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https://www.selleckchem.com/products/Idarubicin.html More than 90% of patients with congenital heart disease (CHD) are nowadays surviving to adulthood and adults account for over two-thirds of the contemporary CHD population in Western countries. Although outcomes are improved, surgery does not cure CHD. Decades of longitudinal observational data are currently motivating a paradigm shift toward a lifespan perspective and proactive approach to CHD care. The aim of this review is to operationalize these emerging concepts by presenting new constructs in CHD research. These concepts include long-term trajectories and a life course epidemiology framework. Focusing on a precision health, we propose to integrate our current knowledge on the genome, phenome, and environome across the CHD lifespan. We also summarize the potential of technology, especially machine learning, to facilitate longitudinal research by embracing big data and multicenter lifelong data collection. The randomized SOLVE-TAVI (compariSon of secOnd-generation seLf-expandable vs. balloon-expandable Valves and gEneral vs. local anesthesia in Transcatheter Aortic Valve Implantation) trial compared newer-generation self-expanding valves (SEV) and balloon-expandable valves (BEV) as well as local anesthesia with conscious sedation (CS) and general anesthesia (GA) in patients undergoing transfemoral transcatheter aortic valve replacement (TAVR). Both strategies showed similar outcomes at 30days. The purpose of this study was to compare clinical outcomes during 1-year follow-up in the randomized SOLVE-TAVI trial. Using a 2× 2 factorial design 447 intermediate- to high-risk patients with severe, symptomatic aortic stenosis were randomly assigned to transfemoral TAVR using either the SEV (Evolut R, Medtronic Inc., Minneapolis, Minnesota) or the BEV (Sapien 3, Edwards Lifesciences, Irvine, California) as well as CS or GA at 7 sites. In the valve-comparison strategy, rates of the combined endpoint of all-cause at 1 y

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