ArticleTranslational vision science & technology2022
Cohort Study of Race/Ethnicity and Incident Primary Open-Angle Glaucoma Characterized by Autonomously Determined Visual Field Loss Patterns.
Article in Translational vision science & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Inequities in glaucoma research: an analysis of Cochrane systematic reviews and randomized trials.Journal of clinical epidemiology · 2025Pooled it
- A Whole-Genome Sequence Genome-Wide Association Study inOphthalmology science · 2026Article
- Ab Interno Minimally Invasive Glaucoma Surgery Effectiveness in Black Patients: An IRIS Registry Study.Journal of glaucoma · 2026Observational
- Dual-Level Pattern Tree for Visual Field Improves Glaucoma Progression and Polygenic Risk Prediction.Translational vision science & technology · 2025Article
- Genetic Risk for Open-Angle Glaucoma Subtypes Is Associated with Specific Visual Field Defect Classes.Ophthalmology · 2025Article
- Understanding Glaucoma: Why it Remains a Leading Cause of Blindness Worldwide.Klinische Monatsblatter fur Augenheilkunde · 2025Review
- Lipids and lipid regulators in intraocular pressure homeostasis.Current opinion in pharmacology · 2025Review
- Equitable artificial intelligence for glaucoma screening with fair identity normalization.NPJ digital medicine · 2025Article
- The Association Between Intermittent Fasting and Glaucoma.Journal of glaucoma · 2025Article
- Feasibility of in-home monitoring for people with glaucoma: the I-TRAC mixed-methods study.Health technology assessment (Winchester, England) · 2024Article
- Impact of Demographics on Regional Visual Field Loss and Deterioration in Glaucoma.Translational vision science & technology · 2024Article
- Features Associated with Visible Lamina Cribrosa Pores in Individuals of African Ancestry with Glaucoma: Primary Open-Angle African Ancestry Glaucoma Genetics (POAAGG) Study.Vision (Basel, Switzerland) · 2024Article
- Multi-Dataset Comparison of Vision Transformers and Convolutional Neural Networks for Detecting Glaucomatous Optic Neuropathy from Fundus Photographs.Bioengineering (Basel, Switzerland) · 2023Article
- Identifying, Understanding, and Addressing Disparities in Glaucoma Care in the United States.Translational vision science & technology · 2023Article
- Revisiting Retinal Degeneration Hallmarks: Insights from Molecular Markers and Therapy Perspectives.International journal of molecular sciences · 2023Review
- Reverse translation of artificial intelligence in glaucoma: Connecting basic science with clinical applications.Frontiers in ophthalmology · 2023Article
- It's Time We Reform Our Perspectives on Race and Glaucoma.Translational vision science & technology · 2022Article
- Artificial Intelligence Models to Identify Patients at High Risk for Glaucoma Using Self-reported Health Data in a United States National Cohort.Ophthalmology scienceArticle
- Artificial Intelligence Models to Identify Patients with High Probability of Glaucoma Using Electronic Health Records.Ophthalmology scienceArticle
- Application of artificial intelligence in glaucoma care: An updated review.Taiwan journal of ophthalmologyReview
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Purpose: We evaluated racial/ethnic differences in primary open-angle glaucoma (POAG) defined by machine-learning-derived regional visual field (VF) loss patterns. Methods: Participants (N = 209,036) from the Nurses' Health Study (NHS; 1980-2018), Nurses' Health Study II (NHS2; 1989-2019), and Health Professionals Follow-Up Study (HPFS; 1986-2018) who were ≥40 years of age and free of glaucoma were followed biennially. Incident POAG cases (n = 1946) with reproducible VF loss were confirmed with medical records. Total deviation information from the earliest reliable glaucomatous VF for each POAG eye (n = 2564) was extracted, and machine learning analyses were used to identify optimal solutions ("archetypes") for regional VF loss patterns. Each POAG eye was assigned a VF archetype based on the highest weighting coefficient. Multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using per-eye Cox proportional hazards models. Results: We identified 14 archetypes: four representing advanced loss patterns, nine of early loss, and one of no VF loss. Compared to non-Hispanic whites, black participants had higher risk of early VF loss archetypes (HR = 1.98; 95% CI, 1.48-2.66) and even higher risk for advanced loss archetypes (HR = 6.17; 95% CI, 3.69-10.32; P-contrast = 0.0002); no differences were observed for Asians or Hispanic whites. Hispanic white participants had significantly higher risks of POAG with paracentral defects and advanced superior loss; black participants had significantly higher risks of all advanced loss archetypes and three early loss patterns, including paracentral defects. Conclusions: Blacks, compared to non-Hispanic whites, had higher risks of POAG with early central and advanced VF loss. Translational Relevance: In POAG, risks of VF loss regional patterns derived from machine learning algorithms showed racial differences.
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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.