Risk Stratification In Heart Failure Research Articles

IGF-1 levels in the general population, heart failure patients, and individuals with acromegaly: differences and projections from meta-analyses—a dual perspective

BackgroundThe complex relationship between insulin-like growth factor 1 (IGF-1) levels and heart failure (HF) is not fully understood, particularly across different populations and conditions. This meta-analysis aims to elucidate the dual perspectives of IGF-1 levels in the general population, HF patients, and individuals with treatment-naïve acromegaly, highlighting IGF-1 as a biomarker and potential therapeutic target in HF management.MethodsStudies were searched across multiple electronic databases up to January 2024 and independently identified by reviewers. The outcomes were analyzed using RevMan 5.4 and STATA 15.ResultsA total of 25 articles were ultimately included in the analysis. Six studies compared IGF-1 levels between HF patients and non-HF controls, revealing significantly lower IGF-1 levels in HF patients (mean difference −20.93; 95% CI −37.88 to −3.97; p = 0.02). This reduction was consistent across various HF subtypes and severities. In addition, individuals with intermediate IGF-1 levels had a lower risk of developing HF [risk ratio (RR) 0.78; 95% CI 0.74–0.83; p < 0.01] and HF-related mortality (RR 0.98; 95% CI 0.97, 0.99; p < 0.01) compared to those with low IGF-1 levels, suggesting a protective role for maintaining adequate IGF-1 levels. Conversely, treatment-naïve acromegaly patients, characterized by excessively high IGF-1 levels, showed a significantly higher incidence of both diastolic HF [odds ratio (OR) 9.08; 95% CI 6.20–13.29; p < 0.01] and systolic HF (OR 13.1; 95% CI 6.64–25.84; p < 0.01), implicating supraphysiological IGF-1 levels in adverse cardiac outcomes.ConclusionsOur meta-analysis highlights the complex interplay between IGF-1 levels and HF. We found that reduced IGF-1 levels are commonly observed in HF patients and are associated with an increased risk of HF and higher HF-related mortality. Conversely, excessively high levels, as observed in acromegaly, are linked to a higher incidence of HF. Based on these results, it is recommended that cardiac function be closely monitored in patients with reduced IGF-1 levels and in those with acromegaly. These findings suggest that IGF-1 could hold potential prognostic value for risk stratification in HF.

Exercise stress testing recovery kinetics: the forgotten phase

Abstract Background Impaired exercise capacity is a cardinal feature of heart failure (HF). Peak oxygen uptake (pVO2) and ventilatory efficiency (VE/VCO2 slope) during exercise are well-consolidated prognostic markers in patients with HF. A previous study suggested that abnormally prolonged VO2 recovery, specifically the failure to decrease VO2 from peak exercise by 10.5 mL/kg/min at 180 seconds of the recovery phase, predicts adverse outcomes in HF. However, it is unknown to what extent the recovery of VEqCO2, a marker of ventilation/perfusion mismatch, adds prognostic value to the already existing parameters. Purpose The aim of this study was to characterize the functional and prognostic significance of VEqCO2 kinetics following peak exercise in individuals with HF. Methods This retrospective single-center study included consecutive adult patients with chronic (>3 months) and stable HF with left ventricular ejection fraction (LVEF) <50% who underwent cardiopulmonary exercise testing (CPET) between 2015 and 2020. Following maximal exercise, patients recovered over a 3-minute period (walking 2km/h for 1 minute and sittng passively for 2 minutes). VO2 and VEqCO2 kinetics during recovery, described as the absolute difference to peak VO2 (difVO2) and VEqCO2 (difVEqCO2), were measured at 30, 60, 120, and 180 seconds. Outcomes were assessed as a composite of cardiovascular (CV) death, urgent cardiac transplant, or left ventricular assist device (LVAD) implantation at 1 year. Results A total of 238 patients were included (mean age 58 ± 12 years; 82% males; mean LVEF 34 ± 10%; 68% with ischemic HF; 75% in NYHA class II-III; mean pVO2 18 ± 6 mL/kg/min; mean VE/VCO2 slope 41 ± 12). During the 1-year follow-up, 19 patients met the endpoint (8 CV deaths, 8 urgent heart transplants, and 3 LVAD). ROC curve analysis showed that the best correlation between difVEqCO2 and outcomes was apparent at difVEqCO2 of 180 seconds (AUC 0.83) with a cut-off value of 1 (sensitivity 93%, specificity 58%). These patients, who had a decrease in VEqCO2 (difVEqCO2 >1) at 180 seconds, were significantly older (p=0.02), had a lower LVEF (p<0.001), and higher NYHA (p<0.001). They were at an increased risk of cardiovascular events compared to those with an increase in VEqCO2 (difVEqCO2 <1) at 180 seconds (event-free survival at 1 year 86% vs. 98%, log-rank p<0.001). In multivariate analysis, the statistical association between difVEqCO2 and outcomes remained significant, even after adjusting for difVO2 at 180 seconds (HR 4.315, CI95% (1.349-13.804), p=0.014). Conclusion Abnormal VEqCO2 kinetics in the recovery period of CPET is an easily recognizable non-invasively derived measurement that predicts outcomes in HF. VEqCO2 may complement the evaluation of VO2 and other parameters during recovery to further improve prognostic risk stratification in HF.

