Development and future deployment of a 5 years allograft survival model for kidney transplantation

Nephrology (Carlton). 2019 Aug;24(8):855-862. doi: 10.1111/nep.13488. Epub 2019 Apr 30.


Aim: Identifying kidney transplant patients at highest risk for graft loss prior to loss may allow for effective interventions to improve 5 years survival.

Methods: We performed a 10 years retrospective cohort study of adult kidney transplant recipients (n = 1747). We acquired data from electronic health records, United Network of Organ Sharing, social determinants of health, natural language processing data extraction, and real-time capture of dynamically evolving clinical data obtained within 1 year of transplant; from which we developed a 5 years graft survival model.

Results: Total of 1439 met eligibility; 265 (18.4%) of them experienced graft loss by 5 years. Graft loss patients were characterized by: older age, being African-American, diabetic, unemployed, smokers, having marginal donor kidneys and cardiovascular comorbidities. Predictive dynamic variables included: low mean blood pressure, higher pulse pressures, higher heart rate, anaemia, lower estimated glomerular filtration rate peak, increased tacrolimus variability, rejection and readmissions. This Big Data analysis generated a 5 years graft loss model with an 82% predictive capacity, versus 66% using baseline United Network of Organ Sharing data alone.

Conclusion: Our analysis yielded a 5 years graft loss model demonstrating superior predictive capacity compared with United Network of Organ Sharing data alone, allowing post-transplant individualized risk-assessed care prior to transitioning back to community care.

Keywords: data analysis; decision support technique; graft survival; kidney; transplant.

MeSH terms

  • Adult
  • Cohort Studies
  • Female
  • Forecasting
  • Graft Rejection / epidemiology
  • Graft Rejection / prevention & control
  • Graft Survival*
  • Humans
  • Kidney Transplantation*
  • Male
  • Middle Aged
  • Models, Statistical*
  • Retrospective Studies
  • Risk Assessment
  • Time Factors
  • Transplantation, Homologous