Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant

IMPORTANCE: Sepsis disproportionately affects recipients of allogeneic hematopoietic cell transplant (allo-HCT), and timely detection is crucial. However, the atypical presentation of sepsis within this population makes detection challenging, and existing clinical sepsis tools have limited prognosti...

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Detalles Bibliográficos
Autores principales: Lind, Margaret L., Mooney, Stephen J., Carone, Marco, Althouse, Benjamin M., Liu, Catherine, Evans, Laura E., Patel, Kevin, Vo, Phuong T., Pergam, Steven A., Phipps, Amanda I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056279/
https://www.ncbi.nlm.nih.gov/pubmed/33871619
http://dx.doi.org/10.1001/jamanetworkopen.2021.4514

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056279/
https://www.ncbi.nlm.nih.gov/pubmed/33871619
http://dx.doi.org/10.1001/jamanetworkopen.2021.4514

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