European Heart Journal

Background and Aims: Epicardial adipose tissue (EAT) has emerged as an important cardiovascular biomarker that reflects both inflammatory and cardiometabolic risk. EAT volume and density vary significantly across populations, yet there is a lack of multicenter studies investigating the predictive value of population-specific EAT percentiles. Methods: In this multicenter study, we retrospectively analyzed low-dose computed tomography correction scans from 42,842 patients undergoing myocardial perfusion imaging. A derivation cohort of 15,082 patients was used to establish sex- and age-specific nomograms for EAT density and EAT volume indexed to body surface area. Percentile-based thresholds were tested for outcome prediction in a validation cohort of 27,760 patients. For clinical implementation, we developed an online EAT percentile calculator. Results: Percentile curves demonstrated increased BSA-indexed EAT volume and decreasing EAT density with age. Over a median follow-up of 3.6 years (IQR: 1.83 - 5.14), 4,956 patients experienced a nonfatal myocardial infarction or death. In multivariable Cox models, patients above the 95th sex- and age-specific percentile had significantly worse outcomes for BSA- indexed EAT volume [adjusted hazard ratio 1.30, 95% CI: 1.14 - 1.49, p < 0.001] and EAT density [adjusted hazard ratio 1.7, 95% CI: 1.51 - 1.92, p<0.001] when compared to patients below the 50th percentile (p<0.001). Conclusion: Age- and sex-specific EAT percentiles provide a clinically interpretable framework for contextualizing automated EAT measurements and identifying patients at increased cardiovascular risk. EAT density was a stronger prognostic marker and identified elevated risk even among patients with normal BMI, supporting its potential to provide information beyond conventional anthropometric assessment.

Background Targeted pharmacologic therapies for transthyretin amyloid cardiomyopathy (ATTR-CM) improve survival; however, their effects on cardiac structural parameters remain incompletely defined. Objectives To evaluate the pooled effects of disease-modifying therapies for ATTR-CM on echocardiographic structural parameters. Methods In accordance with PRISMA guidelines, we performed a systematic review and meta-analysis of randomized controlled trials and observational studies published through March 2025 assessing transthyretin stabilizers and RNA-silencing therapies in adults with cardiac amyloidosis. Outcomes included changes in global longitudinal strain (GLS), left ventricular ejection fraction (LVEF), interventricular septal (IVS) thickness, left ventricular mass, stroke volume, E/e? ratio, and LV end-diastolic volume. Pooled between-group mean differences were calculated using random-effects models. Sensitivity analyses were performed. Results Eighteen studies (11 randomized, 7 observational) encompassing 3,646 patients were included. Compared with control, drug therapy was associated with attenuation of GLS decline (mean difference [MD] -0.69%; 95% CI -1.10 to -0.29; P<0.001) and preservation of LVEF (MD 1.62%; 95% CI 0.73 to 2.51; P<0.001). Treatment was also associated with reduced worsening of E/e? ratio, and preservation of stroke volume. No significant between-group differences were observed for IVS thickness, LV mass and LV end-diastolic volume. Within-group analyses showed no change in echocardiographic parameters between baseline and follow-up in treated patients, in contrast to significant worsening in the control cohort. Conclusions Disease-modifying therapies for ATTR-CM are associated with stabilization and attenuated progression of cardiac remodeling rather than reversal of structural abnormalities.

Background: Atrial fibrillation detected after stroke (AFDAS) is frequently diagnosed after embolic stroke of undetermined source (ESUS) and has important implications for secondary stroke prevention. Although prediction scores have been proposed to identify patients at increased risk of AFDAS, prospective evidence supporting their implementation to guide rhythm monitoring in routine clinical practice is limited. Methods: In this prospective, population-based implementation cohort study, adults with ESUS were enrolled between January 2022 and December 2024 across all stroke centers in Styria, Austria. The Graz AF Risk Score was prospectively implemented as part of a risk-adapted diagnostic pathway for cardiac rhythm monitoring. Patients with a score [&ge;]4 were recommended for implantable loop recorder monitoring, whereas monitoring in those with scores <4 remained at the treating physician's discretion. The primary outcome was AFDAS detection; recurrent ischemic stroke and recurrent stroke etiology were secondary outcomes. Results: Among 784 patients (median age 73 years [IQR 64-80], 45.7% women), AFDAS was detected in 166 patients (21.2%) during a median follow-up of 26.3 months (IQR 20-34). AFDAS detection was substantially higher in patients with a Graz AF Risk Score [&ge;]4 than <4 (38.1% vs. 3.9%; p<0.001). After adjustment for age, sex and ILR monitoring, a score [&ge;]4 independently predicted AFDAS (HR 6.3, 95% CI 3.5-11.2; p<0.001) and recurrent ischemic stroke (HR 2.2, 95% CI 1.1-4.1; p=0.023). Only one recurrent stroke in patients with a score <4 was attributable to atrial fibrillation (AF) (1/18, 5.6%). Conclusions: Prospective implementation of the Graz AF Risk Score identified patients with ESUS at markedly different risks of AFDAS. A Graz AF Risk Score [&ge;]4 was also independently associated with recurrent ischemic stroke. These findings support a risk-adapted approach to cardiac rhythm monitoring after ESUS.

