Actively Recruiting
The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)
Led by Huede Healthtech Co., Ltd. · Updated on 2024-11-12
3600
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
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)
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Over 20 years old
- Admitted to adult ICU
- Hospital stay of more than 30 hours
You will not qualify if you...
- 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
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Up to 14 days from randomization
Participants in the intervention group will have the Acura AKI software installed on hospital servers to predict acute kidney injury risk within 24 hours. Alerts are sent to nephrologists and ICU pharmacists to guide treatment suggestions based on the predictions.
Continuous monitoring during ICU stay
Duration - Up to 30 days from randomization
Participants are monitored for acute kidney injury incidence, dialysis needs, mortality, and hospital stay length after randomization.
Ongoing assessments during hospital stay
Duration - Up to 90 days post discharge
Participants are followed for treatment costs and long-term dialysis outcomes following hospital discharge.
Follow-up visits or assessments up to 90 days after hospital discharge
Trial Site Locations
Total: 1 location
1
Taichung Veterans General Hospital (TCVGH)
Taichung, Taiwan
Actively Recruiting
Research Team
C
Chun-Te Huang
How is the study designed?
Study Type
INTERVENTIONAL
Masking
SINGLE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
PREVENTION
Number of Arms
2
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