Heart Failure With Reduced Ejection Fraction Group Research Articles

Dynamic trajectories of left ventricular ejection fraction in heart failure with improved ejection fraction.

Heart failure with improved ejection fraction (HFimpEF) has been regarded as a new heart failure (HF) type in 2022. However, studies on the impact of left ventricular ejection fraction (LVEF) trajectories on the prognosis of patients with HFimpEF are scarce. In this study, we investigated dynamic trajectories of LVEF and different clinical outcomes in HFimpEF. This was a multi-center study included patients diagnosed with HF with reduced ejection fraction (HFrEF) between January 1, 2015, and October 31, 2022. Enrolled patients were divided into HFimpEF and persistent HFrEF groups. To further investigate different LVEF trajectories in HFimpEF patients, they were classified into persistent HFimpEF and transient HFimpEF subgroups. Adverse clinical outcomes encompassed all-cause death, cardiovascular death, and HF-related rehospitalization. A total of 734 patients were included (HFimpEF: n = 162; persistent HFrEF: n = 572). Cox regression analysis revealed that compared with persistent HFrEF, patients with HFimpEF experienced a lower risk of all-cause and cardiovascular death. Subgroup analysis determined that only 113 (69.75%) patients maintained an LVEF exceeding 40%. Cox regression analysis revealed that persistent HFimpEF patients had a lower risk of all-cause and cardiovascular death compared to those with transient HFimpEF. Finally, multivariate logistic analysis showed that gender and high-density lipoprotein cholesterol levels were independent predictors of persistent HFimpEF. HFimpEF does not accurately represent HF recovery, given that there are different trajectories of LVEF in HFimpEF. Patients with persistent HFimpEF experience better clinical outcomes, highlighting clinicians should identify clinical modifiable factors to maintain a stable HF stage for better prognosis. ChiCTR2400086622, 08/07/2024.

Effect of exogenous ketone supplementation on cardiac energetics, function, and perfusion in type 2 diabetes, heart failure, and healthy participants- A single center, open labelled clinical study

Abstract Background Type 2 diabetes (T2D) confers loss of cardiac metabolic flexibility in fuel selection and impaired mitochondrial function. Enhanced ketone metabolism observed in T2D may represent a compensatory adaptive mechanism as ketones are a more energy efficient resource than carbohydrates or fatty acids. Favorable energetic properties of ketones may potentially mitigate the energy starved state in T2D and heart failure (HF). Purpose To test whether exogenous oral ketone supplementation would reverse cardiac energetic deficit, as well as improve cardiac function and perfusion in patients with T2D, with HF with reduced ejection fraction (HFrEF), and healthy volunteers (HV). Methods Three groups of patients were recruited: patients with T2D (n=33); patients with HFrEF (n=29, 14 with T2D); and HVs(n=25). Participants underwent cardiovascular magnetic resonance and spectroscopy to assess left ventricular (LV) function, rest and dobutamine stress perfusion and energetics (phosphocreatine/adenosine triphosphate ratio[PCr/ATP]). After the initial visit, participants had an identical second visit following 2 weeks of oral ketone supplementation (30g daily). Results Participants were matched in age and sex distribution. There were no significant differences in LV ejection fraction (LVEF) between T2D and HV groups with significantly lower LVEF in HFrEF group. Both the T2D group and the HFrEF group showed significant reductions in PCr/ATP ratio and the rest and stress GLS compared to the HV. The resting and dobutamine-stress myocardial blood flow (MBF) were only significantly reduced in patients with HFrEF compared to T2D and HV groups. Subgroup analyses of HFrEF group with and without T2D showed no significant differences in energetics, perfusion, or functional assessments. Significant increase in PCr/ATP ratio was seen only in T2D group from baseline after 2 weeks of ketone supplementation (Visit-1:1.6[1.5,1.8] vs Visit-2:1.9[1.7,2.1]; P=0.01). This significant increment was not observed in HFrEF or HV groups. Two weeks of ketone supplementation was not associated with any significant changes in LVEF, GLS, rest or dobutamine-stress myocardial blood flow, or in myocardial lipid content (Table-1). Conclusions Short-term ketone supplementation is associated with isolated significant improvements in resting cardiac energetics in patients with T2D and preserved LVEF, without changes cardiac function or perfusion. In contrast to patients with T2D and preserved LVEF, short-term ketone supplementation does not lead to any significant improvements in energetics in patients with HFrEF suggesting loss of mitochondrial plasticity with transition to HFrEF. Moreover, healthy volunteers experience no further increments of myocardial energetics from the normal range values at baseline with ketone supplementation.

Gut Microbiota and Metabolic Alterations Associated with Heart Failure and Coronary Artery Disease.

