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ID06685367

Evaluating the Cost-effectiveness of Artificial Intelligence Software Acura AKI for Early Prediction and Intervention of Acute Kidney Injury in Adult Intensive Care Units

Led by Huede Healthtech Co., Ltd. · Updated on 2024-11-12

3600

Participants Needed

1

Research Sites

N/A

Total Duration

AI-Summary

What this Trial Is About

This research aims to evaluate the use of Huede AI Aided AKI Prediction Software, called Acura AKI, which uses machine learning to predict the risk of acute kidney injury AKI within the next 24 hours in adult intensive care unit ICU patients. The study is a prospective randomized clinical trial designed to assess whether early prediction and intervention with Acura AKI can improve outcomes for critically ill patients with kidney problems. The main goal is to determine the cost-effectiveness of using this AI software by looking at AKI incidence, dialysis rates, mortality, hospital stay length, and treatment costs. Participants are divided into two groups one using the Acura AKI system and the other receiving standard care. In the Acura AKI group, the software identifies high-risk patients and sends alerts to nephrologists and ICU pharmacists, who then review patient records and suggest treatments such as blood pressure management, fluid control, medication adjustments, and dialysis recommendations. Additionally, 20ml urine samples will be collected from patients identified by Acura AKI to test urinary biomarkers for AKI prediction. The control group will be managed per usual medical procedures. Throughout the study, patients will be monitored for the occurrence of AKI within 7 days of randomization, dialysis needs within 14 days, mortality within 14 days, length of hospital stay up to 30 days, and treatment costs up to 90 days after hospital discharge. The study also tracks the percentage of treatment recommendations implemented and long-term dialysis use up to 90 days post-discharge. Physicians and pharmacists provide ongoing feedback based on alerts, and patient data including lab tests and medications are used for risk assessment and outcome measurement.

CONDITIONS

Brief Title

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

Research Team

C

Chun-Te Huang

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