Identifying Acute Kidney Injury Trajectory Phenotypes Associated with Hospital Mortality

Taylor D. Smith, Victor Ortiz-Soriano, Javier A. Neyra, Jin Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Acute kidney injury (AKI) is a complex systemic syndrome associated with high morbidity and mortality and risk for the subsequent development of kidney and non-kidney complications. Nearly 50% of patients in the intensive care unit (ICU) experience AKI. AKI severity is a key metric for evaluating patients risk of hospital mortality. Current AKI serum creatinine (SCr) stratification is based on absolute changes in Serum Creatinine (SCr) and the maximal increase relative to the patients baseline value. However, such characterization does not include either the progression or duration of AKI, both of which are associated with adverse outcomes. In this article, by leveraging a large volume of SCr temporal variabilities within the first 7 days of ICU stay, we propose a novel model called Trajectory of Acute Kidney Injury (TAKI) for the identification of AKI trajectory subtypes. Experimental results demonstrate that TAKI is a feasible method of AKI subtyping and superior to the current AKI KDIGO definition for the association with hospital mortality in this subset of critically ill patients.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Healthcare Informatics, ICHI 2019
ISBN (Electronic)9781538691380
DOIs
StatePublished - Jun 2019
Event7th IEEE International Conference on Healthcare Informatics, ICHI 2019 - Xi'an, China
Duration: Jun 10 2019Jun 13 2019

Publication series

Name2019 IEEE International Conference on Healthcare Informatics, ICHI 2019

Conference

Conference7th IEEE International Conference on Healthcare Informatics, ICHI 2019
Country/TerritoryChina
CityXi'an
Period6/10/196/13/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Acute Kidney Injury
  • Dynamic Trajectory Alignment
  • KDIGO Trajectory Subtyping

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Health Informatics
  • Biomedical Engineering

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