Cardiovascular Diseases Including Heart Failure Research Articles

Low serum irisin levels predicted newly atrial fibrillation in patients with any phenotypes of chronic heart failure

Abstract Background Atrial fibrillation (AF) continues to be a major health problem among patients with known cardiovascular disease including heart failure (HF). AF is not only powerful risk factor for newly HF, but also it contributes to untoward clinical course of the condition. Although, natriuretic peptides are well-validated biomarkers to predict poor clinical outcomes of HF, their accuracy for AF in patients with different phenotypes of HF is not optimal. Recent studies showed that adipocytokines including irisin affect the risk of AF occurrence. We hypothesized that serum irisin can have additional discriminative potency for AF among HF in patients. Methods The study group comprised 541 consecutive patients with chronic HF aged 41 to 76 years recruited for the study from October 2020 to December 2022. We included 153 patients with any phenotypes of HF who were hospitalized due to paroxysmal or persistent AF and a control group of 388 age- and sex-matched individuals admitted to hospitals due to exacerbation of HF. All patients included in the study were examined by conventional general clinical and physical investigations, B-mode echocardiography and Doppler. The plasma levels N-terminal-natriuretic pro-peptide (NT-proBNP), high sensitivity (hs) C-reactive protein, tumor necrosis factor-alpha (TNF-alpha), hs-troponin T, adropin, apelin, leptin, adiponectin, and irisin were measured using ELISA. Results Compared with patients from control groups, patients with AF had greater left atrial volume index (LAVI), higher serum levels of NT-proBNP, hs-CRP, TNF-alpha, and lower left ventricular ejection fraction (LVEF), irisin and apelin levels. There were no significant difference between groups in left ventricular mass index, the serum levels of hs-troponin T, adropin, leptin, and adiponectin. Multivariate linear regression adjusted to LVEF and LAVI revealed that irisin and NT-proBNP were the predictors for AF. We found that the well-balanced cut-off point for serum concentration of irisin (AF versus non-AF) were 10.5 ng/mL (area under curve [AUC] = 0.96, sensitivity = 81.0%, specificity = 88.0%; P = 0.0001). Cutoff point of NT-proBNP that distinguished patients with AF and without AF was 750 pmol/L (AUC = 0.96; sensitivity = 72.7%, specificity 76.5%, р = 0.0001). Multivariate Cox regression model yielded that the serum levels of irisin < 10.5 ng/mL (odds ratio [OR] = 1.40; P = 0.001) and NT-proBNP > 750 pmol/mL (OR = 1.22; P = 0.012), LAVI > 34 mL/m2 (OR = 1.06; P = 0.010) remained to be strong predictors for newly AF. Add-on of irisin < 10.5 ng/mL to the predictive model constructed from NT-proBNP (> 750 pg/mL) significantly improved discriminatory potency of the whole model for HF. Conclusion We found that decreased serum levels of irisin significantly predicted newly AF in patients with any phenotypes of HF.

Reinforcement Learning for Closed-loop Regulation of Cardiovascular System with Vagus Nerve Stimulation: A Computational Study.

(Objective). Vagus nerve stimulation (VNS) is being investigated as a potential therapy for cardiovascular diseases including heart failure, cardiac arrhythmia, and hypertension. The lack of a systematic approach for controlling and tuning the VNS parameters poses a significant challenge. Closed-loop VNS strategies combined with artificial intelligence (AI) approaches offer a framework for systematically learning and adapting the optimal stimulation parameters. In this study, we presented an interactive AI framework using reinforcement learning (RL) for automated data-driven design of closed-loop VNS control systems in a computational study. (Approach). Multiple simulation environments with a standard application programming interface were developed to facilitate the design and evaluation of the automated data-driven closed-loop VNS control systems. These environments simulate the hemodynamic response to multi-location VNS using biophysics-based computational models of healthy and hypertensive rat cardiovascular systems in resting and exercise states. We designed and implemented the RL-based closed-loop VNS control frameworks in the context of controlling the heart rate (HR) and the mean arterial pressure (MAP) for a set point tracking task. Our experimental design included two approaches; a general policy using deep RL algorithms and a sample-efficient adaptive policy using probabilistic inference for learning and control (PILCO). (Main results). Our simulation results demonstrated the capabilities of the closed-loop RL-based approaches to learn optimal VNS control policies and to adapt to variations in the target set points and the underlying dynamics of the cardiovascular system. Our findings highlighted the trade-off between sample-efficiency and generalizability, providing insights for proper algorithm selection. Finally, we demonstrated that transfer learning improves the sample efficiency of Deep RL algorithms allowing the development of more efficient and personalized closed-loop VNS systems. (Significance). We demonstrated the capability of RL-based closed-loop VNS systems. Our approach provided a systematic adaptable framework for learning control strategies without requiring prior knowledge about the underlying dynamics.

