Types Of Heart Failure Research Articles

Echocardiographic predictors of atrial fibrillation recurrence after catheter ablation in patients with heart failure.

Abstract Background Atrial fibrillation (AF) and heart failure (HF) often occur together. Restoring and maintaining sinus rhythm in these patients appears to be beneficial, however difficult. Purpose The aim of the study was to assess AF recurrence after catheter ablation and its predictors in patients with diagnosed HF. Methods Consecutive patients with AF undergoing first-time AF ablation in 2019-2022 were enrolled. Comprehensive echocardiography was performed in all patients on the day of ablation. AF recurrence was assessed during a follow-up consisting of outpatient visits/televisits and 7-day Holter monitoring (at 6 and 12 months after ablation and annually thereafter). Results Out of total 293 patients enrolled in the study (7 of whom were excluded due to poor image quality), 27.6% (n=81) were diagnosed with HF (12.3% with reduced ejection fraction – HFrEF; 27.2% with mildly reduced EF – HFmrEF, and 60.5% with preserved EF – HFpEF). Median follow-up was at 12 months (IQR 6–16). The incidence of AF recurrence did not differ between the group with and without HF (33.3% vs. 30.7%, p=0.67). There were no differences in AF recurrence rate between the different types of HF (30% AF recurrence rate in HFrEF, 31.8% in HFmrEF and 34.7% in HFpEF, p=0.75). The AF recurrence rate did not vary between patients with AF during echocardiography and those with sinus rhythm (p=0.24), so therefore a combined analysis of them was performed. The groups of HF patients with and without AF recurrence did not differ in terms of demographic data, comorbidities, or results of baseline laboratory tests. In a univariable Cox regression analysis only echocardiographic parameters (left atrial (LA) volume index, LA reservoir strain, LA emptying fraction - LAEF, E wave, e’average, E/e’ average ratio, LA appendage velocity) correlated significantly with AF recurrence in the group of patients with HF. In a multivariable Cox regression analysis, after exclusion of interdependent values, only LAEF (determined automatically using automated functional imaging of the LA) remained significant predictor of the AF recurrence (hazard ratio (HR) 0.962, 95% confidence interval (CI) 0.926-0.998, p=0.043). An LAEF threshold of 35% presented with 62% sensitivity and 85% specificity in predicting AF recurrence (with area under curve 0.733). Conclusions AF recurrence rate after ablation was similar in AF patients with and without diagnosed HF as well as in the different types of HF. LAEF was found to be the best predictor of AF recurrence in patients with AF and HF undergoing catheter ablation.

Frailty determinants in heart failure: Inflammatory markers, cognitive impairment and psychosocial interaction.

This study aimed to identify factors associated with frailty in heart failure (HF) patients, focusing on demographic, biochemical and health-related variables. It also explored the correlation between frailty and comorbidities such as malnutrition, cognitive impairment and depression, assessing how these factors interact to influence frailty risk. A total of 250 HF patients (mean age 73.5±7.2years; 45.6% female) hospitalized for acute decompensated HF were included. Frailty was assessed using Fried phenotype criteria. Cognitive function, depression and nutritional status were evaluated using validated instruments [Mini-Mental State Examination (MMSE), Patient Health Questionnaire-9 (PHQ-9) and Mini Nutritional Assessment (MNA)]. Biochemical markers included C-reactive protein (CRP), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), haemoglobin, estimated glomerular filtration rate (eGFR) and systolic blood pressure (SBP). Statistical analyses, including logistic regression, were performed to assess associations and odds ratios (ORs) for frailty, adjusted for inflammation and HF type. Frailty was present in 60.4% of patients. Frail individuals exhibited significantly higher CRP (median 4.60 vs. 2.54mg/L, P<0.001) and NT-proBNP (median 2558.8 vs. 1102.6pg/mL, P=0.001) and lower haemoglobin (13.7 vs. 14.3g/dL, P=0.012), eGFR (62 vs. 71mL/min/1.73m2, P=0.025) and SBP (130 vs. 134mmHg, P=0.026). Each 10% increase in CRP was associated with a 5.5% increase in frailty odds (P<0.001). Frailty was linked to cognitive impairment (OR 2.1, P=0.018), malnutrition (OR 3.0, P<0.001) and depression (OR 3.1, P<0.001), while high adherence to treatment reduced frailty risk by 78.9% (P=0.027). Interactions were observed between cognitive impairment and body mass index (BMI) (P=0.020), where higher BMI mitigated the frailty odds difference between cognitively impaired and unimpaired patients. Depression's association with frailty odds varied by adherence levels (P=0.034) and central obesity (P=0.047), with the absence of depression offering protection against frailty in patients with central obesity. These interactions remained significant after adjustment for HF type and left ventricular ejection fraction (LVEF) and were consistent across stratifications by these factors. Frailty in HF is influenced by inflammatory markers, cognitive impairment and psychosocial factors. Elevated CRP and NT-proBNP were strong predictors of frailty. Cognitive impairment and depression were key modifiable factors, interacting with BMI, adherence and obesity. Targeting these factors with early interventions could mitigate frailty risk, improving outcomes and quality of life in HF patients.

