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Objective: Heart failure (HF) pathophysiology in patients with obesity may be distinct. To study these features, we identified obesity‐related biomarkers from 4210 circulating proteins in patients with HF with reduced ejection fraction (HFrEF) and examined associations of these proteins with HF prognosis and biological mechanisms. Methods: In 373 patients with trimonthly blood sampling during a median follow‐up of 2.1 (25th–75th percentile: 1.1–2.6) years, we applied an aptamer‐based multiplex approach measuring 4210 proteins in baseline samples and the last two samples before study end. Associations between obesity (BMI > 30 kg/m2) and baseline protein levels were analyzed. Subsequently, associations of serially measured obesity‐related proteins with biological mechanisms and the primary endpoint (PEP; composite of cardiovascular mortality, HF hospitalization, left ventricular assist device implantation, and heart transplantation) were examined. Results: Obesity was identified in 26% (96/373) of patients. A total of 30% (112/373) experienced a PEP (with obesity: 26% [25/96] vs. without obesity: 31% [87/277]). A total of 141/4210 proteins were linked to obesity, reflecting mechanisms of neuron projection development, cell adhesion, and muscle cell migration. A total of 50/141 proteins were associated with the PEP, of which 12 proteins related to atherosclerosis or hypertrophy provided prognostic information beyond clinical characteristics, N‐terminal pro‐B‐type natriuretic peptide, and high‐sensitivity troponin T. Conclusions: Patients with HFrEF and obesity show distinct proteomic profiles compared to patients with HFrEF without obesity. Obesity‐related proteins are independently associated with HF outcome. These proteins carry potential to improve management of obesity‐related HF and could be leads for future research. [ABSTRACT FROM AUTHOR]

Circulating proteins may provide insights into the varying biological mechanisms involved in heart failure (HF) with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF). We aimed to identify specific proteomic patterns for HF, by comparing proteomic profiles across the ejection fraction spectrum. We investigated 4210 circulating proteins in 739 patients with normal (Stage A/Healthy) or elevated (Stage B) filling pressures, HFpEF, or ischemic HFrEF (iHFrEF). We found 2122 differentially expressed proteins between iHFrEF-Stage A/Healthy, 1462 between iHFrEF–HFpEF and 52 between HFpEF-Stage A/Healthy. Of these 52 proteins, 50 were also found in iHFrEF vs. Stage A/Healthy, leaving SLITRK6 and NELL2 expressed in lower levels only in HFpEF. Moreover, 108 proteins, linked to regulation of cell fate commitment, differed only between iHFrEF–HFpEF. Proteomics across the HF spectrum reveals overlap in differentially expressed proteins compared to stage A/Healthy. Multiple proteins are unique for distinguishing iHFrEF from HFpEF, supporting the capacity of proteomics to discern between these conditions. [ABSTRACT FROM AUTHOR]

Aims: This study aims to provide insight into sex‐specific cardiovascular protein profiles and their associations with adverse outcomes, which may contribute to a better understanding of heart failure (HF) pathophysiology and the optimal use of circulating proteins for prognostication in women and men. Methods and results: In 250 stable patients with HF with reduced ejection fraction (HFrEF), we performed trimonthly blood sampling (median follow‐up: 26 [17–30] months). We selected all baseline samples and two samples closest to the primary endpoint (PEP; composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization) or one sample closest to censoring and applied the Olink Cardiovascular III panel. We used linear regression to study sex‐based differences in baseline levels and joint models to study differences in the prognostic value of serially measured proteins. In 66 women and 184 men (mean age of 66 and 67 years, respectively), 21% and 28% reached the PEP, respectively. Mean baseline levels of fatty acid‐binding protein 4, secretoglobin family 3A member 2, paraoxonase 3, and trefoil factor 3 were higher in women (Pinteraction: 0.001, 0.007, 0.018, and 0.049, respectively), while matrix metalloproteinase‐3, interleukin 1 receptor‐like 1, and myoglobin were higher in men (Pinteraction: <0.001, 0.001, and 0.049, respectively), independent of clinical characteristics. No significant differences between sexes were observed in the longitudinal associations of proteins with the PEP. Only peptidoglycan recognition protein 1 showed a suggestive interaction with sex for the primary outcome (Pinteraction = 0.028), without multiple testing correction, and was more strongly associated with adverse outcome in women {hazard ratio [HR] 3.03 [95% confidence interval (CI), 1.42 to 6.68], P = 0.008} compared with men [HR 1.18 (95% CI, 0.84 to 1.66), P = 0.347]. Conclusions: Although multiple cardiovascular‐related proteins show sex differences at baseline, temporal associations with the adverse outcome do not differ between women and men with HFrEF. [ABSTRACT FROM AUTHOR]