Nrf2-Keap1 in Cardiovascular Disease: Which is the Cart and Which the Horse?

High levels of oxidant stress in the form of reactive oxidant species (ROS) are prevalent in the circulation and tissues in various types of cardiovascular disease including heart failure, hypertension, peripheral arterial disease, and stroke. Here we review the role of nuclear factor erythroid 2-related factor 2 (Nrf2), an important and widespread antioxidant and anti-inflammatory transcription factor that may contribute to the pathogenesis and maintenance of cardiovascular diseases. We review studies showing that downregulation of Nrf2 exacerbates heart failure, hypertension and autonomic function. Finally, we discuss the potential for using Nrf2 modulation as a therapeutic strategy for cardiovascular diseases and autonomic dysfunction.

The Role of Circular RNA for Early Diagnosis and Improved Management of Patients with Cardiovascular Diseases.

Cardiovascular diseases (CVDs) are responsible for approximately 17.9 million deaths every year. There is growing evidence that circular RNAs (circRNAs) may play a significant role in the early diagnosis and treatment of cardiovascular diseases. As regulatory molecules, circular RNAs regulate gene expression, interact with proteins and miRNAs, and are translated into proteins that play a key role in a wide variety of biological processes, including the division and proliferation of cells, as well as the growth and development of individuals. An overview of the properties, expression profiles, classification, and functions of circRNAs is presented here, along with an explanation of their implications in cardiovascular diseases including heart failure, hypertension, ischemia/reperfusion injury, myocardial infarction, cardiomyopathies, atherosclerosis, and arrhythmia.

New Insights into Endothelial Dysfunction in Cardiometabolic Diseases: Potential Mechanisms and Clinical Implications.

The endothelium is a monocellular layer covering the inner surface of blood vessels. It maintains vascular homeostasis regulating vascular tone and permeability and exerts anti-inflammatory, antioxidant, anti-proliferative, and anti-thrombotic functions. When the endothelium is exposed to detrimental stimuli including hyperglycemia, hyperlipidemia, and neurohormonal imbalance, different biological pathways are activated leading to oxidative stress, endothelial dysfunction, increased secretion of adipokines, cytokines, endothelin-1, and fibroblast growth factor, and reduced nitric oxide production, leading eventually to a loss of integrity. Endothelial dysfunction has emerged as a hallmark of dysmetabolic vascular impairment and contributes to detrimental effects on cardiac metabolism and diastolic dysfunction, and to the development of cardiovascular diseases including heart failure. Different biomarkers of endothelial dysfunction have been proposed to predict cardiovascular diseases in order to identify microvascular and macrovascular damage and the development of atherosclerosis, particularly in metabolic disorders. Endothelial dysfunction also plays an important role in the development of severe COVID-19 and cardiovascular complications in dysmetabolic patients after SARS-CoV-2 infection. In this review, we will discuss the biological mechanisms involved in endothelial dysregulation in the context of cardiometabolic diseases as well as the available and promising biomarkers of endothelial dysfunction in clinical practice.

Cardiovascular aging: spotlight on mitochondria.

Mitochondria are cellular organelles critical for ATP production and are particularly relevant to cardiovascular diseases including heart failure, atherosclerosis, ischemia-reperfusion injury, and cardiomyopathies. With advancing age, even in the absence of clinical disease, mitochondrial homeostasis becomes disrupted (e.g., redox balance, mitochondrial DNA damage, oxidative metabolism, and mitochondrial quality control). Mitochondrial dysregulation leads to the accumulation of damaged and dysfunctional mitochondria, producing excessive reactive oxygen species and perpetuating mitochondrial dysfunction. In addition, mitochondrial DNA, cardiolipin, and N-formyl peptides are potent activators of cell-intrinsic and -extrinsic inflammatory pathways. These age-related mitochondrial changes contribute to the development of cardiovascular diseases. This review covers the impact of aging on mitochondria and links these mechanisms to therapeutic implications for age-associated cardiovascular diseases.

