A Multifaceted Approach to AKI Intervention

Session Description:
This session will cover the several aspects around the detection and care of patients at risk and diagnosed with AKI. While the traditional, consensus definition of AKI involves measurement of serum creatinine and urine output however increasingly in both high and low resources settings new methods to assess AKI have been used. This session will cover the use of machine learning risk scores as well as other point of care devices (e.g. point of care creatinine and salivary urea nitrogen)  to detect AKI. Additionally, we will discuss the use of other point of care devices that can help in the assessment and care of AKI patients (e.g. point of care ultrasound (POCUS)). Lastly this session will discuss the clinical utility of AKI care bundles and the mixed results that have been reported when these multifaceted bundles have been studied in randomized controlled trials.

Learning Objectives:
To increase understanding of what artificial intelligence is and how it has been used in the settings of AKI. To develop an appreciation for the variety of point of care tools which can help providers to diagnose and manage patients with AKI. To summarize conflicting data around the use of care bundles in the setting of inpatient AKI.