Heart

Abstract Background: Heart failure (HF) is a major public health challenge in ageing populations and a leading cause of unplanned hospital readmissions. Biological, social, and economic factors contribute to recurrent hospitalisation, but gaps remain in understanding how these factors interact and patterns of healthcare use following hospitalisation. Methods: We conducted an explanatory sequential mixed-methods study of patients aged ?60 years with an HF hospital admission between 2016 and 2020 who completed the Sax Institute?s 45 and Up Study baseline questionnaire. Data were linked to Admitted Patient Data Collection, Medicare Benefits Schedule, and Pharmaceutical Benefits Scheme data. HF readmission within 30 days of the index admission was the outcome. Cox proportional hazards models estimated crude and adjusted hazard ratios (HRs and adjHRs) with 95% confidence intervals (CIs). Kaplan-Meier curves and log-rank tests compared survival between groups. Time-series plots mapped healthcare interactions over 1 year following the index admission. Results: Among 4,252 patients with HF, 409 were readmitted within 30 days. Significant predictors included age ?80 years (adjHR, 1.30; 95%CI, 1.01?1.67), 1 chronic condition (adjHR, 2.49; 95%CI, 1.41?4.40), ?2 chronic conditions (adjHR, 1.75; 95%CI, 1.04?2.95), and alcohol consumption above national guidelines (adjHR, 1.45; 95%CI, 1.06?1.98). Time-series analysis indicated that participants with readmission had more frequent out-of-hospital health service contact following their initial HF admission than those without readmission. Conclusions: Older age, chronic conditions, and high alcohol intake increased 30-day HF readmission risk. Differences in healthcare use after admission highlight opportunities for targeted and coordinated post-discharge care.

Background: Myocardial infarction (MI) and heart failure (HF) impose a physical and emotional toll that has not been measured nationally with a standard instrument. Methods: We pooled the 2019 to 2024 Medical Expenditure Panel Survey into 4 mutually exclusive groups of adults aged 18 and older: MI without HF, HF without MI, both conditions, and neither condition. Quality of life was assessed with the Veterans RAND 12-item component summaries, T scores (mean 50, SD 10) on which higher is better and 3 points is minimally important. Survey-weighted linear regression adjusted for demographics, socioeconomic factors, and comorbidity. Results: Among 79,853 adults representing 253.8 million US adults, 4.2% (3,340) had MI alone, 0.6% (480) HF alone, and 0.3% (236) both. Unadjusted physical scores ranged from 33.2 with HF alone to 39.1 with MI alone, versus 50.5 with neither. Adjusted physical scores were lower by 3.84 points (95% CI, 3.20-4.47) with MI alone, 8.32 (95% CI, 7.04-9.61) with HF alone, and 7.74 (95% CI, 5.73-9.76) with both, each beyond the minimally important threshold. Adjusted mental scores were lower by 1.35 points with MI alone, 1.20 with HF alone, and 1.69 with both, all below that threshold. Adults with both conditions did not differ from those with HF alone (0.58 points; 95% CI, -1.76 to 2.92). Emergency visits, inpatient discharges, and expenditure were higher in every cardiac group and highest with both conditions, where annual expenditure reached $37,198 versus $7,845 with neither. Conclusions: Physical quality of life fell steadily across the cardiac groups, with HF rather than prior MI accounting for most of it. The difference in mental quality of life did not persist after adjustment. Utilization and spending were highest with both conditions.

Background: CPR is the primary intervention for cardiac arrest, and the mortality trends before and after the pandemic remain are not fully understood. Methods: This cross-sectional study used the National Inpatient Sample (NIS) database from 2016-2022 and International Classification of Diseases, Tenth Revision (ICD-10) codes to evaluate the mortality trend for adult patients undergoing CPR after in-hospital cardiac arrest (IHCA). Primary exposures were calendar year, demographics, socioeconomic factors, and hospital characteristics. Multivariable weighted logistic regression was performed to identify predictors of mortality after CPR for IHCA. Results: Among 612,930 weighted adult hospitalizations undergoing CPR for IHCA between 2016 and 2022, overall in-hospital mortality was 67.8%. Risk-adjusted mortality declined through 2019 before increasing sharply during the COVID-19 pandemic, peaking in 2021 and remaining above pre-pandemic levels in 2022. Compared with 2016, admission in 2020 (aOR 1.18, 95% CI 1.12-1.25; p<0.001) and 2021 (aOR 1.26, 95% CI 1.19-1.33; p<0.001) was independently associated with higher mortality, whereas admission in 2019 was associated with lower mortality (aOR 0.89, 95% CI 0.84-0.95; p<0.001). Higher mortality was also associated with increasing age (aOR 1.01 per year; p<0.001), female sex (aOR 1.05, 95% CI 1.02-1.08; p<0.001), Black (aOR 1.14, 95% CI 1.10-1.18; p<0.001) and Hispanic race/ethnicity (aOR 1.20, 95% CI 1.15-1.26; p<0.001), and self-pay insurance (aOR 1.62, 95% CI 1.51-1.74; p<0.001). Protective factors included private insurance (aOR 0.91, 95% CI 0.87-0.94; p<0.001), residence in the highest income quartile (aOR 0.91, 95% CI 0.87-0.94; p<0.001), and treatment at private, non-profit hospitals (aOR 0.89, 95% CI 0.85-0.94; p<0.001). Conclusion: This large nationwide patient database analysis demonstrates that mortality following CPR for IHCA declined before the COVID-19 pandemic but increased during 2020, remaining above pre-pandemic levels through 2022. Independent predictors of mortality reveal socioeconomic disparities in mortality outcomes.

