Diabetic Neuropathies Clinical Trial
— EyekonT1DOfficial title:
Eye-tracking-based Artificial Intelligence Detects Abnormalities of the Oculomotor System in Type 1 Diabetes
| Verified date | May 2022 |
| Source | University of Milan |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Observational |
Abnormalities of the oculomotor system may represent an early sign of diabetic neuropathy and are currently poorly studied. The investigators designed an eye-tracking-based test to evaluate the oculomotor function in patients with type 1 diabetes. The investigators used the SRLab -Tobii TX300 Eye tracker®, an eye-tracking device, coupled with a software that we developed to test abnormalities of the oculomotor system. The software consists in a series of screens divided in 5 classes of parameters (Resistance, Wideness, Pursuit, Velocity and Optokinetic Nystagmus [OKN]) to evaluate both smooth and saccadic movement in different directions. 40 healthy volunteers and 40 patients with long-standing type 1 diabetes will be enrolled to analyze the alterations in the oculomotor system and function.
| Status | Completed |
| Enrollment | 40 |
| Est. completion date | December 31, 2021 |
| Est. primary completion date | November 1, 2021 |
| Accepts healthy volunteers | |
| Gender | All |
| Age group | 16 Years to 60 Years |
| Eligibility | Patients: Inclusion Criteria: - Type 1 diabetes - willing to give consent Exclusion Criteria: - Diabetic retinopathy and other ocular diseases - other endocrine disease - malignancy Healthy volunteers: Inclusion Criteria: - willing to give consent Exclusion Criteria: - Other ocular diseases - Any endocrine disease - Malignancy |
| Country | Name | City | State |
|---|---|---|---|
| Italy | Sacco University Hospital | Milan | MI |
| Lead Sponsor | Collaborator |
|---|---|
| University of Milan | ASST Fatebenefratelli Sacco |
Italy,
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Percentage of patients with a change in eye movement test in each class Resistance, Velocity, Pursuit, Wideness and OKN measured by the eye-tracking based test | Percentage of all parameters tested in each class changed in patients with type 1 diabetes as compared to healthy subjects. Parameters evaluated include number of visualization required to recognize a target and time (seconds), to recognize a target moving on the screen in different directions. | End of the study (when all patients have completed all sessions of the test), an average of 6 months | |
| Secondary | Percentage of patients with a change in eye movement test in the Resistance class | Percentage of parameters tested in the Resistance class changed in patients with type 1 diabetes as compared to healthy subjects. Resistance will be measured by using number of visualization required to recognize a target and time (seconds) required to recognize a target moving on the screen in different directions. An algorithm will attribute those measurements to the specific class of Resistance. | End of the study (when all patients have completed all sessions of the test), an average of 6 months | |
| Secondary | Percentage of patients with a change in eye movement test in the Wideness class | Percentage of parameters tested in the Wideness class changed in patients with type 1 diabetes as compared to healthy subjects. Wideness will be measured by using number of visualization required to recognize a target and time (seconds) required to recognize a target moving on the screen in different directions. An algorithm will attribute those measurements to the specific class of Wideness. | End of the study (when all patients have completed all sessions of the test), an average of 6 months | |
| Secondary | Percentage of patients with a change in eye movement test in the Velocity class | Percentage of parameters tested in the Velocity class changed in patients with type 1 diabetes as compared to healthy subjects. Velocity will be measured by using number of visualization required to recognize a target and time (seconds) required to recognize a target moving on the screen in different directions. An algorithm will attribute those measurements to the specific class of Velocity. | End of the study (when all patients have completed all sessions of the test), an average of 6 months |
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