HF Phenotypes Research Articles

Kiosk 6R-FB-03 - Impaired Cardiac Sympathetic Innervation Activity Is Associated with Myocardial Extracellular Remodeling and Discriminates Between HF Phenotypes

Kiosk 6R-FB-03 - Impaired Cardiac Sympathetic Innervation Activity Is Associated with Myocardial Extracellular Remodeling and Discriminates Between HF Phenotypes

Cause-specific death in heart failure across the ejection fraction spectrum

Abstract Background Heart failure (HF) is associated with increased cardiovascular (CV) and non-CV mortality, but little data is available on underlying causes of death in HF phenotypes based on ejection fraction (EF). Knowledge about causes of mortality may have implications for healthcare decisions, treatment priorities and clinical trial design. Purpose To examine cause-specific mortality in patients with HF with reduced EF (HFrEF), HF with mildly reduced EF (HFmrEF), and HF with preserved EF (HFpEF). Methods Patients enrolled in the Swedish Heart Failure Registry between 2000-2021 were included. The causes and incidence rates of death across the EF categories were studied. In addition, to examine the association between EF categories and cardiovascular (CV) and non-CV mortality, sub-distributional hazards models were performed accounting for competing risk of death from other causes and adjusted for age and sex. Results Among 100,584 patients (23% HFpEF, 23% HFmrEF, 53% HFrEF), median age (IQR) was 75.0 (66.0-82.0) and 36.5% were females. Of those who died within 5 years, most deaths were ascribed to CV deaths across all EF categories (65% in HFrEF, 59% in HFmrEF and 58% in HFpEF, respectively). Within 5 years, patients with HFpEF had higher risk of non-CV mortality (adjusted HR 1.38, 95% CI 1.33-1.43, p< 0.001) and lower risk of CV mortality (adjusted HR 0.80, 95% CI, 0.78-0.83, p< 0.001) compared to patients with HFrEF. Ischemic heart disease (IHD) was the most common cause of CV-death while cancer was the most common cause of non-CV death across all EF categories. The incidence rate of CV death due to IHD was higher in HFrEF while the incidence rates of CV death due to pulmonary vascular disease, stroke, valvular heart disease and atrial fibrillation were higher in HFpEF compared to HFrEF and HFmrEF (Figure 1). Patients with HFpEF had higher incidence rate of non-CV deaths due to cancer, respiratory disease, accidents and infections including covid -19 compared with HFrEF and HFmrEF patients (figure 2). Conclusion In this large and contemporary cohort of patients with HF, CV death was more common than non-CV death across all EF categories although the risk of non-CV mortality within 5-years was higher with increasing EF. IHD and cancer were the most common causes of CV and non-CV deaths, respectively, regardless of EF category. Patients with HFpEF had a higher burden of non-CV causes of death than patients with HFrEF and HFmrEF.Incidence rate CV deathIncidence rate non-CV death

Prognosis, characteristics, and provision of care for patients with the unspecified heart failure electronic health record phenotype: a population-based linked cohort study of 95262 individuals

Whether the accuracy of the phenotype ascribed to patients in electronic health records (EHRs) is associated with variation in prognosis and care provision is unknown. We investigated this for heart failure (HF, characterised as HF with preserved ejection fraction [HFpEF], HF with reduced ejection fraction [HFrEF] and unspecified HF). We included individuals aged 16 years and older with a new diagnosis of HF between January 2, 1998 and February 28, 2022 from linked primary and secondary care records in the Clinical Practice Research Datalink in England. We investigated the provision of guideline-recommended diagnostic investigations and pharmacological treatments. The primary outcome was a composite of HF hospitalisation or all-cause death, and secondary outcomes were time to HF hospitalisation, all-cause death and death from cardiovascular causes. We used Kaplan-Meier curves and log rank tests to compare survival across HF phenotypes and adjusted for potential confounders in Cox proportional hazards regression analyses. Of a cohort of 95,262 individuals, 1271 (1.3%) were recorded as having HFpEF, 10,793 (11.3%) as HFrEF and 83,198 (87.3%) as unspecified HF. Individuals recorded as unspecified HF were older with a higher prevalence of dementia. Unspecified HF, compared to patients with a recorded HF phenotype, were less likely to receive specialist assessment, echocardiography or natriuretic peptide testing in the peri-diagnostic period, or receive angiotensin-converting enzyme inhibitors, beta blockers or mineralocorticoid receptor antagonists up to 12 months after diagnosis (risk ratios compared to HFrEF, 0.64, 95% CI 0.63-0.64; 0.59, 0.58-0.60; 0.57, 0.55-0.59; respectively) and had significantly worse outcomes (adjusted hazard ratios compared to HFrEF, HF hospitalisation and death 1.66, 95% CI 1.59-1.74; all-cause mortality 2.00, 1.90-2.10; cardiovascular death 1.77, 1.65-1.90). Our findings suggested that absence of specification of HF phenotype in routine EHRs is inversely associated with clinical investigations, treatments and survival, representing an actionable target to mitigate prognostic and health resource burden. Japan Research Foundation for Healthy Aging and British Heart Foundation.

