Endomyocardial biopsy (EMB) is an invasive procedure, globally most often used for the monitoring of heart transplant (HTx) rejection. In addition, EMB can have an important complementary role to the clinical assessment in establishing the diagnosis of diverse cardiac disorders, including myocarditis, cardiomyopathies, drug-related cardiotoxicity, amyloidosis, other infiltrative and storage disorders, and cardiac tumours. Improvements in EMB equipment and the development of new techniques for the analysis of EMB samples have significantly improved diagnostic precision of EMB. The present document is the result of the Trilateral Cooperation Project between the Heart Failure Association of the European Society of Cardiology, the Heart Failure Society of America, and the Japanese Heart Failure Society. It represents an expert consensus aiming to provide a comprehensive, up-to-date perspective on EMB, with a focus on the following main issues: (i) an overview of the practical approach to EMB, (ii) an update on indications for EMB, (iii) a revised plan for HTx rejection surveillance, (iv) the impact of multimodality imaging on EMB, and (v) the current clinical practice in the worldwide use of EMB.

Background: We assessed the prevalence of newly diagnosed prediabetes and type-2 diabetes mellitus (T2DM), and their impact on long-term mortality in patients hospitalized for worsening heart failure with reduced ejection fraction (HFrEF). Methods: We included patients hospitalized with HFrEF and New York Heart Association (NYHA) functional class II-III. Baseline two-hour oral glucose tolerance test was used to classify patients as normoglycaemic or having newly diagnosed prediabetes or T2DM. Outcomes included post-discharge all-cause and cardiovascular mortality during the median follow-up of 2.1 years. Results: At baseline, out of 150 patients (mean-age 57 AE 12 years; 88% male), prediabetes was diagnosed in 65 (43%) patients, and T2DM in 29 (19%) patients. These patients were older and more often with NYHA class III symptoms, but distribution of comorbidities was similar to normoglycaemic patients. Taking normoglycaemic patients as a reference, adjusted risk of all-cause mortality was significantly increased both in patients with prediabetes (hazard ratio, 2.6; 95% confidence interval (CI), 1.1-6.3; p ¼ 0.040) and in patients with T2DM (hazard ratio, 5.3; 95% CI, 1.7-15.3; p ¼ 0.023). Likewise, both prediabetes (hazard ratio, 2.9; 95% CI, 1.1-7.9; p ¼ 0.041) and T2DM (hazard ratio, 9.7; 95% CI 2.9-36.7; p ¼ 0.018) independently increased the risk of cardiovascular mortality compared with normoglycaemic individuals. There was no interaction between either prediabetes or T2DM and heart failure aetiology or gender on study outcomes (all interaction p-values > 0.05). Conclusions: Newly diagnosed prediabetes and T2DM are highly prevalent in patients hospitalized for worsening HFrEF and NYHA functional class II-III. Importantly, they impose independently increased long-term risk of higher all-cause and cardiovascular mortality.

Aims Impact of type 2 diabetes mellitus (T2DM) on non‐thromboembolic outcomes in atrial fibrillation (AF) is insufficiently explored. This prospective cohort study of AF patients aimed (i) to analyse the association between T2DM and heart failure (HF) events (including new‐onset HF), and all‐cause and cardiovascular mortality, (ii) to assess the impact of baseline T2DM treatment on outcomes, and (iii) to explore characteristics of new‐onset HF phenotypes in relation to T2DM status. Methods and results Of 1803 AF patients (515/1288, with/without prior HF), 389 (22%) had T2DM at baseline. After 5 years of median follow‐up, T2DM patients had an 85% greater risk of HF events [adjusted hazard ratio (aHR) 1.85; 95% confidence interval (CI) 1.51–2.28; P < 0.001], including a 45% increased risk for new‐onset HF (1.45; 1.17–2.28; P = 0.015). T2DM conferred a 56% higher all‐cause (1.56, 1.22–2.01; P = 0.003) and a 48% higher cardiovascular mortality (1.48; 1.34–1.93; P = 0.007). Fine–Gray analysis, with mortality as a competing risk, confirmed greater HF risk among T2DM patients. All risks were highest among insulin‐treated patients. The prevalence of new‐onset HF phenotypes was as follows: 67% preserved ejection fraction (HFpEF), 20% mid‐range ejection fraction (HFmrEF) and 13% reduced ejection fraction (HFrEF). On time‐dependent Cox regression, adjusted for baseline characteristics and an interim acute coronary event, T2DM increased aHRs for new‐onset HFpEF (2.38; 1.30–4.58; P <0.001) and the combined HFmrEF/HFrEF (1.77; 1.11–3.62; P = 0.017). Conclusions Atrial fibrillation patients with T2DM have independently increased risk of new‐onset/recurrent HF events, cardiovascular and all‐cause mortality, particularly when insulin‐treated. The prevailing phenotype of new‐onset HF was HFpEF; T2DM conferred higher risk of both HFpEF and HFmrEF/HFrEF.

