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Aims: Heart failure (HF), a global pandemic affecting millions of individuals, calls for adequate predictive guidance for improved therapy. Congestion, a key factor in HF‐related hospitalizations, further underscores the need for timely interventions. Proactive monitoring of intracardiac pressures, guided by pulmonary artery (PA) pressure, offers opportunities for efficient early‐stage intervention, since haemodynamic congestion precedes clinical symptoms. Methods: The BioMEMS study, a substudy of the MONITOR‐HF trial, proposes a multifaceted approach integrating blood biobank data with traditional and novel HF parameters. Two additional blood samples from 340 active participants in the MONITOR‐HF trial were collected at baseline, 3‐, 6‐, and 12‐month visits and stored for the BioMEMS biobank. The main aims are to identify the relationship between temporal biomarker patterns and PA pressures derived from the CardioMEMS‐HF system, and to identify the biomarker profile(s) associated with the risk of HF events and cardiovascular death. Conclusion: Since the prognostic value of single baseline measurements of biomarkers like N‐terminal pro‐B‐type natriuretic peptide is limited, with the BioMEMS study we advocate a dynamic, serial approach to better capture HF progression. We will substantiate this by relating repeated biomarker measurements to PA pressures. This design rationale presents a comprehensive review on cardiac biomarkers in HF, and aims to contribute valuable insights into personalized HF therapy and patient risk assessment, advancing our ability to address the evolving nature of HF effectively. [ABSTRACT FROM AUTHOR]

Aims: Many European healthcare providers struggle to adopt multidisciplinary, integrated care pathways for people with heart failure (HF) as recommended by the European Society of Cardiology. PRO‐HF (Program to Optimize Heart Failure Patient Pathways) was developed to help clinicians identify strengths, gaps, and shortcomings in their HF pathways and support tailored interventions to optimize pathways and enhance patient care. We report initial findings from baseline assessments of HF pathway characteristics and challenges from 10 hospitals in six European countries (France, Ireland, Portugal, Spain, The Netherlands, and United Kingdom). Methods and results: Baseline assessments were holistic appraisals of full HF services to calibrate current status and development needs and assist management teams in prioritizing improvement projects. Assessments were performed using a comprehensive checklist of measures covering the HF patient journey from diagnosis to ongoing follow‐up. These included a digital survey sent to full HF care teams and one‐to‐one interviews. The digital survey focused on four key areas (HF outpatient clinic; remote patient management; efficient device implantation and inpatient pathways; and network maximization) and 16 dimensions of excellence. Priority areas and themes for action identified in baseline assessments were (i) provision of HF specialist care; (ii) data capture and analysis; (iii) institutional care protocols; (iv) hospital‐wide strategies; and (v) multidisciplinary teams (MDTs). Suboptimal specialist care of emergency inpatients was an issue at all hospitals and prioritized at 8/10. Availability and accessibility of data on patients, activities, and outcomes was an issue at all hospitals and prioritized by 4/10. A lack of clear protocols, templates, and tools for some HF activities created variability in patient care (e.g., HF specialist consultations, diagnostic testing, follow‐up appointments, medications, and device eligibility) and inefficient use of clinician time. This made it difficult to initiate new technologies (e.g., remote patient monitoring) due to the risk of overburdening staff. MDTs were frequently understaffed. Multiple interventions were identified to address gaps and shortcomings that could be tailored to specific needs of individual hospitals (e.g., inpatient pathway optimization, creation/optimization of HF outpatient clinics, development of an HF performance dashboard, enhancement of protocol adherence, streamlining cardiac resynchronisation therapy pathways, and MDT coordination). Conclusions: PRO‐HF provides a valuable opportunity to identify gaps and significant shortcomings in HF pathways in European hospitals. Preliminary findings from hospitals that have initiated suggested changes to address these challenges are encouraging, though longer‐term follow‐up from more hospitals is needed to confirm the impact of PRO‐HF on HF pathway optimization and patient care. [ABSTRACT FROM AUTHOR]

