Aragón-Basanta Elisa, Ayala Guillermo, Page Álvaro, Serra-Añó Pilar
Instituto Universitario de Ingeniería Mecánica y Biomecánica, Universitat Politècnica de València, Camino de Vera s/n, Valencia, 46022, Spain.
Departamento de Estadística e Investigación Operativa, Facultad de Matemáticas, Universitat de Valéncia, Avda Vicent Andrés Estellés s/n, Burjassot, 46100, Valencia, Spain.
Med Biol Eng Comput. 2025 Jul 8. doi: 10.1007/s11517-025-03400-3.
We have analyzed the relationship between disability and neck flexion-extension kinematics in non-specific neck pain subjects. A functional approach is used considering the angle, velocity, and acceleration curves. Different regression models have been fitted for each time in order to obtain these curves using scalar predictors such as the Neck Disability Index (NDI), age, sex, and neck length. In addition to classical regression, a limma (Linear Models for Microarray Data) model has been used, which improves the fit by modifying the estimation of the variances of the different fits using an empirical Bayes approach. As point-by-point adjustments are performed, this introduces a multiple comparison problem, and the corresponding p-values have to be adjusted in order to control the false discovery rate (FDR). In particular, a Benjamini-Hochberg method was used. The results show significant differences between raw and adjusted p-values for all variables, so spurious results were detected, e.g., the effect of neck length on velocity and acceleration curves. Differences between usual multiple linear regressions and the modified fits using the limma method (limma models) are minor, with a slight decrement of p-values in limma models. Once the p-values are adjusted, none of the variables analyzed significantly affects the angular curves. In contrast, NDI and age affect velocity and acceleration curves. Furthermore, the study of p-values throughout the movement shows that velocity and acceleration curves provide complementary information, so they should be used together in neck kinematics studies.
我们分析了非特异性颈部疼痛患者的残疾与颈部屈伸运动学之间的关系。采用功能方法，考虑角度、速度和加速度曲线。为了使用诸如颈部残疾指数（NDI）、年龄、性别和颈部长度等标量预测变量来获得这些曲线，每次都拟合了不同的回归模型。除了经典回归外，还使用了limma（微阵列数据线性模型）模型，该模型通过使用经验贝叶斯方法修改不同拟合的方差估计来改善拟合效果。由于进行了逐点调整，这引入了多重比较问题，因此必须调整相应的p值以控制错误发现率（FDR）。特别是，使用了Benjamini-Hochberg方法。结果显示，所有变量的原始p值和调整后的p值之间存在显著差异，因此检测到了虚假结果，例如颈部长度对速度和加速度曲线的影响。普通多元线性回归与使用limma方法的修正拟合（limma模型）之间的差异较小，limma模型中的p值略有下降。一旦调整了p值，分析的变量均未对角度曲线产生显著影响。相比之下，NDI和年龄会影响速度和加速度曲线。此外，对整个运动过程中p值的研究表明，速度和加速度曲线提供了互补信息，因此在颈部运动学研究中应将它们一起使用。