Financial burden of heart failure in Malaysia: A perspective from the public healthcare system.

Estimating and evaluating the economic burden of HF and its impact on the public healthcare system is necessary for devising improved treatment plans in the future. The present study aimed to determine the economic impact of HF on the public healthcare system. The annual cost of HF per patient was estimated using unweighted average and inverse probability weighting (IPW). Unweight average estimated the annual cost by considering all observed cases regardless of the availability of all the cost data, while IPW calculated the cost by weighting against inverse probability. The economic burden of HF was estimated for different HF phenotypes and age categories at the population level from the public healthcare system perspective. The mean (standard deviation) annual costs per patient calculated using unweighted average and IPW were USD 5,123 (USD 3,262) and USD 5,217 (USD 3,317), respectively. The cost of HF estimated using two different approaches did not differ significantly (p = 0.865). The estimated cost burden of HF in Malaysia was USD 481.9 million (range: USD 31.7 million- 1,213.2 million) per year, which accounts for 1.05% (range: 0.07%-2.66%) of total health expenditure in 2021. The cost of managing patients with heart failure with reduced ejection fraction (HFrEF) accounted for 61.1% of the total financial burden of HF in Malaysia. The annual cost burden increased from USD 2.8 million for patients aged 20-29 to USD 142.1 million for those aged 60-69. The cost of managing HF in patients aged 50-79 years contributed 74.1% of the total financial burden of HF in Malaysia. A large portion of the financial burden of HF in Malaysia is driven by inpatient costs and HFrEF patients. Long-term survival of HF patients leads to an increase in the prevalence of HF, inevitably increasing the financial burden of HF.

Relationship between iron deficiency and expression of genes involved in iron metabolism in human myocardium and skeletal muscle

BackgroundIron deficiency (ID) is associated with adverse prognosis in patients with heart failure. This study aims to investigate the relationship between ID and expression of genes involved in iron metabolism in human myocardium and skeletal muscle, focusing on Transferrin 1 receptor (TfR1), the main pathway of cellular iron uptake. MethodsPatients undergoing elective CABG were assessed prior to surgery with echocardiography and serum iron parameters. Core needle biopsies were collected from the left and right ventricle (LV, RV), the right atrium and intercostal skeletal muscle (SM). Gene expression analyses were done by mRNA sequencing. ResultsOf 69 patients (median age 69 years, 91% men), 28% had ID. 26% had HFrEF, 25% had HFpEF physiology according to echocardiographic findings and NT-proBNP levels, and 49% had normal LV function. The expression of TfR1 was increased in patients with ID compared to patients without ID in ventricular tissue (p = 0.04) and in intercostal SM (p = 0.01). The increase in TfR1 expression in LV and RV was more pronounced when analysing patients with absolute ID (S-Ferritin<100 μg/L). Analysing the correlation between various iron parameters, S-Ferritin levels showed the strongest correlation with TfR1 expression. There was no correlation with NT-proBNP levels and no difference in TfR1 expression between different HF phenotypes. ConclusionsIn patients undergoing elective CABG we found an association between ID and increased TfR1 expression in myocardium regardless of LV function, indicating physiologically upregulated TfR1 expression in the presence of ID to restore intracellular iron needs.Clinical Trial Registration:Clinicaltrials.govNCT03671122

The Impact of SGLT2 Inhibitor Dapagliflozin on Adropin Serum Levels in Men and Women with Type 2 Diabetes Mellitus and Chronic Heart Failure

adropin plays a protective role in cardiac remodeling through supporting energy metabolism and water homeostasis and suppressing inflammation. Low circulating levels of adropin were positively associated with the risk of cardiovascular diseases and type 2 diabetes mellitus (T2DM). We hypothesized that sodium-glucose linked transporter 2 (SGLT2) inhibitor dapagliflosin might represent cardiac protective effects in T2DM patients with known chronic HF through the modulation of adropin levels. we prospectively enrolled 417 patients with T2DM and HF from an entire cohort of 612 T2DM patients. All eligible patients were treated with the recommended guided HF therapy according to their HF phenotypes, including SGLT2 inhibitor dapagliflozin 10 mg, daily, orally. Anthropometry, clinical data, echocardiography/Doppler examinations, and measurements of biomarkers were performed at the baseline and over a 6-month interval of SGLT2 inhibitor administration. in the entire group, dapagliflozin led to an increase in adropin levels by up to 26.6% over 6 months. In the female subgroup, the relative growth (Δ%) of adropin concentrations was sufficiently higher (Δ% = 35.6%) than that in the male subgroup (Δ% = 22.7%). A multivariate linear regression analysis of the entire group showed that the relative changes (Δ) in the left ventricular (LV) ejection fraction (LVEF), left atrial volume index (LAVI), and E/e' were significantly associated with increased adropin levels. In the female subgroup, but not in the male subgroup, ΔLVEF (p = 0.046), ΔLAVI (p = 0.001), and ΔE/e' (p = 0.001) were independent predictive values for adropin changes. the levels of adropin seem to be a predictor for the favorable modification of hemodynamic performances during SGLT2 inhibition, independent ofN-terminal brain natriuretic pro-peptide levels.

