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Objectives This study evaluated the comparative effectiveness of vitamin K antagonists (VKAs), direct thrombin inhibitors (DTIs) and factor Xa inhibitors (FXaI) in patients with atrial fibrillation (AF) at risk of stroke in everyday practice. Methods Data from patients with AF and Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, prior Stroke, TIA, or thromboembolism, Vascular disease, Age 65-74 years, Sex category (CHA2DS2-VASc) score ≥2 (excluding gender) in the Global Anticoagulant Registry in the FIELD–Atrial Fibrillation registry were analysed using an improved method of propensity weighting, overlap weights and Cox proportional hazards models. Results All-cause mortality, non-haemorrhagic stroke/systemic embolism (SE) and major bleeding over 2 years were compared in 25 551 patients, 7162 (28.0%) not treated with oral anticoagulant (OAC) and 18 389 (72.0%) treated with OAC (FXaI (41.8%), DTI (11.4%) and VKA (46.8%)). OAC treatment compared with no OAC treatment was associated with decreased risk of all-cause mortality (HR 0.82 (95% CI 0.74 to 0.91)) and non-haemorrhagic stroke/SE (HR 0.71 (95% CI 0.57 to 0.88)) but increased risk of major bleeding (HR 1.46 (95% CI 1.15 to 1.86)). Non-vitamin K antagonist oral anticoagulant (NOAC) use compared with no OAC treatment was associated with lower risks of all-cause mortality and non-haemorrhagic stroke/SE (HR 0.67 (95% CI 0.59 to 0.77)) and 0.65 (95% CI 0.50 to 0.86)) respectively, with no increase in major bleeding (HR 1.10 (95% CI 0.82 to 1.47)). NOAC use compared with VKA use was associated with lower risk of all-cause mortality and major bleeding (rates/100 patient-years 3.6 (95% CI 3.3 to 3.9) vs 4.8 (95% CI 4.5 to 5.2) and 1.0 (95% CI 0.9 to 1.1) vs 1.4 (95% CI 1.2 to 1.6); HR 0.79 (95% CI 0.70 to 0.89) and 0.77 (95% CI 0.61 to 0.98) respectively), with similar risk of non-haemorrhagic stroke/SE (rates/100 patient-years 0.8 (95% CI 0.7 to 0.9) versus 1.0 (95% CI 0.8 to 1.1); HR 0.96 (95% CI 0.73 to 1.25). Conclusion Important benefits in terms of mortality and major bleeding were observed with NOAC versus VKA with no difference among NOAC subtypes. Trial registration number NCT01090362.

Abstract Background We have demonstrated that artificial intelligence interpretation of ECGs (AI-ECG) can estimate an individual's physiologic age and that the gap between AI-ECG and chronologic age (Age-Gap) is associated with increased mortality. We hypothesized that Age-Gap would predict long-term atherosclerotic cardiovascular disease (ASCVD) and that Age-Gap would refine the ACC/AHA Pooled Cohort Equations' (PCE) predictive abilities. Methods Using the Rochester Epidemiology Project (REP) we evaluated a community-based cohort of consecutive patients seeking primary care between 1998–2000 and followed through March 2016. Inclusion criteria were age 40–79 and complete data to calculate PCE. We excluded those with known ASCVD, AF, HF or an event within 30 days of baseline.A neural network, trained, validated, and tested in an independent cohort of ∼ 500,000 independent patients, using 10-second digital samples of raw, 12 lead ECGs. PCE was categorized as low<5%, intermediate 5–9.9%, high 10–19.9%, and very high≥20%. The primary endpoint was ASCVD and included fatal and non-fatal myocardial infarction and ischemic stroke; the secondary endpoint also included coronary revascularization [Percutaneous Coronary Intervention (PCI) or Coronary Artery Bypass Graft (CABG)], TIA and Cardiovascular mortality. Events were validated in duplicate. Follow-up was truncated at 10 years for PCE analysis. The association between Age-Gap with ASCVD and expanded ASCVD was assessed with cox proportional hazard models that adjusted for chronological age, sex and risk factors. Models were stratified by PCE risk categories to evaluate the effect of PCE predicted risk. Results We included 24,793 patients (54% women, 95% Caucasian) with mean follow up of 12.6±5.1 years. 2,366 (9.5%) developed ASCVD events and 3,401 (13.7%) the expanded ASCVD. Mean chronologic age was 53.6±11.6 years and the AI-ECG age was 54.5±10.9 years, R2=0.7865, p<0.0001. The mean Age-Gap was 0.87±7.38 years. After adjusting for age and sex, those considered older by ECG, compared to their chronologic age had a higher risk for ASCVD when compared to those with <−2 SD age gap (considered younger by ECG). (Figure 1A), with similar results when using the expanded definition of ASCVD (data not shown). Furthermore, Age-Gap enhanced predicted capabilities of the PCE among those with low 10-year predicted risk (<5%): Age and sex adjusted HR 4.73, 95% CI 1.42–15.74, p-value=0.01 and among those with high predicted risk (>20%) age and sex adjusted HR 6.90, 95% CI 1.98–24.08, p-value=0.0006, when comparing those older to younger by ECG respectively (Figure 1B). Conclusion The difference between physiologic AI-ECG age and chronologic age is associated with long-term ASCVD, and enhances current risk calculators (PCE) ability to identify high and low risk individuals. This may help identify individuals who should or should not be treated with newer, expensive risk-reducing therapies. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Mayo Clinic

