Evidence map›Paper›PMID 31317094›Full record

ArticleJournal of current ophthalmology2019

Optical coherence tomography angiography image quality assessment at varying retinal expertise levels.

Anne K Woetzel, Jost L Lauermann, Kiana Kreitz, Maged Alnawaiseh, Christoph R Clemens, Nicole Eter, Florian Alten

Open access · diamondAbstract read
In one paragraph

Article in Journal of current ophthalmology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

10 citing papers in PubMed, 13 citations in OpenAlex.

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  6. Artificial intelligence in OCT angiography.Progress in retinal and eye research · 2021
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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

7 authors.

Anne K WoetzelDepartment of Ophthalmology, University of Muenster Medical Center, Muenster, Germany.
Jost L LauermannDepartment of Ophthalmology, University of Muenster Medical Center, Muenster, Germany.
Kiana KreitzInstitute of Biostatistics and Clinical Research, University of Muenster, Muenster, Germany.
Maged AlnawaisehDepartment of Ophthalmology, University of Muenster Medical Center, Muenster, Germany.
Christoph R ClemensDepartment of Ophthalmology, University of Muenster Medical Center, Muenster, Germany.
Nicole EterDepartment of Ophthalmology, University of Muenster Medical Center, Muenster, Germany.
Florian AltenDepartment of Ophthalmology, University of Muenster Medical Center, Muenster, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo compare optical coherence tomography angiography (OCT-A) image quality gradings performed by readers of varying retinal expertise levels in different retinal diseases.

methodsCentral 3 × 3 mm

resultsRegarding MAS, inter-reader agreement between SE and OR was 93.7% (Cohen's kappa = 0.907) and 85.4% (Cohen's kappa = 0.786) between SE and MD. Regarding SAS, inter-reader agreement between SE and OR was 95.1% (Cohen's kappa = 0.92) and 92.2% (Cohen's kappa = 0.874) between SE and MD. In the SAS analysis, signal strength index (SSI) and presence of retinal pathology had a significant influence on the overall agreement (

conclusionsOCT-A image quality assessment can be performed most reliably by an ophthalmologist with knowledge in retinal image analysis. Yet, well-instructed non-ophthalmologic assessors show only slightly inferior results and, thus, may be integrated in routine OCT-A image quality assessment as well.

Indexed as

Image qualityMotion artifactsOCT angiographyOptical coherence tomographySegmentation

Identifiers

PMID31317094
PMCPMC6611935
OpenAlexW2908129927

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.