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Machine learning derivation of four computable 24-h pediatric sepsis phenotypes to facilitate enrollment in early personalized anti-inflammatory clinical trials
BACKGROUND: Thrombotic microangiopathy-induced thrombocytopenia-associated multiple organ failure and hyperinflammatory macrophage activation syndrome are important causes of late pediatric sepsis mortality that are often missed or have delayed diagnosis. The National Institutes of General Medical S...
Autores principales: | Qin, Yidi, Kernan, Kate F., Fan, Zhenjiang, Park, Hyun-Jung, Kim, Soyeon, Canna, Scott W., Kellum, John A., Berg, Robert A., Wessel, David, Pollack, Murray M., Meert, Kathleen, Hall, Mark, Newth, Christopher, Lin, John C., Doctor, Allan, Shanley, Tom, Cornell, Tim, Harrison, Rick E., Zuppa, Athena F., Banks, Russell, Reeder, Ron W., Holubkov, Richard, Notterman, Daniel A., Michael Dean, J., Carcillo, Joseph A. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077858/ https://www.ncbi.nlm.nih.gov/pubmed/35526000 http://dx.doi.org/10.1186/s13054-022-03977-3 |
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