Serum metabolomics improve risk stratification for incident heart failure

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

The mortality implications of increasing and decreasing sST2 levels during acute decompensated heart failure

Abstract Introduction Soluble Suppressor of Tumorigenicity (sST2), a marker of cardiac remodelling and fibrosis, has demonstrated promises in prognostication of heart failure (HF) and therefore recommended as an additional test for risk stratification of HF in the 2017 ACC/AHA/HFSA guidance. It is well investigated as single measurements in acute and ambulatory settings. Data regarding sST2 level changes during acute decompensated heart failure (ADHF) and its potential in providing additional prognostic information is however sparse. We therefore sought to evaluate changes in sST2 and its prognostic implications in hospitalized patients during ADHF. Methods Between December 2019 and February 2022, consecutive patients with ADHF and reduced ejection fraction (EF<50%) presenting to our University Hospital were recruited as part of the Investigating the soluble ST2 biomarker in addition to Natriuretic peptides in managing patients with Heart Failure and a Reduced Ejection Fraction (INST2ANT-HF) study (REC Reference: 19/EE/0269). Serum samples were taken at clinician determined decompensation and recompensation in all participants, who were then followed up for one year post discharge. The study primary end point was all-cause mortality at one year. A 2x2 contingency table was constructed to display the relationship between the frequency of unchanged/increased or decreased sST2 levels at recompensation and the frequency of mortality at one year (Table 1). A Kaplan-Meier curve was plotted to display the survival probability of the two groups during one-year follow up (Figure 1), and log-rank test applied to evaluate for significant difference in the survival distributions. Results In 169 patients with paired sST2 samples, median age (IQR) was 72 (62-80.8), 39 (23.2%) were female and 160 (95.2%) were ethnically white. 158 (94.1%) presented with NYHA class II-IV and the median (IQR) EF was 26% (17.5-32.5). Median (IQR) length of stay in hospital was 8 days (5-13). Median (IQR) sST2 level at decompensation and recompensation were 60ng/ml (40-93.3) and 39.5ng/ml (24-64.8) respectively. At clinician determined recompensation, sST2 level decreased in 136 (81%) patients while 32 (19%) had unchanged/increased sST2 levels. One-year mortality was 37.5% in patients with unchanged or increasing sST2 levels during ADHF, compared to 16.2% in those with decreased sST2 levels. The mean (SE) survival time was 332 (7) days for patients with unchanged/increasing sST2, and 274 (22.5) days for patients with decreasing sST2 at HF recompensation (p=0.003). Conclusion Our data demonstrates that there was a downward trend in sST2 in most patients during recovery from an ADHF episode. Importantly, a static or increasing sST2 level from HF decompensation to recompensation was associated with a significantly higher risk of mortality at one year. Further research may ascertain if the mortality risk is also dependent on the percentage changes in sST2 concentrations.Table 1:2x2 contingency tableFigure 1:Kaplan-Meier curve

Heart failure risk assessment using biomarkers in patients with atrial fibrillation: analysis of 32,041 patients from the COMBINE-AF study

