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The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)
Sponsor: Huede Healthtech Co., Ltd.
Summary
"Huede" AI Aided AKI Prediction Software, Acura AKI, uses machine learning algorithms to predict the risk of AKI within the next 24 hours and provide a ranking of feature importance. By using Acura AKI, physicians can assess the risk of AKI, focusing on high-risk patients to provide care decisions. This study will be conducted in a prospective randomized clinical trial in adult ICUs, implementing the Acura AKI system for predicting AKI. The study aims to determine whether early prediction and intervention using the Acura AKI system can improve the outcomes of critically ill patients with adverse kidney conditions. The study endpoint is to evaluate the cost-effectiveness of using Acura AKI, including the incidence of AKI, dialysis rates, mortality rates, length of hospital stay, and treatment costs.
Key Details
Gender
All
Age Range
20 Years - Any
Study Type
INTERVENTIONAL
Enrollment
3600
Start Date
2024-10-17
Completion Date
2025-09-15
Last Updated
2024-11-12
Healthy Volunteers
No
Interventions
Acura AKI
When the AI algorithm (Acura AKI) identifies a high-risk AKI patient, nephrologists and ICU pharmacists will receive an alert message. Upon receiving the alert, they will review the patient's electronic health record and make treatment suggestions based on AKI bundle care protocols. They will also coordinate with the patient's primary care team to ensure that the recommendations are implemented
Locations (1)
Taichung Veterans General Hospital (TCVGH)
Taichung, Taiwan