BackgroundHeart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome associated with metabolic stress, hypertension, systemic inflammation, and microvascular dysfunction. Early cell-type-specific events and intercellular communication programs that accompany disease onset and progression remain poorly defined. MethodsWe performed a longitudinal study of HFpEF progression in high-fat diet (HFD)+L-NAME mice at control/baseline (0 weeks, 0w/Ctrl), early (1w), intermediate (4w), and established (8w) stages. Metabolic, hemodynamic, exercise, echocardiographic, and single-cardiomyocyte function were assessed. Cardiac non-cardiomyocytes (non-CMs) were profiled by single-cell RNA sequencing (scRNA-seq), with bulk RNA-seq for tissue-level comparison. Endothelial remodeling was assessed in an L-NAME-independent HFD plus mild transverse aortic constriction model (HFD+mTAC) and a published human HFpEF single-nucleus RNA-seq cohort. An endothelial-macrophage adhesion assay tested whether HFpEF-mimic stress promotes endothelial activation and macrophage adhesion. ResultsIn the HFD+L-NAME model, metabolic dysfunction, hypertension, reduced exercise tolerance, abnormal diastolic filling with preserved ejection fraction, and altered cardiomyocyte calcium handling were detected by 1w and persisted through 8w. Bulk RNA-seq showed progressive remodeling, with limited change between 8w and 12w, guiding scRNA-seq timepoint selection. scRNA-seq of 94,848 cardiac non-CMs identified nine major populations with stage-dependent remodeling. Endothelial cells (ECs) were recovered in high proportion and showed an early, pronounced transcriptional response, with inflammatory, adhesion, interferon-response, migratory, and vascular-remodeling programs emerging by 1w. Related EC activation signatures were observed in HFD+mTAC and human HFpEF data. Functionally, HFpEF-mimic stress increased adhesion and chemokine expression in human ECs and enhanced macrophage adhesion. Fibroblast matrix remodeling occurred at later stages, while macrophages progressively shifted toward inflammatory states. CellChat suggested stage-dependent communication remodeling from early endothelial-immune interactions toward later macrophage-fibroblast crosstalk. ConclusionTime-resolved scRNA-seq reveals coordinated, stage-dependent remodeling of the cardiac microvascular and interstitial microenvironment during HFpEF progression. Early endothelial activation emerges before later fibroblast matrix remodeling and inflammatory macrophage remodeling, identifying candidate cell states and signaling pathways for future mechanistic investigation. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study provides a time-resolved single-cell atlas of the cardiac non-cardiomyocyte compartment across baseline, early, intermediate, and established stages of HFpEF progression, rather than a single late-stage snapshot. C_LIO_LIEndothelial cells exhibit early inflammatory, adhesion, interferon-response, and vascular-remodeling programs within the first week of disease, preceding the later predominance of fibroblast matrix remodeling and inflammatory macrophage remodeling. C_LIO_LIThis endothelial activation signature is supported across two mechanistically distinct HFpEF mouse models and aligns with endothelial inflammatory and vascular-remodeling programs in human HFpEF myocardium, supporting its translational relevance. C_LI What Are the Clinical Implications?O_LIEarly endothelial activation may represent a targetable stage of HFpEF pathogenesis that arises before more established structural and fibrotic remodeling. C_LIO_LITherapeutic strategies aimed at limiting endothelial inflammatory activation or endothelial-immune interactions may help attenuate downstream vascular, immune, and stromal remodeling in HFpEF. C_LIO_LIThese findings provide a preclinical foundation for future longitudinal human studies testing whether early endothelial activation can serve as a biomarker, therapeutic target, or disease-staging feature in HFpEF. C_LI

Background: Adults aged [&ge;]75 years represent a rapidly growing population at risk of acute myocardial infarction (AMI), yet they remain markedly underrepresented in statin trials for primary prevention. The limited evidence base, together with multimorbidity, functional heterogeneity, and competing mortality risks, has contributed to uncertainty regarding the potential role of statins in very old adults. This study evaluated the association between baseline statin exposure and incident AMI among community-dwelling adults aged [&ge;]75 years without prior cardiovascular disease. Methods: We conducted a retrospective population-based cohort study using linked primary-care, hospital, laboratory, and pharmacy dispensing data from the Community of Madrid. Statin exposure was ascertained during a 24-month exposure-assessment period from 1 January 2018 to 31 December 2019 and classified at a landmark date of 1 January 2020, when outcome follow-up began. Participants were classified as exposed if they had received at least two statin dispensations during the exposure-assessment period and had no record of prior lipid-lowering therapy before 2018. Individuals with prior cardiovascular disease, type 1 diabetes, cancer, dementia, or advanced chronic kidney disease were excluded. Missing data were addressed using multiple imputation. The association between baseline statin exposure and incident AMI was estimated using multivariable Cox proportional hazards regression. Propensity-score matching and Fine-Gray competing-risk regression, with all-cause mortality as the competing event, were performed as sensitivity analyses. Results: Among 174,014 individuals included in the final cohort, 32,698 (18.8%) met the criteria for baseline statin exposure. The mean age was 82.5 years. During a median follow-up of 5 years, AMI occurred in 533 (1.63%) statin-exposed individuals and 2722 (1.93%) non-exposed individuals (p=0.0003). The observed absolute risk difference was 0.30 percentage points (95% CI, 0.14-0.45), corresponding to an estimated observational number needed to treat of 338 over 5 years (95% CI, 222-708). In the fully adjusted Cox model, baseline statin exposure was associated with a lower risk of incident AMI (HR, 0.805; 95% CI, 0.731-0.887). In the full-cohort Fine-Gray model accounting for competing mortality, baseline statin exposure remained associated with a lower cumulative incidence of AMI (sHR, 0.823; 95% CI, 0.748-0.905). After propensity-score matching, the association remained in the competing-risk analysis (subdistribution HR, 0.852; 95% CI, 0.738-0.983). Conclusions: In this large population-based cohort of adults aged [&ge;]75 years without prior cardiovascular disease, baseline statin exposure was associated with a lower incidence of AMI across several analytical approaches. The observed absolute risk difference was modest, and the findings should be interpreted in light of the observational design, residual confounding, and the potential for selection related to survival to the landmark date. Further randomized evidence is needed to determine whether this association reflects a causal effect of statin therapy in very old adults. Keywords: Statins; primary prevention; acute myocardial infarction; aged [&ge;]75 years; landmark analysis; competing risks; propensity-score matching; real-world data.