Abstract Introduction Heart failure (HF) is one of the most common comorbidities in patients with AF, resulting in a clinical need for robust risk assessment. Purpose To investigate the incremental value of adding NTproBNP, high-sensitivity cardiac troponin T (hs-cTnT), and growth-differentiation factor-15 (GDF-15) to clinical predictors for HF risk stratification in patients with AF, and the individual contribution of each biomarker accounting for inter-biomarker correlation. Methods We used pooled individual patient data from 3 large RCTs investigating DOACs versus VKAs (ARISTOTLE, ENGAGE AF-TIMI 48, RE-LY) from the COMBINE-AF cohort and included all patients with available biomarkers at baseline. The composite primary endpoint was hospitalization for HF (HHF) or CV death (CVD), with HHF as secondary endpoint. We employed analyses of absolute risk and Cox-regression adjusting for clinical factors to assess the association of the individual biomarkers with both endpoints, testing incremental discrimination with the likelihood ratio test from nested models. To address the inter-biomarker correlation, weighted quantile sum (WQS) regression analysis summarizing the adjusted risk of all biomarkers (per quartile) in one index was applied, thereby exploring the individual and additive contribution of each biomarker to risk assessment. Results Data were available in 32,041 patients (median age 71 [IQR 64-77] years, 36.7% female, 23.0% with paroxysmal AF, 41.6% with established HF). Higher biomarker values were associated with a graded increase in absolute risk for HHF/CVD and HHF (Figure 1). In a model adjusting for clinical variables and all biomarkers, hs-cTnT (HR per 1-SD 1.39 [95% CI 1.33-1.44]), NT-proBNP (HR 1.67 [95% CI 1.58-1.76]), and GDF-15 (HR 1.20 [95% CI 1.15-1.25]) were associated with HHF/CVD. The c-index increased with addition of biomarkers (0.70 [0.69, 0.70] to 0.77 [0.76, 0.78]; Likelihood ratio test p<0.001). Results were similar for HHF alone. NTproBNP was significantly correlated with hs-cTnT (r=0.40, p<0.0001) and GDF-15 (r=0.36, p<0.001). To address this correlation, WQS regression analysis was conducted (Figure 2). NTproBNP and hs-cTnT contributed nearly equally to the risk assessment for HHF/CVD and HHF, with GDF-15 providing statistically significant but less contribution to risk assessment (Figure 2). Conclusion Hs-cTnT, NT-proBNP and GDF-15 contribute individually and additively to the risk assessment for HHF/CVD and HHF in patients with AF. Our analysis suggests that hs-cTnT is as important as NTproBNP for HF risk assessment, with significant but less contribution of GDF-15. Our findings support the possible future routine use of biomarkers to distinguish patients with AF at low or high risk for HF and could guide the introduction of therapies to mitigate the risk of HF events in this growing population.Event incidence by biomarker quartilesWeighted quantil sum regression analysis

Leukocyte Extracellular Vesicles Predict Progression of Systolic Dysfunction in Heart Failure with Mildly Reduced Ejection Fraction (LYCHEE) - A Prospective, Multicentre Cohort Study.

Risk stratification in heart failure with mildly-reduced ejection fraction (HFmrEF) remains challenging. We evaluated the predictive value of advanced glycation end products (AGEs) and plasma concentrations of extracellular vesicles (EVs) for the systolic and diastolic dysfunction progression in HFmrEF patients. Skin AGE accumulation was measured using AGE Reader. Plasma EV concentrations were measured using flow cytometry. Among 74 patients enrolled, 13 (18%) had systolic dysfunction progression and 5 (7%) had diastolic dysfunction progression during 6.5months follow-up. Leukocyte EVs concentrations were higher in patients with systolic dysfunction progression (p = 0.002) and predicted the progression with 75.0% sensitivity and 58.3% specificity, independent of other clinical variables (OR 4.72, 95% CI 0.99-22.31). Skin AGE levels and concentrations of other EV subtypes were not associated with systolic or diastolic dysfunction progression. Increased leukocyte EVs concentrations are associated with 4.7-fold higher odds of systolic dysfunction progression in HFmrEF patients.

The LUSBI Protocol (Lung Ultrasound/BREST Score/Inferior Vena Cava)-Its Role in a Differential Diagnostic Approach to Dyspnea of Cardiogenic and Non-Cardiogenic Origin.

Background and Objectives: PoCUS ultrasound applications are widely used in everyday work, especially in the field of emergency medicine. The main goal of this research was to create a diagnostic and therapeutic protocol that will integrate ultrasound examination of the lungs, ultrasound measurements of the inferior vena cava (assessment of central venous pressure) and BREST scores (risk stratification for heart failure), with the aim of establishing a more effective differential diagnostic approach for dyspneic patients. Materials and Methods: A cross-sectional study was conducted in the emergency medicine department with the educational center of the community health center of Banja Luka. Eighty patients of both sexes were included and divided into experimental and control groups based on the presence or absence of dyspnea as a dominant subjective complaint. Based on the abovementioned variables, the LUSBI protocol (lung ultrasound/BREST score/inferior vena cava) was created, including profiles to determine the nature of the origin of complaints. The biochemical marker of heart failure NT pro-BNP served as a laboratory confirmation of the cardiac origin of the complaints. Results: The distribution of NT pro BNP values in the experimental group showed statistically significant differences between individual profiles of the LUSBI protocol (p < 0.001). Patients assigned to group B PLAPS 2 had significantly higher average values of NT pro-BNP (20159.00 ± 3114.02 pg/mL) compared to other LUSBI profiles. Patients from the experimental group who had a high risk of heart failure according to their BREST scores also had a significantly higher average maximum expiratory diameter compared to those without heart failure (p = 0.004). A statistically significant difference (p = 0.001) in LUSBI profiles was observed between the groups of patients divided according to CVP categories. Conclusion: The integration of the LUSBI protocol into the differential diagnosis of dyspnea has been shown to be very effective in confirming or excluding a cardiac cause of the disease in patients.