Background: Pulsed field ablation (PFA) has been rapidly adopted for atrial fibrillation (AF) on the premise of greater safety than thermal ablation. Real-world signals of hemolysis, coronary spasm, and neurologic events have since emerged, and prior Manufacturer and User Facility Device Experience (MAUDE) analyses relied on term matching without prospective signal detection. Methods: We queried MAUDE for AF ablation catheter reports received January 2016 through June 2026 and assigned each to PFA, radiofrequency ablation (RFA), or cryoballoon ablation. We adjudicated injury and death narratives into predefined complication families and severity tiers with a large language model, checked against a larger model and by physician review. We calculated reporting odds ratios (ROR) and Bayesian shrinkage estimators compared against an empirical null, applied interrupted time series and prospective sequential detection, and repeated estimates on a 2026 hold-out. Results: Among 44,623 reports, 30.1% were PFA, 50.9% RFA, and 19.0% cryoballoon, with 91.8% model agreement on event occurrence (? = 0.83). PFA carried an ROR of 527 (95% CI, 33, 8,509) for hemolysis, 2.83 (2.55, 3.16) for arrhythmia, 2.83 (2.30, 3.48) for coronary, and 2.39 (2.10, 2.73) for cerebrovascular events, against 0.024 (0.008, 0.075) for esophageal and 0.34 (0.32, 0.37) for pericardial events. The cerebrovascular excess was largest for VARIPULSE, but without it the class proportional reporting ratio was 1.36 (1.13, 1.65), concordant with the 1.56 measured in EMBOL-AF. In the hold-out, the cerebrovascular, arrhythmia and hemolysis signals replicated, and coronary events kept their direction without meeting the signal rule. Prospective detection flagged cerebrovascular events 13 months before AVANT GUARD published its neurologic events. Conclusions: PFA showed disproportionate reporting of hemolysis, cerebrovascular, coronary, and arrhythmic events across sequential testing. Machine learning methods allowed for flagging these signals months before confirmatory trials, demonstrating a scalable tool for early detection of procedural risk.

Background: Cardiovascular (CV) screening is critical for personnel deploying to Antarctica, where geographic isolation and limited medical care make the management of acute cardiovascular events challenging. The utility of contemporary risk prediction tools such as the AHA PREVENT equations in this unique population remains uncertain. Methods: We retrospectively analyzed 154 individuals referred for enhanced CV evaluation before deployment to the U.S. Antarctic Program (USAP). Participants were evaluated across three temporal cohorts (2018-2020, 2021-2023, and 2024-2026). Demographics, CV risk factors, cardiac testing, and deployment clearance outcomes were collected. Risk was estimated using the Framingham Risk Score (FRS), AHA/ACC Pooled Cohort Equations (PCE), and AHA PREVENT risk models. Results: The cohort was predominantly male (79.9%; mean age 44.6 {+/-} 14.6 years), and abnormal ECG was the most common referral trigger (70.8%). Median 10-year risk was low by PREVENT and FRS and borderline elevated by PCE (PREVENT 2.7% [IQR 1.1-6.6], FRS 2.3% [IQR 0.5-7.1], and PCE 6.1% [IQR 2.4-9.2]). Among 72 participants with all scores, 51% were classified discordantly; PREVENT ASCVD agreed closely with FRS (=0.77) but poorly with PCE (=0.24-0.35), which consistently estimated higher risk. PCE was calculable in 52.6% versus 70.8% for PREVENT. Overall, 132 participants (85.7%) were cleared for deployment, while 8 (5.2%) were not physically qualified (NPQ); 6 of these NPQs were due to cardiovascular causes. Of 22 cardiac medical evacuations during the study period, 21 involved individuals without prior advanced cardiovascular screening. One screened individual was evacuated for symptoms subsequently found to have no cardiac cause. Conclusions: Risk calculators disagree substantially in the fitness-selected population. We recommend PREVENT as the primary risk-stratification tool as it is the most contemporary derivation, incorporates renal function, is race-agnostic, extends to heart failure, applies from age 30, and agrees closely with FRS, easing transition. Targeted imaging, including coronary artery calcium scoring, may supplement intermediate-risk candidates.

