Artificial Intelligent System for Eye Emergency Triage and Primary Diagnosis

Recruiting

• Conditions: Emergencies; Eye Diseases
• Interventions: Diagnostic Test: Artificial intelligent system for eye emergency triage and primary diagnosis

• Registration Number: NCT05680090
• Lead Sponsor: Sun Yat-sen University

Brief Summary

Ophthalmic emergencies are acute vision-threatening disorders, for which a delay in prompt emergency response could result in catastrophic vision loss. Triage is an effective process for ensuring that timely emergency care is provided despite limited resource by prioritizing patients to appropriate orders for visits. Historically, registered nurses classify emergency patients based on personal experiences with high variation. Additionally, primary healthcare providers have been conventionally at the forefront of providing first aid care. However, most of ocular emergencies are wrongly diagnosed or referred due to non-eye specialists' limited knowledge and training in the ophthalmology.

Here, the investigators established and validated an artificial intelligence system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images. This system has been integrated into a website to be prospectively validated in the real world.

Detailed Description

Not available

Study Timeline

• Status Verified: 2022-12
• Study Start: 2022-12-10
• Study First Submitted: 2022-12-13
• Study First Submitted QC: 2022-12-25
• Last Update Submitted: 2022-12-25
• Study First Posted: 2023-01-11
• Last Update Posted: 2023-01-11
• Primary Completion: 2023-01-13
• Study Completion: 2023-01-20

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 100

Inclusion Criteria

1. Suffering acute ophthalmic symptoms within one month
2. Visiting the ocular emergency department for the first time
3. Must be able to complete the triage form for ophthalmic emergency
4. Must be able to cooperate either by submitting smartphone photographs or receiving slit-lamp examination

Exclusion Criteria

The image quality does not meet the clinical requirements.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Eligible participants for AI-based ophthalmic emergency triage and primary diagnosis	Artificial intelligent system for eye emergency triage and primary diagnosis	-

Primary Outcome Measures

Name	Time	Method
The accuracy of the triage model	2023.1	Use the triage model to classify patients with acute ocular symptoms, and count the proportion of correct classification.

Secondary Outcome Measures

Name	Time	Method
The accuracy of the primary diagnostic model	2023.1	Use the primary diagnostic model to diagnose patients with ophthalmic emergencies, and count the proportion of correct diagnosis in all patients.

Trial Locations

Locations (1)

Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity; 🇨🇳 Guangzhou, Guangdong, China