This study investigates the role of gut microbiota in cardiovascular diseases, with an additional focus on pro-atherogenic metabolites. We use advanced network analysis and machine learning techniques to identify key microbial features linked to coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF). This cross-sectional study included 189 participants divided into three groups: coronary artery disease (n = 93), heart failure with reduced ejection fraction (n = 43), and controls (n = 53). Assessments included physical exams, echocardiography, dietary surveys, blood analysis, and fecal analysis. Gut microbiota composition was analyzed using next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR). Statistical analysis methods for testing hypotheses and correlations, alpha and beta-diversity analyses, co-occurrence networks, and machine learning were conducted using Python libraries or R packages with multiple comparisons corrected using the Benjamini-Hochberg procedure. Significant gut microbiota alterations were observed, with higher Bacillota/Bacteroidota ratios in CAD and HFrEF groups compared to controls (p < 0.001). Significant differences were observed in α-diversity indices (Pielou, Chao1, Faith) between disease groups and controls (p < 0.001). β-diversity analyses also revealed distinct microbial profiles (p = 0.0015). Interestingly, trimethylamine N-oxide (TMAO) levels were lower in CAD and HFrEF groups compared to controls (p < 0.05), while indoxyl sulfate (IS) levels were comparable between the study groups. Co-occurrence network analysis and machine learning identified key microbial features linked to these conditions, highlighting complex interactions within the gut microbiota associated with cardiovascular disease.

Right-ventricle heart failure in PAH vs. HFrEF with secondary PH: Hemodynamic, ergospirometric, and organ function correlations

PurposeThe goal of the study was to identify markers of organ function used in daily routines that could potentially aid in the overall evaluation of the cardiovascular system in patients with right-ventricle heart failure due to pulmonary arterial hypertension (PAH) and left-ventricle heart failure. We analyzed correlations between parameters from right heart catheterization (RHC), cardiopulmonary exercise test (CPET), and selected laboratory parameters of thyroid, liver, kidneys function and iron homeostasis. Patients and methodsA retrospective analysis included 107 patients (mean age 57.6 ​± ​16.2; 34.6 ​% women), comprising 57 patients with PAH (mean age 54.0 ​± ​18.2; 49.1 ​% women) and 50 patients with heart failure with reduced ejection fraction (HFrEF) ​< ​40 ​% (mean age 61.6 ​± ​12.7; 18 ​% women). All patients underwent CPET. Each patient in the PAH group had RHC performed. Fifteen patients from the HFrEF group underwent RHC, which confirmed the suspicion of pulmonary hypertension (HFrEF-SPH). ResultsCPET and laboratory parameters’ analysis showed strong correlations between ventilation/carbon dioxide production (VE/VCO2) slope and NT-proBNP in HFrEF without secondary PH and HFrEF-SPH groups. In the PAH group, VE/VCO2 slope correlated with liver and thyroid function but also with morphological parameters of red-cell system.Analysis of correlations between laboratory and hemodynamic parameters revealed significant correlations between pulmonary arterial pressure, pulmonary vascular resistance (PVR) and red-cell parameters, especially strong with fT4 in the PAH group. ConclusionsIn HFrEF-SPH patients, laboratory parameters strongly correlated with pulmonary pressures and pulmonary capillary wedge pressure (PCWP).

Predictors and Prognostic Factors of Heart Failure with Improved Ejection Fraction.

Heart failure with reduced ejection fraction (HFrEF) patients who have improved ejection fraction have a better prognosis than those with persistently reduced ejection fraction. This study aimed to analyze the predictors for progression of patients with HFrEF to heart failure with improved ejection fraction (HFimpEF), as well as their characteristics and analyze predictors for prognosis. A retrospective analysis was conducted on 1251 patients with HFrEF at baseline, who also had a second echocardiogram 3 months. After left ventricular ejection fraction (LVEF) reassessment, patients were separated into the HFimpEF group (n = 408) and the persistent HFrEF group (n = 611). The primary endpoint was a composite of cardiovascular death or heart failure hospitalization. Multivariate logistic regression showed that without history of alcohol consumption (OR: 0.47, 95% CI: 0.28-0.78), non-New York Heart Association (NYHA) class III-IV (OR: 0.28, 95% CI: 0.15-0.52), without dilated cardiomyopathy (OR: 0.47, 95% CI: 0.26-0.84), concomitant hypertension (OR: 1.53, 95% CI: 1.02-2.29), -blockers use (OR: 2.29, 95% CI: 1.54-3.43), and lower uric acid (OR: 0.999, 95% CI: 0.997-1.000) could predict LVEF improvement. Kaplan-Meier curves demonstrated that HFimpEF patients had a significantly lower incidence of adverse events than HFrEF patients (log Rank p 0.001). Multivariate Cox regression found that older age (HR: 1.04, 95% CI: 1.02-1.06), NYHA class III-IV (HR: 2.25, 95% CI: 1.28-3.95), concomitant valvular heart disease (HR: 1.98, 95% CI: 1.01-3.85), and higher creatinine (HR: 1.003, 95% CI: 1.001-1.004) were independent risk factors for the primary endpoint in HFimpEF patients. HFrEF patients without a history of alcohol consumption, non-NYHA class III-IV, without dilated cardiomyopathy, concomitant hypertension, -blockers use, and lower uric acid were more likely to have LVEF improvement. Although the prognosis of HFimpEF patients was better than that of HFrEF patients, older age, NYHA class III-IV, concomitant valvular heart disease, and higher creatinine were still risk factors for cardiovascular events in HFimpEF patients.