Background. Information is lacking about everyday psychological states of individuals with a recent myocardial infarction (MI) and whether they influence outcomes. We investigated real world psychological experiences and their association with subsequent cardiovascular events in survivors of an MI. Methods. We studied 287 individuals [&le;] 60 years of age within 8 months from an MI. At the baseline visit, we assessed sociodemographic and clinical factors, and administered a battery of psychological scales of depression, anxiety, anger, perceived stress and social support. Participants underwent a 7-day home monitoring of mood and stress using ecological momentary assessments, and a momentary negative affect (MNA) score, integrating daily mean ratings of sadness, anxiety, anger, distress and loneliness, was calculated. Participants were followed for a median time of 28 months. The study endpoint was a composite index of major adverse cardiovascular events (MACE), including cardiovascular death, nonfatal MI, stroke or hospitalizations for heart failure. Cox proportional hazards models adjusted for sociodemographic and clinical factors. Results. The mean age of the sample was 51 years, and 43% of participants were women. Each standard deviation increase in MNA was significantly associated with a 60% increased risk of MACE (95% confidence interval (CI), 20% to 100%), irrespective of adjustment for sociodemographic factors and clinical characteristics. The association was similar in women and men. Momentary positive mood and momentary perceived stress were not associated with MACE. The MNA score showed a larger independent contribution to MACE compared to the combined battery of baseline psychological assessments and the association was independent of baseline history of depression. Conclusion. Among individuals after MI, moment-to-moment negative affect during one week of monitoring in daily life is a powerful predictor of subsequent cardiovascular events. A prospective evaluation of negative mood during everyday living could represent a novel strategy to uncover residual risk after MI.

Condensed Abstract: Using the 2016?2022 National Inpatient Sample, this study evaluated temporal trends and demographic adoption patterns of percutaneous left atrial appendage occlusion (LAAO). Among 190,020 weighted procedures, annual volume increased from 4,875 to 60,445. In-hospital mortality was exceptionally low (0.1%). Age-adjusted procedural rates rose from 34.19 to 379.87 per 100,000 population. However, significant disparities persisted, characterized by heavy centralization in urban teaching hospitals (87.0%) and disproportionately lower absolute age-adjusted utilization among female, Black, Hispanic, and Asian/Pacific Islander patients compared to male and White cohorts. Targeted initiatives are needed to ensure equitable access to structural heart interventions.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is a pan-ethnic disease, at least as common in Black as in White Americans, yet Black patients reach specialist care later, undergo septal reduction less often, and die sooner. Whether the defining trials enrolled representatively is unknown. We sought to measure Black participation in the landmark HCM trials against three expectations of increasing stringency, and to test whether trial site geography or quantitative eligibility thresholds account for the shortfall. METHODS: Of 197 registered interventional HCM trials, 32 met prespecified landmark tiers; demographics were extracted for 16 and 13 reported race. The Black share of Black plus White participants was pooled by random-effects meta-analysis and compared with the US adult population, with each trial?s own site counties, and with a disease-referenced echocardiographic expectation. Site geography and eligibility thresholds were tested using site addresses, census data, and NHANES. RESULTS: Across 13 trials, 70 of 1,780 Black or White participants were Black. The pooled Black share was 3.98% (95% CI 2.68-5.86), against a population expectation of 16.5%, giving a participation-to-prevalence ratio (PPR) of 0.24 (95% CI 0.16-0.36), the lowest of any racial and/or ethnic minority group. The clinical trial site network reached 63.7% of Black and 47.5% of White US adults, with geospatial analysis predicting 26.4% Black enrollment; however, every trial fell below this expectation. Quantitative eligibility thresholds closed only 2.0% of the enrollment gap. CONCLUSIONS: Black participation was about one quarter of the population expectation. Neither site geography nor eligibility thresholds explain it.