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.

Background: Right ventricular (RV) function predicts survival in pulmonary hypertension (PH) and other cardiovascular diseases, yet echocardiographic AI has largely focused on the left ventricle (LV). Objectives: To develop and evaluate PH-ECHO-AI, a unified deep learning model performing four-chamber segmentation, landmark localisation, biventricular ejection fraction (EF) estimation, deformation analysis, and PH prediction from a single apical four-chamber (A4C) clip. Methods: We developed the model using 8,416 clips from four public datasets and no institutional data: EchoNet-Dynamic, CAMUS, RVENet (apical four-chamber clips paired with 3D-echocardiographic right ventricular ejection fraction, RVEF), and MIMIC-IV-ECHO. Evaluation used held-out, training-excluded data with expert-reviewed reference standards and a per-cohort audit of patient-level separation: 1,416 clips for segmentation; 600 clips for function and deformation (350 referenced to 3D-echocardiographic RVEF, 250 to the EchoNet LVEF); and 1,076 MIMIC-IV patients for PH prediction, with five-fold cross-validation. Performance measures were Dice, correlation, mean absolute error (MAE), Bland-Altman agreement, and area under the receiver operating characteristic curve (AUC). Results: Four-chamber segmentation generalised robustly across all datasets (pooled Dice: LV 0.925, RV 0.836, LA 0.910, RA 0.904). Left ventricular ejection fraction (LVEF) was estimated with r=0.845 (95% CI 0.786 to 0.886) and MAE 4.67%. RVEF, regressed directly from the clip by a supervised head trained on 3D-echocardiographic labels with no geometric assumption, reached r=0.754 (95% CI 0.690 to 0.806) and MAE 4.98%, matching published single-view RVEF ceilings and exceeding geometric RV fractional area change (RVFAC; r=0.278). Deformation and excursion metrics, namely RV free-wall and LV A4C longitudinal strain and tricuspid and mitral annular plane systolic excursion (TAPSE, MAPSE), proved physiologically coherent. Segmentation generalised to the external MIMIC-IV cohort, and PH prediction was developed and evaluated entirely within it; RVEF evaluation was clip-disjoint and same-source, so cross-centre RVEF validation remains outstanding. Using echocardiographic geometry alone, confirmed PH was detected with an AUC of 0.697 and strong calibration (Brier 0.061). Conclusions: A single, reproducible model provides comprehensive right-heart-focused interpretation from one A4C view. It achieves RVEF accuracy competitive with dedicated RV models while simultaneously delivering segmentation, deformation, annular excursion (TAPSE and MAPSE), and PH prediction. Registration: This retrospective study used existing datasets. Code is openly released, and trained model weights are available to credentialed investigators, for independent evaluation.

Background: The 2026 American Heart Association/American College of Cardiology (AHA/ACC) guidelines replaced the 2019 European Society of Cardiology (ESC) four-tier pulmonary embolism (PE) risk scheme with five clinical categories (A-E) and subcategories. These categories were set by expert consensus and have not been validated against outcomes. How patients are reclassified relative to ESC, or how the two systems compare prognostically, is unknown. Methods: We utilized three cohorts of patients with confirmed PE using structured electronic health record data, laboratory biomarkers, and large-language-model abstraction of radiology reports: Duke University Health System (n=12,992, drawn from 95,760 consecutive inpatient CT pulmonary angiography studies, 2014-2025, with no referral or registry enrollment step between imaging and cohort entry), INSPECT (Stanford; n=3,870), and MIMIC-IV (Beth Israel Deaconess; n=361). Patients were assigned AHA/ACC categories B through E, subcategorized where data allowed, and mapped to 2019 ESC risk strata. The primary outcome was 30-day mortality; discrimination was assessed with Harrell C-index. Results: Among 17,223 patients with confirmed PE, pooled 30-day mortality rose monotonically across categories: 1.5% (B), 8.9% (C), 15.5% (D), and 31.9% (E), with the ordering preserved in all three cohorts despite differing baseline mortality. Subcategory-level discrimination was reliable only at the high-acuity extreme (D2-E2); across subcategories C1 through D1, mortality did not order monotonically (9.2%, 10.8%, 8.1%, 10.9%), and adding subcategories to category C did not improve discrimination at Duke (C-index 0.699 vs 0.699). Category C patients lacking both echocardiography and biomarker testing (12.7% of category C) had mortality (10.4%) equal to or exceeding classified peers. Relative to ESC, the frameworks were concordant at the extremes, but 5.7%of ESC intermediate-risk patients were reclassified to category D, with modestly higher but non-significant 30-day mortality than those remaining in category C (10.8% versus 8.9%). Conclusions: Across a three-health-system cohort, the 2026 AHA/ACC framework produced a reproducible mortality gradient at the category level, with added subcategory granularity refining risk chiefly at the highest-acuity tiers. Discrimination across the broad intermediate band was limited, and reclassification from ESC fell almost entirely within this range.

