ArticleOphthalmology2016
Plus Disease in Retinopathy of Prematurity: A Continuous Spectrum of Vascular Abnormality as a Basis of Diagnostic Variability.
Article in Ophthalmology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04995341 (Analyzing Retinal Microanatomy in Retinopathy of Prematurity to Improve Care 2 and School Age Follow on Study), which is not on this map. Cited by 56 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Analyzing Retinal Microanatomy in Retinopathy of Prematurity to Improve Care 2 and School Age Follow on Study (BabySTEPS2)
Who cites it
56 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.
- Guideline
- Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.Radiology. Artificial intelligence · 2024Trial
- Application of a Quantitative Vascular Severity Score in Retinopathy of Prematurity in the United States and India: New Insights Into Disease Epidemiology and Pathophysiology.American journal of ophthalmology · 2026Article
- Impact of image enhancement on grading agreement of plus disease features in retinopathy of prematurity.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Leveraging deep learning to infer continuous predictions from ordinal labels in medical imaging.PLOS digital health · 2026Article
- Automated Feature Segmentation of Ultra-Widefield OCT Images.Ophthalmology science · 2026Article
- A Novel Chaos-inspired Artificial Intelligence-based Model for Keratoconus Prediction.Journal of ophthalmic & vision research · 2026Article
- OCT-Derived Quantitative Measurement of Extent of Vascularization ("Zone") in Retinopathy of Prematurity.Ophthalmology science · 2026Article
- External validation of an artificial intelligence-based model for retinopathy of prematurity screening using Phoenix ICON retinal images.Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus · 2025Article
- Does field of view matter? Assessing its impact on Plus disease diagnosis in retinopathy of prematurity.International journal of retina and vitreous · 2025Article
- SmartPlus: a computer-based image analysis method to predict continuous-valued vascular abnormality index in Retinopathy of Prematurity.International journal of retina and vitreous · 2025Article
- Association between retinal vascular fractal dimensions and retinopathy of prematurity: an AI-assisted retrospective case-control study.International ophthalmology · 2025Article
- Computer-aided detection of retinopathy of prematurity severity assessment via vessel tortuosity measurement in preterm infants' fundus images.Eye (London, England) · 2024Article
- P Score: A Reference Image-Based Clinical Grading Scale for Vascular Change in Retinopathy of Prematurity.Ophthalmology · 2024Article
- Use of an Artificial Intelligence-Generated Vascular Severity Score Improved Plus Disease Diagnosis in Retinopathy of Prematurity.Ophthalmology · 2024Article
- Ocular blood flow in preterm neonates.Scientific reports · 2024Article
- Automated diagnosis of plus disease in retinopathy of prematurity using quantification of vessels characteristics.Scientific reports · 2024Article
- Retinal blood flow velocities in infants with retinopathy of prematurity after intravitreal administration of bevacizumab.European journal of ophthalmology · 2024Observational
- Article
- Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study.The Lancet. Digital health · 2023Article
Corrections and comments
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Authors and funding
20 authors at 10 institutions in 2 countries.
Funding
Abstract
purposeTo identify patterns of interexpert discrepancy in plus disease diagnosis in retinopathy of prematurity (ROP).
designWe developed 2 datasets of clinical images as part of the Imaging and Informatics in ROP study and determined a consensus reference standard diagnosis (RSD) for each image based on 3 independent image graders and the clinical examination results. We recruited 8 expert ROP clinicians to classify these images and compared the distribution of classifications between experts and the RSD.
participantsEight participating experts with more than 10 years of clinical ROP experience and more than 5 peer-reviewed ROP publications who analyzed images obtained during routine ROP screening in neonatal intensive care units.
methodsExpert classification of images of plus disease in ROP.
main outcome measuresInterexpert agreement (weighted κ statistic) and agreement and bias on ordinal classification between experts (analysis of variance [ANOVA]) and the RSD (percent agreement).
resultsThere was variable interexpert agreement on diagnostic classifications between the 8 experts and the RSD (weighted κ, 0-0.75; mean, 0.30). The RSD agreement ranged from 80% to 94% for the dataset of 100 images and from 29% to 79% for the dataset of 34 images. However, when images were ranked in order of disease severity (by average expert classification), the pattern of expert classification revealed a consistent systematic bias for each expert consistent with unique cut points for the diagnosis of plus disease and preplus disease. The 2-way ANOVA model suggested a highly significant effect of both image and user on the average score (dataset A: P < 0.05 and adjusted R
conclusionsThere is wide variability in the classification of plus disease by ROP experts, which occurs because experts have different cut points for the amounts of vascular abnormality required for presence of plus and preplus disease. This has important implications for research, teaching, and patient care for ROP and suggests that a continuous ROP plus disease severity score may reflect more accurately the behavior of expert ROP clinicians and may better standardize classification in the future.
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Registered trials
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.