Latent variable modeling improves AKI risk factor identification and AKI prediction compared to traditional methods

BACKGROUND: Acute kidney injury (AKI) is diagnosed based on postoperative serum creatinine change, but AKI models have not consistently performed well, in part due to the omission of clinically important but practically unmeasurable variables that affect creatinine. We hypothesized that a latent var...

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Bibliographic Details
Published in:BMC Nephrol
Main Authors: Smith, Loren E., Smith, Derek K., Blume, Jeffrey D., Siew, Edward D., Billings, Frederic T.
Format: Artigo
Language:Inglês
Published: BioMed Central 2017
Subjects:
Research Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC5299779/
https://ncbi.nlm.nih.gov/pubmed/28178929
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12882-017-0465-1
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