Trial reportJAMA ophthalmology2020
Quantification of Fluid Resolution and Visual Acuity Gain in Patients With Diabetic Macular Edema Using Deep Learning: A Post Hoc Analysis of a Randomized Clinical Trial.
Trial report in JAMA ophthalmology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01627249 (A Comparative Effectiveness Study of Intravitreal Aflibercept, Bevacizumab and Ranibizumab for Diabetic Macular Edema), which is not on this map. Cited by 45 papers.
What it found
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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.
A Comparative Effectiveness Study of Intravitreal Aflibercept, Bevacizumab and Ranibizumab for Diabetic Macular Edema
Who cites it
45 citing papers in PubMed, 78 citations in OpenAlex.
- Anatomic Control with Faricimab versus Aflibercept in the YOSEMITE/RHINE Trials in Diabetic Macular Edema.Ophthalmology. Retina · 2025Trial
- Therapeutic response in the HAWK and HARRIER trials using deep learning in retinal fluid volume and compartment analysis.Eye (London, England) · 2023Trial
- Trial
- Early Intraretinal Fluid Reduction is Linked to Vision Gains in Patients with Diabetic Macular Edema.Ophthalmology and therapy · 2026Article
- Correlation between the optical density ratio of subretinal fluid in OCT images and visual outcome in eyes with diabetic MacularEdema.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Optical Coherence Tomography Biomarkers as Potential Predictors for Visual Function and Response to Intravitreal Therapy in Diabetic Macular Edema.Journal of vitreoretinal diseases · 2026Article
- Anatomical and Systemic Predictors of Early Response to Subthreshold Micropulse Laser in Diabetic Macular Edema: A Retrospective Cohort Study.Journal of clinical medicine · 2026Article
- What Lies beneath Diabetic Macular Edema: Latent Phenotypic Clustering and Differential Treatment Responses to Intravitreal Therapies.Ophthalmology science · 2026Article
- Artificial Intelligence in Diabetic Retinopathy and Diabetic Macular Edema: A Narrative Review.Bioengineering (Basel, Switzerland) · 2025Review
- AI-based fluid quantification in neovascular age-related macular degeneration and diabetic macular edema treated with faricimab - a real-life study.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Article
- Diagnostic Accuracy of Artificial Intelligence in Predicting Anti-VEGF Treatment Response in Diabetic Macular Edema: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2025Review
- Validation of a deep learning model for the automated detection and quantification of cystoid macular oedema on optical coherence tomography in patients with retinitis pigmentosa.Acta ophthalmologica · 2025Article
- Real-World Functional and Anatomic Outcomes With Aflibercept 8.0 mg in Patients With Diabetic Macular Edema.Journal of vitreoretinal diseases · 2025Article
- Ophthalmic drug discovery and development using artificial intelligence and digital health technologies.NPJ digital medicine · 2025Review
- Human expert grading versus automated quantification of fluid volumes in nAMD, DME and BRVO.Scientific reports · 2025Article
- Differences in Artificial Intelligence-Based Macular Fluid Parameters Between Clinical Stages of Diabetic Macular Edema and Their Relationship with Visual Acuity.Journal of clinical medicine · 2025Article
- Interpretation of SD-OCT imaging data in real-life conditions versus standardized reading centre analysis in eyes with diabetic macular oedema or macular oedema secondary to retinal vein occlusion: 24-month follow-up of the ORCA study.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Article
- Subfoveal neurosensory detachment flattening and observe (SNF-Ob) approach for the management of Ci-DMO - a multicentric study.Eye (London, England) · 2024Observational
- Anti-VEGF therapy for the long-term management of diabetic macular edema: a treat-to-target strategy based on macular morphology.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Review
- [OCT biomarkers in diabetic maculopathy and artificial intelligence].Die Ophthalmologie · 2024Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Large amounts of optical coherence tomographic (OCT) data of diabetic macular edema (DME) are acquired, but many morphologic features have yet to be identified and quantified. Objective: To examine the volumetric change of intraretinal fluid (IRF) and subretinal fluid (SRF) in DME during anti-vascular endothelial growth factor treatment using deep learning algorithms. Design, Setting, and Participants: This post hoc analysis of a randomized clinical trial, the Diabetic Retinopathy Clinical Research Network (protocol T), assessed 6945 spectral-domain OCT volume scans of 570 eyes from 570 study participants with DME. The original trial was performed from August 21, 2012, to October 18, 2018. This analysis was performed from December 7, 2017, to January 15, 2020. Interventions: Participants were treated according to a predefined, standardized protocol with aflibercept, ranibizumab, or bevacizumab with or without deferred laser. Main Outcomes and Measures: The association of treatment with IRF and SRF volumes and best-corrected visual acuity (BCVA) during 12 months using deep learning algorithms. Results: Among the 570 study participants (302 [53%] male; 369 [65%] white; mean [SD] age, 43.4 [12.6] years), the mean fluid volumes in the central 3 mm were 448.6 nL (95% CI, 412.3-485.0 nL) of IRF and 36.9 nL (95% CI, 27.0-46.7 nL) of SRF at baseline and 161.2 nL (95% CI, 135.1-187.4 nL) of IRF and 4.4 nL (95% CI, 1.7-7.1 nL) of SRF at 12 months. The presence of SRF at baseline was associated with a worse baseline BCVA Early Treatment Diabetic Retinopathy Study (ETDRS) score of 63.2 (95% CI, 60.2-66.1) (approximate Snellen equivalent of 20/63 [95% CI, 20/50-20/63]) in eyes with SRF vs 66.9 (95% CI, 65.7-68.1) (approximate Snellen equivalent, 20/50 [95% CI, 20/40-20/50]) without SRF (P < .001) and a greater gain in ETDRS score (0.5; 95% CI, 0.3-0.8) every 4 weeks during follow-up in eyes with SRF at baseline vs 0.4 (95% CI, 0.3-0.5) in eyes without SRF at baseline (P = .02) when adjusted for baseline BCVA. Aflibercept was associated with greater reduction of IRF volume compared with bevacizumab after the first injection (difference, 79.8 nL; 95% CI, 5.3-162.5 nL; P < .001) and every 4 weeks thereafter (difference, 10.4 nL; 95% CI, 0.7-20.0 nL; P = .004). Ranibizumab was associated with a greater reduction of IRF after the first injection compared with bevacizumab (difference, 75.2 nL; 95% CI, 1.4-154.7 nL; P < .001). Conclusions and Relevance: Automated segmentation of fluid in DME revealed that the presence of SRF was associated with lower baseline BCVA but with good response to anti-vascular endothelial growth factor therapy. These automated spectral-domain OCT analyses may be used clinically to assess anatomical change during therapy. Trial Registration: ClinicalTrials.gov Identifier: NCT01627249.
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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.