Dry Eye Screening and Referral System
Study Details
Study Description
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.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Severe Group This group of subjects needed a referral to the hospital for further treatments. |
Diagnostic Test: Dry eye diagnostic test
The artificial intelligent dry eye screening platform
|
| Mild group This group of subjects was diagnosed with dry eye but can use artificial tears instead of further treatment. |
Diagnostic Test: Dry eye diagnostic test
The artificial intelligent dry eye screening platform
|
| Follow-up group This group of subjects had no dry eye symptoms and signs and belonged to the normal control group. |
Diagnostic Test: Dry eye diagnostic test
The artificial intelligent dry eye screening platform
|
Outcome Measures
Primary Outcome Measures
- Area under the curve (severe) [up to 1 month]
AUC values for predicting whether subject need to be referral or not.
Secondary Outcome Measures
- 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.
Eligibility Criteria
Criteria
Inclusion Criteria:
-
Subjects whose age are greater than or equal to 18 years old;
-
Subjects who can cooperate with the inspection;
-
Subjects who agree to participate in the study and sign the consent form.
Exclusion Criteria:
-
Subjects who cannot do the inspection.
-
Subjects who suffer from diseases that compromise the inspection.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Zhongshan Ophthalmic Center | Guangzhou | Guangdong | China | 510632 |
Sponsors and Collaborators
- Sun Yat-sen University
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- Dry eye screening system