Abstract
Purpose :
Age-related macular degeneration (AMD) is the leading cause of irreversible blindness in industrialized countries. While treatments are available, prompt identification of conversion to wet AMD is necessary for optimal patient outcomes. A digital, handheld standalone device using shape discrimination hyperacuity to identify a patient’s minimum distortion-detection threshold has been described. This study performs a clinical validation of that device.
Methods :
Using a prototype device (KalEYEdoscope) with an injection-molded 3D printed shell, two tactile buttons, a battery, a processing unit (Raspberry Pi 3), and a 1.5 inch RGB OLED screen, a clinical validation was conducted on 15 patients after approval of the University of Michigan IRB. Patients were presented with a series of circle-like images and, after each image, asked whether the image previously displayed was a perfect circle. The duration of the test and responses to a post-test questionnaire were recorded.
Results :
All patients were able to complete the test (n=15, 100%). The total duration of the test took a mean of 70 seconds (standard deviation 9.1 seconds), with a range from 32 seconds to 2 minutes and 23 seconds. Compared to other home monitoring products, ForeseeHome and myVisionTrack (mVT), this device reduced test time by 67% on average. On a Likert scale from 1 to 5 with 1 being the easiest and 5 the hardest, patients rated the test as a mean of 1.545 in difficulty. All 15 patients found the device comfortable to hold for the duration of the test (100%). The device was devised to accommodate refractive errors from +5 D to -10 D and accommodated 100% of the evaluated patients, whom had refractive errors ranging from +1.25 D to -7.0 D.
Conclusions :
This clinical validation demonstrates that a digital, handheld standalone device using shape discrimination hyperacuity to identify a patient’s minimum distortion-detection threshold can provide a rapid, easy, comfortable testing solution for a range of patients. Further validation and trials are necessary to demonstrate that this device results in improved outcomes of patients with AMD.
This is a 2021 ARVO Annual Meeting abstract.