Risk Of Heart Failure Research Articles

High-Sensitivity Troponin-T and heart failure risk in individuals with suspected acute coronary syndrome

Abstract Background In individuals with suspected acute coronary syndrome (ACS), serial assessments of high-sensitivity cardiac troponin-T (hsTnT) levels demonstrate associations with both short- and long-term mortality and recurrent ischemic events. Nonetheless, the relationship with subsequent heart failure remains inadequately characterized. Purpose We investigated the association between single and serial hsTnT levels and subsequent hospitalization or outpatient medical encounters related to heart failure in individuals presenting with suspected ACS. Methods Utilizing Danish national registries from 2012 to 2019, we identified individuals without known heart failure who underwent dual hsTnT assessments ( 99th percentile upper reference limit: 13.5 ng/l), spaced 1-7 hours apart during hospitalization for myocardial infarction (MI), unstable angina, observation for suspected MI, or chest pain. Participants were categorized based on their hsTnT concentration patterns from the first to the second measurement (primary groups: normal, rising, persistently elevated, or falling) and the extent of hsTnT concentration alterations (secondary groups: <20%, >20 to 50%, or >50% in either direction). Additionally, they were grouped into quartiles based on the initial hsTnT measurement (<=9 ng/l, 10-15 ng/l, 16-66 ng/l, >=67 ng/l) to assess whether heightened hsTnT concentrations correlated with an increased risk of heart failure. Standardized risks of hospitalization or outpatient contacts for heart failure were computed using multivariable logistic regression with average treatment effect modeling. Results The study encompassed 26,835 individuals, of whom 38.9% received discharge diagnoses of MI, 5.1% were diagnosed with unstable angina, and 56.1% with observation for suspected MI or chest pain. Median age was 64.2 years, with 59.5% males. Prevalence of known cardiovascular disease included coronary disease in 18.1% of cases, prior revascularization in 7.2%, atrial fibrillation or flutter in 7.9%, and a history of stroke in 6.3%. Within the initial 30 days, 628 persons received a heart failure diagnosis, with an additional 960 diagnosed between days 31-365. Subjects displaying two normal hsTnT values exhibited the lowest standardized absolute risk (0.39% in days 0-30; 0.58% in days 31-365), while those with persistently elevated concentrations demonstrated the highest risk (6.45% in days 0-30; 7.05% in days 31-365) (Figure). Notably, the magnitude of hsTnT within each primary group did not affect heart failure risk. Conversely, heart failure risk exhibited a positive association with hsTnT concentrations measured in the initial sample. Conclusions In individuals presenting with suspected ACS, subjects with a sustained elevation in hsTnT levels showed the highest risk of subsequent heart failure events. Moreover, a dose-response association was observed between hsTnT concentrations and heart failure risk.Figure

Differences in risk profiles and clinical outcomes according to age in patients with high-risk myocardial infarction: insights from the PARADISE-MI trial

Abstract Introduction Temporal declines in rates of rehospitalization and death after acute myocardial infarction (MI) have not been uniform across age groups. A better understanding of how risk profiles and clinical outcomes differ after MI by age may allow for targeted treatment and prevention strategies. Aims To investigate risk profiles and clinical outcomes following high-risk MI according to age in the Prospective ARNI vs ACE inhibitor trial to DetermIne Superiority in reducing heart failure Events after Myocardial Infarction (PARADISE-MI). Methods Adults without prior heart failure (HF) were randomized to sacubitril/valsartan versus ramipril within 0.5 to 7 days of a MI complicated by transient pulmonary congestion and/or left ventricular systolic dysfunction and additional risk-augmenting factors. Associations between age and clinical outcomes were analyzed using Cox proportional hazards regression models, which were additionally adjusted for baseline demographic and clinical covariates (Figure). Results The mean age of the 5,661 PARADISE-MI participants was 64 ± 11 years. Patients aged ≥75 years (n=1051) were more likely women, had more hypertension and atrial fibrillation and lower estimated glomerular filtration rate, were less likely to present with ST-segment elevation MI and regardless of type of MI were less likely to receive primary reperfusion and guideline-based medical therapy (Table). Age was significantly associated with all-cause death (HR 1.54 per 10-year increase; 95% CI, 1.41-1.68) and was more strongly associated with non-CV death (HR 2.09; 95% CI, 1.70-2.56) than with CV death (HR 1.43; 95% CI, 1.29-1.57). Age was also associated with incident HF (HR 1.37; 95% CI, 1.25-1.49) (Figure). Multivariable adjustment attenuated the risk relationship of age with recurrent fatal or non-fatal MI (HR 1.08; 95% CI, 0.96-1.21) and the coronary composite outcome (HR 1.01; 95% CI, 0.93-1.09). The relative treatment effect of sacubitril/valsartan versus ramipril on the primary composite outcome of CV death or incident HF was not significantly modified by age (p-interaction = 0.19). Conclusions Following high-risk MI, age was most strongly associated with subsequent non-CV death followed by CV death and incident HF, but was not independently associated with recurrent coronary events. The heightened risk of CV death and HF with advancing age was not explained by differences in clinical characteristics. Older patients may require closer surveillance and more aggressive treatment after MI to mitigate the elevated risk of CV death and HF.

