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

NCT ID: NCT06685367

Last Updated: 2024-11-12

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 3600 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-10-17
• Study Completion Date: 2025-09-15

Brief Summary

"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.

Conditions

Acute Kidney Injury; Intensive Care; Renal Replacement Therapy

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: SINGLE

Study Groups

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.

Group Type: EXPERIMENTAL

Acura AKI

Intervention Type: DEVICE

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

Without Acura AKI

The group without Acura AKI will be managed based on standard medical procedures.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

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

Intervention Type: DEVICE

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

• Minimum Eligible Age: 20 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Huede Healthtech Co., Ltd.

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Chun-Te Huang

Role: PRINCIPAL_INVESTIGATOR

Taichung Veterans General Hospital (TCVGH)

Locations

Taichung Veterans General Hospital (TCVGH)

Taichung, , Taiwan

Site Status: RECRUITING

Countries

Taiwan

Central Contacts

Chun-Te Huang

Role: CONTACT

huangchunte@gmail.com

+8864-23592525 ext. 3169

Facility Contacts

Chun-Te Huang

Role: primary

huangchunte@gmail.com

+8864-23592525 ext. 3169

Other Identifiers

Huede-113001

Identifier Type: -

Identifier Source: org_study_id