Chen, Horng H.

BACKGROUND: It is unknown whether cardiac resynchronization therapy (CRT) improves systemic metabolomic profile by enhancing left ventricular function. The observational cohort study aimed to investigate the effect of CRT on left ventricular ejection fraction (LVEF) and circulating plasma metabolites in patients who had heart failure with reduced LVEF. METHODS: We prospectively screened patients with ischemic cardiomyopathy and nonischemic cardiomyopathy who received CRT with a defibrillator for LVEF ≤35% according to current guidelines. Clinical assessment included echocardiography and device interrogation. Blood samples for metabolomic analysis were collected before CRT and at 6-month follow-up. Plasma was subjected to gas chromatography-mass spectrometry and 1 H nuclear magnetic resonance-based metabolomic analysis. RESULTS: Totally 92 patients were enrolled, with a mean age of 67.3±11.3 years (37.0% female). LVEF was significantly improved from 28.9±7.6% at baseline to 36.0±11.3% at 6 months ( P <0.001) and to 40.1±12.6% at 12 months ( P <0.001). After CRT, 42 metabolite features were significantly decreased compared with the baseline. The ketone bodies, including 3-hydroxybutyrate ( P <0.001) and acetone ( P =0.01), were reduced. A branched-chain amino acid, isoleucine, was also decreased after CRT ( P =0.01). These metabolomic changes were mainly observed in the nonischemic cardiomyopathy group, while the metabolomic profile in the ischemic cardiomyopathy group was characterized by enhanced amino acid oxidation and elevated levels of lactate and pyruvate. The improvement in LVEF positively correlated with the ratio of changes in ketone bodies and isoleucine. CONCLUSIONS: CRT may modulate the systemic plasma metabolomic profile, which correlated with improvement in left ventricular function in patients with severe heart failure with reduced ejection fraction.

BACKGROUND: Although diabetes is a known driver of heart failure with preserved ejection fraction, whether antecedent hyperinsulinemia drives preclinical diastolic dysfunction (DD) progression before overt hyperglycemia remains unknown. Therefore, we investigated whether elevated endogenous insulin and insulin resistance independently predict longitudinal DD progression and adverse cardiovascular outcomes. METHODS: In a community-based cohort study, we evaluated 1191 participants from the Olmsted County Heart Function Study (median age, 58.7 [interquartile range, 52.4–66.6 years]) who underwent echocardiography at baseline and after 4 years. Fasting insulin and homeostatic model assessment of insulin resistance were assessed. The primary end point was DD progression. Secondary outcomes (mortality, heart failure) were assessed in 2030 participants followed for a median of 10.97 (95% CI, 10.90–11.05) years for heart failure and a median of 18.1 (95% CI, 18.0–18.2) years for mortality. RESULTS: DD progression occurred in 7.5% of participants. Baseline fasting insulin and homeostatic model assessment of insulin resistance strongly predicted progression ( P <0.001). In multivariable analysis, every 1-SD increase in log-transformed insulin was associated with 65% increased odds of progression (odds ratio, 1.65 [95% CI, 1.33–2.07]; P <0.001), adjusting for age, creatinine, and NT-proBNP (N-terminal pro-B-type natriuretic peptide). Similar results were observed for homeostatic model assessment of insulin resistance (odds ratio, 1.66 [95% CI, 1.34–2.08]; P <0.001). In secondary analyses, elevated insulin independently predicted all-cause (hazard ratio, 1.11 per 1-SD [95% CI, 1.02–1.21]) and cardiovascular mortality (hazard ratio, 1.16 [95% CI, 1.02–1.33]). Homeostatic model assessment of insulin resistance was similarly predictive of all-cause (hazard ratio, 1.11 [95% CI, 1.03–1.20]) and cardiovascular mortality (hazard ratio, 1.16 [95% CI, 1.02–1.32]). CONCLUSIONS: Elevated endogenous insulin and insulin resistance are predictors of progressive DD and long-term mortality, even after accounting for body mass index. Metabolic dysregulation may drive myocardial stiffening before diabetes onset, identifying a potential early therapeutic window for heart failure with preserved ejection fraction prevention.