Heart failure classification based on resting ejection fraction does not display a unique exercise response pattern

BackgroundHeart failure with preserved (HFpEF), mildly reduced (HFmrEF) and reduced (HFrEF) ejection fraction (EF) remains a controversial categorization. Whether these three categories reflect a distinct pattern of exercise limitation in cardiopulmonary exercise testing (CPET) needs to be investigated. We aimed to analyze whether CPET variables differ between all heart failure categories (HF). MethodsWe analyzed CPET variables of stable HFpEF (n = 123), HFmrEF (n = 31), and HFrEF (n = 153; 74 patients with and 79 patients without left ventricular assist device, LVAD) patients. The association between HF and peak oxygen consumption (VO2peak) was used as a primary outcome, while the association between HF, oxygen uptake efficiency slope (OUES), and increase of O2 pulse (ΔO2 pulse) were analyzed as secondary outcomes. ResultsVO2peak displayed a consistent decline across all HF categories (19.8 ml ± 6.2/kg/min vs. 17.5 ± 7.9 ml/kg/min vs. 13.7 ± 4.0 ml/kg/min, p < 0.001). OUES only showed differences between HFpEF and HFrEF (1.8 ± 0.6 vs. 1.4 ± 0.5, p < 0.001) as well as HFmrEF and HFrEF (1.9 ± 0.9 vs. 1.4 ± 0.5, p = 0.004). ΔO2 pulse differed between HFpEF and HFrEF (7.7 ± 3.5 ml/beat/kg*100 vs. 5.5 ± 3.0 ml/beat/kg*100, p < 0.001) as well as HFpEF and HFmrEF (7.7 ± 3.5 ml/beat/kg*100 vs. 6.3 ± 4.1 ml/beat/kg*100, p = 0.049). Outcome variables did not differ between HFrEF with and without LVAD support (VO2peak: p = 0.364, OUES: p = 0.129, ΔO2 pulse: p = 0.564). ConclusionsHF did not display a distinct CPET profile. Thus, EF-based categorization does not entirely reflect exercise limitations. CPET variables could contribute to better characterize HF phenotypes.

328 IMPACT OF INTEGRATED CARE WITH ABC PATHWAY IN PATIENTS WITH ATRIAL FIBRILLATION AND HEART FAILURE: DATA FROM MORE THAN 11000 PATIENTS ENROLLED IN A EUROPEAN REGISTRY

Abstract Background and aim Heart failure (HF) is closely associated with atrial fibrillation (AF). The Atrial fibrillation Better Care (ABC) pathway is recommended in guidelines as a holistic or integrated care approach to AF management. However, few data are specifically available on ABC pathway adherence in AF patients with HF, especially according to HF phenotypes. Therefore, we aimed to retrospectively investigate the effect of ABC management in a large contemporary cohort of AF patients with HF and the impact on the clinical outcomes. Methods We analyzed patients enrolled in the ESC-EHRA EORP-AF General Long-Term Registry. According to the availability of HF status and ejection fraction (EF) values, patients were categorized as follows: i) non-HF; ii) HF EF&amp;gt;40% iii) HF EF≤40%. The primary outcome was a composite outcome of all-cause death and major adverse cardiac events. Results Among the original 11 096 AF patients enrolled, 9175 (82.7%) were included in this analysis (median age 71 years, interquartile range [IQR 63-77], 40.1% were female, with median EF 55% [IQR 45-61%] and median CHA2DS2-VASc 3 [2-4]). In this cohort, 5935 (64.7%) were non-HF patients, and 3240 (35.3%) had HF patients. According to the EF values, 2005 (65%) were categorized as HF EF&amp;gt;40%, and 1235 (35%) were HF EF≤40%. Overall, ABC pathway adherence in HF patients was 23.3% [95% CI: 21.6-25.2], being higher in HF EF≤40% patients (28.0%) and lower in HF EF&amp;gt;40% ones (21.9%). After a median follow-up of 731[IQR 690-748] days, ABC adherence was associated with a lower risk for the composite outcome compared to non-ABC adherent patients in each HF group (HF EF&amp;gt;40%: ABC 15.4% vs no ABC 20.9%; HF EF≤40%: ABC 20.3% vs no ABC 33.9%; both p&amp;lt;0.001). Cox regression analysis showed that ABC adherence was associated with a lower risk of composite outcome in each HF category (HF EF&amp;gt;40%: HR 0.66 [95% CI: 0.46-0.96], p=0.030; HF EF≤40%: HR 0.60 [95% CI: 0.40-0.90], p=0.013). ABC adherence was associated with a consistent risk reduction for the composite outcome across the entire EF spectrum [Figure]. Conclusions In this large contemporary cohort of AF-HF patients, adherence to the ABC pathway was associated with a lower occurrence of the primary outcome, irrespective of baseline EF. ABC pathway is consistently associated with a lower risk for adverse outcomes across the entire spectrum of EF.

