Circulation: Heart Failure

Background: Neighborhood-level social determinants of health influence cardiovascular outcomes; however, their association with post-discharge healthcare utilization in heart failure with preserved ejection fraction (HFpEF) remains incompletely defined. Methods: We conducted a retrospective cohort study of 6,702 adults hospitalized for HFpEF (2014 to 2022). Patients were assigned to one of four neighborhood environments (NEnv-1 to NEnv-4) using a validated clustering framework based on ZIP code-level socioeconomic variables. The primary outcome was time to first HF readmission, evaluated within prespecified post-discharge intervals (0-30 days, >30-90 days, and >90-365 days). Secondary outcomes included HF-related healthcare re-encounters and HF hospitalization burden (0, 1, or [≥]2 admissions). Cox proportional hazards and multinomial logistic regression models were used. Results: Neighborhood environment was independently associated with post-discharge outcomes with distinct temporal patterns. Early (0-30 days) HF readmission risk was higher in NEnv-3 (aHR, 1.63) and NEnv-4 (aHR, 1.76), with similar increases in HF-related re-encounters (aHR, 1.72 and 1.84) persisting through the >30-90-day interval. In contrast, NEnv-2 demonstrated a delayed-risk pattern, with the highest risk occurring in the >90-365-day interval (readmission aHR, 3.42; re-encounter aHR, 3.45). All non-reference environments were associated with a higher likelihood of at least one post-index HF admission (aOR range, 1.84-2.24). NEnv-4 uniquely demonstrated higher odds of recurrent hospitalization ([≥]2 vs. 1 admission; aOR, 1.64). Conclusions: Neighborhood environment is associated with distinct, time-dependent patterns of HF utilization in HFpEF, including early, delayed, and recurrent risks. Incorporating neighborhood context may help identify when patients with HFpEF are most vulnerable after discharge and guide the timing of post-discharge interventions.

Background: Glucagon-like peptide 1 receptor agonists (GLP-1 RA) are indicated for weight reduction and offer cardiometabolic health benefits, yet there is little real-world evidence regarding their association with healthcare resource utilization (HCRU) and costs for Medicare Advantage (MA) beneficiaries with heart failure and obesity. Methods: We used a prevalent new-user study design and the Humana Healthcare Research database to identify MA beneficiaries with heart failure (HF) and obesity receiving standard HF therapy or HF therapy + newly initiating GLP-1 RA between January 1, 2022, and December 31, 2023. We observed adjusted, one-year mean difference in all-cause and heart failure-related HCRU. Results: In our cohort of 4,677 matched pairs (mean age 72 years, male: 41%), one-year, adjusted risk ratio (RR) for HF therapy + GLP-1 RA vs HF therapy was 0.89 (95% CI: 0.84 ? 0.93) for all-cause inpatient utilization, 0.88 (95% CI: 0.82 ? 0.94) for avoidable hospitalizations, and 0.99 (95% CI: 0.95 ? 1.03) for emergency department visits. For individuals receiving HF therapy + GLP-1 RA vs HF therapy, the mean difference was 30.6% (95% CI: 26.7% ?34.7%) for all-cause total costs, 105.9% (95% CI: 99.1% ?112.9%) for pharmacy costs, and ?4.7% (95% CI: ?8.7% to ?0.6%) for medical costs. HF-related HCRU measures were lower among beneficiaries augmenting HF therapy with GLP 1 RA vs individuals receiving HF therapy alone. Conclusions: Among MA beneficiaries with heart failure and obesity, the addition of GLP-1 RA to standard heart failure therapy reduced the likelihood of inpatient admissions or avoidable hospitalizations compared with HF therapy alone.

Residual congestion is the principal driver of heart failure readmission, and reliable serial assessment of volume status remains an unmet clinical need. This study asked whether a wrist-worn, machine-learning-based device for non-invasive venous waveform analysis in heart failure (the NIVAHF device), which produces an integer-scaled estimate of pulmonary capillary wedge pressure termed the NIVA Score, responds to acute changes in volume status. Agreement between the NIVA Score and invasively measured pulmonary capillary wedge pressure at single time points has been established in a separate prospective, multi-site study; however, such static agreement does not establish whether the measure tracks dynamic decongestion. We therefore evaluated the directional responsiveness of the locked NIVA Score in two prespecified cohorts: hospitalized adults with acute decompensated heart failure undergoing routine intravenous diuresis, and a controlled porcine model of volume overload followed by diuresis. In eleven patients contributing thirteen paired measurements (mean net fluid balance -2.1 {+/-} 1.0 L), NIVA Scores decreased significantly after diuresis (paired t-test, P = 0.04). In five pigs contributing twenty-four paired measurements, NIVA Scores decreased significantly after intravenous furosemide following crystalloid loading (P < 0.01), and the direction of change was concordant with measured urine output in every animal. Statistical significance was reached in both cohorts despite modest sample sizes, indicating a measurable NIVA Score reduction with volume removal. In an exploratory analysis, the discharge NIVA Score yielded an area under the receiver-operating-characteristic curve of 0.85 (95% confidence interval 0.575-1.00; P = 0.04) for thirty-day readmission. Together, the significant, directionally concordant NIVA Score reductions across independent clinical and preclinical cohorts demonstrate that the device tracks acute decongestion and support its use for serial, non-invasive congestion monitoring; an adequately powered prospective study is the planned next step.