Background. Real-world 12-lead electrocardiograms (ECGs) often have missing or corrupted leads. A deep-learning classifier can be prepared for this by random lead masking during training, or by injecting clinical knowledge, for example by pulling its attention towards the leads that guidelines use for each diagnosis. Whether this knowledge adds robustness beyond masking is unknown. Methods. Pre-registered comparison of three arms sharing one network (per-lead 1D-ResNet encoder and per-diagnosis attention over the 12 leads): standard training (M0); random whole-lead masking (M1); masking plus a Kullback-Leibler penalty pulling attention towards a fixed guideline-derived key-lead map (M2, guideline-based attention guidance). Six diagnoses; five seeds per arm. Development on PTB-XL (21,799 ECGs); single sealed evaluation on PTB-XL fold 10 (2,198 ECGs) and on CODE-15% (233,204 exams, external validation). Primary endpoint: AUROC difference M2 - M1, averaged over first-degree AV block, right and left bundle branch block and atrial fibrillation and over 1 to 6 lost (zeroed) leads, with a patient-level paired BCa bootstrap 95% confidence interval. Results. The guidance did not change robustness: {Delta}AUROC -0.0010 (95% CI -0.0033 to +0.0006), an interval entirely within the pre-specified +-0.02 margin; the result was unchanged with another bootstrap seed, other interval methods and leave-one-diagnosis-out analyses. Masking improved AUROC: M1 - M0 = +0.0134 (95% CI +0.0102 to +0.0172) when one key lead was lost, and the number of lost leads tolerated before AUROC fell by more than 0.02 rose from 7 (M0) to 10 (M1). M2 attention matched the map and M2 was non-inferior on intact ECGs, but its calibration slope was lower for all six diagnoses in both datasets. M2 lost slightly more when all key leads were lost together (-0.0067) and gained only when one to three leads remained (exploratory; AUROC 0.9408 vs 0.9210 with 11 leads lost). CODE-15% reproduced every pattern (primary -0.0007, 95% CI -0.0011 to -0.0003). Conclusions. Random lead masking suffices to make an ECG classifier robust to missing leads; adding guideline knowledge aligns attention with clinical criteria but adds no robustness and worsens calibration. Guideline-aligned attention should not be taken as evidence of robustness.

Background: Multiple performance measures are used to assess the management of common cardiovascular conditions, such as coronary artery disease (CAD), heart failure with reduced ejection fraction (HFrEF), and atrial fibrillation (AF). These measures are sometimes used to assess individual clinicians, despite lack of evidence of reliability and accuracy. We used national Veteran Affairs (VA) data to test medication-based performance measures for assessment of clinician performance in outpatient cardiology care. Methods: This retrospective study examined VA cardiology clinician/Veteran dyads from 2017-2023 to evaluate 10 medication-based performance measures for CAD, HFrEF, or AF with elevated stroke risk. Achievement of each performance measure was defined as an active prescription of an indicated medication for each eligible patient encounter, summarized at the clinician level. Reliability was calculated using the beta-binomial method. A Bayesian causal model was used to assess the impact of case complexity on performance measure achievement. Finally, we performed peer review of a subset of cases (n=952) to assess the accuracy of three representative performance measures. Results: Of 456,071 unique cardiology encounters, 312,331 included CAD, 224,599 included HFrEF, and 178,678 included AF. These patients were treated by 1,043 cardiology clinicians. Median performance measure achievement ranged from 0.23 (SGLT2i for HFrEF) to 0.99 (beta blocker for HFrEF). Measure reliability varied from 0.63 to 0.90. Case complexity did not significantly affect performance measure achievement. Using peer review as the gold standard, accuracy was poor to moderate (balanced accuracy 0.51-0.73), and measures underestimated performance relative to peer review. Conclusions: Ten medication-based performance measures for CAD, HFrEF, and AF can be efficiently measured using electronic health record data, and most have sufficient reliability to support clinician benchmarking and the identification of potential care gaps. However, suboptimal accuracy compared with a peer review indicates that these measures may be insufficient as a standalone assessment of clinician quality.

