Background: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is increasingly used to treat cardiogenic shock. However, VA-ECMO might hamper myocardial recovery. The Impella unloads the left ventricle. This study aimed to evaluate whether left ventricular unloading in patients with cardiogenic shock treated with VA-ECMO was associated with lower mortality. Methods: Data from 686 consecutive patients with cardiogenic shock treated with VA-ECMO with or without left ventricular unloading using an Impella at 16 tertiary care centers in 4 countries were collected. The association between left ventricular unloading and 30-day mortality was assessed by Cox regression models in a 1:1 propensity score–matched cohort. Results: Left ventricular unloading was used in 337 of the 686 patients (49%). After matching, 255 patients with left ventricular unloading were compared with 255 patients without left ventricular unloading. In the matched cohort, left ventricular unloading was associated with lower 30-day mortality (hazard ratio, 0.79 [95% CI, 0.63–0.98]; P =0.03) without differences in various subgroups. Complications occurred more frequently in patients with left ventricular unloading: severe bleeding in 98 (38.4%) versus 45 (17.9%), access site–related ischemia in 55 (21.6%) versus 31 (12.3%), abdominal compartment in 23 (9.4%) versus 9 (3.7%), and renal replacement therapy in 148 (58.5%) versus 99 (39.1%). Conclusions: In this international, multicenter cohort study, left ventricular unloading was associated with lower mortality in patients with cardiogenic shock treated with VA-ECMO, despite higher complication rates. These findings support use of left ventricular unloading in patients with cardiogenic shock treated with VA-ECMO and call for further validation, ideally in a randomized, controlled trial.

Cardiomyopathies are a heterogeneous group of structural, mechanical, and electrical heart muscle disorders which often correlate with life-threatening arrhythmias and progressive heart failure accounting for significant cardiovascular morbidity and mortality. Currently, cardiomyopathies still represent a leading reason for heart transplantation worldwide. The last years have brought remarkable advances in the field of cardiomyopathies especially in terms of understanding the molecular basis as well as the diagnostic evaluation and management. Although most cardiomyopathy treatments had long focused on symptom management, much of the current research efforts aim to identify and act on the disease-driving mechanisms. Regarding risk assessment and primary prevention of sudden cardiac death, additional data are still pending in order to pave the way for a more refined and early patient selection for defibrillator implantation. This review summarizes the current knowledge of hypertrophic, dilated and arrhythmogenic cardiomyopathy with a particular emphasis on their pathophysiology, clinical features, and diagnostic approach. Furthermore, the relevant ongoing studies investigating novel management approaches and main gaps in knowledge are highlighted.

Background: Coronary artery disease (CAD) is a frequent comorbidity in patients undergoing transcatheter aortic valve implantation (TAVI). If significant CAD can be excluded on coronary CT-angiography (cCTA), invasive coronary angiography (ICA) may be avoided. However, a high plaque burden may make the exclusion of CAD challenging, particularly for less experienced readers. The objective was to analyze the ability of machine learning (ML)-based CT-derived fractional flow reserve (CT-FFR) to correctly categorize cCTA studies without obstructive CAD acquired during pre-TAVI evaluation and to correlate recategorization to image quality and coronary artery calcium score (CAC). Methods: In total, 116 patients without significant stenosis (≥50% diameter) on cCTA as part of pre-TAVI CT were included. Patients were examined with an electrocardiogram-gated CT scan of the heart and high-pitch scan of the torso. Patients were re-evaluated with ML-based CT-FFR (threshold = 0.80). The standard of reference was ICA. Image quality was assessed quantitatively and qualitatively. Results: ML-based CT-FFR was successfully performed in 94.0% (109/116) of patients, including 436 vessels. With CT-FFR, 76/109 patients and 126/436 vessels were falsely categorized as having significant CAD. With CT-FFR 2/2 patients but no vessels initially falsely classified by cCTA were correctly recategorized as having significant CAD. Reclassification occurred predominantly in distal segments. Virtually no correlation was found between image quality or CAC. Conclusions: Unselectively applied, CT-FFR may vastly increase the number of false positive ratings of CAD compared to morphological scoring. Recategorization was virtually independently from image quality or CAC and occurred predominantly in distal segments. It is unclear whether or not the reduced CT-FFR represent true pressure ratios and potentially signifies pathophysiology in patients with severe aortic stenosis.