Cardiac contractility index, a novel biomarker of incident heart failure amongst people with normal left ventricular ejection fraction in the UK Biobank

Abstract Background Cardiac contractility index (CCI) is a simple non-invasive measure of myocardial contractility defined by systolic blood pressure divided by indexed left ventricular end-systolic volume. Although left ventricular ejection fraction (LVEF) is essential for phenotyping patients with suspected heart failure (HF), it is load dependent and insensitive to subtle subclinical ventricular dysfunction. Left ventricular (LV) strain, although more sensitive at detecting subtle disturbances in myocardial function, also does not reflect loading conditions and dependency on image quality and inter-vendor variability limit widespread use. The ability of CCI to identify patients with subclinical left ventricular dysfunction at risk of developing HF is unknown. Purpose We aimed to: 1) explore the relationship between CCI with conventional imaging biomarkers of LV systolic dysfunction and 2) assess whether CCI could identify those at increased risk of incident HF in people without pre-existing left ventricular dysfunction in the UK Biobank imaging study. Methods We explored the relationship between CCI and laboratory and imaging biomarkers of systolic function, including LVEF and LV strain. Scatter plots were constructed for CCI with LVEF and LV strain. Pearson’s coefficients (r) and coefficient of determination (r2) were calculated to assess for correlations. People with sex-specific thresholds of abnormally low LVEF derived from within the same cohort (<48% for men, and <51% for women) were then excluded. CCI was then dichotomised as being high or low based its median value (4.4 mmHg/ml/m2). Age-sex adjusted Cox proportional hazards ratios (HR) with 95% CIs were estimated for the primary outcome of incident HF (derived from linked national digital registries) in addition to modelling with restricted cubic splines. Results We included 38,215 people (median age 55 years, 48% men). There was moderate correlation between CCI with LVEF (r=0.53 [0.53-0.54], R2=0.29; p<0.001), LV global circumferential strain (r=-0.50 [-0.50- -0.49], R2=0.25; p<0.001) and radial strain (r=-0.49 [0.48-0.50], R2=0.24; p<0.001), although was only weekly correlated with LV global longitudinal strain (r=-0.19 [-0.20- -0.18], R2=0.03; p<0.001) (Figure 1A). Using sex-specific thresholds 33,739 (88.3%) had a normal LVEF. During 195,584 person-years of follow-up (median 5.5 years), a total of 221 (0.7%) participants developed HF. Age-sex adjusted low CCI at baseline was associated with an increased risk of incident HF (adjusted HR 1.33 [1.01-1.75]; p=0.043). The association between CCI and incident HF was curvilinear (Figure 1B). Conclusions CCI identifies people with subclinical left ventricular systolic dysfunction at risk of developing incident heart failure.

Relationship between 3-dimensional aortic geometry and the risk of new-onset heart failure

Abstract Introduction Aortic geometric assessments to date have typically involved cross-sectional imaging of discrete aortic segments. However, the complex 3D geometry of the thoracic aorta, and its relationship to the risk of cardiovascular disease has not been assessed in large studies. Methods We segmented the thoracic aorta in SSFP axial MRI images from 49,282 UK Biobank participants using a deep convolutional neural network (U-Net). We then computed geometric measurements (centerline length, arch height, arch width, arch height-width ratio, arch unfolding index [inverse of tortuosity], curvature and mean, minimum and maximum diameters) in the overall thoracic aorta as well as in 6 subsegments. We quantified their relationship to the risk of cardiomyopathy and heart failure (HF) using multivariable Cox-proportional hazards models. All hazard ratios are standardized. Centerline length was allometrically indexed to body height. Results In models adjusted for age, sex, BMI kg/m2, low-density lipoprotein mg/dl, high-density lipoprotein mg/dl, triglycerides mg/dl, systolic blood pressure and diastolic blood pressure, the curvature of the aorta (HR=0.63; 95% CI=0.39, 0.99; P<0.05), particularly the aortic arch (HR=0.54; 95% CI= 0.35, 0.87; P<0.05) was strongly related to a lower risk of incident cardiomyopathy. A higher arch unfolding index (HR=1.46; 95% CI=1.03, 2.07; P<0.05), higher width-to-height ratio (HR=1.10; 95% CI= 1.02, 1.19; P<0.05) and lower aorta tortuosity (HR=1.20; 95% CI= 1.09, 1.32; P<0.05) were all associated with a higher risk of cardiomyopathy. This aortic geometric pattern was also associated with a greater risk of a new HF diagnosis (arch unfolding [HR=1.23; 95% CI= 1.07, 1.42; P<0.05], width to heigh ratio [HR=1.06; 95% CI= 1.01, 1.11; P0.05]). Conclusion We demonstrate that 3-D thoracic aortic geometric indices are strongly associated with incident cardiomyopathy and HF, independent of classic risk factors. This is likely related to abnormal afterload and ventricular-arterial interactions since adverse geometric remodeling affects left ventricular pulsatile load.Cardiomyopathy & Heart Failure Hazards

External validation of the HFA-ICOS risk stratification tool for prediction of cardiovascular complications after cancer treatment

Abstract Background The 2022 ESC Guidelines on Cardio-oncology recommends using the HFA-ICOS (Heart Failure Association and the International Cardio-Oncology Society) four-category risk stratification tool to predict risk of heart failure (HF) and other cardiovascular disease (CVD) complications during and after cancer therapy. However, the actual risk associated with assignment to these categories is unknown. Purpose We aimed to assess the prognostic performance the HFA-ICOS risk stratification tool in a large cancer subpopulation of a general health survey linked to Norwegian health registries. Methods Participants in a large-scale population study diagnosed with cancer between 2006 and 2012 were included (n=2290) and followed for CVD endpoints until Sept 2023. CVD risk factors were measured at baseline between 2006 and 2008. The Norwegian Cancer Registry provided detailed information about cancer characteristics and therapy. We retrieved CVD endpoints from the local hospitals’ registries and the national causes of death registry. Kaplan Meier survival curves were used to estimate the risk of the combined endpoint of HF hospitalization, myocardial infarction (MI), stroke and CVD death, as well as HF hospitalization alone and non-CVD death. Harrel’s C-statistic was used to validate the discriminative abilities. Results Mean (SD) age was 65.8 (12.4) years, 48% were female, cancer types and cardiovascular risk factors are shown in Table 1. During a median (interquartile range) follow-up of 6.9 (1.4 to 12.2) years, there were 460 first CVD events (HF hospitalizations 87 (19%), MIs 161 (35%), strokes 130 (28%), CVD deaths 82 (18%)) and 1003 (44%) non-CVD deaths. When applying the HFA-ICOS tool, 649 (28%) were assigned to the low-risk category, 912 (40%) to medium, 661 (29%) to high-risk and 68 (3%) to the very high-risk category. Between the HFA-ICOS risk categories, there were clear differences in the observed risk of CVD events, HF hospitalizations and non-CVD mortality (Figure 1). CVD incidence was highest in the highest HFA-ICOS risk categories (7% in the low risk group, 21% in the medium risk group, 31% in the high risk group and 37% in the very high-risk group (p-value <0.001)). C-statistics for predicting CVD events was 0.696 (95% CI, 0.674 to 0.718). When only assessing patients with HF hospitalizations as (first) outcome (n=116), the risk of HF was higher in the high and very high-risk groups (0% in the low risk group, 4% in the medium, 9% in high and 21% in the very high risk group (C-statistics 0.794 (95% CI, 0.762 to 0.827)). Conclusion The HFA-ICOS baseline risk assessment was useful to identify patients at risk of both clinical overt heart failure and other major CV complications and non-CV death in a population with a variety of cancers. These results can help communicate absolute risks to cancer patients, which may be helpful in the shared decision-making for cardioprotective treatment and intensified follow-up.

