Unknown

Dataset Information

0

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


ABSTRACT: 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.

SUBMITTER: DuBay DA 

PROVIDER: S-EPMC6408984 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

DuBay Derek A DA   Su Zemin Z   Morinelli Thomas A TA   Baliga Prabhakar P   Rohan Vinayak V   Bian John J   Northrup David D   Pilch Nicole N   Rao Vinaya V   Srinivas Titte R TR   Mauldin Patrick D PD   Taber David J DJ  

Nephrology (Carlton, Vic.) 20190430 8


<h4>Aim</h4>Identifying kidney transplant patients at highest risk for graft loss prior to loss may allow for effective interventions to improve 5 years survival.<h4>Methods</h4>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 obt  ...[more]

Similar Datasets

| S-EPMC3083491 | biostudies-literature
| S-EPMC9641958 | biostudies-literature
| S-EPMC8514869 | biostudies-literature
| S-EPMC6585795 | biostudies-literature
2024-11-04 | GSE280787 | GEO
| S-EPMC7015097 | biostudies-literature
| S-EPMC9745471 | biostudies-literature
| S-EPMC11335780 | biostudies-literature
| S-EPMC5642346 | biostudies-literature
| S-EPMC9510367 | biostudies-literature