Background Cardiac amyloidosis is an increasingly recognized cause of heart failure in older adults, yet Colombian data, and data from the southwest of the country in particular, remain scarce. We describe the clinical, diagnostic, imaging and outcome profile of patients with cardiac amyloidosis at two high-complexity institutions in Cali. Methods Observational, descriptive, retrospective, two-center study. Patients were identified in the institutional registries of both centers using ICD-10 codes for amyloidosis, and clinical data were abstracted manually from medical records. Continuous variables are reported as median (interquartile range) and categorical variables as counts and percentages over the number of patients with available data. Results Thirty-two patients were analyzed (median age 77 years; 68.8% men). Heart failure (90.6%), atrial fibrillation (46.9%) and carpal tunnel syndrome (31.2%) were frequent. The etiological classification depended on the test considered: bone scintigraphy was positive (Perugini 2-3) in 23 of 26 patients studied (88.5%), but a monoclonal protein was screened for in only 22, and the full non-invasive criteria for ATTR were met in 16 of 32 (50.0%). Genetic testing was positive in 9 of 18 tested, and the variant was Val142Ile in all 8 patients in whom it was characterized. The working diagnosis was ATTR in 26 patients (81.2%) and AL in 6 (18.8%). Tafamidis was used in 37.5%. Eleven of the 31 patients with known vital status died (35.5%), and NT-proBNP was markedly higher among those who died (6640 vs 1186 pg/mL; p=0.003). Conclusions In this southwestern Colombian cohort, cardiac amyloidosis presented as the classic transthyretin phenotype, with the Val142Ile variant in all 8 patients in whom it was characterized. Bone scintigraphy was frequently positive, but screening for a monoclonal protein was often omitted, so only half the cohort met the full non-invasive criteria for ATTR. Mortality was high and closely associated with NT-proBNP.

The COVID-19 pandemic led to significant disruptions in cardiovascular care and reductions in physical activity, but little is known about how exercise patterns changed after this period. This study assessed changes in weekly aerobic and strength training activity between 2020 and 2022 amongst adults aged 18 years or older who reported one or more cardiovascular diseases or risk factors. This study used National Health Interview Survey data from 2020 and 2022. Adjusted differences for moderate-to-vigorous physical activity (MVPA) were calculated using a linear regression model and for strength sessions using a Poisson regression, adjusting for sex and age. Changes in these outcomes were then stratified by age and sex subgroups. The weighted study population included 182,783,008 (standard error, +/-3,334,337) adults in 2020 and 185,388,060 (SE, +/-3,285,161) adults in 2022. Between 2020 and 2022, the overall weekly MVPA increased from 244.2 (SE, +/-4.5) minutes to 266.3 (SE, +/-5.7) minutes (adjusted difference, +22.1 [SE, +/-6.92] minutes). There were no statistically significant changes in the number of strength session per week overall or among sex and age subgroups. Across sex and age subgroups, increases in weekly MVPA were entirely concentrated among males and younger adults. The recovery from pandemic era reductions in aerobic and strength exercise training was uneven amongst demographic subgroups, which aligns with concurrent persistent disruptions in cardiovascular care.

Background This study presents reference ranges for cardiovascular magnetic resonance (CMR)-derived myocardial strain from the Healthy Hearts Consortium, while evaluating variations by demographic characteristics (age, sex, and ethnicity) and technical factors (scanner vendor, magnetic field strength). We derived reference ranges and centile-based categories for ventricular, atrial, and rapid strain parameters. The prognostic relevance of these categories was assessed by examining their associations with incident cardiovascular events. Methods The dataset included 9,088 CMR studies. Automated image analysis pipelines were established using suiteHEART (NeoSoft Inc.) and cvi42 (Circle Cardiovascular Imaging). A three-step quality control framework was applied including exclusion of incomplete data, visual assessment of image and segmentation quality, and statistical outlier removal. Ventricular strain and strain rate were measured using both software solutions. Additional cvi42 derived metrics included velocity and displacement, annular plane systolic excursion metrics, and rapid strain parameters. Age- and sex-specific reference ranges were generated using lambda-mu-sigma (LMS) modeling with penalized splines. Reference ranges were defined as values between the 2.5th and 97.5th percentiles. For lower-tail classification, values below the 2.5th percentile were considered mildly out-of-range and values below the 0.5th percentile at least moderately out-of-range. Differences across scanner vendors (Siemens, Philips, GE) and magnetic field strengths (1.5 T vs. 3 T) were evaluated using adjusted linear models. The prognostic relevance of selected cvi42-derived categories was evaluated in approximately 45,000 UK Biobank participants using Cox regression adjusted for age, sex, and body mass index. Results After quality control, 8,975 CMR examinations (cvi42) and 8,992 (suiteHEART) were available for analysis; these represent software-specific analytic cohorts. Most exclusions occurred during visual quality control. Women had higher absolute ventricular and atrial strain values than men across all age groups. Left ventricular (LV) longitudinal strain and strain rate were slightly lower in older ages, whereas circumferential and radial parameters remained largely stable. Left atrial strain was also lower in older age groups, while right atrial strain did not vary by age. Annular plane systolic excursion and rapid strain metrics showed similar sex-specific patterns, with modestly lower atrial and displacement values in older groups. Ethnicity-related differences were modest, heterogeneous, and substantially smaller in magnitude than age- and sex-related differences. Technical effects were parameter specific. While LV longitudinal and circumferential strains were largely unaffected, radial strain was higher at 3 T and showed vendor-related differences. LMS-derived reference ranges and centile thresholds were applied both across all ethnicities and within ethnicity-specific analyses, and are presented stratified by age and sex. In the prognostic analysis, centile categories were most consistently associated with incident heart failure. LV longitudinal, circumferential, and radial strain below the 0.5th centile were associated with significantly increased risk of incident heart failure (HRs: 9.9 to 12.4, 95% CIs 7.00-13.90 to 8.49-18.06). Conclusion This study provides age- and sex-specific reference ranges and centile-based categories for CMR-derived strain parameters in a large reference population. Age and sex represent the primary determinants of myocardial deformation, whereas scanner-related effects are parameter-specific. Values in the lower extremes of the healthy reference distribution, particularly for LV strain, are associated with increased risk of incident heart failure. These findings enable standardized, centile-based classification of myocardial strain, facilitating consistent interpretation and improving risk stratification in research and clinical practice.

