Risk Factors and Deep Learning Model for CI-AKI

Contrast-associated acute kidney injury (CI-AKI) is a sudden and significant decline in renal function resulting from the use of a contrast agent.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

AKI - Acute Kidney Injury Acute Kidney Injury Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Kidney Diseases Male Urogenital Diseases Renal Insufficiency Urogenital Diseases Urologic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital

Jinan, Shandong, 250014, China

About this study

Contrast-associated acute kidney injury (CI-AKI) is a sudden and significant decline in renal function resulting from the use of a contrast agent. Despite the frequent use of iodinated contrast agents in medical investigations, predictive models for CI-AKI are scarce. This study aimed to construct and validate interpretable deep learning models for the early risk prediction of acute kidney injury (AKI) associated with iodinated contrast agents.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

patients who received iodinated contrast agents during hospitalization
age ≥ 18 years
hospitalization length ≥ 48 hours
at least two serum creatinine tests during hospitalization

Exclusion criteria

patients with stage 4 or 5 chronic kidney disease prior to admission
patients undergoing hemodialysis, hemofiltration or peritoneal before admission
a history of nephrectomy or kidney transplantation during hospitalization
incomplete clinical information
Serum creatinine always ≤ 40 μmol/L during hospitalization

Treatment and study plan

Primary outcomes

AKI

Time frame: Completed through study, up to half a year

During the patient's hospitalization, acute kidney injury occurred after the use of Iodinated contrast media

Sponsors and collaborators

Lead sponsor

Xiao Li，MD

Other

Registry information

Official study title

Investigation and Early Risk Prediction of Acute Kidney Injury Caused by Iodinated Contrast Agents: Development of CI-AKIDPi Model Based on Interpretable Deep Learning

Important dates

Study start: 2024
Primary completion: 2025
Study completion: 2025
First posted: Sep 19, 2024
Registry last updated: Sep 19, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Active, Not Recruiting