Heart failure and cardiovascular outcomes in european patients with atrial fibrillation

Abstract Background Heart failure (HF) has an intimate bidirectional association with atrial fibrillation (AF). Few data are available about the impact of HF phenotypes (HF with preserved ejection fraction, HFpEF; HF with mildly reduced ejection fraction, HFmrEF; HF with reduced ejection fraction, HFrEF) as predictors for adverse outcomes in AF patients. Purpose To investigate the association of HFpEF, HFmrEF and HFrEF with adverse outcomes in a large contemporary cohort of European AF patients and evaluate the effect of EF throughout its entire spectrum. Methods We analyzed patients enrolled in the ESC-EHRA EORP-AF General Long-Term Registry. HF patients were categorized according the three phenotypes and compared to those without HF (“non HF”). Main outcome was a composite outcome of all-cause death and major adverse cardiac events (MACE). Results Among the original 11,096 AF patients enrolled, 9857 (88.8%) were included in this analysis (median age 71 years, interquartile range [IQR 63–77], 40.1% females) with median EF 55% [IQR 45–61%] and CHA2DS2-VASc 3 [2–4]). In this cohort, 5935 (60.2%) were non HF patients, and 3240 (32.9%) had HF patients (with HF status and EF values data available). Accordingly, 1662 (51.2%) were categorized as HFpEF; 523 (14.1%) were HFmrEF; and 1235 (35.1%) were HFrEF. After a median follow-up of 731 days [IQR 690–748], the composite outcome was significantly higher throughout HF categories (HFpEF 19.0%, HFmrEF 21.8% and HFrEF 29.6%, compared to non HF 10.7%; p&amp;lt;0.001). In a fully adjusted multivariate Cox regression, HF phenotypes were associated with a progressively higher risk for the composite outcome (HFpEF HR 1.45 [95% CI, 1.23–1.70]; HFmrEF HR 1.82 [95% CI, 1.45–2.3]; HFrEF HR 2.51 [95% CI, 2.14–2.95], when compared to non HF patients). Considering EF in its continuous spectrum, an adjusted regression curve analysis found that progressively lower EF was associated with a progressively higher risk for the composite outcome, both in HF and overall AF patients (Figure 1, left and right panel, respectively). Conclusions Over a two-years follow-up, in a large contemporary cohort of European AF patients, HF phenotypes were associated with a progressively higher risk for adverse outcomes. Lower EF values increased the risk of adverse outcomes both in HF patients and overall AF patients, irrespective of HF phenotype status. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): Since the start of EORP, the following companies have supported the programme: Abbott Vascular Int. (2011–2021), Amgen Cardiovascular (2009–2018), AstraZeneca (2014–2021), Bayer (2009–2018), Boehringer Ingelheim (2009–2019), Boston Scientific (2009–2012), The Bristol Myers Squibb and Pfizer Alliance (2011–2016), The Alliance Daiichi Sankyo Europe GmbH and Eli Lilly and Company (2011–2017), Edwards (2016–2019), Gedeon Richter Plc. (2014–2017), Menarini Int. Op. (2009–2012), MSD-Merck &amp; Co. (2011–2014), Novartis Pharma AG (2014–2020), ResMed (2014–2016), Sanofi (2009–2011), SERVIER (2010–2021), and Vifor (2019–2022).

Impaired renal function and mortalities in acute heart failure with different phenotypes.

Impaired renal function (IRF) prevails in patients with acute heart failure. The study aimed to investigate the prevalence of on-admission IRF and its association with short-term and long-term mortalities in patients hospitalized for HF with reduced (HFrEF), mildly reduced (HFmrEF), and preserved (HFpEF) left ventricular ejection fraction (LVEF). Patients hospitalized for acute heart failure were enrolled and stratified by LVEF into three phenotypes as HFpEF (≥50%), HFmrEF (40-49%), and HFrEF (<40%). IRF was defined as an estimated glomerular filtration rate of ≤60mL/min/1.73m2 on admission. National Death Registry was linked for the identification of mortality. Of 2613 patients enrolled, 673 (25.7%) had HFrEF, 367 (14.0%) had HFmrEF, and 1573 (60.1%) had HFpEF, whereas IRF was prevalent among 63.7, 68.6, and 67.5% of them, respectively. IRF significantly correlated with higher long-term mortality in each phenotype of HF. However, IRF was associated with 90-day and 1-year mortality in subjects with HFrEF and HFmrEF, but not HFpEF. After accounting for age, gender, hypertension, diabetes, coronary artery disease, atrial fibrillation, stroke, serum sodium, de novo heart failure, date of enrolment, and systolic blood pressure <90mmHg or use of inotropic agents, IRF remained related to 5-year mortality in patients with HFrEF (hazard ratio and 95% confidence interval: 1.346, 1.034-1.751), HFmrEF (2.210, 1.435-3.404), and HFpEF (1.493, 1.237-1.801). On-admission IRF was independently predictive of long-term mortality in patients hospitalized for HF, irrespective of HF phenotypes. Furthermore, IRF was also associated with short-term mortality in HFrEF and HFmrEF, but not in HFpEF.