Background: Tirzepatide and semaglutide improve functional status and heart failure (HF) events in patients with obesity and HF with preserved ejection fraction. Tirzepatide has been associated with greater control of cardiometabolic risk factors in patients with obesity compared to semaglutide. Whether tirzepatide is associated with lower risk of new-onset HF than semaglutide in patients with obesity is underexplored. Methods: A retrospective cohort study was conducted using data pooled from the TriNetX platform. Patients with obesity who initiated therapy with tirzepatide or semaglutide during the period Jun 4, 2021 to Aug 13, 2026 were identified and 1:1 propensity-score matched to produce two study cohorts. The one-year incidence of new-onset HF was calculated and compared between the two cohorts. Secondary outcomes included new-onset systolic HF, new-onset diastolic heart failure, new-onset atrial fibrillation or flutter, all-cause mortality, and hospital encounters. Cox proportional hazards models were fitted to calculate hazard ratios (HR) along with 95% confidence intervals (CI). Results: Two well-matched cohorts (N=424,269 in each) were formed. The incidence of new-onset HF was lower in the tirzepatide group (1.0% vs. 1.3%; absolute risk difference -0.3%, 95% CI -0.35 to -0.26; HR 0.9, 95% CI 0.86[boxh]0.93). The tirzepatide group were also at lower risk of all-cause mortality (HR, 95% CI: 0.8, 0.77[boxh]0.91) and new-onset systolic HF (0.8, 0.79[boxh]0.92). All other secondary outcomes occurred at similar rates in both study groups. Conclusion: Among patients with obesity, tirzepatide therapy was associated with lower risk of new-onset HF compared to semaglutide although the effect sizes were modest.

Background: Racial disparities in incident heart failure (HF) are well documented, yet the extent to which systemic inflammatory burden-shaped by structural determinants of environmental exposure-accounts for these disparities remains unquantified in multi-ethnic prospective cohorts. Methods: Among 6785 participants in the Multi-Ethnic Study of Atherosclerosis (enrolled 2000-2002; 4 racial/ethnic groups) followed for approximately 16 years, we estimated associations of 4 prespecified baseline inflammatory and hemostatic biomarkers (interleukin-6 [IL-6], C-reactive protein [CRP], fibrinogen, and D-dimer; per 1-SD increment) with incident HF (485 events) using Cox proportional hazards models. A composite inflammatory burden index was derived by principal components analysis. Race x biomarker multiplicative interactions were tested with Holm correction. Sequential biomarker adjustment quantified the percentage of the Black-White log-hazard difference explained relative to a clinical-only model. Robustness to ambient air pollution (PM2.5, NO2) was assessed in a geocoded subcohort. Results: All 4 biomarkers were independently associated with incident HF (IL-6: hazard ratio [HR], 1.20 [95% CI, 1.08-1.34]; D-dimer: 1.18 [1.06-1.30]; CRP: 1.14 [1.02-1.27]; fibrinogen: 1.13 [1.02-1.24]). The composite index (first principal component, 53.7% of variance explained) yielded an HR of 1.25 (1.12-1.39) per 1-SD increase. No multiplicative race x biomarker interaction was detected (all Holm-corrected P=1.0), indicating that the per-SD inflammatory hazard was directionally consistent across groups. Sequential biomarker adjustment reduced the Black-White log-hazard difference by 57.5%, a pattern consistent with-but not sufficient to prove-attenuation by inflammatory pathways. Associations were robust to PM2.5/NO2 co-adjustment. Conclusions: Inflammatory and hemostatic burden partially explains the Black-White disparity in incident HF. The null multiplicative interaction pattern indicates that per-unit biological risk is equitable across groups, consistent with differential structural exposure-rather than differential susceptibility-as a primary driver of disparity. Key Words: heart failure; inflammation; health equity; structural determinants; MESA; biomarkers