Prevalence and outcomes of American Heart Association stages of heart failure in an adult brazilian population of the ELSA-Brasil study

Abstract Aims Heart failure (HF) has a major impact on public health, affecting up to 2% of adult population. HF staging is helpful in capturing pre-clinical disease and its progression to advanced stages. We aimed to determine the prevalence and mortality of HF stages in the participants of a Brazilian adult cohort. Methods The ELSA-Brasil cohort comprises 15,105 adult public servants from 6 Brazilian capitals. In the initial evaluation of the study (2008-2010), ELSA carried out interviews and clinical, laboratory, and cardiovascular ancillary tests. In this analysis, we included participants who had electrocardiogram and echocardiogram performed at baseline visit, and additional information regarding risk factors and functional capacity. The HF stages were defined based on AHA guidelines criteria as follow: Stage 0 was defined as a healthy individual with no risk factors for heart failure. Stage A (at risk for HF) included those without cardiac structural or functional abnormality but with any of the following conditions: systemic hypertension; diabetes mellitus, obesity, history of myocardial revascularization, history of rheumatic fever, and seropositivity for Chagas’ disease. Stage B (pre-HF) was defined as asymptomatic participants with history of myocardial infarction or any major abnormalities on ECG or echocardiogram. Stage C (symptomatic HF) included participants with a clinical history of HF, or HF symptoms in the presence of structural heart disease (defined as in Pre-HF stage). Considering the community-dwelling profile of the sample, we did not expect to have advanced heart failure patients in our sample. Results We included the 3,267 participants (61±9 years; 53% women) with baseline data. Prevalences of HF stages were stage 0: 938 (29%) A: 1,385 (42%), B: 651 (28%) and C: 293 (9%), with different distribution between sexes (p<0.001). Older participants had higher prevalences of stages B and C (p<0.001), with the prevalence of stage C increasing from 1.8% at 35-44 years to 12.2% at 65-74 years. After 12 years of follow-up, total mortality rates of HF stages were Stage 0: 4%; A:10%. B: 16%, and C: 26%, and respective Cox proportional hazard ratios [95% CI] adjusted for age and sex were A: 1.94 [1.3-2.8], B:2.78 [1.9-4.1], and C: 5.39 [3.6-8.1] compared to stage 0. Conclusions The prevalence of HF in Brazilians reflects what is described in international literature, with a large proportion of individuals in pre-symptomatic stages. A notable shift in the sample toward pre-symptomatic and symptomatic HF occurred gradually and persistently across the age span studied. Mortality rates increase incrementally across the HF stages. This information is important for understanding and planning health policies for this syndrome.

Long term risk of heart failure in adult cancer survivors: a systematic review and meta-analysis

Abstract Background Evaluation of the cardiotoxic effects from cancer is most commonly evaluated at the time of chemotherapy. Although cancer survivorship populations are rapidly expanding, there is a paucity of evidence regarding the frequency and causes of heart failure (HF) >5 years after cardiotoxic therapy. Objectives This systematic review sought to investigate the relationship between cardiotoxic cancer therapies and late-onset HF. Methods We searched the EMBASE and MEDLINE databases for studies reporting HF in adult survivors (≥50 years old), who were ≥5 years post-breast/lymphoma cancer therapy. A random effects model was used to examine the associations of HF. A meta-regression analysis was implemented to determine causes of heterogeneity. Results Thirteen papers were included in the review and meta-analysis (Figure 1), comprising 190,259 participants (mean age 53.5 years, 93% female). The risk of HF was increased (overall log risk-ratio 0.39 (95%CI (0.16-0.62)), (Figure 2). Cardiotoxic treatment, compared with cancer alone, provided a similar risk (log risk ratio of 0.38 [95% CI 0.02-0.77]). In the breast cancer population ratio (11 studies) the overall heart failure log risk was 0.41 [95% CI 0.13-0.69]). Although heterogeneity was significant (I²=77.17), this was explained by differences in patient characteristics; once multivariable analysis accounted for follow up (0.99, 95%CI (0.97-0.99), p=0.047), age (1.14, 95%CI (1.04-1.25), p=0.003) and hypertension (0.95, 95%CI (0.92-0.98), p<0.001), residual heterogeneity was low (I²=28.73). Conclusions HF is increased in adult cancer survivors, associated with cardiotoxic cancer therapy and standard risk factors. Consideration should be given for selective screening for HF in this at-risk population.Fig 1:Literature Search Flow DiagramFig 2:Incident HF in Cancer Survivors

Non-linear causal effects of kidney function on the risk of heart failure: a Mendelian randomization study

Abstract Background Kidney insufficiency is defined as the early stage of heart failure, but Mendelian randomization (MR) analyses based on several large heart failure cohorts suggest no linear causal effect between kidney function and heart failure (HF), inconsistent with observational studies evidence. However, whether there is a non-linear causal relationship between kidney function and HF has not been reported. Methods and Results Observational and non-linear MR analyses were performed using individual-level data from a UK Biobank cohort of white British ancestry subjects (N = 386,304). There were non-linear observational associations of between kidney function as assessed with estimated glomerular filtration rate (eGFR) and HF (P for nonlinear <0.001). Non-linear MR analyses showed a U-shaped association between genetically predicted eGFR values (both creatinine- and cystatin C-based eGFR) and the risk of HF (Quadratic P value < 0.05) and the risk of HF increased with both reduced and supranormal eGFR levels (β1 = -1.70E-05, P1-value = 0.004; β2 = 3.56E-06, P2-value = 0.004). Conclusion This study observed a non-linear U-shaped genetic relationship between eGFR and HF outcomes, indicating that both reduced and supranormal eGFR may be causally linked to a higher risk of HF.Central Illustration

