@mastersthesis{10336/25254,
author = {pinto, jessica},
url = {https://repository.urosario.edu.co/handle/10336/25254},
abstract = {Kidney transplantation is the treatment of choice in patients with chronic kidney disease in advanced stages; however, there are factors that can be associated with the loss of the graft and the death of the patient; Identifying the factors and generating prediction models is of great clinical utility in the monitoring of kidney transplant patients. Objective: To determine the factors associated with graft loss and mortality of the kidney transplant patient. Methodology: A retrospective analytical study of a historical cohort was carried out in a solid organ transplant center in Colombia. Kidney transplant patients were included between July 22, 2008 and May 31, 2019. Overall survival was estimated with the Kaplan-Meier method at 1, 5 and 10 years and survival curves were compared for donor type subgroups; living vs cadaveric donor. A competing risk analysis was performed taking death into account as a competing risk of graft loss. The subdistribution hazard ratio (sHR) was estimated and the statistically significant variables were taken into account for the estimation of predictive models of graft loss and death, and finally the internal validation of the models was carried out. Results: In the follow-up period, 1,634 kidney transplants were performed in 1,621 patients and 1,454 patients were included in the study. Of the total population, 868 (59.7%) were men and 586 (40.3%) were women; the mean age was 43.58 years (SD +/- 13.21) and a range of 18 - 77 years. Predictive variables for 5-year renal graft loss were: the history of stroke (sHR 9.3 95% CI 1.77 - 48.76; p 0.00), the reactive panel of qualitative class II antibody (sHR 0.56 95% CI 0.43 - 0.71 ; p 0.00), the number of renal biopsies (sHR 1.3 95% CI 1.11 - 1.53; p 0.00), polyomavirus nephropathy (sHR 4.76 95% CI 2.22 - 10.19; p 0.00), acute cell rejection (sHR 2.99 IC 95% 1.45-6.18; p 0.00) and creatinine 12 months after kidney transplantation (sHR 1.80 95% CI 1.59 - 2.03; p 0.00). For death at 5 years; age at transplant (sHR 1.04 95% CI 1.02 - 1.05; p 0.00), living donor transplant (sHR 0.42 95% CI 0.24 - 0.72; p 0.00), range body mass index at time of transplant obesity (sHR 2.11 95% CI 1.14 - 3.89; p 0.01) and cytomegalovirus disease (sHR 2.45 CI eleven 95% 1.48 - 4.06; p 0.00) were found as the predictive variables of death of the kidney transplant patient. Conclusions: The risk stratification and the generation of prediction models based on the identification of the factors associated with graft loss and death in our population is very useful for daily practice in kidney transplantation. The history of stroke, the qualitative class II antibody reactive panel, the number of kidney biopsies, acute cell rejection and creatinine at 12 months were found as predictive variables of loss of the renal graft at 5 years; and age at the time of transplantation, living donor transplant, body mass index in the obesity range at the time of transplantation, and cytomegalovirus disease were found as predictors of death in the 5-year-old kidney transplant patient. External validation of these models is required.},
keywords = {Riesgos competitivos},
keywords = {Trasplante renal},
keywords = {Sobrevida del injerto renal},
keywords = {Enfermedad injerto-huésped},
title = {Factores asociados a la pérdida del injerto renal y mortalidad en Colombiana de Trasplantes entre el 2008– 2019},
publisher = {Universidad del Rosario},
keywords = {Kidney transplantation},
keywords = {Graft survival},
keywords = {Registry-based studies},
keywords = {Retrospective studies},
keywords = {Competing risks.},
}