Assessing the risk of heart failure in type 2 diabetes: a prediction algorithm to sustain the evaluation of NT-proBNP in primary care.

Heart failure (HF) is a disease that leads to approximately 300,000 fatalities annually in Europe and 250,000 deaths each year in the United States. Type 2 Diabetes Mellitus (T2DM) is a significant risk factor for HF, and testing for N-terminal (NT)-pro hormone BNP (NT-proBNP) can aid in early detection of HF in T2DM patients. We therefore developed and validated the HFriskT2DM-HScore, an algorithm to predict the risk of HF in T2DM patients, so guiding NT-proBNP investigation in a primary care setting. Using a primary care database, we formed a cohort of patients aged ≥18 years diagnosed with T2DM between 2002 and 2022. A multivariate Cox model was adopted to assess the determinants associated with the occurrence of HF to combine them to form an individual score. Within a cohort of 167,618 patients (52.3% males; mean age 64.4 (SD: 14.4); HF rate equal to 6.7 cases per 1000 person-years), we developed the HFriskT2DM-HScore. When it was applied to the validation sub-cohort we found an explained variation and discrimination value of 43% (95% CI: 42-44) and 81% (95% CI: 0.80-0.83), respectively. Calibration slope was equal to 0.93 (95% CI: 0.81-1.1; p = 0.3123). The HFriskT2DM-HScore might be implemented as a decision support system for primary care to appropriately ease the prescription of NT-proBNP and early identification of HF.

Diabetes, Subclinical Myocardial Injury or Stress and Risk of Heart Failure Subtypes: The Jackson Heart Study

OBJECTIVE To assess the extent to which the concomitant presence of subclinical myocardial injury or stress and diabetes affects the risk of heart failure (HF) subtypes. RESEARCH DESIGN AND METHODS The Jackson Heart Study included Black adults, categorized based on diabetes status, high-sensitivity cardiac troponin I (hs-cTnI), and brain natriuretic peptide (BNP) levels. Subclinical myocardial injury was defined as hs-cTnI ≥4 ng/L in women and ≥6 ng/L in men, and subclinical myocardial stress as BNP ≥35 pg/mL. The study outcomes included incident HF, HF with preserved ejection fraction (HFpEF), and HF with reduced ejection fraction (HFrEF). RESULTS Among 3,484 participants (mean age 54.6 years, 63.2% women, 22.3% with diabetes, 26.4% with subclinical myocardial injury, 9.4% with subclinical myocardial stress), 306 developed HF (151 HFpEF and 139 HFrEF) over 12 years. Compared with individuals with no diabetes and no subclinical myocardial injury at recruitment, participants with diabetes and subclinical myocardial injury had a higher HF risk (hazard ratio [HR] 3.84, 95% CI 2.60–5.66), HFpEF (HR 3.68, 95% CI 2.13–6.36), and HFrEF (HR 4.26, 95% CI 2.40–7.53). The HRs associated with the presence of diabetes and subclinical myocardial stress versus their joint absence were 4.03 (95% CI 2.50–6.51), 5.71 (95% CI 3.11–10.47), and 2.13 (95% CI 0.88–5.17) for HF, HFpEF, and HFrEF, respectively. There was no significant diabetes status and cardiac biomarkers interaction. CONCLUSIONS Both diabetes and subclinical myocardial damage significantly increase the risk of all HF types among Black individuals.

Diagnosing and managing patients with heart failure with preserved ejection fraction: a consensus survey

AimAs heart failure (HF) with preserved ejection fraction (HFpEF) prevalence increases, it remains frequently underdiagnosed and poorly managed. Recent positive pharmacological trials have increased interest in HFpEF but challenges of...

The risk of death according to left ventricular ejection fraction and right ventricular dilatation in 17 321 adults with heart failure from 40 high-, middle- and low-income countries-A Global Congestive Heart Failure (G-CHF) study.

The aim of this study was to describe the prognostic importance of left ventricular ejection fraction (LVEF) versus right ventricular (RV) dilatation and dysfunction in patients with heart failure (HF) from countries of different income levels. We enrolled 17 321 participants with HF from 40 countries. Participants were followed for a median (25th-75th percentile) of 2.1 (2.0-4.6) years. Cox proportional hazards models were performed with adjustment for age, sex, HF aetiology, diabetes, atrial fibrillation, chronic obstructive pulmonary disease, tobacco and alcohol use, functional class, and the use of HF medications, blood pressure, serum creatinine and HF duration. During follow-up, 5738 (33%) participants died and 3569 (21%) were hospitalized for HF. Compared with LVEF ≥50%, the hazard ratios (HR) for death were 0.88 (95% confidence interval [CI] 0.80-0.97, p = 0.009) in patients with LVEF 40-49%, 0.96 (95% CI 0.88-1.05, p = 0.40) for LVEF 30-39%, and 1.18 (95% CI 1.08-1.29, p < 0.0001) for LVEF <30%. RV enlargement was associated with an increased risk of death (HR 1.35, 95% CI 1.26-1.44, p < 0.0001). The relationship between LVEF and death differed according to HF aetiology (interaction p = 0.0010). In ischaemic HF and idiopathic dilated cardiomyopathy, there was a continuous inverse association between LVEF and the risk of death, but in hypertensive, valvular and other HF types, there was no association between LVEF and the risk of mortality. Reduced LVEF was associated with worse prognosis in ischaemic and idiopathic dilated cardiomyopathy but not in HF of other causes. RV enlargement was associated with a more marked increase in the risk of death.

