ArticleAmerican journal of nephrology2025
Sociodemographic Barriers to Starting the Kidney Transplantation Evaluation Process and Waitlisting in the Ohio River Valley.
Article in American journal of nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed.
- Leveraging Natural Language Processing to Identify Variation in Kidney Transplant Access.Kidney international reports · 2026Article
- Gaps in Dialysis Staff Knowledge of the Kidney Transplantation Process.Kidney international reports · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
introductionIndividuals with end-stage kidney disease face barriers and delays in access to kidney transplantation, but little is known about access before waitlisting due to the lack of national data on pre-waitlisting measures. The Early Steps to Transplant Access Registry (E-STAR) captures referral and evaluation data in four US regions, including the Ohio River Valley, and this study utilizes E-STAR data to describe sociodemographic factors associated with starting the transplant evaluation and waitlisting in this region.
methodsAdults referred to a transplant center for evaluation within the Ohio River Valley during 2015-2021 and captured within E-STAR were included. Linked E-STAR, US Renal Data System, and American Community Survey data were used to assess the association between sociodemographic (age, sex, race or ethnicity, insurance status), clinical, and neighborhood factors and time from referral to evaluation start and time from evaluation start to waitlisting by Cox proportional hazards analyses.
resultsAmong 15,673 referred adults, the mean age was 55 years, and the majority were male (61.4%) and had public insurance (56.6%), while 21.3% were preemptively referred. Compared to individuals aged 18-29, all other age groups had a lower likelihood of starting the evaluation in the adjusted model. Black adults (vs. White; adjusted hazard ratio: 0.89 [95% CI: 0.81-0.98]), and those with Medicaid or Medicare were less likely to start the evaluation (vs. employer-sponsored, 0.58 [0.50-0.66]; 0.66 [0.66-0.82], respectively). Among individuals who started the evaluation, those with Black (vs. White) race, and Medicaid or Medicare (vs. employer-sponsored) were less likely to be waitlisted in the adjusted analysis.
conclusionAssociations between age, sex, race, and economic characteristics and access to evaluation start and waitlisting were observed. Future research investigating underlying causes and points of intervention in this region is warranted.
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