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Background Considering clinical importance of bleeding complications in patients with acute myocardial infarction (AMI), bleeding risk stratification is a key part of the management of these patients. CRUSADE, ACTION and ACUITY-HORIZONS bleeding risk scores are available for predicting in-hospital major bleeding events in patients with acute myocardial infarction. Purpose We aimed to evaluate performance of the three above mentioned risk scores for predicting in-hospital bleeding events defined according to The Bleeding Academic Research Consortium (BARC) criteria. Methods From a prospective electronic registry of a high-volume catheterization laboratory in a period from January 2009 to December 2017, a total of 6505 consecutive patients with acute myocardial infarction who underwent pPCI were included in analysis. Calibration and discrimination of the three risk models were evaluated by the Hosmer-Lemeshow (H-L) goodness-of-fit test and C-statistic, respectively. Results Overall there were 372 (5.7%) bleeding events out of which 117 (1.8%) fulfilled stage BARC 3 or higher bleeding criteria. All three scores showed good model calibration as assessed by the H-Ls test and very good discriminative power for BARC 3 of higher bleeding events detection as assessed by C-statistics (Table 1 & Figure 1): Bleeding events stage BARC 3 or higher were statistically highly related with higher in-hospital mortality (13.7% vs. 3.5%; p<0.000). Table 1 Risk score H-L H-L p AUC 95% CI p CRUSADE 11.46 0.177 0.761 0.750–0.771 vs. ACUITY = ns vs. ACTION <0.000 ACUITY-HORIZONS 10.47 0.236 0735 0.724–0.745 vs. ACTION = ns ACTION 5.74 0.677 0.701 0.698–0.712 Figure 1 Conclusions All three evaluated scores showed very good discriminative capacity for predicting BARC 3 or higher bleeding events in patients undergoing pPCI for AMI.

