The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
"Huede" AI Aided AKI Prediction Software, Acura AKI, uses machine learning algorithms to predict the risk of AKI within the next 24 hours. It has undergone cross-hospital validation at four medical centers in Taiwan (Taichung Veterans General Hospital, Mackay Memorial Hospital, National Cheng Kung University Hospital, and Kaohsiung Medical University Hospital), successfully obtaining invention patents in Taiwan and the United States, as well as receiving a software medical device license from the Taiwan Food and Drug Administration. Acura AKI is installed on the hospital's servers, where it processes patient physiological data, laboratory parameters, and medication information to infer the risk of AKI occurring within 24 hours. It also provides 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. In the intervention group with Acura AKI system, physicians will be proactively notified via sending alarm message when Acura AKI identifies a high-risk patient population. After receiving alarm message, physicians and pharmacists will provide feedback and recommendations, including blood pressure, fluid management, infusion options, medication adjustment suggestions, and dialysis recommendations. 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. Additionally, the researchers will collect 20ml of urine from Acura AKI identified patients to test for urinary biomarkers predictive of AKI then verify the performance of Acura AKI with these urinary biomarkers. 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.
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Chun-Te Huang
- Phone Number: 3169 +8864-23592525
- Email: huangchunte@gmail.com
Study Locations
-
-
-
Taichung, Taiwan
- Recruiting
- Taichung Veterans General Hospital (TCVGH)
-
Contact:
- Chun-Te Huang
- Phone Number: 3169 +8864-23592525
- Email: huangchunte@gmail.com
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Over 20 years old
- Admitted to adult ICU
- Hospital stay of more than 30 hours
Exclusion Criteria:
- 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
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Prevention
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: With Acura AKI
The group with Acura AKI will receive the Acura AKI software, which identifies high-risk AKI patients and sends alert messages to nephrologists and ICU pharmacists.
Upon receiving the alert, they will make treatment suggestions.
|
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
|
|
No Intervention: Without Acura AKI
The group without Acura AKI will be managed based on standard medical procedures.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Acute kidney injury (AKI) incidence
Time Frame: Assessed from time of randomization to time of AKI occurrence (within 7 days post randomization)
|
Acute kidney injury (AKI) incidence in ICU.
AKI is defined by an increase in KDIGO creatinine stage.
|
Assessed from time of randomization to time of AKI occurrence (within 7 days post randomization)
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Percentage of recommendations implemented by the primary care team.
Time Frame: 24 hours after Randomization
|
Upon receiving the alert message from the AI algorithm (Acura AKI), nephrologists and ICU pharmacists 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
|
24 hours after Randomization
|
|
Dialysis rate
Time Frame: Assessed from time of randomization to time of receipt of inpatient dialysis (within 14 days post randomization)
|
Dialysis is defined by the receipt of hemodialysis, continuous renal replacement therapy or peritoneal dialysis.
Isolated ultrafiltration treatments (for the purpose of volume removal) will not be included.
|
Assessed from time of randomization to time of receipt of inpatient dialysis (within 14 days post randomization)
|
|
Mortality rate
Time Frame: Assessed from time of randomization to date of death from any cause, within 14 days of randomization
|
Mortality will be determined from hospital administrative records
|
Assessed from time of randomization to date of death from any cause, within 14 days of randomization
|
|
Length of hospital stay
Time Frame: Assessed from time of randomization to date of hospital discharge, assessed up to 30 days
|
The total days of hospitalization stay
|
Assessed from time of randomization to date of hospital discharge, assessed up to 30 days
|
|
Change in treatment costs
Time Frame: Assessed from time of randomization to 60 days post hospital discharge date, accessed up to 90 days
|
|
Assessed from time of randomization to 60 days post hospital discharge date, accessed up to 90 days
|
|
Long term dialysis
Time Frame: From hospital discharge date up to 90 days post discharge date
|
Receive regular dialysis
|
From hospital discharge date up to 90 days post discharge date
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Chun-Te Huang, Taichung Veterans General Hospital (TCVGH)
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimated)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- Huede-113001
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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