首页> 外文期刊>Stroke: A Journal of Cerebral Circulation >Visual rating scales for age-related white matter changes (leukoaraiosis): can the heterogeneity be reduced?
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Visual rating scales for age-related white matter changes (leukoaraiosis): can the heterogeneity be reduced?

机译:年龄相关性白质变化(白质疏松症)的视觉评定量表:是否可以减少异质性?

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BACKGROUND AND PURPOSE: It has been hypothesized that the use of different visual rating scales partly explains the discordant results of studies investigating risk factors and clinical correlates of age-related cerebral white matter changes (leukoaraiosis). We aimed to compare 6 widely used rating scales for leukoaraiosis and to calculate conversion coefficients of the score of 1 scale in the score of a second scale. METHODS: Two trained raters evaluated 80 pairs of CT and MRI scans using 2 CT and 4 MRI rating scales for white matter changes. Correlations among the scales were evaluated and regression lines were constructed with each of the CT and MRI scale scores as variables. RESULTS: A high correlation was observed in all the paired comparisons of the 6 scales (Spearman's rho ranging from 0.85 to 0.96, P<0.0001). Using regression analysis, we determined numeric parameters to transform the score of 1 scale to the corresponding score for each of the remaining scales and relative confidence intervals.The predictive values of these conversions expressed as R(2) ranged from 0.75 to 0.92. CONCLUSIONS: The present findings support the view that a good correlation exists among the considered visual rating scales for white matter changes. With the limitation that conversion parameters are calculated by applying a linear regression to partly nonlinear scales, their use allows comparison of the results of previous studies that used different scales and to pool data from past and ongoing clinical trials.
机译:背景与目的:假设使用不同的视力评定量表部分解释了与年龄相关的脑白质变化(白斑病)的危险因素和临床相关性研究的不一致结果。我们旨在比较6种广泛使用的白细胞疏松症的评分量表,并计算1量表的得分与第二量表的得分的换算系数。方法:两名训练有素的评估者使用2个CT和4个MRI评分量表评估了80对CT和MRI扫描的白质变化。评估量表之间的相关性,并以CT和MRI量表的每个分数为变量构建回归线。结果:在所有6个量表的配对比较中均观察到高度相关(Spearman的rho范围为0.85至0.96,P <0.0001)。使用回归分析,我们确定了数值参数,以将1个量表的得分转换为其余每个量表和相对置信区间的相应得分。这些转换的预测值为R(2),范围为0.75至0.92。结论:本研究结果支持这样的观点,即考虑的白质变化视觉等级量表之间存在良好的相关性。由于转换参数是通过对部分非线性比例应用线性回归来计算转换参数的限制,因此可以将使用不同比例的先前研究结果进行比较,并汇总过去和正在进行的临床试验中的数据。

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