Targeted Quantitative Plasma Metabolomics Identifies Metabolite Signatures that Distinguish Heart Failure with Reduced and Preserved Ejection Fraction.

Two general phenotypes of heart failure (HF) are recognized: HF with reduced ejection fraction (HFrEF) and with preserved EF (HFpEF). To develop HF disease phenotype-specific approaches to define and guide treatment, distinguishing biomarkers are needed. The goal of this study was to utilize quantitative metabolomics on a large, diverse population to replicate and extend existing knowledge of the plasma metabolic signatures in human HF. Quantitative, targeted LC/MS plasma metabolomics was conducted on 787 samples collected by the Penn Medicine BioBank from subjects with HFrEF (n=219), HFpEF (n=357), and matched non-failing Controls (n=211). A total of 90 metabolites were analyzed, comprising 28 amino acids, 8 organic acids, and 54 acylcarnitines. 733 of these samples were also processed via an OLINK protein panel for proteomic profiling. Consistent with previous studies, unsaturated forms of medium/long chain acylcarnitines were elevated in the HFrEF group to a greater extent than the HFpEF group compared to Controls. A number of amino acid derivatives, including 1- and 3-methylhistidine, homocitrulline, and symmetric (SDMA) and asymmetric (ADMA) dimethylarginine were elevated in HF, with ADMA elevated uniquely in HFpEF. Plasma branched-chain amino acids (BCAA) were not different across the groups; however, short-chain acylcarnitine species indicative of BCAA catabolism were significantly elevated in both HF groups. The ketone body 3-hydroxybutyrate (3-HBA) and its metabolite C4-OH carnitine were uniquely elevated in the HFrEF group. Linear regression models demonstrated a significant correlation between plasma 3-HBA and NT-proBNP in both forms of HF, stronger in HFrEF. These results identify plasma signatures that are shared as well as potentially distinguish between HFrEF and HFpEF. Metabolite markers for ketogenic metabolic reprogramming in extra-cardiac tissues were identified as unique signatures in the HFrEF group, possibly related to the lipolytic action of increased levels of BNP. Future studies will be necessary to further validate these metabolites as HF biosignatures that may guide phenotype-specific therapeutics and provide insight into the systemic metabolic responses to HFpEF and HFrEF.

Increased Risk of End-Stage Kidney Disease in Patients with Chronic Kidney Disease and Heart Failure with Reduced Ejection Fraction.

The prevalence of heart failure (HF) is more common in people with advanced non-dialysis chronic kidney disease (ND-CKD) compared to the general population. It is well known that HF with reduced ejection fraction (HFrEF) is associated with a higher risk of mortality in people with ND-CKD. However, the impact of HFrEF on progression into end-stage kidney disease (ESKD) is not well studied. Our study aimed to examine the independent association of HFrEF on progression to ESKD after correcting for confounding factors using two methods of propensity scoring. This study used data from the Salford Kidney Study, a longitudinal study which has recruited more than 3,000 patients with ND-CKD since 2002. Patients without a history of HF during the recruitment questionnaire were included in the control group. Patients with a reported history of HF and echo showing left ventricular ejection fraction &lt;40% at enrolment were included in the HFrEF group. Two propensity score methods were used to attenuate the effects of confounding factors between the two groups - propensity score matching (PSM) and inverse probability weighting (IPW). Univariate and multivariate Cox-regression analyses were performed. A total of 2,383 patients were included in the analysis. Patients with HFrEF had significantly higher median age and a higher percentage of male gender compared to patients with no HF (72.5 vs. 66.6 years and 71.8 vs. 61.1%, respectively). Univariate and 5 models of multivariate Cox-regression analysis showed that HFrEF in people with CKD was a strong predictor for a higher incidence of ESKD (model 5: hazard ratio 1.38; 95% confidence interval = 1.01-1.90; p = 0.044). The association between HFrEF and the risk of ESKD remained significant after using the PSM and the IPW methods. Patients with concomitant advanced ND-CKD and prevalent HFrEF were found to have a higher risk of ESKD when compared to patients with no HF. This risk persists despite the adjustment of confounding factors using PSM and IPW.

Comparative Analysis of Heart Failure with Preserved Vs Reduced Ejection Fraction: Patient Characteristics, Outcomes, Mortality Prediction, and Machine Learning Model Development in the JoHFR.