ABSTRACT Background Acute heart failure (AHF) exhibits marked heterogeneity in diastolic hemodynamics, yet comprehensive echocardiographic assessment of diastolic function (DF) and filling pressure (FP) is often infeasible. We evaluated whether artificial intelligence–enabled electrocardiography (AI-ECG) could provide scalable DF grading and FP estimation in hospitalized AHF patients. Methods We retrospectively studied adults hospitalized for AHF across Mayo Clinic sites (2013–2023) who received ≥1 dose of intravenous loop diuretic and had paired 12-lead ECG and TTE. The previously validated AI-ECG DF model was applied without retraining to generate four DF grades and a continuous FP probability. Clinical outcomes were all-cause mortality and heart failure rehospitalization. Associations with clinical severity markers and echocardiographic indices were examined. Kaplan–Meier survival analysis and adjusted multivariable Cox proportional hazards models were performed. Exploratory analyses examine the kinetics of change in FP probability and impact on mortality. Results Among 11,513 patients (median age 75 years, 39% female), AI-ECG DF grading was feasible in 100%, whereas echocardiographic DF was indeterminate in 44% of clinically eligible patients. In 2,582 patients with determinate echocardiographic DF, AI-ECG FP probability discriminated TTE Grade 2–3 dysfunction with AUC 0.85 (95% CI 0.83 – 0.86). Higher AI-ECG DF grades were associated with higher comorbidity burden, worse NYHA class, elevated NT-proBNP, higher MAGGIC scores, elevated PCWP, and more advanced structural remodeling. After multivariable adjustment, AI-ECG DF remained independently associated with mortality (hazard ratio [HR] 1.25, 95% CI 1.16–1.35 for Grade 2; HR 1.44, 95% CI 1.33–1.56 for Grade 3 versus Normal/Grade 1). Combining AI-ECG DF with MAGGIC scores yielded ordered risk gradients, with highest mortality in patients with both high MAGGIC and Grade 2–3 DF. Among patients with serial ECGs, improvement in FP probability was independently associated with lower mortality (HR 0.85, 95% CI 0.79–0.91), whereas worsening did not show a consistent adverse gradient beyond baseline DF. Conclusions In a large, geographically diverse AHF cohort, AI-ECG DF grading was universally feasible, correlated with established hemodynamic severity markers, and provided independent prognostic information beyond established risk factors, supporting its role as a pragmatic, scalable diastolic biomarker in AHF. CLINICAL PERSPECTIVE What Is New? In 11,513 hospitalized acute heart failure (HF) patients, artificial intelligence-enabled electrocardiography provided diastolic function grading in 100% of patients from a single 12-lead ECG without requiring additional clinical variables, compared with 56% feasibility for guideline-based echocardiography grading. AI-ECG diastolic function grades correlated with established marker of severity (NYHA functional class, NT-proBNP, MAGGIC risk scores, and pulmonary capillary wedge pressure) and remained independently associated with both mortality and HF rehospitalization after multivariable adjustment. Serial AI-ECG measurements identified post-discharge filling pressure trajectories, with improvement independently associated with 15% lower mortality, a first demonstration that longitudinal ECG assessment can track post-discharge hemodynamic recovery. What Are the Clinical Implications? AI-ECG transforms the universally obtained 12-lead ECG into an actionable hemodynamic biomarker that addresses the critical gap when echocardiographic diastolic function assessment is indeterminate or unavailable in acute HF patients. Despite markedly different hemodynamic severity and long-term outcomes across AI-ECG diastolic function grades, hospitalization length of stay did not differ, suggesting advanced diastolic dysfunction represents occult risk not easily recognized during routine acute care and highlighting the need for improved post-discharge risk stratification. The continuous filling pressure probability metric enables longitudinal monitoring of post-discharge hemodynamic status using serial routine ECGs, potentially identifying patients requiring intensified follow-up or specialist referral.

Abstract Background Left ventricular diastolic function (LVDF) and left bundle branch block (LBBB) are both linked with increased risk of LV systolic dysfunction, heart failure, and mortality. Assessing LVDF, which is typically done through echocardiography, becomes challenging in the presence of LBBB due to the intraventricular conduction delay that disrupts the reliability of tissue Doppler imaging. Recently, we validated an artificial intelligence-enabled electrocardiogram (AI-ECG) model to assess LVDF and filling pressures. Methods We performed a retrospective study among patients with ECG-confirmed LBBB who also underwent comprehensive echocardiography within 14 days of the index ECG between September 2001 and June 2022. Using multivariable survival models, we assessed the risk of all-cause mortality across AI-ECG-derived LVDF grades. Results Of 2,554 patients with LBBB (mean age 72.0+12.6, 54.6% women), 252 (9.8%), 656 (25.7%), and 1,436 (56.2%), and 210 (8.2%) had normal LVDF, G1 LVDF, G2 LVDF, and G3 LVDF, respectively. The median LV ejection fraction (LVEF) was 54% and 49.3% of the patients had heart failure. Worse LVDF was associated with older age, lower LVEF, and higher rates of diabetes, hypertension, chronic pulmonary disease, renal failure, cardiovascular disease, and heart failure (p-of-trend&lt;0.001 for all). During a median follow-up of 2.6 years (interquartile range 0.5-4.0 years), 847 (33.2%) patients died. In multivariable survival analysis, adjusted to multiple risk factors including baseline LVEF and heart failure, worse LVDF was independently associated with a higher risk of death [G1 LVDF: adjusted hazard ratio (aHR) 2.15 (95% confidence interval (95%CI) 0.75-1.77), G2 LVDF: aHR 2.25 (95%CI 1.50-3.38) G3 LVDF: aHR 2.96 (95%CI 1.88-4.65); p&lt;0.001 for both)]. These findings were consistent also in a subgroup of patients with baseline LVEF &gt; 50%. Conclusion Among patients with LBBB, worse LVDF, as derived by a dedicated AI-ECG algorithm is independently associated with all-cause mortality beyond baseline LVEF and clinical heart failure.survival across AI-ECG LVDF grades