Exploring heart failure prevalence and overlooked dimensions: a comprehensive NT Pro-BNP study in high-risk primary care patients

Abstract Background Heart failure (HF) is a prevalent syndrome linked to significant morbidity and mortality, especially in those with comorbid conditions like diabetes, hypertension, and atherosclerotic cardiovascular disease. Early detection and intervention are crucial. Natriuretic peptides, particularly NT-proBNP, are promising biomarkers for identifying at-risk individuals, but their use in primary care settings is not fully understood. Methods This prospective cohort study enrolled 874 participants aged 40 and above with documented risk factors for HF, such as diabetes mellitus, hypertension, metabolic syndrome, obesity, atherosclerotic cardiovascular disease, genetic variants for cardiomyopathy, or exposure to cardiotoxic agents. NT-proBNP levels were measured in blood samples collected at primary care clinics, and participants underwent comprehensive cardiac evaluations at a referral hospital. Clinical characteristics, laboratory findings, electrocardiography, and echocardiography results were recorded. Results The study included 874 patients with at least one risk factor for HF, with a mean age of 62.5 ± 9.1 years and 51.9% female. According to the 2022 AHA/ACC/HFSA HF Guideline, 69.1% were Stage A HF, 21.9% Stage B HF, and 9% Stage C HF. Clinical characteristics, laboratory and echocardiographic findings are shown in Picture 1. The majority had hypertension (71.1%), while other prevalent comorbidities included diabetes mellitus (43.4%), dyslipidemia (35.2%), obesity (27.1%), and atherosclerotic cardiovascular disease (26.2%). Laboratory findings showed a significant decrease in HbA1C, eGFR, LDL, triglycerides, and hemoglobin from Stage A to C HF. Median NT-proBNP levels rose from Stage A to C HF (46.4 pg/mL in Stage A, 219 pg/mL in Stage B, and 268.5 pg/mL in stage C), with 84.8% of Stage B HF patients exhibiting elevated levels. NT-proBNP levels were correlated positively with left atrial volume index, left ventricular mass index, age, E/e’, and estimated systolic pulmonary artery pressure levels. Conversely, NT-proBNP levels showed a negative correlation with estimated glomerular filtration rate and left ventricular ejection fraction. Among Stage C patients, 92.4% had HFpEF. The Picture 2 depicted the study's design and outcomes, providing a comprehensive visual representation. Conclusion NT-proBNP screening in primary care settings identified a substantial proportion of individuals with undiagnosed HF, particularly those in Stage B and Stage C. The high prevalence of HFpEF underscores the need for comprehensive evaluation and management strategies targeting this population. Early detection facilitated by NT-proBNP screening may lead to timely interventions and improved outcomes in individuals at risk for HF.

Clinical validated risk prediction model for development of heart failure after contemporary breast cancer treatment

Abstract Background Patients receiving breast cancer (BC) treatment are at risk for heart failure and cardiomyopathy (HF/CM). European Society of Cardiology (ESC) cardio-oncology guidelines recommend baseline cardiovascular (CV) assessment, however, there is limited data about cardiotoxicity risk specific to patients with BC. Our aim was to develop and validate model for prediction of HF/CM in women receiving contemporary treatment for invasive early-stage BC. Methods We assembled a cohort women diagnosed with Stage I-III BC from 2008-2020 and followed through 2021 in a large health care plan. Women age >80, with history of HF/CM, and women who received both anthracyclines and trastuzumab were excluded, leaving N=26,044 for analysis. Study cohort was randomly split into derivation (60%) and validation (40%) datasets. Elastic-net penalized Cox proportional hazard model was created using the derivation dataset to select risk factors and to calculate the panelized coefficient which defined the HF/CM risk score. Risk score system was assessed by Hosmer-Lemeshow goodness-of-fit test and area under the ROC curve (AUC). Event rates of <5% constituted low risk; 5-14% moderate; and >15% high risk category. Incident HF/CM events were examined using Kaplan-Meier approach in derivation and validation datasets. Results HF/CM risk score had high discrimination ability and sufficiently good model of fit regarding HF/CM events (P value=0.163 and 0.667 from Hosmer–Lemeshow test;AUC 0.751 and 0.764, in derivation and validation sets, respectively). There were 10% of women in the high risk; 30% in moderate; and 60% in low-risk group. Variables associated with the higher HF/CM risk score included age, receipt of anthracycline-based chemotherapy or anti-HER2 therapy, presence of hypertension, diabetes, or history of other CV conditions at baseline. The score pattern showed major effect of age, with anthracycline and anti-HER2 therapy increasing the risk across all age groups (Figure 1). Kaplan-Meier analysis of incident HF/CM over 14 years after BC diagnosis showed significantly lower number of HF/CM events in low risk compared to moderate and high-risk score groups (p<0.0001, Figure 2). Conclusion Our robust risk prediction model for HF/CM among women with early-stage BC provides a new tool to identify women at higher CV risk and inform cardiac function monitoring during and after BC treatment. Our findings may guide further validation studies and build evidence for the cardiotoxicity risk stratification in patients with BC.Risk Score for HF/CM by Age/ChemoTxK-M curves of freedom from HF/CM

Blood plasma metabolites and heart failure risk: insights from Mendelian randomization analysis

Abstract Background Heart failure remains a leading cause of mortality and disability worldwide. Blood plasma metabolites play a crucial role in influencing heart failure, yet they are subject to numerous confounding factors. Mendelian randomization analysis provides a powerful tool for assessing causal relationships between them. Methods We conducted a Mendelian randomization analysis using a meta-analysis comprising 115,150 heart failure cases (155,331 controls) and 1400 serum metabolites. Various methods including Inverse variance weighting (IVW), MR Egger, Weighted median, and Weighted mode were employed to estimate causal effects. Sensitivity analyses were conducted using Cochran’s Q test, MR Steiger test, leave-one-out analyses, funnel plot, and MR-PRESSO. Results Following rigorous selection, among the 1400 blood plasma metabolites, 71 metabolites including Sphingomyelin, Myristate, AMP to methionine ratio showed significant associations with increased risk of heart failure. Additionally, 40 metabolites including Glycine, octadecenedioylcarnitine (C18:1-DC), 1-palmitoyl-2-dihomo-linolenoyl-GPC (16:0/20:3n3 or 6) exhibited significant associations with decreased risk of heart failure. Conclusion Identified blood plasma metabolites provide crucial insights into screening and prevention strategies for heart failure. Further validation is warranted through animal models and large-scale cohorts.