Prognostic significance of growth differentiation factor-15 across the BMI spectrum in patients with chronic heart failure: Insights from the SUPPORT trial

Abstract Background Obesity is a risk factor for cardiovascular diseases including heart failure (HF), yet patients with obesity have better outcomes than their leaner counterparts in HF (i.e. the obesity paradox). We sought to investigate whether growth differentiation factor-15 (GDF15), an emerging biomarker in HF reflecting inflammation and oxidative stress, is a prognostic indicator across the body mass index (BMI) spectrum in chronic heart failure (CHF). Methods Serum levels of GDF15 and its prognostic significance across BMI were examined in a total of 1,040 Japanese patients with CHF enrolled in a randomized clinical trial of the SUPPORT trial (supplemental benefit of an angiotensin receptor blocker in hypertensive patients with stable heart failure using olmesartan) (mean age 66.0±9.9 years, 26% female). Patients were categorized into four groups: underweight (BMI <18.5 kg/m2; n = 56), normal (BMI 18.5-22.9; n = 304), overweight (BMI 23-24.9; n = 257), and obese (BMI ≥25; n = 423) defined based on the WHO recommendation for Asian-Pacific population. Results The underweight group consisted of older patients with a higher prevalence of NYHA class III and reduced left ventricular ejection fraction (LVEF) compared to obese patients (mean age 69.0 vs 64.7 years, NYHA class III 17.9 vs 5.9%, and mean LVEF 49.3 vs 55.5%; all p<0.05). Median GDF15 level in the underweight group was higher (1,864 pg/mL [IQR 1,070-2,626]) but was similar in overweight and obese groups (1,285 [953, 1772] and 1,220 [888-1,789], respectively) compared to normal BMI group (1,276 [879-2,018]). During follow-up (median 10.3 years), 540 composite events of HF hospitalization or all-cause death occurred. The risk was higher in the underweight group (adjusted HR 1.8, 95%CI [1.3-2.5]) and lower in the obesity group (adjusted HR 0.8 [95% CI 0.6-0.9]) compared to the normal BMI group. An increased GDF15 incurred a consistently higher risk from underweight to obese groups; per unit increase in logGDF15 (pg/mL) was associated with 4.1, 2.4, 1.7 and 2.4 times higher risk, respectively. The optimal cut-off point for discriminating those with and without the composite events was 1,343 pg/mL in overall patients. This cut-off value performed well as a prognostic indicator across the continuous BMI spectrum including those with higher BMI (Figure). Conclusions The prognostic significance of GDF15 persisted across the BMI spectrum in patients with CHF. GDF15 may be useful for providing prognostic information across patients with a diverse range of BMI even in those with modest outcomes.HF events in high GDF15 across BMI

Change in hbA1c following treatment with and the short-term risk of major adverse cardiovascular outcomes

Abstract Background Post-hoc analyses from glucagon-like peptide-1 receptor agonist (GLP1-RA) trial populations have shown a benefit on cardiovascular outcomes from reduction in glycated hemoglobin (HbA1c). It is of interest to see if this finding translates into a cohort of real-world GLP1-RA users. Purpose To study among new GLP1-RA users, how reaching a Hba1c below 53 mmol/mol six months after initiation affects the risk of major adverse cardiovascular outcomes (MACE), compared with a HbA1c above 53 mmol/mol. Methods We included new GLP1-RA users six months after initiation of treatment, with an available HbA1c value 0-6 months before and 0-6 months after GLP1-RA initiation, from the Danish registries between 2010-2022. HbA1c levels pre- and post-treatment were categorized as above 53 mmol/mol or below 53mmol/mol. The primary outcome was defined as a composite of myocardial infarction, stroke, and all-cause death. Patients were followed from index (6 months after GLP1-RA initiation) until the outcome, a total of 1 years, or end-of-study (31.12.21), whichever comes first. Crude 1-year risks were compared using the Kaplan Meier estimator, or the Aalen Johansen estimator if competing risk was present. The effect of HbA1c below 53 mmol/mol versus a HbA1c above 53 mmol/mol on MACE was estimated using a Cox regression model adjusted for age, sex, educational level, baseline comorbidities, type 2 diabetes duration, and baseline cardiovascular disease including heart failure. Hospitalization for hyperglycemia was also evaluated using a Cox regression. Results A total of 4,081 new GLP1-RA users (median age: 58y [IQR:50;66], 52% males) were included, 3,090 had a post-treatment HbA1c below 53 mmol/mol and 991 had a post-treatment Hba1c above 53 mmol/mol. During a median follow-up of 1 year (IQR:1.0,1.0), the crude 1-year risk of MACE in persons with a HbA1c below 53 mmol/mol was 6.4% (95% confidence interval [CI]: 5.5;7.2) and 9.5% (7.7;11.3) in persons with HbA1c above 53 mmol/mol, yielding a hazard rate of 0.69 (0.54;0.88). No interaction between pre-and post HbA1c was found (p=0.59). The hazard rate of hospitalization for hypoglycemia was 0.76 (0.45:1.23) for persons reaching HbA1c level below 53 mmol/mol compared to patients with a HbA1c above 53 mmol/mol, with no interaction between pre- and post HbA1c observed (p =0.052). Conclusion A HbA1c level below 53 mmol/mol, among GLP1-RA users reduced the 1-year rate of MACE and did not significantly increase the 1-year rate of hospitalization for hypoglycemia.

