Natus Medical, Inc, Hopewell Junction, New York, USA.
Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Muscle Nerve. 2021 May;63(5):737-744. doi: 10.1002/mus.27195. Epub 2021 Mar 4.
In this study we describe a method called "multivariable extrapolated reference values" (MeRef) that derives reference values (RVs) using patient data and includes the dependence of these variables on multiple patient demographic variables, such as age and height.
Computer simulations were used to generate "normal" and "patient" nerve conduction data. Median, ulnar, and tibial motor nerve conduction data from 500 patients studied were tabulated. Data were analyzed using the MeRef method.
The simulations showed great similarity between RVs obtained from MeRef of "patient" data and traditional analysis of "normal" data. In the real patient data, MeRef gave RVs as regression equations based on patient age and/or height.
MeRef can provide RVs by including patient demographic data and does not require subject grouping. It provides parameters of multivariable linear regression and standard deviation, and requires a few hundred patient studies to define reference values.
本研究描述了一种名为“多变量外推参考值”（MeRef）的方法，该方法使用患者数据推导参考值（RVs），并包括这些变量对多个患者人口统计学变量（如年龄和身高）的依赖性。
计算机模拟用于生成“正常”和“患者”神经传导数据。列出了 500 名研究患者的正中、尺和胫神经传导数据。使用 MeRef 方法对数据进行了分析。
模拟结果表明，MeRef 从“患者”数据中获得的 RVs 与传统的“正常”数据分析非常相似。在真实的患者数据中，MeRef 根据患者的年龄和/或身高给出了 RVs 的回归方程。
MeRef 可以通过包含患者人口统计学数据来提供 RVs，并且不需要对受试者进行分组。它提供了多元线性回归的参数和标准差，并且需要几百名患者的研究来定义参考值。