Abstract Background While the presence left ventricular (LV) remodelling after ST-segment elevation myocardial infarction (STEMI) is known to worsen prognosis, the impact of progressive vs. stable LV remodelling on outcome has not been established. Purpose To investigate the impact of progressive LV remodelling on outcome in STEMI patients who were treated with primary percutaneous coronary intervention (PCI) and optimal pharmacotherapy. Methods Baseline, 3-, 6- and 12-month echocardiograms were analysed. Early LV remodelling (ER) was defined as a ≥20% increase in LV end-diastolic volume (EDV) during the first 3 months post-STEMI, and mid-term remodelling (MTR) as ≥20% LVEDV change by 6 months. Progressive LV remodelling was defined according to spline curve analyses: ≥0% LVEDV increase by 6 months (i.e. further increase after 3 months) for ER, and ≥20% by 12 months (i.e. an additional increase after 6 months) for MTR. The impact of progressive LV remodelling on outcome was evaluated with a Log rank test. Results 589 STEMI patients (mean age 61±12 years, 78% male) who demonstrated LV remodelling in the first 6 months post-infarct, were analysed: 408 (69%) ER and 181 (31%) MTR. Progressive LV remodelling occurred in 146 (36%) ER and in 12 (7%) MTR. After a median follow-up of 90 (IQR 64–117) months, 39 (10%) ER were hospitalised for heart failure. 25 (14%) MTR remodellers died after a median follow-up of 86 (IQR 66–112) months. Progressive LV remodelling in ER led to a higher rate of heart failure hospitalisation (P=0.017 vs. non-progressive ER, Fig. 1A) but no mortality difference (P=0.10 vs. non-progressive ER). In contrast, MTR with progressive LV remodelling experienced worse survival (P=0.01 vs. non-progressive MTR, Fig. 1B) but no increase in heart failure hospitalisation (P=0.65 vs. non-progressive MTR). Conclusions Progressive LV remodelling causes an increased risk of heart failure in ER post-infarct, vs. higher mortality in MTR. These two patterns of progressive, post-infarct LV remodelling possibly represent different underlying pathophysiological mechanisms: i.e. evolution of true post-infarct remodelling in ER, vs. natural history of established heart failure in MTR. Figure 1 Funding Acknowledgement Type of funding source: None

Abstract Aims This study aims to explore long-term clinical outcomes of cardiopoiesis-guided stem cell therapy for ischaemic heart failure assessed in the Congestive Heart Failure Cardiopoietic Regenerative Therapy (CHART-1) trial. Methods and results CHART-1 is a multinational, randomized, and double-blind trial conducted in 39 centres in heart failure patients (n = 315) on standard-of-care therapy. The ‘active’ group received cardiopoietic stem cells delivered intramyocardially using a retention-enhanced catheter. The ‘control’ group underwent patient-level sham procedure. Patients were followed up to 104 weeks. In the entire study population, results of the primary hierarchical composite outcome were maintained neutral at Week 52 [Mann–Whitney estimator 0.52, 95% confidence interval (CI) 0.45–0.59, P = 0.51]. Landmark analyses suggested late clinical benefit in patients with significant left ventricular enlargement receiving adequate dosing. Specifically, beyond 100 days of follow-up, patients with left ventricular end-diastolic volume of 200–370 mL treated with ≤19 injections of cardiopoietic stem cells showed reduced risk of death or cardiovascular hospitalization (hazard ratio 0.38, 95% CI 0.16–0.91, P = 0.031) and cardiovascular death or heart failure hospitalization (hazard ratio 0.28, 95% CI 0.09–0.94, P = 0.040). Cardiopoietic stem cell therapy was well tolerated long term with no difference in safety readouts compared with sham at 2 years. Conclusions Longitudinal follow-up documents that cardiopoietic stem cell therapy is overall safe, and post hoc analyses suggest benefit in an ischaemic heart failure subpopulation defined by advanced left ventricular enlargement on tolerable stem cell dosing. The long-term clinical follow-up thus offers guidance for future targeted trials.