Background: Stroke remains a leading cause of mortality and long-term disability worldwide, with high residual vascular risk among survivors despite optimal secondary prevention. The contribution of inherited polygenic risk to this residual vulnerability remains unclear. Methods: We analyzed 2,701 stroke survivors (mean age 59.8{+/-}7.1 years, 61.7% male) from the UK Biobank. Stroke- and coronary artery disease (CAD)-polygenic risk scores (metaGRS), comprising approximately 3.2 million and 1.7 million genetic variants, respectively, were derived from large-scale genome-wide association studies using penalized regression. The primary outcome was major adverse cardiovascular events (MACE), while secondary outcomes included recurrent stroke and vascular risk factor control. metaGRS associations with incident MACE and recurrent stroke were tested using Cox models, whereas associations with baseline risk-factor control were assessed using logistic regression. Mediation analyses quantified indirect effects of metaGRS to MACE via HbA1c, LDL cholesterol, and blood pressure. Results: Over 12 years, 731 MACE events (27.1%) and 351 recurrent stroke events (13.0%) occurred. CAD-metaGRS was independently associated with future MACE (age- and sex-adjusted HR per SD increment 1.15, 95%CI 1.07-1.24; p<0.001), whereas higher stroke- and CAD metaGRS were both associated with poorer glycemic control. A higher CAD-metaGRS was also associated with poorer lipid control. Mediation analyses identified glycemic regulation as a significant pathway linking polygenic risk to recurrent vascular events. Conclusions: Polygenic risk scores for cardiovascular disease are associated with recurrent vascular events and vascular risk factor control among stroke survivors, pointing to potentially actionable insights in secondary prevention that merit further investigation.

Background: Cardiovascular disease (CVD) is a leading global health concern. Traditional models often miss nonlinear dependencies among physiological and behavioral factors. We hypothesized that a Transformer-based deep learning model, which excels at capturing complex patterns in structured data trained on large-scale health check-up records, would improve long-term CVD risk prediction. Methods: We analyzed longitudinal health records (2010?2024) from the Hokuriku Health Service Association (n = 100,056 without baseline CVD; development cohort). Incident CVD was defined as the first self-reported physician diagnosis of heart disease or stroke during the 10-year follow-up and was modeled as right-censored survival data. An external evaluation cohort comprised 79,756 Kanazawa City participants with health records. A Transformer model was trained using anthropometric, laboratory, and self-reported lifestyle data. Benchmarks included Cox regression, XGBoost survival embeddings, multilayer perceptron, the Framingham Risk Score, and the Hisayama Risk Score. Performance was evaluated using time-dependent area under the receiver operating characteristic curve (ROC-AUC) with a primary focus on the 10-year ROC-AUC, precision?recall AUC (PR-AUC), and concordance index (C-index). Interpretability was assessed through SHapley Additive exPlanations (SHAP) and a Feature-level Attention Network (FAN), visualizing the top 12 SHAP-ranked features to highlight key interactions. Results: In the development cohort, 4,113 CVD events (4.1%) occurred. The Transformer model achieved the best internal performance: 10-year ROC-AUC 0.821 (95% confidence interval [CI], 0.816?0.826), PR-AUC 0.427 (CI, 0.419?0.435), and C-index 0.781 (CI, 0.775?0.787). Performance remained robust externally (21,179 CVD events, 26.6%): ROC-AUC, 0.762; PR-AUC, 0.500; and C-index, 0.744. Regarding interpretability, SHAP identified age, electrocardiogram abnormality, antihypertensive medication, and sex as the most critical predictors. Notably, FAN elucidated the prognostic value of self-reported lifestyle factors. For example, daily exercise and weight gain modulated the model?s assessment of age-related risk. Within the attention network, age served as a central hub, linking these behavioral habits with physiological features. Conclusion: The Transformer-based model outperformed conventional methods in predicting long-term CVD risk. Model interpretation demonstrated the predictive utility of self-reported lifestyle factors, such as weight gain and daily exercise. These findings may support personalized CVD prevention and population-level risk stratification using routinely collected health checkup data.