Assessment of Contributing Risk Factors Leading to Heart Failure in Patients Who Are Methamphetamine Users.

Methamphetamine abuse is a public health problem across the world, and the cardiovascular system experiences a significant effect on the myocardium over time. Methamphetamine is a common cause of heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF). The prevalence and risk factors for HFpEF and HFrEF in this patient population remain unclear. This retrospective case-control study is based on a chart review of patients from 139 Hospital Corporation of America (HCA) community hospitals across the United States from January 2013 to December 2017. Active methamphetamine users were identified based on International Classification of Diseases (ICD)codes and a positive urine drug screen during hospitalization. The total number of patients was then divided into two groups: heart failure (HF) vs. no HF. Then exclusion criteria were applied to remove any possible characteristics that might confound the data. The number of patients left was then analyzed. This study identified 9,518 active methamphetamine users, with 403 patients (4.23%) having HF, 41 having unspecified HF, and 51 having HFpEF only, vs. 311 having HFrEF only, compared to 9,115 in the control group without HF. After exclusion criteria were applied, the HF group had 166 patients, and the control group had 398 patients. Heart failure was significantly higher in men, 65.7% men compared to 34.3% women (adjusted odds ratio (OR): 1.894, p = 0.022). The average ages of HF group patients before exclusion criteria, after exclusion criteria, and in the control group were 52.5 years, 46.5 years, and 42.7 years, respectively. The age difference between the HF group (average 46.5 years old) and the control group (average 42.7 years old) was not statistically significant (adjusted OR: 1.007, p = 0.540). However, the average age of the HFpEF population significantly differs from the HFrEF population, 70.2 years old compared to 47.1 years old, respectively (adjusted OR: 1.053, p = 0.001). Female patients appeared to be more likely to have HFpEF (70.6%) compared to HFrEF (18.9%, adjusted OR: 3.738, p < 0.001). Amongst methamphetamine users who develop HF, men appeared to be affected more compared to women. This difference may stem from the differences in activities between men and women. On the other hand, age appeared to not play a role when viewing the entire HF group as a whole. However, when broken down into reduced and preserved groups, age appeared to play a significant role in the type of HF that methamphetamine users may develop. The HFpEF age in methamphetamine users appeared to follow the trend of the general population age with HFpEF. The HFrEF rate was about six times higher among methamphetamine users, excluding the population with unspecified HF. Higher rates of methamphetamine abuse are prompting further studies and programs to reduce cardiac morbidity and mortality in this group and decrease the burden on health systems.

Intercellular Mitochondrial transfer: Therapeutic implications for energy metabolism in heart failure.

Heart failure (HF) remains one of the leading causes of high morbidity and mortality globally. Impaired cardiac energy metabolism plays a critical role in the pathological progression of HF. Various forms of HF exhibit marked differences in energy metabolism, particularly in mitochondrial function and substrate utilization. Recent studies have increasingly highlighted that improving energy metabolism in HF patients as a crucial treatment strategy. Mitochondrial transfer is emerging as a promising and precisely regulated therapeutic strategy for treating metabolic disorders. This paper specifically reviews the characteristics of mitochondrial energy metabolism across different types of HF and explores the modes and mechanisms of mitochondrial transfer between different cell types in the heart, such as cardiomyocytes, fibroblasts, and immune cells. We focused on the therapeutic potential of intercellular mitochondrial transfer in improving energy metabolism disorders in HF. We also discuss the role of signal transduction in mitochondrial transfer, highlighting that mitochondria not only function as energy factories but also play crucial roles in intercellular communication, metabolic regulation, and tissue repair. This study provides new insights into improving energy metabolism in heart failure patients and proposes promising new therapeutic strategies.

Cardiovascular Risk Factors and Echocardiographic Findings in a Predominantly Black Population With Rheumatoid Arthritis and Heart Failure.

Among white rheumatoid arthritis (RA) cohorts, heart failure with preserved ejection fraction is the most prevalent type of heart failure (HF). We aimed to assess the type of HF affecting Black RA patients. A total of 64 patients with RA-HF were compared with age-, sex-, and race-matched RA patients without HF. Left ventricular ejection fraction, wall motion abnormalities, left ventricle (LV) mass, and wall thickness were reviewed. About 87.3% were Black and 84.4% were women, with a mean age of 69.6 ± 1.38 (± SEM) and body mass index (kg/m 2 ) of 29.6 ± 1.07. RA-HF patients had higher rates of hypertension (HTN), chronic kidney disease, and atrial fibrillation. However, 66.7% had ≥3 cardiovascular risk factors compared with RA patients without HF. 2D echocardiograms of RA-HF revealed that 62.3% had left ventricular ejection fraction ≥50%, 37% had diastolic dysfunction, and 43.1% had wall motion abnormalities. LV mass and relative wall thickness measurements indicated LV eccentric remodeling. The odds ratio for HF was 4.7 (CI, 1.5-14.53), P < 0.01, among the RA-HTN group and 3.5 (CI, 1.091-11.7) P < 0.01 among smokers. In our predominantly Black RA-HF patients, heart failure with preserved ejection fraction was the most common type of HF. HTN was associated with the highest OR for HF. Eccentric hypertrophic remodeling, a known poor prognostic indicator for cardiovascular events, was found. Further studies are required to confirm our findings.

