Verisee Software for Diabetic Retinopathy Screening
The Clinical Benefit of an Artificial Intelligence Software Implementation on Diabetic Retinopathy Screening
1 other identifier
interventional
1,000
1 country
1
Brief Summary
The investigators aim to improve the diagnostic accuracy and the clinical referral rate for diabetic retinopathy by using a deep learning-based software.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Dec 2020
Typical duration for not_applicable
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
First Submitted
Initial submission to the registry
October 18, 2020
CompletedFirst Posted
Study publicly available on registry
November 17, 2020
CompletedStudy Start
First participant enrolled
December 1, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2023
CompletedNovember 17, 2020
November 1, 2020
3.1 years
October 18, 2020
November 15, 2020
Conditions
Outcome Measures
Primary Outcomes (1)
diagnostic accuracy
diagnostic accuracy compared to the baseline
12 months
Secondary Outcomes (3)
Screening rate of diabetic retinopathy
12 months
Changes in HbA1c
3 months
Referral rate of diabetic retinopathy
12 months
Study Arms (1)
Verisee
EXPERIMENTALScreening diabetic retinopathy using Verisee software
Interventions
Screening of diabetic retinopathy using a validated deep learning-based software,VeriSee®
Eligibility Criteria
You may qualify if:
- Adults
- Patients with diabetes
- Cooperation to fundal scopic examination
You may not qualify if:
- Diabetic duration \< 5 years in patients with type 1 diabetes
- Pregnancy
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Division of Endocrinology and Metabolism in Taichung Veterans General Hospital
Taichung, 407, Taiwan
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
I-Te Lee, MD,PhD
Taichung Veterans General Hospital
Central Study Contacts
Yu-Hsuan Li, MD
CONTACT
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- SCREENING
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
October 18, 2020
First Posted
November 17, 2020
Study Start
December 1, 2020
Primary Completion
December 31, 2023
Study Completion
December 31, 2023
Last Updated
November 17, 2020
Record last verified: 2020-11
Data Sharing
- IPD Sharing
- Will not share