Background: Artificial intelligence (AI) may improve electrocardiographic differentiation of Takotsubo syndrome from acute anterior ST-segment elevation myocardial infarction (STEMI), but its impact on human diagnostic performance, the added value of visual explanations, and differences by reader background and experience remain uncertain. Methods: Using 12-lead electrocardiogram (ECG) images from two hospitals, we developed and externally validated an ensemble of three deep learning models after self-supervised pretraining and fine-tuning. The diagnostic task used ECGs recorded within 14 days after symptom onset, regardless of reperfusion status. We conducted a four-phase reader study. Phases 1-3 compared unaided interpretation, a reference sheet, and additional AI assistance. In Phase 4, readers evaluated a new ECG set after randomization to reference-sheet support alone, with AI predictions, or with AI predictions plus gradient-weighted class activation mapping (Grad-CAM) heatmaps. Diagnostic correctness was analyzed using generalized linear mixed-effects models. Exploratory analyses examined differences by cardiologist status and experience. Results: Development and external-validation cohorts, including healthy controls, comprised 832 and 95 participants, respectively. For Takotsubo-STEMI discrimination, external-validation accuracy was 0.914, with areas under the receiver operating characteristic and precision-recall curves of 0.970 and 0.984. Seventy healthcare providers completed the reader study. The estimated probability of correct diagnosis increased from 0.632 without assistance to 0.864 with AI assistance (odds ratio [OR], 3.71; P<0.001). In randomized Phase 4, AI assistance improved accuracy vs reference-sheet support alone (OR, 4.28; 95% CI, 3.08-5.95; P<0.001), and Grad-CAM provided additional benefit (OR, 1.53; 95% CI, 1.04-2.25; P=0.033). Exploratory analyses showed greater improvement among less experienced readers; with AI assistance, non-cardiologists outperformed cardiologists. AI-assisted readers remained less accurate overall than the model alone. Conclusions: An ECG image-based ensemble differentiated Takotsubo syndrome from anterior STEMI and improved reader accuracy. Visual explanations provided additional benefit, while experience-related differences highlight the importance of effective human-AI interaction.

Background Real-world data regarding mavacamten use in underserved and racially diverse populations remain limited, particularly for long-term therapy implementation. Structural barriers such as financial instability, fragmented healthcare access, and challenges adhering to REMS-related monitoring requirements may affect longitudinal therapy implementation. Methods We performed a retrospective observational study of consecutive patients with symptomatic obstructive hypertrophic cardiomyopathy (oHCM) evaluated for mavacamten therapy at a tertiary HCM center in Bronx, NY, between 6/2022-10/2025. Patients were followed for up to 48 weeks after treatment initiation. Clinical characteristics, treatment interruptions, adverse events, echocardiographic and functional outcomes, and implementation barriers were assessed descriptively. Results Seventy-two patients with symptomatic oHCM were evaluated for mavacamten; sixty-seven initiated treatment. Mean age was 66.9{+/-}15.3 years, 72% were female, and 61% identified as Black or Hispanic. Median resting left ventricular outflow tract (LVOT) gradient decreased from 51mmHg (IQR30-88) at baseline to 7mmHg (IQR5-10) at 48 weeks. Median Valsalva LVOT gradient decreased from 74mmHg (IQR50-104) to 20mmHg (IQR10-29). At final follow-up, 80% of patients improved by [&ge;]1 NYHA functional class. LVEF declined below 50% in five patients and recovered in all cases. Approximately one-quarter experienced treatment interruption or discontinuation, nearly half related to insurance instability, non-adherence, and REMS-related monitoring barriers. Conclusions Mavacamten demonstrated efficacy and safety outcomes comparable to those reported in clinical trials and prior registries in this predominantly underserved minority urban cohort. However, structural and healthcare-access barriers substantially affected long-term treatment implementation. These findings highlight the need to address healthcare-system barriers to ensure equitable implementation of contemporary HCM therapies.

