiological cohorts appear to have limited value in patients with HF who have high prevalence of ECG atrial abnormalities at baseline.

As described in Part I of this 2-part article,1 diastolic heart failure is common and causes significant alterations in prognosis. In Part II, experimental studies that have provided insight into the mechanisms that cause diastolic heart failure will be described.2–19⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓ In addition, current treatment strategies and the design of future clinical trials of diastolic heart failure will be discussed. The development of truly effective therapy for diastolic heart failure depends on gaining a clear understanding of the basic mechanisms that alter diastolic function and the ability to efficiently target these mechanisms to correct these abnormalities in diastolic function. Conceptually, the mechanisms that cause abnormalities in diastolic function that lead to the development of diastolic heart failure can be divided into factors intrinsic to the myocardium itself (myocardial) and factors that are extrinsic to the myocardium (extramyocardial; Table 1). Myocardial factors can be divided into structures and processes within the cardiac muscle cell (cardiomyocyte), within the extracellular matrix (ECM) that surrounds the cardiac muscle cell, and that activate the autocrine or paracrine production of neurohormones. Each of these mechanisms are active in the major pathological processes that result in diastolic dysfunction and heart failure. Myocardial and extramyocardial mechanisms, cellular and extracellular mechanisms, and neurohumoral activation each play a role in the development of diastolic heart failure caused by ischemia, pressure-overload hypertrophy, and restrictive and hypertrophic cardiomyopathy. View this table: Table 1105290. Diastolic Heart Failure: Mechanisms ### Cardiomyocyte Diastolic dysfunction can be caused by mechanisms that are intrinsic to the cardiac muscle cells themselves. These include changes in calcium homeostasis caused by (1) abnormalities in the sarcolemmal channels responsible for short- and long-term extrusion of calcium from the cytosol, such as the sodium calcium exchanger and the calcium pump; (2) …

Endothelial dysfunction may be a phenotypic expression of heart failure (HF). Total brachial artery reactivity (TBAR) is a non-invasive measurement of endothelial function that has been associated with increased risk of cardiovascular outcomes. Limited information is currently available on the impact of TBAR on incident HF and its subtypes. The aim of this study was to investigate whether TBAR is associated with overall incident HF, and the two HF subtypes, HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF) in a community-based study. The sample included 5499 participants (45-84years of age) from the Multi-Ethnic Study of Atherosclerosis who were free of cardiovascular disease at baseline. Brachial artery was imaged via ultrasound after five minutes of cuff occlusion at the right forearm. TBAR was calculated as the difference between maximum and minimum brachial artery diameters following cuff release, divided by the minimum diameter multiplied by 100%. A dichotomous TBAR variable was created based on the median value (below or above 7.9%). Participants with EF ≤ 40% were considered HFrEF and those with EF ≥ 50% were considered HFpEF. Cox proportional hazards regression models were used to calculate hazard ratios (HR) and 95% confidence intervals (CI). Over a mean follow-up period of 12.5years, incident HF was diagnosed in 250 participants: 98 classified as HFrEF, 106 as HFpEF, and 46 with unknown or borderline EF (41-49%). Crude analysis revealed that those with TBAR below the median had a significantly greater risk of HF (HR 1.46; 95% CI 1.13-1.88, p < 0.01) and HFrEF (HR 1.61; 95% CI 1.07-2.43, p < 0.05). Following adjustment for known HF risk factors (e.g., age, sex, race, blood pressure), the strength of these relationships was attenuated. Borderline significant results were revealed in those with HFpEF (HR 1.43; 95% CI 0.97-2.12, p = 0.06). Kaplan-Meier curves suggest significantly lower risks of developing HF and HFrEF in those with TBAR above the median (log-rank p ≤ 0.05 for both). When examined as a continuous variable, with a cut point of 50% for EF, every 1-standard deviation (9.7%) increase in TBAR resulted in a 19 and 29% decrease in risk of HF (p < 0.05) and HFrEF (p = 0.05), respectively. Lower TBAR values were associated with higher rates of incident HF and HFrEF, suggesting a possible role of endothelial dysfunction in HF pathogenesis. The impact of other known HF risk factors may mediate this relationship, thus further research is warranted.

Relation of Baseline Systolic Blood Pressure and Long-Term Outcomes in Ambulatory Patients With Chronic Mild to Moderate Heart Failure

