Evidence map›Paper›PMID 38866367›Full record

ArticleOphthalmology2024

Use of an Artificial Intelligence-Generated Vascular Severity Score Improved Plus Disease Diagnosis in Retinopathy of Prematurity.

Aaron S Coyner, Benjamin K Young, Susan R Ostmo, Florin Grigorian, Anna Ells, Baker Hubbard, Sarah H Rodriguez, Pukhraj Rishi, Aaron M Miller, Amit R Bhatt and 7 more

Abstract read
In one paragraph

Article in Ophthalmology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 3 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

12 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. P-Score Variability as a Function of Retinopathy of Prematurity Severity.Investigative ophthalmology & visual science · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Artificial intelligence in ophthalmology: opportunities, challenges, and ethical considerations.Medical hypothesis, discovery & innovation ophthalmology journal · 2025
    Review
  12. 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

17 authors.

Aaron S CoynerCasey Eye Institute, Oregon Health & Science University, Portland, Oregon.
Benjamin K YoungCasey Eye Institute, Oregon Health & Science University, Portland, Oregon.
Susan R OstmoCasey Eye Institute, Oregon Health & Science University, Portland, Oregon.
Florin GrigorianArkansas Children's Hospital, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Anna EllsCalgary Retina Consultants, University of Calgary, Calgary, Alberta, Canada.
Baker HubbardEmory Eye Center, Emory University School of Medicine, Atlanta, Georgia.
Sarah H RodriguezDepartment of Ophthalmology and Visual Science, University of Chicago, Chicago, Illinois.
Pukhraj RishiTruhlsen Eye Institute, University of Nebraska Medical Centre, Omaha, Nebraska.
Aaron M MillerDepartment of Ophthalmology, Blanton Eye Institute, Houston Methodist Hospital, Houston, Texas.
Amit R BhattDepartment of Ophthalmology, Texas Children's Hospital, Houston, Texas.
Swati Agarwal-SinhaDepartment of Ophthalmology, University of Washington, Seattle, Washington.
Jonathan SearsCole Eye Institute, The Cleveland Clinic, Cleveland, Ohio.
R V Paul ChanIllinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois.
Michael F ChiangNational Eye Institute, National Institutes of Health, Bethesda, Maryland.
Jayashree Kalpathy-CramerNational Eye Institute, National Institutes of Health, Bethesda, Maryland; Department of Ophthalmology, University of Colorado School of Medicine, Aurora, Colorado.
Gil BinenbaumChildren's Hospital of Philadelphia, Philadelphia, Pennsylvania.
J Peter CampbellCasey Eye Institute, Oregon Health & Science University, Portland, Oregon. Electronic address: campbelp@ohsu.edu.

Funding

Proteomics CoreP30EY010572 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI Kate E Keller · 1995 to 2026
$19.4M
Clinical and Genetic Analysis of Retinopathy of PrematurityR01EY019474 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI CAMPBELL, JOHN PETER · 2010 to 2020
$7.0M
Artificial Intelligence Assisted Panoramic Optical Coherence Tomography Angiography for Retinopathy of PrematurityR01HD107494 · NICHD · OREGON HEALTH & SCIENCE UNIVERSITY · PI John Peter Campbell, Yifan Jian · 2021 to 2026
$2.4M
Validation of artificial intelligence (AI) based software as medical device (SaMD) for retinopathy of prematurity (ROP)R44EY035596 · NEI · SILOAM VISION, INC. · PI CAMPBELL, JOHN PETER, JONAS, KARYN · 2023 to 2024
$2.0M
Clinical and genetic analysis of retinopathy of prematurityR01HD107493 · NICHD · OREGON HEALTH & SCIENCE UNIVERSITY · PI CAMPBELL, JOHN PETER · 2021 to 2023
$1.8M
Robust AI to develop risk models in retinopathy of prematurity using deep learningR21EY031883 · NEI · MASSACHUSETTS GENERAL HOSPITAL · PI KALPATHY-CRAMER, JAYASHREE, RUBIN, DANIEL L · 2020 to 2021
$472k
Artificial intelligence assisted panoramic Optical Coherence Tomography Angiography for Retinopathy of PrematurityR01EY031331 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI CAMPBELL, JOHN PETER, JIAN, YIFAN · 2020 to 2020
$342k
NEI NIH HHS P30 EY010572NEI NIH HHS R01 EY019474NEI NIH HHS R01 EY031331NEI NIH HHS R21 EY031883NEI NIH HHS R44 EY035596NICHD NIH HHS R01 HD107493NICHD NIH HHS R01 HD107494
6 · The paper itself

Abstract

purposeTo evaluate whether providing clinicians with an artificial intelligence (AI)-based vascular severity score (VSS) improves consistency in the diagnosis of plus disease in retinopathy of prematurity (ROP).

designMultireader diagnostic accuracy imaging study.

participantsEleven ROP experts, 9 of whom had been in practice for 10 years or more.

methodsRetCam (Natus Medical Incorporated) fundus images were obtained from premature infants during routine ROP screening as part of the Imaging and Informatics in ROP study between January 2012 and July 2020. From all available examinations, a subset of 150 eye examinations from 110 infants were selected for grading. An AI-based VSS was assigned to each set of images using the i-ROP DL system (Siloam Vision). The clinicians were asked to diagnose plus disease for each examination and to assign an estimated VSS (range, 1-9) at baseline, and then again 1 month later with AI-based VSS assistance. A reference standard diagnosis (RSD) was assigned to each eye examination from the Imaging and Informatics in ROP study based on 3 masked expert labels and the ophthalmoscopic diagnosis.

main outcome measuresMean linearly weighted κ value for plus disease diagnosis compared with RSD. Area under the receiver operating characteristic curve (AUC) and area under the precision-recall curve (AUPR) for labels 1 through 9 compared with RSD for plus disease.

resultsExpert agreement improved significantly, from substantial (κ value, 0.69 [0.59, 0.75]) to near perfect (κ value, 0.81 [0.71, 0.86]), when AI-based VSS was integrated. Additionally, a significant improvement in plus disease discrimination was achieved as measured by mean AUC (from 0.94 [95% confidence interval (CI), 0.92-0.96] to 0.98 [95% CI, 0.96-0.99]; difference, 0.04 [95% CI, 0.01-0.06]) and AUPR (from 0.86 [95% CI, 0.81-0.90] to 0.95 [95% CI, 0.91-0.97]; difference, 0.09 [95% CI, 0.03-0.14]).

conclusionsProviding ROP clinicians with an AI-based measurement of vascular severity in ROP was associated with both improved plus disease diagnosis and improved continuous severity labeling as compared with an RSD for plus disease. If implemented in practice, AI-based VSS could reduce interobserver variability and could standardize treatment for infants with ROP. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Artificial IntelligenceRetinopathy of PrematuritySeverity of Illness IndexFemaleGestational AgeHumansInfant, NewbornInfant, PrematureMaleOphthalmoscopyReproducibility of ResultsRetinal VesselsROC CurveArtificial intelligenceAssistive diagnosisRetinopathy of prematurity

Identifiers

PMID38866367
PMCPMC11499038

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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.