Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Department of Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Am J Nephrol. 2022;53(11-12):826-838. doi: 10.1159/000528602. Epub 2022 Dec 9.
A comprehensive geriatric assessment (CGA) tailored to the chronic kidney disease (CKD) population would yield a more targeted approach to assessment and care. We aimed to identify domains of a CKD-specific CGA (CKD-CGA), characterize patterns of these domains, and evaluate their predictive utility on adverse health outcomes.
We used data from 864 participants in the Chronic Renal Insufficiency Cohort aged ≥55 years and not on dialysis. Constituents of the CKD-CGA were selected a priori. Latent class analysis informed the selection of domains and identified classes of participants based on their domain patterns. The predictive utility of class membership on mortality, dialysis initiation, and hospitalization was examined. Model discrimination was assessed with C-statistics.
The CKD-CGA included 16 domains: cardiovascular disease, diabetes, five frailty phenotype components, depressive symptoms, cognition, five kidney disease quality-of-life components, health literacy, and medication use. A two-class latent class model fit the data best, with 34.7% and 65.3% in the high- and low-burden of geriatric conditions classes, respectively. Relative to the low-burden class, participants in the high-burden class were at increased risk of mortality (aHR = 2.09; 95% CI: 1.56, 2.78), dialysis initiation (aHR = 1.63; 95% CI: 1.06, 2.52), and hospitalization (aOR = 2.00; 95% CI: 1.38, 2.88). Model discrimination was the strongest for dialysis initiation (C-statistics = 0.86) and moderate for mortality and hospitalization (C-statistics = 0.70 and 0.66, respectively).
With further validation in an external cohort, the CKD-CGA has the potential to be used in nephrology practices for assessing and managing geriatric conditions in older adults with CKD.
针对慢性肾脏病(CKD)患者量身定制的全面老年评估(CGA)将为评估和护理提供更有针对性的方法。我们旨在确定 CKD 特异性 CGA(CKD-CGA)的领域,描述这些领域的模式,并评估其对不良健康结果的预测效用。
我们使用了年龄≥55 岁且未接受透析的 864 名慢性肾功能不全队列研究参与者的数据。CKD-CGA 的组成部分是预先选择的。潜在类别分析用于选择领域,并根据其领域模式确定参与者的类别。研究了类别成员资格对死亡率、透析开始和住院的预测效用。通过 C 统计量评估模型区分度。
CKD-CGA 包括 16 个领域:心血管疾病、糖尿病、五种衰弱表型成分、抑郁症状、认知、五种肾脏疾病生活质量成分、健康素养和药物使用。两类别潜在类别模型最适合数据,高和低老年病负担类别分别为 34.7%和 65.3%。与低负担类别相比,高负担类别参与者的死亡率(aHR = 2.09;95%CI:1.56,2.78)、透析开始(aHR = 1.63;95%CI:1.06,2.52)和住院(aOR = 2.00;95%CI:1.38,2.88)的风险增加。模型区分度对透析开始最强(C 统计量= 0.86),对死亡率和住院率中等(C 统计量分别为 0.70 和 0.66)。
在外部队列中进一步验证后,CKD-CGA 有可能在肾脏病实践中用于评估和管理老年慢性肾脏病患者的老年病。