Heart failure (HF) is a global health challenge affecting millions, with significant variations in patient characteristics and outcomes based on ejection fraction. This study aimed to differentiate between HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF) with respect to patient characteristics, risk factors, comorbidities, and clinical outcomes, incorporating advanced machine learning models for mortality prediction. The study included 1861 HF patients from 21 centers in Jordan, categorized into HFrEF (EF <40%) and HFpEF (EF ≥ 50%) groups. Data were collected from 2021 to 2023, and machine learning models were employed for mortality prediction. Among the participants, 29.7% had HFpEF and 70.3% HFrEF. Significant differences were noted in demographics and comorbidities, with a higher prevalence of males, younger age, smoking, and familial history of premature ASCVD in the HFrEF group. HFpEF patients were typically older, with higher rates of diabetes, hypertension, and obesity. Machine learning analysis, mainly using the Random Forest Classifier, demonstrated significant predictive capability for mortality with an accuracy of 0.9002 and an AUC of 0.7556. Other models, including Logistic Regression, SVM, and XGBoost, also showed promising results. Length of hospital stay, need for mechanical ventilation, and number of hospital admissions were the top predictors of mortality in our study. The study underscores the heterogeneity in patient profiles between HFrEF and HFpEF. Integrating machine learning models offers valuable insights into mortality risk prediction in HF patients, highlighting the potential of advanced analytics in improving patient care and outcomes.

Predictive value of early-phase heart rate reduction for subsequent recovery of left ventricular systolic function in heart failure with reduced ejection fraction.

Predictors of heart failure with recovered ejection fraction (HFrecEF) remain to be fully elucidated. This study investigated the impact of heart rate and its change on the recovery of left ventricular ejection fraction (LVEF) in heart failure with reduced ejection fraction (HFrEF). From 398 outpatients who had a history of hospitalisation for heart failure, 138 subjects diagnosed as HFrEF (LVEF < 40%) on heart failure hospitalisation were enrolled and longitudinally surveyed. During follow-up periods more than one year, 64 and 46 patients were identified as HFrecEF (improved LVEF to ≥ 40% and its increase of ≥ 10 points) and persistent HFrEF, respectively. In the overall subjects, the reduction of heart rate through the observation periods was closely correlated with the improvement of LVEF (r = -0.508, p < 0.001). Heart rate on hospital admission for heart failure was markedly higher in patients with HFrecEF (112 ± 26 bpm) than in those with persistent HFrEF (90±18 bpm). Whereas heart rate at the first outpatient visit after discharge was already lower in the HFrecEF group (80 ± 13 vs. 85 ± 13 bpm in the persistent HFrEF group). A multivariate logistic regression analysis revealed that the decrease in heart rate from admission to the first visit after discharge was a significant determinant of HFrecEF (p < 0.001), independently of confounding factors such as ischemic heart disease and baseline LVEF and left ventricular dimension. Our findings suggest that heart rate reduction in the early phase after heart failure onset is a powerful independent predictor of the subsequent recovery of LVEF in HFrEF patients.

Detecting heart failure from B-mode ultrasound characterization of arterial pulse waves.

This study investigated the sensitivity and specificity of identifying heart failure with reduced ejection fraction (HFrEF) from measurements of the intensity and timing of arterial pulse waves. Previously validated methods combining ultrafast B-mode ultrasound, plane-wave transmission, singular value decomposition (SVD), and speckle tracking were used to characterize the compression and decompression ("S" and "D") waves occurring in early and late systole, respectively, in the carotid arteries of outpatients with left ventricular ejection fraction (LVEF) < 40%, determined by echocardiography, and signs and symptoms of heart failure, or with LVEF ≥ 50% and no signs or symptoms of heart failure. On average, the HFrEF group had significantly reduced S-wave intensity and energy, a greater interval between the R wave of the ECG and the S wave, a reduced interval between the S and D waves, and an increase in the S-wave shift (SWS), a novel metric that characterizes the shift in timing of the S wave away from the R wave of the ECG and toward the D wave (all P < 0.01). Receiver operating characteristics (ROCs) were used to quantify for the first time how well wave metrics classified individual participants. S-wave intensity and energy gave areas under the ROC of 0.76-0.83, the ECG-S-wave interval gave 0.85-0.88, and the S-wave shift gave 0.88-0.92. Hence the methods, which are simple to use and do not require complex interpretation, provide sensitive and specific identification of HFrEF. If similar results were obtained in primary care, they could form the basis of techniques for heart failure screening.NEW & NOTEWORTHY We show that heart failure with reduced ejection fraction can be detected with excellent sensitivity and specificity in individual patients by using B-mode ultrasound to detect altered pulse wave intensity and timing in the carotid artery.

Artificial intelligence-assisted automated heart failure detection and classification from electronic health records.

