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[肾移植受者中衰弱的患病率及相关因素]

[Prevalence of frailty and associated factors among kidney transplant recipients].

作者信息

Cao H W, Zhang J D, Wang W, Xu Q Z

机构信息

Department of Urology, Beijing Chao-yang Hospital, Capital Medical University, Beijing 100020, China.

Health Check-up Center, Beijing Chao-yang Hospital, Capital Medical University, Beijing 100020, China.

出版信息

Zhonghua Yi Xue Za Zhi. 2023 May 30;103(20):1531-1537. doi: 10.3760/cma.j.cn112137-20221104-02307.

DOI:10.3760/cma.j.cn112137-20221104-02307
PMID:37246002
Abstract

To investigate the prevalence of frailty among kidney transplant recipients and to analyze the influential factors of frailty after kidney transplantation. We retrospectively included 201 kidney transplant recipients who were followed up in the Department of Urology, Beijing Chao-yang Hospital, Capital Medical University from November 2020 to May 2022. We investigated the prevalence of frailty based on the Fried Frailty Scale (including unexpected shrinking, slow walking speed, poor grip strength, low physical activity, and exhaustion). Then the logistic regression model and CART decision tree model were established separately to explore the influential factors of frailty after kidney transplantation. Frail kidney transplant recipients accounted for 25.9% (=52) of all participants. The age [ (, )] of the frailty group was higher than that of the non-frailty group, and the median ages of the two groups were 57(49, 62) and 46(38, 56) (0.001); the males accounted for 51.9% (=27) and 62.4% (=93), respectively. There was no significant difference in gender composition (=0.244). Among the five components of Fried Frailty Scale, the incidence of unexpected shrinking was the lowest (19.4%, 39/201). In the frailty group, the frailty combination with the highest incidence was slow walking speed+low physical activity+exhaustion, which was 19.2% (10/52). The logistic regression model showed that advanced age (=1.062, 95%: 1.005-1.123), history of acute rejection (=16.776, 95%: 2.288-123.028), increased neutrophil/lymphocyte ratio (NLR) (=2.096, 95%: 1.158-3.792), and comorbidity (=10.600, 95%: 1.828-61.482) were risk factors for frailty among kidney transplant recipients, and high serum albumin level (=0.623, 95%: 0.488-0.795) was a protective factor. The CART decision tree grew in three layers with four terminal nodes, and three explanatory variables were screened out: serum albumin, NLR, and age. The accuracy, sensitivity, and specificity of the logistic regression model were 87.1% (95%: 82.5%-91.7%), 69.2% (95%: 54.7%-80.9%), and 93.3% (95%: 87.7%-96.6%), respectively. The area under the ROC curve (AUC) of the logistic regression model was 0.951 (95%: 0.923-0.978). The accuracy, sensitivity, and specificity of the CART decision tree model were 91.0% (95%: 87.0%-95.0%), 82.7% (95%: 69.2%-91.3%), and 94.0% (95%: 88.5%-97.0%), respectively. The AUC of the CART decision tree model was 0.883 (95%: 0.819-0.948). The prevalence of frailty among kidney transplant recipients in this study is 25.9%. Advanced age, history of acute rejection, low serum albumin level, increased NLR, and comorbidity are likely to be associated with the long-term frailty among kidney transplant recipients.

摘要

为调查肾移植受者中衰弱的患病率,并分析肾移植后衰弱的影响因素。我们回顾性纳入了2020年11月至2022年5月在首都医科大学附属北京朝阳医院泌尿外科随访的201例肾移植受者。我们基于弗里德衰弱量表(包括意外体重减轻、步速缓慢、握力差、体力活动少和疲惫)调查衰弱的患病率。然后分别建立逻辑回归模型和CART决策树模型,以探讨肾移植后衰弱的影响因素。衰弱的肾移植受者占所有参与者的25.9%(=52例)。衰弱组的年龄[(,)]高于非衰弱组,两组的中位年龄分别为57(49,62)岁和46(38,56)岁(0.001);男性分别占51.9%(=27例)和62.4%(=93例)。性别构成无显著差异(=0.244)。在弗里德衰弱量表的五个组成部分中,意外体重减轻的发生率最低(19.4%,39/201)。在衰弱组中,发生率最高的衰弱组合是步速缓慢+体力活动少+疲惫,为19.2%(... 此处原文有误,应为19.2%(10/52))。逻辑回归模型显示,高龄(=1.062,95%置信区间:1.005 - 1.123)、急性排斥反应史(=16.776,95%置信区间:2.288 - 123.028)、中性粒细胞/淋巴细胞比值(NLR)升高(=2.096,95%置信区间:1.158 - 3.792)和合并症(=10.600,95%置信区间:1.828 - 61.482)是肾移植受者衰弱的危险因素,而高血清白蛋白水平(=0.623,95%置信区间:0.488 - 0.795)是保护因素。CART决策树生长为三层,有四个终端节点,筛选出三个解释变量:血清白蛋白、NLR和年龄。逻辑回归模型的准确性、敏感性和特异性分别为87.1%(95%置信区间:82.5% - 91.7%)、69.2%(95%置信区间:54.7% - 80.9%)和93.3%(95%置信区间:87.7% - 96.6%)。逻辑回归模型的ROC曲线下面积(AUC)为0.951(95%置信区间:0.923 - 0.978)。CART决策树模型的准确性、敏感性和特异性分别为91.0%(95%置信区间:87.0% - 95.0%)、82.7%(95%置信区间:69.2% - 91.3%)和94.0%(95%置信区间:88.5% - 97.0%)。CART决策树模型的AUC为0.883(95%置信区间:0.819 - 0.948)。本研究中肾移植受者衰弱的患病率为25.9%。高龄、急性排斥反应史、低血清白蛋白水平、NLR升高和合并症可能与肾移植受者的长期衰弱有关。

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