Relationship Between Left Ventricular Ejection Fraction and ICD-10 Codes Among Patients Hospitalized With Heart Failure.

While left ventricular ejection fraction (LVEF) represents an important means by which to classify patients with heart failure (HF), relatively little is known about the distribution of LVEFs among patients hospitalized for HF based on their International Classification of Disease (ICD)-10 code. We performed a retrospective cross-sectional analysis of patients admitted to a large integrated health system within the western US between January 1, 2018 and October 1, 2022 with a principal diagnosis of HF (defined by ICD-10 codes: I50.2, systolic HF; I50.3, diastolic HF; I50.4, combined systolic and diastolic HF; I11.0, hypertensive heart disease with HF; and I13.0 and I13.2, hypertensive heart disease with HF and chronic kidney disease). Over nearly 5 years, 61,238 HF hospitalizations occurred, of which 49,772 (81%) had a LVEF available by echocardiography within the preceding 3 months. Whereas most patients hospitalized with systolic HF (n = 2220) as well as systolic and diastolic heart failure (n = 1582) had an LVEF ≤ 40% (86.2% and 74.8%, respectively), most patients hospitalized with diastolic HF (n = 1542) had an LVEF ≥ 50% (94.0%) (Figure). A much greater range of LVEFs were noted for those with hypertensive heart disease with HF (n = 18,092) and hypertensive heart disease with HF and CKD (n = 26,336) (Figure). While there was relatively good concordance between LVEF and the ICD-10 code-defined HF type for systolic HF, diastolic HF, and systolic and diastolic HF, these codes represent a small subset (~10%) of total HF hospitalizations.

Identifying Demographic and Clinical Determinants of Ischemic Workup in Patients with Heart Failure.

Background/Objectives: Coronary artery disease (CAD) is a common and treatable cause of heart failure (HF), but ischemic evaluation is often overlooked when evaluating patients with new-onset HF. Here, we sought to discern demographic and clinical predictors of ischemic workup in patients with newly diagnosed HF. Methods: A retrospective study of 200 consecutive patients with new-onset HF admitted to our safety-net hospital between 2011 and 2015 was performed. We developed a multivariate logistic regression model to analyze determinants of undergoing ischemic evaluation. Results: A total of 99 patients (49.5%) underwent ischemic workup, while 101 patients (50.5%) did not. The mean age of the cohort was 73.9 ± 16, with 50% as male and 51% as White. In total, 41.5% of patients had HF with reduced ejection fraction, and 37% of patients had HF with preserved ejection fraction. Among the patients who underwent ischemic evaluation, 63.6% received nuclear stress testing, 24.2% received cardiac catheterization, 9.1% received stress echocardiography, and 3% received computed tomography angiography. Demographic and clinical factors such as sex, age, race, presence of hypertension, hyperlipidemia, chronic kidney disease, diabetes, or obesity had no significant association with receiving ischemic workup (p > 0.05). Patients with known CAD (OR 2.816, p = 0.015) and a higher social deprivation index (SDI) (OR 1.022, p = 0.003) were significantly more likely to receive an ischemic evaluation. Atrial fibrillation was significantly negatively associated with receiving ischemic workup (OR: 0.24; p = 0.001). Conclusions: In our single-center safety-net hospital analysis, known CAD and higher SDI were significant predictors of ischemic evaluation in patients with newly diagnosed HF. Multiple demographic features, including age, sex, race, and clinical features, including HF type, hypertension, hyperlipidemia, and diabetes, had no significant correlation with ischemic workup.

Abstract 4135905: The Impact of Emergent Atrial Fibrillation in Patients With Newly Diagnosed Heart Failure and Differences in Risk Among Preserved vs. Reduced Ejection Fraction

