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Peter Reese

Professor

Vanderbilt University Medical Center
Country flagUnited States

Research Interests

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Articles (17)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Key Points Hemodialysis clinic social networks spread attitudes and behaviors toward kidney transplants. Identifying and characterizing influential patients is a first step in future hemodialysis clinic social network interventions to promote kidney transplantation. Background Hemodialysis clinics help develop patient social networks that may spread kidney transplant (KT) attitudes and behaviors. Identifying influential social network members is an important first step to increase KT rates. We mapped the social networks of two hemodialysis facilities to identify which patients were influential using in-degree centrality as a proxy for popularity and influence. Methods In this cross-sectional study, we performed a sociocentric social network analysis of patients on hemodialysis in two geographically and demographically different hemodialysis facilities. Statistical and social network analyses were performed using R statistical software. Results More patients at facility 1 ( N =71) were waitlisted/evaluating living donor KT (50.7% versus 20.0%, P = 0.021), considered KT as very important (70.4% versus 45.0%, P = 0.019), and knew people who received a successful KT (1.0 versus 0.0, P = 0.003). Variables predicting relationship formation at facility 1 were the same shift ( β =1.87, 95% confidence interval [CI] [1.19 to 2.55]; P < 0.0001), same sex ( β =0.51, 95% CI [0.01 to 1.00]; P = 0.045), younger age ( β =−0.03, 95% CI [−0.05 to −0.01]; P = 0.004), different lengths of time on hemodialysis ( β =−0.49, 95% CI [−0.86 to −0.12]; P = 0.009), and knowing more people who received a successful KT ( β =0.12, 95% CI [0.03 to 0.21]; P = 0.009). Predictive variables at facility 2 ( N =40) were the same race ( β =2.52, 95% CI [0.39 to 4.65]; P = 0.021) and knowing fewer people with successful KT ( β =−0.92, 95% CI [−1.82 to −0.02]; P = 0.045). In-degree centrality was higher at facility 1 (1.1±1.2) compared with facility 2 (0.6±0.9). Conclusions Social networks differed between the hemodialysis clinics in structure and prevalent transplant attitudes. Influential patients at facility 1 (measured by in-degree centrality) had positive attitudes toward KT, whereas influential patients at facility 2 had negative attitudes.

Year:

2024

Year:

2024

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2024

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2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (19)

Harald Schmidt

Assistant Professor, Clinician-Educator

University of Pennsylvania

UNITED STATES
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Matthew Cooper

Medical College of Wisconsin

UNITED STATES
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John Friedewald

Professor

Northwestern University Feinberg School of Medicine

UNITED STATES
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Vineeta Kumar

Professor of Medicine, Endowed Professor of Transplant Nephrology

The University of Alabama at Birmingham School of Medicine

UNITED STATES
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Benjamin Lok

Professor

University of Florida

UNITED STATES
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Andrew Adams

Professor

University of Minnesota

UNITED STATES
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Ciara Shaver

Assistant Professor

Vanderbilt University Medical Center

UNITED STATES
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Angie Gabriela Nishio Lucar

Associate Professor

University of Virginia

UNITED STATES
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Mona D. Doshi

University of Michigan

UNITED STATES
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Neetika Garg

University of Wisconsin-Madison

UNITED STATES
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Michael S. Wolf

Northwestern University

UNITED STATES
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Vishnu Potluri

University of Pennsylvania

UNITED STATES
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Matthew Bacchetta

Vanderbilt University Medical Center

UNITED STATES
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Avrum Gillespie

Associate Professor of Medicine

Temple University Hospital

UNITED STATES
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Catherine R. Butler

University of Washington

UNITED STATES
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Xingxing Cheng

Stanford University Medical Center

UNITED STATES
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Allan Kirk

Duke University

UNITED STATES
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Emily Vail

Assistant professor

University of Pennsylvania

UNITED STATES
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Heather Thiessen Philbrook

Johns Hopkins University

UNITED STATES
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