BACKGROUND:Whether COVID-19 vaccination is associated with lower long-term cardiovascular risk after SARS-CoV-2 infection and how much infection prevention mediates this association remain unclear. OBJECTIVE:To evaluate associations of vaccination, including its timing relative to SARS-CoV-2 infection, with post-COVID-19 cardiovascular disease (CVD), and quantify the contribution of infection prevention. METHODS:This statewide population-based cohort study used linked administrative health data for 2,391,456 adults in Victoria, Australia (2019-2025). Associations of pre- or post-infection vaccination with major adverse cardiovascular events (MACE; primary outcome), stroke, heart failure, acute myocardial infarction (AMI), acute coronary syndrome (ACS), atrial fibrillation (AF), and venous thromboembolism (VTE) were evaluated using time-varying Cox proportional hazards regression, causal mediation analysis, and target trial emulation. RESULTS:Vaccination was associated with lower hazards of MACE and all secondary outcomes. Estimated absolute risk reductions for MACE were 0.21% with pre-infection vaccination and 0.24% with post-infection vaccination. Three or more vaccine doses were associated with progressively lower hazards across cardiovascular outcomes. Mediation analysis suggested that approximately 68% of the estimated association between vaccination and lower post-COVID cardiovascular risk was not explained by prevention of SARS-CoV-2 infection. CONCLUSION:Vaccination before or after SARS-CoV-2 infection was associated with lower hazards of post-COVID-19 cardiovascular outcomes, with stronger observed associations at higher dose numbers. Most of the estimated association was not explained by infection prevention alone. These findings support COVID-19 vaccination as an important component of strategies to reduce the burden of post-COVID-19 CVD while highlighting the need for further studies to clarify the mechanisms underlying these associations.
AIMS:Although implantation volume of cardiac implantable electronic device (CIED) is widely considered a prognostic factor, Germany continues to show a wide distribution of hospitals performing CIED procedures, with annual volumes ranging from fewer than 10 to over 500 cases. Using a new statistical volume-outcome model, we examined the existence and shape of the relationship between complication rates and hospital volume. METHODS AND RESULTS:The analysis is based on data from all first inpatient CIED implantations performed between 1 January 2010 and 31 December 2020, in hospitals across North Rhine-Westphalia. All peri- and post-operative complications documented in mandatory quality assurance were included. A possible association between implantation volume and quality was assessed using a flexible generalized additive mixed model. Out of 249 118 cases, the overall complication rate was 2.4%, with lead-related issues being the most common (1.5%). Forest plot analysis identified American Society of Anaesthesiologists Class 4-5, New York Heart Association Class IV, subclavian vein access, and dual-chamber pacemaker systems as the strongest predictors of complications. Volume-outcome analysis revealed a significant association between implantation volume and complications, particularly among pacemaker patients [P < 0.001, area under the curve (AUC) 0.7], and showed a relevant reduction in hospital stays and healthcare costs. Modelling suggested that a 50-case annual cut-off could prevent ∼16% of complications, requiring ∼16% of patients to be redirected to other hospitals. CONCLUSION:This study demonstrates a statistically significant association between implantation volume and complication rates across all CIED procedures, with the effect being particularly pronounced among pacemaker patients.
BACKGROUND:N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a cornerstone biomarker for the diagnosis and management of heart failure, but its use may be limited by the need for blood testing and laboratory infrastructure. Artificial intelligence (AI) applied to electrocardiograms (ECGs) may offer a widely accessible, non-invasive approach to estimate NT-proBNP levels. METHODS:We developed a convolutional neural network incorporating residual and attention-based layers to estimate NT-proBNP levels from standard 12-lead ECGs. The model was trained using 84,895 ECG-NT-proBNP pairs from 40,762 adult patients; 8,545 patients were held out for internal validation. The model generated a nine-level ECG-BNP score. External validation was conducted in 679 patients at two tertiary cardiovascular centers. Discrimination for prespecified thresholds (>250, >500, >1,000 pg/mL) was assessed by AUROC with 95% CIs; calibration and threshold-specific sensitivity, specificity, PPV/NPV were evaluated. RESULTS:In internal validation, the AI-ECG score showed a strong correlation with measured NT-proBNP levels (Spearman ρ=0.85, p<0.001) and high discrimination across thresholds (AUROC >0.92). In external validation, the model achieved AUROCs of 0.866 (95% CI 0.838-0.894) for >250 pg/mL, 0.882 (95% CI 0.857-0.907) for >500 pg/mL, and 0.885 (95% CI 0.859-0.914) for >1,000 pg/mL. Performance was consistent across key clinical subgroups. CONCLUSIONS:An AI-enabled ECG model can identify patients with elevated NT-proBNP levels with good accuracy in both internal and external validation cohorts. This approach may help identify patients who should undergo confirmatory NT-proBNP testing, particularly when biomarker testing is delayed, unavailable, or not routinely performed. Prospective studies are warranted to define whether this strategy provides incremental clinical value and can be integrated into clinical pathways.
