血液透析患者生存率的竞争风险分析方法

Q4 Medicine Nephro-urology Monthly Pub Date : 2022-09-14 DOI:10.5812/numonthly-128158
Azita Zafar Mohtashami, B. Hadian, Narges Izadi Meidarsofla
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引用次数: 0

摘要

背景:慢性肾脏疾病是一个全球性的健康问题,可导致终末期肾脏疾病,其治疗需要长期肾脏替代治疗。终末期肾病血液透析患者的发病率在世界范围内呈上升趋势。血液透析患者的存活率对决策和计划至关重要。目的:本研究旨在采用竞争风险分析方法确定血液透析患者的生存率及其相关因素,以更准确地估计患者的生存和死亡率。方法:本研究主要基于2011年1月至2017年12月开始透析的血液透析患者的医疗记录。研究随访期于2021年12月结束。该研究包括214名符合条件的患者。死亡被视为值得关注的事件,肾移植被视为竞争风险,其他后果被审查。我们采用累积关联函数、Gray检验和Fine-Gray回归模型对数据进行分析,使用R version 4.1.2和Stata v.16,显著性水平为0.05。结果:开始血液透析的中位年龄为60岁。第一、二、三、四、五年的死亡风险分别为18.3%、31.7%、41.6%、49.9%和60.9%。在回归模型中,开始血液透析的年龄(p值= 0.000)和教育程度(p值= 0.000)与死亡率相关。结论:血液透析患者生存分析的竞争风险估计比传统方法(例如Kaplan-Meier估计)在计划和改进干预措施和分配资源方面更可靠。在更年轻的年龄发现患者并增加患者的知识对提高患者的生存率具有重要作用。
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Survival Rate of Hemodialysis Patients: A Competing Risk Analysis Approach
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.
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来源期刊
Nephro-urology Monthly
Nephro-urology Monthly Medicine-Urology
CiteScore
0.40
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0.00%
发文量
26
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