Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality

Autor: Yvan Devaux, Lu Zhang, Andrew I. Lumley, Kanita Karaduzovic-Hadziabdic, Vincent Mooser, Simon Rousseau, Muhammad Shoaib, Venkata Satagopam, Muhamed Adilovic, Prashant Kumar Srivastava, Costanza Emanueli, Fabio Martelli, Simona Greco, Lina Badimon, Teresa Padro, Mitja Lustrek, Markus Scholz, Maciej Rosolowski, Marko Jordan, Timo Brandenburger, Bettina Benczik, Bence Agg, Peter Ferdinandy, Jörg Janne Vehreschild, Bettina Lorenz-Depiereux, Marcus Dörr, Oliver Witzke, Gabriel Sanchez, Seval Kul, Andy H. Baker, Guy Fagherazzi, Markus Ollert, Ryan Wereski, Nicholas L. Mills, Hüseyin Firat

Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)

Abstract Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-h

Externí odkaz: https://doaj.org/article/54234423656547d89b595a58c9921da7

Adjudicated myocarditis and multisystem illness trajectory in healthcare workers post-COVID-19

Autor: Kevin G Blyth, Naveed Sattar, Colin Berry, David Corcoran, Kenneth Mangion, Alex McConnachie, David Carrick, Stuart Watkins, Paul Welsh, Sabrina Nordin, Ross McGeoch, Rhian Touyz, David J Lowe, Andrew J Morrow, Antonia Ho, Ryan Wereski, Alasdair McIntosh, Giles H Roditi, Peter MacFarlane, David B Stobo, Robert Sykes, Colin Church, Nicola Ryan, N N Lang, C Delles, Iain Findlay, Michael Briscoe, Gruschen Veldtman, Heeraj Bulluck, Patrick Mark, Vera Lennie, Alexander Payne, Keith E Robertson, Anna Kamdar, C Bagot, Hannah Bayes, Vivienne B Gibson, Lynsey Gillespie, Douglas Grieve, Pauline Hall Barrientos, Kaithlin J Mayne, Christopher McGinley, Connor Mckee, Alastair Rankin, Sarah Allwood-Spiers, Sarah Weeden

Publikováno v: Open Heart, Vol 10, Iss 1 (2023)

Background We investigated the associations of healthcare worker status with multisystem illness trajectory in hospitalised post-COVID-19 individuals.Methods and results One hundred and sixty-eight patients were evaluated 28–60 days after the last

Externí odkaz: https://doaj.org/article/2803299856a24ddab07adfd0640b2cc8

Improving Risk Stratification for Patients with Type 2 Myocardial Infarction

Autor: Caelan Taggart, Karla Monterrubio-Gómez, Andreas Roos, Jasper Boeddinghaus, Dorien M. Kimenai, Erik Kadesjo, Anda Bularga, Ryan Wereski, Amy Ferry, Matthew Lowry, Atul Anand, Kuan Ken Lee, Dimitrios Doudesis, Ioanna Manolopoulou, Thomas Nestelberger, Luca Koechlin, Pedro Lopez-Ayala, Christian Mueller, Nicholas L. Mills, Catalina A. Vallejos, Andrew R. Chapman

Publikováno v: Taggart, C, Monterrubio-Gomez, K, Roos, A, Boeddinghaus, J, Kimenai, D, Kadesjo, E, Bularga, A, Wereski, R, Ferry, A, Lowry, M, Anand, A, Lee, K K, Doudesis, D, Manolopoulou, I, Nestelberger, T, Koechlin, L, Lopez-Ayala, P, Mueller, C, Mills, N L, Vallejos, C A & Chapman, A R 2023, ' Improving Risk Stratification for Patients with Type 2 Myocardial Infarction ', Journal of the American College of Cardiology, vol. 81, no. 2, pp. 156-168 . https://doi.org/10.1016/j.jacc.2022.10.025

BackgroundDespite poor cardiovascular outcomes, there are no dedicated, validated risk stratification tools to guide investigation or treatment in type 2 myocardial infarction.ObjectivesThe goal of this study was to derive and validate a risk stratif

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c321fbdbb80cf93ba97e2a516cdff9a5
https://hdl.handle.net/20.500.11820/b6b78c02-5669-4cb3-8304-4f9574947ed7

Distinguishing Type 1 from Type 2 Myocardial Infarction Using CT Coronary Angiography

Autor: Mohammed N. Meah, Anda Bularga, Evangelos Tzolos, Andrew R. Chapman, Marwa Daghem, John D. Hung, Justin Chiong, Caelan Taggart, Ryan Wereski, Alasdair Gray, Marc R. Dweck, Carl Roobottom, Nick Curzen, Attila Kardos, Dirk Felmeden, Nicholas L. Mills, Piotr J. Slomka, David E. Newby, Damini Dey, Michelle C. Williams

Publikováno v: Meah, M, Bularga, A, Tzolos, E, Chapman, A R, Daghem, M, Hung, J, Chiong, J, Taggart, C, Wereski, R, Gray, A, Dweck, M R, Roobottom, C, Curzen, N, Kardos, A, Felmeden, D, Mills, N L, Slomka, P J, Newby, D E, Dey, D & Williams, M C 2022, ' Distinguishing Type 1 from Type 2 Myocardial Infarction Using CT Coronary Angiography ', Radiology: Cardiothoracic Imaging . https://doi.org/10.1148/ryct.220081
Radiol Cardiothorac Imaging

PURPOSE: To determine whether quantitative plaque characterization by using CT coronary angiography (CTCA) can discriminate between type 1 and type 2 myocardial infarction. MATERIALS AND METHODS: This was a secondary analysis of two prospective studi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d04947bcc8246f4f22093a9922b2520
https://www.pure.ed.ac.uk/ws/files/305365346/Full_Title_Page_RADIOLOGY_CVI.docx

Cardiac Troponin Thresholds and Kinetics to Differentiate Myocardial Injury and Myocardial Infarction

Autor: Dimitrios Doudesis, Andrew R. Chapman, Dorien M Kimenai, Ryan Wereski, Takeshi Fujisawa, Paul O. Collinson, Fred S. Apple, David J Lowe, Caelan Taggart, Kuan Ken Lee, Anda Bularga, Atul Anand, Matthew T H Lowry, Nicholas L. Mills

Publikováno v: Circulation
Wereski, R, Kimenai, D, Taggart, C, Doudesis, D, Lee, K K, Lowry, M, Bularga, A, Lowe, D J, Fujisawa, T, Apple, F S, Collinson, P O, Anand, A, Chapman, A R & Mills, N L 2021, ' Cardiac troponin thresholds and kinetics to differentiate myocardial injury and myocardial infarction ', Circulation . https://doi.org/10.1161/CIRCULATIONAHA.121.054302

Supplemental Digital Content is available in the text.
Background: Although the 99th percentile is the recommended diagnostic threshold for myocardial infarction, some guidelines also advocate the use of higher troponin thresholds to rule in myo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c29a566d9fc66d605a26c0aa4c16ccd
https://doi.org/10.1161/circulationaha.121.054302