Acute Kidney Injury in Critically Ill Patients

Sponsor
Beijing Chao Yang Hospital
Study ID
NCT07653321
Status
Enrolling By Invitation

Conditions

  • Acute Kidney Injury

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Not applicable- observational study — OTHER
    Save the blood and urine samples

Study Details

Acute kidney injury (AKI) in critically ill patients is characterized by high incidence, delayed diagnosis and treatment, and high mortality. Early identification and precision management are key to improving prognosis. Currently, in China, the population with severe AKI faces prominent challenges, including a lack of standardized, localized specialized data, insufficient early warning and subtyping capabilities, and a shortage of high-quality evidence-based guidance for clinical decision-making. These issues constrain the application of artificial intelligence (AI) technologies in the precision diagnosis and treatment of AKI. Leveraging the Critical Care Medicine Specialty Alliance, which has been approved by the Beijing Hospital Management Center and consists of 19 tertiary hospital ICUs nationwide, this project will conduct a three-year prospective, observational registry study. The investigators plan to consecutively enroll 23,600 adult critically ill patients (with an anticipated \>3,000 AKI patients). The study will systematically collect clinical characteristics, time-series monitoring data, laboratory parameters, renal ultrasound imaging, biomarkers, and omics data, while concurrently retaining biological samples, to establish the largest multi-modal specialized disease dataset and biobank for severe AKI in China. Focusing on the entire AKI continuum of "early warning - diagnosis - phenotyping - treatment - prognosis," the study aims to: ① characterize the epidemiological features and disease burden of ICU-AKI in China; ② develop an early warning system for AKI; ③ identify AKI sub-phenotypes using machine learning and establish a precision management framework; ④ develop an intelligent decision support system for renal replacement therapy; ⑤ evaluate prognosis; and ⑥ promote medical-engineering collaborative translation. Expected outcomes include 3-5 early warning/prognostic models and one intelligent decision support system, along with applications for 3-5 invention patents and 2-3 software copyrights. The project aims to translate at least one outcome into practical application, provide high-level evidence-based support for developing national guidelines on severe AKI management tailored to China's context, and contribute to reducing the incidence and mortality of AKI.

Key Dates

First listed
Jun 17, 2026
Start date
May 1, 2026
Status verified
Jun 2026
Primary completion
May 1, 2029
Completion
May 1, 2029

Study Design

Enrollment
23,600 participants (estimated)

Primary Outcome Measure

Incidence of acute kidney injury during ICU admission [ Time Frame: During ICU admission, assessed up to 1 year ]

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