Evidence map›Paper›PMID 38783384›Full record

ArticleInternational journal of retina and vitreous2024

A pilot cost-analysis study comparing AI-based EyeArt® and ophthalmologist assessment of diabetic retinopathy in minority women in Oslo, Norway.

Mia Karabeg, Goran Petrovski, Silvia Nw Hertzberg, Maja Gran Erke, Dag Sigurd Fosmark, Greg Russell, Morten C Moe, Vallo Volke, Vidas Raudonis, Rasa Verkauskiene and 3 more

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In one paragraph

Article in International journal of retina and vitreous, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
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

13 authors.

Mia KarabegCenter for Eye Research and Innovative Diagnostics, Department of Ophthalmology, Institute for Clinical Medicine, University of Oslo, Kirkeveien 166, 0450, Oslo, Norway.
Goran PetrovskiCenter for Eye Research and Innovative Diagnostics, Department of Ophthalmology, Institute for Clinical Medicine, University of Oslo, Kirkeveien 166, 0450, Oslo, Norway.
Silvia Nw HertzbergCenter for Eye Research and Innovative Diagnostics, Department of Ophthalmology, Institute for Clinical Medicine, University of Oslo, Kirkeveien 166, 0450, Oslo, Norway.
Maja Gran ErkeDepartment of Ophthalmology, Oslo University Hospital, Kirkeveien 166, 0450, Oslo, Norway.
Dag Sigurd FosmarkDepartment of Ophthalmology, Oslo University Hospital, Kirkeveien 166, 0450, Oslo, Norway.
Greg RussellClinical Development, Eyenuk Inc, Woodland Hills, CA, USA.
Morten C MoeCenter for Eye Research and Innovative Diagnostics, Department of Ophthalmology, Institute for Clinical Medicine, University of Oslo, Kirkeveien 166, 0450, Oslo, Norway.
Vallo VolkeFaculty of Medicine, Tartu University, 50411, Tartu, Estonia.
Vidas RaudonisAutomation Department, Kaunas University of Technology, 51368, Kaunas, Lithuania.
Rasa VerkauskieneInstitute of Endocrinology, Lithuanian University of Health Sciences, 50161, Kaunas, Lithuania.
Jelizaveta SokolovskaFaculty of Medicine, University of Latvia, Jelgavas street 3, LV1004, Riga, Latvia.
Inga-Britt Kjellevold HaugenNorwegian Association of the Blind and Partially Sighted, Oslo, Norway.
Beata Eva PetrovskiCenter for Eye Research and Innovative Diagnostics, Department of Ophthalmology, Institute for Clinical Medicine, University of Oslo, Kirkeveien 166, 0450, Oslo, Norway. b.e.petrovski@medisin.uio.no.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic retinopathy (DR) is the leading cause of adult blindness in the working age population worldwide, which can be prevented by early detection. Regular eye examinations are recommended and crucial for detecting sight-threatening DR. Use of artificial intelligence (AI) to lessen the burden on the healthcare system is needed. PURPOSE: To perform a pilot cost-analysis study for detecting DR in a cohort of minority women with DM in Oslo, Norway, that have the highest prevalence of diabetes mellitus (DM) in the country, using both manual (ophthalmologist) and autonomous (AI) grading. This is the first study in Norway, as far as we know, that uses AI in DR- grading of retinal images.

methodsOn Minority Women's Day, November 1, 2017, in Oslo, Norway, 33 patients (66 eyes) over 18 years of age diagnosed with DM (T1D and T2D) were screened. The Eidon - True Color Confocal Scanner (CenterVue, United States) was used for retinal imaging and graded for DR after screening had been completed, by an ophthalmologist and automatically, using EyeArt Automated DR Detection System, version 2.1.0 (EyeArt, EyeNuk, CA, USA). The gradings were based on the International Clinical Diabetic Retinopathy (ICDR) severity scale [1] detecting the presence or absence of referable DR. Cost-minimization analyses were performed for both grading methods.

results33 women (64 eyes) were eligible for the analysis. A very good inter-rater agreement was found: 0.98 (P < 0.01), between the human and AI-based EyeArt grading system for detecting DR. The prevalence of DR was 18.6% (95% CI: 11.4-25.8%), and the sensitivity and specificity were 100% (95% CI: 100-100% and 95% CI: 100-100%), respectively. The cost difference for AI screening compared to human screening was $143 lower per patient (cost-saving) in favour of AI.

conclusionOur results indicate that The EyeArt AI system is both a reliable, cost-saving, and useful tool for DR grading in clinical practice.

Indexed as

Artificial intelligenceAutomated gradingCost-analysisDiabetic retinopathyManual gradingMinority womenNorwayScreening

Identifiers

PMID38783384
PMCPMC11112837

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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.