ArticleIndian journal of ophthalmology2020
Accuracy of the smartphone-based nonmydriatic retinal camera in the detection of sight-threatening diabetic retinopathy.
Article in Indian journal of ophthalmology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.
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Who cites it
30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 43 citations in OpenAlex.
- Comparative diagnostic accuracy of photographic methods for detecting diabetic retinopathy: A systematic review and meta-analysis.European journal of ophthalmology · 2026Pooled it
- Diabetic Retinopathy Screening Approaches in Developing Countries: A Systematic Review and Meta-Analysis.Turkish journal of ophthalmology · 2025Pooled it
- Reach and implementation of human and AI-assisted diabetic retinopathy screening models in primary healthcare settings in India.Scientific reports · 2025Observational
- Application of smartphone ophthalmoscope in ophthalmic clinical practice and teaching.International journal of ophthalmology · 2025Review
- Diagnostic accuracy of a smartphone-based device (VistaView) for detection of diabetic retinopathy: A prospective study.PLOS digital health · 2024Article
- Clinical Applications and Future Directions of Smartphone Fundus Imaging.Diagnostics (Basel, Switzerland) · 2024Review
- One-field, two-field and five-field handheld retinal imaging compared with standard seven-field Early Treatment Diabetic Retinopathy Study photography for diabetic retinopathy screening.The British journal of ophthalmology · 2024Article
- Evaluation of an offline, artificial intelligence system for referable glaucoma screening using a smartphone-based fundus camera: a prospective study.Eye (London, England) · 2024Article
- Clinical utility of handheld fundus and smartphone-based camera for monitoring diabetic retinal diseases: a review study.International ophthalmology · 2024Review
- Evaluation of Sensitivity and Specificity of Acuity 360 Telemedicine Vision Screening System.Clinical ophthalmology (Auckland, N.Z.) · 2024Article
- Prevalence of blindness and distance vision impairment in the Gambia across three decades of eye health programming.The British journal of ophthalmology · 2023Article
- Health system adaptions to improve care for people living with non-communicable diseases during COVID-19 in low-middle income countries: A scoping review.Journal of global health · 2023Article
- A Systematic Review of Digital Ophthalmoscopes in Medicine.Clinical ophthalmology (Auckland, N.Z.) · 2023Review
- Accuracy of Low-Cost, Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening: A Systematic Review.Clinical ophthalmology (Auckland, N.Z.) · 2023Review
- Diabetic retinopathy screening in the public sector in India: What is needed?Indian journal of ophthalmology · 2022Review
- [Smartphone-based fundus imaging: applications and adapters].Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft · 2022Review
- Towards a Device Agnostic AI for Diabetic Retinopathy Screening: An External Validation Study.Clinical ophthalmology (Auckland, N.Z.) · 2022Article
- Optimized hybrid machine learning approach for smartphone based diabetic retinopathy detection.Multimedia tools and applications · 2022Article
- Burden of Diabetic Retinopathy amongst People with Diabetes Attending Primary Care in Kerala: Nayanamritham Project.Journal of clinical medicine · 2021Article
- Commentary: Utility of a smartphone-assisted direct ophthalmoscope camera for a general practitioner in screening of diabetic retinopathy at a primary health care center.Indian journal of ophthalmology · 2021Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To evaluate the sensitivity and specificity of smartphone-based nonmydriatic (NM) retinal camera in the detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) in a tertiary eye care facility. Methods: Patients with diabetes underwent retinal photography with a smartphone-based NM fundus camera before mydriasis and standard 7-field fundus photography with a desktop mydriatic fundus camera after mydriasis. DR was graded using the international clinical classification of diabetic retinopathy system by two retinal expert ophthalmologists masked to each other and to the patient's identity. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to detect DR and STDR by NM retinal imaging were assessed. Results: 245 people had gradable images in one or both eyes. DR and STDR were detected in 45.3% and 24.5%, respectively using NM camera, and in 57.6% and 28.6%, respectively using mydriatic camera. The sensitivity and specificity to detect any DR by NM camera was 75.2% (95% confidence interval (CI) 68.1-82.3) and 95.2% (95%CI 91.1-99.3). For STDR the values were 82.9% (95% CI 74.0-91.7) and 98.9% (95% CI 97.3-100), respectively. The PPV to detect any DR was 95.5% (95% CI 89.8-98.5) and NPV was 73.9% (95% CI 66.4-81.3); PPV for STDR detection was 96.7% (95% CI 92.1-100)) and NPV was 93.5% (95% CI 90.0-97.1). Conclusion: Smartphone-based NM retinal camera had fairly high sensitivity and specificity for detection of DR and STDR in this clinic-based study. Further studies are warranted in other settings.
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Registered trials
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