Urinary Marker Profiles in Heart Failure with Reduced Versus Preserved Ejection Fraction.

BACKGROUND: Recent data suggest different causes of renal dysfunction between heart failure with reduced (HFrEF) versus preserved ejection fraction (HFpEF). We therefore studied a wide range of urinary markers reflecting different nephron segments in heart failure patients. METHODS: In 2070, in chronic heart failure patients, we measured several established and upcoming urinary markers reflecting different nephron segments. RESULTS: Mean age was 70 ± 12 years, 74% was male and 81% (n = 1677) had HFrEF. Mean estimated glomerular filtration rate (eGFR) was lower in patients with HFpEF (56 ± 23 versus 63 ± 23 ml/min/1.73 m2, P = 0.001). Patients with HFpEF had significantly higher values of NGAL (58.1 [24.0-124.8] versus 28.1 [14.6-66.9] µg/gCr, P < 0.001) and KIM-1 (2.28 [1.49-4.37] versus 1.79 [0.85-3.49] µg/gCr, P = 0.001). These differences were more pronounced in patients with an eGFR > 60 ml/min/1.73m2. CONCLUSIONS: HFpEF patients showed more evidence of tubular damage and/or dysfunction compared with HFrEF patients, in particular when glomerular function was preserved.

Differential biomarker expression in heart failure patients with and without mitral regurgitation: Insights from BIOSTAT-CHF.

BACKGROUND: Mitral regurgitation (MR) frequently coexists with heart failure (HF). OBJECTIVES: To better understand potential pathophysiological differences between patients with HF with or without moderate-severe MR, we compared differentially expressed circulating biomarkers between these two groups. METHODS: The Olink Proteomics® Multiplex Cardiovascular (CVD) -II, CVD-III, Immune Response and Oncology-II panels of 363 unique proteins from different pathophysiological domains were used to investigate the biomarker profiles of HF patients from index and validation cohorts of the BIOSTAT-CHF study stratified according to the presence of moderate-to-severe MR or no-mild MR. RESULTS: The index cohort included 888 patients (46%) with moderate-to-severe MR and 1029 (54%) with no-mild MR at baseline. The validation cohort included 522 patients (33%) with moderate-to-severe MR and 1076 (66%) with no-mild MR at baseline. Compared to patients with no-mild MR, those with moderate-to-severe MR had lower body mass index, higher comorbidity burden, signs and symptoms of more severe HF, lower systolic blood pressure, and larger left atrial and ventricular dimensions, in both cohorts. NT-proBNP, CA125, fibroblast growth factor 23 (FGF23) and growth hormone 1 (GH1) were up-regulated, whereas leptin (LEP) was down-regulated in patients with moderate-severe MR versus no-mild MR, in both index and validation cohorts. CONCLUSION: Circulating biomarkers differently expressed in HF patients with moderate-severe MR versus no-mild MR were related to congestion, lipid and mineral metabolism and oxidative stress. These findings may be of value for the development of novel treatment targets in HF patients with MR.

Multiomics Analysis Provides Novel Pathways Related to Progression of Heart Failure.

BACKGROUND: Despite major advances in pharmacological treatment for patients with heart failure, residual mortality remains high. This suggests that important pathways are not yet targeted by current heart failure therapies. OBJECTIVES: We sought integration of genetic, transcriptomic, and proteomic data in a large cohort of patients with heart failure to detect major pathways related to progression of heart failure leading to death. METHODS: We used machine learning methodology based on stacked generalization framework and gradient boosting algorithms, using 54 clinical phenotypes, 403 circulating plasma proteins, 36,046 transcript expression levels in whole blood, and 6 million genomic markers to model all-cause mortality in 2,516 patients with heart failure from the BIOSTAT-CHF (Systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure) study. Results were validated in an independent cohort of 1,738 patients. RESULTS: The mean age of the patients was 70 years (Q1-Q3: 61-78 years), 27% were female, median N-terminal pro-B-type natriuretic peptide was 4,275 ng/L (Q1-Q3: 2,360-8,486 ng/L), and 7% had heart failure with preserved ejection fraction. During a median follow-up of 21 months, 657 (26%) of patients died. The 4 major pathways with a significant association to all-cause mortality were: 1) the PI3K/Akt pathway; 2) the MAPK pathway; 3) the Ras signaling pathway; and 4) epidermal growth factor receptor tyrosine kinase inhibitor resistance. Results were validated in an independent cohort of 1,738 patients. CONCLUSIONS: A systems biology approach integrating genomic, transcriptomic, and proteomic data identified 4 major pathways related to mortality. These pathways are related to decreased activation of the cardioprotective ERBB2 receptor, which can be modified by neuregulin.