Accelerated decline in lung function is associated with cardiac structure and function and independently predicts incident heart failure

Abstract Background The association between impaired lung function and cardiovascular disease is well known. However, it is not fully understood how a decline in lung function affects the development of cardiovascular disease including heart failure (HF). Purpose We aimed to investigate the association between declining lung function and changes in cardiac structure and function. Furthermore, we investigated the association between a decline in lung function and the risk of HF. Methods The study included 2,995 participants from a general population study. All participants had two examinations with spirometry performed 10 years apart. Participants were free of valvular heart disease and HF. A subsample (n=1,164) was also examined with echocardiography at both timepoints. The decline in the forced expiratory volume in one second (dFEV1) from the first visit to the second visit, was calculated. The change in cardiac structure and function between the two visits, was calculated as the decline in left ventricular ejection fraction (dLVEF), global longitudinal strain (dGLS), left ventricular mass index (dLVMi) and the ratio of early diastolic mitral inflow velocity to early diastolic mitral annulus velocity (dE/e’). Linear regression models were adjusted for the baseline FEV1 and echocardiographic value to account for regression to the mean. Outcome was incident HF. Results The entire sample consisted of 57% women, and the mean age was 62 ± 14 years. A total of 59% had hypertension, 8% had ischemic heart disease (IHD), 6% had diabetes, and 18% were active smokers. Mean FEV1 at baseline was 2.8 ± 0.95 liters (95 ± 19% as percentage of the predicted value). The mean decline in FEV1 between visits (median 10.8 years, IQR: 10.3-11.2) was 309 ± 362 mL. In the subsample examined with echocardiography, decreasing dLVEF was significantly associated with decreasing dFEV1 (p=0.030) in multivariable linear regression analysis, whereas dGLS, dLVMi, and dE/e’ were not. In the total study sample, 105 participants developed incident heart failure following the second visit during a median follow-up of 5.4 years (IQR: 4.5-6.3). Participants in the lowest quartile of dFEV1 (no change or increase) had an incidence rate of 2.48 per 1,000 person years (95%CI 1.33-4.60) versus participants in the highest quartile of dFEV1 (largest decline) with an incidence rate of 13.9 per 1,000 person years (95%CI 10.6-18.3), p<0.001. In multivariable Cox regression analysis, dFEV1 was an independent predictor of HF with a hazard ratio of 3.37 per 1 liter decline (95%CI 1.53-7.43, p=0.003). Conclusion We found a strong association between a decline in FEV1 and a decline in LVEF over a decade. Decreasing FEV1 was independently associated with incident HF. The incidence was highest for those with the largest decline in FEV1.A) Linear association B) Hist. of dLVEFA) Incidence rate B) Cumulative inc.

Abstract 16389: Inflammatory Chronic Kidney Disease is Associated With Incident Heart Failure: A Pooled Cohort Analysis

Introduction: High sensitivity C-reactive protein (hsCRP), a biomarker of inflammation, can risk stratify patients for cardiovascular disease including heart failure (HF). It is not well established if inflammation increases the risk of HF in patients with chronic kidney disease (CKD) and if hsCRP can be utilized to risk stratify patients with CKD for their risk of incident HF. Aims: We assessed the role of hsCRP in risk stratifying patients with CKD for incident HF. Methods: We studied participants of 3 major epidemiologic cohorts: Atherosclerosis Risk in Communities Study, Multi-Ethnic Study of Atherosclerosis, and Jackson Heart Study. High inflammation was classified as hsCRP >3 mg/L and CKD was classified as estimated glomerular filtration rate <60 mL/min/1.73m2. Participants were stratified into 3 groups: neither CKD nor high inflammation, CKD without high inflammation, or CKD with high inflammation. Cox hazards models adjusted for age, sex, race, body mass index, smoking, alcohol use, diabetes, hypertension, and coronary disease were utilized for analysis. Results: 8,692 participants with 460 incident HF events followed over a median 8.32 years were included in our analysis. Participants with CKD without high inflammation (HR = 1.45; 95% CI 1.14 to 1.85) and CKD with high inflammation (2.05; 1.61 to 2.61) were associated with an increased risk of incident HF compared with participants without CKD or high inflammation (referent, Figure). Furthermore, participants with CKD and a hsCRP >3 mg/L had an increased risk of incident HF (1.41; 1.06 to 1.88) compared with participants with CKD but hsCRP ≤3 mg/L (referent). Conclusions: Patients with CKD and high levels of inflammation carry a 2-fold increased risk of incident HF. In patients with CKD, hsCRP levels >3mg/L may be useful to risk stratify patients with increased risk of developing HF.

