Back to resultsThe Efficacy of an Artificial Intelligence Platform to Adapt Visual Aids for Patients With Low Vision: a Randomised Controlled Trial (AI)
Primary Purpose
Ophthalmology, Low Vision Aids, Artificial Intelligence
Status
Unknown status
Phase
Not Applicable
Locations
China
Study Type
Interventional
Intervention
Low vision aids
Sponsored by
About this trial
This is an interventional supportive care trial for Ophthalmology
Eligibility Criteria
Inclusion Criteria:
- Low vision Aged 3 to 105
Exclusion Criteria:
- Severe systemic diseases Failure to sign informed consent or unwilling to participate
Sites / Locations
- 2nd Affilliated Hospital of Jujian Medical UniversityRecruiting
Arms of the Study
Arm 1
Arm 2
Arm Type
Experimental
Experimental
Arm Label
Algorithm assisted group
Human doctor group
Arm Description
Patients receive assisting devices fitting services from human doctors assisted by the machine learning model
Patients receive assisting devices fitting services from humanr doctors
Outcomes
Primary Outcome Measures
The proportion of giving up assisting devices
The investigator will calculate the proportion of giving up more than one assisting devices in two groups for three months and six months
Secondary Outcome Measures
Time cost of using assisting devices of patients
The investigator will apply survival analysis for the time cost of using assisting devices in different groups.
Full Information
NCT ID
NCT04919837
First Posted
June 6, 2021
Last Updated
June 6, 2021
Sponsor
Sun Yat-sen University
Collaborators
2nd Affilliated Hospital of Fujian Medical University
1. Study Identification
Unique Protocol Identification Number
NCT04919837
Brief Title
The Efficacy of an Artificial Intelligence Platform to Adapt Visual Aids for Patients With Low Vision: a Randomised Controlled Trial
Acronym
AI
Official Title
The Efficacy of an Artificial Intelligence Platform to Adapt Visual Aids for Patients With Low Vision: a Randomised Controlled Trial
Study Type
Interventional
2. Study Status
Record Verification Date
June 2021
Overall Recruitment Status
Unknown status
Study Start Date
July 27, 2020 (Actual)
Primary Completion Date
July 27, 2021 (Anticipated)
Study Completion Date
July 30, 2021 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Sun Yat-sen University
Collaborators
2nd Affilliated Hospital of Fujian Medical University
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes
5. Study Description
Brief Summary
According to the WHO's definition of visual impairment, as of 2018, there were approximately 1.3 billion people with visual impairment in the world, and only 10% of countries can provide assisting services for the rehabilitation of visual impairment. Although China is one of the countries that can provide rehabilitation services for patients with visual impairment, due to restrictions on the number of professionals in various regions, uneven diagnosis and treatment, and regional differences in economic conditions, not all visually impaired patients can get the rehabilitation of assisting device fitting.
Traditional statistical methods were not enough to solve the problem of intelligent fitting of assisting devices. At present, there are almost no intelligent fitting models of assisting devices in the world. Therefore, in order to allow more low-vision patients to receive accurate and rapid rehabilitation services, we conducted a cross-sectional study on the assisting devices fitting for low-vision patients in Fujian Province, China in the past five years, and at the same time constructed a machine learning model to intelligently predict the adaptation result of the basic assisting devices for low vision patients.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Ophthalmology, Low Vision Aids, Artificial Intelligence
7. Study Design
Primary Purpose
Supportive Care
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
ParticipantOutcomes Assessor
Allocation
Randomized
Enrollment
200 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Algorithm assisted group
Arm Type
Experimental
Arm Description
Patients receive assisting devices fitting services from human doctors assisted by the machine learning model
Arm Title
Human doctor group
Arm Type
Experimental
Arm Description
Patients receive assisting devices fitting services from humanr doctors
Intervention Type
Other
Intervention Name(s)
Low vision aids
Intervention Description
the assisting devices fitting for low-vision patients
Primary Outcome Measure Information:
Title
The proportion of giving up assisting devices
Description
The investigator will calculate the proportion of giving up more than one assisting devices in two groups for three months and six months
Time Frame
Baseline
Secondary Outcome Measure Information:
Title
Time cost of using assisting devices of patients
Description
The investigator will apply survival analysis for the time cost of using assisting devices in different groups.
Time Frame
Baseline
10. Eligibility
Sex
All
Minimum Age & Unit of Time
3 Years
Maximum Age & Unit of Time
105 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Low vision Aged 3 to 105
Exclusion Criteria:
Severe systemic diseases Failure to sign informed consent or unwilling to participate
Facility Information:
Facility Name
2nd Affilliated Hospital of Jujian Medical University
City
Quanzhou
State/Province
Fujian
ZIP/Postal Code
362000
Country
China
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Jianmin Hu, M.D., Ph.D.
Phone
+8615359595888
Email
doctorhjm@163.com
12. IPD Sharing Statement
Learn more about this trial
The Efficacy of an Artificial Intelligence Platform to Adapt Visual Aids for Patients With Low Vision: a Randomised Controlled Trial
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