Screening for Heart Failure: Biomarkers to Detect Heightened Risk in the General Population.

Heart failure (HF) represents a growing global burden of morbidity and mortality. Identifying individuals at risk for HF development is increasingly important, particularly given the advent of disease-modifying therapies for HF as well as its major risk factors such as obesity actalnd diabetes. We aim to review the key circulating biomarkers associated with future HF which may contribute to HF risk prediction. While current guidelines recommend the use of natriuretic peptides and cardiac troponins in HF risk stratification, there are a diverse array of other emerging protein, metabolic, transcriptomic, and genomic biomarkers of future HF development. These biomarkers not only lend insight into the underlying pathophysiology of HF, which spans inflammation to cardiac fibrosis, but also offer an opportunity to further refine HF risk in addition to established biomarkers. As evolving techniques in molecular biology enable an increased understanding of the complex biologic contributions to HF pathophysiology, there is an important opportunity to construct integrated clinical and multi-omic models to best capture HF risk. Moving forward, future studies should seek to understand the contributions of sex differences, underlying comorbidity burden, and HF subtypes to an individual's HF risk. Further studies are necessary to fully define the clinical utility of biomarker screening approaches to refine HF risk assessment, as well as to link risk assessment directly to preventive strategies for HF.

Elevated carbohydrate antigen 125 (CA125) is associated with incident heart failure and mortality in acute coronary syndrome.

Carbohydrate antigen 125 (CA125), a mucin produced by serosal cells in response to mechanical and inflammatory stimuli, has emerged as an important biomarker to guide risk stratification in heart failure (HF). The prognostic value of CA125 in acute coronary syndrome (ACS) patients is less explored. In a cohort of 524 ACS patients (73% males, mean age 67±12years), we assessed the associations between CA125 and the risk for HF and death during a median follow-up period of 27.3months for incident HF and 39.5months for mortality. Plasma CA125 was measured within 24h after admission in the entire cohort and after 6weeks in a subgroup of 115 elderly patients (>75years of age). We also assessed the relationships between baseline CA125 and echocardiographic parameters of cardiac structure and function at 1year post-ACS in this subgroup. Baseline CA125 was associated with incident HF in the entire cohort in a Cox proportional hazards model adjusted for age, sex, cardiovascular (CV) risk factors (diabetes, smoking, hypertension, previous HF, previous ACS and previous stroke), renal function and revascularization {hazard ratio [HR] 1.46 [95% confidence interval (CI) 1.10-1.93] per 1-standard deviation [SD] CA125 increase; P=0.009}. In the detailed follow-up subgroup, elevated baseline CA125 predicted subsequent deterioration of left ventricular (LV) ejection fraction (LVEF), defined as a >5% absolute LVEF decrease in patients with LVEF≥50% at discharge [odds ratio (OR) 3.31 (95% CI 1.15-9.54) per 1-SD baseline CA125 increase; P=0.027]. We also found significant correlations between high baseline CA125 and larger LV volumes (LV end-diastolic volume index, Spearman's r=0.329, P<0.001; LV end-systolic volume index, r=0.391, P<0.001) and left atrial volume index (r=0.320, P<0.001) at 1year post-ACS, indicative of adverse cardiac remodelling. Elevated baseline and follow-up CA125 were associated with increased mortality, independently of age and sex [HR 1.37 (95% CI 1.09-1.71), P=0.006, per 1-SD baseline CA125; HR 1.98 (95% CI 1.06-3.67), P=0.031, per increasing 6week CA125 tertile]. The relationship between 6week CA125 and incident mortality remained significant in the fully adjusted model [HR 2.23 (95% CI 1.15-4.35) per increasing CA125 tertile; P=0.018]. We report independent associations between elevated CA125, LV dysfunction, cardiac remodelling, incident HF and mortality post-ACS. Our results warrant further evaluation of CA125 as a potential biomarker for risk stratification and management of ACS patients, both at the time of the acute coronary event and during follow-up.

Prognoses and risk stratification of thrombus-associated events in heart failure patients without atrial fibrillation.

