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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Implementation and evaluation of a statistical framework for nerve conduction study reference range calculation.
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Implementation and evaluation of a statistical framework for nerve conduction study reference range calculation.

机译：神经传导研究参考范围计算的统计框架的实施和评估。

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摘要

Nerve conduction studies (NCS) play a central role in the clinical evaluation of neuropathies. Their clinical utilization depends on reference ranges that define the expected parameter values in disease-free individuals. In this paper, a statistical framework is proposed and described in detail for deriving NCS parameter reference ranges. The bootstrap technique is used to identify demographic and physiologic covariates that influence the NCS measurements. Multi-variate linear regression is used to improve the accuracy and effectiveness of NCS interpretation by reducing parameter variance. Non-linear mappings are used to transform parameters into a Gaussian distribution in order to minimize the influence of outliers. Modeling of heteroscedasticity observed in this and other studies leads to more sensible normal limits for several parameters. The proposed reference range method is automated using the MATLAB programming language. Data from a large sample of healthy subjects are used to establish reference ranges for 24 commonly measured NCS parameters. All but three parameters follow Gaussian distributions in their respective transformed domains. Excluding the distal motor latency difference between median and ulnar nerves, the reduction of the parameter variance as a result of regression in the transform domain is greater than 50% for all F-wave latency parameters and at least 10% for all other NCS parameters. Subject age is found to influence normal limits of all but one parameter and height has a statistically significant impact on all but three parameters. These reference range specifications provide clinicians with an alternative to developing their own reference ranges as long as their NCS techniques are consistent with those described in this paper. The proposed method should also be applicable to reference range development for other NCS techniques and physiological measurements.
机译：神经传导研究（NCS）在神经病的临床评估中起着核心作用。它们的临床利用取决于参考范围，该参考范围定义了无病个体的预期参数值。在本文中，提出并详细描述了用于导出NCS参数参考范围的统计框架。自举技术用于识别影响NCS测量的人口统计学和生理协变量。多元线性回归用于通过减少参数方差来提高NCS解释的准确性和有效性。非线性映射用于将参数转换为高斯分布，以最大程度地减少离群值的影响。在本研究和其他研究中观察到的异方差建模导致对多个参数的更合理的正常极限。所提出的参考范围方法是使用MATLAB编程语言自动实现的。来自健康受试者的大量样本的数据用于建立24个通常测量的NCS参数的参考范围。除三个参数外，所有参数均在其各自转换后的域中遵循高斯分布。除去正中神经和尺神经之间的远端运动潜伏期差异，对于所有F波潜伏期参数，由于变换域中的回归而导致的参数方差的减小大于50％，而对于所有其他NCS参数则至少大于10％。发现受试者年龄影响除一个参数以外的所有参数的正常极限，而身高对除三个参数以外的所有参数具有统计学上的显着影响。这些参考范围规范为临床医生提供了开发自己的参考范围的替代方法，只要他们的NCS技术与本文中描述的技术保持一致即可。所提出的方法还应该适用于其他NCS技术和生理测量的参考范围开发。

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