Electronic health records (EHR) linked to Digital Imaging and Communications in Medicine (DICOM), biological specimens, and deep learning (DL) algorithms could potentially improve patient care through automated case detection and surveillance. We hypothesized that by applying keyword searches to routinely stored EHR, in conjunction with AI-powered automated reading of DICOM echocardiography images and analysing biomarkers from routinely stored plasma samples, we were able to identify heart failure (HF) patients. We used EHR data between 1993 and 2021 from Tayside and Fife (~20% of the Scottish population). We implemented a keyword search strategy complemented by filtering based on International Classification of Diseases (ICD) codes and prescription data to EHR data set. We then applied DL for the automated interpretation of echocardiographic DICOM images. These methods were then integrated with the analysis of routinely stored plasma samples to identify and categorize patients into HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF), and controls without HF. The final diagnosis was verified through a manual review of medical records, measured natriuretic peptides in stored blood samples, and by comparing clinical outcomes among groups. In our study, we selected the patient cohort through an algorithmic workflow. This process started with 60850 EHR data and resulted in a final cohort of 578 patients, divided into 186 controls, 236 with HFpEF, and 156 with HFrEF, after excluding individuals with mismatched data or significant valvular heart disease. The analysis of baseline characteristics revealed that compared with controls, patients with HFrEF and HFpEF were generally older, had higher BMI, and showed a greater prevalence of co-morbidities such as diabetes, COPD, and CKD. Echocardiographic analysis, enhanced by DL, provided high coverage, and detailed insights into cardiac function, showing significant differences in parameters such as left ventricular diameter, ejection fraction, and myocardial strain among the groups. Clinical outcomes highlighted a higher risk of hospitalization and mortality for HF patients compared with controls, with particularly elevated risk ratios for both HFrEF and HFpEF groups. The concordance between the algorithmic selection of patients and manual validation demonstrated high accuracy, supporting the effectiveness of our approach in identifying and classifying HF subtypes, which could significantly impact future HF diagnosis and management strategies. Our study highlights the feasibility of combining keyword searches in EHR, DL automated echocardiographic interpretation, and biobank resources to identify HF subtypes.

Atrial Fibrillation Ablation in Heart Failure With Reduced vs Preserved Ejection Fraction

Catheter ablation is associated with reduced heart failure (HF) hospitalization and death in select patients with atrial fibrillation (AF) and heart failure with reduced ejection fraction (HFrEF). However, the benefit in patients with HF with preserved ejection fraction (HFpEF) is uncertain. To investigate whether catheter ablation for AF is associated with reduced HF-related outcomes according to HF phenotype. A systematic search of MEDLINE, Embase, and Cochrane Central was conducted among studies published from inception to September 2023. Parallel-group randomized clinical trials (RCTs) comparing catheter ablation with conventional rate or rhythm control therapies in patients with HF, New York Heart Association functional class II or greater, and a history of paroxysmal or persistent AF were included. Pairs of independent reviewers screened 7531 titles and abstracts, of which 12 RCTs and 4 substudies met selection criteria. Data were abstracted in duplicate according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Pooled effect estimates were calculated using random-effects Mantel-Haenszel models. Interaction P values were used to test for subgroup differences. The primary outcome was HF events, defined as HF hospitalization, clinically significant worsening of HF, or unscheduled visits to a clinician for treatment intensification. Secondary outcomes included cardiovascular and all-cause mortality. A total of 12 RCTs with 2465 participants (mean [SD] age, 65.3 [9.7] years; 658 females [26.7%]) were included; there were 1552 participants with HFrEF and 913 participants with HFpEF. Compared with conventional rate or rhythm control, catheter ablation was associated with reduced risk of HF events in HFrEF (risk ratio [RR], 0.59; 95% CI, 0.48-0.72), while there was no benefit in patients with HFpEF (RR, 0.93; 95% CI, 0.65-1.32) (P for interaction = .03). Catheter ablation was associated with reduced risk of cardiovascular death compared with conventional therapies in HFrEF (RR, 0.49; 95% CI, 0.34-0.70) but a differential association was not detected in HFpEF (RR, 0.91; 95% CI, 0.46-1.79) (P for interaction = .12). Similarly, no difference in the association of catheter ablation with all-cause mortality was found between HFrEF (RR vs conventional therapies, 0.63; 95% CI, 0.47-0.86) and HFpEF (RR vs conventional therapies, 0.95; 95% CI, 0.39-2.30) groups (P for interaction = .39). This study found that catheter ablation for AF was associated with reduced risk of HF events in patients with HFrEF but had limited or no benefit in HFpEF. Results from ongoing trials may further elucidate the role of catheter ablation for AF in HFpEF.

Diabetes mellitus does not alter mortality or hospitalisation risk in patients with newly diagnosed heart failure with preserved ejection fraction: Time to rethink pathophysiological models of disease progression.