We aim to assess the risk of thrombus-associated events (TAE) in patients with heart failure (HF) without atrial fibrillation (AF) and develop an effective scoring system for a risk stratification model. This retrospective study included 450 patients (median age 64.0years, interquartile range [55.0, 75.0]; 31.6% women) hospitalized for HF without AF and atrial flutter, but with a left ventricular ejection fraction (LVEF)≤55% and New York Heart Association (NYHA) functional class of III-IV. A median follow-up of 47months was conducted. In the present study, TAE during follow-up was independently associated with both all-cause death [hazard ratio (HR) 1.756, 95% confidence interval (CI) 1.324-2.328, P<0.001] and readmission for HF (HR 1.574, 95% CI 1.122-2.208, P=0.009) after adjustment for covariates. Hypertension (HR 1.573, 95% CI 1.018-2.429, P=0.041), atrial arrhythmia excluding AF (AAexAF) (HR 2.041, 95% CI 1.066-3.908, P=0.031), previous ischaemic stroke (HR 2.469, 95% CI 1.576-3.869, P<0.001), and vascular disease (HR 1.658, 95% CI 1.074-2.562, P=0.023) were independently associated with TAE. Age (HR 1.021, 95% CI 1.008-1.033, P=0.001), previous ischaemic stroke (HR 1.685, 95% CI 1.248-2.274, P=0.001), LVEF ([10, 25] vs. [40, 55]) HR 1.925, 95% CI 1.311-2.826, P=0.001; (25, 40] vs. (40, 55] HR 1.084, 95% CI 0.825-1.424, P=0.563), and creatinine clearance rate (Ccr) (HR 0.991, 95% CI 0.986-0.996, P=0.001) were independently associated with composite events of TAE and death (TAE-D). CHA2DS2VASc modestly predicted 5-year TAE [area under the receiver operating characteristic curves (AUC) 0.660, P<0.001 compared with 0.5] and TAE-D (AUC 0.639, P<0.001 compared with 0.5). (C)ACE, formed by incorporating AAexAF, LVEF, and Ccr into CHA2DS2VASc, had higher AUC for predicting 5-year TAE (0.694 vs. 0.660, P=0.018) and TAE-D (0.708 vs. 0.639, P<0.001) compared with CHA2DS2VASc. In patients with HF with reduced ejection fraction (HFrEF), (C)ACE and (C)ACEN [formed by incorporating NYHA into (C)ACE] had higher AUC compared with CHA2DS2VASc in predicting 5-year TAE (0.700 and 0.707 vs. 0.649, P=0.013 and 0.030, respectively) and TAE-D (0.712 and 0.713 vs. 0.622, P<0.001 and <0.001, respectively). The AUC did not improve statistically from (C)ACE to (C)ACEN (0.700 vs. 0.707, P=0.600 for TAE; 0.712 vs. 0.713, P=0.917 for TAE-D). In HF without AF, TAE during follow-up was associated with adverse prognoses. The independent risk factors of TAE or TAE-D improved CHA2DS2-VASc predictive ability, especially in patients with HFrEF. Our findings provide new evidence for TAE risk stratification in HF without AF, potentially guiding prophylactic anticoagulation.

Long-term outcomes of phenoclusters in preclinical heart failure with preserved and mildly reduced ejection fraction.

The identification of subjects at higher risk for incident heart failure (HF) with preserved ejection fraction (EF) suitable for more intensive preventive programmes remains challenging. We applied phenomapping to the DAVID-Berg population, comprising subjects with preclinical HF, aiming to refine HF risk stratification. The DAVID-Berg study prospectively enrolled 596 asymptomatic outpatients with EF>40% with hypertension, diabetes mellitus or known cardiovascular disease. In this cohort, we performed an unsupervised cluster analysis on 591 patients, including clinical, laboratory, electrocardiographic and echocardiographic parameters. We tested the association between each cluster and a composite outcome of HF/death. The median age was 70years, 55.5% were males and the median EF was 61.0%. Phenomapping provided three different clusters. Subjects in Cluster 3 were the oldest and had the highest prevalence of atrial fibrillation, the lowest estimated glomerular filtration rate (eGFR), the highest N-terminal pro-brain natriuretic peptide (NT-proBNP) and the largest left atrium. During a median follow-up of 5.7years, 13.4% of subjects experienced HF/death events (N=79). Compared with Clusters 1 and 2, Cluster 3 had the worst prognosis (log-rank test: Cluster 3 vs. 1 P<0.001; Cluster 3 vs. 2 P=0.008). Cluster 3 was associated with a risk of HF/death 2.5 times higher than Cluster 1 [adjusted hazard ratio (HR)=2.46, 95% confidence interval (CI) 1.24-4.90]. Based on phenomapping, older patients with lower kidney function and worse diastolic function might represent a subset of preclinical HF with EF>40% who deserve more efforts to prevent clinical HF.

Value of the monocyte-to-high-density lipoprotein cholesterol ratio in refining the detection of prevalent heart failure: Insights from the NHANES 1999-2018.