Biomarker signature and pathophysiological pathways in patients with chronic heart failure and metabolic syndrome.

AIM: The comorbidities that collectively define metabolic syndrome are common in patients with heart failure. However, the role of metabolic syndrome in the pathophysiology of heart failure is not well understood. We therefore investigated the clinical and biomarker correlates of metabolic syndrome in patients with heart failure. METHODS AND RESULTS: In 1103 patients with heart failure, we compared the biomarker expression using a panel of 363 biomarkers among patients with (n = 468 [42%]) and without (n = 635 [58%]) metabolic syndrome. Subsequently, a pathway overrepresentation analysis was performed to identify key biological pathways. Findings were validated in an independent cohort of 1433 patients with heart failure of whom 615 (43%) had metabolic syndrome. Metabolic syndrome was defined as the presence of three or more of five criteria, including central obesity, elevated serum triglycerides, reduced high-density lipoprotein cholesterol, insulin resistance and hypertension. The most significantly elevated biomarkers in patients with metabolic syndrome were leptin (log2 fold change 0.92, p = 5.85 × 10-21 ), fatty acid-binding protein 4 (log2 fold change 0.61, p = 1.21 × 10-11 ), interleukin-1 receptor antagonist (log2 fold change 0.47, p = 1.95 × 10-13 ), tumour necrosis factor receptor superfamily member 11a (log2 fold change 0.35, p = 4.16 × 10-9 ), and proto-oncogene tyrosine-protein kinase receptor Ret (log2 fold change 0.31, p = 4.87 × 10-9 ). Network analysis identified 10 pathways in the index cohort and 6 in the validation cohort, all related to inflammation. The primary overlapping pathway in both the index and validation cohorts was up-regulation of the natural killer cell-mediated cytotoxicity pathway. CONCLUSION: Metabolic syndrome is highly prevalent in heart failure and is associated with biomarkers and pathways relating to obesity, lipid metabolism and immune responses underlying chronic inflammation.

Albuminuria as a marker of systemic congestion in patients with heart failure.

AIMS: Albuminuria is common in patients with heart failure and associated with worse outcomes. The underlying pathophysiological mechanism of albuminuria in heart failure is still incompletely understood. The association of clinical characteristics and biomarker profile with albuminuria in patients with heart failure with both reduced and preserved ejection fractions were evaluated. METHODS AND RESULTS: Two thousand three hundred and fifteen patients included in the index cohort of BIOSTAT-CHF were evaluated and findings were validated in the independent BIOSTAT-CHF validation cohort (1431 patients). Micro-albuminuria and macro-albuminuria were defined as urinary albumincreatinine ratio (UACR) 30 mg/gCr and 300 mg/gCr in spot urines, respectively. The prevalence of micro- and macro-albuminuria was 35.4 and 10.0, respectively. Patients with albuminuria had more severe heart failure, as indicated by inclusion during admission, higher New York Heart Association functional class, more clinical signs and symptoms of congestion, and higher concentrations of biomarkers related to congestion, such as biologically active adrenomedullin, cancer antigen 125, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) (all P 0.001). The presence of albuminuria was associated with increased risk of mortality and heart failure (re)hospitalization in both cohorts. The strongest independent association with log UACR was found for log NT-proBNP (standardized regression coefficient 0.438, 95 confidence interval 0.350.53, P 0.001). Hierarchical clustering analysis demonstrated that UACR clusters with markers of congestion and less with indices of renal function. The validation cohort yielded similar findings. CONCLUSION: In patients with new-onset or worsening heart failure, albuminuria is consistently associated with clinical, echocardiographic, and circulating biomarkers of congestion.

