Assisting Pulmonary Disease Diagnosis With Ophthalmic Artificial Intelligence Technology
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
AgeNot listed
SponsorZhongshan Ophthalmic Center, Sun Yat-sen University
About this trial
This study intends to collect ophthalmologic examination results, pulmonary examination results and related indexes from patients with pulmonary disease and control populations, and combine big data analysis and artificial intelligence technology to explore whether new methods can be provided for early screening strategies for pulmonary disease with the aid of ophthalmologic examination, and thus assist in identifying the types of pulmonary disease and determining disease prognosis.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
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;
Disqualifiers
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.
Trial population
The study population was recruited from people who visited the cooperative medical unit for lung screening, and from people who were recruited through publicity at the unit and in the community.
Trial design
Design model
Cohort
Time perspective
Cross-sectional
Treatments tested in this trial
Ophthalmic examination
Diagnostic testVarious ophthalmic examination modalities, including slit lamp photography, fundus photography, optical coherence tomography imaging and optical coherence tomography angiography, etc.
Pulmonary Examination
Diagnostic testVarious pulmonary examination modalities, including radiography, chest CT, pulmonary function measurement, etc.
Treatment groups
10,000 Participants
are divided into 2 treatment groupsGroup A: Test group2 interventions
Group B: Control group2 interventions
Trial outcomes
Primary outcomes
1
Area Under the Receiver Operating Characteristic curve
Determining the accuracy of diagnosing pulmonary disease with ophthalmic examination
Time frame
Through study completion, an average of 1 yearSponsors and contacts
Click on the lead sponsor to view all of their trials.
Zhongshan Ophthalmic Center, Sun Yat-sen University
Lead sponsor
The First Affiliated Hospital of Guangzhou Medical University
Collaborator
Shenzhen Third People's Hospital
Collaborator
Guangzhou Kindness Health Care Center (Guangzhou Jiubang Shanxin Clinic Ltd), Guangzhou, China
Collaborator
Source ClinicalTrials.gov