NCT04416776

Brief Summary

Strabismus affects approximately 0.8%-6.8% of the world's population and appears by the age of 3 years in 65% of affected individuals. Manual measurement of deviation is often laborious and highly dependent on the experience of the specialist and the cooperation of the patients. Current strabismus evaluation technologies are heavily dependent on model eyes. Here, the investigators use deep learning to develop an artificial intelligence (AI) platform consisting of three deep learning (DL) systems to screen strabismus, evaluate deviation and propose a surgical plan based on corneal light-reflection photos. The investigator also conduct clinical trial to validate its versatility in clinical practice.

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
323

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Sep 2019

Shorter than P25 for all trials

Geographic Reach
1 country

1 active site

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

September 1, 2019

Completed
9 months until next milestone

First Submitted

Initial submission to the registry

June 2, 2020

Completed
2 days until next milestone

First Posted

Study publicly available on registry

June 4, 2020

Completed
6 days until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 10, 2020

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

June 10, 2020

Completed
Last Updated

June 4, 2020

Status Verified

June 1, 2020

Enrollment Period

9 months

First QC Date

June 2, 2020

Last Update Submit

June 2, 2020

Conditions

Outcome Measures

Primary Outcomes (1)

  • The proportion of accurate, mistaken and miss detection of the diagnostic system.

    up to 3 years

Study Arms (1)

Eligible patients for AI test

Device: strabismus diagnostic system.

Drug: Strabismus diagnostic system.

Interventions

An AI platform based on corneal light-reflection photos to facilitate the diagnosis and angle evaluation of strabismus and to provide advice for surgical planning.

Eligible patients for AI test

Eligibility Criteria

Sexall
Healthy VolunteersNo
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

A prospective study to validate the accuracy of the strabismus intelligent diagnostic system in the clinical practice.

You may qualify if:

  • Patients in the outpatient clinic of strabismus department.

You may not qualify if:

  • Patients or their parents diagree to participate in the trial.
  • Patients with blepharoptosis.
  • Patients can't facing forward or lacking fixation.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Zhongshan Ophthalmic Center, Sun Yat-sen University

Guangzhou, Guangdong, 510080, China

RECRUITING

MeSH Terms

Conditions

Eye DiseasesStrabismus

Condition Hierarchy (Ancestors)

Ocular Motility DisordersCranial Nerve DiseasesNervous System Diseases

Central Study Contacts

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Clinical Professor

Study Record Dates

First Submitted

June 2, 2020

First Posted

June 4, 2020

Study Start

September 1, 2019

Primary Completion

June 10, 2020

Study Completion

June 10, 2020

Last Updated

June 4, 2020

Record last verified: 2020-06

Locations