The care pathway for severe aortic stenosis (AS) remains vulnerable to diagnostic delay, referral inertia, undertreatment, and procedural waiting times despite the availability of definitive intervention with surgical or transcatheter aortic valve replacement. This systematic review with narrative synthesis aimed to identify where delay and attrition occur across the contemporary severe AS pathway and to summarise evidence for digital, organisational, and workflow interventions designed to improve timely care. Randomised and non-randomised studies examining diagnostic, referral, treatment-decision, or procedural-access delays in adults with severe AS were eligible. Findings were mapped onto a four-checkpoint framework: pre-echocardiographic recognition, echocardiographic detection, post-diagnostic referral and decision-making, and procedural access. Nineteen studies met inclusion criteria. After de-duplication of overlapping registries and exclusion of studies without a verifiable unique severe-AS or severe-AS pathway denominator, the synthesis represented approximately 52,000 patients. Evidence was unevenly distributed, with no included study providing severe-AS-specific data before echocardiography. At echocardiographic detection, missed or delayed recognition was concentrated in low-gradient phenotypes and women; an artificial-intelligence-assisted alert system increased severe-AS detection from 2.4% to 4.1%. After diagnosis, undertreatment persisted despite guideline indications, and non-cardiology ordering of the diagnostic echocardiogram was associated with lower early follow-up or AVR and higher mortality. Electronic provider notification increased one-year AVR rates from 37.2% to 48.2%, with the largest observed effects in women, patients older than 80 years, and inpatient echocardiography. At procedural access, wait-list mortality was approximately 4.5%-5.8%, with deaths occurring early after referral. Risk-based triage reduced modelled wait-list mortality, while decentralised pre-procedural work-up shortened referral-to-TAVI time from 126 to 32 days. Severe AS care is characterised by measurable delay and attrition across multiple post-diagnostic transitions, while pre-echocardiographic recognition remains an important evidence gap. A four-checkpoint framework may support benchmarking and targeted pathway improvement through structured reporting, electronic referral prompts, risk-based triage, and decentralised workflows.
Aims Access to cardiac implantable electronic device (CIED) therapy varies substantially across Europe, yet data from the European Society of Cardiology (ESC) EuroAsia region remain limited. We aimed to compare implantation activity of pacemakers (PMs), implantable cardioverter-defibrillators (ICDs), and cardiac resynchronization therapy (CRT) devices across ESC EuroAsia Task Force (TF) countries and to examine how infrastructure, workforce capacity, and health financing patterns relate to device uptake. Methods and results National-level aggregated data were collected in 2025 through a standardized ESC EuroAsia TF survey and contextualized using European Heart Rhythm Association Atlas indicators and World Bank/World Health Organization Health Expenditure Data. Implantation rates per million population were compared across Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Turkmenistan, and Uzbekistan. Pacemaker implantation showed moderate variability (21-333 per million), whereas ICD (0.1-172 per million) and particularly CRT (1-135 per million) implantation demonstrated pronounced disparities. Countries with higher density of implanting centres and greater electrophysiology workforce availability-most notably Georgia-had substantially higher per capita ICD and CRT implantation rates. Exploratory analyses suggested moderate positive correlations between national health expenditure (%gross domestic product) and ICD and CRT implantation rates, whereas financing structure (out-of-pocket vs. government share) showed no consistent association. Conclusion Cardiac implantable electronic device implantation activity in the ESC EuroAsia region follows a clear complexity gradient (PM > ICD > CRT), indicating that access to advanced device therapy is primarily determined by system capacity rather than guideline awareness alone. Strengthening predictable reimbursement pathways, structured referral networks, workforce development, and national registries may reduce inequities and narrow the evidence-practice gap in sudden cardiac death prevention and heart failure management.
