| Summary: | 碩士 === 中臺科技大學 === 健康產業管理研究所 === 100 === Intradialytic hypotension (IDH) remains an important issue during hemodialysis treatment. Many tools were developed to investigate the mechanisms and predict the hypotensive events when receiving dialysis. Our aim is to design intelligent classifies to identify high risk hemodialysis patients.
Data from 160 hemodialysis patients (61 IDH-prone, 99 IDH-resistant) were analyzed with support vector machines (SVM) and logistic regression analysis (LRA). The IDH event was defined as a systolic pressure <100mmHg or a fall in systolic pressure >20mmHg associated with symptoms of hypotension (cramps, dizziness, nausea, vomiting, headache, sweating, loss of consciousness). The different abilities to predict the occurrences of IDH were compared between these two methods.
SVM demonstrated better overall classification accuracy (81.3%) compared to LRA (76.3%). It was also shown that SVM had higher sensitivity (70.5%) and specificity (87.9%) than LRA (sensitivity: 62.3% and specificity: 84.8%).
SVM is superior to logistic regression method in predicting the risk of hypotension during hemodialysis. Clinical application of the clinical decision support system designed with SVM may be helpful for nephrologist in discriminating the high risk patients when receiving hemodialysis treatments.
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