Title of article :
Survival Rate of Hemodialysis Patients: A Competing Risk Analysis Approach
Author/Authors :
Zafar Mohtashami ، Azita Department of Internal Medicine - Shahid Rahimi Hospital - Lorestan University of Medical Sciences , Hadian ، Babak Department of Internal Medicine - Shahid Rahimi Hospital - Lorestan University of Medical Sciences , Izadi Meidarsofla ، Narges School of Medicine - Lorestan University of Medical Sciences
From page :
1
To page :
7
Abstract :
Background: Chronic kidney disease, a global health problem, leads to end-stage kidney disease, whose treatment requires long-term renal replacement therapy. The incidence of hemodialysis patients with end-stage kidney disease is increasing worldwide. The survival rate of hemodialysis patients is crucial for decision-making and planning. Objectives: This study aimed to determine the survival rate of hemodialysis patients and its related factors using the competing risk analysis approach to acquire more precise estimations of survival and mortality of the patients. Methods: This study was primarily based on medical records of hemodialysis patients who started dialysis from January 2011 to December 2017. The end of the study follow-up period was December 2021. The study included 214 eligible patients. Death was regarded as the event of interest, kidney transplantation as the competing risk, and other consequences as censored. We analyzed the data by cumulative incidence functions, Gray’s test, and Fine-Gray regression model using R version 4.1.2 and Stata v.16 at a significance level of 0.05. Results: The median age at the initiation of hemodialysis was 60 years. The risks of death in the first, second, third, fourth, and fifth years were 18.3%, 31.7%, 41.6%, 49.9%, and 60.9%, respectively. In the regression model, age at the initiation of hemodialysis (P-value = 0.000) and education (P-value = 0.000) were associated with mortality. Conclusions: Competing risk estimates of survival analysis of hemodialysis patients are more reliable than conventional approaches (e.g., Kaplan–Meier estimator) for planning and improving interventions and allocating resources. Detection of patients at a younger age and increasing patients knowledge plays a significant role in improving their survival.
Keywords :
Survival Rate , Competing Risks , Cumulative Incidence Function , Hemodialysis , Chronic Kidney Disease , End Stage Renal Disease
Journal title :
Nephro- Urology Monthly
Journal title :
Nephro- Urology Monthly
Record number :
2742507
Link To Document :
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