Background: Atrial fibrillation (AF) and heart failure (HF) are associated with an increased risk of adverse events, with their diagnoses often coexisting. The impact of AF in HF needs additional study, with further delineation among HF type. Therefore, this study sought to determine the degree of AF burden among newly diagnosed HF patients and whether differences in risk exist between heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF) patients. Methods: Patients with new-onset HF between 2000-2019 were studied. To be included, patients had to have 1-year of follow-up, an ejection fraction (EF) measurement within 30 days of HF diagnosis, and no history of cancer. EF was used to define HFrEF (EF &lt;40%) and HFpEF (EF &gt; 40%). Multivariable Cox hazard regression was used to evaluate the risk of death and HF hospitalization at 1- and 3-years. Results: A total of 21,925 patients were studied with HFrEF (n=7931 [36.2%]) and HFpEF (n=13,994 [63.8%]). HFpEF patients were older (74 vs. 65 years) and more often female (53.7% vs. 33.1%). Prevalent AF was 40.5% (n=8879), being more common in HFpEF compared to HFrEF (65.2% vs. 34.8%). Among AF patients, HFpEF patients were also older (76 vs. 72 years) and more often female (52.7% vs. 30.8%) compared to HFrEF. The presence of AF was associated with an increased risk of HFpEF (OR=1.11, p=0.001). Prevalent AF was associated with an increased risk of death and follow-up HF hospitalization (Table). Death at 1-year and 3-years were similar between the HF groups (Table). However, the risk of HF hospitalization was greater among HFrEF patients (Table). Similar associations persisted when AF patients were propensity matched (Table). Conclusions: Among a newly diagnosed HF population, AF was common (40%) and was associated with an increased risk of HFpEF, death, and HF hospitalization. These results provide a rationale for aggressive management of HF and AF patients and the need for a randomized clinical trial to determine optimal therapy by ablation and 4-pillar HF therapy.

Abstract 4126304: A Cardiac Targeting Peptide Linked to miRNA106a Targets and Suppresses Genes Known to Cause Heart Failure: Reversing Heart Failure at the Source

Background: About one in five adults at age 40 will develop heart failure (HF) during their lifetime. Risk factors for HF (e.g., hypertension, etc.) alter cardiomyocytes structure and function resulting in HF. At the cellular level, these changes consist of mis/over-expression of genes that regulate cardiac identity (e.g., CamK2d, PKC, etc). The current paradigm for treating HF is pharmacological intervention or surgery; however, with few exceptions, the condition worsens with time. We are proposing a paradigm-shift for treating HF from a drug-centric system to a molecular approach that would reverse hypertrophy and adverse remodeling. Methods: A cardiac targeting peptide (CTP) was generated and linked by disulfide bond to miRNA106a, which was then introduced into a HF mouse model to measure its ability to reverse multiple heart failure parameters. CTP-miRNA106a was also introduced into a human cardiac cell line, followed by multiple analyses including Western Blot, qPCR, FACS, immunofluorescence all used to identify mechanism(s) utilized by CTP-miRNA106a to reverse HF characteristics. Results: Bio-distribution studies showed CTP delivered its miRNA106a cargo specifically to the heart within 30 mins, followed by clearance of CTP from the heart to the kidneys and liver by 3-5hrs post systemic drug injection. MiRNA106a persisted in cardiomyocytes until day 7 (latest tested time-point). CTP-miRNA106a reversed Ang2/Iso induced hypertrophy in 90% of the experimental mice ( Fig1 ). We also identified two potential HF intracellular signaling mechanisms (PLCb1/PKC/IP3 and NfkB) targeted by CTP-miRNA106a that could benefit both types of HF, HFrEF and HFpEF. PLCβ1 is a direct target for miRNA106a while the Nfkb pathway is indirectly targeted by decreased Camk2d (an miRNA106a target) signaling to IκBα. NfkB activity is quelled by miRNA106a. Conclusions: Our approach utilizes the function of miRNA106a to downregulate genes involved in cardiac hypertrophy and inflammation through the PLCb1 and CamKIId/Nfkb pathways. Most importantly, using a CTP-miRNA106a, we show delivery of miRNA106a cargo is specific to cardiomyocytes both in vitro and in vivo and that once delivered, many HF parameters including hypertrophy are reversed.

Triglyceride-glucose index is associated with heart failure with preserved ejection fraction in different metabolic states in patients with coronary heart disease.

The triglyceride-glucose (TyG) index is a surrogate indicator of insulin resistance. Therefore, we aimed to determine the association between TyG index and heart failure (HF) with preserved ejection fraction (HFpEF) in patients with coronary heart disease (CHD) and to explore whether such associations would be modified by different metabolic states. Among 107,301 CHD patients, 62,794 were included to analyze the relationship between the TyG index and HF. Among them, 8,606 patients who had undergone echocardiography were included to identify different types of HF, including HF with reduced ejection fraction (HFrEF), HF with intermediate-range ejection fraction (HFmrEF), and HFpEF. Among them, 1896 patients were diagnosed with HFpEF. Logistic regression was used to analyze the relationship between the TyG index and HFpEF in CHD patients. In addition, the association between TyG index and HFpEF according to sex, age, blood lipids, and blood pressure was assessed. A baseline analysis of CHD patients divided into four groups according to the tertile level of the TyG index showed significant differences in the related parameters between the groups. In the multi-adjusted models, the TyG index was significantly associated with the risk of HFpEF (odds ratio [OR]: 1.17; 95% confidence interval [CI]: 1.09-1.25). After adjustment for multivariates, TyG index levels for T2 (OR: 1.33; 95% CI: 1.16-1.52) and T3 (OR: 1.52; 95% CI: 1.32-1.74) were associated with increased OR in HFpEF. In addition, the TyG index of CHD patients was significantly associated with HFpEF in older adults aged > 60 years (OR: 1.20; 95% CI: 1.11-1.29), hypertension (OR: 1.27; 95% CI: 1.17-1.37), and dyslipidemia (OR: 1.15; 95% CI: 1.08-1.24). Moreover, the OR (OR: 1.23; 95% CI: 1.11-1.36) in women is higher than in men (OR: 1.17; 95% CI: 1.02-1.22, indicating a stronger association between TyG index and HFpEF in women. Our findings demonstrated a significant association between TyG index and HFpEF in CHD patients. Furthermore, TyG index was independently associated with HFpEF in hypertension, dyslipidemia, and older patients (aged > 60 years). In addition, the association between the TyG index and HFpEF in CHD patients differed according to sex.