Clustering analysis based on automated electrocardiographic measurements to identify prognostically distinct phenotypes in patients hospitalized for heart failure: a retrospective cohort study

Abstract Funding Acknowledgements Type of funding sources: None. Background Heart failure (HF) is a heterogeneous disease with complex structural and electrophysiological derangements of the heart. Attempts to classify HF from the electrophysiological perspective are lacking. Purpose To use electrocardiographic (ECG) data for phenotypic classification of patients with HF. Methods In this retrospective cohort study, all adult patients hospitalized for HF during 2010-2016 at a tertiary center were included. Automated measurements of the first ECG obtained during the index admission were recorded. K-means clustering using premorbid conditions and selected ECG measurements were used to classify the cohort into four mutually exclusive clusters. The primary (all-cause and cardiovascular mortality) and secondary (ventricular arrhythmia (VA)) outcomes were compared between clusters using Cox regression analysis. Results In total, 2849 patients (1363 males, age 75.1 ± 13.4 years) were included. Over a mean follow-up period of 5.37 ± 4.10 years, all-cause and cardiovascular mortality occurred in 2071 (72.7%) and 600 (21.1%) patients respectively, while VA occurred in 110 patients (3.9%). Cluster 1 was characterised by a low heart rate and low ventricular activation time (VAT). Cluster 2 was characterised by old age, low absolute QRS area, and high QTc and QT dispersion. Cluster 3 was characterised by young age, and left ventricular hypertrophy (LVH), and few had history of VA. Cluster 4 was characterised by wide QRS, hypertension, ischaemic heart disease, high VAT, and high absolute T wave area. Cluster 4 had the highest and cluster 1 the lowest risks of all-cause (hazard ratio (HR) 2.96 [1.09, 1.50], p = 0.003; Figure A) and cardiovascular mortality (HR 2.90 [1.15, 2.11], p = 0.004; Figure B). Meanwhile, cluster 2 had the highest risk of VA (HR 2.23 [1.09, 3.85], p = 0.025; Figure C) while clusters 1 and 3 similarly had the lowest risks. Conclusion HF presents with clinically and electrophysiologically distinct phenotypes. Clustering analysis is useful in identifying HF phenotypes which are prognostically significant. Abstract Figures A, B, and C

Association of DNA methylation and transcriptome reveals epigenetic etiology of heart failure.

Epigenetic modifications viz. DNA methylation, histone modifications, and RNA-based alterations play a crucial role in the development of cardiovascular diseases. In this study, we investigated DNA methylation with an aim to reveal the epigenetic etiology of heart failure. Sprague-Dawley rats surviving myocardial infarction developed acute heart failure in 1week. Genomic DNA methylation changes were profiled by bisulfite sequencing, and gene expression levels were analyzed by RNA-seq in failing and sham-operation hearts. A total of 3480 differentially methylated genes in the promoter regions including transcriptional start site and 1934 transcriptome-altered genes were identified in the defected hearts. Common differential genes were enriched by the gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and protein-protein interaction for HF phenotypes. Among these, Mettl11b, HDAC3, HDAC11, ubiquitination-related genes, and snoRNAs are new epigenetic classifiers that had not been reported yet, which may be important regulators in HF.

Deep learning for mortality prediction in patients with a de-novo or worsened heart failure

Abstract Background Heart failure (HF) is a heterogenous syndrome with complex pathophysiology. Biomarkers and clinical risk scores often fail to provide optimal patient-level precision in the prognostic stratification. As utilizing single observational timepoint, they do not capture the entire care pathway with variations in individual patient management. Electronic patient records provide an opportunity to develop new artificial intelligence (AI) strategies for comprehensive prognostic re-stratification reflecting diagnostic and therapeutic management. Purpose We sought to use deep artificial intelligence (AI) and develop an unbiased predictive algorithm for all-cause mortality in a cohort of patients hospitalized with a de novo or worsened HF. Methods In a cohort of 2449 HF patients hospitalized between 2011–2017, we utilized 151 451 patient exams from 422 parameters. They included clinical phenotyping, medication, ECG, laboratory, echocardiography, catheterization data or percutaneous and surgical interventions gathered on a routine clinical basis reflecting standard of care as captured in individual electronic records. The AI model development consisted of 101 iterations of repeated random subsampling splits into balanced training and validation sets. Results AI models yielded performance ranging from 0.83 to 0.89 AUC on the outcome-balanced validation set in predicting all-cause mortality at 30-, 90-, 180-, 360- and 720-day time-limits (Figure 1). The primary endpoint, 1-year mortality prediction model, recorded an 0.85 AUC accuracy. We observed stable model performance across all HF phenotypes: HFpEF 0.83 AUC, HFmrEF 0.85 AUC and HFrEF 0.86 AUC, respectively). Conclusion Our findings present a novel, patient-level, AI-based risk prediction of all-cause mortality in heart failure with a robust accuracy across its phenotypes. This suggests the potential of AI based predictive models in a point-of-care approach to guide clinical risk stratification. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): VZW Cardiovascular Research Center Aalst

