E-POSTER DETAIL

Title
Teleophthalmology for ophthalmic emergencies: A systematic review
Authors
Layla Aqeela Khairul Anuar, Nur Musfirah Mahmud, Tengku Ain Fathlun Tengku Kamalden
Presenting
Layla Aqeela Khairul Anuar
PURPOSE:
Ocular emergencies require timely recognition and intervention to prevent permanent visual impairment. However, access to ophthalmology expertise in acute care settings is often limited. Teleophthalmology in emergency settings has expanded to facilitate remote evaluation, yet current literature provides fragmented and heterogeneous evidence on its effectiveness. This systematic review and meta-analysis demonstrates that teleophthalmology achieves high pooled diagnostic accuracy for urgent ocular conditions and may reduce unnecessary in-person referrals. Performance varies by modality, with imaging-based approaches generally showing stronger discriminatory metrics.
METHODS:
This study evaluates the diagnostic accuracy and clinical utility of teleophthalmology in managing ocular emergencies, identifying 3,163 records. Following screening, 15 studies were included. Seven diagnostic accuracy studies were included in a bivariate random-effects meta-analysis. Risk of bias was assessed using QUADAS-2 and the Newcastle–Ottawa Scale, while others were narratively appraised.
RESULTS:
Pooled sensitivity and specificity of teleophthalmology for diagnosing ocular emergencies were 82.4% (95% CI: 55.0%–94.7%) and 92.5% (95% CI: 86.7%–95.9%), respectively. The area under SROC curve was 0.947, indicating excellent discrimination. Subgroup analysis revealed performance differences based on imaging modality, with the highest accuracy seen in studies employing high-resolution imaging and AI-assisted triage. Secondary outcomes from cohort and feasibility studies demonstrated improved visual acuity, reduced treatment delays, high patient satisfaction and avoidance of in-person referral in 14%–73% of cases.
CONCLUSIONS:
Evidence supports the important role of teleophthalmology in reducing unnecessary hospital visits and facilitating timely care. Further research should focus on standardising diagnostic protocols and integrating AI-driven decision support to enhance performance consistency.