Relationship between chronic obstructive pulmonary disease and heart failure hospitalization in patients with atrial fibrillation: the Fushimi AF Registry

Abstract Background Chronic heart failure and chronic obstructive pulmonary disease (COPD) are both common diseases and often co-exist. Patients with COPD are at increased risk for hospitalizations due to cardiovascular diseases. However, in patients with atrial fibrillation (AF), the relationship between COPD and the risk of heart failure (HF) hospitalization remains unclear. Purpose The purpose of this study was to investigate the relationship between COPD and HF hospitalization in AF patients. Methods The Fushimi AF Registry, a community-based prospective survey, was designed to enroll all of the AF patients in Fushimi-ku, Japan. Fushimi-ku is densely populated with a total population of 283,000 and is assumed to represent a typical urban community in Japan. We started to enroll patients from March 2011, and follow-up data were available for 4,496 patients by the end of February 2022. We compared patients with and without COPD with regard to clinical background and HF hospitalization during follow-up period. Results In this cohort, the proportion of pre-existing HF among patients with COPD was 30.1%, and the proportion of COPD among patients with pre-existing HF was 5.9%. Of 4,496 patients, 238 (5.3%) patients had COPD (COPD; the mean age 75.6 years, female 20.6%), and the remaining 4,258 patients did not (Non-COPD; the mean age 73.5 years, female 41.6%). Patients with COPD were older than those without COPD. However, the proportions of patients with pre-existing HF, previous stroke, vascular disease, cardiomyopathy, coronary artery disease (CAD), diuretic use, renal dysfunction, diabetes mellitus (DM) and hypertension were comparable. During the median follow-up period of 1,824 days, the incidence of HF hospitalization was significantly higher in COPD than in Non-COPD (COPD vs. Non-COPD; 4.85% vs. 3.01% per person-year: p<0.01). In multivariate analysis adjusted by sex, age (≥ 75 years), heart disease (combined by heart failure, vascular disease, cardiomyopathy and CAD), renal dysfunction, DM, hypertension and diuretic use, COPD was an independent risk factor for HF hospitalization (hazard ratio (HR) 1.54, 95% confidence interval (CI) 1.15-2.07, P<0.01) (Figure 1). When we analyzed patients without pre-existing HF, the incidence of HF hospitalization was also significantly higher in COPD than in Non-COPD (COPD vs. Non-COPD; 2.87% vs. 1.75% per person-year: p=0.02). In multivariate analysis after adjusting for the same factors, COPD was an independent risk factor for HF hospitalization (HR 1.63, 95% CI 1.05-2.53, P=0.03) (Figure 2). Conclusion In patients with AF, COPD was the risk of HF hospitalization. The results were consistent in AF patients without pre-existing HF.

Prevalence and implications of cardiomyopathy-associated genetic variants in early-onset atrial fibrillation

Abstract Background Atrial fibrillation (AF) is a common and morbid arrhythmia. Despite a substantial heritable component, genetics does not currently play a role in personalized medicine for AF. Rare genetic variants in genes associated with inherited cardiomyopathies (CMP) are enriched in AF patients. However, prior studies on rare variants in AF mainly relied on hospital-based populations, and knowledge on clinical outcomes remains limited. Purpose We aimed to evaluate the potential diagnostic yield and prognostic implication of pathogenic or likely pathogenic (PLP) genetic variants for CMP in persons with AF, using large population-based cohorts. Methods This study utilized sequencing data and electronic health records (EHR) from the All of Us Researh Program (AllofUs) and UK Biobank (UKB). Using ClinVar, we curated a set of PLP variants in 36 CMP-associated genes and assessed the carrier prevalence overall, in participants with AF, and in participants with early-onset AF (below 65, 55 and 45 years). Next, we used Cox proportional hazards models to evaluate the association between variant carrier status and incident risk of heart failure or CMP, after AF diagnosis. In all time-to-event analyses, individuals with prevalent heart failure or CMP at AF diagnosis were excluded and models were adjusted for age, sex, and principal components of ancestry. Sensitivity analyses were performed requiring a minimum period from AF to HF or CMP, of 1, 3 and 6 months. Results After excluding related individuals, we identified 32,281 (8.19%) and 9,666 (6.06%) AF cases in UKB and AllofUs, respectively. Compared to the overall populations (UKB: 1.15%; AllofUs: 1.36%), PLP variants for CMP were about ~5 times more prevalent in AF with onset before 45 (UKB: 4.98%; AllofUs: 5.26%), ~3 times more prevalent in AF with onset before 55 (UKB: 3.41%; AllofUs: 4.34%) and ~2 times more prevalent in all AF patients (UKB: 2.03%; AllofUs: 2.67%). In turn, AF patients carrying PLP variants had increased risk of developing heart failure or CMP, after AF diagnosis (AllofUs HR 1.81, 1.44-2.29, p<1e10-6, UKB:HR=1.39 1.08-1.78, p<0.01), which remained present when requiring a minimum of 6 months after AF diagnosis (AllofUs:HR 1.70, 1.29-2.25, p<0.001; UKB:HR=1.59, 1.21-2.07, p<0.001). Effect sizes were greater when limiting analysis to AF patients with onset before 65 (cases=1021, HR 1.91, 1.35-2.68, p<0.0001) and before 55 years (cases=384, HR 2.53, 1.55-4.1, p <0.001) in AllofUs. UK Biobank did not reflect this increase (cases<65=513, HR<65=1.27, 0.63-2.39, p<65>0.05). Considering only HF events in AllofUs, the effect remained present (HR 1.70, 1.32-2.19, p<0.0001). Conclusion The yield of CMP-associated PLP variants is substantial among persons with early-onset AF, even when considering a 55 year cutoff. AF patients with PLP variants have an increased risk of future heart failure or CMP. Our results further support the clinical relevance of genetic testing in early-onset AF.Prevalence of CMP variants in AF by age