Advancing Efficacy Prediction for EHR-based Emulated Trials in Repurposing Heart Failure Therapies.

The High mortality rates associated with heart failure (HF) have propelled the strategy of drug repurposing, which seeks new therapeutic uses for existing, approved drugs to enhance the management of HF symptoms effectively. An emerging trend focuses on utilizing real-world data, like EHR, to mimic randomized controlled trials (RCTs) for evaluating treatment outcomes through what are known as emulated trials (ET). Nonetheless, the intricacies inherent in EHR data-comprising detailed patient histories in databases, the omission of certain biomarkers or specific diagnostic tests, and partial records of symptoms-introduce notable discrepancies between EHR data and the stringent standards of RCTs. This gap poses a substantial challenge in conducting an ET to accurately predict treatment efficacy. The objective of this research is to predict the efficacy of drugs repurposed for HF in randomized trials by leveraging EHR in ET. We proposed an ET framework to predict drug efficacy, integrating target prediction based on biomedical databases with statistical analysis using EHR data. Specifically, we developed a novel target prediction model that learns low-dimensional representations of drug molecules, protein sequences, and diverse biomedical associations from a knowledge graph. Additionally, we crafted strategies to improve the prediction by considering the interactions between HF drugs and biological factors in the context of HF prognostic markers. Our validation of the drug-target prediction model against the BETA benchmark demonstrated superior performance, with an average AUCROC of 97.7%, PRAUC of 97.4%, F1 score of 93.1%, and a General Score of 96.1%, surpassing existing baseline algorithms. Further analysis of our ET framework on identifying 17 repurposed drugs-derived from 266 phase 3 HF RCTs-using data from 59,000 patients at the Mayo Clinic highlighted the framework's remarkable predictive accuracy. This analysis took into account various factors such as biological variables (e.g., gender, age, ethnicity), HF medications (e.g., ACE inhibitors, Beta-blockers, ARBs, Loop Diuretics), types of HF (HFpEF and HFrEF), confounders, and prognostic markers (e.g., NT-proBNP, bUn, creatinine, and hemoglobin). The ET framework significantly improved the accuracy compared to the baseline efficacy analysis that utilized EHR data. Notably, the best results were improved in AUC-ROC from 75.71% to 93.57% and in PRAUC from 78.66% to 90.34%, compared to the baseline models. Our study presents an ET framework that significantly enhances drug efficacy emulation by integrating EHR-based analysis with target prediction. We demonstrated substantial success in predicting the efficacy of 17 HF drugs repurposed for phase 3 RCTs, showcasing the framework's potential in advancing HF treatment strategies.

A Cross-Sectional Study of Capillary Blood Ketone Concentrations in Heart Failure Based on Sodium-Glucose Co-Transporter-2 Inhibitor Use and Heart Failure Type

Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are standard-of-care treatment in heart failure (HF). The risk of ketosis in patients with HF is unclear, especially during hospitalisation. We aimed to evaluate the normal ketone concentration range in HF patients. We performed a cross-sectional study of inpatients with acutely decompensated HF and outpatients with stable HF. Ketone concentrations were measured and analysed based on SGLT2i use. Baseline demographic data (age, gender, body mass index [BMI]), time since last meal, HF type, type 2 diabetes status, insulin use, and blood parameters (creatinine, glycosylated haemoglobin A1c [HbA1c] and N-terminal pro-B-type natriuretic peptide) were collected from patients or medical records. The primary outcome was capillary blood ketone concentration in patients with acute decompensated HF and stable chronic HF stratified by SGLT2i use. Multivariate regression was also performed using ketones as the outcome variable, with age, gender, BMI, glucose levels, HbA1c, time since last meal and presence of insulin therapy as predictor variables. A total of 20 individuals with decompensated HF (n=5 SGLT2i treated) and 47 with stable chronic HF (n=22 SGLT2i treated) were recruited. Median ketone concentrations were similar in all groups irrespective of SGLT2i use and the presence of acute decompensation (0.1 mmol/L, biggest interquartile range 0.2 mmol/L, p=0.49). Apart from time from last meal, multivariate regression analysis showed no association of ketone concentration with SGLT2i use, age, gender, BMI, type 2 diabetes status, insulin use and blood glucose level. Ketone concentrations were low in individuals with HF regardless of SGLT2i use or the presence of acute decompensation.

