Artificial Intelligence System for the Detection and Prediction of Kidney Diseases Using Ocular Information
1 other identifier
observational
4,000
1 country
1
Brief Summary
This is an retrospective and prospective multicenter study to develop and validate an artificial intelligent (AI) aided diagnosis, therapeutic effect assessment model including chronic kidney disease (CKD) and dialysis patients starting from April 2009, which is based on ophthalmic examinations (e.g. retinal fundus photography, slit-lamp images, OCTA, etc.) and CKD diagnostic and therapeutic data (routine clinical evaluations and laboratory data), to provide a reliable basis and guideline for clinical diagnosis and treatment.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Aug 2021
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
August 28, 2021
CompletedFirst Submitted
Initial submission to the registry
January 23, 2022
CompletedFirst Posted
Study publicly available on registry
February 4, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
December 1, 2022
CompletedFebruary 4, 2022
January 1, 2022
1.3 years
January 23, 2022
January 25, 2022
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Area under the receiver operating characteristic curve of the deep learning system
The investigators will calculate the area under the receiver operating characteristic curve of deep learning system and compare this index between deep learning system and human doctors
baseline
Secondary Outcomes (1)
Sensitivity and specificity of the deep learning system
baseline
Study Arms (6)
Development Dataset 01
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Department of Nephrology of the First Affiliated Hospital of Sun Yat-sen University
Development Dataset 02
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Medical Centre of Aikang Health Care, Guangzhou, China
Validation Dataset 01
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Department of Nephrology of the First Affiliated Hospital of Sun Yat-sen University
Validation Dataset 02
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Medical Centre of Aikang Health Care, Guangzhou, China
Test Dataset 01
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Department of Nephrology of the First Affiliated Hospital of Sun Yat-sen University
Test Dataset 02
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Medical Centre of Aikang Health Care, Guangzhou, China
Interventions
The development datasets were used to train the deep learning model, which was validated and tested by the other 4 datasets.
Eligibility Criteria
Participants who had slit-lamp, retinal fundus photography and kidney disease tests at the Department of Nephrology, First Affiliated Hospital of Sun Yat-sen University and Medical Centre of Aikang Health Care, Guangzhou, China
You may qualify if:
- Patients previously received kidney biopsy, ophthalmic examinations and routine examinations of the department of nephrology during in-hospital period with BCVA\>0.5.
You may not qualify if:
- Patients without retinal fundus images or kidney diseases.
- The quality of the retinal fundus images can not meet the requirement for furthur analysis.
- Severe loss of results of routine examinations of the department of nephrology.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, 510060, China
Biospecimen
Blood, urine and renal biopsy samples from CKD patients.
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- STUDY CHAIR
Yizhi Liu, M.D., Ph.D.
Zhongshan Ophthalmic Center, Sun Yat-sen University
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- OTHER
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Principal Investigator
Study Record Dates
First Submitted
January 23, 2022
First Posted
February 4, 2022
Study Start
August 28, 2021
Primary Completion
December 1, 2022
Study Completion
December 1, 2022
Last Updated
February 4, 2022
Record last verified: 2022-01
Data Sharing
- IPD Sharing
- Will not share