Epi-Allele: CRISPR-mediated allele-specific epigenetic editing alleviates hypertrophic cardiomyopathy

Abstract Background Hypertrophic cardiomyopathy (HCM) is a prevalent genetic heart disease caused by variants in sarcomere genes like MYH7, which accounts for 40% of cases with 75% being heterozygous. HCM shows incomplete penetrance, where mutant allele expression correlates with severity. Thus, allele-specific suppression is a potential therapy. While allele-specific RNAi or CRISPR/Cas9 showed moderate efficacy, low expression level of MYH7 is associated with the risk of heart failure and dilated cardiomyopathy. We hypothesized CRISPR-based epigenetic editing（dCas9 fused with DNA methylation and histone regulation elements） may potently achieve phenotypic modification without impacting overall gene expression. Objective We investigated allele-specific CRISPR epigenetic editing (Epi-Allele) to selectively suppress mutant Myh6 allele expression without affecting total expression, as a novel HCM therapy in a mouse model. Results We first generated C57R403Q/DBA mice to simulate heterozygous HCM patients. Allele-specific Myh6 gRNAs reduced C57 allele expression and increased DBA expression without impacting total Myh6 expression in primary cardiomyocytes, effects sustained for one year in report cells. HCM mice with Epigenetic editor and allele-specific gRNAs (Epi-Allele) showed reduced left ventricular wall thickness, normalized ECG, and less cardiac fibrosis. Similar therapeutic effects were observed in HCM mice treated by a dual AAV delivery system of Epi-Allele. We further found that Epi-Allele could reverse established disease in the inducible transgene mice. We’ve also seen similar surprising therapeutic effects from Epi-Alleles in patient-derived pluripotent stem cell-induced cardiomyocytes (iPSC-CMs). Conclusion We suggest that Epi-Allele may be a novel therapy for HCM and other dominant diseases where the mutant gene plays a vital role, overcoming the limitations of previous allele-specific suppression strategy.Figure abstract of Epi-AlleleThe universality of Epi-Alleles

A smartphone based AI model to detect left ventricular systolic dysfunction on 12-lead ECG

Abstract Background Despite echocardiography being essential for cardiac assessment, a point-of-care tool for rapid left ventricular ejection fraction (LVEF) evaluation is lacking in current clinical practice, highlighting the need for a widescale, easily deployable method to assess LV function. Purpose To develop and validate two artificial intelligence (AI) models that accurately detect reduced LVEF on a single 12-lead ECG using a smartphone, facilitating early identification of patients at risk for heart failure who may benefit from more detailed echocardiographic evaluation. Methods A large collection of ECGs and transthoracic echocardiograms (TTEs) was sourced from our hospital data vault from 2011 to 2021. ECGs were paired to TTEs within a 24h time window and the resulting pairs were randomly assigned to the model development dataset (50%) and validation dataset (50%). Two distinct AI-ECG models were developed: one to detect LVEF≤40% and another for LVEF<50%, derived from the ESC definition of heart failure. Both AI-ECG models were paired with smartphone based ECG digitization technology. Key performance metrics include area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1-score. Results A total of 1,205,370 ECGs (198,274 patients) and 291,433 TTEs (105,849 patients) were collected and paired, resulting in 109,809 ECG-TTE pairs (56,236 patients). The validation dataset consisted of 25,510 distinct TTE-ECG pairs (25,510 patients). Prevalence of LVEF≤40% and LVEF<50% was 5.4% and 7.9% respectively. The LVEF≤40% model demonstrated an AUC of 0.963 (95% CI: 0.959-0.966), sensitivity 0.924 (95% CI: 0.91-0.937), specificity 0.887 (95% CI: 0.883-0.891), and F1-score of 0.474 (95% CI: 0.457-0.490). PPV and NPV were 0.318 (95% CI: 0.304-0.333) and 0.995 (95% CI: 0.994-0.996) respectively. Performance of the LVEF <50% model shows an AUC of 0.952 (95% CI: 0.947-0.956), with a slightly lower sensitivity of 0.899 (95% CI: 0.886-0.912), specificity of 0.875 (95% CI: 0.871-0.879), PPV of 0.382 (95% CI: 0.368-0.395), NPV of 0.99 (95% CI: 0.989-0.992), and F1-score of 0.536 (0.521-0.55). Conclusion The AI models exhibit the ability to identify reduced LVEF from standard 12-lead ECGs using a smartphone. Results suggest potential clinical utility as a preliminary screening tool to select patients for confirmatory echocardiography. This AI application could potentially offer a timely and cost-effective method for identifying patients at risk for future development of heart failure.