Abstract 15653: Heart Failure Medications Have a Direct Inhibitory Effect on Endothelial-to-Mesenchymal Transition in an in vitro Model

Introduction: Endothelial-to-Mesenchymal Transition (EndoMT) is a process where endothelial cells can transform into mesenchymal cells. This mechanism, while well established in embryogenesis and cancer, has been accumulating evidence as a contributor to cardiovascular diseases including heart failure (HF). While current guideline-directed medications (GDMT) for HF have postulated benefits to help cardiomyocytes and the heart, further investigation on the specific impact of HF drugs on this pro-fibrotic mechanism of EndoMT is required. Hypothesis: We hypothesize that HF drugs can inhibit EndoMT in an in vitro model Methods: Human umbilical vascular endothelial cells (HUVECs) were incubated for 24 h with the drugs - metoprolol, losartan, lisinopril, dapagliflozin, and valsartan/sacubitril, at concentrations ranging from 1 mg to 1 ng per mL, to evaluate cell viability using alamarBlue TM assay. In vitro EndoMT is induced with Nω-Nitro-L-arginine methyl ester hydrochloride and angiotensin II in HUVECs. During EndoMT, HUVECs were co-incubated with the drugs to determine their effect on EndoMT. Immunofluorescence for Endothelial (VE-Cadherin) and Mesenchymal (Transgelin) markers was used to characterize EndoMT. Results: All the HF drugs tested had a dose-dependent effect on HUVEC viability. The highest drug concentration (1 mg/mL) resulted in cell death while lower concentrations (1 μg to 1 ng per mL) did not affect cell viability. A concentration of 1 μg/mL was used to investigate the drugs’ effect on EndoMT. Immunofluorescence staining revealed reduced levels of expression for Transgelin in HUVCEs induced to undergo EndoMT in the presence of the treated drugs compared to the untreated and vehicle-treated cells after 4 days of incubation. Conclusion All the HF medications inhibited EndoMT in an in vitro model. Our results show that some of the beneficial effects of the HF GDMT medications used in clinical practice could be through an inhibitory effect on EndoMT.

Abstract 14547: Genetically Predicted Inhibition of HMG-CoA Reductase Reduces Risk of DNMT3A Clonal Hematopoiesis

Introduction: Clonal hematopoiesis (CH) is associated with increased morbidity and mortality from cancer and cardiovascular diseases including heart failure and ischemic heart disease. At present no medications are known to protect from CH. However, leukemia cells with equivalent mutations show sensitivity to statin-induced cell death. Aims: To evaluate the association of LDL-C lowering genetic variants at HMGCR (the target of statins) with CH risk using two-sample Mendelian randomization. Methods: We investigated whether lower LDL-C genetically predicted by 6 variants at HMGCR associates with CH risk. Secondary exposures included a polygenic instrument of 74 LDL-C-lowering genome-wide variants. Genetic associations for LDL-C derived from a genome-wide association study (GWAS) meta-analysis of circulating LDL-C levels by the Global Lipid Genetics Consortium (N≤188,578 individuals of European ancestry). Outcome associations for CH were from a GWAS in 368,526 European individuals in UK Biobank. Results: Genetically predicted reduction in HMG-CoA reductase activity equivalent to a 38.7mg/dL lower circulating LDL-C level was associated with reduced odds of overall CH (OR 0.75, 95% CI 0.58-0.97, P = 0.027) or DNMT3A CH (OR 0.64, 95% CI 0.48-0.86, P = 0.003) but not TET2 CH (OR 1.12, 95% CI 0.63-2.00, P = 0.70). Associations were consistent across all 6 HMGCR variants in sensitivity analyses. Co-localization plots showed evidence of co-localization of LDL-C with DNMT3A CH and overall CH at the HMGCR locus. Associations were stronger for CH with variant allele fraction ≥10%, and, statins suppressed colony formation of mutant DNMT3A cells in vitro , suggesting statins may limit clonal expansion. In a secondary analysis to explore LDL-C dependence, LDL-C lowering predicted by the polygenic instrument did not associate with overall or DNMT3A CH but associated with increased odds of TET2 CH (OR 1.13, 95% CI 1.01-1.27, P = 0.03). Findings were replicated in a non-European cohort. Conclusions: Genetically predicted lifelong reduction of HMG-CoA reductase activity was associated with reduced risk of overall and DNMT3A -mutant CH, likely by LDL-C-independent mechanisms. This provides a strong rationale for clinical trials testing the effects of statins in CH.

