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| Use the Cox - Regression Model for Survival Times Patients with Renal Failure Disease Case Study - Sinnar Center for Renal Diseases |
Dr. Magdy Abd Alelah Mohammed Abass and Dr. Khansa Omer Edrees Ahmed
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Abstract:
Introduction: This study was conducted because the disease of failure has become a rapidly spreading disease the social and economic impacts have become evident and it is therefore possible to reduce these effects. Survival analysis is essential and the child variable is the time until a particular event and the application of these models help to identify the characteristics lead to increase or decrease probability of survival. Objectives: to find the appropriate model to describe the difference in the risk of death for patients with renal failure and patients who are not infected with renal failure. Methods: The study sample size is 73 respondents infected by Kidney failure 52 males and 21 females in Sinnar Center for Renal Diseases and using the Cox Regression model and measuring the average survival time after the disease. The study her used the Statistical Package for Social Sciences program (SPSS) to analyzed. Result: cases of failure with diabetes and hypertension are over 40 years old. The average probability of survival of people with diabetes is 17.5 months and 19.2 the average probability of survival of people with blood pressure and the highest average probability of survival for people without diabetes or hypertension. Recommendation: renal failure is one of the disease require awareness .The ministry of health should make period campaigns for awareness. The need for a psychologist and a social worker in dialysis center to support the psychological condition of patient.
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