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Current Problems in Cardiology ; 48(1), 2023.
Article in English | Scopus | ID: covidwho-2239181


In the COVID-19 pandemic, to minimize aerosol-generating procedures, cardiac magnetic resonance imaging (CMR) was utilized at our institution as an alternative to transesophageal echocardiography (TEE) for diagnosing infective endocarditis (IE). This retrospective study evaluated the clinical utility of CMR for detecting IE among 14 patients growing typical microorganisms on blood cultures or meeting modified Duke Criteria. Seven cases were treated for IE. In 2 cases, CMR results were notable for possible leaflet vegetations and were clinically meaningful in guiding antibiotic therapy, obtaining further imaging, and/or pursuing surgical intervention. In 2 cases, vegetations were missed on CMR but detected on TEE. In 3 cases, CMR was non-diagnostic, but patients were treated empirically. There was no difference in antibiotic duration or outcomes over 1 year. CMR demonstrated mixed results in diagnosing valvular vegetations and guiding clinical decision-making. Further prospective controlled trials of CMR Vs TEE are warranted. © 2022 Elsevier Inc.

American Journal of Respiratory and Critical Care Medicine ; 205:2, 2022.
Article in English | English Web of Science | ID: covidwho-1880009
Infosys Science Foundation Series in Mathematical Sciences ; : 329-355, 2021.
Article in English | Scopus | ID: covidwho-1491037


In this paper, we discuss impact of the Covid-19 pandemic on the North American financial markets and propose a framework for stress testing and financial scenario generation of market indicators. This framework includes the following main components: Epidemiological dynamic model describing evolution of the number of Susceptible, Infected, Recovered and Death cases with social distancing,Dynamical model describing dependence between financial indicators and growth of the pandemic in different geographical areas,Conditional stress scenario generation and financial portfolio analysis. We apply an extended epidemiological model to analysis of Covid-19 pandemic spread and analyze its impact on some of the main financial indicators, including stock indices, credit spreads and FX rates, and characteristics of the pandemic process in different geographical areas. This analysis results in a model connecting the dynamics of the pandemic and that of the main financial indicators. The model allows one to generate pandemic scenarios under different assumptions on the parameters of the infectious disease and that of the social distancing policies. Once the pandemic scenarios are generated, one can transform them into a set of scenarios on macro-economic risk factors. Then, applying the conditional scenario technique we obtain a set of Monte Carlo scenarios on the risk factors driving the portfolio dynamics. The proposed dynamic models allow one to generate various financial stress scenarios on market indicators and compute the distribution of financial portfolio losses and their risk measures. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.