評估罹患慢性腎臟病風險以達初級預防之功效

Abstract

今日於台灣有200萬人罹患慢性腎臟病，終其餘生以洗腎度日。台灣在2015年健保在洗腎的支出上更高達400億台幣。因此慢性腎臟病的初級預防將有效降低日後罹患慢性腎臟病的可能，並節省健保的龐大醫療支出。本研究目的是開發一套非侵入式的初級預防系統。來達到初期預測、預防、與個人化醫療的目的。本研究從國民健康署六百五十位慢性腎臟病患者的生活飲食問卷，以及五千兩百位未確診的人作生活飲食問卷，在基於演化式篩選演算法有效篩選潛在健康樣本後，並經由繼承式雙目標基因演算法搭配支持向量機建立準確數學模型。研究結果經測試資料驗證後，模型之預測靈敏度達到83%，並找到三十七個重要風險因子可能增加罹患慢性腎臟病之風險。

Nowadays, there are two million people suffering from chronic kidney disease (CKD) in Taiwan. These CKD patients have to dialysis in the rest of their life. In 2015, dialysis costs approximately forty billion NT dollars from Taiwan National Health Insurance. Hence, primary prevention of chronic kidney disease can reduce the possible risk of CKD in the future, and can save huge medical expenses. The purposes of this work were to develop a non-invasive primary prevention system, to achieve early prediction, prevention, and personalized medicine. In this work, the questionnaire data were from the Health Promotion Administration, Ministry of Health and Welfare, which related to the lifestyle and diet. There are 650 CKD patients, and 5,200 people are not confirmed patients. This work based on Evolutionary Screening Algorithm to screen effective healthy people, and an accurate model derived by using the Inheritable Bi-objective Genetic Algorithm with Support Vector Machine. The results showed that the test sensitivity is 83%. In addition, 37 informative risk factors that may increase the risk of suffering from chronic kidney disease.