To evaluate the feasibility of a telemedicine workflow using the Smart Eye Camera (SEC) for anterior segment imaging during community outreach screenings in Timor-Leste, and to describe the distribution of anterior segment findings among screening attendees. Prospective, community outreach, cross-sectional pilot screening study.. Eighty-two adults (164 eyes) who participated in community eye screenings in Timor-Leste. Uncorrected distance visual acuity (UCVA) and pinhole visual acuity were recorded in logMAR units. Anterior segment slit-lamp videos were acquired using the SEC (a smartphone-attachable slit-beam camera) and uploaded to a secure cloud platform for remote grading by ophthalmologists. Nuclear cataracts were graded (NUC1–NUC3) from slit-beam images in a subset with nuclear cataract. Feasibility of remote image acquisition and grading; frequency of anterior segment findings among screened eyes; UCVA and pinhole visual acuity; and exploratory description of nuclear cataract grade in relation to visual acuity. Participants had a mean age of 58.95±14.03 years (range, 29–87), and 52.4% were female. Mean UCVA was 0.55±0.65 logMAR and mean pinhole visual acuity was 0.42±0.66 logMAR. Among screened eyes, the most common findings were cataract (37.1%), conjunctivitis (25.9%), and pterygium (12.3%). In descriptive age-stratified summaries, cataract was identified only in the ≥50 years group (44.7% of eyes), and visual acuity was worse in older participants. In the nuclear cataract subset (59 eyes), higher nuclear grades were associated with worse UCVA and pinhole visual acuity. In this pilot convenience sample, telemedicine screening using a portable smartphone-based slit-beam camera was feasible and enabled remote identification of common anterior segment conditions in Timor-Leste. Cataract and ocular surface conditions were frequent among screening attendees, but these findings should not be interpreted as population prevalence. Larger, systematically sampled studies incorporating best-corrected visual acuity and reproducibility assessments of image grading are needed to estimate population prevalence and to evaluate clinical impact and referral outcomes.
Fernando et al. (Sun,) studied this question.