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用于加快血液透析患者衰弱评估的筛查工具:一项诊断准确性研究。

Screening tools to expedite assessment of frailty in people receiving haemodialysis: a diagnostic accuracy study.

机构信息

Centre for Health, Activity and Rehabilitation Research, School of Health Sciences, Queen Margaret University, Edinburgh, EH21 6UU, UK.

Present Address: Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66103, USA.

出版信息

BMC Geriatr. 2021 Jul 2;21(1):411. doi: 10.1186/s12877-021-02356-x.

Abstract

BACKGROUND

Frailty is associated with multiple adverse outcomes in stage-5 chronic kidney disease (CKD-5) and upwards of one third of people receiving haemodialysis (HD) are frail. While many frailty screening methods are available in both uremic and non-uremic populations, their implementation in clinical settings is often challenged by time and resource constraints. In this study, we explored the diagnostic accuracy of time-efficient screening tools in people receiving HD.

METHODS

A convenience sample of 76 people receiving HD [mean age = 61.1 years (SD = 14), 53.9% male] from three Renal Units were recruited for this cross-sectional study. Frailty was diagnosed by means of the Fried phenotype. Physical performance-based screening tools encompassed handgrip strength, 15-ft gait speed, timed up and go (TUG), and five-repetition sit to stand (STS-5) tests. In addition, participants completed the SF-36 Health Survey, the short-form international physical activity questionnaire and the Tinetti falls efficacy scale (FES) as further frailty-related measures. Outcome measures included the area under the curve (AUC), sensitivity, specificity, positive (PPV) and negative predictive values (NPV). The diagnostic performance of screening tools in assessing fall-risk was also investigated.

RESULTS

Overall, 36.8% of participants were classified as frail. All the examined instruments could significantly discriminate frailty status in the study population. Gait speed [AUC = 0.89 (95%CI: 0.81-0.98), sensitivity = 75%, specificity = 93%] and TUG [AUC = 0.90 (95%CI: 0.80-0.99), sensitivity = 89%, specificity = 85%] exhibited the highest diagnostic accuracy. There was a significant difference in gait speed AUC (20%, p = 0.013) between participants aged 65 years or older (n = 36) and those under 65 years of age (n = 40), with better discriminating performance in the younger sub-group. The Tinetti FES was the only instrument showing good diagnostic accuracy (AUCs≥0.80) for both frailty (sensitivity = 82%, specificity = 79%) and fall-risk (sensitivity = 82%, specificity = 71%) screening.

CONCLUSIONS

This cross-sectional study revealed that time- and cost-efficient walking performance measures can accurately be used for frailty-screening purposes in people receiving HD. While self-selected gait speed had an excellent performance in people under 65 years of age, TUG may be a more suitable screening method for elderly patients (≥65 years). The Tinetti FES may be a clinically useful test when physical testing is not achievable.

摘要

背景

衰弱与 5 期慢性肾脏病(CKD-5)患者的多种不良结局相关,超过三分之一接受血液透析(HD)的患者存在衰弱。虽然在尿毒症和非尿毒症人群中都有许多衰弱筛查方法,但在临床环境中,由于时间和资源的限制,这些方法的实施往往面临挑战。在这项研究中,我们探讨了在接受 HD 治疗的人群中,时间效率高的筛查工具的诊断准确性。

方法

本横断面研究便利招募了来自三个肾脏科的 76 名接受 HD 治疗的患者(平均年龄 61.1 岁,标准差 14 岁,53.9%为男性)。衰弱的诊断采用 Fried 表型。基于身体表现的筛查工具包括握力、15 英尺步行速度、计时起立行走测试(TUG)和五次重复站立坐下测试(STS-5)。此外,参与者还完成了 SF-36 健康调查、短式国际体力活动问卷和 Tinetti 跌倒效能量表(FES),作为进一步的衰弱相关措施。主要结局指标包括曲线下面积(AUC)、敏感度、特异度、阳性预测值(PPV)和阴性预测值(NPV)。还研究了筛查工具在评估跌倒风险方面的诊断性能。

结果

总的来说,36.8%的参与者被归类为衰弱。所有检查的仪器都可以显著区分研究人群的衰弱状态。步行速度(AUC=0.89,95%CI:0.81-0.98,敏感度=75%,特异度=93%)和 TUG(AUC=0.90,95%CI:0.80-0.99,敏感度=89%,特异度=85%)具有最高的诊断准确性。65 岁或以上(n=36)和 65 岁以下(n=40)参与者之间的步行速度 AUC 有显著差异(20%,p=0.013),年轻组的区分性能更好。Tinetti FES 是唯一一种对衰弱(敏感度=82%,特异度=79%)和跌倒风险(敏感度=82%,特异度=71%)筛查均具有良好诊断准确性(AUC≥0.80)的仪器。

结论

这项横断面研究表明,时间和成本效益高的步行表现测量可以准确用于接受 HD 治疗的人群的衰弱筛查。虽然自我选择的步行速度在 65 岁以下的人群中表现出色,但 TUG 可能是老年患者(≥65 岁)更适合的筛查方法。当无法进行身体测试时,Tinetti FES 可能是一种有用的临床测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/226c/8252257/7dc3832f485f/12877_2021_2356_Fig1_HTML.jpg

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