The Cost-effectiveness of Artificial Intelligence Acute Kidney Injury Prediction Auxiliary Software (Acura AKI)
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Acura AKI.
- Who it may be relevant to
- Registry conditions: Acute Kidney Injury, Intensive Care, Renal Replacement Therapy. Basic parameters: from 20 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Taiwan
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
"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.
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.
Interventions
- 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
Primary outcome measures
- Acute kidney injury (AKI) incidence [Time frame: Assessed from time of randomization to time of AKI occurrence (within 7 days post randomization)]
Secondary outcome measures (6)
- Percentage of recommendations implemented by the primary care team. [Time frame: 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)]
- Mortality rate [Time frame: 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]
- Change in treatment costs [Time frame: 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]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Single blind
- Primary purpose
- Prevention
Study locations
Taiwan · 1 center
- Taichung Veterans General Hospital (TCVGH) — Taichung
Identifiers
NCT: NCT06685367 · Huede-113001