Abstract

Introduction: Kidney transplant (KT) has the highest survival rate amongst kidney replacement therapies (KRT). Objective: Analyze the incidence density of all-cause mortality in chronic kidney disease transplant-recipients and to identify covariables associated with higher risk of death. Methodology: Cohort study using medical records of 605 KT patients with seven years follow-up (2011-2018). Records with insufficient data or from patients with incomplete treatment were excluded. The variables analyzed were demographic, clinical and laboratory data, duration of KRT, type of donor, immunological compatibility, panel-reactive HLA-antibody, infections, and use of hypothermic perfusion machine (HPPM). Hazard ratio (HR) and incidence density of all-cause deaths were estimated. Results: 15 of 553 KT-recipients died during the follow-up. The survival in the first year post-KT was 98.0% and in the fifth year was 93.2%. The incidence density of deaths is 10/1,000 person-years. Variables pre- and post-KT related with higher death risk were allograft pyelonephritis ≥6-months and delayed graft function >4 weeks. Survival among KT-recipients with loss >5 mL/min/1.73m2/year in the estimated glomerular filtration rate (eGFR) were lower than the others (88% vs. 97%). Covariates associated with mortality post-transplant included pre-KT obesity, HPPM, allograft pyelonephritis, and new-onset diabetes after transplantation. Conclusion: The mortality post-KT is low in these population. Cox's modelling demonstrated that the decline in eGFR >5 mL/min/1.73m2/year, allograft pyelonephritis ≥6-months, pre-KT obesity, fasting blood glucose ≥126 mg/dL presented worst probability of survival. Rapid decline in eGFR reduces substantially the survival probability in these population.

Highlights

  • Kidney transplant (KT) has the highest survival rate amongst kidney replacement therapies (KRT)

  • Covariates associated with mortality post-transplant included pre-KT obesity, hypothermic perfusion machine (HPPM), allograft pyelonephritis, and new-onset diabetes after transplantation

  • Multivariate modelling demonstrated that the pre-KT obesity, use of MPPH, ICU up to six months post-KT, fasting blood glycose ≥ 126 mg/dL (≥ 6.99 mmol/L) or New-onset diabetes after transplantation (NODAT), and chronic kidney disease transplant recipients (CKD-T)-fast behavior were associated with a higher risk of death (Table 7)

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Summary

Introduction

Kidney transplantation (KT) is the kidney replacement therapy (KRT) with the longest survival rate amongst all the therapeutic options available. The survival of chronic kidney disease transplant recipients (CKD-T) has been increasing in recent decades, possibly due to advances in immunopharmacology and improved care (Wekerle et al, 2017), together with reduction of infections, early identification of acute T-cell mediated rejections (aTCMR) or acute antibody-mediated rejection (aABMR) (Ashby et al, 2017). The analysis of survival rates and the components of mortality-associated covariates are crucial in the planning and evaluation of CKD-T care (Djamali et al, 2006). 2. Methodology 2.1 Study design and database selection. Methodology 2.1 Study design and database selection This is a retrospective cohort study (Sampieri, Collado & Lucio, 2013) involving the follow-up of CKD-T outpatients from January 2011 to January 2018, accompanied in the post-kidney transplant follow-up clinic at the Real Hospital Português de Beneficência em Pernambuco (RHP/PE), Recife, Pernambuco, Brazil. Consent to participate was not necessary because only medical records were used without any contact with individual participants

Analysis of covariables
Statistical analysis
Description of the general characteristics of the population
Analysis of the survival function and characteristics related to death
Analysis of the eGFR and rapid progression behavior
Selection of the composition of covariates correlated to death
Main causes of death in kidney recipients-transplant
CKD-T fast-progressor behavior
New-onset diabetes after transplantation and pre-kidney transplant obesity
Hypothermic pulsatile perfusion preservation machine
Effectiveness of the prediction model
Final Considerations
Full Text
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