Acute Kidney Injury (AKI) is a common complication in hospitalized patients and is associated with increased morbidity and mortality. My objective is to transform the medical care of hospitalized patients at risk for the development of AKI through the utilization of an automated, real-time, electronic health record risk assessment score allowing for early standardized nephrology intervention. The current gold standards for AKI detection (serum creatinine (SCr) and urine output) are imperfect flawed biomarkers; they are neither sensitive nor specific for AKI and often do not change until 24 to 48 hours after the initial injury. This time-lag is often compounded by the fact that nephrologists are often not called until severe AKI is present (e.g. a tripling of SCr from baseline). At the University of Chicago (UofC) we have data demonstrating that on average ward- based consult for AKI occur on hospital day 4 after a 1.6 mg/dL increase in SCr from baseline with over 40% of patients already having Stage 2 or 3 AKI. Using a multi-center cohort we derived and validated an Electronic Health Record (EHR)-based AKI risk assessment model to predict the development of SCr based AKI in hospitalized patients using patient vital signs, labs and demographics (called Electronic Signal to Prevent AKI E-STOP-AKI). E-STOP-AKI, which is entirely derived from data freely available in the EHR, accurately predicts the future development of stage 3 AKI a median (IQR) of 35 (14-97) hours before any evidence of SCr-based AKI with an AUC of 0.83. We will combine the power of E-STOP-AKI with an intervention that has been repeatedly shown to improve patient outcomes across several clinical settings, nephrology consultation. Early nephrology consultation for AKI has been associated with improved patient outcomes, lower peak serum creatinine, less severe AKI, shorter length of hospital stay, increased renal recovery post-AKI and reduced morbidity /mortality. These same studies mirrors our data in that the average UofC nephrology consultation is not called until 2 days after there is clinical evidence of SCr ?based AKI and that 35-50% of AKI patients are not referred to nephrology until 5 days after their clinical diagnosis of AKI. As such we seek to combine these 2 tools, E-STOP-AKI and early standardized nephrology consultation in a randomized trial aimed to mitigate severe AKI in high risk patients. Patients at high risk for AKI, as measured by an elevated E-STOP-AKI score will be randomized to receive an early structured individualized nephrology consult which will explicitly comment on fundamental issues which have been shown to impact AKI severity and outcomes (Differential Diagnosis of AKI, nephrotoxins/ drug dosing and volume status /renal perfusion) versus usual care. We hypothesize that combining the precision medicine approach of E-STOP AKI with early standardized real-time individualized nephrology-centered care in ward patients will improve patient outcomes (as measured by lower peak SCr, less severe AKI, fewer ICU transfers, shorter LOS and less mortality). If this hypothesis is correct it will serve as a major paradigm shift in AKI consultative care, using an electronic risk assessment tool to bring the expert physician to the high-risk patient's bedside several days earlier than the current standard of care.

Public Health Relevance

We seek to determine if we can improve outcomes in hospitalized patients at high risk for acute kidney injury (AKI) through use of early standardized but individualized nephrology consultation. Using our recently developed automated, real-time AKI risk algorithm (called Electronic Signal to Prevent AKI E-STOP-AKI) we will identify patients at high risk for the development of severe AKI and then randomize subjects to receive either an early personalized yet structured renal consultation with a nephrologist versus usual care. The insight this randomized trial would provide into the utility of early standardized nephrology care on the inpatient and post-discharge patient outcomes will be very valuable, but this intervention may potentially change the nature of nephrology consultation, bringing the expert physician to bedside several days earlier than the current standard of care.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DK113420-02
Application #
9750719
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Schulman, Ivonne Hernandez
Project Start
2018-08-01
Project End
2020-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Chicago
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
005421136
City
Chicago
State
IL
Country
United States
Zip Code
60637