Predicting Major Adverse Kidney Events among Critically Ill Adults Using the Electronic Health Record.

ABSTRACT: Prediction of major adverse kidney events in critically ill patients may help target therapy, allow risk adjustment, and facilitate the conduct of clinical trials. In a cohort comprised of all critically ill adults admitted to five intensive care units at a single tertiary care center over one year, we developed a logistic regression model for the outcome of Major Adverse Kidney Events within 30 days (MAKE30), the composite of persistent renal dysfunction, new renal replacement therapy (RRT), and in-hospital mortality. Proposed risk factors for the MAKE30 outcome were selected a priori and included age, race, gender, University Health System Consortium (UHC) expected mortality, baseline creatinine, volume of isotonic crystalloid fluid received in the prior 24 h, admission service, intensiv

SUBMITTER: McKown AC 

PROVIDER: S-EPMC5821255 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature