Real-world field studies aimed at implementing future ophthalmological examinations in society

Real-world field studies aimed at implementing future ophthalmological examinations in society - Real-world field studies aimed at implementing future ophthalmological examinations in society

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000059337

Enrollment

1500

Registered

2025-10-09

Start date

2025-10-10

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Individuals who underwent a medical examination at the Sendai Open Hospital Health Checkup Center and provided their consent to participate in the research

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Individuals who visited the Sendai Open Hospital Health Checkup Center and provided their consent to participate in the research (18 years of age or older)

Exclusion criteria

Exclusion criteria: (1) Individuals who cannot provide informed consent (2) Patients with a history of photosensitivity (3) Patients who have recently undergone photodynamic therapy (PDT) (Refer to the package insert of the administered photosensitizer for the prohibited period.) (4) Patients currently taking medications with photosensitivity as a potential side effect (5) Individuals with epilepsy

Design outcomes

Primary

Measure	Time frame
Evaluation of System Functionality and Accuracy AI-predicted risks of atherosclerotic diseases and glaucoma from fundus and nailfold images, along with disease screening results, and their consistency with the presence of abnormal findings and Grade assessments during health examinations (cross-sectional evaluation)	—

Secondary

Measure	Time frame
Consistency between AI-predicted risks of atherosclerotic disease and glaucoma from fundus images and the actual incidence rates of these conditions within 10 years after image acquisition (longitudinal evaluation using historical data) Percentage of image and other data meeting quality standards required for analysis Evaluation of the correlation between disease risk and disease occurrence and the results of parameters calculated from background information (age, gender, medical history, etc.), health checkup results (blood tests, etc.), parameters calculated from fundus images and OCT examinations (vascular density, nerve thickness, etc.), ophthalmic findings (visual acuity, intraocular pressure, etc.), and parameters calculated from nail bed examination image evaluations Evaluation of improvements in accuracy after updating fine-tuning training data and post-annotation Functional verification of each system and assessment of system errors, malfunctions, and risk occurrence Investigation of task processing times Value Assessment of Future-Oriented Health Checkups: Concept, Platform, and System Evaluation Confirmation of Implementation Structure: Identifying and Improving Issues in Structure, Workflow, and Operations Task Processing Time Survey	—

Measure

Time frame

Consistency between AI-predicted risks of atherosclerotic disease and glaucoma from fundus images and the actual incidence rates of these conditions within 10 years after image acquisition (longitudinal evaluation using historical data) Percentage of image and other data meeting quality standards required for analysis Evaluation of the correlation between disease risk and disease occurrence and the results of parameters calculated from background information (age, gender, medical history, etc.), health checkup results (blood tests, etc.), parameters calculated from fundus images and OCT examinations (vascular density, nerve thickness, etc.), ophthalmic findings (visual acuity, intraocular pressure, etc.), and parameters calculated from nail bed examination image evaluations Evaluation of improvements in accuracy after updating fine-tuning training data and post-annotation Functional verification of each system and assessment of system errors, malfunctions, and risk occurrence Investigation of task processing times Value Assessment of Future-Oriented Health Checkups: Concept, Platform, and System Evaluation Confirmation of Implementation Structure: Identifying and Improving Issues in Structure, Workflow, and Operations Task Processing Time Survey

—

Countries

Japan

Contacts

Public ContactYu Yokoyama

Tohoku University Hospital Department of Ophthalmology

yu.yokoyama.c4@tohoku.ac.jp022-717-7294

Outcome results