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

Recruiting now · Not applicable

Conditions studied: Acute Kidney Injury, Intensive Care, Renal Replacement Therapy

In brief

"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 facts

Study ID

NCT06685367

Run by

Huede Healthtech Co., Ltd.

People needed

3600

Starts

2024-10-17

Expected to finish

2025-09-15

Last updated by the study team

2024-11-12

Who can join

Age: 20 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Over 20 years old
• Admitted to adult ICU
• Hospital stay of more than 30 hours

You may not qualify if…

• Known to have acute kidney injury at enrollment
• Currently undergoing hemodialysis treatment
• No available blood or urine test data
• Pregnant women
• HIV-positive patients
• Those who have not provided informed consent form
• Regarded as unsuitable for inclusion in the trial by the researcher

Where it is running

• Taichung Veterans General Hospital (TCVGH) — Taichung, Taiwan (enrolling)

Full record on ClinicalTrials.gov

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