Background Type 2 diabetes (T2DM) portends adverse prognosis in patients with atrial fibrillation (AF). Whether T2DM independently increases the risk of incident heart failure (HF) in AF is uncertain. Also, HF phenotype developing in patients with vs. those without T2DM has not been characterised. Purpose In AF patients without a history of prior HF, we aimed to assess: 1) the impact of T2DM on the risk of new-onset HF; and 2) the association between T2DM and HF phenotype developing during the prospective follow-up. Methods We included diabetic and non-diabetic AF patients, without a history of HF. Baseline T2DM status was inferred from medical history, haemoglobin A1c levels and oral glucose tolerance test. Study outcome was the first hospital admission or emergency department treatment for new-onset HF during the prospective follow-up. The phenotype of new-onset HF was determined by echocardiographic exam performed following clinical stabilisation (at hospital discharge, or within a month after HF diagnosis). HF phenotype was defined as HFrEF (left ventricular ejection fraction [LVEF] <40%), HFmrEF (LVEF 40–49%) or HFpEF (LVEF≥50%). Cox regression analyses adjusted for age, sex, baseline LVEF, comorbidities, smoking status, alcohol intake, AF type (paroxysmal vs. non-paroxysmal) and T2DM treatment was used to analyse the association between T2DM and incident HF. Results Among 1,288 AF patients without prior HF (mean age: 62.1±12.7 years; 61% male), T2DM was present in 16.5%. Diabetic patients had higher mean baseline LVEF compared with nondiabetic patients (50.0±6.2% vs. 57.6±9.0%; P<0.001). During the median 5.5-year follow-up, new-onset HF occurred in 12.4% of patients (incidence rate, 2.9; 95% confidence interval [CI], 2.5–3.3 per 100 patient-years). Compared with non-diabetic patients, those with T2DM had a hazard ratio of 2.1 (95% CI, 1.6–2.8; P<0.001) for new-onset HF, independent of baseline LVEF or other factors. In addition, diabetic patients had a significantly greater decline in covariate-adjusted mean LVEF (−10.4%; 95% CI, −9.8% to −10.8%) at follow-up, compared with nondiabetic patients (−4.0%; 95% CI, −3.8% to −4.2%), P<0.001. The distribution of HF phenotypes at follow-up is presented in Figure. Among patients with T2DM, HFrEF (56.9%) was the most common phenotype of HF, whereas in patients without T2DM, HF mostly took the phenotype of HFpEF (75.0%). Conclusions T2DM is associated with an independent risk of new-onset HF in patients with AF and confers a greater decline in LVEF compared to individuals without T2DM. HFrEF was the most prevalent presenting phenotype of HF in AF patients with T2DM.

Background Predicting malignant ventricular arrhythmias and heart failure in patients (pts) with acute myocarditis and middle-range and preserved EF is challenge Aim: to define whether quantification of myocardial mechanics in early, acute phase of myocarditis offers more information to predict six months outcome of patients.Methods: In the 36 consecutive pts with myocarditis, middle age 32.86 ± 12.04yr, 75% males, echocardiography exam was done 1-3 day of diseases, including conventional parameters and comprehensive speckle tracking LV deformation analysis with longitudinal (L), circumferential (C) strain (S;%), strain rate (SR, 1/sec) and rotational LV mechanics. Results: The most patients were present as infarct-like myocarditis (80.56%), the others patients were present as heart failure-like (11.11%) and arrhythmia-like myocarditis (8.33%). At admission 27 (90%) pts had chest pain, 20 (66.7%) pts had ECG changes, 15 (50%) pts had symptoms of heart failure, 5 (16.7%) pts had arrhythmias. Amount of edema and fibrosis assessed by cardiovascular magnetic resonance (CMR) and echo correlate significantly. Classical and conventional parameters of LV systolic function, and deformation were not significantly different between groups. However, mechanical dispersion index (IMD) of global LS and systolic S were significantly different between groups (p &lt; 0.05). Conclusion: Myocardial deformation imaging, like speckle tracking echocardiography, offers deeper insight into complex mechanical abnormalities during not only LV contraction but LV relaxation in longitudinal directions in patients with acute myocarditis. Infarct-like Arrhythmia-like Heart failure-like p EF (%) 57.5 ± 5.42 54.7 ± 12.9 58.3 ± 6.8 NS GLS endo (%) -20.8 ± 2.59 -19.78 ± 2.27 -17.36 ± 5.65 NS GLS (mid (%) -18.31 ± 2.4 -17.31 ± 1.52 -15.3 ± 5.10 NS GLS epi (%) -16.15 ± 2.28 -15.20 ± 0.92 -13.55 ± 4.68 NS IMD LS (ms) 37.04 ± 7.71 33.04 ± 6.58 60.75 ± 38.56 0.008 CS endo (%) -26.39 ± 6.93 -21.59 ± 3.88 -25.17 ± 6.48 NS CS mid (%) -17.32 ± 6.77 -13.03 ± 2.07 -15.95 ± 4.41 NS CS epi (%) -10.99 ± 6.89 -7.13 ± 0.72 -9.53 ± 2.73 NS IMD CS (ms) 47.69 ± 8.86 41.43 ± 23.92 41.01 ± 20.51 NS IMD SL peak S* 12.27 (21) 13.96 (4) 20.28 (84) 0.042 *Median and range values are presented.