一种新的血管性认知障碍诊断算法：提出的标准及其可靠性和有效性评估。
A new diagnostic algorithm for vascular cognitive impairment: the proposed criteria and evaluation of its reliability and validity.
机构信息
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China.
出版信息
Chin Med J (Engl). 2010 Feb 5;123(3):311-9.
BACKGROUND
Vascular cognitive impairment (VCI) is considered to be the most common pattern of cognitive impairment. We aimed to devise a diagnostic algorithm for VCI, and evaluate the reliability and validity of our proposed criteria.
METHODS
We based our new algorithm on previous literature, a Delphi consensus method, and preliminary testing. First, successive 100 patients with cerebrovascular disease (CVD) in hospital underwent a structured medical examination. Twenty-five case vignettes fulfilled the proposed criteria of diagnosis for probable or possible VCI were divided into three subtype categories: vascular cognitive impairment, no dementia (VCIND), vascular dementia (VaD) or mixed VCI/Alzheimer's disease (AD). Inter-raters reliability was assessed using a Fleiss kappa analysis. Convergent validity was also evaluated by correlation coefficients (r) between the proposed key points for each subtype and the currently accepted criteria. Forty-five patients with probable VCI were examined to determine the accuracy of identification for each subtype.
RESULTS
The proposed criteria showed clinical diagnostic validity for VCI, and were able to define probable, possible and definite VCI, three VCI subtypes, and vascular causes. There was good consensus between experts (Cronbach's alpha = 0.96 for both rounds). Significant moderate to good items-total correlations were found for two questionnaires (50-r range, 0.40 - 0.97 and 0.41 - 0.99, respectively). Significant slight and moderate inter-raters reliability were obtained for VCI (k = 0.13) and three VCI subtypes (k = 0.45). Furthermore, good convergent validity was observed in a comparison of significant correlations between criteria: good (4-r range, 0.75 - 0.92) to perfect (3-r = 1.00) validity for the VCIND subtype, and moderate to good validity for the VaD subtype (1-r = 0.46; 5-r range, 0.76 - 0.92) and for the mixed VCI/AD subtype (r = 0.92 and 1.00; 4-r range, 0.47 - 0.70). Importantly, the area under receiver operating characteristic (ROC) curves for the subtypes of VCIND, VaD and mixed VCI/AD were 0.85, 0.67 and 0.93, respectively.
CONCLUSION
Our results suggest that the new VCI diagnostic algorithm might be a suitable clinical approach for assessing stroke patients.
背景
血管性认知障碍（VCI）被认为是最常见的认知障碍模式。我们旨在设计一种 VCI 的诊断算法，并评估我们提出的标准的可靠性和有效性。
方法
我们的新算法基于先前的文献、德尔菲共识方法和初步测试。首先，对医院中连续 100 例脑血管病（CVD）患者进行了结构化的医学检查。25 个病例简述符合可能或可能的 VCI 诊断标准的被分为三个亚型类别：血管性认知障碍，非痴呆（VCIND）、血管性痴呆（VaD）或混合 VCI/阿尔茨海默病（AD）。使用 Fleiss kappa 分析评估了评分者间的可靠性。还通过对每个亚型的拟议关键点与当前公认标准之间的相关系数（r）评估了收敛有效性。对 45 例可能的 VCI 患者进行了检查，以确定每个亚型的识别准确性。
结果
所提出的标准对 VCI 具有临床诊断有效性，能够定义可能的、可能的和明确的 VCI、三个 VCI 亚型和血管原因。专家之间有很好的一致性（两轮 Cronbach's alpha 均为 0.96）。两个问卷的项目-总分之间存在显著的中度至高度相关性（50-r 范围分别为 0.40-0.97 和 0.41-0.99）。VCI（k=0.13）和三个 VCI 亚型（k=0.45）的评分者间可靠性具有显著的轻度至中度。此外，在对显著相关标准的比较中观察到良好的收敛有效性：VCIND 亚型的良好（4-r 范围为 0.75-0.92）至完美（3-r=1.00）的有效性，VaD 亚型的中度至良好的有效性（1-r=0.46；5-r 范围为 0.76-0.92）和混合 VCI/AD 亚型的有效性（r=0.92 和 1.00；4-r 范围为 0.47-0.70）。重要的是，VCIND、VaD 和混合 VCI/AD 亚型的受试者工作特征（ROC）曲线下面积分别为 0.85、0.67 和 0.93。
结论
我们的结果表明，新的 VCI 诊断算法可能是评估中风患者的一种合适的临床方法。
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