ArticleEye (London, England)2023
Personalized treatment supported by automated quantitative fluid analysis in active neovascular age-related macular degeneration (nAMD)-a phase III, prospective, multicentre, randomized study: design and methods.
Article in Eye (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- Fluid/function correlation using AI-based quantification versus central subfield thickness in treatment-naïve and pre-treated patients with neovascular AMD in a real-world setting.Acta ophthalmologica · 2026Trial
- Artificial Intelligence-based characterization of therapeutic response in fluid types and volumes influencing retinal function in neovascular age-related macular degeneration.Scientific reports · 2026Trial
- Early Structure-Function Correlates in Neovascular Age-Related Macular Degeneration Using Artificial Intelligence-Derived OCT Biomarkers.Ophthalmology science · 2026Article
- Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England.Eye (London, England) · 2025Article
- Reshaping the Burden of nAMD: National, Regional, and Global Prevalence of MNV3 and Its Correlation With Life Expectancy-The RAP Study, Report 7.Investigative ophthalmology & visual science · 2025Article
- Comparison of AI-based retinal fluid monitoring in neovascular age-related macular degeneration with manual assessment by different eye care professionals under optimized conditions.Acta ophthalmologica · 2025Article
- Automated fluid monitoring to optimize the follow-up of neovascular age-related macular degeneration patients in the Brazilian population.International journal of retina and vitreous · 2025Article
- Correlation of retinal fluid and photoreceptor and RPE loss in neovascular AMD by automated quantification, a real-world FRB! analysis.Acta ophthalmologica · 2025Article
- Artificial intelligence in managing retinal disease-current concepts and relevant aspects for health care providers.Wiener medizinische Wochenschrift (1946) · 2025Review
- Quantitative Assessment of En‑face OCT‑Derived Minimum Intensity Fluid Changes Following Ranibizumab Biosimilar Therapy in Macular Neovascularization Secondary to nAMD and PCV.Clinical ophthalmology (Auckland, N.Z.) · 2025Article
- Intervention design for artificial intelligence-enabled macular service implementation: a primary qualitative study.Implementation science communications · 2024Article
- Analysis of OCT Scanning Parameters in AMD and RVO.Diagnostics (Basel, Switzerland) · 2024Article
- Progress in clinical research and applications of retinal vessel quantification technology based on fundus imaging.Frontiers in bioengineering and biotechnology · 2024Review
- A Systematic Prospective Comparison of Fluid Volume Evaluation across OCT Devices Used in Clinical Practice.Ophthalmology scienceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionIn neovascular age-related macular degeneration (nAMD) the exact amount of fluid and its location on optical coherence tomography (OCT) have been defined as crucial biomarkers for disease activity and therapeutic decisions. Yet in the absence of quantitative evaluation tools, real-world care outcomes are disappointing. Artificial intelligence (AI) offers a practical option for clinicians to enhance point-of-care management by analysing OCT volumes in a short time. In this protocol we present the prospective implementation of an AI-algorithm providing automated real-time fluid quantifications in a clinical real-world setting.
methodsThis is a prospective, multicentre, randomized (1:1) and double masked phase III clinical trial. Two-hundred-ninety patients with active nAMD will be randomized between a study arm using AI-supported fluid quantifications and another arm using conventional qualitative assessments, i.e. state-of-the-art disease management. The primary outcome is defined as the mean number of injections over 1 year. Change in BCVA is defined as a secondary outcome. DISCUSSION: Automated measurement of fluid volumes in all retinal compartments such as intraretinal fluid (IRF), and subretinal fluid (SRF) will serve as an objective tool for clinical investigators on which to base retreatment decisions. Compared to qualitative fluid assessment, retreatment decisions will be plausible and less prone to error or large variability. The underlying hypothesis is that fluid should be treated, while residual persistent or stable amounts of fluid may not benefit from further therapy. Reducing injection numbers without diminishing the visual benefit will increase overall patient safety and relieve the burden for healthcare providers. TRIAL-REGISTRATION: EudraCT-Number: 2019-003133-42.
Indexed as
Identifiers
What OpenQuestion holds
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.