Introduction: Diabetes mellitus (DM) is strongly associated with metabolic and cardiorenal derangements. Natriuretic peptides (NPs), and glucagon-like peptide 1 receptor agonists (GLP-1 RA) have well-established cardiometabolic and cardiorenal protective effects. We developed a novel bispecific biologic, CRRL 101, which agonizes guanylyl cyclase A (GCA) NP receptors and GLP-1 receptors. In this study, we sought to evaluate the in vitro effects and in vivo impact of CRRL 101 in a DM rat model. Methods: In vitro experiments evaluated the impact of CRRL 101 treatment of GCA receptor transfected human embryonic kidney (HEK) cells and INS-1 rat pancreatic beta cells. In vivo experiments were conducted by inducing DM in Wistar rats (male, 6-8-week-old) by intraperitoneal Streptozotocin (STZ) injection (65 mg/kg). One week after STZ injection, DM was confirmed (fasting blood glucose > 350 mg/dL). Rats were then divided into 3 groups: saline control (n=6), 1 pmol/kg/min CRRL-101 (“1pmol” n= 4), and 10 pmol/kg/min CRRL-101 (“10 pmol” n=5). Treatment was infused for 120 min after which rat blood and urine were collected. Data were analyzed using GraphPad Prism 10.0.0. Results: In vitro, there was a marked increase in cyclic GMP (cGMP) levels (pmol/mL) in HEK treated with 10 -6 M CRRL 101 (mean difference ± SEM:1.603 ± 0.29 p = 0.0048). In INS-1 cells treated with CRRL 101 at 10 -6 M in a 20 mM glucose medium, cAMP levels (pmol/mL) markedly increased (16.7 ± 1.47 vs 23.19 ± 1.51 p=0.0036) and insulin levels (ng/mL) doubled (4.4 ng/mL ± 0.44 vs 9.5 ng/mL ± 0.34 in 20 mM glucose p < 0.0001). Similar increases were observed at lower doses (10 -7 M, 10 -8 M) of CRRL 101. In vivo , after 120 minutes of treatment, mean plasma cGMP levels were 6.5x greater in both groups (mean difference± SEM) (1pmol: 38.89 ± 7.93, p = 0.016; 10pmol: 39.40 ± 4.84 p=0.001). Plasma insulin (ng/mL) more than doubled with both doses (1pmol: 0.39 ± 0.148, p = 0.039; 10 pmol: 0.198 ± 0.051, p = 0.004) with no significant increase with placebo ( 0.03 ± 0.08, p = 0.67). Rate of natriuresis (mEq/min) more than doubled with peptide administration vs placebo (1 pmol: 0.36 ± 0.093 p = 0.014; 10 pmol: 0.38 ± 0.13, p = 0.034). Conclusions: Our novel bispecific biologic, CRRL 101, activates GC-A, increasing plasma cGMP and inducing natriuresis, and stimulates GLP-1R, raising cAMP and plasma insulin. Chronic administration studies to eludicate its therapeutic efficacy are warranted.

Abstract Aims Define the relationship between N‐terminal atrial natriuretic peptide (NT‐ANP) levels and incident metabolic syndrome and type 2 diabetes mellitus (‘metabolic disease’) in healthy adults and develop a risk prediction score. Materials and Methods Retrospective cohort study of Olmsted County Heart Function Study participants, a random sampling of county residents aged 45 years and older ( n = 2042). Clinical data were collected during enrolment between 1997 and 2000 and upon follow‐up 4 years later. Outcomes were followed for 8 years. We studied 715 subjects without metabolic disease at enrolment who completed follow‐up, assessing incident metabolic disease as the primary outcome. Youden's index was used to identify optimal cut‐points and develop the risk score. Results Upon multivariate analysis adjusting for age gender, HDL and triglycerides, higher baseline serum NT‐ANP levels were associated with a lower risk of metabolic disease (OR: 0.65, CI 0.49–0.85, p = 0.002). Higher baseline serum insulin and aldosterone levels were associated with higher risk of incident metabolic disease (OR: 2.04, CI 1.57–2.65, p < 0.001; OR: 1.43, CI 1.14–1.81, p = 0.002, respectively). Baseline serum NT‐ANP < 3337 pg/mL was 96.6% sensitive for future development of metabolic disease. A weighted score including all three biomarkers was 78.6% sensitive and 77.3% specific. Conclusions In healthy adults aged 45 years or older, higher baseline NT‐ANP levels are associated with a lower four‐year risk of developing metabolic disease. Serum NT‐ANP levels are a sensitive biomarker of future risk of metabolic disease and have screening utility when combined with insulin and aldosterone levels into a composite score.