Fatty acid metabolism disorders and potential therapeutic traditional Chinese medicines in cardiovascular diseases.

Cardiovascular diseases are currently the primary cause of mortality in the whole world. Growing evidence indicated that the disturbances in cardiac fatty acid metabolism are crucial contributors in the development of cardiovascular diseases. The abnormal cardiac fatty acid metabolism usually leads to energy deficit, oxidative stress, excessive apoptosis, and inflammation. Targeting fatty acid metabolism has been regarded as a novel approach to the treatment of cardiovascular diseases. However, there are currently no specific drugs that regulate fatty acid metabolism to treat cardiovascular diseases. Many traditional Chinese medicines have been widely used to treat cardiovascular diseases in clinics. And modern studies have shown that they exert a cardioprotective effect by regulating the expression of key proteins involved in fatty acid metabolism, such as peroxisome proliferator-activated receptor α and carnitine palmitoyl transferase 1. Hence, we systematically reviewed the relationship between fatty acid metabolism disorders and four types of cardiovascular diseases including heart failure, coronary artery disease, cardiac hypertrophy, and diabetic cardiomyopathy. In addition, 18 extracts and eight monomer components from traditional Chinese medicines showed cardioprotective effects by restoring cardiac fatty acid metabolism. This work aims to provide a reference for the finding of novel cardioprotective agents targeting fatty acid metabolism.

Non-contact heart vibration measurement using computer vision-based seismocardiography

Seismocardiography (SCG) is the noninvasive measurement of local vibrations of the chest wall produced by the mechanical activity of the heart and has shown promise in providing clinical information for certain cardiovascular diseases including heart failure and ischemia. Conventionally, SCG signals are recorded by placing an accelerometer on the chest. In this paper, we propose a novel contactless SCG measurement method to extract them from chest videos recorded by a smartphone. Our pipeline consists of computer vision methods including the Lucas–Kanade template tracking to track an artificial target attached to the chest, and then estimate the SCG signals from the tracked displacements. We evaluated our pipeline on 14 healthy subjects by comparing the vision-based SCG^mathrm{{v}} estimations with the gold-standard SCG^mathrm{{g}} measured simultaneously using accelerometers attached to the chest. The similarity between SCG^mathrm{{g}} and SCG^mathrm{{v}} was measured in the time and frequency domains using the Pearson correlation coefficient, a similarity index based on dynamic time warping (DTW), and wavelet coherence. The average DTW-based similarity index between the signals was 0.94 and 0.95 in the right-to-left and head-to-foot directions, respectively. Furthermore, SCG^mathrm{{v}} signals were utilized to estimate the heart rate, and these results were compared to the gold-standard heart rate obtained from ECG signals. The findings indicated a good agreement between the estimated heart rate values and the gold-standard measurements (bias = 0.649 beats/min). In conclusion, this work shows promise in developing a low-cost and widely available method for remote monitoring of cardiovascular activity using smartphone videos.

Changes in left ventricular systolic function for 1 year in patients with acute heart failure <50 years of age

