Abstract
A retrospective analysis of the improvement in the health condition of patients undergoing hemodialysis was done to understand the important factors that can affect malnutrition in these patients. In this study, data from patients who underwent hemodialysis between 2010 and 2015 in a regional hospital in Yunlin County were collected from the Taiwan Society of Nephrology-Kidney Transplantation database. A total of 1049 medical records from 300 patients with age over 20 and underwent hemodialysis were collected for this study. A decision tree C5.0 and logistic regression were used to identify 40 independent variables, as well as the association of the dependent variable albumin. Then, the C5.0 decision tree, logistic regression, and support vector machine (SVM) methods were applied to find a combination of factors that contributed to malnutrition in patients undergoing hemodialysis. Predictive models were established. Finally, a receiver operating characteristic curve and confusion matrix was used to evaluate the standard of performance of these models. All analytical methods indicated that “age” was an important factor. In particular, the best predictive model was the SVM-model 4, with a training accuracy rate of 98.95% and test accuracy rate of 66.89%, identified that “age” and 15 other important factors were the most related to hemodialysis. The findings of this study can be used as a reference for clinical applications.
Highlights
Since 2001, Taiwan had the highest incidences of end-stage renal disease (ESRD) in the world and the second highest in 2009
Patients undergoing long-term hemodialysis are prone to protein-energy malnutrition (PEM) conditions
In the current study which uses the Taiwan Society of Nephrology-Kidney Transplantation (TSN-KiDiT) database, data were retrospectively collected from 300 patients aged above 20 and had undergone hemodialysis in National Taiwan University Hospital, Yun-Lin Branch between 2010 and 2015
Summary
Since 2001, Taiwan had the highest incidences of end-stage renal disease (ESRD) in the world and the second highest in 2009. Studies have shown that approximately 18–70% of patients undergoing hemodialysis have PEM complications. In the current study which uses the Taiwan Society of Nephrology-Kidney Transplantation (TSN-KiDiT) database, data were retrospectively collected from 300 patients aged above 20 and had undergone hemodialysis in National Taiwan University Hospital, Yun-Lin Branch between 2010 and 2015. Data mining techniques were applied to identify factors related to malnutrition in patients undergoing hemodialysis. All relevant factors related to malnutrition were identified in patients undergoing hemodialysis with and without malnutrition. These findings were provided to the physicians of the hospital as a reference for clinical treatment, thereby improving the nutritional conditions of patients undergoing hemodialysis. Affecting malnutrition in patients undergoing hemodialysis, and to use this model to provide reference values to improve prediction and treatment of malnutrition in these patients
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