Background. Heart failure with preserved ejection fraction (HFpEF) accounts for more than half of heart failure cases and is characterized by substantial clinical and biological heterogeneity. Sex differences are central to HFpEF pathophysiology, yet current phenotyping approaches often aggregate women and men, potentially obscuring distinct molecular mechanisms of disease progression. Molecularly resolved, sex-specific stratification is therefore needed to identify divergent risk pathways and improve biological understanding of HFpEF heterogeneity. Methods. In 698 HFpEF participants from the prospective MyoVasc cohort (379 females, 319 males), we run separate analyses on sex-specific cohorts. For each cohort, we integrated 92 circulating proteins (Olink Inflammation panel) and 49 clinical variables using Similarity Network Fusion to construct sex-stratified patient-patient similarity networks. Spectral clustering identified sex-specific prognostic subgroups related to the primary endpoint, i.e. worsening of Heart Failure (WHF). XGBoost models characterizing cluster-defining features were validated in an independent cohort of 342 HFpEF patients from the Gutenberg Health Study (GHS; 194 females, 148 males). Results. Two clusters emerged in each sex, with high-risk and low-risk clusters, showing the difference in WHF risk (MyoVasc females: HR 2.45, 95% CI 1.32-4.54, p=0.005; males: HR 2.77, 95% CI 1.27-6.04, p=0.011; C-index 0.62-0.63). Kaplan-Meier analyses confirmed separation (p<0.02 females, p<0.01 males). Clusters were reproduced in GHS using MyoVasc-trained XGBoost (females p=0.0082, males p=0.037). Shared top-ranking features included VEGF-A, TNFRSF9, and TGF-. Females were characterized by inflammatory (CD40, HGF, TNF) and glycemic signatures, whereas males showed prominence of immune-regulatory markers (IL-10RB, PD-L1) and renal function indicators (eGFR, creatinine). Conclusions. Sex-stratified molecular-clinical networks define prognostically distinct HFpEF subgroups with robust external validation. Shared protein biomarkers alongside sex-specific drivers reveal complementary progression mechanisms, supporting precision medicine strategies targeting high-risk cluster patients in sex-specific manner.

Background World Symposium on Pulmonary Hypertension (WSPH) Group 2 pulmonary hypertension (PH) is a clinically integrated phenotype attributed to left heart disease, whereas pre- versus post-capillary classification is operationalized primarily by pulmonary capillary wedge pressure (PCWP). Although current recommendations emphasize contextual interpretation and provocative testing for intermediate PCWP values, the relationship between PCWP-based classification and underlying phenotype has not been systematically evaluated. We aim to quantify phenotype-hemodynamic discordance across the PCWP spectrum and evaluate a staged physiology-guided framework incorporating inhaled nitric oxide (iNO), ventricular geometry, and provocative testing. Methods We studied 1,032 participants from the NHLBI-sponsored PVDOMICS cohort with multidisciplinary adjudicated phenotypes integrating clinical, imaging, physiologic, and hemodynamic data. Stage-specific PCWP thresholds classified pre- versus post-capillary physiology at rest, during iNO, and during provocation (fluid challenge or invasive cardiopulmonary exercise testing [iCPET]). Echocardiographic right ventricular-to-left ventricular (RV/LV) ratio was evaluated as a marker of ventricular interdependence. Restricted cubic spline and staged concordance analyses defined certainty-based PCWP ranges and incremental diagnostic yield. Results Adjudicated Group 2 phenotype was present in 37.0% of participants. Resting PCWP demonstrated good discrimination (AUC 0.86), but substantial bidirectional phenotype-hemodynamic discordance persisted across intermediate PCWP ranges. At a resting PCWP of 12 mmHg, 25% of participants classified as pre-capillary had adjudicated Group 2 PH, whereas at 18 mmHg, 35% classified as post-capillary remained discordant non-Group 2. Concordance did not approach 90% until PCWP values were <9 mmHg or >24 mmHg. Dynamic testing incrementally improved concordance within these overlap zones. Nearly half of adjudicated Group 2 PH participants (46.5%) were not identified by resting PCWP alone; incorporation of iNO and provocative testing increased cumulative Group 2 identification by 63.4% and improved sensitivity from 79.9% to 83.7%. Model discrimination improved from an AUC of 0.863 to 0.908 (likelihood-ratio P<0.001). iNO increased PCWP in discordant Pre/G2 participants, unmasking latent left-sided limitation, while lowering PCWP in discordant Post/NonG2 participants, consistent with ventricular interdependence. RV/LV ratio [&ge;]0.94 reduced discordant Post/NonG2 classification by 70.5%, and incorporation of PCWP/cardiac output slope improved physiologic specificity during exercise. Conclusions Group 2 PH is a dynamic, load-dependent phenotype inadequately characterized by resting PCWP alone. Intermediate PCWP values represent continuous probabilities of bidirectional discordance rather than discrete diagnostic states. A staged physiology-guided approach integrating iNO, ventricular geometry, and provocative testing improves concordance between hemodynamic classification and clinically integrated phenotype assignment.