Abstract Funding Acknowledgements Type of funding sources: None. Background Though old age is an important risk factor for cardiovascular disease including heart failure (HF), HF can develop in young patients and can have a greater impact on a quality of life because they are active individuals. Purpose We evaluated the clinical characteristics and prognosis according to change of left ventricular (LV) function in younger patients with acute HF. Methods Study data were obtained from a multicenter cohort that included patients hospitalized for acute HF. Patients who were under 50 years of age and had available data regarding baseline and one-year follow-up left ventricular ejection fraction (LVEF) were included in this analysis. Patient were classified into two groups according changes in LVEF: the improved or stationary group whose LVEF improved or maintained at one-year follow-up; the aggravated LVEF group whose LVEF deteriorated at one-year follow-up. Results Among 437 patients, 14.6% of patients had experienced worsening of LVEF at the one-year follow-up. The patients in aggravated LVEF group had a worse clinical profile than patients with improved or stationary LVEF. During follow-up (median 1946 days), a total of 56 patients (12.8%) died. Among them, the aggravated LVEF group had higher incidence of all-cause death (32.8% vs. 9.4%, p < 0.001). The aggravated LVEF group showed significant lower cumulative all-cause death free survival rate than improved or stationary LVEF group (Figure). In addition, the aggravated LVEF group had significantly higher incidence of cardiac death (14.1% vs. 2.9%, p < 0.001), readmission (76.6% vs. 55.5%, p = 0.002), readmission due to cardiac cause (57.8% vs.30.8%, p < 0.001), and HF readmission (51.6% vs. 26.0%, p < 0.001). After adjusting for confounding factors, Cox regression analysis showed that use of angiotensin converting enzyme inhibitors at discharge was independently associated with 63% reduced risk of aggravated LVEF (Odds ratio 0.37, 95% confidence interval 0.168–0.791, p = 0.001). Conclusions Poor clinical prognosis is expected if LVEF worsens after 1 year in young patients with HF. Clinicians need to be aware of the deteriorating characteristics of young HF patients and provide delicate treatment.

Microbially Produced Imidazole Propionate Is Associated With Heart Failure and Mortality

BackgroundOver the past years, it has become clear that the microbial ecosystem in the gut has a profound capacity to interact with the host through the production of a wide range of bioactive metabolites. The microbially produced metabolite imidazole propionate (ImP) is clinically and mechanistically linked with insulin resistance and type 2 diabetes, but it is unclear how ImP is associated with heart failure. ObjectivesThe authors aimed to explore whether ImP is associated with heart failure and mortality. MethodsImP serum measurements in 2 large and independent clinical cohorts of patients (European [n = 1,985] and North American [n = 2,155]) with a range of severity of cardiovascular disease including heart failure. Univariate and multivariate Cox regression analyses were performed to delineate the impact of ImP on 5-year mortality in the North American cohort, independent of other covariates. ResultsImP is independently associated with reduced ejection fraction and heart failure in both cohorts, even after adjusting for traditional risk factors. Elevated ImP was a significant independent predictor of 5-year mortality (for the highest quartile, adjusted HR: 1.85 [95% CI: 1.20-2.88]; P < 0.01). ConclusionsThe gut microbial metabolite ImP is increased in individuals with heart failure and is a predictor of overall survival.

Coffee consumption and associations with blood pressure, LDL-cholesterol and echocardiographic measures in the general population

Coffee, next to water the most widespread beverage, is attributed both harmful and protective characteristics concerning cardiovascular health. This study aimed to evaluate associations of coffee consumption with cardiac biomarkers, echocardiographic, electrocardiographic parameters and major cardiovascular diseases. We performed a cross-sectional analysis of 9009 participants of the population-based Hamburg City Health Study (HCHS), enrolled between 2016 and 2018 median age 63 [IQR: 55; 69] years. Coffee consumption was classified into three groups: < 3 cups/day (low), 3–4 cups/day (moderate), > 4 cups/day (high). In linear regression analyses adjusted for age, sex, body mass index, diabetes, hypertension, smoking, and additives, high coffee consumption correlated with higher LDL-cholesterol (β = 5.92; 95% CI 2.95, 8.89; p < 0.001). Moderate and high coffee consumption correlated with lower systolic (β = − 1.91; 95% CI − 3.04, − 0.78; p = 0.001; high: β = − 3.06; 95% CI − 4.69, − 1.44; p < 0.001) and diastolic blood pressure (β = − 1.05; 95% CI − 1.67, − 0.43; p = 0.001; high: β = − 1.85; 95% CI − 2.74, − 0.96; p < 0.001). Different levels of coffee consumption did neither correlate with any investigated electrocardiographic or echocardiographic parameter nor with prevalent major cardiovascular diseases, including prior myocardial infarction and heart failure. In this cross-sectional analysis, high coffee consumption correlated with raised LDL-cholesterol levels and lower systolic and diastolic blood pressure. However, major cardiovascular diseases including heart failure and its diagnostic precursors were not associated with coffee consumption, connoting a neutral role of coffee in the context of cardiovascular health.

Electrocardiogram-based artificial intelligence for the diagnosis of heart failure: a systematic review and meta-analysis.