Pathophysiologic Processes and Novel Biomarkers Associated With Congestion in Heart Failure.

BACKGROUND: Congestion is the main driver behind symptoms of heart failure (HF), but pathophysiology related to congestion remains poorly understood. OBJECTIVES: Using pathway and differential expression analyses, the authors aim to identify biological processes and biomarkers associated with congestion in HF. METHODS: A congestion score (sum of jugular venous pressure, orthopnea, and peripheral edema) was calculated in 1,245 BIOSTAT-CHF patients with acute or worsening HF. Patients with a score ranking in the bottom or top categories of congestion were deemed noncongested (n = 408) and severely congested (n = 142), respectively. Plasma concentrations of 363 unique proteins (Olink Proteomics Multiplex CVD-II, CVD-III, Immune Response and Oncology II panels) were compared between noncongested and severely congested patients. Results were validated in an independent validation cohort of 1,342 HF patients (436 noncongested and 232 severely congested). RESULTS: Differential protein expression analysis showed 107/363 up-regulated and 6/363 down-regulated proteins in patients with congestion compared with those without. FGF-23, FGF-21, CA-125, soluble ST2, GDF-15, FABP4, IL-6, and BNP were the strongest up-regulated proteins (fold change [FC] >1.30, false discovery rate [FDR], P < 0.05). KITLG, EGF, and PON3 were the strongest down-regulated proteins (FC <-1.30, FDR P < 0.05). Pathways most prominently involved in congestion were related to inflammation, endothelial activation, and response to mechanical stimulus. The validation cohort yielded similar findings. CONCLUSIONS: Severe congestion in HF is mainly associated with inflammation, endothelial activation, and mechanical stress. Whether these pathways play a causal role in the onset or progression of congestion remains to be established. The identified biomarkers may become useful for diagnosing and monitoring congestion status.

Clinical implications of low estimated protein intake in patients with heart failure.

BACKGROUND: A higher protein intake has been associated with a higher muscle mass and lower mortality rates in the general population, but data about protein intake and survival in patients with heart failure (HF) are lacking. METHODS: We studied the prevalence, predictors, and clinical outcome of estimated protein intake in 2516 patients from the BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF) index cohort. Protein intake was calculated in spot urine samples using a validated formula [13.9 + 0.907 * body mass index (BMI) (kg/m2 ) + 0.0305 * urinary urea nitrogen level (mg/dL)]. Association with mortality was assessed using multivariable Cox regression models. All findings were validated in an independent cohort. RESULTS: We included 2282 HF patients (mean age 68 ± 12 years and 27% female). Lower estimated protein intake in HF patients was associated with a lower BMI, but with more signs of congestion. Mortality rate in the lowest quartile was 32%, compared with 18% in the highest quartile (P < 0.001). In a multivariable model, lower estimated protein intake was associated with a higher risk of death compared with the highest quartile [hazard ratio (HR) 1.50; 95% confidence interval (CI) 1.03-2.18, P = 0.036 for the lowest quartile and HR 1.46; 95% CI 1.00-2.18, P = 0.049 for the second quartile]. CONCLUSIONS: An estimated lower protein intake was associated with a lower BMI, but signs of congestion were more prevalent. A lower estimated protein intake was independently associated with a higher mortality risk.

The Association of Smoking with Hospitalization and Mortality Differs According to Sex in Patients with Heart Failure Following Myocardial Infarction.

Background: Smoking has been associated with higher morbidity and mortality following myocardial infarction (MI), but reports of the impact on morbidity and mortality for females and elderly patients experiencing MI complicated with left ventricular dysfunction or overt heart failure are limited. Materials and Methods: In an individual patient data meta-analysis of high-risk MI patients, the association of smoking with hospitalizations and death were investigated. Weighted Cox proportional hazard modeling were used to study the risks of smoking on adjudicated endpoints among different sex and age categories. Results: Twenty-eight thousand seven hundred thirty-five patients from the CAPRICORN, EPHESUS, OPTIMAAL, and VALIANT trials were assessed. After weighting, smokers (N = 18,148) were unfrequently women (29.2%) and a minority were above ≥80 years (9.8%). Smoking was significantly more associated with all-cause hospitalizations in women (hazard ratio [HR] 1.24; 95% confidence interval [95% CI] 1.16-1.32) than in men (HR = 1.10; 95% CI 1.05-1.16) resulting in a significant interaction between smoking and sex (p = 0.005). Smoking was predictive of all-cause mortality homogenously across age categories (p for interaction = 0.25) and sex (p for interaction = 0.58). Conclusions: The influence of smoking on morbidity differed according to sex following high-risk MI. The deleterious impact of smoking on hospitalization appeared particularly potent in women, which should further reinforce preventive strategies in females.