The monocyte-to-high-density lipoprotein cholesterol ratio (MHR) is a novel marker that can help estimate the degree of atherosclerosis by considering inflammation and lipid abnormalities. This study aimed to assess the association between the MHR and prevalent heart failure (HF) and to explore the value of the MHR in detecting prevalent HF in the general US population. Our study included 25,374 participants from the National Health and Nutrition Examination Survey (1999-2018). Among the participants, 749 (2.95%) reported a history of HF, and the HF group had a significantly higher MHR than the non-HF group. Adjusted analyses revealed that each standard deviation increase in the MHR was associated with a 27.8% increase in the risk of HF. The association between the MHR and prevalent HF was linear across the entire MHR range. Adding the MHR to conventional cardiovascular risk factors significantly improved the area under the curve (0.875; p < 0.001), continuous net reclassification index (0.187; p < 0.001), and integrated discrimination index (0.004; p < 0.001). Our study suggests a potential association between the MHR and HF risk, and the findings enhance HF risk stratification and provide novel insights into the interplay between the coronary atherosclerotic burden and HF in clinical settings.

Evaluating Biomarkers as Tools for Early Detection and Prognosis of Heart Failure: A Comprehensive Review.

There is a high prevalence of heart failure (HF) worldwide, which has significant consequences for healthcare costs, patient death and quality of life. Therefore, there has been much focus on finding and using biomarkers for early diagnosis, prognostication and therapy of HF. This overview of the research presents a thorough examination of the current state of HF biomarkers and their many uses. Their function in diagnosing HF, gauging its severity and monitoring its response to therapy are all discussed. Particularly promising in HF diagnosis and risk stratification are the cardiac-specific biomarkers, B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide. Markers of oxidative stress, extracellular matrix, renal function, inflammation and cardiac peptides have shown promise in evaluating HF severity and prognosis. MicroRNAs and insulin-like growth factor are two emerging biomarkers that have shown potential in helping with HF diagnosis and prognosis.

Sudden Cardiac Death Risk Stratification in Heart Failure With Preserved Ejection Fraction.

Heart failure with preserved ejection fraction (HFpEF) poses a significant clinical challenge, with sudden cardiac death (SCD) emerging as one of the leading causes of mortality. Despite advancements in cardiovascular medicine, predicting and preventing SCD in HFpEF remains complex due to multifactorial pathophysiological mechanisms and patient heterogeneity. Unlike heart failure with reduced ejection fraction, where impaired contractility and ventricular remodeling predominate, HFpEF pathophysiology involves heavy burden of comorbidities such as hypertension, obesity, and diabetes. Diverse mechanisms, including diastolic dysfunction, microvascular abnormalities, and inflammation, also contribute to distinct disease and SCD risk profiles. Various parameters such as clinical factors and electrocardiogram features have been proposed in SCD risk assessment. Advanced imaging modalities and biomarkers offer promise in risk prediction, yet comprehensive risk stratification models specific to HFpEF ar0e lacking. This review offers recent evidence on SCD risk factors and discusses current therapeutic strategies aimed at reducing SCD risk in HFpEF.

Using Artificial Intelligence to Predict Heart Failure Risk from Single-lead Electrocardiographic Signals: A Multinational Assessment.

Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) can enable large-scale community-based risk assessment. To evaluate an artificial intelligence (AI) algorithm to predict HF risk from noisy single-lead ECGs. Multicohort study. Retrospective cohort of individuals with outpatient ECGs in the integrated Yale New Haven Health System (YNHHS) and prospective population-based cohorts of UK Biobank (UKB) and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Individuals without HF at baseline. AI-ECG-defined risk of left ventricular systolic dysfunction (LVSD). Among individuals with ECGs, we isolated lead I ECGs and deployed a noise-adapted AI-ECG model trained to identify LVSD. We evaluated the association of the model probability with new-onset HF, defined as the first HF hospitalization. We compared the discrimination of AI-ECG against the pooled cohort equations to prevent HF (PCP-HF) score for new-onset HF using Harrel's C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). There were 194,340 YNHHS patients (age 56 years [IQR, 41-69], 112,082 women [58%]), 42,741 UKB participants (65 years [59-71], 21,795 women [52%]), and 13,454 ELSA-Brasil participants (56 years [41-69], 7,348 women [55%]) with baseline ECGs. A total of 3,929 developed HF in YNHHS over 4.5 years (2.6-6.6), 46 in UKB over 3.1 years (2.1-4.5), and 31 in ELSA-Brasil over 4.2 years (3.7-4.5). A positive AI-ECG screen was associated with a 3- to 7-fold higher risk for HF, and each 0.1 increment in the model probability portended a 27-65% higher hazard across cohorts, independent of age, sex, comorbidities, and competing risk of death. AI-ECG's discrimination for new-onset HF was 0.725 in YNHHS, 0.792 in UKB, and 0.833 in ELSA-Brasil. Across cohorts, incorporating AI-ECG predictions in addition to PCP-HF resulted in improved Harrel's C-statistic (Δ=0.112-0.114), with an IDI of 0.078-0.238 and an NRI of 20.1%-48.8% for AI-ECG vs. PCP-HF. Across multinational cohorts, a noise-adapted AI model with lead I ECGs as the sole input defined HF risk, representing a scalable portable and wearable device-based HF risk-stratification strategy.