Aims: Arrhythmogenic cardiomyopathy (ACM) is a genetic disease defined by arrhythmias and myocardial fibrosis with impaired cardiac function and increased risk of sudden cardiac death. Pathogenic variants are mostly identified in desmosomal genes such as desmoglein-2 (DSG2). We identified a novel disease phenotype in patients homozygous for the DSG2 variant c.523+2T>C (splice site of exon 5/intron 5), characterized by cardioembolic events in addition to classical ACM features. Here, we evaluate this new thromboembolic phenotype by comparing the clinical data to specific murine disease models. Methods and Results: We describe three unrelated patients presenting with an embolic event and/or left ventricular thrombus. Clinical evaluation revealed a shared right ventricular ACM phenotype characterized by arrhythmias, impaired function, and fibrotic remodeling. In addition, patients exhibited localized fibrotic changes of the left ventricular apex with formation of an aneurysm and predisposition to thrombus formation. Genetic analysis identified the DSG2 variant c.523+2T>C as a founder variant from the "Bernese Oberland". To elucidate the variant's functional impact, a mouse model deficient for Dsg2 exon 5 (Dsg2{Delta}ex5) was established and compared to a model carrying the adhesion-deficient Dsg2-W2A variant. Echocardiography, ECG, and histology in Dsg2{Delta}ex5 mice revealed similar disease patterns to patients and a loss of DSG2 expression. Importantly, these animals exhibited left apical fibrosis with aneurysm formation and left ventricular thrombus formation. In contrast, the Dsg2-W2A model presented with a biventricular ACM-phenotype but without left ventricular thrombi. Conclusions: We identified a novel ACM phenotype in patients homozygous for the DSG2 founder variant c.523+2T>C characterized by left ventricular apical fibrosis. Dsg2{Delta}ex5 mice recapitulate the patients' phenotype suggesting a causative link between left ventricular aneurysm due to DSG2 deficiency and thrombus formation with subsequent embolism. This highlights a novel pathological feature of ACM and the need for variant and phenotype-specific therapy.

BACKGROUND People with type 2 diabetes mellitus (T2DM) are at higher risk of cerebral small vessel disease and left ventricular hypertrophy (LVH), potentially contributing to cognitive decline and dementia. We aimed to describe brain volume and cognitive trajectories over 2 years in a cohort of people with T2DM and to determine whether LVH causes increased brain atrophy and cognitive decline. METHODS Diabetes and Dementia (D2) study is a multicentre observational cohort study in Melbourne, Australia. Participants aged >50 years were recruited via 2 hospital outpatient clinics, 3 private clinics, and study advertisements. Participants with pre-existing cognitive impairment, life-limiting medical illness, and severe chronic renal impairment were excluded. Participants attended study visits for brain MRI, transthoracic echocardiography (TTE), and cognitive testing at baseline and 2 years. The exposure was LVH determined on baseline TTE. Pre-specified outcomes were total brain volume (TBV) change and cognitive decline (z-score change?-1 in any cognitive domain) over 2 years. Regression analyses examined associations between baseline variables and outcomes. A causal inference approach was utilized using inverse probability of treatment weighting to standardize for confounding covariates, excluding participants for non-positivity on age and baseline TBV. RESULTS Participants were recruited 20May2016 to 20March2020: 2378 screened, 702 eligible, 196 consented, 150 baseline and 123 2-year assessments with complete MRI, TTE, and cognitive data (17.4% attrition). At baseline, LVH was associated with female sex, older age, lower educational attainment, lower mood, hypertension, obesity, beta-blocker use, and smaller TBV. Participants with baseline cognitive impairment exhibited greater brain atrophy. Lower educational attainment, hypertension, and lower baseline cognitive scores were associated with cognitive decline. Causal inference analysis included 62 participants with no LVH (20(32%) women; mean [SD]=66.9[5.9] years), and 31 with LVH (17(55%) women, 67.4[5.4] years). LVH caused lower TBV change: standardized mean difference (95% CI) 6.3 (0.1, 12.5) cm3, P=.048. LVH had no effect on cognitive decline. CONCLUSIONS Brain atrophy and cognitive decline were associated with baseline cognitive impairment. LVH caused less brain atrophy and cognitive decline in people with T2DM. We conclude that guideline-directed LVH therapies such as beta-blockers have both cardioprotective (remodelling) and neuroprotective effects. TRIAL REGISTRATION ACTRN12616000546459 UTN: U1111-1181-6659

