Evidence map›Paper›PMID 42621295›Full record

ArticleOphthalmology science2026

Early Structure-Function Correlates in Neovascular Age-Related Macular Degeneration Using Artificial Intelligence-Derived OCT Biomarkers.

Virginia Mares, Stefan Sacu, Sophie Frank-Publig, Anna Eidenberger, Philipp Fuchs, Leonard M Coulibaly, Magdalena Baratsits, Georg Faustmann, Markus Gumpinger, Emese Sükei and 10 more

Abstract read
In one paragraph

Article in Ophthalmology science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Virginia MaresDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Stefan SacuDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Sophie Frank-PubligDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Anna EidenbergerDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Philipp FuchsDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Leonard M CoulibalyDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Magdalena BaratsitsDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Georg FaustmannDepartment of Ophthalmology, Christian Doppler Lab for Artificial Intelligence in Retina, Medical University of Vienna, Austria.
Markus GumpingerDepartment of Ophthalmology, Christian Doppler Lab for Artificial Intelligence in Retina, Medical University of Vienna, Austria.
Emese SükeiDepartment of Ophthalmology, Christian Doppler Lab for Artificial Intelligence in Retina, Medical University of Vienna, Austria.
Hrvoje BogunovicDepartment of Ophthalmology, Christian Doppler Lab for Artificial Intelligence in Retina, Medical University of Vienna, Austria.
Gregor S ReiterDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.
Oliver LeingangRetInSight, Vienna, Austria.
Alexandra MiereDepartment of Ophthalmology, Intercity Hospital of Créteil, University Paris-Est Créteil, France.
Catherine Creuzot-GarcherDepartment of Ophthalmology, Dijon University Hospital, Dijon, France.
Laurent KodjikianDepartment of Ophthalmology, Croix Rousse University Hospital, Hospices Civils de Lyon, Lyon, France.
Vincent GualinoDepartment of Ophthalmology, Clinique Honoré-Cave, Montauban, France.
Benjamin WolffMaison Rouge Eye Center, Strasbourg, France.
Ulrike ScheschyDepartment of Ophthalmology, Horn Regional Hospital, Horn, Austria.
Ursula Schmidt-ErfurthDepartment of Ophthalmology, Medical University of Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To correlate automated artificial intelligence-based retinal fluid quantification with ellipsoid zone (EZ) thickness and loss, macular neovascularization (MNV) type, and visual function. Design: This is a post hoc analysis of a prospective, real-world, multicenter clinical trial. Subjects: Patients with active neovascular age-related macular degeneration (nAMD) were included. Methods: Best-corrected visual acuity (BCVA), measured using the ETDRS chart, OCT, OCT angiography, and microperimetry, were collected by the same certified examiners. Subretinal fluid (SRF), intraretinal fluid (IRF), and pigment epithelial detachment (PED) volumes for the central 1- and 6- mm areas were calculated at baseline using the Fluid Monitor (Retinsight) on Spectralis OCT (Heidelberg Engineering). An automated algorithm segmented EZ thickness and loss detectable after fluid resolution at month 1. Main Outcome Measures: Fluid volumes were associated with MNV type, EZ thickness and loss, retinal sensitivity, and BCVA using univariate and multivariate regression models and Wilcoxon rank-sum tests with bootstrapped confidence intervals. Spearman correlation was used to analyze retinal sensitivity and EZ loss. Results: Two hundred ninety eyes from 290 consecutive patients with active MNV were included in the study at baseline. Macular neovascularization type 1 was the most prevalent in this cohort. Comparing MNV types, lower amounts of IRF were found in type 1 (all Conclusion: Retinal fluid volumes in nAMD are triggered by MNV types and correlate with photoreceptor integrity and visual function, with the impact depending on the fluid compartment. Although fluid is central to disease monitoring, a more comprehensive approach to structural-functional assessment in nAMD is of interest. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

BiomarkersDeep learningNeovascular age-related macular degenerationOCTVisual acuity

Identifiers

PMID42621295
PMCPMC13487276

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.