A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children

BACKGROUND: Timely prediction of AKI in children can allow for targeted interventions, but the wealth of data in the electronic health record poses unique modeling challenges. METHODS: We retrospectively reviewed the electronic medical records of all children younger than 18 years old who had at lea...

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Detalhes bibliográficos
Publicado no:J Am Soc Nephrol
Main Authors: Sandokji, Ibrahim, Yamamoto, Yu, Biswas, Aditya, Arora, Tanima, Ugwuowo, Ugochukwu, Simonov, Michael, Saran, Ishan, Martin, Melissa, Testani, Jeffrey M., Mansour, Sherry, Moledina, Dennis G., Greenberg, Jason H., Wilson, F. Perry
Formato: Artigo
Idioma:Inglês
Publicado em: American Society of Nephrology 2020
Assuntos:
Clinical Research
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7269342/
https://ncbi.nlm.nih.gov/pubmed/32381598
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1681/ASN.2019070745
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