Lipoprotein Insulin Resistance Score and Mortality Risk Stratification in Heart Failure

BackgroundHigher total serum cholesterol is associated with lower mortality in heart failure. Evaluating associations between lipoprotein subfractions and mortality among people with heart failure may provide insights into this observation. MethodsWe prospectively enrolled a community cohort of people with heart failure from 2003 to 2012 and assessed vital status through 2021. Plasma collected at enrollment was used to measure lipoprotein subfractions via nuclear magnetic resonance spectroscopy. A composite score of 6 lipoprotein subfractions was generated using the lipoprotein insulin resistance index (LP-IR) algorithm. Using covariate-adjusted proportional hazards regression models, we evaluated associations between LP-IR score and all-cause mortality. ResultsAmong 1382 patients with heart failure (median follow-up 13.9 years), a one-standard-deviation (SD) increment in LP-IR score was associated with lower mortality (hazard ratio [HR] 0.93; 95% confidence interval [CI], 0.97-0.99). Among LP-IR parameters, mean high-density lipoprotein (HDL) particle size was significantly associated with lower mortality (HR per 1-SD decrement in mean HDL particle size = 0.83; 95% CI, 0.78-0.89), suggesting that the inverse association between LP-IR score and mortality may be driven by smaller mean HDL particle size. ConclusionsLP-IR score was inversely associated with mortality among patients with heart failure and may be driven by smaller HDL particle size.

Clinical Trajectory and Risk Stratification for Heart Failure with Preserved Ejection Fraction in a Real-World Cohort of Patients with Suspected Coronary Artery Disease.

Background: Heart failure with preserved ejection fraction (HFpEF) is a widespread condition with significant morbidity and mortality. Its clinical heterogeneity may delay the diagnosis. Aim: To identify predictors of HFpEF-related hospitalizations in ambulatory patients presenting with elevated cardiovascular risk, suspected coronary artery diseases (CADs), and positive HFpEF screenings. Methods: Consecutive patients presenting with suspected CAD, enrolled in the observational LIFE-Heart study (2006-2014, NCT00497887), and meeting HFpEF criteria per the 2016 European Society of Cardiology (ESC) guidelines were categorized according to the presence of "overlapping conditions" potentially masking or contributing to their symptoms. Additional stratification using the H2FPEF score (<2: low risk, 2-5: intermediate risk, and ≥6 high risk) was performed. Follow-up for hospitalizations, reasons of hospitalization, and death spanned a median of 6 years. Results: Of 1054 patients (66 ± 10 years, 60% male, NT-pro-BNP 286, IQR 183-574 pg/mL), 53% had overlapping conditions, while 47% had "isolated HFpEF". The H2FPEF scores classified 23%, 57%, and 20% as low-, intermediate-, and high-risk, respectively, with consistent proportions across patients with and without overlapping conditions (p = 0.91). During the follow-up observational phase, 54% were rehospitalized, 22% experienced heart failure (HF) rehospitalizations, and 11% of patients died. Multivariable logistic regression revealed a high-risk H2FPEF category as an independent predictor of HF rehospitalization in the overall cohort (odds ratio: 3.4, CI: 2.4-4.9, p < 0.01) as well as in patients with and without overlapping conditions. Furthermore, a H2FPEF score ≥ 6 was independently associated with higher mortality rates (hazard ratio: 1.8, CI: 1.2-2.6, p < 0.01) in the Cox regression analysis. Conclusions: Ambulatory patients presenting for suspected CAD and meeting HFpEF screening criteria face elevated risks for rehospitalizations over six years. Regardless of concomitant diagnoses, quantifying cardiac damage with the H2FPEF score helps in risk-stratifying patients for HF hospitalization and mortality.

Jugular Venous Response for Risk Stratification in Heart Failure.