Importance: Active pharmacovigilance via sequential target trial emulation can detect adverse drug event (ADE) signals missed by spontaneous reporting, yet signals identified through high-dimensional screening require rigorous, pre-specified confirmation that addresses residual confounding, outcome heterogeneity, multiplicity, and absolute risk. Objective: To confirm or refute previously detected ADE signals associated with atorvastatin initiation among older adults by applying refined and more homogeneous outcome definitions, expanded family- and component-level exclusions, within-outcome false-discovery-rate control, and probabilistic quantitative bias analysis within a sequential target-trial framework. Design, Setting, and Participants: Confirmatory sequential target trial emulation study using Medicare fee-for-service claims (2017-2019). Eligible participants were statin-naive beneficiaries aged [&ge;]65 years hospitalized for myocardial infarction or cerebral infarction (primary diagnosis, length of stay [&ge;]3 days) and discharged home. Up to 14 nested daily trials (Trials 0-13) were constructed beginning on the discharge date, with eligibility, treatment assignment, and follow-up synchronized at each trial origin to eliminate immortal time. Primary analyses stacked all eligible trials; a pre-specified sensitivity analysis restricted inference to Trials 0 and 1, which achieved superior covariate balance (maximum standardized mean difference <0.1). Treatment Strategies: Initiation of atorvastatin (strategy A1) versus initiation of any other new outpatient medication (strategy A2). Strategy A0 (no new medication) was retained only to preserve sequential eligibility. Per-protocol effects were estimated after inverse-probability-of-treatment and inverse-probability-of-censoring weighting, with artificial censoring for treatment deviation (including a 30-day grace period) and death treated as a competing risk in Fine-Gray models. Main Outcomes and Measures: Previously detected signals and more granular, clinically coherent alternatives within the same outcome families (i.e., hemorrhagic events, cardiac valve disorders, musculoskeletal injuries, sensory symptoms, abnormal laboratory findings, and hyperglycemic events), defined by Clinical Classifications Software Refined categories plus independently validated Sentinel or published algorithms. Incident events required absence of relevant baseline codes. Confirmation required (1) within-outcome Benjamini-Hochberg q [&le;]0.05 with subdistribution hazard ratio (sHR) >1.0 and (2) both the median and 2.5th percentile of the bias-adjusted sHR remaining >1.0 across 5,000 Monte Carlo draws of probabilistic quantitative bias analysis (confounder-outcome risk ratio 1.25-3.00; prevalence difference 0.05-0.25). Absolute risks, risk differences, and numbers needed to harm (NNH) were reported. Stratified analyses examined time windows (1-30, 31-91, 92-182 days), age, sex, and race. Results: Of 70,130 eligible patients, 39,948 initiated atorvastatin and 19,182 initiated another new medication. After weighting, baseline covariates were closely balanced. Acute hemorrhagic cerebrovascular disease was confirmed overall (sHR 1.43, 95% CI 1.00-2.04; risk difference 0.5%; NNH 205) and more strongly in the first 30 days (sHR 2.20, 1.35-3.58); the association persisted in Trials 0 and 1 (sHR 1.50, 1.02-2.20). Related early intracranial hemorrhage signals were likewise confirmed. Nonrheumatic and unspecified valve disorders were confirmed in days 92-182 (sHR 1.48-1.58), as was cardiac valve intervention overall (sHR 1.74-1.83). Sprains, strains, and related composites were confirmed among men (sHR 1.66-1.94). General sensation/perception symptoms and dizziness were confirmed among non-White patients (sHR 1.40-1.43) but only in the unrestricted trial set. Acute hepatic failure was confirmed overall (sHR 1.61-1.72), and biliary tract disease among women (sHR 1.45-1.49). For every confirmed association the proportion of bias-adjusted draws remaining above the null was 1.00. Multiple prior signals, including prediabetes and acute posthemorrhagic anemia, failed the dual confirmation criteria. Conclusions: Sequential target-trial emulations with refined outcome definitions, within-outcome multiplicity control, restriction to optimally balanced early trials, and probabilistic quantitative bias analysis confirmed several ADE signals associated with atorvastatin initiation in older adults--most notably early hemorrhagic cerebrovascular events, cardiac valve disorders and interventions, musculoskeletal injuries in men, and selected hepatobiliary events--while attenuating others. Absolute excess risks were modest yet clinically relevant in a high-risk post-infarction population. These findings support a two-stage active pharmacovigilance paradigm (signal detection followed by rigorous confirmation) and justify heightened clinical vigilance for the confirmed events, while underscoring the need for external validation in independent populations and data sources.

Objectives: Mitral regurgitation (MR) evolution after transcatheter aortic valve replacement (TAVR) in low-flow aortic stenosis (LFAS) is poorly characterized. We evaluated MR trajectories across LFAS phenotypes, predictors of MR worsening, and associations with clinical outcomes. Methods: We retrospectively studied 614 LFAS patients undergoing TAVR: low-flow high-gradient (LFHG; n=153, 24.9%), classical low-flow low-gradient (cLFLG; n=155, 25.2%), and paradoxical low-flow low-gradient (pLFLG; n=306, 49.8%). MR severity was abstracted from clinical echocardiography reports using a 6-level ordinal scale. MR worsening was defined as a [&ge;]1-grade increase from baseline MR at ~30 days or ~1 year. Multivariable logistic models identified predictors of MR worsening. Kaplan-Meier and Cox models evaluated associations of MR trajectory and LFAS subtype with all-cause death, heart failure hospitalization (HFH), and their composite. Results: Among 614 LFAS patients, 443 had 30-day and 290 had 1-year echocardiographic follow up. At 30 days, MR trajectory differed significantly across LFAS phenotypes, with the highest rate of worsening in cLFLG and the lowest in LFHG. At 1 year, unadjusted MR trajectory distributions did not differ significantly across phenotypes. In adjusted logistic models, cLFLG remained independently associated with MR worsening at both timepoints. MR worsening was associated with worse unadjusted outcomes at 30 days but was not independently associated with the composite endpoint after multivariable adjustment. LFAS phenotype, particularly cLFLG, remained the dominant predictor of adverse clinical outcomes. Conclusions: MR evolution after TAVR is phenotype-specific: cLFLG patients have the highest risk of MR worsening and lowest event-free survival, supporting phenotype-informed post-TAVR surveillance.

