Evidence map›Paper›PMID 40998972›Full record

ArticleScientific reports2025

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry.

Philipp Fuchs, Ursula Schmidt-Erfurth, Leonard M Coulibaly, Hrvoje Bogunovic, Oliver Leingang, Anastasiia Gruber, Florian Frommlet, Virginia Mares, Daniel Barthelmes, Gregor S Reiter

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Philipp FuchsDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Ursula Schmidt-ErfurthDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria. Ursula.schmidt-erfurth@meduniwien.ac.at.
Leonard M CoulibalyDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Hrvoje BogunovicDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Oliver LeingangDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Anastasiia GruberDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Florian FrommletCenter for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Virginia MaresDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Daniel BarthelmesDepartment of Ophthalmology, University Hospital Zurich, Zurich, Switzerland.
Gregor S ReiterDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monitoring. Real-world data comprising OCT scans and electronic medical records from 148 patients (187 eyes) were extracted from the Fight Retinal Blindness! (FRB! ) Zürich database. OCT scans were analysed using an approved AI algorithm (RetInSight, Vienna, Austria) to quantify fluid volumes by compartements. The impact of fluid persistence and fluctuations on BCVA change was assessed using forward stepwise regression and mixed models. Fluid compartments were further categorized into quartiles (SD-Qs), and the effect of fluid fluctuations on BCVA analysed (SD-Q1 least and SD-Q4 greatest variability of fluctuations). The greatest PED fluctuations in the central 1-mm showed an accentuated BCVA decrease after 2 and 4 years (estimate: -0.07, P = 0.019; estimate: -0.15, P < 0.01). After 4 years, eyes in SD-Q4 compared with SD-Q1 with greater PED fluctuations in the central 1-mm and 6-mm area were affected by a significant mean reduction in BCVA (-5.7 letters (P = 0.013); -6.1 letters (P = 0.015)). Greater intraretinal fluid (IRF) fluctuations (central 1-mm) (SD-Q4 compared with SD-Q1) were associated with a significantly worse mean BCVA by -6.8 letters (P = 0.018) after 5 years. Fluid persistence was not associated with statistically significant BCVA changes. In routine clinical management of nAMD, greater fluctuations of PED and IRF correlate with worse BCVA outcomes over long-term follow-up. A well-suited treatment regimen is required in the real world which can be utilized with AI-based fluid monitoring.

Indexed as

Artificial IntelligenceMacular DegenerationSubretinal FluidVisual AcuityAgedAged, 80 and overAlgorithmsFemaleHumansHydrodynamicsMaleMiddle AgedRegistriesTomography, Optical CoherenceTreatment OutcomeAnti-VEGFArtificial intelligenceFluid dynamicsFluid fluctuationsFluid persistenceNeovascular AMDOCT

Identifiers

PMID40998972
PMCPMC12464290

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LicenceCC BY-NC-ND
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Registered trials

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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.