Dry Eye Screening and Referral System

• Conditions: Dry Eye

• Registration Number: NCT04413370
• Lead Sponsor: Sun Yat-sen University

Brief Summary

Dry eye is one of the most common ocular surface diseases. Its pathogenic factors are related to multiple etiology. Because of the complexity of the pathogenesis of dry eye, the diversity of related examinations, and the inconsistency of symptoms and signs of dry eye patients, the diagnosis of dry eye has higher requirements on the professional technology and examination equipment of ophthalmologists.

The purpose of this study is to establish a case-control cohort of dry eye patients. Multimodal data will be collected from participants, including medical history information, ocular surface disease index scale (OSDI), anterior segment photography, and treatment outcome of dry eye patients. The correlation between the characteristics of anterior segment images and dry eye diagnosis will be explored by artificial intelligence algorithms. The purpose of this study was to develop an artificial intelligence dry eye screening and referral system.

Detailed Description

Not available

Study Timeline

• Study Start: 2020-01-06
• Study First Submitted: 2020-05-28
• Study First Submitted QC: 2020-05-28
• Study First Posted: 2020-06-02
• Status Verified: 2022-04
• Last Update Submitted: 2022-04-18
• Primary Completion: 2022-04-19
• Last Update Posted: 2022-04-25
• Study Completion: 2022-08-01

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 518

Inclusion Criteria

1. Subjects whose age are greater than or equal to 18 years old;
2. Subjects who can cooperate with the inspection;
3. Subjects who agree to participate in the study and sign the consent form.

Exclusion Criteria

1. Subjects who cannot do the inspection.
2. Subjects who suffer from diseases that compromise the inspection.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Area under the curve (severe)	up to 1 month	AUC values for predicting whether subject need to be referral or not.

Secondary Outcome Measures

Name	Time	Method
Area under the curve (each group)	up to 1 month	AUC values for predicting whether subject can be accurately grouped into each of the four groups.
Accuracy, true positive rate, and true negative rate	up to 1 month	The performance of this artificial platform.

Trial Locations

Locations (1)

Zhongshan Ophthalmic Center; 🇨🇳 Guangzhou, Guangdong, China