BACKGROUND:Guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) is well established, but data on differences between men and women in real-world use, tolerability, and outcomes are limited. We examined these differences in contemporary HFrEF patients. METHODS AND RESULTS:TITRATE-HF is a prospective registry across 48 Dutch hospitals (inclusion June 2022-February 2024), enrolling patients with de novo, chronic, and worsening heart failure (HF). This analysis studied 3,367 HFrEF patients and compared men and women regarding GDMT implementation, side effects, change in left ventricular ejection fraction (LVEF), and clinical outcomes (composite endpoint: first HF hospitalization or all-cause death). The cohort included 2,408 men (71.5%; 71 years [IQR 63-77]) and 959 women (28.5%; 72 years [IQR 64-79]). At 12-month follow-up, 59.0% of men and 59.7% of women received quadruple therapy (p=0.729). Men more often achieved quadruple therapy at ≥50% of target doses (16.2% versus 11.9%, p=0.004). Compared to men, women experienced more downgrades of ARB (11.6% versus 6.9%, p=0.040) and MRA (13.2% versus 10.4%, p=0.038) due to side effects. In de novo HFrEF, women showed greater LVEF improvement than men (15% versus 13%, p=0.005). In chronic HFrEF, women had lower risk of the composite endpoint compared to men (aHR 0.64, 95% CI 0.45-0.91; p=0.015). CONCLUSIONS:GDMT initiation and sequencing were comparable between men and women, but differences were observed in dose achievement, treatment tolerability, and clinical outcomes. These findings underscore the need for implementation and dosing strategies that account for differences between men and women.
Abstract Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide, typically driven by age, obesity, and other conventional cardiovascular risk factors. However, a subset of patients develop early-onset AF—often before 65 years of age in the absence of structural heart disease—suggesting alternative mechanisms beyond acquired risk. Emerging evidence implicates pathogenic variants in cardiomyopathy-associated genes as key drivers in this population. This review synthesizes contemporary evidence linking cardiomyopathy gene variants, particularly in TTN, LMNA, MYH7, and PKP2, to early-onset AF. Across multiple sequencing cohorts, pathogenic or likely pathogenic variants are identified in 5–20% of young AF patients, with prevalence rising sharply at younger ages. TTN truncating variants confer up to a two-fold increased risk of AF and a 10-fold higher risk of subsequent dilated cardiomyopathy, whereas LMNA mutations are associated with aggressive atrial fibrosis, conduction disease, and early recurrence after catheter ablation. Longitudinal studies demonstrate that genotype-positive AF patients face higher risks of heart failure, sudden cardiac death, and progression to overt cardiomyopathy. These findings redefine early-onset AF as a potential sentinel manifestation of inherited myocardial disease rather than an isolated electrical disorder. Genetic testing—especially in individuals with AF onset ≤45 years or a family history of cardiomyopathy—enables early detection, cascade screening, and personalized surveillance. Integrating genomics, advanced imaging, and electrophysiological management supports a precision medicine framework that may improve outcomes by identifying and intervening before structural disease develops.
The European Society of Cardiology (ESC) develops and updates clinical practice guidelines (CPGs) based on the latest evidence. However, their implementation remains suboptimal, leading to missed opportunities to improve cardiovascular (CV) outcomes. The success of CPG implementation is influenced by four key factors: (i) patient-related barriers, (ii) health care professionals’ engagement, (iii) the clarity and usability of CPGs, and (iv) the health care system and economic context in which care is delivered. To address these challenges, innovative strategies are needed to bridge the gap between CPG recommendations and clinical practice. The ESC has developed several initiatives to improve implementation, including (i) educational programmes, (ii) examinations for cardiologists, (iii) accreditation policies, and (iv) registries. However, persistent gaps indicate that knowledge dissemination alone is insufficient. A more integrated, structured, and equitable approach to quality-of-care improvement is required. Despite the need for evidence-based implementation strategies, only a limited number of high-quality randomized controlled trials have evaluated individual approaches for CV conditions. Strategies such as text messaging, educational interventions, the involvement of non-physician health workers, structured order sheets, and financial incentives have been tested, but their feasibility and effectiveness can vary across health care systems. Future research should explore the potential of artificial intelligence-enhanced technologies to support and scale implementation efforts. This manuscript reviews current evidence on CPG implementation and proposes strategies to enhance the adoption of best practices in CV care.
