Customize your JAMA Network experience by selecting one or more topics from the list below.
Bastawrous A, Giardini ME, Bolster NM, et al. Clinical Validation of a Smartphone-Based Adapter for Optic Disc Imaging in Kenya . JAMA Ophthalmol. 2016;134(2):151–158. doi:https://doi.org/10.1001/jamaophthalmol.2015.4625
Visualization and interpretation of the optic nerve and retina are essential parts of most physical examinations.
To design and validate a smartphone-based retinal adapter enabling image capture and remote grading of the retina.
Design, Setting, and Participants
This validation study compared the grading of optic nerves from smartphone images with those of a digital retinal camera. Both image sets were independently graded at Moorfields Eye Hospital Reading Centre. Nested within the 6-year follow-up (January 7, 2013, to March 12, 2014) of the Nakuru Eye Disease Cohort in Kenya, 1460 adults (2920 eyes) 55 years and older were recruited consecutively from the study. A subset of 100 optic disc images from both methods were further used to validate a grading app for the optic nerves. Data analysis was performed April 7 to April 12, 2015.
Main Outcomes and Measures
Vertical cup-disc ratio for each test was compared in terms of agreement (Bland-Altman and weighted κ) and test-retest variability.
A total of 2152 optic nerve images were available from both methods (also 371 from the reference camera but not the smartphone, 170 from the smartphone but not the reference camera, and 227 from neither the reference camera nor the smartphone). Bland-Altman analysis revealed a mean difference of 0.02 (95% CI, −0.21 to 0.17) and a weighted κ coefficient of 0.69 (excellent agreement). The grades of an experienced retinal photographer were compared with those of a lay photographer (no health care experience before the study), and no observable difference in image acquisition quality was found.
Conclusions and Relevance
Nonclinical photographers using the low-cost smartphone adapter were able to acquire optic nerve images at a standard that enabled independent remote grading of the images comparable to those acquired using a desktop retinal camera operated by an ophthalmic assistant. The potential for task shifting and the detection of avoidable causes of blindness in the most at-risk communities makes this an attractive public health intervention.
Create a personal account or sign in to: