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Effect of age and care organization on sources of variation in kidney transplant waiting list registration
Authors:Cécile Couchoud  Florian Bayer  Muriel Rabilloud  Carole Ayav  Sahar Bayat  Clemence Bechade  Philippe Brunet  Sebastien Gomis  Emilie Savoye  Olivier Moranne  Thierry Lobbedez  Rene Ecochard  the REIN registry
Affiliation:1. REIN registry, Agence de la biomédecine, Saint-Denis La Plaine, France;2. CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique Santé, Université Lyon I, Villeurbanne, France

Service de Biostatistique, Hospices Civils de Lyon, Lyon, France;3. INSERM, CIC, Epidémiologie Clinique, CHRU-Nancy, Nancy, France;4. EHESP, REPERES (Recherche en pharmaco-épidémiologie et recours aux soins) – EA 7449, Université Rennes, Rennes, France;5. Nephrology Department, Caen University Hospital, Caen, France;6. Nephrology Department, APHM University Hospital, Marseille, France;7. Nephrology Department, Lille University Hospital, Lille, France;8. Direction Prélèvement Greffe Organes-Tissus, Agence de la biomédecine, Saint-Denis La Plaine, France;9. Nephrology-Dialysis-Apheresis Department, Nîmes University Hospital, Nîmes, France

Abstract:Despite national guidelines, medical practices and kidney transplant waiting list registration policies may differ from one dialysis/transplant unit to another. Benefit risk assessment variations, especially for elderly patients, have also been described. The aim of this study was to identify sources of variation in early kidney transplant waiting list registration in France. Among 16 842 incident patients during the period 2016–2017, 4386 were registered on the kidney transplant waiting list at the start of, or during the first year after starting, dialysis (26%). We developed various log-linear mixed effect regression models on three levels: patients, dialysis networks, and transplant centers. Variability was expressed as variance from the random intercepts (± standard error). Although patient characteristics have an important impact on the likelihood of registration, the overall magnitude of variability in registration was low and shared by dialysis networks and transplant centers. Between-transplant center variability (0.23 ± 0.08) was 1.8 higher than between-dialysis network variability (0.13 ± 0.004). Older age was associated with a lower probability of registration and greater variability between networks (0.04, 0.20, & 0.93 in the 18–64, 65–74, and 75–84 age groups). Targeted interventions should focus on elderly patients and/or certain regions with greater variability in waiting list access.
Keywords:
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