A clinical, proteomics, and artificial intelligence‐driven model to predict acute kidney injury in patients undergoing coronary angiography

BACKGROUND: Standard measures of kidney function are only modestly useful for accurate prediction of risk for acute kidney injury (AKI). HYPOTHESIS: Clinical and biomarker data can predict AKI more accurately. METHODS: Using Luminex xMAP technology, we measured 109 biomarkers in blood from 889 patie...

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Detalles Bibliográficos
Autores principales: Ibrahim, Nasrien E., McCarthy, Cian P., Shrestha, Shreya, Gaggin, Hanna K., Mukai, Renata, Magaret, Craig A., Rhyne, Rhonda F., Januzzi, James L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wiley Periodicals, Inc. 2019
Materias:
Clinical Investigations
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6712314/
https://www.ncbi.nlm.nih.gov/pubmed/30582197
http://dx.doi.org/10.1002/clc.23143

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6712314/
https://www.ncbi.nlm.nih.gov/pubmed/30582197
http://dx.doi.org/10.1002/clc.23143

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