Molecular biomarker profile of heart failure with mid-range and preserved ejection fraction in patients with type 2 diabetes

Aim. To study molecular biomarkers in patients with type 2 diabetes (T2D) in combination with heart failure with preserved (HFpEF) and mid-range ejection fraction (HFmrEF) and compare the data obtained with clinical characteristics of myocardial remodeling.Material and methods. The study included 42 patients with T2D (men — 53%, mean age — 60 years) with clinical manifestations of class II HF: 29 patients with HFpEF (group 1) and 13 patients with HFmrEF (group 2). The control group consisted of 13 healthy people, which were comparable in sex and age and had a normal body mass index (BMI). Patients received stable glucose-lowering and optimal drug therapy for HF for 3 months prior to enrollment in the study. Patients with HFpEF and HFmrEF were comparable in clinical and demographic parameters, had glycated hemoglobin (HbA ) of 8,5% and 8,8%, respectively (p&gt;0,05), increased BMI or grade I-II obesity.We studied following biomarkers: NT-proBNP, highly sensitive C-reactive protein (hsCRP), sST2, galectin-3, procollagen type I C-terminal propeptide (PICP), matrix metalloproteinase 9 (MMP-9), tissue inhibitor of metalloproteinase-1 (TIMP-1).Results. Volumetric parameters of the left ventricle (LV),LV mass indexed to growth and NT-proBNP were higher in the group of HFpEF patients (p&lt;0,05 for all). The concentrations of galectin-3, PICP were higher, and the MMP-9/TIMP-1 ratio decreased in patients with T2D compared with the control group (p&lt;0,05 for all). PICP values were higher in patients with HFmrEF compared with patients with HFpEF (106,4 (85,4; 140,4) ng/ml vs 46,8 (12,6; 98,6 ng/ml), respectively, p=0,043). In patients with T2D and HF, a relationship was found between TIMP-1 andLV end-diastolic volume (r=-0,68; p=0,042).Conclusion. Patients with HFmrEF and T2D have higherLV volume and mass, higher concentrations of NT-proBNP and PICP in comparison with patients with HFpEF. The direction of MMP-9/TIMP-1 changes may reflect a decrease in antifibrotic processes. Further prospective studies on large samples using a multiple biomarker model are required in T2D and various HF phenotypes.

Response to beta-blockers and natriuretic peptide level in acute heart failure: analysis of data from the Korean acute heart failure registry.

To investigate the effect of beta-blockers according to NP levels and HF phenotypes because natriuretic peptide (NP) level can be used to risk-stratify HF patients regardless of left ventricular ejection fraction (LVEF). Of 5,625 patients in the Korean acute heart failure registry, we included patients with LVEF and NP levels. HF phenotypes were defined as HF with reduced ejection fraction (HFrEF) (EF ≤ 40%), HF with midrange ejection fraction (HFmrEF) (40% < EF < 50%), and HF with preserved EF (HFpEF) (EF ≥ 50%). Patients were further stratified by NP tertiles. Primary outcome was 5-year all-cause mortality according to beta-blocker use at discharge. Both B-type NP (BNP) (r = -0.279, P < 0.001) and N-terminal pro-BNP (r = -0.186, P < 0.001) levels correlated inversely with LVEF. During a median follow-up duration of 961days, 1560 (35.3%) patients died. In HFrEF, patients taking beta-blockers showed better survival regardless of NP levels. Regarding HFmrEF, there was no mortality difference between those taking and not taking beta-blockers. In HFpEF, beta-blocker use demonstrated lower mortality in those in the 3rd NP tertile (log-rank P = 0.041) but not in those in the 1st and 2nd NP tertiles (log-rank P > 0.05). After adjusting covariates, the use of beta-blockers was associated with a 38%-reduced mortality (hazard ratio: 0.62; 95% confidence interval: 0.39-0.98; P = 0.040) in HFpEF patients in the 3rd NP tertile but not in those in 1st and 2nd tertiles. We confirm that the use of beta-blockers is beneficial in patients with HFrEF. Furthermore, we extend the benefits of beta-blockers to patients with HFpEF and high NP levels. ClinicalTrial.gov identifier: NCT01389843 URL: https://clinicaltrials.gov/ct2/show/NCT01389843.

Characterizing heart failure with preserved and reduced ejection fraction: An imaging and plasma biomarker approach.

