Observational studyPloS one2020
Optical coherence tomography and color fundus photography in the screening of age-related macular degeneration: A comparative, population-based study.
Observational study in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Performance of Deep Learning in Classifying Age-Related Macular Degeneration From Images: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Diagnosing neurodegenerative disorders using retina as an external window: A systematic review of OCT-MRI correlations.Journal of Alzheimer's disease : JAD · 2025Pooled it
- Clinical effectiveness of screening for age-related macular degeneration: A systematic review.PloS one · 2023Pooled it
- I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care.Eye (London, England) · 2026Article
- TPA-ConvNeXt: Trigonometric Phase Attention for Robust Retinal Disease Classification Across Fundus and OCT.Bioengineering (Basel, Switzerland) · 2026Article
- Prevalence of macular disorders assessed by OCT in adults 45 years and older from Parintins - the Brazilian Amazon Region Eye Survey (BARES).International journal of retina and vitreous · 2026Article
- Determinants of Intergrader Agreement for Key Retinal Photography and OCT Biomarkers in AMD.Translational vision science & technology · 2025Article
- Deep learning based retinal hard exudates quantification of optical coherence tomography.International journal of retina and vitreous · 2025Article
- Advancing AMD screening with an offline, AI-powered smartphone-based fundus camera: A prospective, real-world clinical validation.Eye (London, England) · 2025Article
- Diagnostic performance and generalizability of deep learning for multiple retinal diseases using bimodal imaging of fundus photography and optical coherence tomography.Frontiers in cell and developmental biology · 2025Article
- A comparative evaluation of deep learning approaches for ophthalmology.Scientific reports · 2024Review
- Prognostic potentials of AI in ophthalmology: systemic disease forecasting via retinal imaging.Eye and vision (London, England) · 2024Review
- Non-Neovascular Age-Related Macular Degeneration Assessment: Focus on Optical Coherence Tomography Biomarkers.Diagnostics (Basel, Switzerland) · 2024Review
- Relative yield of retinal imaging versus clinical exam in following neovascular exudative age related macular degeneration.International ophthalmology · 2024Article
- Few-shot out-of-distribution detection for automated screening in retinal OCT images using deep learning.Scientific reports · 2023Article
- Periodontitis and Outer Retinal Thickness: a Cross-Sectional Analysis of the United Kingdom Biobank Cohort.Ophthalmology scienceArticle
- Deep Learning and The Retina: A New Frontier in Multiple Sclerosis Diagnosis.Current health sciences journalReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo analyze the individual value and the contribution of color fundus photography (CFP) and optical coherence tomography (OCT) in the screening of age-related macular degeneration (AMD) of an unselected population.
methodsCFP and OCT images of 15957 eyes of 8069 subjects older than 55 years, obtained during a population-based screening for AMD using a single diagnostic non-mydriatic imaging device, were analyzed by a blinded examiner. The two techniques were preliminary evaluated considering the dichotomous parameter "gradable/ungradable", then gradable images were classified. CFP were graded according to the standardized classification of AMD lesions. OCT images were also categorized considering the presence of signs of early/intermediate AMD, late AMD, or other retinal diseases. Another blinded operator re-graded 1978 randomly selected images (for both CFP and OCT), to assess test reproducibility.
resultsOf the 15957 eyes, 8356 CFP (52.4%) and 15594 (97.7%) OCT scans were gradable. Moreover, most of the eyes with ungradable CFP (7339, 96.6%) were gradable at OCT. AMD signs were revealed in 7.4% of gradable CFP and in 10.4% of gradable OCT images. Moreover, at OCT, AMD signs were found in 1110 (6.9%) eyes whose CFP were ungradable or without AMD (847 and 263 eyes, respectively). The inter-operator agreement was good for the gradable versus ungradable parameter, and optimal for the AMD grading parameter of CFP. The agreement was optimal for all OCT parameters.
conclusionsOCT provided gradable images in almost all examined eyes, compared to limited CFP efficiency. Moreover, OCT images allowed to detect more AMD eyes compared to gradable photos. OCT imaging appears to significantly improve the power of AMD screening in a general, unselected population, compared to CFP alone.
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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.