Background:
One of the greatest challenges in the field of medicine is the increasing burden
of chronic diseases, such as diabetes. Diabetes may cause several complications, such as kidney failure
which is followed by hemodialysis and an increasing risk of cardiovascular diseases.
Objective:
The purpose of this research was to develop a clinical decision support system for assessing
the risk of cardiovascular diseases in diabetic patients undergoing hemodialysis by using a fuzzy logic
approach.
Methods:
This study was conducted in 2018. Initially, the views of physicians on the importance of assessment
parameters were determined by using a questionnaire. The face and content validity of the
questionnaire was approved by the experts in the field of medicine. The reliability of the questionnaire
was calculated by using the test-retest method (r = 0.89). This system was designed and implemented
by using MATLAB software. Then, it was evaluated by using the medical records of diabetic patients
undergoing hemodialysis (n=208).
Results:
According to the physicians' point of view, the most important parameters for assessing the
risk of cardiovascular diseases were glomerular filtration, duration of diabetes, age, blood pressure,
type of diabetes, body mass index, smoking, and C reactive protein. The system was designed and the
evaluation results showed that the values of sensitivity, accuracy, and validity were 85%, 92% and
90%, respectively. The K-value was 0.62.
Conclusion:
The results of the system were largely similar to the patients’ records and showed that the
designed system can be used to help physicians to assess the risk of cardiovascular diseases and to improve
the quality of care services for diabetic patients undergoing hemodialysis. By predicting the risk
of the disease and classifying patients in different risk groups, it is possible to provide them with better
care plans.
Real Time Clinical Decision Support System