Pathophysiological pathways related to high plasma growth differentiation factor 15 concentrations in patients with heart failure.

AIMS: Elevated concentrations of growth differentiation factor 15 (GDF-15) in patients with heart failure (HF) have been consistently associated with worse clinical outcomes, but what disease mechanisms high GDF-15 concentrations represent remains unclear. Here, we aim to identify activated pathophysiological pathways related to elevated GDF-15 expression in patients with HF. METHODS AND RESULTS: In 2279 patients with HF, we measured circulating levels of 363 biomarkers. Then, we performed a pathway over-representation analysis to identify key biological pathways between patients in the highest and lowest GDF-15 concentration quartiles. Data were validated in an independent cohort of 1705 patients with HF. In both cohorts, the strongest up-regulated biomarkers in those with high GDF-15 were fibroblast growth factor 23 (FGF-23), death receptor 5 (TRAIL-R2), WNT1-inducible signalling pathway protein 1 (WISP-1), tumour necrosis factor receptor superfamily member 11a (TNFRSF11A), leucocyte immunoglobulin-like receptor subfamily B member 4 (LILRB4), and trefoil factor 3 (TFF3). Pathway over-representation analysis revealed that high GDF-15 patients had increased activity of pathways related to inflammatory processes, notably positive regulation of chemokine production; response to interleukin-6; tumour necrosis factor and death receptor activity; and positive regulation of T-cell differentiation and inflammatory response. Furthermore, we found pathways involved in regulation of insulin-like growth factor (IGF) receptor signalling and regulatory pathways of tissue, bones, and branching structures. GDF-15 quartiles significantly predicted all-cause mortality and HF hospitalization. CONCLUSION: Patients with HF and high plasma concentrations of GDF-15 are characterized by increased activation of inflammatory pathways and pathways related to IGF-1 regulation and bone/tissue remodelling.

Multimarker profiling identifies protective and harmful immune processes in heart failure: findings from BIOSTAT-CHF.

AIMS: The exploration of novel immunomodulatory interventions to improve outcome in heart failure (HF) is hampered by the complexity/redundancies of inflammatory pathways, which remain poorly understood. We thus aimed to investigate the associations between the activation of diverse immune processes and outcomes in patients with HF. METHODS AND RESULTS: We measured 355 biomarkers in 2022 patients with worsening HF and an independent validation cohort (n = 1691) (BIOSTAT-CHF index and validation cohorts), and classified them according to their functions into biological processes based on the gene ontology classification. Principal component analyses were used to extract weighted scores per process. We investigated the association of these processes with all-cause mortality at 2-year follow-up. The contribution of each biomarker to the weighted score(s) of the processes was used to identify potential therapeutic targets. Mean age was 69 (±12.0) years and 537 (27%) patients were women. We identified 64 unique overrepresented immune-related processes representing 188 of 355 biomarkers. Of these processes, 19 were associated with all-cause mortality (10 positively and 9 negatively). Increased activation of 'T-cell costimulation' and 'response to interferon-gamma/positive regulation of interferon-gamma production' showed the most consistent positive and negative associations with all-cause mortality, respectively, after external validation. Within T-cell costimulation, inducible costimulator ligand, CD28, CD70, and tumour necrosis factor superfamily member-14 were identified as potential therapeutic targets. CONCLUSIONS: We demonstrate the divergent protective and harmful effects of different immune processes in HF and suggest novel therapeutic targets. These findings constitute a rich knowledge base for informing future studies of inflammation in HF.

Additional burden of iron deficiency in heart failure patients beyond the cardio-renal anaemia syndrome: findings from the BIOSTAT-CHF study.