Type 2 diabetes is a common and adverse prognostic co-morbidity for patients with heart failure with reduced ejection fraction (HFrEF). The effect of diabetes on long-term outcomes for heart failure with preserved ejection fraction (HFpEF) is less established. Prospective cohort study of patients referred to a regional HF clinic with newly diagnosed with HFrEF and HFpEF according to the 2016 European Society of Cardiology guidelines. The association between diabetes, all-cause mortality and hospitalisation was quantified using Kaplan-Meier or Cox regression analysis. Between 1st May 2012 and 1st May 2013, of 960 unselected consecutive patients referred with suspected HF, 464 and 314 patients met the criteria for HFpEF and HFrEF respectively. Within HFpEF and HFrEF groups, patients with diabetes were more frequently male and in both groups patients with diabetes were more likely to be treated with β-adrenoceptor antagonists and angiotensin converting enzyme inhibitors. After adjustment for age, sex, medical therapy and co-morbidities, diabetes was associated with increased mortality in individuals with HFrEF (HR 1.46 95% CI: 1.05-2.02; p = .023), but not in those with HFpEF (HR 1.26 95% CI 0.92-1.72; p = .146). In unselected patients with newly diagnosed HF, diabetes is not an adverse prognostic marker in patients with HFpEF, but is in HFrEF.

The efficacy and safety of cryoballoon atrial fibrillation ablation in patients with heart failure: A systematic review and meta-analysis

IntroductionWhile atrial fibrillation (AF) ablation has proven beneficial for heart failure (HF) patients, most reports were performed with radiofrequency ablation. We aimed to evaluate the efficacy and safety of cryoballoon AF ablation in patients with HFrEF. MethodWe comprehensively searched the databases of MEDLINE, EMBASE, and Cochrane database from inception to December 2022. Studies that reported the outcomes of freedom from atrial arrhythmia, complications, NYHA functional class (NYHA FC), and left ventricular ejection fraction (LVEF) after Cryoballoon AF ablation in HF patients were included. Data from each study were combined with a random-effects model. ResultA total of 9 studies observational studies with 1414 HF patients were included. Five studies had only HF with reduced ejection fraction (HFrEF), 1 study with HF with preserved ejection fraction (HFpEF), and others with mixed HF types. Freedom from AA in HFrEF at 12 months was 64% (95% CI 56–71%, I2 58%). There was a significant improvement of LVEF in these patients with a standard mean difference of 13% (95% CI 8.6–17.5%, I2 99% P < 0.001. The complication rate in HFrEF group was 6% (95% CI 4–10%, I2 0%). The risk of recurrence of atrial arrhythmia was not significantly different between HF and no HF patients (RR 1.34, 95% CI 0.8–2.23, I2 76%). ConclusionCryoballoon AF ablation is effective in HFrEF patients comparable to radiofrequency ablation. The complication rate was low.

Effects of High-Intensity Interval Training Using the 3/7 Resistance Training Method on Metabolic Stress in People with Heart Failure and Coronary Artery Disease: A Randomized Cross-Over Study.

The 3/7 resistance training (RT) method involves performing sets with increasing numbers of repetitions, and shorter rest periods than the 3x9 method. Therefore, it could induce more metabolic stress in people with heart failure with reduced ejection fraction (HFrEF) or coronary artery disease (CAD). This randomized cross-over study tested this hypothesis. Eleven individuals with HFrEF and thirteen with CAD performed high-intensity interval training (HIIT) for 30 min, followed by 3x9 or 3/7 RT according to group allocation. pH, HCO3-, lactate, and growth hormone were measured at baseline, after HIIT, and after RT. pH and HCO3- decreased, and lactate increased after both RT methods. In the CAD group, lactate increased more (6.99 ± 2.37 vs. 9.20 ± 3.57 mmol/L, p = 0.025), pH tended to decrease more (7.29 ± 0.06 vs. 7.33 ± 0.04, p = 0.060), and HCO3- decreased more (18.6 ± 3.1 vs. 21.1 ± 2.5 mmol/L, p = 0.004) after 3/7 than 3x9 RT. In the HFrEF group, lactate, pH, and HCO3- concentrations did not differ between RT methods (all p > 0.248). RT did not increase growth hormone in either patient group. In conclusion, the 3/7 RT method induced more metabolic stress than the 3x9 method in people with CAD but not HFrEF.

Left Ventricular End-Systolic Diameter May Predict Persistent Heart Failure with Reduced Ejection Fraction.

