Evidence map›Paper›PMID 39012371›Full record

ReviewDie Ophthalmologie2024

[OCT biomarkers in diabetic maculopathy and artificial intelligence].

Anna Theresa Lorenz, Andreas Pollreisz, Ursula Schmidt-Erfurth, Peter Szurman, Boris Stanzel

Abstract readEnglish AbstractReview
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In one paragraph

Review in Die Ophthalmologie, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Anna Theresa LorenzAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach, Deutschland.ORCID http://orcid.org/0009-0004-5945-1081
Andreas PollreiszUniversitätsklinik für Augenheilkunde und Optometrie, Medizinische Universität Wien, Wien, Österreich.
Ursula Schmidt-ErfurthUniversitätsklinik für Augenheilkunde und Optometrie, Medizinische Universität Wien, Wien, Österreich.
Peter SzurmanAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach, Deutschland.
Boris StanzelAugenklinik Sulzbach, Knappschaftsklinikum Saar, An der Klinik 10, 66280, Sulzbach, Deutschland. boris.stanzel@kksaar.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus is a chronic disease the microvascular complications of which include diabetic retinopathy and maculopathy. Diabetic macular edema, proliferative diabetic retinopathy, and diabetic macular ischemia pose a threat to visual acuity. Artificial intelligence can play an increasingly more important role in making the diagnosis and the treatment regimen of maculopathies in everyday clinical practice in the future. It can be used to automatically detect and quantify pathological parameters of the retina. The aim is to improve patient care in the clinical routine using so-called clinical decision support systems with personalized treatment algorithms. This review article outlines the current research regarding new biomarkers in diabetic maculopathy using optical coherence tomography (OCT) and OCT angiography (OCT-A).

Indexed as

Artificial IntelligenceBiomarkersDiabetic RetinopathyTomography, Optical CoherenceFluorescein AngiographyHumansImage Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificityBiomarkersDiabetic macular ischemiaEllipsoid zone integrityHyperreflective fociOCT angiographyRetinal fluid

Identifiers

PMID39012371

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.