Sex-biased proteomic regulation in obesity

Abstract Background Obesity is a major risk factor for heart failure with preserved ejection fraction, particularly in women. Obesity-associated inflammation is thought to contribute to this relationship. However, the role of biological sex in the regulation of circulating inflammatory proteins in obesity is not well understood. Purpose We aimed to explore sex differences in the plasma inflammatory protein profile in obese subjects. Methods Clinical data and samples were collected from 450 women and men with a body mass index (BMI) >27 kg/m² without known cardiovascular disease participating in the FAT associated CardiOvasculaR dysfunction study. Obesity was defined as BMI≥30 kg/m². Olink’s Target 96 inflammation panel, which profiles 92 proteins using proximity extension assay technology, was analysed in biobank samples. A comprehensive correlation analysis was performed to describe relationships between protein biomarkers and clinical variables. Gene enrichment analysis was performed to shed light on biological pathways associated with differentially expressed proteins (DEPs). To determine the functional significance of the DEPs, we used the repositories Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Pearson correlation coefficients were calculated to assess linear associations between the DEPs and relevant clinical variables. Results Women and men did not differ by age (49±9 vs 48±9 years), BMI (32.3±4.6 vs 31.6±3.7 kg/m²) or in prevalences of diabetes (both 11%) or obesity (65% vs 62%) (all p>0.05). However, hypertension was more common in men than women (74% vs 52%, p<0.001). In men (n=188), obesity was associated with downregulation of monocyte chemotactic protein 3, tumor necrosis factor (ligand) superfamily member 12, interleukin 10 and protein S100-A12 and with upregulation of neurotrophin-3 (all p<0.05), thereby suggesting a mechanism for the observed impaired inflammatory response and insulin resistance. In women (n=262), obesity was associated with the downregulation of interleukin 7, interleukin 12 subunit beta, interleukin 6, and C-X-C motif chemokine 11, suggesting a state of persistent low-grade inflammation. In addition, the upregulated sulfotransferase 1A1 and SIR2-like protein 2 proteins indicate a physiologic adaptation to oxidative stress and the metabolic excess endemic to obesity. Conclusion We found that the abundance of several circulating inflammatory proteins was altered in presence of obesity, and that the plasma proteomic profile differed by sex. Interestingly, there was no overlap in the DEPs between women and men in the presence of obesity. These findings support the hypothesis that the pathophysiological mechanisms driving obesity-associated inflammation and immune dysregulation differ by sex. In turn, this may aid in the pursuit of discovering sex-specific biomarkers to identify obese individuals at particular risk of heart failure.

Assessing stroke and mortality risk in heart failure: the CHA2DS2-VASc score's prognostic value in patients with and without atrial fibrillation - a systematic review and meta analysis

Abstract Background Heart failure (HF) is a common cardiovascular disorder that is linked to substantial morbidity and mortality. The CHA2DS2-VASc score, originally designed to assess the risk of stroke in patients with atrial fibrillation, has demonstrated potential as a prognostic indicator for adverse outcomes in patients with heart failure. This systematic review and meta-analysis aimed to assess the predictive accuracy of the CHA2DS2-VASc score in determining the occurrence of stroke and increased mortality rates in patients with heart failure. Methods A thorough search of electronic databases, such as PubMed, EMBASE, and the Cochrane Library, was performed to find pertinent papers published until the search cutoff date. Included studies examined the correlation between the CHA2DS2-VASc score and the likelihood of stroke or death in patients with heart failure. The assessment of the quality of the included studies was conducted using recognized criteria, and data were collected for quantitative synthesis. Findings The meta-analysis encompassed four studies (45864 patients), revealing a consistent and substantial correlation between elevated CHA2DS2-VASc scores and heightened risks of both stroke and mortality in heart failure patients. More precisely, patients with CHA2DS2-VASc scores ≥4 had a greater risk of stroke compared to those with scores <4 (odds ratio 0.38, 95% confidence interval 0.33-0.43, p-value < 0.00001). The combined data showed homogeneity (p-value = 0.24, I2 = 29%). Similarly, patients with CHA2DS2-VASc scores ≥4 had a higher risk of mortality compared to those with scores <4 (OR 0.49, 95% CI 0.30-0.80, P = 0.05). However, the combined data showed significant heterogeneity (P < 0.00001, I2 = 96%). Conclusion The CHA2DS2-VASc score is a useful predictive tool for identifying heart failure patients who are hospitalized and at a high risk of both stroke and high mortality. The results of this study provide evidence for the practicality of using the CHA2DS2-VASc score for risk stratification in patients with heart failure. Additional investigation is necessary to confirm these findings and examine the incorporation of the CHA2DS2-VASc score into risk assessment algorithms for tailored patient management.Figure:Risk of strokeFigure:Risk of mortality

Atrial Fibrillation (AF) detected by repeat handheld ECG screening and the risk of heart failure hospitalization

Abstract Purpose Heart failure and atrial fibrillation (AF) frequently complicate one another. Risk of heart failure in screen-detected patients was not investigated. We aimed to compare risk of hospitalization for heart failure (HHF) between screen-detected and clinically-diagnosed AF, and to evaluate the impact of AF burden. Methods Consecutive patients aged over 65 attending outpatient clinics were prospectively recruited for AF screening, using handheld single-lead ECG (AliveCor) during December 2014 and December 2017. Patients who had >1 visits received repeat screening. All participants were divided into 5 cohorts: (i) previously known AF at enrolment; (ii) initial screen-detected AF; (iii) subsequent screen-detected AF; (iv) clinically-diagnosed AF during follow-up (FU); (v) No AF. Risk of HHF was estimated by adjusted sub-distribution hazard ratios (aSHR) derived from Fine and Gray regression, accounting for death as competing risk, adjusting for CHA2DS2VASC components and chronic kidney disease, AF diagnosis being handled as time-dependent variable. Patients who participated in repeat screening and previously known AF formed a sub-cohort. Patients with previously known AF who were in AF in the initial screening and those with repeat screen-positivity were defined probably persistent AF, otherwise paroxysmal AF (single screen-positivity) or no AF (never screen-positive). Risk of HHF was compared between groups stratified by AF burden (persistent vs. paroxysmal) and scenario of AF diagnosis (screen-detected vs. clinically-diagnosed). Results Of 11,972 subjects (mean age 76.6±7.8, female 49.2%), 18.7% (n=2,236) had known AF, 1.9% (n=223) initial screen-detected AF, 0.6% (n=71) subsequent screen-detected AF, 7.3% (n=867) clinically-diagnosed AF during FU, and 71.6% (n=8,559) no AF. During a median FU of 6.7 (IQR:4.4-8.0) years, risk of HHF was highest in patients with clinically-diagnosed AF (aSHR=3.5(2.7-4.5)), followed by subsequent screen-detected AF (aSHR=2.8(1.6-5.0)), previously known AF (aSHR=1.9(1.6-2.2)), and initial screen-detected AF (aSHR=1.7(1.1-2.4)) (Figure 1a). Sensitivity analysis excluded those with known heart failure at baseline, after which risk of HHF became comparable between previously known and initial screen-detected AF (Figure 1b). Sub-analysis for participants (32.2% (n=3,853), mean age 76.7±7.3, female 47.5%) of repeat screening showed screen-detected persistent AF (aSHR=3.7(1.9-7.2)) was at highest risk of HHF, followed by clinically-diagnosed AF (AF burden unassessed) (aSHR=3.3(2.2-5.0)), previously known persistent AF (aSHR=3.1(2.5-3.8)), screen-detected paroxysmal AF (aSHR=2.1(1.4-3.4)), previously known paroxysmal AF (aSHR=1.8(1.3-2.4) (Figure 1c). Conclusion Higher AF burden and FU new AF diagnosed by either screening or clinic visit was associated with higher risk of HHF. Screening facilitating early AF diagnosis and early downstream intervention, warranted further study.