Aims: High left ventricular filling pressure increases left atrial volume and causes myocardial fibrosis, which may decrease with spironolactone. We studied clinical and proteomic characteristics associated with left atrial volume indexed by body surface area (LAVi), and whether LAVi influences the response to spironolactone on biomarker expression and clinical variables. Methods and results: In the HOMAGE trial, where people at risk of heart failure were randomized to spironolactone or control, we analysed 421 participants with available LAVi and 276 proteomic measurements (Olink) at baseline, month 1 and 9 (mean age 73 ± 6 years; women 26%; LAVi 32 ± 9 ml/m2). Circulating proteins associated with LAVi were also assessed in asymptomatic individuals from a population‐based cohort (STANISLAS; n = 1640; mean age 49 ± 14 years; women 51%; LAVi 23 ± 7 ml/m2). In both studies, greater LAVi was significantly associated with greater left ventricular masses and volumes. In HOMAGE, after adjustment and correction for multiple testing, greater LAVi was associated with higher concentrations of matrix metallopeptidase‐2 (MMP‐2), insulin‐like growth factor binding protein‐2 (IGFBP‐2) and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) (false discovery rates [FDR] <0.05). These associations were externally replicated in STANISLAS (all FDR <0.05). Among these biomarkers, spironolactone decreased concentrations of MMP‐2 and NT‐proBNP, regardless of baseline LAVi (pinteraction > 0.10). Spironolactone also significantly reduced LAVi, improved left ventricular ejection fraction, lowered E/e', blood pressure and serum procollagen type I C‐terminal propeptide (PICP) concentration, a collagen synthesis marker, regardless of baseline LAVi (pinteraction > 0.10). Conclusion: In individuals without heart failure, LAVi was associated with MMP‐2, IGFBP‐2 and NT‐proBNP. Spironolactone reduced these biomarker concentrations as well as LAVi and PICP, irrespective of left atrial size. [ABSTRACT FROM AUTHOR]

Background: We hypothesize that Alzheimer's disease (AD)-related pathology may accelerate cognitive decline in patients with cardiovascular diseases. Objective: To investigate the association between blood-based biomarkers of AD, astrocyte activation, and neurodegeneration and cognitive decline. Methods: From the multi-center Heart-Brain study, we included 412 patients with heart failure, carotid occlusive disease or vascular cognitive impairment (age:68.6±9.0) and 128 reference participants (65.7±7.5). Baseline amyloid-β42/40 (Aβ42/40), phosphorylated-tau181 (pTau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) were determined using SiMoA (Quanterix). Memory, attention, language, and executive functioning were evaluated (follow-up:2.1±0.3 years). We applied linear mixed models with terms for biomarker, time and biomarker*time interactions, adjusted for age, sex, education, and site, to assess associations between biomarkers and cognitive decline. Results: Among patients, Aβ42/40 was not associated with cognitive performance at baseline. However, lower Aβ42/40 was associated with steeper decline in global cognition (β±SE:0.04±0.02). Higher pTau181 was associated with worse baseline performance on global cognition (–0.14±0.04) and memory (–0.31±0.09) and with steeper decline in global cognition (–0.07±0.02), memory (–0.09±0.04), attention (–0.05±0.02), and language (–0.10±0.03). Higher GFAP was associated with worse baseline performance on global cognition (–0.22±0.05), memory (–0.43±0.10), attention (–0.14±0.06), language (–0.15±0.05), and executive functioning (–0.15±0.05) and steeper decline in global cognition (–0.05±0.01). Higher NfL was associated with worse baseline performance on global cognition (–0.16±0.04), memory (–0.28±0.09), attention (–0.20±0.06), and executive functioning (-0.10±0.04), but was not associated with performance over time. In reference participants, no associations were found. Conclusions: Our findings suggest that blood-based biomarkers of AD-related pathology predict cognitive decline in patients with cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Introduction: Heart failure is a serious burden on health care systems due to frequent hospital admissions. Early recognition of outpatients at risk for clinical deterioration could prevent hospitalization. Still, the role of signs and symptoms in monitoring heart failure patients is not clear. The heart failure coach is a web-based telemonitoring application consisting of a 9-item questionnaire assessment of heart failure signs and symptoms and developed to identify outpatients at risk for clinical deterioration. If deterioration was suspected, patients were contacted by a heart failure nurse for further evaluation. Methods: Heart failure coach questionnaires completed between 2015 and 2018 were collected from 287 patients, completing 18,176 questionnaires. Adverse events were defined as all-cause mortality, heart failure- or cardiac-related hospital admission or emergency cardiac care visits within 30 days after completion of each questionnaire. Multilevel logistic regression analyses were performed to assess the association between the heart failure coach questionnaire items and the odds of an adverse event. Results: No association between dyspnea and adverse events was observed (odds ratio 1.02, 95% confidence interval 0.79–1.30). Peripheral edema (odds ratio 2.21, 95% confidence interval 1.58–3.11), persistent chest pain (odds 2.06, 95% confidence interval 1.19–3.58), anxiety about heart failure (odds ratio 2.12, 95% confidence interval 1.44–3.13), and extensive struggle to perform daily activities (odds ratio 2.23, 95% confidence interval 1.38–3.62) were significantly associated with adverse outcome. Discussion: Regular assessment of more than the classical signs and symptoms may be helpful to identify heart failure patients at risk for clinical deterioration and should be an integrated part of heart failure telemonitoring programs. [ABSTRACT FROM AUTHOR]

