Shelby Kutty, director of pediatric and congenital cardiology and Helen B. Taussig professor, discusses the latest National Institutes of Health grants received for research at Johns Hopkins. Areas of research supported by the three grants range from investigation of personalized prediction of cardiovascular disease clinical outcomes clinical outcomes of cardiovascular disease using personalized prediction to management of long COVID by a clinical decision support system.
Hello everyone. I'm dr Shelby Cuddy. I'm the Helen Taussig professor and director of pediatric and congenital cardiology at johNS Hopkins, I'll be talking about three data science grand award from the NIH we received in the last quarter of 2022. The first grant is to investigate clinical outcomes of cardiovascular disease with the use of a personalized predictive medicine approach. The current paradigm is to treat most patients according to standard clinical guidelines where all patients with a similar condition receive substantially similar treatment. This is different from personalized approaches that use prediction models to assign treatment. Our aim is to quantify the potential benefits of using a personalized approach by computational simulating the outcomes of predictive allocation in data from 130 previously published NIH randomized controlled trials comparing outcomes in a simulated environment. Our goal is to determine whether predictive allocation would result in a net benefit at the population level. The second grand we received was a sub award as participant in the national consortium of centers as part of a large NIH research initiative. This collaborative long term study of outcomes of COVID-19 and kids or the clock consortium will investigate the post acute secretary of Covid 19 commonly referred to as long covid Data collected as part of this study will include clinical information, lab tests and imaging analysis of patients from ages newborn to 25 years in various stages of recovery following COVID infection. The study will characterize the clinical course and recovery over time and determine risk factors mechanisms and potential modifiers for post acute sequelae of COVID-19. Finally, the third grand is a Phase two grand in which we are designing and validating a predictive decision support system for the management of Covid 19 associated multi system inflammatory syndrome and Children missy. Two years ago in the Phase one of the study performed in collaboration with the international Kawasaki disease registry. We had adapted and re trained machine learning algorithms. In Phase two of the study, these algorithms will be packaged in their clinical decision support system and deployed at six study sites. This is for the prospective evaluation of the performance and clinical utility of the algorithms ahead of their large scale deployment. Thank you for attending to our studies.
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