Serum metabolomics improve risk stratification for incident heart failure

Abstract Background The prediction and early detection of heart failure (HF) is vital to reduce its substantial impact on quality of life, survival and healthcare expenditure. Current incident HF risk stratification strategies achieve only modest performance. Moreover, state-of-the-art risk scores focus on commonly acknowledged clinical risk factors, thus necessitating the integration of heterogenous data sources and prioritizing individuals with obvious risk constellations. Purpose Here, we explored the predictive value of serum metabolomics (168 metabolites detected by proton nuclear magnetic resonance (1H-NMR) spectroscopy) for incident HF. Methods Leveraging data of n = 68,311 individuals and > 0.8 million person-years of follow-up from the UK Biobank (UKB) cohort, we (I) evaluated the association of individual metabolites with incident HF via fitting of per-metabolite COX proportional hazards models and (II) trained and validated elastic net (EN) models to predict incident HF using the serum metabolome. Discriminative performance was benchmarked against a comprehensive, well-validated clinical risk score (Pooled Cohort Equations to Prevent HF, PCP-HF). External validation was conducted in the independent FINRISK study. Results Several metabolites were independently associated with incident HF (90/168 adjusting for age and sex, 48/168 adjusting for PCP-HF). Performance-optimized risk models effectively retained key predictors representing highly correlated clusters (≈ 80 % feature reduction). The addition of metabolomics to PCP-HF improved predictive performance (Harrel’s C: 0.768 vs. 0.755, ΔC = 0.013 (95% confidence interval (CI) 0.004 – 0.022), continuous net reclassification improvement (NRI) = 0.287 (95% CI 0.200 – 0.367), relative integrated discrimination improvement (IDI): 17.47 % (95% CI 9.463 - 27.825)). Simplified models only including age, sex and metabolomics performed almost as well as the PCP-HF model (Harrel’s C: 0.745 vs. 0.755, ΔC = 0.010 (95% CI -0.004 - 0.027), continuous NRI: 0.097 (95% CI -0.025 - 0.217), relative IDI: 13.445 % (95% CI -10.608 - 41.454)). Risk and survival stratification was improved by integrating metabolomics. External validation within FINRISK revealed similar patterns using the original model coefficients. Conclusions Serum metabolomics improve the prediction of incident HF risk. Scores obtained from the combination of age, sex and metabolomics exhibit similar predictive power as clinical risk models. Offering serum metabolomics to a middle-aged cohort might significantly improve HF risk stratification, thus facilitating preventive efforts. Via a single blood draw, serum metabolomics displays a highly cost- and time-effective, standardizable, and scalable alternative to clinical risk scores involving physical measurements and history taking in addition to clinical chemistry.Relative performance (test split)ROC & DCA plots (test split)

Risk prediction models for incident heart failure: a systematic review and meta-analysis

Abstract Background Heart failure (HF) risk prediction models combine multivariable patient data to estimate an individual's risk of developing HF. By detecting at-risk and early-stage patients, models may facilitate earlier intervention to prevent or delay HF development. Previous systematic reviews were unable to recommend any existing prediction models for clinical use due to insufficient evidence and lack of guidelines on appraising study quality at their time of publication. Purpose To summarize the performance of risk prediction models for incident HF and identify models for further validation and potential clinical use. Methods We searched MEDLINE and EMBASE in June 2021 for English-language studies developing or validating HF risk prediction models. Studies were also retrieved from two previous systematic reviews. We narratively summarized model characteristics (e.g. model type, predictors used, prediction horizon) and study methodology (e.g. validation methods). Performance was assessed among all models validated in ≥ 1 cohort. For all models validated in ≥ 2 cohorts, we pooled discrimination measures using random-effects meta-analyses. Calibration was descriptively summarized based on individual study results from statistical tests and graph digitization of calibration plots. Study quality was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Results Of 18,937 publications screened, 41 studies consisting of 120 prediction models were included. Twenty models were both derived and validated, 99 only derived, and 1 only validated. Risk of bias was rated as high in nearly all (94.7%) PROBAST assessments, mostly attributable to issues with analysis. Among 21 models validated in ≥ 1 cohort, most had moderate (61.9%, C-statistic 0.7 to <0.8) or high (23.8%, C-statistic 0.8 to <0.9) discrimination. In patients with low predicted risk (<10%), the calibration was adequate. Nine (42.9%) of these 21 models were presented as web-based calculators and five (23.8%) as points-based risk scores. Based on performance, number of validation cohorts, study risk of bias, and user friendliness, the Atherosclerosis Risk in Communities (ARIC), Multi-Ethnic Study of Atherosclerosis (MESA), Pooled Cohort equations to Prevent Heart Failure (PCP-HF), and Health ABC models emerged as the most promising risk scores for clinical practice. Conclusions Given their acceptable performance but high risk of bias, future studies should focus on the external validation of these models in studies of high methodological rigor. Models should be validated in a greater diversity of patient populations, particularly with respect to race. Impact analyses assessing how the clinical implementation of these models affects patient outcomes are also required prior to their routine use. Once validated, these models may help guide clinical decision making to prevent the onset of HF with early, aggressive risk factor modification.Discrimination in 21 validated modelsCharacteristics of recommended models