Circulation: Heart Failure最新文献

Background: Patients with heart failure and reduced ejection fraction (HFrEF) have a high residual risk for heart failure hospitalizations and cardiovascular death. We aimed to use multimodality data to identify unique HFrEF subgroups with high residual risk.

Methods: In this VICTORIA substudy (Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction), clinical, electrocardiographic, echocardiographic, quantitative biomarker, and targeted proteomics data were collected. Agglomerative hierarchical clustering was performed using 105 variables to define HFrEF phenogroups. Cox regression estimated the relationship between the HFrEF phenogroups and the primary composite outcome of cardiovascular death or heart failure hospitalization. External validation of the phenogroups was performed in the BIOSTAT-CHF cohort (Biology Study to Tailored Treatment in Chronic Heart Failure). Multinomial logistic regression identified the most important variables in defining the HFrEF phenogroups.

Results: There were 564 participants; after clustering, the optimal number of HFrEF phenogroups was 3. Phenogroup 1 was young, well-treated with guideline-directed medical therapy, and least likely to have an implantable cardioverter defibrillator. Phenogroup 2 had the highest prevalence of atrial fibrillation and pathological Q-waves on electrocardiography. Phenogroup 3 was older, had more biventricular dysfunction, and had advanced renal disease. A stepwise increase in risk of the primary composite outcome was observed from HFrEF phenogroup 1 to 3 (hazard ratio, 7.0 [95% CI, 4.1-12.0]; P≤0.01). The phenogroups were externally validated in BIOSTAT-CHF, and phenogroup 3 had similar patient characteristics (eg, older with more significant renal dysfunction) and had the highest event rate at 1 year (41% [95% CI, 38-45]). After multinomial regression, GDF-15 (growth differentiation factor 15) was most important in discriminating the 3 HFrEF phenogroups in both VICTORIA and BIOSTAT-CHF.

Conclusions: We identified and externally validated unique HFrEF subpopulations with shared biological characteristics that differentiated residual risk for cardiovascular death or heart failure hospitalization. GDF-15 was the most important protein used to distinguish the 3 HFrEF phenogroups. These findings may inform study entry criteria for future HFrEF trials focused on the development of novel therapeutics.

Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02861534.

Background: The 2022 American Heart Association/American College of Cardiology/Heart Failure Society of America guidelines introduced elevated natriuretic peptide (NP) levels as a criterion for defining stage B heart failure (HF), or pre-HF, to identify individuals at greatest risk for future HF. Given the known NP deficiency in obesity, we aimed to assess whether a single NP cut point would disproportionately up-classify individuals with versus without obesity to stage B HF.

Methods: Participants free of HF from 5 community-based cohorts were included. We examined the reclassification of individuals to stage B HF using the 2022 versus 2013 guidelines, stratified by obesity class. Cox proportional hazards models were used to assess the association of NPs with incident HF across obesity classes.

Results: Among 32 735 participants, 35% had normal weight, 40% were overweight, 17% had obesity class 1, and 8% had obesity class 2/3. When applying the 2022 versus 2013 criteria, the proportion of individuals up-classified to stage B HF using the NP criterion was 62% among those with normal weight, 51% for those overweight, 47% for individuals with obesity class 1, and 42% for individuals with obesity class 2/3. Over a median follow-up of 13 years, 3077 HF events occurred. Both higher NP and body mass index were associated with greater HF risk, as expected (P<0.0001 for both). Importantly, body mass index modified the association of NP with HF risk, such that higher NP concentration was associated with greater HF risk among individuals with lower body mass index. The optimal NT-proBNP (N-terminal pro-B-type natriuretic peptide) cut point to predict future HF risk was lower among individuals with obesity (80 pg/mL; 95% CI, 53-121) compared with normal-weight individuals (109 pg/mL; 95% CI, 80-157).

Conclusions: The application of a single NP cut point resulted in fewer individuals with obesity being up-classified to stage B HF compared with normal-weight individuals. Adjusting NP cut points for individuals with obesity may improve the accuracy of HF risk stratification.

Background: Pulmonary hypertension (PH) is classified as precapillary, isolated postcapillary pulmonary hypertension (IpcPH), combined postcapillary and precapillary (CpcPH), or exercise PH. IpcPH associated with left heart disease can lead to pulmonary vascular remodeling and eventually CpcPH. Conversely, precapillary PH may be diagnosed in the presence of cardiovascular comorbidities, including left heart disease. Atrial functional impairment is a frequent finding in cardiopulmonary disease, reflecting both intrinsic atrial cardiomyopathy and congestion. Consequently, we sought to investigate this across the PH spectrum.

Methods: Patients referred to both right heart catheterization and cardiovascular magnetic resonance imaging were enrolled in this monocentric registry. Patients were classified by right heart catheterization according to current guideline recommendations. Cardiovascular magnetic resonance assessment included left/right ventricular and left atrial (LA)/right atrial volumes and deformation imaging.

Results: The study population consisted of N=209 patients (n=55 normal, n=72 precapillary, n=27 CpcPH, n=15 IpcPH, n=34 exercise, and n=6 unclassified PH). N=126 patients underwent additional exercise stress right heart catheterization. Median LA reservoir function was lowest and similar in IpcPH (10.0%) and CpcPH (10.0%), which were significantly impaired compared with normal hemodynamics (30.8%, both P<0.001), precapillary (28.2%, both P<0.001), and exercise PH (26.9%, IpcPH: P=0.039, CpcPH: P=0.048). LA reservoir function and left ventricular global longitudinal strain showed good diagnostic performance to identify patients with left cardiac involvement evident at rest (pulmonary capillary wedge pressure ≥15 mm Hg; area under the curve, 0.81 versus 0.77; P=0.20), whereas LA reservoir function emerged superior for identification of exercise stress induced pulmonary capillary wedge pressure ≥25 mm Hg (area under the curve, 0.79 versus 0.70, P=0.039).

