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Development and future deployment of a five-year allograft survival model for kidney transplantation.

Development and future deployment of a five-year allograft survival model for kidney transplantation.

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DuBay DA1Su Z2Morinelli TA1Baliga P1Rohan V1Bian J2Northrup D3Pilch N4Rao V1Srinivas TR5Mauldin PD2Taber DJ1,6.

Author information:

  1. Department of Surgery, Medical University of South Carolina, Charleston, SC, USA.
  2. Division of General Internal Medicine and Geriatrics, Medical University of South Carolina, Charleston, SC, USA.
  3. Office of the Chief Information Officer, Medical University of South Carolina, Charleston, SC, USA.
  4. Department of Clinical Pharmacy and Outcomes Sciences, College of Pharmacy, Medical University of South Carolina, Charleston, SC, USA.
  5. Intermountain Transplant Services, Salt Lake City, UT.
  6. Department of Pharmacy, Ralph H Johnson VAMC, Charleston, SC, USA.

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

METHODS: We performed a ten-year retrospective cohort study of adult kidney transplant recipients (n=1,747). 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-year graft survival model.

RESULTS: 1,439 met eligibility; 265 (18.4%) of which 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, anemia, lower eGFR peak, increased tacrolimus variability, rejection, and readmissions. This Big Data analysis generated a 5-year graft loss model with an 82% predictive capacity, vs 66% using baseline United Network of Organ Sharing data alone.

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

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DOI: 10.1111/nep.13488
PMID: 30198104