Background and aimsCardiovascular-kidney-metabolic (CKM) syndrome stages confer graded CVD risk, but the underlying stage-specific molecular mechanisms remain undefined. MethodsIn 355,724 UK Biobank participants (median follow-up 13.5 years), we mapped CKM stages (0-3) to incident CVD. Using proteomics (n=37,785) and metabolomics (n=190,112), we identified stage-specific biomarkers via LASSO and XGBoost-SHAP. Mediation analyses were performed to quantify the proportion of the CKM-CVD association that was statistically accounted for by these biomarkers. The proportion of the protective association between cardiovascular health (Lifes Crucial 9 [LC9]) and incident CVD that was mediated by the same molecules was quantified. ResultsCVD risk increased across CKM stages. Beyond 11 pan-stage proteins (e.g., RTN4R,LEP) and 29 pan-stage metabolites (e.g.,GlycA), stage-specific molecular signatures emerged, whose pathway enrichment revealed a shift from metabolic/extracellular matrix dysregulation (Stage 1) to inflammation (Stage 2) to hypoxia/fibrosis (Stage 3). The proportion of the CKM-CVD risk association statistically accounted for by these molecules shifted accordingly: ADM (42.9%) in Stage 1, FABP4 (24.6%) in Stage 2, and HAVCR1 (28.0%) in Stage 3. High CVH (LC9[&ge;]80) was associated with approximately 80% lower CVD risk in Stages 0-2; a proportion of this protective association was statistically accounted for by the same stage-specific molecules. ConclusionsThese findings reveal a stage-ordered molecular continuum--from ECM remodeling to inflammation to fibrosis--that redefines CKM-driven CVD risk, and the strong protection of high CVH in early stages was statistically accounted for in part by these stage-specific molecules, generating the hypothesis that CVH may reduce risk through these modifiable pathways and providing a molecular framework for future stage-adapted intervention trials.

BACKGROUNDInterleukin-27 (IL-27) is a heterodimeric cytokine that serves as a bifunctional rheostat rather than an inherently pro- or anti-inflammatory signaling protein. However, the specific role of IL-27 in regulating systolic overload-induced cardiac inflammation and heart failure (HF) pathogenesis remains unknown. METHODSWe investigated the effects of genetic IL-27 receptor deficiency (IL-27R knockout), pharmacological IL-27 blockade, and recombinant IL-27 administration on transverse aortic constriction (TAC)-induced HF in mice. RESULTSCardiac IL-27 expression was significantly elevated in both murine and human HF tissues. The global genetic ablation of the IL-27 receptor (IL-27R) significantly suppressed TAC-induced cardiac inflammation, fibrosis, hypertrophy, HF progression, and mortality. Corroborating these protective effects, transcriptomic analysis (RNA-seq) revealed that IL-27R deficiency drastically suppressed pathways driving immune responses and antigen presentation, alongside the significant downregulation of networks governing systemic inflammation, pathogen infection, and extracellular matrix remodeling. Furthermore, pharmacological neutralization of IL-27 effectively attenuated TAC-induced left ventricular dysfunction, chamber dilation, myocardial hypertrophy, fibrosis, and leukocyte infiltration. Conversely, the administration of recombinant mouse IL-27 exacerbated the TAC-induced cardiac accumulation of multiple immune cell subsets, resulting in worsened cardiac fibrosis, cardiomyocyte hypertrophy, and overall HF progression. CONCLUSIONSOur findings demonstrate that IL-27 acts as a critical pathogenic driver of cardiac inflammation and HF development by modulating both cardiac immune cells (predominantly T cells) and non-immune cells, highlighting the IL-27 signaling axis as a promising therapeutic target.

Purpose: Family-based interventions are proposed for primordial cardiovascular disease (CVD) prevention, yet which family-environment components to target remains unclear. We quantified effects of parenting styles in adolescence on adult cardiovascular conditions, including hypertension, and whether effects differ by family financial hardship. Methods: Data were from the US National Longitudinal Study of Adolescent to Adult Health (n=4,050). Parenting styles were derived via latent class analysis of adolescent-reported parental responsiveness and demandingness (ages 12-19, 1994-1995). Family financial hardship was based on parent-reported ability to pay bills. CVD and hypertension were assessed via biomarkers and self-report (ages 33-43, 2016-2018). Confounding factors were selected based on a directed acyclic graph; risk differences were estimated using doubly robust inverse-probability-weighted models. Results: Three parenting styles emerged: authoritative (11.1%), permissive (77.9%), and indifferent (11.0%). After 21 years, 33.0% had CVD or hypertension. Whole-population risk differences for permissive and indifferent versus authoritative parenting were -1.0% (95% CI: -5.3, 3.3%) and -1.8% (95% CI: -7.8, 4.2%), respectively. Among families reporting financial hardship, permissive parenting had lower risk (-15.9%, 95%CI: -28.4%, -3.3%), though inconsistent across sensitivity analyses. Conclusions: Adolescent parenting styles had small estimated long-term cardiovascular effects, with no robust evidence of differences by financial hardship.