AIMS: Whereas the combination of anaemia and chronic kidney disease (CKD) has been extensively studied in patients with heart failure (HF), the contribution of iron deficiency (ID) to this dysfunctional interplay is unknown. We aimed to assess clinical associates and pathophysiological pathways related to ID in this multimorbid syndrome. METHODS AND RESULTS: We studied 2151 patients with HF from the BIOSTAT-CHF cohort. Patients were stratified based on ID (transferrin saturation <20%), anaemia (World Health Organization definition) and/or CKD (estimated glomerular filtration rate <60 ml/min/1.73 m2 ). Patients were mainly men (73.3%), with a median age of 70.5 (interquartile range 61.4-78.1). ID was more prevalent than CKD and anaemia (63.3%, 47.2% and 35.6% respectively), with highest prevalence in those with concomitant CKD and anaemia (77.5% vs. 59.3%; p < 0.001). There was a considerable overlap in biomarkers and pathways between patients with isolated ID, anaemia or CKD, or in combination, with processes related to immunity, inflammation, cell survival and cancer amongst the common pathways. Key biomarkers shared between syndromes with ID included transferrin receptor, interleukin-6, fibroblast growth factor-23, and bone morphogenetic protein 6. Having ID, either alone or on top of anaemia and/or CKD, was associated with a lower overall summary Kansas City Cardiomyopathy Questionnaire score, an impaired 6-min walk test and increased incidence of hospitalizations and/or mortality in multivariable analyses (all p < 0.05). CONCLUSION: Iron deficiency, CKD and/or anaemia in patients with HF have great overlap in biomarker profiles, suggesting common pathways associated with these syndromes. ID either alone or on top of CKD and anaemia is associated with worse quality of life, exercise capacity and prognosis of patients with worsening HF.

Development and external validation of prognostic models to predict sudden and pump-failure death in patients with HFrEF from PARADIGM-HF and ATMOSPHERE.

BACKGROUND: Sudden death (SD) and pump failure death (PFD) are the two leading causes of death in patients with heart failure and reduced ejection fraction (HFrEF). OBJECTIVE: Identifying patients at higher risk for mode-specific death would allow better targeting of individual patients for relevant device and other therapies. METHODS: We developed models in 7156 patients with HFrEF from the Prospective comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure (PARADIGM-HF) trial, using Fine-Gray regressions counting other deaths as competing risks. The derived models were externally validated in the Aliskiren Trial to Minimize Outcomes in Patients with Heart Failure (ATMOSPHERE) trial. RESULTS: NYHA class and NT-proBNP were independent predictors for both modes of death. The SD model additionally included male sex, Asian or Black race, prior CABG or PCI, cancer history, MI history, treatment with LCZ696 vs. enalapril, QRS duration and ECG left ventricular hypertrophy. While LVEF, ischemic etiology, systolic blood pressure, HF duration, ECG bundle branch block, and serum albumin, chloride and creatinine were included in the PFD model. Model discrimination was good for SD and excellent for PFD with Harrell's C of 0.67 and 0.78 after correction for optimism, respectively. The observed and predicted incidences were similar in each quartile of risk scores at 3 years in each model. The performance of both models remained robust in ATMOSPHERE. CONCLUSION: We developed and validated models which separately predict SD and PFD in patients with HFrEF. These models may help clinicians and patients consider therapies targeted at these modes of death. TRIAL REGISTRATION NUMBER: PARADIGM-HF: ClinicalTrials.gov NCT01035255, ATMOSPHERE: ClinicalTrials.gov NCT00853658.

Machine learning based on biomarker profiles identifies distinct subgroups of heart failure with preserved ejection fraction.

