Department of Neurological and Psychiatric Sciences, University of Florence, and Department of Radiology, Neuroradiology Unit, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy.
Stroke. 2012 Nov;43(11):2871-6. doi: 10.1161/STROKEAHA.112.665927. Epub 2012 Sep 20.
Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) phenotype is highly variable, and, although the full clinical-neuroimaging picture may be suggestive of the disease, no characteristic is pathognomonic. Thus, a genetic test remains the diagnostic gold standard, but because it is costly and time-consuming, a pregenetic screening appears desirable. We aimed at developing the CADASIL scale, a screening tool to be applied in the clinical setting.
A preliminary scale was created assigning weighted scores to common disease features based on their frequencies obtained in a pooled analysis of selected international CADASIL series. The accuracy of the scale versus the genetic diagnosis was tested with receiver operating characteristic analysis after the application of this scale to 61 CADASIL and 54 NOTCH3-negative patients (no pathogenic mutation on exons 2-23 of the NOTCH3 gene). To improve the scale accuracy, we then developed an ad hoc optimization algorithm to detect the definitive scale. A third group of 39 patients affected by sporadic small-vessel disease was finally included in the algorithm to evaluate the stability of the scale.
The cutoff score of the definitive CADASIL scale had a sensitivity of 96.7% and a specificity of 74.2%. This scale was robust to contamination of patients with sporadic small-vessel disease.
The CADASIL scale is a simple and sufficiently accurate screening tool to select patients with a high probability to be affected by the disease and therefore to be subjected to the genetic testing.
脑常染色体显性遗传性动脉病伴皮质下梗死和白质脑病（CADASIL）表型高度可变，尽管完整的临床-神经影像学图像可能提示该疾病，但没有任何特征具有特异性。因此，基因检测仍然是诊断的金标准，但由于其昂贵且耗时，因此需要进行预基因筛查。我们旨在开发 CADASIL 量表，这是一种可在临床环境中应用的筛查工具。
根据在选定的国际 CADASIL 系列的汇总分析中获得的频率，为常见疾病特征分配加权分数，从而创建了初步量表。在将该量表应用于 61 例 CADASIL 和 54 例 NOTCH3 阴性患者（NOTCH3 基因外显子 2-23 上无致病性突变）后，通过接收者操作特征分析测试该量表与基因诊断的准确性。为了提高量表的准确性，我们随后开发了一个专门的优化算法来检测确定的量表。最后，将第三组 39 例散发性小血管疾病患者纳入算法中，以评估量表的稳定性。
确定的 CADASIL 量表的截断分数具有 96.7%的敏感性和 74.2%的特异性。该量表对混杂有散发性小血管疾病的患者具有稳健性。
CADASIL 量表是一种简单且足够准确的筛查工具，可用于选择患有高概率疾病的患者，并对其进行基因检测。
