ArticleIndian journal of ophthalmology2016
A novel smartphone ophthalmic imaging adapter: User feasibility studies in Hyderabad, India.
Article in Indian journal of ophthalmology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 56 citations in OpenAlex.
- Evaluating the Diagnostic Accuracy of a Portable, Motorized, and Remotely Controlled Slit Lamp Imaging Adaptor Prototype for Head-Mounted Displays.Translational vision science & technology · 2024Trial
- Application of smartphone ophthalmoscope in ophthalmic clinical practice and teaching.International journal of ophthalmology · 2025Review
- Portable Anterior Eye Segment Imaging System for Teleophthalmology.Translational vision science & technology · 2023Article
- Smartphone-based Anterior Segment Imaging: A Comparative Diagnostic Accuracy Study of a Potential Tool for Blindness Prevalence Surveys.Ophthalmic epidemiology · 2022Article
- [Smartphone-based fundus imaging: applications and adapters].Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft · 2022Review
- Cobalt blue light unit filter - A smartphone attachment for blue light photography.Indian journal of ophthalmology · 2021Article
- Imaging Modalities Employed in Diabetic Retinopathy Screening: A Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2021Review
- Acceptance of a Smartphone-Based Visual Field Screening Platform for Glaucoma: Pre-Post Study.JMIR formative research · 2021Article
- Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society · 2021Article
- Telehealth and Screening Strategies in the Diagnosis and Management of Glaucoma.Journal of clinical medicine · 2021Review
- Design and Performance Characterization of a Novel, Smartphone-Based, Portable Digital Slit Lamp for Anterior Segment Screening Using Telemedicine.Translational vision science & technology · 2021Article
- Learning curve evaluation upskilling retinal imaging using smartphones.Scientific reports · 2021Article
- Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective.Progress in retinal and eye research · 2021Review
- Clinically useful smartphone ophthalmic imaging techniques.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2021Review
- Smartphone Ophthalmoscopy: is there a place for it?Clinical ophthalmology (Auckland, N.Z.) · 2021Review
- Automatic Identification of Referral-Warranted Diabetic Retinopathy Using Deep Learning on Mobile Phone Images.Translational vision science & technology · 2020Article
- Development and validation of a machine learning, smartphone-based tonometer.The British journal of ophthalmology · 2020Article
- A Novel Device for Smartphone-Based Fundus Imaging and Documentation in Clinical Practice: Comparative Image Analysis Study.JMIR mHealth and uHealth · 2020Article
- Usability testing of a smartphone-based retinal camera among first-time users in the primary care setting.BMJ innovations · 2019Article
- Teleophthalmology through handheld mobile devices: a pilot study in rural Nepal.Journal of mobile technology in medicine · 2019Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
aim of studyTo evaluate the ability of ancillary health staff to use a novel smartphone imaging adapter system (EyeGo, now known as Paxos Scope) to capture images of sufficient quality to exclude emergent eye findings. Secondary aims were to assess user and patient experiences during image acquisition, interuser reproducibility, and subjective image quality. MATERIALS AND
methodsThe system captures images using a macro lens and an indirect ophthalmoscopy lens coupled with an iPhone 5S. We conducted a prospective cohort study of 229 consecutive patients presenting to L. V. Prasad Eye Institute, Hyderabad, India. Primary outcome measure was mean photographic quality (FOTO-ED study 1-5 scale, 5 best). 210 patients and eight users completed surveys assessing comfort and ease of use. For 46 patients, two users imaged the same patient's eyes sequentially. For 182 patients, photos taken with the EyeGo system were compared to images taken by existing clinic cameras: a BX 900 slit-lamp with a Canon EOS 40D Digital Camera and an FF 450 plus Fundus Camera with VISUPAC™ Digital Imaging System. Images were graded post hoc by a reviewer blinded to diagnosis.
resultsNine users acquired 719 useable images and 253 videos of 229 patients. Mean image quality was ≥ 4.0/5.0 (able to exclude subtle findings) for all users. 8/8 users and 189/210 patients surveyed were comfortable with the EyeGo device on a 5-point Likert scale. For 21 patients imaged with the anterior adapter by two users, a weighted κ of 0.597 (95% confidence interval: 0.389-0.806) indicated moderate reproducibility. High level of agreement between EyeGo and existing clinic cameras (92.6% anterior, 84.4% posterior) was found.
conclusionThe novel, ophthalmic imaging system is easily learned by ancillary eye care providers, well tolerated by patients, and captures high-quality images of eye findings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.