ArticleKidney medicine2023
Dialysis Patients' Social Networks and Living Donation Offers.
Article in Kidney medicine, 2023. 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
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.
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.
Who cites it
2 citing papers in PubMed.
- A Cross-Sectional Social Network Analysis of Decision-Making About Recruiting a Living Donor for Kidney Transplantation.Kidney medicine · 2025Article
- Expanding Access to Living Donor Kidney Transplants Through Social Networks.Kidney medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Rationale & Objective: Most living kidney donors are members of a hemodialysis patient's social network. Network members are divided into core members, those strongly connected to the patient and other members; and peripheral members, those weakly connected to the patient and other members. We identify how many hemodialysis patients' network members offered to become kidney donors, whether these offers were from core or peripheral network members, and whose offers the patients accepted. Study Design: A cross-sectional interviewer-administered hemodialysis patient social network survey. Setting & Participants: Prevalent hemodialysis patients in 2 facilities. Predictors: Network size and constraint, a donation from a peripheral network member. Outcomes: Number of living donor offers, accepting an offer. Analytical Approach: We performed egocentric network analyses for all participants. Poisson regression models evaluated associations between network measures and number of offers. Logistic regression models determined the associations between network factors and accepting a donation offer. Results: The mean age of the 106 participants was 60 years. Forty-five percent were female, and 75% self-identified as Black. Fifty-two percent of participants received at least one living donor offer (range 1-6); 42% of the offers were from peripheral members. Participants with larger networks received more offers (incident rate ratio [IRR], 1.26; 95% CI, 1.12-1.42; Limitations: A small sample of only hemodialysis patients. Conclusions: Most participants received at least one living donor offer, often from peripheral network members. Future living donor interventions should focus on both core and peripheral network members.
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Registered trials
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