Patients with persistent heart failure (HF) with reduced ejection fraction (HFrEF) have a poorer prognosis than those with HF with improved ejection fraction (HFimpEF). However, data on the predictive value of echocardiographic parameters for persistent HFrEF are lacking. We retrospectively studied 443 patients who were diagnosed with HFrEF (EF ≤ 40%) during hospitalization and underwent echocardiography at the 1-year follow-up. We divided them into the 2 groups: HFimpEF (EF > 40%) and persistent HFrEF group at 1-year follow-up, and assessed the predictive value of echocardiographic parameters at discharge for persistent HFrEF. In total, 301/443 patients (68%) were diagnosed with persistent HFrEF and 142/443 (32%) with HFimpEF at the 1-year follow-up. Kaplan-Meier analysis revealed that the persistent HFrEF group had a poorer prognosis than the HFimpEF group (log-rank, P < 0.001). Receiver operating characteristic curve analysis revealed that left ventricular end-systolic diameter (LVESD) had the highest area under the curve (AUC) (0.70; 95% confidence interval [CI]: 0.64-0.75; cutoff value: 55 mm) among various echocardiographic parameters. LVESD was an independent predictor of persistent HFrEF at the 1-year follow-up (odds ratio: 1.07, 95%CI: 1.02-1.12) upon multivariable logistic regression analysis. The incidence of persistent HFrEF was higher in patients with an LVESD ≥ 55 mm than in those with an LVESD < 55 mm (81% versus 55%, Fisher's exact test, P < 0.001). In conclusion, an LVESD (≥ 55 mm) was associated with persistent HFrEF. Focusing on LVESD in daily practice may help clinicians with risk stratification for decision-making regarding management in patients with advanced HF refractory to guideline-directed medical therapy.

Abstract 12727: Liver Elasticity in Elderly Heart Failure Patient

Introduction: Liver elastography is a novel ultrasound technique assessing elasticity of liver tissue. Clinical indication of liver elastography remains unrevealed. Moreover, reports about relationship between liver stiffness and heart failure subtypes haven’t well been published. Hypothesis: We have investigated the cardio-hepatic interaction using liver elastography in heart failure subtypes. Methods: We prospectively enrolled 58 consecutive patients with heart failure admission from April 2022 to March 2023. Liver elastography, transthoracic echocardiography and blood sampling were done at the time of discharge from heart failure treatment. Results: Patients were divided into two groups according to the left ventricular ejection fraction (LVEF) of echocardiography: heart failure with reduced ejection fraction (HFrEF) group (EF ≦40%, n = 11) and non-HFrEF group (EF &gt;40%, n = 31). The mean age of all patients was 83 ± 11 years. The mean age and the prevalence of hypertension and diabetes mellitus was higher in non-HFrEF group than in HFrEF group. The prevalence of taking sodium glucose co-transporter 2 (SGLT2) inhibitors was lower in non-HFrEF group than in HFrEF group. LV end-diastolic diameter, LV end-systolic diameter was larger in HFrEF group than in non-HFrEF group. Tricuspid regurgitation pressure gradient (TRPG) was higher in non-HFrEF group than in HFrEF group. Inferior vena cava diameter was not different between two groups. The mean values of almost liver function tests of all patients were within the normal range. eGFR was lower in non-HFrEF group than in HFrEF group. Liver elasticity was higher in non-HFrEF group than in HFrEF group (7.1 ± 2.7 vs. 5.1 ± 1.5 hPa; P=0.008) indicating liver stiffness. Pearson’s correlation coefficient showed that liver elasticity was positively correlated with the prevalence of diabetes mellitus, LVEF, TRPG, serum creatinine, aspartate aminotransferase, γ-glutamyl transpeptidase and was negatively correlated with LV end-diastolic diameter, LV end-systolic diameter. Conclusions: Liver stiffness was elevated in EF-preserved heart failure patients. Liver elasticity was correlated with parameters of congestion (TRPG) and useful for the assessment of congestion in patients with heart failure.

Abstract 13532: Long-Term Survival of Different Heart Failure Categories in Patients Discharged Owing to Coronary Artery Disease With/Without Acute Coronary Syndrome

Background: Heart failure (HF) has been classified into distinct phenotypes based on left ventricular ejection fraction (LVEF). We conducted this retrospective cohort study to explore the long-term survival prognosis of different types of HF especially the HF with improved ejection fraction (HFimpEF) group. Methods: We collected patients who had ever been hospitalized owing to coronary artery disease or acute coronary syndrome between July 2006 and June 2017 at National Taiwan University Hospital (NTUH) and NTUH Hsin-Chu Branch. Patients were classified as (1) HF with reduced ejection fraction (HFrEF); (2) HFimpEF; (3) HF with mildly reduced ejection fraction (HFmrEF); (4) HF with preserved ejection fraction (HFpEF); according to echocardiography-derived LVEF during or after the index hospitalization. The date of the first echocardiography during or after the index hospitalization was defined as the index date. All patients were followed from their index date until death or the end of the study (December 31 2017), whichever occurred first. Results: Totally, 11549 patients were categorized into 4 groups (HFrEF group, n = 986; HFimpEF group, n = 461; HFmrEF group, n = 1454; and HFpEF group, n = 8648). The crude mortality rate during follow-up in HFrEF group, HFimpEF group, HFmrEF group, and HFpEF group was 60.4%, 28.0%, 36.6%, and 18.3%, respectively. Patients in HFimpEF group, HFmrEF group, and HFpEF group all possessed a significantly reduced risk of all-cause mortality compared with HFrEF group (adjusted hazard ratio [HR] 0.241, 95% confidence interval [CI] 0.199-0.292 for HFimpEF group; 0.443, 95% CI 0.393-0.500 for HFmrEF group; and 0.292, 95% CI 0.262-0.324 for HFpEF group). Using the time-varying Cox regression model to deal with the immortal time bias, we found a persistent lower risk of all-cause mortality in patients in HFimpEF group compared with patients in HFrEF group (adjusted HR 0.579, 95% CI 0.467-0.718). Conclusion: Patients in HFrEF group had the worst long-term survival prognosis and patient in HFpEF group had the best long-term survival prognosis. Patients in HFimpEF group represented a distinctive population with good survival prognosis than HFrEF group and HFmrEF group.

