Evidence map›Paper›PMID 38959998›Full record

ArticleOphthalmology. Glaucoma

Social Factors Associated with the Risk of Glaucoma Suspect Conversion to Glaucoma: Analysis of the Nationwide All of Us Program.

Jo-Hsuan Wu, Willam Halfpenny, Jennifer Bu, Manreet Brar, Robert N Weinreb, Sally L Baxter

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Ophthalmology. Glaucoma. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

6 authors.

Jo-Hsuan WuDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California; Health Department of Biomedical Informatics, University of California San Diego, La Jolla, California; Hamilton Glaucoma Center, Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California, San Diego, La Jolla, California.
Willam HalfpennyDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California; Health Department of Biomedical Informatics, University of California San Diego, La Jolla, California.
Jennifer BuDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California; Health Department of Biomedical Informatics, University of California San Diego, La Jolla, California.
Manreet BrarDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California; Health Department of Biomedical Informatics, University of California San Diego, La Jolla, California.
Robert N WeinrebDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California; Hamilton Glaucoma Center, Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California, San Diego, La Jolla, California.
Sally L BaxterDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California; Health Department of Biomedical Informatics, University of California San Diego, La Jolla, California; Hamilton Glaucoma Center, Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California, San Diego, La Jolla, California. Electronic address: s1baxter@health.ucsd.edu.

Funding

Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7M
Precision Medicine Initiative Cohort Program BiobankU24OD023121 · OD · MAYO CLINIC ROCHESTER · PI CEKANOVA, MARIA, CICEK, MINE · 2016 to 2024
$185.5M
Enhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7M
Adaptive Platform for Personalized EngagementU24OD023163 · OD · VIGNET, INC. · PI JAIN, PRADUMAN · 2017 to 2020
$102.6M
UC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3M
University of Arizona-Banner Health All of Us Research Program OT2OD026549 · OD · UNIVERSITY OF ARIZONA · PI MORENO, FRANCISCO A, REIMAN, ERIC MICHAEL · 2018 to 2023
$78.9M
California Precision Medicine Research Program ConsortiumOT2OD026552 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANTON-CULVER, HODA A, OHNO-MACHADO, LUCILA · 2018 to 2023
$73.4M
All of Us PennsylvaniaOT2OD026554 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E, VISWESWARAN, SHYAM · 2018 to 2023
$72.1M
New York City Consortium for Precision MedicineOT2OD026556 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BIER, LOUISE E, GHARAVI, ALI G · 2018 to 2023
$67.3M
SouthEast Enrollment Center (SEEC) OT2OD026551 · OD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, COLON, VIVIAN · 2018 to 2023
$62.8M
Southern All of Us NetworkOT2OD026548 · OD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI FOUAD, MONA N., KORF, BRUCE R · 2018 to 2023
$60.5M
Illinois Precision Medicine Consortium OT2OD026557 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI AHSAN, HABIBUL, ARGOS, MARIA · 2018 to 2023
$60.5M
NCATS NIH HHS UL1 TR001442NEI NIH HHS P30 EY022589NIH HHS DP5 OD029610NIH HHS OT2 OD023205NIH HHS OT2 OD023206NIH HHS OT2 OD025276NIH HHS OT2 OD025277NIH HHS OT2 OD025315NIH HHS OT2 OD025337NIH HHS OT2 OD026548NIH HHS OT2 OD026549NIH HHS OT2 OD026550NIH HHS OT2 OD026551NIH HHS OT2 OD026552NIH HHS OT2 OD026553NIH HHS OT2 OD026554NIH HHS OT2 OD026555NIH HHS OT2 OD026556NIH HHS OT2 OD026557NIH HHS U24 OD023121NIH HHS U24 OD023163NIH HHS U24 OD023176NIH HHS U2C OD023196NIMHD NIH HHS R01 MD014850NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

purposeTo examine social factors associated with the 5-year risk of glaucoma suspects (GS) converting to open-angle glaucoma (OAG).

designRetrospective cohort analysis. SUBJECTS: We screened for participants diagnosed with GS in the All of Us database. Cases that converted to OAG within 5 years of GS diagnosis (the "conversion group") were compared with control cases that did not convert.

methodsDemographic, socioeconomic and health-care utilization data of the cases were extracted and compared between the conversion group and the control group. Multivariable Cox proportional hazards modeling was used to identify potential factors associated with the risk of conversion.

main outcome measuresHazard ratios (HRs) of significant factors associated with the risk of conversion.

resultsA total of 5274 GS participants were identified, and 786 (15%) cases converted to OAG within 5-year follow-up. The 2 groups showed significant differences in age, race, gender, employment status, income/education level, history of intraocular surgery, and health-care utilization patterns. In the multivariable model, African American/Black race (HR : 1.70 [95% confidence interval (CI), 1.44-2.00]), older age at GS diagnosis (1.17 [95% CI, 1.09-1.25]), male gender (1.30 [95% CI, 1.13-1.50], no history of recreational drug use (1.23 [1.07-1.42]), history of intraocular surgery (1.60 [95% CI, 1.02-1.53]), and having more reasons for delayed health-care access (2.27 [95% CI, 1.23-4.18]) were associated with a greater hazard of conversion, while being employed (0.71 [95% CI, 0.60-0.86]) was associated with a smaller hazard of conversion (P < 0.05 for all).

conclusionsSeveral social factors were associated with the conversion from GS to OAG, which may help to identify patients at higher risk of disease progression. Future studies are needed to examine the basis for these findings and the potential interventions that could address them. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Glaucoma, Open-AngleIntraocular PressureAgedDisease ProgressionFemaleFollow-Up StudiesHumansIncidenceMaleMiddle AgedOcular HypertensionRetrospective StudiesRisk FactorsSocioeconomic FactorsUnited StatesAll of Us programGlaucoma suspectHealth-care access and utilizationSocial determinants of healthSocioeconomic factors

Identifiers

PMID38959998
PMCPMC11585445

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