Evidence map›Paper›PMID 33214495›Full record

ArticleTransplantation2020

Does Sex, Race, and the Size of a Kidney Transplant Candidate's Social Network Affect the Number of Living Donor Requests? A Multicenter Social Network Analysis of Patients on the Kidney Transplant Waitlist.

Avrum Gillespie, Heather M Gardiner, Edward L Fink, Peter P Reese, Crystal A Gadegbeku, Zoran Obradovic

Registry-linked trialAbstract readComparative StudyMulticenter Study
In one paragraph

Article in Transplantation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06182475 (Increasing Equity in Live Donor Kidney Transplantation Through Effective Patient-Provider Communication), which is not on this map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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.

NCT06182475 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Increasing Equity in Live Donor Kidney Transplantation Through Effective Patient-Provider Communication

TypeinterventionalSponsorTemple UniversityRan2026 to 2027Enrolled70ConditionsKidney Disease, Chronic, End Stage Renal Disease, Kidney ReplacementArmsEPPComm Provider Training
3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Evaluation via simulation of statistical corrections for network nonindependence.Health services & outcomes research methodology · 2024
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Impact of having potential living donors on ethnic/racial disparities in access to kidney transplantation.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2022
    Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. 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.

Avrum GillespieDivision of Nephrology, Hypertension, and Kidney Transplantation, Department of Medicine, Lewis Katz School of Medicine, Temple University, Philadelphia, PA.
Heather M GardinerDepartment of Social & Behavioral Sciences, College of Public Health, Temple University, Philadelphia, PA.
Edward L FinkDepartment of Communication and Social Influence, Klein College of Media and Communication, Temple University, Philadelphia, PA.
Peter P ReeseRenal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Crystal A GadegbekuDivision of Nephrology, Hypertension, and Kidney Transplantation, Department of Medicine, Lewis Katz School of Medicine, Temple University, Philadelphia, PA.
Zoran ObradovicCenter for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA.

Funding

Social Network Analysis and Renal Education to Promote Transplantation (SNARE Transplant)K23DK111943 · NIDDK · TEMPLE UNIV OF THE COMMONWEALTH · PI GILLESPIE, AVRUM · 2017 to 2021
$904k
AHRQ HHS K01 HS018113AHRQ HHS R03 HS021312NIDDK NIH HHS K23 DK111943
6 · The paper itself

Abstract

backgroundA kidney transplant candidate's social network serves as a pool of potential living donors. Sex and racial differences in network size, network strength, and living donor requests may contribute to disparities in living donor kidney transplantation.

methodsIn this multicenter cross-sectional study, we performed an egocentric network analysis via a telephone survey of 132 waitlisted candidates (53% female and 69% Black) to identify demographic and network factors associated with requesting living kidney donations.

resultsFemale participants made requests to more network members than male participants: incidence rate ratio (IRR) 1.95, 95% confidence interval (CI) [1.24-3.06], P < 0.01. Black participants tended to make more requests than whites (IRR 1.65, 95% CI [0.99-2.73], P = 0.05). The number of requests increased with the size of the network (IRR 1.09, 95% CI [1.02-1.16], P = 0.01); however, network size did not differ by sex or race. Network members who provided greater instrumental support to the candidates were most likely to receive a request: odds ratio 1.39, 95% CI [1.08-1.78], P = 0.01.

conclusionsTransplant candidates' networks vary in size and in the number of requests made to the members. Previously observed racial and sex disparities in living donor kidney transplantation do not appear to be related to network size or to living donation requests, but rather to the network members themselves. Future living donor interventions should focus on the network members and be tailored to their relationship with the candidate.

Indexed as

Kidney TransplantationSocial NetworkingSocial SupportWaiting ListsAdultFamilyFemaleFriendsHumansInterpersonal RelationsKidney Failure, ChronicLiving DonorsMaleMiddle AgedRace FactorsRetrospective Studies

Identifiers

PMID33214495
PMCPMC8855970

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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.