Development and Validation of a Real-time Prediction Model for Acute Kidney Injury in Hospitalized Patients

September 12, 2024 updated by: Li Yang, Peking University First Hospital
Early prediction of acute kidney injury (AKI) may provide a crucial opportunity for AKI prevention. To date, no prediction model targeting AKI among general hospitalized patients in developing countries has been published. We developed a simple, real-time, interpretable AKI prediction model for general hospitalized patients from a large tertiary hospital in China, and validated it across five independent, geographically distinct, different tiered hospitals.

Study Overview

Status

Recruiting

Conditions

Detailed Description

Early prediction of acute kidney injury (AKI) may provide a crucial opportunity for AKI prevention. To date, no prediction model targeting AKI among general hospitalized patients in developing countries has been published. We developed a simple, real-time, interpretable AKI prediction model for general hospitalized patients from a large tertiary hospital in China using the machine learning technique, and then validated the performance of the prediction model across five independent, geographically distinct, different tiered hospitals in China.

Study Type

Observational

Enrollment (Estimated)

161876

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

  • China
    • Beijing
      • Beijing, Beijing, China, 100034
        • Recruiting
        • Peking University First Hospital
        • 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

N/A

Sampling Method

Probability Sample

Study Population

Adult patients admitted to five hospitals during the study period.

Description

Inclusion Criteria:

  • Adult patients (18 years and older) admitted to five hospitals during the study period

Exclusion Criteria:

  • Have less than 2 documented serum creatinine (Scr) measurements during hospitalization
  • Being diagnosed with end-stage renal disease (ESRD)
  • Maintained on dialysis or had an initial Scr greater than or equal to 4.0 mg/dL at admission
  • Developed AKI prior to admission or within 24 hours after admission
  • Length of stay shorter than 24 hours
  • Underwent kidney transplantation or nephrectomy during hospitalization
  • With all Scr measurements lower than or equal to 0.6 mg/dL from 90 days prior to admission until discharge.

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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Predictive performance of the prediction model for Acute Kidney Injury
Time Frame: through study completion, varied from one to three years in different validation cohorts.
Evaluated using AUC
through study completion, varied from one to three years in different validation cohorts.

Collaborators and Investigators

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

Sponsor

Peking University First Hospital

Investigators

  • Study Director: Li Yang, Peking University First Hospital

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)

February 28, 2023

Primary Completion (Estimated)

October 30, 2024

Study Completion (Estimated)

December 30, 2024

Study Registration Dates

First Submitted

September 9, 2024

First Submitted That Met QC Criteria

September 12, 2024

First Posted (Estimated)

September 19, 2024

Study Record Updates

Last Update Posted (Estimated)

September 19, 2024

Last Update Submitted That Met QC Criteria

September 12, 2024

Last Verified

September 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2023[069-001]

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

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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