Background: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome, and patients with a small left ventricular (LV) volume phenotype exhibit greater preload dependency. Whether the association between persistent outpatient oral loop diuretic use and clinical outcomes differs by LV volume phenotype remains unclear. Methods: We conducted a retrospective single-center cohort study of consecutive patients with heart failure and an LV ejection fraction [&ge;]50% who underwent transthoracic echocardiography between 2009 and 2024. Patients were stratified by LV volume phenotype using sex-specific LV end-diastolic volume index cutoffs. Associations between outpatient oral loop diuretic use and HF hospitalization, worsening renal function, and all-cause death were evaluated using multivariable time-varying Cox proportional hazards models, including interaction testing by LV phenotype. Results: Among 12,748 eligible patients, 1,437 had a small LV phenotype and 11,311 had a normal LV phenotype. Patients with a small LV phenotype initiated outpatient oral loop diuretics earlier and more frequently than those with a normal LV phenotype, while maintenance doses were comparable between groups. Outpatient oral loop diuretic use was associated with HF hospitalization in both phenotypes, with a significantly stronger association in the small LV group (hazard ratio [HR], 2.52; 95% confidence interval [CI], 1.68-3.78) than in the normal LV group (HR, 2.10; 95% CI, 1.77-2.49; P for interaction = 0.001). No significant interaction by LV phenotype was observed for worsening renal function or all-cause death. Fine-Gray competing-risk analyses showed a consistent interaction pattern. Conclusions: Persistent outpatient oral loop diuretic use was more strongly associated with HF hospitalization in patients with a small LV phenotype than in those with a normal LV phenotype. LV volume phenotype may help identify patients who warrant closer monitoring and more individualized diuretic management.

Population-level data on preclinical heart failure (HF) remain limited because most epidemiological studies focus on symptomatic HF. We therefore developed an administrative-data algorithm to classify HF stages across the national population and describe temporal trends, stage transitions, and mortality across the HF continuum. Methods Using a claims-based staging framework adapted from the Universal Definition of HF, we classified HF stages from ICD-10 codes, prescription records, and medical procedures. We applied this algorithm to the Czech population, linking the National Registry of Reimbursed Health Services to National mortality records from 2015 to 2024. Results In 2024, 27.8% of the Czech population met criteria for Stage A HF and 8.2% for Stage B. Over 10 years, the prevalence of both preclinical stages increased beyond what could be explained by population aging alone, with age-standardized prevalence rising by 9.5% for Stage A and 19.2% for Stage B. Age-standardized 1-year mortality showed a steep stepwise gradient, from 0.69% in Stage A to 1.69% in Stage B, 3.06% in Stage C, and 7.27% in Stage D. Among 52,172 individuals with incident clinical HF in 2024, more than 95% had previously met administrative criteria for Stage A or Stage B. Conclusion Administrative surveillance of the HF continuum using routinely collected healthcare data provides a scalable administrative framework for population-level monitoring of HF burden. In Czechia, both preclinical and clinical HF burdens increased over time beyond population aging alone, underscoring the need for earlier preventive strategies targeting preclinical disease.