Summary: Background: Heart failure is a severe condition and telemedicine can improve the care of heart failure. Many patients are unable to use telemedicine applications due to visual impairment and limited health-related literacy. Avatar technology might help to overcome these limitations. Methods: A telemedicine application was combined with a nurse avatar and offered to heart failure outpatients for 3 months. System usability and patient satisfaction were evaluated monthly by the system usability score (maximum score=100) and the patient satisfaction scale (maximum score=50). Results: In total, 37 heart failure patients were enrolled. The mean system usability score after 1 month was 73 (standard deviation=24) and 72 (standard deviation=10) after 3 months of follow-up, which was not significantly different (p = 0.40). The mean patient satisfaction scale after 1 month was 42 (standard deviation=5) and 39 (standard deviation=8) after 3 months, which was not significantly different (p = 0.10). Conclusion: A nurse look-a-like avatar integrated into a telemedicine application was positively assessed by heart failure patients. Future studies are warranted to clarify the role of avatar technology in telemedicine. [ABSTRACT FROM AUTHOR]

Aims: Diagnosis of heart failure with preserved ejection fraction (HFpEF) can be challenging. This study aimed to evaluate the potential of a webtool to enhance the scoring accuracy when applying the complex HFA‐PEFF and H2FPEF algorithms, which are commonly used for diagnosing HFpEF. Methods and results: We developed an online tool, the HFpEF calculator, that enables the automatic calculation of current HFpEF algorithms. We assessed the accuracy of manual vs. automatic scoring, defined as the percentage of correct scores, in a cohort of cardiologists with varying clinical experience. Cardiologists scored eight online clinical cases using a triple cross‐over design (i.e. two manual–two automatic–two manual–two automatic). Data were analysed in study completers (n = 55, 29% heart failure specialists, 42% general cardiologists, and 29% cardiology residents). Manually calculated scores were correct in 50% (HFA‐PEFF: 50% [50–75]; H2FPEF: 50% [38–50]). Correct scoring improved to 100% using the HFpEF calculator (HFA‐PEFF: 100% [88–100], P < 0.001; H2FPEF: 100% [75–100], P < 0.001). Time spent on clinical cases was similar between scoring methods (±4 min). When corrections for faulty algorithm scores were displayed, cardiologists changed their diagnostic decision in up to 67% of cases. At least 67% of cardiologists preferred using the online tool for future cases in clinical practice. Conclusions: Manual calculation of HFpEF diagnostic algorithms is often inaccurate. Using an automated webtool to calculate HFpEF algorithms significantly improved correct scoring. This new approach may impact the eventual diagnostic decision in up to two‐thirds of cases, supporting its routine use in clinical practice. [ABSTRACT FROM AUTHOR]

Background: Collagen cross-linking is a fundamental process in dilated cardiomyopathy (DCM) and occurs when collagen deposition exceeds degradation, leading to impaired prognosis. This study investigated the associations of collagen-metabolism biomarkers with left ventricular function and prognosis in DCM. Methods: DCM patients who underwent endomyocardial biopsy, blood sampling, and cardiac MRI were included. The primary endpoint included death, heart failure hospitalization, or life-threatening arrhythmias, with a follow-up of 6 years (5–8). Results: In total, 209 DCM patients were included (aged 54 ± 13 years, 65% male). No associations were observed between collagen volume fraction, circulating carboxy-terminal propeptide of procollagen type-I (PICP), or collagen type I carboxy-terminal telopeptide [CITP] and matrix metalloproteinase [MMP]-1 ratio and cardiac function parameters. However, CITP:MMP-1 was significantly correlated with global longitudinal strain (GLS) in the total study sample (R = −0.40, p < 0.0001; lower CITP:MMP-1 ratio was associated with impaired GLS), with even stronger correlations in patients with LVEF > 40% (R = −0.70, p < 0.0001). Forty-seven (22%) patients reached the primary endpoint. Higher MMP-1 levels were associated with a worse outcome, even after adjustment for clinical and imaging predictors (1.026, 95% CI 1.002–1.051, p = 0.037), but CITP and CITP:MMP-1 were not. Combining MMP-1 and PICP improved the goodness-of-fit (LHR36.67, p = 0.004). Conclusion: The degree of myocardial cross-linking (CITP:MMP-1) is associated with myocardial longitudinal contraction, and MMP-1 is an independent predictor of outcome in DCM patients. [ABSTRACT FROM AUTHOR]