Conclusions: LA functional impairment is a sign of left heart involvement in patients with PH. Left atrial reservoir function emerged superior for the identification of left heart disease unmasked during exercise stress compared with left ventricular global longitudinal strain. Consequently, LA strain may become an innovative method to detect early-stage left heart disease in PH.

Background: The performance of estimated glomerular filtration rate (eGFR) among patients with heart failure (HF) may be worse than in the general population due to a higher prevalence of confounding factors affecting creatinine and cystatin C. Studies in this area are scarce and not stratified by type of HF. We evaluated the performance of current creatinine and cystatin C equations (eGFRcr, eGFRcys, and eGFRcrcys) compared with measured GFR (mGFR) among patients with HF stratified by ejection fraction.

Methods: We pulled data on Mayo Clinic patients with an mGFR performed for clinical indications from 2011 to 2023, with serum creatinine and cystatin C measured within 7 days and an echocardiogram performed up to 1 year before the mGFR date. HF was identified by the presence of International Classification of Diseases codes within 1 year before the mGFR and subgrouped into ejection fraction (EF) ≥50% (HFEF≥50%, n=182) or <50% (HFEF<50%, n=115) and compared with no-HF controls (n=1871). CKD-EPI (and EKFC) eGFRcr, eGFRcys, and eGFRcrcys equations were calculated and compared for bias (mGFR minus eGFR) and accuracy (1-P30, proportion of people with ≥30% difference between eGFR and mGFR). CIs were generated by bootstrapping.

Results: The HF groups were characterized by older age, higher proportion of males, more diabetes, higher creatinine, and higher cystatin C than controls. In terms of bias, eGFRcr overestimated mGFR to a greater extent in both HF groups compared with controls, whereas eGFRcys and eGFRcrcys showed similar bias in both HF groups and controls. In the HF groups, cystatin C-based equations were more accurate than eGFRcr, particularly within HFEF<50% (1-P30 of 28% and 34% for CKD-EPI eGFRcys and eGFRcrcys, respectively, versus 60% for eGFRcr), whereas eGFRcrcys was more accurate in controls. The CKD-EPI and EKFC equations were overall convergent, showing similar results.

Conclusions: Among patients with HF, eGFRcr demonstrates inferior performance (more bias and less accuracy) compared with cystatin C-based eGFRs, with this effect being more pronounced in those with HFEF<50%.

The Get With The Guidelines-Heart Failure program was developed in 2005 with the goal of bringing evidence-based guidelines in heart failure management into widespread clinical practice. The program includes workshops, webinars, tool kits, chart abstraction, performance benchmarking, and achievement awards to drive quality improvement at participating hospitals. Two decades after its inception, the program has grown to include over 600 participating institutions across the United States. Linking registry data to Centers for Medicare and Medicaid Services claims has also allowed for the evaluation of longitudinal outcomes. Get With The Guidelines-Heart Failure has helped improve the quality of care for patients and has contributed substantially to the understanding of clinical science and optimal management of heart failure. This narrative review provides an overview of the indelible impact of the Get With The Guidelines-Heart Failure program on quality heart failure care over the past 20 years and highlights future challenges and directions.

Background: This study evaluates clinical trends and mid-term waitlist and posttransplant outcomes following the 2018 heart allocation policy change.

Methods: The United Network for Organ Sharing registry was queried to analyze adult waitlisted and transplanted patients undergoing isolated heart transplantation. Two analyses were conducted: (1) waitlist and (2) posttransplant outcomes. For the waitlist analysis, candidates were stratified into seasonally matched prepolicy (October 18, 2012-June 30, 2017) and postpolicy (October 18, 2018-June 30, 2023) groups, with a 1-year follow-up period. Waitlist outcomes included 1-year cumulative incidences of transplantation, delisting due to death/clinical deterioration, and all-cause survival from the initial waitlisting. For the posttransplant analysis, recipients were stratified into seasonally matched prepolicy (October 18, 2014-June 30, 2018) and postpolicy (October 18, 2018-June 30, 2020) groups, with a 4-year follow-up period. Posttransplant outcomes included 4-year survival. Propensity score-matching and multivariable Cox regression were used for risk adjustment.

Results: Under the 2018 allocation system, there was a continued shift toward the use of older donors, longer graft ischemic times, and shorter waitlist durations. In the waitlist analysis, 30 620 waitlisted candidates were analyzed, with 14 908 (48.7%) listed after the policy change. The postpolicy candidates had a higher 1-year cumulative incidence of transplantation (subhazard ratio, 2.06 [95% CI, 2.00-2.12]; P<0.001) and a lower 1-year cumulative incidence of delisting (subhazard ratio, 0.58 [95% CI, 0.53-0.63]; P<0.001) compared with the prepolicy candidates. In addition, the postpolicy candidates had significantly improved 1-year survival from initial waitlisting compared with the prepolicy candidates (90.0% versus 86.8%; P<0.001). In the posttransplant analysis, 13 712 recipients were analyzed, with 4597 (33.5%) transplanted following the policy change. The 4-year post-transplant survival was similar between the groups (83.3% versus 82.8%; P=0.593). Furthermore, the comparable 4-year post-transplant survival persisted in the propensity score-matched comparison and multivariable Cox regression.

Conclusions: Despite the changes in donor and recipient profiles following the 2018 allocation system change, this mid-term reassessment demonstrates its success in significantly improving waitlist survival, while maintaining comparable posttransplant survival.