Výsledky vyhledávání - "Grady Barnes"

Akademický článek

Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease

Autor: Cian P. McCarthy, Johannes T. Neumann, Sam A. Michelhaugh, Nasrien E. Ibrahim, Hanna K. Gaggin, Nils A. Sörensen, Sarina Schäefer, Tanja Zeller, Craig A. Magaret, Grady Barnes, Rhonda F. Rhyne, Dirk Westermann, James L. Januzzi

Publikováno v: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 9, Iss 16 (2020)

Background Current noninvasive modalities to diagnose coronary artery disease (CAD) have several limitations. We sought to derive and externally validate a hs‐cTn (high‐sensitivity cardiac troponin)–based proteomic model to diagnose obstructive

Externí odkaz: https://doaj.org/article/f2baa752ba934595b750d6242d5e7a88

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Akademický článek

Performance of a clinical/proteomic panel to predict obstructive peripheral artery disease in patients with and without diabetes mellitus

Autor: Nasrien Ibrahim, Renata Mukai, Craig Magaret, Rhonda Rhyne, Grady Barnes, Roland R J van Kimmenade, James L Januzzi, Cian P McCarthy, Shreya Shrestha, Hanna K Gaggin, Joseph M Garasic

Publikováno v: Open Heart, Vol 6, Iss 1 (2019)

Background Patients with diabetes mellitus (DM) are at substantial risk of developing peripheral artery disease (PAD). We recently developed a clinical/proteomic panel to predict obstructive PAD. In this study, we compare the accuracy of this panel f

Externí odkaz: https://doaj.org/article/861a872d49294482b830b4a7d9b1a352

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An Artificial Intelligence Derived Blood Test to Diagnose Kawasaki Disease

Autor: Michael A. Portman, Craig A. Magaret, Grady Barnes, Celine Peters, Aparna Rao, Rhonda Rhyne

Publikováno v: Hospital Pediatrics. 13:201-210

OBJECTIVETo develop a highly sensitive and specific blood biomarker panel that identifies febrile children with Kawasaki disease (KD).METHODSWe tested blood samples from a single-center cohort of KD (n = 50) and control febrile children (n = 100) to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e78f303d5e697df8efbd14a5edac2ce5
https://doi.org/10.1542/hpeds.2022-006868

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A pooled multi-national validation study of a machine learning, high-sensitivity troponin-based multi-proteomic model to predict the presence of obstructive coronary artery disease

Autor: Johannes T Neumann, Rhonda F. Rhyne, Christopher DeFilippi, Cian P. McCarthy, Craig A. Magaret, James L. Januzzi, Dirk Westermann, Grady Barnes, N A Sorenson, Celine Peters

Publikováno v: European Heart Journal. 42

Background Undetected obstructive coronary artery disease (oCAD) is a global health problem associated with significant morbidity and mortality. A need exists for an accurate and easily accessible diagnostic test for oCAD. Using machine learning, a m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4592cb12026af5499709a2c8a9c06c63
https://doi.org/10.1093/eurheartj/ehab724.1374

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Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease

Autor: Sarina Schaefer, James L. Januzzi, Rhonda F. Rhyne, Dirk Westermann, Craig A. Magaret, Johannes T Neumann, Grady Barnes, Sam A. Michelhaugh, Cian P. McCarthy, Hanna K. Gaggin, Tanja Zeller, Nasrien E. Ibrahim, Nils A Sörensen

Publikováno v: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ca1d000c760e0e7b8d4fe089bb77949
https://doi.org/10.1161/jaha.120.017221

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Application of a machine learning-driven, multibiomarker panel for prediction of incident cardiovascular events in patients with suspected myocardial infarction

Autor: Craig A. Magaret, James L. Januzzi, Johannes T Neumann, Celine Peters, Alina Goßling, Tanja Zeller, Dirk Westermann, Grady Barnes, Rhonda F. Rhyne, Paul M Haller, Sarina Schäfer, Tau S Hartikainen, Jonas Lehmacher, Nils A Sörensen

Publikováno v: Biomarkers in medicine. 14(9)

Background: In patients with suspected myocardial infarction (MI), we sought to validate a machine learning-driven, multibiomarker panel for prediction of incident major adverse cardiovascular events (MACE). Methodology & results: A previously descri

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ba55dd961e1ae0d7ca18eb6da7be406
https://pubmed.ncbi.nlm.nih.gov/32462911

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Performance of a clinical/proteomic panel to predict obstructive peripheral artery disease in patients with and without diabetes mellitus

Autor: Joseph M. Garasic, Shreya Shrestha, Cian P. McCarthy, Nasrien E. Ibrahim, Roland R.J. van Kimmenade, James L. Januzzi, Renata Mukai, Rhonda F. Rhyne, Craig A. Magaret, Grady Barnes, Hanna K. Gaggin

Publikováno v: Open Heart, 6, e000955
Open Heart, 6, 1, pp. e000955
Open Heart

BackgroundPatients with diabetes mellitus (DM) are at substantial risk of developing peripheral artery disease (PAD). We recently developed a clinical/proteomic panel to predict obstructive PAD. In this study, we compare the accuracy of this panel fo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::989fc76f1731d4cf3b8a719f6367e060
http://hdl.handle.net/2066/209487

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