Heart Failure with Preserved Ejection Fraction (HFpEF) is more prevalent in females and is associated with altered cardiac glucose metabolism. However, whether these metabolic alterations are conserved across sexes and between humans and widely used cardiometabolic mouse model of HFpEF remains unclear. We investigated species-, sex-, and ventricle-specific conserved and divergent features of HFpEF. Cardiometabolic HFpEF was induced in mice using the 'two-hit' model (high-fat diet + L-NAME), followed by assessment of cardiac function, RNA sequencing, and protein expression in the right (RV) and left (LV) ventricles. Published human HFpEF RV and LV RNA-seq datasets were reanalyzed and compared with our mouse data. Only male HFpEF mice recapitulated human phenotype of increased RV GLUT1 protein. In contrast, mouse GLUT1 was downregulated in RV of females and in the LV of both sexes, whereas GLUT4 protein remained unchanged. Cardiac PDK4 transcript and protein levels increased in the RV and LV of mice. Conversely, human PDK4 mRNA levels were reduced in the RV with HFpEF and unchanged in LV. Cardiac transcriptome analysis in mice revealed extensive alterations in LV, particularly in females, with enrichment of inflammatory pathways. Cross-species analysis demonstrated greater conservation of HFpEF-associated signatures in the RV than the LV. Furthermore, number of differentially expressed transcripts in human LV increased substantially after excluding patients with atrial fibrillation or diabetes. Overall, the RV of the 'two-hit' model more closely resembles human HFpEF. The cardiac transcriptome reflects sexual dimorphism, and conserved signatures are primarily associated with metabolic alteration, mitochondrial dysfunction, and cellular stress.

Contemporary national-scale electronic health record (EHR) trends in documented acute myocardial infarction (AMI) rates during the high-sensitivity cardiac troponin (hs-cTn) and Type 2 myocardial infarction (T2MI) era are not well characterized. We conducted a serial cross-sectional analysis of U.S. adults aged 18 years in Epic Cosmos from 2016-2024, encompassing 821,859,867 patient-years. Age- and sex-standardized AMI diagnosis rates increased 75.7%, from 343.1 to 602.7 per 100,000 patients. This increase was predominantly driven by T2MI, which increased 133.8% from 99.9 per 100,000 in 2018 to 233.4 per 100,000 in 2024; NSTEMI increased 13.8% while STEMI decreased 4.1%. Annual hs-cTn-tested encounters increased 34.5-fold from 2017 through 2024. The proportion of tested encounters associated with any AMI remained relatively stable after 2021, whereas T2MI continued to increase and surpassed NSTEMI in 2024 as the most frequently diagnosed AMI subtype per hs-cTn-tested encounters. Males had higher absolute AMI rates across all age groups, although relative increases were greater among females. Documented AMI epidemiology shifted substantially toward T2MI during expanding hs-cTn utilization, underscoring the need for evidence-based approaches to the evaluation and management of T2MI.

Background and AimsCardiac fibrosis is a major contributor to heart failure (HF), yet mechanisms limiting pathological fibroblast activation remain incompletely understood. We identified dysferlin (DYSF), a membrane repair protein, as highly induced in HF fibroblasts and investigated its role in regulating profibrotic responses. MethodsCardiac fibroblasts from patients with end-stage HF and unaffected donor hearts were analysed by liquid chromatography-tandem mass spectrometry and bulk RNA sequencing. Dysferlin expression was validated in independent cohorts. Selected gene/protein expression was validated using single-cell/single-nucleus RNA sequencing and multiplex immunofluorescence of human myocardium from dilated cardiomyopathy (DCM), ischaemic cardiomyopathy (ICM), acute myocardial infarction (AMI), and unaffected hearts. Functional studies were performed in human and mouse cardiac fibroblasts using siRNA-mediated silencing and TGF-{beta} stimulation, and in engineered human 3D cardiac microtissues. Fibrotic remodelling, autophagy, apoptosis, and contractile function were assessed by molecular, histological, biochemical and functional analyses. ResultsDysferlin abundance was markedly increased in HF fibroblasts. Across HF myocardium, DYSF was enriched in activated fibroblasts but largely excluded from COMP-enriched fibrotic regions, consistent with a role in restraining fibroblast state transitions. Although induced by TGF-{beta}, DYSF silencing enhanced extracellular matrix production, increased FOSL2 expression, and promoted differentiation into COMP-positive matrifibrocytes. In engineered human cardiac microtissues, DYSF silencing exacerbated fibrosis, increased apoptosis, and impaired contractility. Mechanistically, dysferlin restrained the TGF-{beta}-FOSL2-autophagy signalling axis, whereas FOSL2 suppressed DYSF expression, defining a reciprocal regulatory circuit. Silencing FOSL2 or MXRA5 increased dysferlin levels, while mRNA-protein discordance implicated S-acylation as a potential regulator of dysferlin protein abundance. ConclusionsDysferlin is a stress-inducible antifibrotic regulator that limits maladaptive fibroblast differentiation and myocardial fibrosis, thereby representing a potential therapeutic target to attenuate adverse cardiac remodelling in HF. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/745492v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@b52f7dorg.highwire.dtl.DTLVardef@140f781org.highwire.dtl.DTLVardef@3964f5org.highwire.dtl.DTLVardef@131404_HPS_FORMAT_FIGEXP M_FIG C_FIG