AIMS: The lack of effective therapies for patients with heart failure with preserved ejection fraction (HFpEF) is often ascribed to the heterogeneity of patients with HFpEF. We aimed to identify distinct pathophysiologic clusters of HFpEF based on circulating biomarkers. METHODS AND RESULTS: We performed an unsupervised cluster analysis using 363 biomarkers from 429 patients with HFpEF. Relative differences in expression profiles of the biomarkers between clusters were assessed and used for pathway over-representation analyses. We identified four distinct patient subgroups based on their biomarker profiles: cluster 1 with the highest prevalence of diabetes mellitus and renal disease; cluster 2 with oldest age and frequent age-related comorbidities; cluster 3 with youngest age, largest body size, least symptoms and lowest N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels; and cluster 4 with highest prevalence of ischaemic aetiology, smoking and chronic lung disease, most symptoms, as well as highest NT-proBNP and troponin levels. Over a median follow-up of 21 months, the occurrence of death or heart failure hospitalization was highest in clusters 1 and 4 (62.1% and 62.8%, respectively) and lowest in cluster 3 (25.6%). Pathway over-representation analyses revealed that the biomarker profile of patients in cluster 1 was associated with activation of inflammatory pathways while the biomarker profile of patients in cluster 4 was specifically associated with pathways implicated in cell proliferation regulation and cell survival. CONCLUSION: Unsupervised cluster analysis based on biomarker profiles identified mutually exclusive subgroups of patients with HFpEF with distinct biomarker profiles, clinical characteristics and outcomes, suggesting different underlying pathophysiological pathways.

The value of spot urinary creatinine as a marker of muscle wasting in patients with new-onset or worsening heart failure.

BACKGROUND: Muscle wasting and unintentional weight loss (cachexia) have been associated with worse outcomes in heart failure (HF), but timely identification of these adverse phenomena is difficult. Spot urinary creatinine may be an easily accessible marker to assess muscle loss and cachexia. This study investigated the association of urinary creatinine with body composition changes and outcomes in patients with new-onset or worsening HF (WHF). METHODS: In BIOSTAT-CHF, baseline spot urinary creatinine measurements were available in 2315 patients with new-onset or WHF in an international cohort (index cohort) and a validation cohort of 1431 similar patients from Scotland. RESULTS: Median spot urinary creatinine concentrations were 5.2 [2.7-9.6] mmol/L in the index cohort. Median age was 69 ± 12 years and 73% were men. Lower spot urinary creatinine was associated with older age, lower height and weight, worse renal function, more severe HF, and a higher risk of >5% weight loss from baseline to 9 months (odds ratio = 1.23, 95% CI = 1.09-1.39 per log decrease; P = 0.001). Spot urinary creatinine was associated with Evans criteria of cachexia (OR = 1.26 per log decrease, 95% CI = 1.04-1.49; P = 0.016) and clustered with markers of heart failure severity in hierarchical cluster analyses. Lower urinary creatinine was associated with poorer exercise capacity and quality of life (both P < 0.001) and predicted a higher rate for all-cause mortality [hazard ratio (HR) = 1.27, 95% CI = 1.17-1.38 per log decrease; P < 0.001] and the combined endpoints HF hospitalization or all-cause mortality (HR = 1.23, 95% CI = 1.15-1.31 per log decrease; P < 0.001). Significance was lost after addition of the BIOSTAT risk model. Analyses of the validation cohort yielded similar findings. CONCLUSIONS: Lower spot urinary creatinine is associated with smaller body dimensions, renal dysfunction, and more severe HF in patients with new-onset/WHF. Additionally, lower spot urinary creatinine is associated with an increased risk of weight loss and a poorer exercise capacity/quality of life. Urinary creatinine could therefore be a novel, easily obtainable marker to assess (risk of) muscle wasting in HF patients.

Differences in biomarkers and molecular pathways according to age for patients with HFrEF.

AIMS: Elderly patients with heart failure with reduced ejection fraction (HFrEF) have worse prognosis and less often receive guideline-recommended therapies. We aim to better understand the underlying pathophysiological processes associated with ageing in HFrEF potentially leading to targeted therapies in this vulnerable population. METHODS AND RESULTS: From a panel of 363 cardiovascular biomarkers available in 1611 patients with HFrEF in the BIOSTAT-CHF index cohort and cross-validated in 823 patients in the BIOSTAT-CHF validation cohort, we tested which biomarkers were dysregulated in patients aged >75 vs. <65 years. Second, pathway overrepresentation analyses were performed to identify biological pathways linked to higher plasma concentrations of biomarkers in elderly vs. younger patients. After adjustment, multiple test correction [false discovery rate (FDR) 1%], and cross-validation, 27/363 biomarkers were associated with older age, 22 positively and 5 negatively. The biomarkers that were positively associated with older age were associated with tumour cell regulation, extra-cellular matrix organization, and inflammatory processes, whereas biomarkers negatively associated with older age were associated with pathways that may point to cell proliferation and tumourigenesis. Among the 27 biomarkers, WFDC2 (WAP four-disulphide core domain protein 2)-that broadly functions as a protease inhibitor-was associated with older age and had the strongest association with all outcomes. No protein-by-sex interaction was observed. CONCLUSIONS: In elderly HFrEF patients, pathways associated with extra-cellular matrix organization, inflammatory processes, and tumour cell regulation were activated, while pathways associated with tumour proliferation functions were down-regulated. These findings may help in a better understanding of the ageing processes in HFrEF and identify potential therapeutic targets.