Background: Obesity is a major modifiable risk factor for heart failure (HF), but body mass index (BMI) does not distinguish biologically distinct fat depots. Whether imaging-derived adipose tissue depots capture specific cardiometabolic pathways underlying HF risk beyond conventional anthropometric measures remains uncertain. Methods: We performed two-sample Mendelian randomization (MR) and multivariable MR mediation analyses using published genome-wide association study summary statistics. General adiposity traits included BMI, waist-to-hip ratio (WHR), and WHR adjusted for BMI from GIANT and UK Biobank meta-analyses of up to 694,649 individuals. MRI-derived visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and gluteofemoral adipose tissue (GFAT) were derived from 38,965 UK Biobank participants. HF outcome data were obtained from the HERMES consortium, including 1,946,349 individuals and 153,174 HF cases. Cardiometabolic mediators included type 2 diabetes (T2D), systolic blood pressure (SBP), LDL cholesterol, HDL cholesterol, and triglycerides. Primary analyses used inverse-variance weighted MR, with sensitivity analyses and directionality testing. Mediation was estimated using joint multivariable MR conditioning on significant cardiometabolic mediators. Results: Among MRI-derived adipose depots, ASAT was the only trait significantly associated with HF risk (odds ratio [OR] 1.64 per 1-SD increase; 95% CI 1.40-1.93; FDR q<0.001). VAT showed a positive but imprecise association (OR 1.38; 95% CI 0.87-2.20), and GFAT was not associated with HF. Among general adiposity measures, BMI (OR 1.65; 95% CI 1.58-1.71) and WHR (OR 1.30; 95% CI 1.23-1.38) were robustly associated with HF, whereas WHR adjusted for BMI was not. ASAT was significantly associated with T2D, SBP, HDL cholesterol, and triglycerides, but not LDL cholesterol. In joint multivariable MR, 67.9% of ASAT's HF effect was mediated through T2D, SBP, HDL cholesterol, and triglycerides (95% CI 49.2-86.8%). In contrast, BMI demonstrated only 8.5% mediation (95% CI -7.4 to 24.4%), and WHR showed non-significant mediation of 36.7% (95% CI -8.3 to 81.7%). Conclusions: MRI-derived abdominal subcutaneous adipose tissue captures a biologically coherent cardiometabolic signal underlying HF risk that is diluted by conventional anthropometric measures. ASAT may represent an imaging biomarker of metabolic syndrome-mediated HF risk and could support more precise risk stratification and mechanistically targeted prevention in HF.

Background: Approximately 40 million individuals in the US have diabetes, and 6.5 million are also afflicted with congestive heart failure (CHF). This paper outlines the natural history of CHF in T2DM and compares CHF outcomes between patients with and without T2DM. Methods: We performed a retrospective analysis of prospectively collected data from 2,008 patients hospitalized for CHF exacerbation between December 2016 and June 2019. Propensity score matching was used to match diabetics and nondiabetics. Outcomes included survival and readmission rates at 28 d, 3 mo and 6 mo, as well as comparison of echocardiographic findings. Results: A total of 2,008 patients were included. After matching, 492 patients were included, with 244 diabetics and 248 nondiabetics. After matching, readmission rates within 28 days (p=0.625) were not different, but there was a trend for higher readmission rates among diabetics at 3 months (29.3% vs. 21.5%, p=0.049) and 6 months (44.3% vs 35.8%, p=0.053). Echocardiographic characteristics, including LVEF (p=0.135), LV EDV (p=0.707), maximum velocity of mitral valve E wave (p=0.407), maximum velocity of mitral valve A wave (p=0.050), E/A ratio (p=0.501) and tricuspid valve regurgitation pressure (p=0.668) were not different in the two groups. However, tricuspid valve regurgitation velocity was higher in diabetics (3.1 vs 2.9, p=0.003). Conclusions: Although diabetes poses an additional burden for patients with CHF, survival is similar in diabetics and nondiabetics. Nonetheless, readmission rates may be higher among diabetics. Tricuspid return velocity is higher in diabetics, suggesting early pulmonary vasculature remodeling.

Background: The PREVENT (Predicting Risk of CVD EVENTs) equations estimate the risk of incident cardiovascular disease (CVD) in primary prevention patients. We hypothesized that risk factors incorporated in the equations may be relevant to prognosis in heart failure (HF) and investigated the association between estimated CVD risk and clinical outcomes in patients with preserved ejection fraction (HFpEF). Methods: We estimated the 10-year CVD risk using the PREVENT equations in 278 patients hospitalized for acutely decompensated HFpEF (median 75 years, 51.4% male). We divided them into four groups according to the quartiles of estimated CVD risk and followed them to observe major adverse cardiovascular events (MACE), a composite of all-cause death, HF hospitalization, and stroke. Results: MACE occurred in 125 patients (45.0%) over a median follow-up of 1,050 days. The estimated CVD risk classification was an independent predictor for MACE (p=0.02) in the multivariable Cox proportional hazard model. There was a difference in MACE-free survival across the four quartile groups (p<0.001 by log-rank test), and the lowest CVD risk group had significantly lower MACE incidence than other groups. The estimated CVD risk provided incremental prognostic value beyond N-terminal pro-B type natriuretic peptide (C-index: 0.626 vs, P=0.009). The predictive value of the estimated CVD risk for MACE at 1 year was comparable to that of the MAGGIC score (AUC 0.676 vs. 0.639, p=0.42). Conclusions: The 10-year CVD risk estimated by the PREVENT equations had a moderate predictive value for MACE in patients hospitalized for HFpEF.