20 year picture of a heart failure clinic: changes in the patients profiles' and 2-year mortality

Abstract Background Heart failure (HF) is one of the most prevalent diseases. Improvements in cardiac disease management in the last two decades and in HF itself might have influenced the referral of patients with HF to a specialised HF clinic. Purpose To evaluate changes in the profile of patients referred to an outpatient HF clinic over the span of 20 years, and to analyse trends in 2-year mortality. Methods A retrospective analysis of a prospective registry of HF patients in a specialised ambulatory HF clinic was conducted, from January 1st 2002 to December 31st 2021. We divided the 20 years of the study into five periods of four years each, in order to compare the clinical characteristics of patients at admission. The variables analysed include age, sex, aetiology, HF type (preserved - HFpEF, reduced - HFrEF, mildly-reduced - HFmrEF), NYHA class, left ventricle ejection fraction (LVEF), NT-proBNP level, number of previous hospitalizations, and treatment at referral (first visit). Two-year mortality was also analysed. Results A total of 2973 patients were included (mean age 67.1± 12,9, 69.7% men). Age remained stable across the five periods, p=0.43), while the referral of women increased throughout the study period (27.7% in 2002-2005 vs 32.9% in 2018-2021, p-for-trend=0.037). Patients with HFpEF were also increasingly referred (12.3% first period vs. 27.6% last period, p-for-trend&amp;lt;0.001) and LVEF tended to be higher (33.09% vs. 40,9%, p&amp;lt;0.001). The main aetiology of the referred patients was ischaemic heart disease, although it progressively decreased in favour of other aetiologies (Table 1) (p&amp;lt;0.001). NYHA class tended to improve (NYHA 3-4 40.3% vs. 21.3%, p-for-trend &amp;lt;0.001) and NT-proBNP levels tended to decrease, predominantly in the last period (p-for-trend=0.025), as well as hospitalisation rates in the previous year (p-for-trend&amp;lt;0.001). Treatment with ACEi/ARB was progressively less frequent (p&amp;lt;0.001), at least partially due to replacement by ARNi (p&amp;lt;0.001). Treatment with digoxin and loop diuretics also diminished (p&amp;lt;0.001 and p=0.04 respectively), whereas treatment with betablockers, ARM, ivabradine and SGLT-2i increased during the study periods (all p&amp;lt;0.001) (Table 2); Patients carrying ICD and CRT also increased (p=0.014 and p&amp;lt;0.001 respectively). Adjusted 2-year mortality significantly decreased, mainly in the last period (p&amp;lt;0.001) (Figure 1). Conclusion The profile of HF patients referred to a tertiary HF ambulatory Clinic changed along 20 years of study. HFrEF remained the most common, but is declining in favour of HFpEF. Ischaemic aetiology also remained the most frequent but, again, showed a decreasing trend. Two-year mortality has globally decreased, markedly in the last period.Figure 1

Comparing treatment strategies for heart failure: a real-world analysis of adding ARNI or SGLT2i to older GDMT

Abstract Background Heart failure (HF) is a global burden with limited treatment options beyond established guideline-directed medical therapy (GDMT). Newer medications, like angiotensin receptor-neprilysin inhibitors (ARNIs) and sodium-glucose cotransporter-2 inhibitors (SGLT2i), show promise, but real-world evidence on their effectiveness compared to traditional GDMT is lacking. Objective This study assessed the real-world effectiveness of adding ARNIs and SGLT2i to existing GDMT regimens for various HF types using network meta-analysis (NMA). Methods We analyzed data from observational studies, evaluating the impact of different treatment combinations on all-cause mortality (ACM) and heart failure hospitalization (HFH). Results Adding ARNIs to GDMT significantly reduced ACM compared to older regimens (hazard ratio [HR] 0.59, 95% confidence interval [CI] 0.42-0.84), representing a 41% decrease in mortality risk. SGLT2i+2GDMT demonstrated the most significant HFH reduction (HR 0.16, 95% CI 0.06-0.47), translating to an 84% reduction in hospitalization risk. Conclusion Incorporating ARNIs or SGLT2i into existing GDMT regimens improves real-world outcomes for HF patients, supporting current guideline recommendations. Personalized treatment plans considering individual needs and preferences are crucial for optimal patient care.Network map of All-cause mortalityRelative treatment effects for ACM

Disparities in SGLT2i utilization among heart failure patients with different ejection fraction in China: findings from chinese cardiovascular association database-heart failure center registry