Vascular Dysfunction in Heart Failure with Preserved Ejection Fraction

BackgroundThe predictive value of atrial conduction abnormalities, reflected by P-wave indices (PWI), and their association with biomarkers signaling fibrosis for the development of atrial fibrillation (AF) in patients with heart failure (HF) remains underexplored. To address this gap, we investigated the associations between PWI, fibrotic biomarkers, and the risk of incident AF in a cohort of HF patients.MethodsA total of 475 patients with new-onset or worsening HF, were followed for 5 years. Fibrosis-associated biomarkers (TIMP-2, MMP-2, MMP-3, MMP-9, ST-2, GDF-15, Gal-3) were analyzed using proximity extension assay. PWI (P-wave duration, P-wave amplitude in lead I, P-wave terminal force in V1, P-wave axis and P-wave morphology in inferior leads required for definition of interatrial block (IAB)) were derived from ECGs processed with the Glasgow algorithm. Cox regression assessed associations between the biomarkers, PWI, and incident AF.ResultsAmong 475 individuals (mean age 74.6 years; 68% male), 41 developed incident AF over 5 years. Low P-wave amplitude at inclusion correlated negatively with GDF-15 (p &lt; 0.001) and MMP-2 (p = 0.037) in both leads I and II. Six biomarkers were significantly associated with incident AF in adjusted analysis: TIMP-4 (HR 2.06, p=0.007), MMP-2 (HR 2.09, p=0.046), MMP-3 (HR 1.48, p=0.007), ST-2 (HR 1.66, p=0.003), GDF-15 (HR 2.26, p=0.001), and Gal-3 (HR 2.14, p=0.048). Among the PWI, P-wave axis &lt;0° (HR: 4.74, p = 0.021) and low P-wave amplitude in lead I (HR: 2.09, p=0.036) were significantly associated with incident AF.ConclusionsIn this long-term prospective follow-up study of patients admitted for HF, biomarkers with proven associations to fibrosis were associated with incident AF. This study also showed that low P-wave amplitude may reflect abnormal LA-conduction pathway and displaced intra-atrial conduction pattern in advanced HF, as low P-wave in lead I and abnormal P-wave axis (&lt;0 degree) were associated with incident AF.

Monitoring Is Key to Heart Failure in Elders

This study investigated Lp(a) (lipoprotein(a)) levels with heart failure (HF) incidence overall and ejection fraction (EF) subtypes among Black and White participants in a pooled analysis of MESA (Multi-Ethnic Study of Atherosclerosis), FOS (Framingham Offspring Study), and ARIC (Atherosclerosis Risk in Communities Study). This study was conducted among 16 771 White and Black participants in ARIC (N=10 347), MESA (N=4150), and FOS (N=2274). Baseline was time of Lp(a) measurement (ARIC Visit 4: 1996-1998; MESA Visit 1: 2000-2002; FOS Cycle 6: 1995-1998). HF with reduced EF (HFrEF) was defined as EF <50% and ≥50% as HF with preserved EF (HFpEF). Cox proportional hazards regression was used to evaluate associations between Lp(a) (log-transformed continuous, dichotomized at ≥30 mg/dL and ≥50 mg/dL, and quartiles) and HF (overall, HFpEF, HFrEF) in the overall population and stratified by race. Analyses were replicated excluding prior history of myocardial infarction. There were 2759 HF cases (HFpEF N=859; HFrEF N=649; EF unknown N=1251) through 2019. Among White participants, Lp(a) ≥50 mg/dL was associated with HF risk overall (hazard ratio [HR], 1.19 [95% CI, 1.07-1.34]) and by EF subtype (HFpEF HR, 1.32 [95% CI, 1.08-1.59]; HFrEF HR, 1.33 [95% CI, 1.05-1.67]). Among Black participants, Lp(a) ≥50 mg/dL was not associated with HF risk overall (HR, 0.93 [95% CI, 0.78-1.11]) or by EF subtype (HFpEF HR, 0.97 [95% CI, 0.69-1.35]; HFrEF HR, 0.89 [95% CI, 0.63-1.26]). Associations were no longer significant after excluding prior myocardial infarction. Elevated Lp(a) levels are associated with HF risk among White, but not Black individuals, and associations appears to be mostly mediated by a history of myocardial infarction.

Introduction: Atrial fibrillation (AF) is a common in patients with heart failure with preserved ejection fraction (HFpEF), and is associated with higher filling pressures, reduced exercise capacity, and reduced survival. The prevalence of subclinical AF in HFpEF remains unknown. Hypothesis: We hypothesized that subclinical AF was more prevalent in individuals with HFpEF when compared to individuals without clinical heart failure history. Methods: We evaluated subclinical AF in 101 HFpEF patients with no prior diagnosis of clinical AF using 14 day ambulatory ECG patch monitoring (Ziopatch XT, iRhythm Technologies). We compared the prevalence of subclinical AF in HFpEF with controls drawn from 3303 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) exam 6 follow-up, excluding those with known heart failure or high H2FpEF score who underwent the same ECG patch monitoring. Case-control comparisons of participants between the ages of 55 to 93 years were performed using multivariable logistic regression to adjust for demographic and clinical comorbidities, as well as patch monitoring duration. Results: 80 HFpEF patients and 1356 MESA participants were included. The HFpEF patients were younger (69 [63, 76] v. 72 [66, 80], p=0.02), more obese (BMI of 36 [30, 45] v. 27 [24, 30], p&lt;0.001) and more likely to have diabetes (34 v. 21%, p=0.01). There was a higher proportion of African Americans in the HFpEF group (57.5 v. 22.8%, p&lt;0.001). The prevalence of subclinical AF was 9.8% in HFpEF group and 6.2% in MESA participants. After multivariable adjustment for age, sex, race, body mass index, hypertension, diabetes, smoking pack-years and total analyzable time on ECG monitor there was a significantly higher odds of subclinical AF in HFpEF compared to MESA (OR 4.26 [1.2, 16.2], p=0.03). Conclusions: HFpEF patients have a higher prevalence of subclinical AF than the general population. Screening for atrial arrhythmias may be appropriate in HFpEF patients for timely initiation of thromboembolic prophylaxis, and may identify individuals at greater risk for clinical decompensation in light of the well documented risks associated with AF in HFpEF.

Heart Failure Risk Among African-American Women With an ICAM1 Missense Variant