학술논문

Diagnostic accuracy of smartphone corneal photography for detection of corneal opacities in a resource-limited setting: a community-based study.
Document Type
article
Source
Cornea Open. 2(3)
Subject
Biomedical and Clinical Sciences
Health Sciences
Ophthalmology and Optometry
Clinical Research
Eye Disease and Disorders of Vision
Clinical Trials and Supportive Activities
Prevention
4.2 Evaluation of markers and technologies
Detection
screening and diagnosis
Eye
Corneal opacity
community
diagnostic accuracy
smartphone photography
Language
Abstract
PurposeTo evaluate the diagnostic accuracy of smartphone corneal photography in detecting corneal opacities in a community-based setting.MethodsA case-control, diagnostic accuracy study was nested in a cluster-randomized trial of a corneal ulcer prevention intervention in Nepal. Smartphone corneal photography was performed annually on community members self-reporting a potential risk factor for a corneal infection. Corneal photographs were graded for the presence or absence of an opacity. All cases with an opacity on smartphone photography and an equal number of controls were invited for a comprehensive eye examination with a slit lamp biomicroscope at an eye hospital. A mobile team visited participants unable to come to the hospital, conducting a limited examination with a penlight.ResultsOf 1332 study participants (666 cases and 666 controls), 1097 had a penlight examination (535 cases and 562 controls) and 191 had a slit lamp examination (120 cases and 71 controls). When penlight examination was considered the reference standard, smartphone diagnosis of a corneal opacity had a positive predictive value (PPV) of 47% (95% confidence interval 43-52%) and negative predictive value (NPV) of 95% (93-97%). When slit lamp examination was considered the reference standard, the overall PPV and NPV were 71% (62-78%) and 80% (70-88%), respectively. The NPV was greater for detection of opacities > 1mm, estimated at 95% (90-98%).ConclusionsCorneal photography performed in a resource-limited community-based setting using a smartphone coupled to an external attachment had acceptable diagnostic accuracy for detection of corneal opacities large enough to be clinically meaningful.