Abstract Background Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are recommended for heart failure (HF) patients regardless of left ventricular ejection fraction (LVEF). Although Chinese HF guidelines still recommend traditional renin–angiotensin–aldosterone system inhibitors, beta blockers, mineralocorticoid receptor antagonists, the Chinese Cardiovascular Association (CCA) HF Center Registry has launched a project to promote the guideline-directed medical therapy (GDMT) for HF patients in China. However, data on the utilization of GDMT in Chinese HF patients is scarce, especially SGLT2i. Purpose We aimed to investigate the usage status of SGLT2i in HF patients with different LVEFs and explore associated factors with SGLT2i adoption in hospitalized HF Chinese patients. Methods This is a retrospective real world study using data from the CCA Database-HF Center Registry. The study included HF patients hospitalized in 52 secondary or tertiary hospitals, including 26 accredited heart failure centers (HFC) and 26 non-accredited heart failure centers (NHFC). Centers that meet the 25 quality control standards established by CCA can be accredited as HFC. We evaluated the use rate of SGLT2i overall and by HF type, as well as the change of SGLT2i usage rate at discharge during the study period from 1st July 2022 to 31st March 2023. LASSO and multivariable logistic regression were also used to explore associated factors of SGLT2i adoption at discharge. Result We included 8,843 hospitalized HF patients: 5,326 (60.2%) were male, 2,980 (33.7%) HFrEF, 1,624 (18.4%) HFmrEF, 3,653 (41.3%) HFpEF and 586 (6.6%) lacked EF data. Overall, SGLT2i were adopted in 3,666 (41.5%) HF patients at discharge (58.1% in HFrEF, 45.3% in HFmrEF, 28.8% in HFpEF). Overall, the usage rate of SGLT2i at discharge rose from 35.2% to 50.2%. Specifically, for HFrEF patients, there was a rise from 56.2% to 64.4%. For HFmrEF and HFpEF patients, the usage rate increased from 37.5% to 54.4% and from 22.2% to 35.7%, respectively (Figure 1). The usage rate of SGLT2i was higher in HFC compared with NHFC (47.1% vs. 35.8%, p&amp;lt;0.001). In multivariable logistic regression, older age, new-onset heart failure, hospital location, etc. were associated with a lower usage rate of SGLT2i at discharge. In contrast, HFC, dilated cardiomyopathy, obesity, etc. were associated with a higher utilization rate of SGLT2i (Figure 2). HF classification by LVEF was also an independent influencing factor even after adjusting other factors; when HFrEF was used as a reference, the use rate of SGLT2i was lower in HFmrEF (OR 0.79, 95% CI 0.69 - 0.91) and HFpEF (OR 0.44, 95% CI 0.39 - 0.49). Conclusion In clinical practice in China, the usage rate of SGLT2i for HF treatment is increasing but needs to be further improved. Disparities exist in usage rates among HF patients with different LVEFs. Addressing this disparity necessitates a targeted approach, emphasizing increased utilization in HF patients regardless of LVEF.SGLT2i usage rate in HFFactors affecting SGLT2i adoption in HF

Incorporating intrathoracic pressure fluctuation can improve noninvasive prediction of left ventricular end-diastolic pressure

Abstract Introduction Heart failure (HF) is a leading cause of mortality and morbidity, with a prevalence above 10% in elderly population (1). Left ventricular end-diastolic pressure (LVEDP) is a known indicator for all types of HF. An invasive pressure catheter is the gold standard for measuring LVEDP (2). However, it involves an in-hospital procedure and is costly, which limits the accessibility. A noninvasive strategy would improve early diagnosis and reduce the burden on secondary care. Several noninvasive classifiers are able to detect elevated LVEDP (3-5), with some receiving FDA clearance (6). While beneficial for triaging patients, these classifiers cannot quantify the severity and track disease progression. Developing a noninvasive LVEDP regression model requires accounting for respiration dynamics. Even invasively, the dynamics make measuring LVEDP challenging. This study uses an error metric from ANSI/AAMI/ISO 81060-2:2019 (AAMI) (7) to evaluate the effect of respiration on noninvasive LVEDP regression results. Methods The dataset (147 patients, 21+ yrs old, mean 65 ± 10 yrs; 68% male) consisted of patients referred for nonemergent left heart catheterisation inclusive of direct assessment of LVEDP. Noninvasive data was collected by a modified brachial cuff with a single-lead electrocardiogram (ECG). Invasive data was acquired using a Millar pressure catheter. LVEDP was derived based on the time of the R-wave of the ECG (8). For each patient, 40 secs of noninvasive data with synchronised catheter signals were analysed to build an LVEDP regression model. Inputs were generated from the ECG and brachial pressure waves based on fiducials identified in both signals. Leave-one-subject-out cross-validation (LOSO CV) was used to train and test the algorithm. The impact of respirophasic variation on the model was analysed by comparing the prediction with the mean LVEDP and the range of the mean ± standard deviation (std) (i.e. AAMI error metric). Results The results, evaluated using Bland-Altman and correlation analysis, showed a decrease in the mean absolute error (MAE) from 3.6 mmHg to 1.4 mmHg, the std from 4.9 mmHg to 3.0 mmHg, and the correlation (r) from 0.57 to 0.77 when incorporating intrathoracic pressure swings (Fig.1 and Fig.2). A Levene test on the residuals of the two error determinations showed a significant difference (p-value &amp;lt; 0.01). Conclusion Irrespective of the error metric, the model performance meets the AAMI standard for blood pressure (BP) measurement. Moreover, when respiratory motion is included, agreement with invasive LVEDP improves considerably. From a clinical perspective, this emphasises the importance of targeting end-expiratory LVEDP. With respect to noninvasive BP measurement, it suggests that both brachial BP evaluation and LVEDP prediction should attempt to quantify fluctuations. While the challenge remains, these results indicate that noninvasive LVEDP prediction could be realised in the near future.Fig.1 Prediction vs mean LVEDP.Fig. 2 Prediction vs mean +/- std.