Predicting neurological outcomes after in-hospital cardiac arrests for patients with Coronavirus Disease 2019

BACKGROUND: Machine learning models are more accurate than standard tools for predicting neurological outcomes in patients resuscitated after cardiac arrest. However, their accuracy in patients with Coronavirus Disease 2019 (COVID-19) is unknown. Therefore, we compared their performance in a cohort...

Descripción completa

Detalles Bibliográficos
Autores principales: Mayampurath, Anoop, Bashiri, Fereshteh, Hagopian, Raffi, Venable, Laura, Carey, Kyle, Edelson, Dana, Churpek, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295318/
https://www.ncbi.nlm.nih.gov/pubmed/35868590
http://dx.doi.org/10.1016/j.resuscitation.2022.07.018

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295318/
https://www.ncbi.nlm.nih.gov/pubmed/35868590
http://dx.doi.org/10.1016/j.resuscitation.2022.07.018

Ejemplares similares