IntroductionThe pathophysiology of heart failure with preserved ejection fraction (HFpEF) remains incompletely defined. We aimed to characterize HFpEF compared to heart failure with reduced ejection fraction (HFrEF) and asymptomatic hypertensive or non-hypertensive controls.Materials and methodsProspective, observational study of 234 subjects (HFpEF n = 140; HFrEF n = 46, controls n = 48, age 73±8, males 49%) who underwent echocardiography, cardiovascular magnetic resonance imaging (CMR), plasma biomarker analysis (panel of 22) and 6-minute walk testing (6MWT). The primary end-point was the composite of all-cause mortality and/or HF hospitalization.ResultsCompared to controls both HF groups had lower exercise capacity, lower left ventricular (LV) EF, higher LV filling pressures (E/E’, B-type natriuretic peptide [BNP], left atrial [LA] volumes), more right ventricular (RV) systolic dysfunction, more focal and diffuse fibrosis and higher levels of all plasma markers. LV remodeling (mass/volume) was different between HFpEF (concentric, 0.68±0.16) and HFrEF (eccentric, 0.47±0.15); p<0.0001. Compared to controls, HFpEF was characterized by (mild) reductions in LVEF, more myocardial fibrosis, LA remodeling/dysfunction and RV dysfunction. HFrEF patients had lower LVEF, increased LV volumes, greater burden of focal and diffuse fibrosis, more RV remodeling, lower LAEF and higher LA volumes compared to HFpEF. Inflammatory/fibrotic/renal dysfunction plasma markers were similarly elevated in both HF groups but markers of cardiomyocyte stretch/damage (BNP, pro-BNP, N-terminal pro-atrial natriuretic peptide and troponin-I) were higher in HFrEF compared to HFpEF; p<0.0001. Focal fibrosis was associated with galectin3, GDF-15, MMP-3, MMP-7, MMP-8, BNP, pro-BNP and NTproANP; p<0.05. Diffuse fibrosis was associated with GDF-15, Tenascin-C, MMP-2, MMP-3, MMP-7, BNP, proBNP and NTproANP; p<0.05. Composite event rates (median 1446 days follow-up) did not differ between HFpEF and HFrEF (Log-Rank p = 0.784).ConclusionsHFpEF is a distinct pathophysiological entity compared to age- and sex-matched HFrEF and controls. HFpEF and HFrEF are associated with similar adverse outcomes. Inflammation is common in both HF phenotypes but cardiomyocyte stretch/stress is greater in HFrEF.

Non-cardiac comorbidities and mortality in patients with heart failure with reduced vs. preserved ejection fraction: a study using the Swedish Heart Failure Registry

BackgroundHeart failure (HF) and non-cardiac comorbidities often coexist and are known to have an adverse effect on outcome. However, the prevalence and prognostic impact of non-cardiac comorbidities in patients with HF with reduced ejection fraction (HFrEF) vs. those with preserved (HFpEF) remain inadequately studied.Methods and resultsWe used data from the Swedish Heart Failure Registry from 2000 to 2012. HFrEF was defined as EF < 50% and HFpEF as EF ≥ 50%. Of 31 344 patients available for analysis, 79.3% (n = 24 856) had HFrEF and 20.7% (n = 6 488) HFpEF. The outcome was all-cause mortality. We examined the association between ten non-cardiac comorbidities and mortality and its interaction with EF using adjusted hazard ratio (HR). Stroke, anemia, gout and cancer had a similar impact on mortality in both phenotypes, whereas diabetes (HR 1.57, 95% confidence interval [CI] [1.50–1.65] vs. HR 1.39 95% CI [1.27–1.51], p = 0.0002), renal failure (HR 1.65, 95% CI [1.57–1.73] vs. HR 1.44, 95% CI [1.32–1.57], p = 0.003) and liver disease (HR 2.13, 95% CI [1.83–2.47] vs. HR 1.42, 95% CI [1.09–1.85] p = 0.02) had a higher impact in the HFrEF patients. Moreover, pulmonary disease (HR 1.46, 95% CI [1.40–1.53] vs. HR 1.66 95% CI [1.54–1.80], p = 0.007) was more prominent in the HFpEF patients. Sleep apnea was not associated with worse prognosis in either group. No significant variation was found in the impact over the 12-year study period.ConclusionsNon-cardiac comorbidities contribute significantly but differently to mortality, both in HFrEF and HFpEF. No significant variation was found in the impact over the 12-year study period. These results emphasize the importance of including the management of comorbidities as a part of a standardized heart failure care in both HF phenotypes.

Biomarkers, myocardial fibrosis and co-morbidities in heart failure with preserved ejection fraction: an overview.