Predictors of sudden cardiac death in high-risk patients following a myocardial infarction.

AIMS: To develop a risk model for sudden cardiac death (SCD) in high-risk acute myocardial infarction (AMI) survivors. METHODS AND RESULTS: Data from the Effect of Carvedilol on Outcome After Myocardial Infarction in Patients With Left Ventricular Dysfunction trial (CAPRICORN) and the Valsartan in Acute Myocardial Infarction Trial (VALIANT) were used to create a SCD risk model (with non-SCD as a competing risk) in 13 202 patients. The risk model was validated in the Eplerenone Post-AMI Heart Failure Efficacy and Survival Study (EPHESUS). The rate of SCD was 3.3 (95% confidence interval 3.0-3.5) per 100 person-years over a median follow-up of 2.0 years. Independent predictors of SCD included age > 70 years; heart rate ≥ 70 bpm; smoking; Killip class III/IV; left ventricular ejection fraction ≤30%; atrial fibrillation; history of prior myocardial infarction, heart failure or diabetes; estimated glomerular filtration rate < 60 mL/min/1.73 m2 ; and no coronary reperfusion or revascularisation therapy for index AMI. The model was well calibrated and showed good discrimination (C-statistic = 0.72), including in the early period after AMI. The observed 2-year event rates increased steeply with each quintile of risk score (1.9%, 3.6%, 6.2%, 9.0%, 13.4%, respectively). CONCLUSION: An easy to use SCD risk score developed from routinely collected clinical variables in patients with heart failure, left ventricular systolic dysfunction or both, early after AMI was superior to left ventricular ejection fraction. This score might be useful in identifying patients for future trials testing treatments to prevent SCD early after AMI.

Concentric vs. eccentric remodelling in heart failure with reduced ejection fraction: clinical characteristics, pathophysiology and response to treatment.

AIMS: Heart failure is traditionally classified by left ventricular ejection fraction (LVEF), rather than by left ventricular (LV) geometry, with guideline-recommended therapies in heart failure with reduced ejection fraction (HFrEF) but not heart failure with preserved ejection fraction (HFpEF). Most patients with HFrEF have eccentric LV hypertrophy, but some have concentric LV hypertrophy. We aimed to compare clinical characteristics, biomarker patterns, and response to treatment of patients with HFrEF and eccentric vs. concentric LV hypertrophy. METHODS AND RESULTS: We performed a retrospective post-hoc analysis including 1015 patients with HFrEF (LVEF <40%) from the multinational observational BIOSTAT-CHF study. LV geometry was classified using two-dimensional echocardiography. Network analysis of 92 biomarkers was used to investigate pathophysiologic pathways. Concentric LV hypertrophy was present in 142 (14%) patients, who were on average older and more likely hypertensive compared to those with eccentric LV hypertrophy. Network analysis revealed that N-terminal pro-B-type natriuretic peptide was an important hub in eccentric hypertrophy, whereas in concentric hypertrophy, tumour necrosis factor receptor 1, urokinase plasminogen activator surface receptor, paraoxonase and P-selectin were central hubs. Up-titration of beta-blockers was associated with a mortality benefit in HFrEF with eccentric but not concentric LV hypertrophy (P-value for interaction ≤0.001). For angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, the hazard ratio for mortality was higher in concentric hypertrophy, but the interaction was not significant. CONCLUSION: Patients with HFrEF with concentric hypertrophy have a clinical and biomarker phenotype that is distinctly different from those with eccentric hypertrophy. Patients with concentric hypertrophy may not experience similar benefit from up.-titration of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers and beta-blockers compared to patients with eccentric hypertrophy.