Background Cardiovascular prevention is organized around target metrics. Blood pressure, LDL cholesterol, and A1c define treatment targets, quality metrics, and, implicitly, who is considered safe. Yet a value below a cutoff is a correlative measurement, not an outcome. We tested whether social context recorded before the measurement separated subsequent cardiovascular events among people whose numbers already met the cutoff. Methods In this retrospective cohort study, we analyzed All of Us participants without recorded cardiovascular disease and with low comorbidity in three separately indexed cohorts: systolic blood pressure (SBP), LDL cholesterol, and A1c. A preindex score combined household income, education, food security, physical activity, and ZIP-linked deprivation, standardized against a fixed pooled reference of 325,652 eligible people. The outcome was first myocardial infarction, ischemic stroke, or heart failure. A sensitivity analysis indexed participants at only events recorded in inpatient or emergency settings. Results The SBP, LDL, and A1c cohorts included 19,525, 16,578, and 18,539 participants with 144, 129, and 191 events. Each one-SD more favorable score was associated with lower hazard: HR 0.611 (95% CI 0.498-0.749), 0.631 (0.512-0.778), and 0.544 (0.457-0.648), respectively. Below each study cutoff (SBP <140 mmHg, LDL <100 mg/dL, A1c <8%), less favorable context had event rates of 3.39 versus 1.68, 7.16 versus 2.05, and 8.67 versus 2.34 per 1,000 person-years. In a one-year analysis restricted to 2019-2023 index dates, the corresponding adjusted HRs were 0.530, 0.336, and 0.365. In the sensitivity cohorts (54,338, 41,451, and 33,607 participants; 493, 288, and 316 events), HRs were 0.732 (0.657-0.815), 0.660 (0.573-0.761), and 0.631 (0.552-0.722). Conclusions A biomarker below the study cutoff did not identify a uniform, low-risk population. Social context recorded before the measurement separated cardiovascular events after adjustment for the measured value and clinical factors. Risk assessment that stops at the number misses this variation.

Background: Pacing-induced cardiomyopathy (PICM) is a major complication of chronic right ventricular pacing and develops in up to 25% of patients. Reliable prediction of PICM may facilitate individualized pacing strategy selection; however, currently available approaches demonstrate limited discriminative performance. This study aimed to develop and validate machine learning (ML) models for predicting PICM in patients with atrioventricular block (AVB) underlying heart failure with mildly reduced or preserved ejection fraction. Methods: In this multicenter prospective study derived from the RISK-PICM registry (January 2002 to January 2026), 125 patients with AVB who underwent pacemaker implantation were analyzed. PICM was defined as a ?10% reduction in left ventricular ejection fraction (LVEF) resulting in an LVEF <50%. Four ML algorithms, including logistic regression, support vector machine, random forest, and XGBoost, were trained using stratified 4-fold cross-validation with hyperparameter optimization and model discrimination was evaluated. Results: PICM developed in 41 patients (32.8%) during a median follow-up of 4.8 years. Male sex, pre-implant minimum QTc interval, and post-implant maximum QRS duration were significantly associated with PICM in univariable Cox regression. XGBoost achieved the highest discriminative performance (AUROC 0.831; sensitivity 0.805; specificity 0.845). Feature importance analysis identified baseline LVEF and post-implant maximum QRS duration as the most influential features. Model-derived risk stratification significantly differentiated high-risk and low-risk groups on Kaplan-Meier analysis (P < 0.001). Conclusions: ML-based models, particularly XGBoost, demonstrated clinically meaningful performance for PICM and may support individualized pacing strategy selection in patients with AVB and underlying heart failure with mildly reduced or preserved ejection fraction.

Background: Rheumatic mitral stenosis (RMS) disproportionately affects low-resource settings where echocardiography is limited. We evaluated foundation model (FM) feasibility for RMS detection using limited, indirectly labeled ECGs. Methods: An ECG-FM was fine-tuned using 804 RMS-positive ECGs per fold and externally validated across clinical and wearable lead configurations. Results: Internal AUROCs were 0.89, 0.87, and 0.87, for 12-Lead, 6-Lead, and 1-Lead respectively. External AUROCs were 0.82, 0.80, and 0.77. Performance remained comparable across demographic subgroups. Conclusions: FM fine-tuning enables RMS detection using limited ICD-derived labels, supporting further evaluation of reduced-lead ECG screening and echocardiography triage in resource-constrained settings.