A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients

Abstract The COVID-19 pandemic has challenged front-line clinical decision-making, leading to numerous published prognostic tools. However, few models have been prospectively validated and none report implementation in practice. Here, we use 3345 retrospective and 474 prospective hospitalizations to...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Narges Razavian, Vincent J. Major, Mukund Sudarshan, Jesse Burk-Rafel, Peter Stella, Hardev Randhawa, Seda Bilaloglu, Ji Chen, Vuthy Nguy, Walter Wang, Hao Zhang, Ilan Reinstein, David Kudlowitz, Cameron Zenger, Meng Cao, Ruina Zhang, Siddhant Dogra, Keerthi B. Harish, Brian Bosworth, Fritz Francois, Leora I. Horwitz, Rajesh Ranganath, Jonathan Austrian, Yindalon Aphinyanaphongs
Format: article
Langue:EN
Publié: Nature Portfolio 2020
Sujets:
Computer applications to medicine. Medical informatics
R858-859.7
Accès en ligne:https://doaj.org/article/24a1e6844b2b4deb962b0c15b73995db
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Internet

https://doaj.org/article/24a1e6844b2b4deb962b0c15b73995db

Documents similaires