Background: Adults with congenital heart disease (ACHD) represent a rapidly expanding population with evolving mortality patterns. Despite improved survival, excess mortality persists. Objective: To evaluate the incidence, causes, and predictors of mortality in a contemporary ACHD cohort. Methods: We performed a retrospective cohort study of adults (?18 years) first evaluated at Mayo Clinic from 2002?2023. Baseline clinical, imaging, and electrocardiographic data were analyzed. Vital status was determined using institutional records and the Accurint national mortality database. Kaplan-Meier analysis and Cox proportional hazard models were used to evaluate mortality and identify independent predictors of mortality Results: A total of 7,678 ACHD patients were included, with median age of 36.8 years and median follow-up of 11.4 years. During 78,768 patient-years of follow-up, 1,116 patients died (median age at death 57.2 years), corresponding to an annual mortality rate of 1.4%. The cumulative rate of all-cause mortality at 5, 10, 15, and 20 years was 6.9%, 12.0%, 19.0%, and 26.2%, respectively. When stratified by CHD complexity, the annual death rate in patients with severe CHD (2.4%/year) was twice that of patients with moderate or mild CHD (both 1.2%/year). Older age and ACHD subtypes, specifically, cyanotic heart disease (HR 3.9, 95% CI 2.9?5.3) and Fontan physiology (HR 3.2, 95% CI 2.3?4.4), were strongly associated with increased mortality. Additional independent predictors included male sex, ventricular dysfunction, advanced NYHA class, prior heart failure hospitalization, hypertension, smoking, coronary artery disease, renal dysfunction, and abnormal hemoglobin levels. Cardiovascular causes accounted for 57.7% of deaths with known etiology, predominantly heart failure (48.9%) and sudden cardiac death (21.9%), while non-cardiovascular causes were driven mainly by infection and malignancy. Conclusions: In this large contemporary ACHD cohort, mortality was driven by ventricular dysfunction, heart failure, and systemic end-organ involvement in addition to the underlying congenital anatomy. Both cardiovascular and non-cardiovascular causes contributed significantly to mortality. These findings underscore the need for comprehensive multidisciplinary ACHD care focused on early recognition of cardiac functional decline, management of acquired comorbidities, and end-organ dysfunction.

Importance: Heart failure readmissions remain common following hospitalization, but accurately identifying which patients will be readmitted after discharge remains challenging. Improved prediction could support targeted transitional care interventions and more efficient allocation of clinical resources. Objective: In this study we attempted to improve readmission prediction after heart failure hospitalization by using variables chosen through a modified Delphi process, and using inpatient Electronic Medical Record (EMR) data, focusing on clinical notes. Design: This prognostic study developed competing risk survival models to predict readmission after heart failure hospitalization. Variables were chosen using a modified Delphi process, and extracted from EMR notes using various natural language processing techniques or from other EMR elements where appropriate. Patients were admitted between 2011 through 2019, and at least one year of follow-up was available for all patients. Models were evaluated using C-statistics, as well as sensitivity, specificity, positive and negative predictive values. Setting: During the study period, all acute-care facilities in Calgary, Alberta used the same EMR system, from which patients were selected. Participants: Patients were 18 years or older, resided in Alberta, and were admitted to a Calgary hospital. All corresponding admissions with a most responsible diagnosis of heart failure were included (n=15,160). Main Outcomes and Measures: The main outcome of interest was readmission within 30 days, though 90- and 365-day time frames were also analyzed. Death was treated as a competing risk and analysed at those time frames as well.

Background: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome comprising multiple pathophysiological phenotypes. HFpEF trials have largely enrolled diverse populations and reported average treatment effects, consistently yielding neutral results that may obscure drug-specific benefits within distinct subgroups. To address this issue, we employ an interaction-based that incorporates treatment-by-variable interactions to uncover drug-specific responses. Methods: We leveraged four HFpEF clinical trials (TOPCAT, RELAX, NEAT-HFpEF, INDIE-HFpEF) and developed a framework comprising two complementary approaches. The first employed a prognostic responder model to evaluate whether conventional responder definitions reflect treatment-specific benefit or instead capture favorable clinical trajectories common to both treatment and placebo groups. The second used an interaction-based individual treatment effect (ITE) modeling to identify baseline variables that modify therapy effect, distinguishing drug-specific response from prognostic phenotypes. Results: Although the prognostic responder model demonstrated good discrimination, further analisys suggested it primarily captured a prognostic signal associated with favorable clinical trajectories common to both treatment and placebo arms. In contrast, the ITE model identified distinct, drug-specific effect modifiers across trials (cardiorenal-inflammatory for spironolactone (TOPCAT), NO-mediated anti-inflammatory for isosorbide mononitrate (NEAT-HFpEF), afterload-reducing for inorganic nitrite (INDIE-HFpEF), and anti-volume-overload for sildenafil (RELAX). Each ITE model demonstrated significance only within its own trial suggesting drug-specific signal. Conclusions: The proposed method identifies mechanism-specific effect modifiers, and uncovers clinically meaningful heterogeneity in treatment response, which is not captured by conventional MCID-based approaches. Although exploratory, these findings support phenotype-guided therapy in HFpEF and argue for phenotype-informed trial design to enhance treatment-effect detection and therapy targeting.

