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

November 10, 2024 updated by: Huede Healthtech Co., Ltd.
"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.

Study Overview

Status

Recruiting

Conditions

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

Interventional

Enrollment (Estimated)

3600

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Taiwan
      • Taichung, Taiwan
        • Recruiting
        • Taichung Veterans General Hospital (TCVGH)
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

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

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / 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.
Device: Acura AKI
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

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

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
  1. Hospital Services [Room and board (inpatient stays), Intensive care unit (ICU) fees, Emergency department charges, Operating room fees, and Recovery room fees]
  2. Professional Fees [Physician services (e.g., consultations, surgery, anesthesia), Nursing services, and Therapist services (physical, occupational, respiratory)]
  3. Diagnostic Services [Laboratory tests (blood tests, urine tests), Imaging studies (X-rays, MRI, CT scans), Biopsies, Electrocardiograms (EKGs), and Other diagnostic procedures]
  4. Medication and Pharmacy [Prescription drugs, Intravenous medications, and Anesthesia drugs]
  5. Medical Supplies and Equipment [Surgical supplies, Disposable supplies (syringes, bandages), and Prosthetics and orthotics]
  6. Rehabilitation Services [Physical therapy, Occupational therapy, Speech therapy, Cardiac rehabilitation]
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

This is where you will find people and organizations involved with this study.

Sponsor

Huede Healthtech Co., Ltd.

Investigators

  • Principal Investigator: Chun-Te Huang, Taichung Veterans General Hospital (TCVGH)

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 17, 2024

Primary Completion (Estimated)

September 15, 2025

Study Completion (Estimated)

September 15, 2025

Study Registration Dates

First Submitted

October 11, 2024

First Submitted That Met QC Criteria

November 10, 2024

First Posted (Estimated)

November 12, 2024

Study Record Updates

Last Update Posted (Estimated)

November 12, 2024

Last Update Submitted That Met QC Criteria

November 10, 2024

Last Verified

November 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Huede-113001

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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