BACKGROUND: Cardiorenal dysfunction with impaired cyclic GMP (cGMP) response is common in patients presenting with acute heart failure (HF). Type V phosphodiesterase (PDEV) is known to be upregulated in HF and may explain the dysfunction of renal response. The aim of this study was to determine whether B-type natriuretic peptide (BNP) alone or in combination with PDEV inhibition improves renal function and increases urinary sodium and cGMP excretion in acute HF. METHODS: This open-label study included 67 patients hospitalized with acute HF and renal dysfunction. Patients were randomized to standard care, low-dose intravenous BNP (0.005 µg/kg per minute), or combination BNP/PDEV inhibition with sildenafil (25 mg q12 hours) for 48 hours. The coprimary end points were the percent change in estimated glomerular filtration rate and blood urea nitrogen from baseline to 48 hours. RESULTS: Treatment with BNP and BNP/PDEV inhibitor significantly increased plasma cGMP at 24 hours (+25.6% [+9.8%, +84.7%] and +60.8% [+32.3%, +103.8%] for BNP and BNP/PDEV versus −13.5% [−29.1%, +14.2%] with standard care; P =0.001). However, there was no significant change in estimated glomerular filtration rate 0 (−10.8%, +12.7%) for standard care versus 0 (−15.3%, +11.8%) for the BNP group versus –8.8% (−14.3%, +8.3%) for the BNP/PDEV group ( P =0.60) or blood urea nitrogen −1.4% (−10.7%, +12.0%) for standard care versus –5.9% (−14.6%, +9.4%) for the BNP group versus +6.9% (−5.3%, +18.8%) for the BNP/PDEV group ( P =0.38) between groups. Hypotension was more common in the BNP/PDEV inhibitor group. CONCLUSIONS: BNP and combination BNP/PDEV inhibition increased plasma cGMP in patients with acute HF but did not improve renal function or urinary sodium/cGMP excretion. Our study does not support the use of intravenous low-dose BNP with or without PDEV inhibition to enhance renal function in patients admitted with acute HF. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT00972569.

Introduction: Among those hospitalized with heart failure, diabetes (DM) is a common comorbid condition and the population characteristics and natural history of those with preserved EF (HFpEF) versus those with reduced EF (HFrEF) remain undefined. Hypothesis: To determine the epidemiologic profile and natural history among those hospitalized with acute heart failure (AHF) with DM and compare outcomes of those with reduced versus preserved EF. Methods: A retrospective chart analysis of adults hospitalized with primary ICD diagnosis of AHF from Olmsted County hospitalized from 2005 - 2008, with follow up until 2013. Demographic, clinical and lab data were collected. Results: Of 912 subjects hospitalized with AHF, 381 (42%) had DM. Among subjects with AHF and DM, those with HFrEF were similar in age to those with HFpEF (76.3±11.7 years vs 78.3±11.2 years, p=0.12), but were more likely to be male (58% vs 37%, p<0.001). Those with DM and HFrEF compared to HFpEF had less hypertension (95% vs 99%, p=0.046), but more coronary artery disease (89% vs 75%, p<0.001), prior myocardial infarction (65% vs 33%, p<0.001), and higher BNP values (1155±906 pg/mL vs 676±568 pg/mL, p<0.001). E/e’ ratio was similar in those with DM and HFrEF versus HFpEF (22.6±10.4 vs 21.7±10.9, p=0.49), suggesting both groups had increased filling pressures. There was no difference in mortality between the HFrEF and HFpEF groups up to 5 years in either the DM group (p=0.46) or the non-DM group (p=0.11). However, those hospitalized with AHF and DM demonstrated a higher rate in those with HFrEF versus HFpEF groups in all cause rehospitalization (p=0.019) and heart failure rehospitalization (p=0.008). This was different from the non-DM group, where there was no difference between HFrEF and HFpEF in all cause hospitalization (p=0.31) or heart failure rehospitalization (p=0.19). Conclusions: In patients hospitalized for AHF with DM, those with HFrEF had increased all cause and heart failure hospitalization as compared to HFpEF. In contrast, subjects without DM had no differences in rehospitalization between the HFrEF and HFpEF groups. Further studies are warranted to define pathophysiological mechanism for this observation.