Aims: Prognostic stratification and individual management are essential in the heterogeneous population of non-ischemic dilated cardiomyopathy (NIDCM). We applied unsupervised machine learning (ML) clustering in NIDCM cohorts, using semi-automated artificial intelligence (AI)-based cardiac magnetic resonance imaging (CMR) measurements with multimodal data to identify distinct phenotypes, characterize echocardiographic remodeling trajectories, and evaluate prognostic significance. Methods and results: We analyzed 347 patients with NIDCM from two tertiary centers who underwent CMR and echocardiography at baseline, with follow-up echocardiography at a median 12 months. The cohort was randomly divided into derivation (n=242) and validation (n=105) sets using stratification by the composite outcome. Remodeling trajectories were evaluated using follow-up echocardiographic changes, and associations with outcomes were assessed by multivariable Cox regression adjusted for age and sex. Using eleven comprehensive clinical, laboratory, echocardiographic, and CMR-derived variables, partitioning around medoids clustering identified three phenotypes: (i) a younger, male-predominant preserved phenotype; (ii) a metabolic, fibrotic-remodeling phenotype; and (iii) an atrial fibrillation-predominant biventricular dysfunction phenotype. Cluster 1 showed the most favorable prognosis, whereas Cluster 3 had the highest risk of the composite outcome. Although LV reverse remodeling occurred across all clusters, Cluster 3 was characterized by attenuated LA reverse remodeling, suggesting persistent LA dysfunction. Conclusion: Unsupervised ML-based clustering of NIDCM patients, integrating AI-derived CMR parameters with multimodal data, identified three clusters exhibiting distinct patterns in longitudinal echocardiographic trajectories and outcomes. This strategy may enable more individualized management in heterogeneous NIDCM.

Aims: Iron deficiency is common among people with heart failure and associated with morbidity and mortality. While intravenous iron improves clinical outcomes, oral iron continues to be prescribed in routine practice despite limited evidence of benefit. Methods: We completed a retrospective primary care cohort study (2016 to 2021) to investigate the proportion of people with an incident diagnosis of heart failure who had iron deficiency identified (defined as ferritin <100 micrograms/L) and subsequently received a first prescription for oral iron within 12 months. Multivariable logistic regression was used to report the odds ratio (OR) of receiving oral iron in relation to key demographic covariates and co-morbidities. Results: Among 105,749 people with an incident diagnosis of heart failure, 35,688 underwent a ferritin test within the first year of whom 11,237 had iron deficiency and no prior prescription for oral iron. Of these, 2,734 (24.3%) were subsequently prescribed oral iron. Increasing age (OR per 10-year increase 1.14, 95%CI: 1.10-1.19), Asian ethnicity (1.33, 1.08-1.64), cirrhosis (2.01, 1.29-3.14) and diabetes (1.36, 1.24-1.49) were associated with increased odds of receiving oral iron. Among 1,357 (49.6%) people who had their ferritin level re-tested, the median change was 26 micrograms/L (interquartile range 7 to 61) among people who were prescribed oral iron compared to 4 micrograms/L (IQR -9 to 34) among people not prescribed oral iron. Conclusions: One in four individuals with heart failure and low ferritin received oral iron replacement, despite this not being recommended in international guidelines. Treatment could be improved and standardised in primary care.

Background Hospitalizations and mortality due to heart failure (HF) are rising in rural areas. However, inpatient outcomes for young adults with HF are not well understood. We aimed to compare in-hospital mortality, advanced procedure utilization, length of stay, and total charges among rural and urban HF patients ages 18-45. Methods We analyzed hospitalizations from the National Inpatient Sample (2016-2022), categorizing discharges as rural (National Center for Health Statistics [NCHS] 5-6), small and medium metropolitan (NCHS 3-4), and urban (NCHS 1-2). Generalized estimating equations were used to model outcomes and adjust for demographics, comorbidities, and hospital characteristics. Outcomes are reported as adjusted rate (aIRRs) or risk ratios (aRRs) with 95% confidence intervals. Results Among 79,258 HF hospitalizations among young adults, 45,075 and 10,722 were for patients from urban and rural areas, respectively. Rural patients had higher rates of in-hospital mortality (1.6% vs. 1.2%; aIRR = 1.28, 95% CI = 1.05, 1.56, p = 0.043), advanced cardiac procedure utilization (15.0% vs. 14.8%; aIRR = 1.19, 95% CI = 1.11, 1.28, p < 0.001), and longer hospital stays (aIRR = 1.10, 95% CI = 1.05, 1.14, p = 0.003). Small and medium metropolitan residents had similar outcomes to urban residents. In interaction analyses, the association between rural-urban residence and mortality differed by race (pint = 0.003) and payer type (pint < 0.001). Conclusions Young adults in rural areas may be prone to poor outcomes following hospitalization for HF. Strategies to identify rural adults at risk for HF and provide affordable and timely care may improve disparities.

