Predicting change with the RBANS in a community dwelling elderly sample
Predicting change with the RBANS in a community dwelling elderly sample
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DOI：
10.1017/s1355617704106048
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发表时间：
2004-10-01
影响因子：
2.6
通讯作者：
Adams, RL
中科院分区：
文献类型：
--
作者：
Duff, K;Schoenberg, MR;Adams, RL
重复的神经心理学评估在老年人中很常见，确定随时间的临床显著变化是一个重要问题。基于回归的预测公式已用于其他患者和健康对照样本，以根据初始性能和人口统计学变量预测随访测试性能。预测和观察到的随访性能之间的比较可以帮助临床医生确定个体患者变化的意义。本研究以223名社区老年人为样本，建立了RBANS五项指标和总分的多元回归预测方程。然后在单独的老年人样本（N = 222）上验证这些算法。在验证样本中，观察到的和预测的随访评分之间存在最小差异，这表明预测公式对评估老年人的从业者具有临床实用性。一个案例的例子，说明了如何可以在临床上使用的算法。
Repeated neuropsychological assessments are common with older adults, and the determination of clinically significant change across time is an important issue. Regression-based prediction formulas have been utilized with other patient and healthy control samples to predict follow-up test performance based on initial performance and demographic variables. Comparisons between predicted and observed follow-up performances can assist clinicians in determining the significance of change in the individual patient. In the current study, multiple regression-based prediction equations for the 5 Indexes and Total Score of the RBANS were developed for a sample of 223 community dwelling older adults. These algorithms were then validated on a separate elderly sample (N = 222). Minimal differences were present between observed and predicted follow-up scores in the validation sample, suggesting that the prediction formulas are clinically useful for practitioners who assess older adults. A case example is presented that illustrates how the algorithms can be used clinically.