Machine learning approaches to analyse effect of ethnicity on outcomes following living kidney donation in UK
sunset in florence
PDF

Keywords

ethnicity
outcomes
kidney transplantation

How to Cite

Basker, S. (2020). Machine learning approaches to analyse effect of ethnicity on outcomes following living kidney donation in UK: BAPIOACI9-P05. The Physician, 6(2). https://doi.org/10.38192/1.6.2.9

Abstract

Poster presented at BAPIO National Conference, London. 2019

Peer reviewed by Subarna Chakravorty PhD & Sunil Daga PhD

Essential hypertension, End age, and deprivation index ranked as three most important variables in the risk of development of hypertension after donation. Logistic regression analysis showed that pre-existing essential hypertension, male gender, age at kidney donation, and low numbers of transplant providers are important risk factors for long term hypertension risk. In sub-analysis, we found that South Asian ethnicity and obesity are additional risk factors.

https://doi.org/10.38192/1.6.2.9
PDF

References

https://www.thephysician.uk/abstract-poster

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Copyright (c) 2020 Array