Abstract 12466: Targeted Quantitative Plasma Metabolomics Identifies Metabolite Signatures That Distinguish Heart Failure With Reduced and Preserved Ejection Fraction

Background: Despite recent advances, heart failure (HF) remains a high burden disease and is largely treated with a “one-size-fits-all” approach. Two phenotypes are recognized: HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF). To develop HF disease-specific approaches to define and guide treatment, distinguishing biomarkers are needed. Methods: We conducted quantitative, targeted LC/MS plasma metabolomics on 787 samples collected by the Penn Medicine BioBank from patients with HFrEF (n=219), HFpEF (n=357), and matched non-failing Controls (n=211). Sample collection time from last meal was not controlled. A total of 97 metabolites were analyzed, comprising 30 amino acids, 8 organic acids, and 59 acylcarnitines classified by carbon length. Results: 3-hydroxybutyrate (3-HBA) was uniquely and significantly elevated in the HFrEF group [mean +/- SEM: HFpEF, 108.7(+/-7.15); HFrEF, 148.0(+/-12.4); Control, 86.29(+/-8.01); p &lt;.0001]. The 3-HBA metabolite C4-OH butyryl-carnitine also showed a similar HFrEF-specific pattern. Consistent with previous studies, long/very-long chain acylcarnitines were elevated in the HFrEF group to a much greater extent than the HFpEF group compared to Controls. Branched-chain amino acid (BCAA) levels were not different across the groups; however, acylcarnitine species indicative of BCAA degradation, including C04 Isobutyryl, C04-DC Methylmalonyl, C04-DC Succinyl, and C05 2-Methylbutyryl, were significantly elevated in both HF groups compared to Controls. Lastly, we found that the amino acid, asymmetric dimethylarginine, which promotes endothelial dysfunction and vasoconstriction, was uniquely elevated in the HFpEF cohort [mean +/- SEM: HFpEF, 1.236(+/- .019); HFrEF, 1.105(+/- .027); Control, 1.077(+/- .022); p &lt; .0001]. Conclusions: Taken together, these results identify plasma metabolite signatures that potentially distinguish between HFrEF and HFpEF and suggest patterns of metabolic re-programming in extra-cardiac tissue in the context of heart failure. Future studies will be necessary to define the utility of these metabolites as biosignatures to help guide therapeutics and to identify the underlying physiology responsible for these observations.

Abstract 18513: Causes and Predictors of 30-day Readmissions Following Covid-19 Hospitalizations and Co-Existing Acute Heart Failure: Insights From National Readmission Database 2020

Introduction: COVID-19 infection notably impacts the cardiovascular system, with evidence of higher in-hospital mortality in patients with acute heart failure (AHF) and COVID-19 infection. However, less is known about short-term outcomes following discharge. Therefore, we sought to analyze readmission data in COVID-19 hospitalizations with AHF from the National Readmission Database (NRD). Methods: NRD (2020) was queried to identify all COVID-19 hospitalizations and co-existing AHF using ICD-10 CM codes. The group was then stratified into heart failure with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF). The outcomes were 30-day readmission rate, length of stay (LOS), total hospital charge (THC), and predictors of readmission. Multivariate/univariate logistic and linear regression analyses were used to analyze the outcomes and adjust for possible confounders. Results: A total of 53,337 COVID-19 admissions with co-existing AHF were identified, of which 38,401 were discharged alive. Within 30 days from discharge, 8,159 (21.26%) were readmitted. Upon stratification, 51% belonged to the HFrEF group and were found to have scarcely higher 30 days readmission rates than encounters with HFpEF (21.46% vs. 21.14%). Readmissions lead to an additional mean THC of $85,687 and a mean LOS of 7.8 days. The top five all-causes of readmissions were COVID-19 infection (24.8%), heart failure (16.2%), sepsis (15.4%), acute kidney injury (2.2%), and pneumonia (1.2%). Figure-1 shows a multivariate analysis of independent factors associated with readmissions. Conclusions: Our analysis showed a 21.26% 30-days readmission rate following acute heart failure during COVID-19 infection. Cirrhosis, anemia, diabetes mellitus, chronic lung diseases, and discharge against medical advice were significant readmission predictors. Optimizing these co-morbidities during index admission may reduce readmissions and overall financial burden.