Evidence map›Paper›PMID 36169715›Full record

ArticleDie Ophthalmologie2023

[Photo-based examination for diabetic eye pathologies in a German ophthalmological practice without personal doctor-patient contact].

Susanna F König, Georg Spital, Focke Ziemssen, Andreas Stahl, Rainer Guthoff, Armin Wolf, Stephanie Glück, Rodrigo Navarette Navarrete Orozco, Michael Ulbig, Alexander K Schuster and 1 more

Open access · hybridAbstract readEnglish Abstract
PubMed Publisher
In one paragraph

Article in Die Ophthalmologie, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
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

11 authors at 6 institutions in 1 country.

Susanna F KönigKlinik für Augenheilkunde, Universitätsklinikum Ulm, Ulm, Deutschland.
Georg SpitalAugenzentrum, St. Franziskus Hospital Münster, Münster, Deutschland.
Focke ZiemssenKlinik und Poliklinik für Augenheilkunde, Universitätsklinikum Leipzig, Leipzig, Deutschland.
Andreas StahlKlinik und Poliklinik für Augenheilkunde, Universitätsmedizin Greifswald, Greifswald, Deutschland.
Rainer GuthoffKlinik für Augenheilkunde, Universitätsklinikum Düsseldorf, Düsseldorf, Deutschland.
Armin WolfKlinik für Augenheilkunde, Universitätsklinikum Ulm, Ulm, Deutschland.
Stephanie GlückAugenarztpraxis Dres. Kortüm, MVZ GmbH, Solitudestr. 24, 71638, Ludwigsburg, Deutschland.
Rodrigo Navarette Navarrete OrozcoAugenpraxisklinik Prof. Reichel, Konstanz, Deutschland.
Michael UlbigKlinik und Poliklinik für Augenheilkunde, Klinikum rechts der Isar, Technische Universität München, München, Deutschland.
Alexander K SchusterAugenklinik, Universitätsmedizin Mainz, Mainz, Deutschland.
Karsten U KortuemKlinik für Augenheilkunde, Universitätsklinikum Ulm, Ulm, Deutschland. K.kortuem@kortuem.de.
Ophthalmology Clinic · DEJohannes Gutenberg University Mainz · DEKlinikum rechts der Isar · DEKlinik und Poliklinik für Augenheilkunde Universitätsklinikum Regensburg · DESt. Franziskus Hospital · DEUniversity Hospital Leipzig · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn increasing number of patients suffering from diabetes require regular ophthalmological check-ups to diagnose and/or treat potential diabetic retinal disease. Some countries have already implemented systematic fundus assessments including artificial intelligence-based programs in order to detect sight-threatening retinopathy. The aim of this study was to improve the detection of diabetic fundus changes in Germany without examination by a doctor and to create an easy access to ophthalmological examinations. MATERIAL AND

methodsIn this prospective monocentric study 93 patients in need for a routine check-up for diabetic retinopathy were included. The study participants took up an offer of an examination (visual examination, non-mydriatic camera-based fundus examination) without doctor-patient contact. Patient satisfaction with the organization and examinations was assessed using a questionnaire.

resultsThe mean age was 53.5 years (SD 13.6 years, 49.5% female) and 17 eyes (18.3%) showed a diabetic retinopathy which was detected using a camera-based examination. Within the small sample, no patient had to repeat the examination due to poor image quality. All categories of the questionnaire showed a good to very good satisfaction, indicating a high acceptance of the other examination form that took place at the ophthalmologist's premises.

conclusionIn our study in an ophthalmological practice a high level of acceptance among the patients interested in the screening for diabetic retinopathy without any direct patient-doctor contact was achieved. Our study shows a very good acceptance and feasibility. Future use of artificial intelligence in clinical practice may help to be able to screen many more patients as in this study imaging quality was very good.

Indexed as

Diabetes MellitusDiabetic RetinopathyArtificial IntelligenceFemaleFundus OculiHumansMaleMass ScreeningMiddle AgedProspective StudiesArtificial intelligenceCamera-based examinationDiabetic retinopathyPatient-doctor interactionPatient satisfaction

Identifiers

PMID36169715
OpenAlexW4297489882

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.