_ SURPASS-HF: Safety and Utility of Remote Pulmonary Artery Sensor Shared-management in Heart Failure --Background-- Insulin-dependent diabetics self-titrate therapy to self-obtained glucose values as standard of care, yet heart failure (HF) patients with implanted pulmonary artery (PA) pressure sensors never see their own readings; clinicians interpret and execute every dose change - a model that does not scale to a ~200-patient HF panel. To our knowledge, SURPASS-HF is the first prospective feasibility study applying the insulin-titration paradigm to PA-pressure-guided HF care: patients executing a prescribed loop-diuretic sliding scale, supported by ARTHUR, a domain-trained large language model, with clinician confirmation of every adjustment. --Methods-- Non-randomized, prospective, single-arm, single-center 90-day feasibility study (January 14-April 14, 2026; 60.1 patient-months). Twenty-one adults with implanted PA sensors enrolled (intention-to-treat, ITT); 19 completed full follow-up (per-protocol, PP). Regimens and individual PA diastolic (PAD) targets were explicitly prescribed; when daily pressures met published serial-reading thresholds, the software prepared the pre-determined adjustment, the clinician confirmed it, and the patient executed it. ARTHUR reinforced dose ceilings, prompted surveillance labs, and escalated edge cases for review. Pre-specified outcomes: adverse events, escalations, time in optimal PA range (TIR-PAP, +/- 5 mmHg of goal), reading adherence, provider overrides, and paired delta_PAD (first vs last 7-day windows). Confidence intervals are descriptive; the study was not powered for significance. --Results-- Mean age was 69+/-11 years, 52% women, mean baseline PAD 14.8 mmHg. No pre-specified safety event (KDIGO >or=1 AKI, hyperkalemia, hyponatremia, symptomatic hypotension) was detected (0/8 post-adjustment draws in 5/21 patients; exact 95% CI 0-37%); laboratory ascertainment was sparse, so a meaningful harm rate cannot be excluded. Seventeen of 19 PP patients (89%) required no protocol-triggered escalation; 4 escalations occurred in 2 patients. TIR-PAP was 88.4% (ITT)/91.3% (PP); reading adherence 92.1%; 53 provider alerts (0.88/patient-month) all resolved (median 24 h) with no overrides. delta_PAD was -0.89 mmHg (ITT; 95% CI -2.60 to +0.82) in a cohort already at goal at baseline. Two non-cardiac hospitalizations occurred. --Conclusions-- LLM-mediated, clinician-confirmed patient execution of a published deterministic PA-pressure-guided diuretic algorithm was feasible over 90 days, with high time-in-range and adherence and no detected safety events. Findings from this prospective, single arm, non-randomized, small cohort are descriptive. The study was not designed or powered to demonstrate evidence of a treatment effect; a randomized, well powered prospective comparison study against provider-led PA-pressure management is the next ideal step.

Importance: Cardiac conduction disorders have traditionally been regarded as a secondary manifestation of underlying structural heart diseases. However, isolated conduction disorders may precede the onset of heart failure (HF) suggesting shared mechanisms. Objective: To evaluate the prevalence and clinical significance of pathogenic/likely pathogenic (P/LP) rare variants in cardiomyopathy genes among individuals with conduction disorders. Design, Setting, and Participants: Biobank analysis of 192,834 participants with whole genome sequence data from Vanderbilt's BioVU and 353,092 participants from the All of Us Research Program (AoU). Participants with primary conduction disorder (left bundle branch block [LBBB], right bundle branch block [RBBB], high-grade atrioventricular block [AVB]) were identified after excluding secondary causes. Exposures: P/LP variants in cardiomyopathy genes. Main Outcomes and Measures: Primary outcome was P/LP carrier status by age and HF status. Secondary outcomes included incident HF and composite ventricular arrhythmias/sudden cardiac death/mortality (VA/SCD/mortality). Results: Among 16,959 participants with conduction disorders in BioVU and 13,442 in AoU, 432 (2.6%) and 206 (1.5%) were P/LP carriers, respectively. Conduction disorder was independently associated with carrier status (BioVU p<0.001; AoU p=0.005). Carrier probability varied by age at conduction disorder onset and HF status. Among participants with HF at age 30 years, predicted carrier probability for LBBB was 7.5% in BioVU and 20.2% in AoU; for high-grade AVB, 7.7% and 8.5%, respectively, compared with 3.7% and 2.9% among those with HF without conduction disorder. P/LP carrier status among participants with conduction disorders was associated with increased risk of incident HF (BioVU p<0.001; AoU p<0.001) and ventricular arrhythmia/sudden death/mortality (BioVU p<0.001; AoU p<0.001). Carriers also demonstrated increased susceptibility to conduction disorder following HF diagnosis, including more than two-fold higher risk of third-degree AVB (BioVU aOR 2.48, 95% CI 1.85-3.32; AoU aOR 2.26, 95% CI 1.35-3.80). Conclusions: Adults with primary conduction disorders have an increased prevalence of P/LP variants in cardiomyopathy genes, which is most pronounced with diagnoses at early ages of adulthood. Furthermore, there is evidence of an interaction between P/LP carrier status and conduction disorder to increase HF risk and composite cardiovascular outcomes, underscoring the potential role of genetic evaluation in patients with primary conduction disorders to inform long-term outcomes.

