Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Department of Neurology, Cognition and Aging Center, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Eur J Neurol. 2022 Jan;29(1):59-68. doi: 10.1111/ene.15123. Epub 2021 Oct 7.
Dementia is prevalent and underdiagnosed in the dialysis population. We aimed to develop and validate a simple dialysis dementia scoring system to facilitate identification of individuals who are at high risk for dementia.
We applied a retrospective, nested case-control study design using a national dialysis cohort derived from the National Health Insurance Research Database in Taiwan. Patients aged between 40 and 80 years were included and 2940 patients with incident dementia were matched to 29,248 non-dementia controls. All subjects were randomly divided into the derivation and validation sets with a ratio of 4:1. Conditional logistic regression models were used to identify factors contributing to the risk score. The cutoff value of the risk score was determined by Youden's J statistic and the graphic method.
The dialysis dementia risk score (DDRS) finally included age and 10 comorbidities as risk predictors. The C-statistic of the model was 0.71 (95% confidence interval [CI] 0.70-0.72). Calibration revealed a strong linear relationship between predicted and observed dementia risk (R = 0.99). At a cutoff value of 50 points, the high-risk patients had an approximately three-fold increased risk of having dementia compared to those with low risk (odds ratio [OR] 3.03, 95% CI 2.78-3.31). The DDRS performance, including discrimination (C-statistic 0.71, 95% CI 0.69-0.73) and calibration (p value of Hosmer-Lemeshow test for goodness of fit = 0.18), was acceptable during validation. The OR value (2.82, 95% CI 2.37-3.35) was similar to those in the derivation set.
The DDRS system has the potential to serve as an easily accessible screening tool to determine the high-risk groups who deserve subsequent neurological evaluation in daily clinical practice.
痴呆在透析人群中普遍存在且诊断不足。我们旨在开发和验证一种简单的透析痴呆评分系统,以帮助识别痴呆风险较高的个体。
我们应用回顾性、嵌套病例对照研究设计,使用来自中国台湾全民健康保险研究数据库的全国透析队列。纳入年龄在 40 至 80 岁之间的患者,并将 2940 例新发痴呆患者与 29248 例非痴呆对照患者进行匹配。所有受试者被随机分为推导组和验证组,比例为 4:1。条件逻辑回归模型用于确定导致风险评分的因素。风险评分的截断值通过 Youden 的 J 统计量和图形法确定。
透析痴呆风险评分(DDRS)最终纳入年龄和 10 种合并症作为风险预测因子。该模型的 C 统计量为 0.71(95%置信区间 [CI] 0.70-0.72)。校准显示预测和观察到的痴呆风险之间存在很强的线性关系(R=0.99)。在 50 分的截断值处,高风险患者患痴呆的风险约为低风险患者的三倍(优势比 [OR] 3.03,95%CI 2.78-3.31)。DDRS 的性能,包括区分度(C 统计量为 0.71,95%CI 0.69-0.73)和校准(拟合优度的 Hosmer-Lemeshow 检验 p 值=0.18),在验证过程中是可以接受的。OR 值(2.82,95%CI 2.37-3.35)与推导组相似。
DDRS 系统有可能成为一种易于获取的筛查工具,用于确定需要在日常临床实践中进行后续神经评估的高危人群。