Using eye exams and AI to help diagnose lung diseases

Assisting Pulmonary Disease Diagnosis With Ophthalmic Artificial Intelligence Technology

This study is testing if eye exams can help doctors find lung diseases earlier by using artificial intelligence to analyze the results from patients with lung problems and healthy individuals.

Quick facts

• Study type: Observational
• Enrollment: 10000 (estimated)
• Sex: All
• Sponsor: Zhongshan Ophthalmic Center, Sun Yat-sen University (other)
• Locations: 4 sites (Guangzhou, Guangdong and 3 other locations)
• Trial ID: NCT05847894 on ClinicalTrials.gov

What this trial studies

This observational study aims to gather results from ophthalmologic and pulmonary examinations of patients with pulmonary diseases and control groups. By utilizing big data analysis and artificial intelligence, the study seeks to determine if eye examinations can provide new strategies for early screening of pulmonary diseases. The goal is to assist in identifying different types of pulmonary diseases and predicting their prognosis based on the collected data.

Who should consider this trial

Good fit: Ideal candidates include individuals aged 18 and older with respiratory-related diseases who can undergo both ophthalmologic and pulmonary examinations.

Not a fit: Patients with serious underlying diseases or those unable to complete the required examinations may not benefit from this study.

Why it matters

Potential benefit: If successful, this approach could lead to earlier and more accurate diagnoses of pulmonary diseases, improving patient outcomes.

How similar studies have performed: While the use of AI in medical diagnostics is growing, this specific approach combining ophthalmologic examinations with pulmonary disease diagnosis is relatively novel and has not been extensively tested.

Eligibility criteria

Inclusion Criteria:

* Those aged ≥18 years; or those aged \<18 years who can cooperate with the relevant examination and are accompanied and informed by a guardian;
* People with respiratory-related diseases who were to undergo pulmonary examination, or those who volunteered to participate in the trial through publicity recruitment;
* expected survival time of 3 months or more;
* Those with no previous serious underlying disease and no history of serious eye disease;
* Those who can cooperate with ophthalmologic and pulmonary-related examinations and have regular follow-up examinations;
* Those who gave informed consent to the study prior to the trial and voluntarily signed the informed consent form;
* Other conditions that can be included in the study as judged by the investigator.

Exclusion Criteria:

* Patients who are unable to complete ophthalmology or pulmonary-related examinations and regular follow-ups due to serious diseases, trauma or surgery (serious ophthalmology diseases such as extremely poor vision that cannot be fixed, ocular atrophy, severe refractive interstitial clouding that prevents fundus photography, etc.);
* People with poor compliance due to various reasons such as alcohol or drug dependence, or mental disorders;
* Those without informed consent;
* Other conditions judged by the investigator to be unsuitable for participation in the trial.

Where this trial is running

Guangzhou, Guangdong and 3 other locations

• Zhongshan Ophthalmic Center, Sun Yat-sen University — Guangzhou, Guangdong, China (RECRUITING)
• Guangzhou Kindness Health Care Center (Guangzhou Jiubang Shanxin Clinic Ltd) — Guangzhou, Guangdong, China (RECRUITING)
• the First Affiliated Hospital of Guangzhou Medical University — Guangzhou, Guangdong, China (RECRUITING)
• Shenzhen Third People's Hospital — Shenzhen, Guangdong, China (RECRUITING)

Study contacts

• Study coordinator: Weixing Zhang, M.D.

Conditions: Pulmonary Diseases, Ophthalmological Diagnostic Techniques, Artificial Intelligence, Artificial intelligence