Aims: Heart failure (HF) is a chronic and progressive syndrome associated with a poor prognosis. While it may seem intuitive that the risk of adverse outcomes varies across the different stages of HF, an overview of these risks is lacking. This study aims to determine the risk of all‐cause mortality and HF hospitalizations associated with new‐onset HF, chronic HF (CHF), worsening HF (WHF), and advanced HF. Methods and results: We performed a systematic review of observational studies from 2012 to 2022 using five different databases. The primary outcomes were 30‐day and 1‐year all‐cause mortality, as well as 1‐year HF hospitalization. Studies were pooled using random effects meta‐analysis, and mixed‐effects meta‐regression was used to compare the different HF groups. Among the 15 759 studies screened, 66 were included representing 862 046 HF patients. Pooled 30‐day mortality rates did not reveal a significant distinction between hospital‐admitted patients, with rates of 10.13% for new‐onset HF and 8.11% for WHF (p = 0.10). However, the 1‐year mortality risk differed and increased stepwise from CHF to advanced HF, with a rate of 8.47% (95% confidence interval [CI] 7.24–9.89) for CHF, 21.15% (95% CI 17.78–24.95) for new‐onset HF, 26.84% (95% CI 23.74–30.19) for WHF, and 29.74% (95% CI 24.15–36.10) for advanced HF. Readmission rates for HF at 1 year followed a similar trend. Conclusions: Our meta‐analysis of observational studies confirms the different risk for adverse outcomes across the distinct HF stages. Moreover, it emphasizes the negative prognostic value of WHF as the first progressive stage from CHF towards advanced HF. [ABSTRACT FROM AUTHOR]

Aim Methods and results Conclusions Senescence is a major risk factor for heart failure (HF), and insulin‐like growth factor‐binding protein‐7 (IGFBP7) has been identified as an important senescence‐inducing factor. The aim of this study was to examine the value of baseline and repeat IGFBP7 measurements in predicting future HF among community‐dwelling Dutch adults from the Prevention of Renal and Vascular End‐stage Disease (PREVEND) study.Individuals without prevalent HF who attended PREVEND visits 2 and 4 median of 5.1 years apart (25th–75th percentile, 4.9–5.2) with measurements of IGFBP7 were included. We used Cox proportional hazards models to investigate the association between IGFBP7 and HF incidence. A total of 6125 participants attending visit 2 (mean ± standard deviation [SD] age 53.1 ± 12.2 years; 3151 [51.4%] men) were followed for a median of 8.4 (7.8–8.9) years, and 194 participants (3.2%) developed incident HF. Median baseline IGFBP7 concentration was 87.0 (75.1–97.3) ng/ml, and baseline IGFBP7 levels were significantly associated with risk for incident HF (HF risk factors adjusted hazard ratio [HR] per 1 SD change in log‐transformed IGFBP7: 1.22, 95% confidence interval [CI] 1.03–1.46). Baseline IGFBP7 was also significantly associated with incident HF in individuals with N‐terminal pro‐B‐type natriuretic peptide <125 ng/L. Among 3879 participants attending both visits 2 and 4 (mean ± SD age 57.5 ± 11.3 years; 1952 [50.3%] men), 93 individuals developed HF (after visit 4) during a median follow‐up of 3.2 (2.8–3.9) years. Median increase in IGFBP7 concentration between visits was 0.68 (−7.09 to 8.36) ng/ml, and changes in IGFBP7 levels were significantly associated with risk for incident HF (HF risk factors adjusted HR per 1 SD change in log‐transformed IGFBP7: 1.68, 95% CI 1.19–2.36).Both baseline as well as repeat IGFBP7 measurements provide information about the risk of developing HF. [ABSTRACT FROM AUTHOR]