Multiple landmark trials have helped to advance the treatment of heart failure with reduced ejection fraction (HFrEF) significantly over the past decade. These trials have led to the introduction of four main drug classes into the 2021 ESC guideline, namely angiotensin-receptor neprilysin inhibitors/angiotensin-converting-enzyme inhibitors, beta-blockers, mineralocorticoid receptor antagonists, and sodium-glucose cotransporter-2 inhibitors. The life-saving effect of these therapies has been shown to be additive and becomes apparent within weeks, which is why maximally tolerated or target doses of all drug classes should be strived for as quickly as possible. Recent evidence, such as the STRONG-HF trial, demonstrated that rapid drug implementation and up-titration is superior to the traditional and more gradual step-by-step approach where valuable time is lost to up-titration. Accordingly, multiple rapid drug implementation and sequencing strategies have been proposed to significantly reduce the time needed for the titration process. Such strategies are urgently needed since previous large-scale registries have shown that guideline-directed medical therapy (GDMT) implementation is a challenge. This challenge is reflected by generally low adherence rates, which can be attributed to factors considering the patient, health care system, and local hospital/health care provider. This review of the four medication classes used to treat HFrEF seeks to present a thorough overview of the data supporting current GDMT, discuss the obstacles to GDMT implementation and up-titration, and identify multiple sequencing strategies that could improve GDMT adherence. Sequencing strategies for GDMT implementation. GDMT: guideline-directed medical therapy; ACEi: angiotensin-converting enzyme inhibitor; ARB: Angiotensin II receptor blocker; ARNi: angiotensin receptor–neprilysin inhibitor; BB: beta-blocker; MRA: mineralocorticoid receptor antagonist; SGLT2i: sodium–glucose co-transporter 2 inhibitor [ABSTRACT FROM AUTHOR]

Aim: An echocardiographic algorithm derived by machine learning (e′VM) characterizes pre‐clinical individuals with different cardiac structure and function, biomarkers, and long‐term risk of heart failure (HF). Our aim was the external validation of the e′VM algorithm and to explore whether it may identify subgroups who benefit from spironolactone. Methods and results: The HOMAGE (Heart OMics in AGEing) trial enrolled participants at high risk of developing HF randomly assigned to spironolactone or placebo over 9 months. The e′VM algorithm was applied to 416 participants (mean age 74 ± 7 years, 25% women) with available echocardiographic variables (i.e. e′ mean, left ventricular end‐diastolic volume and mass indexed by body surface area [LVMi]). The effects of spironolactone on changes in echocardiographic and biomarker variables were assessed across e′VM phenotypes. A majority (>80%) had either a 'diastolic changes' (D), or 'diastolic changes with structural remodelling' (D/S) phenotype. The D/S phenotype had the highest LVMi, left atrial volume, E/e', natriuretic peptide and troponin levels (all p < 0.05). Spironolactone significantly reduced E/e' and B‐type natriuretic peptide (BNP) levels in the D/S phenotype (p < 0.01), but not in other phenotypes (p > 0.10; pinteraction <0.05 for both). These interactions were not observed when considering guideline‐recommended echocardiographic structural and functional abnormalities. The magnitude of effects of spironolactone on LVMi, left atrial volume and a type I collagen marker was numerically higher in the D/S phenotype than the D phenotype but the interaction test did not reach significance. Conclusions: In the HOMAGE trial, the e′VM algorithm identified echocardiographic phenotypes with distinct responses to spironolactone as assessed by changes in E/e' and BNP. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to assess heart failure (HF) treatment in patients with and without obesity in a large contemporary real‐world Western European cohort. Methods: Patients with a left ventricular ejection fraction (LVEF) <50% and available information on body mass index (BMI) were selected from the CHECK‐HF registry. The CHECK‐HF registry included chronic HF patients in the period between 2013 and 2016 in 34 Dutch outpatient clinics. Patients were divided into BMI categories. Differences in HF medical treatment were analysed, and multivariable logistic regression analysis (dichotomized as BMI <30 kg/m2 and ≥30 kg/m2) was performed. Results: Seven thousand six hundred seventy‐one patients were included, 1284 (16.7%) had a BMI ≥30 kg/m2, and 618 (8.1%) had a BMI ≥35 kg/m2. Median BMI was 26.4 kg/m2. Patients with obesity were younger and had a higher rate of comorbidities such as diabetes mellitus, hypertension and obstructive sleep apnoea (OSAS). Prescription rates of guideline‐directed medical therapy (GDMT) increased significantly with BMI. The differences were most pronounced for mineralocorticoid receptor antagonists (MRAs) and diuretics. Patients with obesity more often received the guideline‐recommended target dose. In multivariable logistic regression, obesity was significantly associated with a higher likelihood of receiving ≥100% of the guideline‐recommended target dose of beta‐blockers (OR 1.34, 95% CI 1.10–1.62), renin–angiotensin system (RAS)‐inhibitors (OR 1.34, 95% CI 1.15–1.57) and MRAs (OR 1.40, 95% CI 1.04–1.87). Conclusions: Guideline‐recommended HF drugs are more frequently prescribed and at a higher dose in patients with obesity as compared to HF patients without obesity. [ABSTRACT FROM AUTHOR]

