Actively Recruiting

Phase Not Applicable
Age: 20Years +
All Genders
NCT06685367

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

47 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

"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.

CONDITIONS

Official Title

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

Who Can Participate

Age: 20Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Over 20 years old
  • Admitted to adult ICU
  • Hospital stay expected to be more than 30 hours
Not Eligible

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
  • Have not provided informed consent
  • Considered unsuitable for the trial by the researcher

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 1 location

1

Taichung Veterans General Hospital (TCVGH)

Taichung, Taiwan

Actively Recruiting

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Research Team

C

Chun-Te Huang

CONTACT

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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