The electrocardiogram (ECG) is an inexpensive and easily accessible investigation for the diagnosis of cardiovascular diseases including heart failure (HF). The application of artificial intelligence (AI) has contributed to clinical practice in terms of aiding diagnosis, prognosis, risk stratification and guiding clinical management. The aim of this study is to systematically review and perform a meta-analysis of published studies on the application of AI for HF detection based on the ECG. We searched Embase, PubMed and Web of Science databases to identify literature using AI for HF detection based on ECG data. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) criteria. Random-effects models were used for calculating the effect estimates and hierarchical receiver operating characteristic curves were plotted. Subgroup analysis was performed. Heterogeneity and the risk of bias were also assessed. A total of 11 studies including 104,737 subjects were included. The area under the curve for HF diagnosis was 0.986, with a corresponding pooled sensitivity of 0.95 (95% CI: 0.86-0.98), specificity of 0.98 (95% CI: 0.95-0.99) and diagnostic odds ratio of 831.51 (95% CI: 127.85-5407.74). In the patient selection domain of QUADAS-2, eight studies were designated as high risk. According to the available evidence, the incorporation of AI can aid the diagnosis of HF. However, there is heterogeneity among machine learning algorithms and improvements are required in terms of quality and study design.

Elevated circulating level of β-aminoisobutyric acid (BAIBA) in heart failure patients with type 2 diabetes receiving sodium-glucose cotransporter 2 inhibitors

AimsThe mechanism by which a sodium-glucose cotransporter inhibitor (SGLT2i) induces favorable effects on diabetes and cardiovascular diseases including heart failure (HF) remains poorly understood. Metabolomics including amino acid profiling enables detection of alterations in whole body metabolism. The aim of this study was to determine whether plasma amino acid profiles are modulated by SGLT2i use in HF patients with type 2 diabetes mellitus (T2DM).MethodsWe retrospectively examined 81 HF patients with T2DM (68 ± 11 years old; 78% male). Plasma amino acid concentrations in a fasting state after stabilization of HF were determined using ultraperformance liquid chromatography. To minimize potential selection bias in the retrospective analyses, the differences in baseline characteristics between patients receiving an SGLT2i and patients not receiving an SGLT2i were controlled by using an inverse probability of treatment weighting (IPTW)-adjusted analysis.ResultsOf amino acids measurable in the present assay, plasma β-aminoisobutyric acid (BAIBA), an exercise-induced myokine-like molecule also known as 3-aminoisobutyric acid or 3-amino-2-methyproponic acid, was detected in 77% of all patients and the proportion of patients in whom plasma BAIBA was detected was significantly higher in patients receiving an SGLT2i than in patients not receiving an SGLT2i (93% vs. 67%, p = 0.01). Analyses in patients in whom plasma BAIBA was detected showed that plasma BAIBA concentration was significantly higher in patients receiving an SGLT2i than in patients not receiving an SGLT2i (6.76 ± 4.72 vs. 4.56 ± 2.93 nmol/ml, p = 0.03). In multivariate logistic regression analyses that were adjusted for age and sex, SGLT2i use was independently associated with BAIBA detection. The independent association between BAIBA and SGLT2i use remained after inclusion of body mass index, HF with reduced ejection fraction, ischemic etiology, renal function, NT-proBNP, albumin, hemoglobin, and HbA1c into the Cox proportional hazards model. When the differences in baseline characteristics between patients receiving an SGLT2i and patients not receiving an SGLT2i were controlled by using an IPTW-adjusted analysis, least squares mean of plasma BAIBA concentration was significantly higher in patients receiving an SGLT2i than in patients not receiving an SGLT2i.ConclusionSGLT2i use is closely associated with increased circulating BAIBA concentration in HF patients with T2DM.

Role of omega-3 fatty acids in the prevention and treatment of cardiovascular Diseases: A consensus statement from the Experts' Committee Of National Society Of Cardiometabolic Medicine.

Low-density lipoprotein cholesterol (LDL-C) has been considered as the primary target for the prevention and treatment of atherosclerotic cardiovascular disease (ASCVD). However, there are still residual cardiovascular risks in some patients even if LDL-C achieves the target level. Emerging evidence suggestes that elevated triglyceride (TG) level or triglyceride-rich lipoprotein (TRL) cholesterol (TRL-C) is one of the important components of the residual cardiovascular risks. Omega-3 fatty acids have been shown to be one of the effective drugs for reducing TG. However, its efficacy in reducing the risk of ASCVD is inconsistent in large randomized clinical trials. There is lack of consensus among Experts regarding the application of omega-3 fatty acids in cardiovascular diseases including heart failure, arrhythmia, cardiomyopathy, hypertension, and sudden death. Hence, the current consensus will comprehensively and scientifically present the detailed knowledge about the omega-3 fatty acids from a variety of aspects to provide a reference for its management of omega-3 fatty acids application in the Chinese population.