Sex-Related Procedural Aspects and Complications in CRT Survey II: A Multicenter European Experience in 11,088 Patients.

OBJECTIVES: This study sought to compare sex difference for procedural aspects and complications in the European Society of Cardiology CRT Survey II, exploring whether adverse events were related to the type of CRT device implanted. BACKGROUND: Sex-related differences in procedural aspects and complications in patients undergoing cardiac resynchronization therapy (CRT) implantation has not been explored in a real-life population. METHODS: A post-hoc analysis of procedural data and complications in different sexes and factors associated with events was performed from data collected in the European Society of Cardiology CRT Survey II. RESULTS: Of all patients (n = 11,088) included, 24.3% were women. The mean age (70 years of age) of male and female recipients was similar. Female patients more frequently had an idiopathic cardiomyopathy (67.4% vs. 44.1%) and fewer comorbidities, including atrial fibrillation (34.8% vs. 42.8%), diabetes (29.1% vs. 32.1%), chronic obstructive lung disease (10.3% vs. 12.6%), and renal failure (28.7% vs. 31.9%), compared with men. More women compared with men had a pacemaker (56.6% vs. 46.3%) and much less often an implantable cardioverter-defibrillator (CRT-D) (19.0% vs. 34.7%) implant. Periprocedural event rate was the highest in women with CRT with defibrillator (7.1% vs. 4.8% in men), followed by women with a CRT with pacing (5.5% vs. 4.4% in men). The higher periprocedural event rate in CRT-D women was attributable primarily to the occurrence of pneumothorax (1.4%), coronary sinus dissection (2.1%), and pericardial tamponade (0.3%). The rate of in-hospital major adverse events (6.0%) and complications necessitating reoperation (4.0%) was not different among sex and device type. CONCLUSIONS: Women are more likely to experience adverse procedure-related events during CRT implantation. Thus, preventive strategies should be employed to minimize complication rate.

Iron deficiency in worsening heart failure is associated with reduced estimated protein intake, fluid retention, inflammation, and antiplatelet use.

AIMS: Iron deficiency (ID) is common in heart failure (HF) patients and negatively impacts symptoms and prognosis. The aetiology of ID in HF is largely unknown. We studied determinants and the biomarker profile of ID in a large international HF cohort. METHODS AND RESULTS: We studied 2357 worsening HF patients from the BIOSTAT-CHF cohort. ID was defined as transferrin saturation <20%. Univariable and multivariable logistic regression models were constructed to identify determinants for ID. We measured 92 cardiovascular markers (Olink Cardiovascular III) to establish a biomarker profile of ID. The primary endpoint was the composite of all-cause mortality and first HF rehospitalization. Mean age (±standard deviation) of all patients was 69 ± 12.0 years, 26.1% were female and median N-terminal pro B-type natriuretic peptide levels (+interquartile range) were 4305 (2360-8329) ng/L. Iron deficiency was present in 1453 patients (61.6%), with highest prevalence in females (71.1% vs. 58.3%; P < 0.001). Independent determinants of ID were female sex, lower estimated protein intake, higher heart rate, presence of peripheral oedema and orthopnoea, chronic kidney disease, lower haemoglobin, higher C-reactive protein levels, lower serum albumin levels, and P2Y12 inhibitor use (all P < 0.05). None of these determinants were sex-specific. The biomarker profile of ID largely consisted of pro-inflammatory markers, including paraoxonase 3 (PON3) and tartrate-resistant acid phosphatase type 5. In multivariable Cox proportional hazard regression analyses, ID was associated to worse outcome, independently of predictors of ID (hazard ratio 1.25, 95% confidence interval 1.06-1.46; P = 0.007). CONCLUSION: Our data suggest that the aetiology of ID in worsening HF is complex, multifactorial and seems to consist of a combination of reduced iron uptake (malnutrition, fluid overload), impaired iron storage (inflammation, chronic kidney disease), and iron loss (antiplatelets).