Background: Heart failure with reduced ejection fraction (HFrEF) remains a major global health burden. Most electrocardiogram (ECG)-based artificial intelligence models are limited to diagnostic tasks or fixed-horizon prognostic classification and provide little insight into the temporal evolution of risk. In addition, concerns regarding model interpretability continue to impede clinical adoption. Whether deep learning applied to ECGs can deliver individualized, time-resolved, and biologically interpretable risk estimates for incident HFrEF across diverse populations remains uncertain. Methods: We developed a convolutional neural network-based survival model using raw 12-lead ECGs from Zhongshan Hospital (SHZS) and externally validated it in independent cohorts from Shanghai Tenth People's Hospital (SHTP) and Beth Israel Deaconess Medical Center (BIDMC). The model generated individualized, day-by-day probabilities of incident HFrEF over a 5-year horizon. Performance was comprehensively evaluated using discrimination, calibration, precision-recall characteristics, clinical utility, and risk stratification metrics, with subgroup analyses across age, sex, and race to assess generalizability. Model interpretability was examined using complementary representation and attention-based frameworks. Results: In 458,884 patients, the survival model demonstrated strong and stable discrimination across cohorts, with overall C-indices of 0.971 (95% CI, 0.965-0.976) in SHZS, 0.945 (95% CI, 0.938-0.950) in SHTP, and 0.855 (95% CI, 0.850-0.860) in BIDMC, and consistently high time-dependent AUROC values across the 1-5-year horizons. Calibration showed close agreement between predicted and observed risks, and decision curve analyses indicated meaningful net clinical benefit across a broad range of thresholds. Kaplan-Meier curves showed clear stratification across predicted risk groups. Interpretability analyses identified physiologically coherent ECG features related to QRS duration, heart rate, and QT interval that were associated with predicted risk. Conclusion: This ECG-based deep learning survival model provides individualized, time-resolved, and clinically interpretable estimates of future HFrEF risk with robust performance across multinational cohorts. These findings support the potential of AI-enabled ECG analysis as an accessible tool for early HFrEF risk stratification within routine clinical workflows.

Background: Neonatal-onset hypertrophic cardiomyopathy (HCM) is a rare condition with limited data regarding clinical presentation, genetic background, and long-term outcomes. We aimed to characterize the phenotype and prognosis of HCM presenting in neonates. Methods: This is a multicenter retrospective study including patients diagnosed with HCM before 1 year of age. Neonatal-onset HCM was defined as presentation {less than or equal to}28 days of life. Clinical, genetic, instrumental data, treatment, and outcomes were collected. Primary outcome included overall and cardiac survival, major arrhythmic events (MAEs), implantable cardioverter-defibrillator (ICD) implantation, and cardiac surgery. Results: Among 321 pediatric HCM, 21% were diagnosed during infancy and 75% were neonates. Median age at diagnosis was 1 day (IQR 0-6), 82% presented within the first week of life. Prenatal suspicion was in 25%. At presentation, 41% were symptomatic. RASopathies represented the most common etiology (41%), followed by gene-elusive (31%), mitochondrial/inborn errors of metabolism (18%), and sarcomeric (8%). Left ventricular outflow tract obstruction was frequent in sarcomeric and RASopathy. Overall survival was 92% and cardiac survival was 96% at 2 years; long-term survival was 88% at 30 years. ICDs were implanted in 8%; 21% required cardiac surgery. Survival free from ICD was 40% at 15 year and 47% from myectomy. All events occurred in patients presenting within the first weeks of life. Conclusions: Neonatal-onset HCM is characterized by etiologic heterogeneity, predominance of syndromic and non-sarcomeric etiologies, and long-term cardiovascular morbidity. Presentation within the first days of life identifies a high-risk subgroup requiring intensive surveillance and specialized multidisciplinary management.