Aims: There is a paucity of data on the performance of angiography-derived vessel fractional flow reserve (vFFR) in coronary artery lesions of patients presenting with non-ST-segment elevation acute coronary syndrome (NSTE-ACS). Optical coherence tomography (OCT) allows for visualization of lumen dimensions and plaque integrity with high resolution. The aim of the present study was to define the association between vFFR and OCT findings in intermediate coronary artery lesions in patients presenting with NSTE-ACS., Methods and Results: The FAST OCT study was a prospective, multicenter, single-arm study. Patients presenting with NSTE-ACS with intermediate to severe coronary artery stenosis in one or multiple vessels with TIMI 3 flow suitable for OCT imaging were eligible. Complete pre-procedural vFFR and OCT data were available in 226 vessels (in 188 patients). A significant association between vFFR and minimal lumen area (MLA) was observed, showing an average decrease of 20.4% (95% CI -23.9% - -16.7%) in MLA per 0.10 decrease in vFFR (adjusted p<0.001). vFFR≤0.80 showed a sensitivity of 56.7% and specificity of 92.5% to detect MLA≤2.5 mm². Conversely, vFFR had a poor to moderate discriminative ability to detect plaque instability (sensitivity, 46.9% specificity 71.6%)., Conclusions: In patients with NSTE-ACS, vFFR is significantly associated with OCT-detected MLA and a vFFR≤0.80 is highly predictive for the presence of significant disease based on OCT. Conversely, the sensitivity of vFFR≤0.80 to detect OCT-assessed significant disease was low, indicating that the presence of significant OCT findings cannot be ruled out based on a negative vFFR., Clinicaltrials.gov Id: NCT04683133., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Paravalvular leakage (PVL) and conduction disorders that require permanent pacemaker implantation (PPI) remain clinically relevant challenges after transcatheter aortic valve implantation (TAVI). Computed tomography-based simulations may predict the risk of significant PVL and PPI., Aims: To evaluate the feasibility and accuracy of preprocedural computer simulation with FEops HEARTguide™ to predict >trace PVL and PPI after TAVI with the self-expanding supra-annular ACURATE Neo2 transcatheter heart valve., Methods: Prospective multicenter observational study that included consecutive patients undergoing TAVI with an ACURATE Neo2 valve. Computer simulations were performed before the TAVI procedure as part of the preprocedural planning. Follow-up period for PPI and PVL was 30 days., Results: Sixty-five patients were included (median age 81 years (25th-75th percentile 77-84.5)). New left bundle branch block occurred in five patients (7.7%) and PPI in two patients (3%). Contact pressure index (CPI) was similar for patients with vs without new conduction disorders. Patients with PPI had numerically higher CPI than those without PPI (median CPI 20.0% (25th-75th percentile 15.0-25.0) vs. 13.0% (25th-75th percentile 5.5-18), p = 0.27). More than trace PVL occurred in 30%. Median PVL was significantly lower in patients with none-trace PVL (3.2 mL/s [25th-75th percentile 2.2-5.0]), compared to mild PVL (5.2 mL/s [25th-75th percentile 3.2-10.3]) and moderate PVL (12.6 mL/s [25th-75th percentile 3.9-21.3])(p = 0.036). A simulated PVL-cutoff of 9.65 mL/s identified patients with >trace PVL (AUC 0.70 (95% CI 0.55-0.85), sensitivity 42%, specificity 95%)., Conclusion: In our study FEops HEARTguide™ simulations identified patients at risk for >trace PVL with ACURATE Neo2 TAVI but not for PPI., (© 2024 The Author(s). Catheterization and Cardiovascular Interventions published by Wiley Periodicals LLC.)

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., (© 2024 The Author(s). European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: We aimed to identify patients with subphenotypes of postacute coronary syndrome (ACS) using repeated measurements of high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, high-sensitivity C-reactive protein, and growth differentiation factor 15 in the year after the index admission, and to investigate their association with long-term mortality risk., Methods and Results: BIOMArCS (BIOMarker Study to Identify the Acute Risk of a Coronary Syndrome) was an observational study of patients with ACS, who underwent high-frequency blood sampling for 1 year. Biomarkers were measured in a median of 16 repeated samples per individual. Cluster analysis was performed to identify biomarker-based subphenotypes in 723 patients without a repeat ACS in the first year. Patients with a repeat ACS (N=36) were considered a separate cluster. Differences in all-cause death were evaluated using accelerated failure time models (median follow-up, 9.1 years; 141 deaths). Three biomarker-based clusters were identified: cluster 1 showed low and stable biomarker concentrations, cluster 2 had elevated concentrations that subsequently decreased, and cluster 3 showed persistently elevated concentrations. The temporal biomarker patterns of patients in cluster 3 were similar to those with a repeat ACS during the first year. Clusters 1 and 2 had a similar and favorable long-term mortality risk. Cluster 3 had the highest mortality risk. The adjusted survival time ratio was 0.64 (95% CI, 0.44-0.93; P =0.018) compared with cluster 1, and 0.71 (95% CI, 0.39-1.32; P =0.281) compared with patients with a repeat ACS., Conclusions: Patients with subphenotypes of post-ACS with different all-cause mortality risks during long-term follow-up can be identified on the basis of repeatedly measured cardiovascular biomarkers. Patients with persistently elevated biomarkers have the worst outcomes, regardless of whether they experienced a repeat ACS in the first year.