The response of jugular venous pressure (JVP) to increased preload with inspiration has been recognized as a method of stratifying risk in the management of heart failure (HF). Whether the JVP response to inspiration may be more effective than other simple approaches in this setting remains unclear. This study enrolled 79 patients with stable HF. JVP was assessed from the right internal jugular vein in the sitting position and was considered high if visible above the right clavicle at rest. JVP responses to inspiration, the five-repetition sit-to-stand test (5-STS), and squatting were also evaluated. The primary outcome was a composite of all-cause death and hospitalization for worsening HF. JVP assessment after 5-STS and during squatting was not conducted in two and 14 HF patients, respectively, due to physical limitations. During a mean follow-up of 837 days, the primary outcome was associated with a high JVP at rest (hazard ratio, 2.47; 95% confidence interval [CI], 1.09 to 5.60; P <0.05), with inspiration (hazard ratio, 2.53; 95% CI, 1.17 to 5.46; P <0.05), after 5-STS (hazard ratio, 2.61; 95% CI, 1.23 to 5.97; P <0.05), and during squatting (hazard ratio, 2.40; 95% CI, 1.03 to 6.06; P <0.05). Among patients without a high JVP at rest, the specificity of the primary outcome at one year was greater for the JVP response to inspiration (89%) and squatting (92%) than for the response to 5-STS (80%). JVP response to increased preload with inspiration may be a simple and practical method for risk assessment in patients with stable HF.

Incremental Value of a Metabolic Risk Score for Heart Failure Mortality: A Population-Based Study.

Heart failure is heterogeneous syndrome with persistently high mortality. Nuclear magnetic resonance spectroscopy enables high-throughput metabolomics, suitable for precision phenotyping. We aimed to use targeted metabolomics to derive a metabolic risk score (MRS) that improved mortality risk stratification in heart failure. Nuclear magnetic resonance was used to measure 21 metabolites (lipoprotein subspecies, branched-chain amino acids, alanine, GlycA (glycoprotein acetylation), ketone bodies, glucose, and citrate) in plasma collected from a heart failure community cohort. The MRS was derived using least absolute shrinkage and selection operator penalized Cox regression and temporal validation. The association between the MRS and mortality and whether risk stratification was improved over the Meta-Analysis Global Group in Chronic Heart Failure clinical risk score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels were assessed. The study included 1382 patients (median age, 78 years, 52% men, 43% reduced ejection fraction) with a 5-year survival rate of 48% (95% CI, 46%-51%). The MRS included 9 metabolites measured. In the validation data set, a 1 standard deviation increase in the MRS was associated with a large increased rate of death (hazard ratio, 2.2 [95% CI, 1.9-2.5]) that remained after adjustment for Meta-Analysis Global Group in Chronic Heart Failure score and NT-proBNP (hazard ratio, 1.6 [95% CI, 1.3-1.9]). These associations did not differ by ejection fraction. The integrated discrimination and net reclassification indices, and Uno's C statistic, indicated that the addition of the MRS improved discrimination over Meta-Analysis Global Group in Chronic Heart Failure and NT-proBNP. This MRS developed in a heart failure community cohort was associated with a large excess risk of death and improved risk stratification beyond an established risk score and clinical markers.

Association of left atrial enlargement with heart failure events in non-valvular atrial fibrillation patients with preserved left ventricular ejection fraction.

Atrial fibrillation (AF) increases the risk of heart failure (HF); however, little is known regarding the risk stratification for incident HF in AF patients, especially with preserved left ventricular ejection fraction (LVEF). The Fushimi AF Registry is a community-based prospective survey of AF patients. From the registry, 3002 non-valvular AF patients with preserved LVEF and with the data of antero-posterior left atrial diameter (LAD) at enrolment were investigated. Patients were stratified by LAD (<40, 40-44, 45-49, and ≥50 mm) with backgrounds and HF hospitalization incidences compared between groups. Of 3002 patients [mean age, 73.5 ± 10.7 years; women, 1226 (41%); paroxysmal AF, 1579 (53%); and mean CHA2DS2-VASc score, 3.3 ± 1.7], the mean LAD was 43 ± 8 mm. Patients with larger LAD were older and less often paroxysmal AF, with a higher CHA2DS2-VASc score (all P < 0.001). Heart failure hospitalization occurred in 412 patients during the median follow-up period of 6.0 years. Larger LAD was independently associated with a higher HF hospitalization risk [LAD ≥ 50 mm: hazard ratio (HR), 2.36; 95% confidence interval (CI), 1.75-3.18; LAD 45-49 mm: HR, 1.84; 95% CI, 1.37-2.46; and LAD 40-44 mm: HR, 1.34; 95% CI, 1.01-1.78, compared with LAD < 40 mm) after adjustment by age, sex, AF type, and CHA2DS2-VASc score. These results were also consistent across major subgroups, showing no significant interaction. Left atrial diameter is significantly associated with the risk of incident HF in AF patients with preserved LVEF, suggesting the utility of LAD regarding HF risk stratification for these patients.