Hemodialysis Patient Death Prediction Using Logistic Regression

Abstract

Hemodialysis is a procedure for cleaning the blood from the waste products of the body’s metabolism. this is one of modality to treat end stage kidney disease. There are two main classifications of this disease, namely acute kidney failure and chronic kidney failure. Kidney failure occurs when kidney damage is severe enough or lasts a long time so that the disease is generally the final stage of kidney disease. Dialysis is performed on patients with kidney failure, both acute kidney failure and chronic kidney failure. This study is aimed to predict the mortality risk of hemodialysis patients. The Taiwanese hemodialysis center enrolled a total of 665 hemodialysis patients. The prediction is based on Logistic Regression. Compared with K-Nearest Neighbor, linear discriminant, Tree, and ensemble, Logistic Regression performed better. As for related medical variables like parathyroid surgery, urea reduction ratio, etc., they play a much smaller role in mortality risk factors than diabetes and cardiovascular disease.