Predicting Kidney Transplantation Outcomes from Donor and Recipient Characteristics at Time Zero: Development of a Mobile Application for Nephrologists

• Published in: Journal of clinical medicine Vol. 13; no. 5; p. 1270
• Main Authors: Pérez Valdivia, Miguel Ángel, Calvillo Arbizu, Jorge, Portero Barreña, Daniel, Castro de la Nuez, Pablo, López Jiménez, Verónica, Rodríguez Benot, Alberto, Mazuecos Blanca, Auxiliadora, de Gracia Guindo, Mª Carmen, Bernal Blanco, Gabriel, Gentil Govantes, Miguel Ángel, Bedoya Pérez, Rafael, Rocha Castilla, José Luis
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.02.2024; MDPI
• Subjects: Age; Biopsy; Body mass index; Cardiovascular disease; Diabetes; Donations; graft failure; Hemodialysis; Ischemia; Kidney diseases; kidney transplantation; Kidney transplants; Kidneys; Life expectancy; Medical prognosis; mobile app; Mobile applications; Mobile communications networks; Organ donors; Organ transplant recipients; Patients; Peritoneal dialysis; predictive model; Prognosis; Regression analysis; survival prediction; Transplantation; Variables; Spain; United States > US; predictive model; survival prediction; graft failure; mobile app; kidney transplantation
• ISSN: 2077-0383; 2077-0383
• DOI: 10.3390/jcm13051270

(1) Background: We report on the development of a predictive tool that can estimate kidney transplant survival at time zero. (2) Methods: This was an observational, retrospective study including 5078 transplants. Death-censored graft and patient survivals were calculated. (3) Results: Graft loss was associated with donor age (hazard ratio [HR], 1.021, 95% confidence interval [CI] 1.018-1.024, < 0.001), uncontrolled donation after circulatory death (DCD) (HR 1.576, 95% CI 1.241-2.047, < 0.001) and controlled DCD (HR 1.567, 95% CI 1.372-1.812, < 0.001), panel reactive antibody percentage (HR 1.009, 95% CI 1.007-1.011, < 0.001), and previous transplants (HR 1.494, 95% CI 1.367-1.634, < 0.001). Patient survival was associated with recipient age (> 60 years, HR 5.507, 95% CI 4.524-6.704, < 0.001 vs. < 40 years), donor age (HR 1.019, 95% CI 1.016-1.023, < 0.001), dialysis vintage (HR 1.0000263, 95% CI 1.000225-1.000301, < 0.01), and male sex (HR 1.229, 95% CI 1.135-1.332, < 0.001). The C-statistics for graft and patient survival were 0.666 (95% CI: 0.646, 0.686) and 0.726 (95% CI: 0.710-0.742), respectively. (4) Conclusions: We developed a mobile app to estimate survival at time zero, which can guide decisions for organ allocation.