Development and future deployment of a five-year allograft survival model for kidney transplantation.
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- Department of Surgery, Medical University of South Carolina, Charleston, SC, USA.
- Division of General Internal Medicine and Geriatrics, Medical University of South Carolina, Charleston, SC, USA.
- Office of the Chief Information Officer, Medical University of South Carolina, Charleston, SC, USA.
- Department of Clinical Pharmacy and Outcomes Sciences, College of Pharmacy, Medical University of South Carolina, Charleston, SC, USA.
- Intermountain Transplant Services, Salt Lake City, UT.
- 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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