Aims: In order to understand how sex differences impact the generalizability of randomized clinical trials (RCTs) in patients with heart failure (HF) and reduced ejection fraction (HFrEF), we sought to compare clinical characteristics and clinical outcomes between RCTs and HF observational registries stratified by sex. Methods and results: Data from two HF registries and five HFrEF RCTs were used to create three subpopulations: one RCT population (n = 16 917; 21.7% females), registry patients eligible for RCT inclusion (n = 26 104; 31.8% females), and registry patients ineligible for RCT inclusion (n = 20 810; 30.2% females). Clinical endpoints included all‐cause mortality, cardiovascular mortality, and first HF hospitalization at 1 year. Males and females were equally eligible for trial enrolment (56.9% of females and 55.1% of males in the registries). One‐year mortality rates were 5.6%, 14.0%, and 28.6% for females and 6.9%, 10.7%, and 24.6% for males in the RCT, RCT‐eligible, and RCT‐ineligible groups, respectively. After adjusting for 11 HF prognostic variables, RCT females showed higher survival compared to RCT‐eligible females (standardized mortality ratio [SMR] 0.72; 95% confidence interval [CI] 0.62–0.83), while RCT males showed higher adjusted mortality rates compared to RCT‐eligible males (SMR 1.16; 95% CI 1.09–1.24). Similar results were also found for cardiovascular mortality (SMR 0.89; 95% CI 0.76–1.03 for females, SMR 1.43; 95% CI 1.33–1.53 for males). Conclusion: Generalizability of HFrEF RCTs differed substantially between the sexes, with females having lower trial participation and female trial participants having lower mortality rates compared to similar females in the registries, while males had higher than expected cardiovascular mortality rates in RCTs compared to similar males in registries. [ABSTRACT FROM AUTHOR]

Aims: Implementation of guideline-recommended pharmacological treatment in heart failure (HF) patients remains challenging. In 2021, the European Heart Failure Association (HFA) published a consensus document in which patient profiles were created based on readily available patient characteristics and suggested that treatment adjusted to patient profile may result in better individualized treatment and improved guideline adherence. This study aimed to assess the distribution of these patient profiles and their treatment in a large real-world chronic HF cohort. Methods and results: The HFA combined categories of heart rate, blood pressure, presence of atrial fibrillation, chronic kidney disease, and hyperkalemia into eleven phenotypic patient profiles. A total of 4,455 patients with chronic HF and a left ventricular ejection fraction ≤40% with complete information on all characteristics were distributed over these profiles. In total, 1,640 patients (36.8%) could be classified into one of the HFA profiles. Three of these each comprised >5% of the population and consisted of patients with a heart rate >60 beats per minute with normal blood pressure (>90/60 mmHg) and no hyperkalemia. Conclusion: Nearly forty percent of a real-world chronic HF population could be distributed over the eleven patient profiles as suggested by the HFA. Phenotypespecific treatment recommendations are clinically relevant and important to further improve guideline implementation. [ABSTRACT FROM AUTHOR]