The association between bicuspid aortic valve (BAV) and ascending aorta aneurysm is well described. Replacement of the ascending aorta is now being considered at 4.5 cm. We identified patients confirmed with BAV who underwent elective aortic valve replacement (AVR) with a mechanical St Jude Bioprosthesis from 1994 to 2000 who were ≤65 years of age at the time of surgery. Follow-up imaging was obtained by computed tomography (CT) angiography or echocardiography. A total of 225 patients who underwent AVR were identified; 60 patients had a BAV. Of all, 36 (60%) patients with BAV returned for follow-up imaging of their ascending aorta. Eight patients (22%) had diameters classifiable as aneurysmal (>4.5 cm) that developed within 9.6 ± 4.1 years from implant and requiring surgery. Of all, 7 patients (12%) died within 5.9 ± 2.5 years from their implant date. Lifelong serial monitoring of the ascending aorta for patients with BAV should be the standard of care.

INSTITUTEThe Open Technology Institute at New America is committed to freedom and social justice in the digital age. To achieve these goals, it intervenes in traditional policy debates, builds technology, and deploys tools with communities. OTI brings together a unique mix of technologists, policy experts, lawyers, community organizers, and urban planners to examine the impacts of technology and policy on people, commerce, and communities. Our current focus areas include surveillance, privacy and security, network neutrality, broadband access, and Internet governance. ABOUT THE CYBERSECURITY INITIATIVEThe Internet has connected us. Yet the policies and debates that surround the security of our networks are too often disconnected, disjointed, and stuck in an unsuccessful status quo. This is what New America's Cybersecurity Initiative is designed to address. Working across our International Security Program and the Open Technology Institute, we believe that it takes a wider network to face the multitude of diverse security issues. We engage across organizations, issue areas, professional fields, and business sectors. And through events, writing and research, our aim is to help improve cybersecurity in ways that work -for the countries, for companies and for individuals.

This study contributes a bathtub‐style inundation prediction model with abstractions of coastal processes (i.e., storm surge and wave runup) for flood forecasting at medium‐range (weekly to monthly) timescales along the coastline of large lakes. Uncertainty from multiple data sources are propagated through the model to establish probabilistic bounds of inundation, providing a conservative measure of risk. The model is developed in a case study of the New York Lake Ontario shoreline, which has experienced two record‐setting floods over the course of three years (2017–2019). Predictions are developed at a parcel‐level and are validated using inundation accounts from an online survey and flyover imagery taken during the recent flood events. Model predictions are compared against a baseline, deterministic model that accounts for the same processes but does not propagate forward data uncertainties. Results suggest that a probabilistic approach helps capture observed instances of inundation that would otherwise be missed by a deterministic inundation model. However, downward biases are still present in probabilistic predictions, especially for parcels impacted by wave runup. The goal of the tool is to provide community planners and property owners with a conservative, parcel‐level assessment of flood risk to help inform short‐term emergency response and better prepare for future flood events.