The prevalence of heart failure with preserved ejection fraction (HFpEF) is steadily increasing. Its diagnosis remains difficult and controversial and relies mostly on non-invasive echocardiographic detection of left ventricular diastolic dysfunction and elevated filling pressures. The large phenotypic heterogeneity of HFpEF from pathophysiologic al underpinnings to clinical manifestations presents a major obstacle to the development of new therapies targeted towards specific HF phenotypes. Recent studies suggest that natriuretic peptides have the potential to improve the diagnosis of early HFpEF, but they still have significant limitations, and the cut-off points for diagnosis and prognosis in HFpEF remain open to debate. The purpose of this review is to present potential targets of intervention in patients with HFpEF, starting with myocardial fibrosis and methods of its detection. In addition, co-morbidities are discussed as a means to treat HFpEF according to cut-points of biomarkers that are different from usual. Biomarkers and approaches to co-morbidities may be able to tailor therapies according to patients’ pathophysiological needs. Recently, soluble source of tumorigenicity 2 (sST2), growth differentiation factor 15 (GDF-15), galectin-3, and other cardiac markers have emerged, but evidence from large cohorts is still lacking. Furthermore, the field of miRNA is a very promising area of research, and further exploration of miRNA may offer diagnostic and prognostic applications and insight into the pathology, pointing to new phenotype-specific therapeutic targets.

Abstract 20954: Abnormal Liver Function Tests Are Association With Adverse Outcomes in Acute Decompensated Heart Failure in the CARRESS Trial

Introduction: Hepatic congestion with abnormal liver function tests (LFTs), including aspartate aminotransferase (AST), alanine aminotransferase (ALT) and total bilirubin (TBL) complicates acute decompensated heart failure (ADHF). The prognostic implication of abnormal LFTs in ADHF is less studied. Hypothesis: We hypothesized that abnormal LFTs would be associated with unfavorable outcomes in the Cardiorenal Rescue Study in Acute Decompensated Heart Failure (CARRESS) trial. Methods: Cox proportional hazards analysis was performed to assess the association between LFTs (AST, ALT and TBL) at baseline in the CARRESS trial with adverse clinical outcomes, including death, death or HF rehospitalization, and death or any rehospitalization. Correlation analysis was used to assess the relationship between baseline LFTs and BNP, a surrogate of cardiac filling pressures. Results: Among 188 patients (67.9 ± 12.8 years, 25% female), 15.4% died, 35.5% died or had a HF rehospitalization, and 53.8% died or were rehospitalized for any reason. Elevated TBL at baseline was associated with an increased risk of death or rehospitalization for any reason (HR 1.65 per each mg/dL increase in total TBL, 95% CI 1.15-2.38, P=0.007), and a TBL in the upper quartile (&gt; 1.2 mg/dL) was associated with an increased risk of death or HF hospitalization (HR 1.96, 95% CI 1.11-3.45, P=0.02) (Figure). Total bilirubin and BNP at baseline were moderately correlated (r=0.34, P=0.007). There were also no significant associations for AST or ALT with any of the clinical outcomes (P&gt;0.20 for all). Conclusion: Total bilirubin was independently associated with adverse events in ADHF and was also correlated with BNP, a marker of increased cardiac filling pressures. More studies are needed to better define the implications of abnormal LFTs in other HF phenotypes.

Differential Responses of Post-Exercise Recovery of Leg Blood Flow and Oxygen Uptake Kinetics in HFpEF versus HFrEF.

The goals of the current study were to compare leg blood flow, oxygen extraction and oxygen uptake (VO2) after constant load sub-maximal unilateral knee extension (ULKE) exercise in patients with heart failure with reduced ejection fraction (HFrEF) compared to those with preserved ejection fraction (HFpEF). Previously, it has been shown that prolonged whole body VO2 recovery kinetics are directly related to disease severity and all-cause mortality in HFrEF patients. To date, no study has simultaneously measured muscle-specific blood flow and oxygen extraction post exercise recovery kinetics in HFrEF or HFpEF patients; therefore it is unknown if muscle VO2 recovery kinetics, and more specifically, the recovery kinetics of blood flow and oxygen extraction at the level of the muscle, differ between HF phenotypes. Ten older (68±10yrs) HFrEF (n = 5) and HFpEF (n = 5) patients performed sub-maximal (85% of maximal weight lifted during an incremental test) ULKE exercise for 4 minutes. Femoral venous blood flow and venous O2 saturation were measured continuously from the onset of end-exercise, using a novel MRI method, to determine off-kinetics (mean response times, MRT) for leg VO2 and its determinants. HFpEF and HFrEF patients had similar end-exercise leg blood flow (1.1±0.6 vs. 1.2±0.6 L/min, p>0.05), venous saturation (42±12 vs. 41±11%, p>0.05) and VO2 (0.13±0.08 vs. 0.11±0.05 L/min, p>0.05); however HFrEF had significantly delayed recovery MRT for flow (292±135sec. vs 105±63sec., p = 0.004) and VO2 (95±37sec. vs. 47±15sec., p = 0.005) compared to HFpEF. Impaired muscle VO2 recovery kinetics following ULKE exercise differentiated HFrEF from HFpEF patients and suggests distinct underlying pathology and potential therapeutic approaches in these populations.