The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age20+
SponsorHuede Healthtech Co., Ltd.

About this trial

"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.

Eligibility criteria

Qualifiers

Over 20 years old

Admitted to adult ICU

Hospital stay of more than 30 hours

Disqualifiers

Known to have acute kidney injury at enrollment

Currently undergoing hemodialysis treatment

No available blood or urine test data

Pregnant women

Trial design

Treatments tested in this trial

  • Acura AKI

Treatment groups

3,600 Participants
are divided into 2 treatment groups

Sponsors and collaborators