Department of Rehabilitation Medicine, National Institutes of Health, Bethesda, MD, USA.
Department of Rehabilitation Medicine, National Institutes of Health, Bethesda, MD, USA.
J Biomech. 2022 Jan;130:110819. doi: 10.1016/j.jbiomech.2021.110819. Epub 2021 Oct 15.
Due to the multifactorial nature of patellofemoral pain, it is often difficult to identify an individual patient's exact cause of pain. Understanding how demographic variability influences these various factors will support improved consensus in regards to the etiology of PF pain. Thus, in this retrospective study, we tested the hypothesis that sex, height, weight, body mass index (BMI), and age influence the determination of between-groups differences in PF kinematics. We included 41 skeletally mature patients with patellofemoral pain and 79 healthy controls. Three-dimensional patellofemoral kinematics were quantified from dynamic magnet resonance images. We ran multiple regression analyses to determine the influence of demographic covariates (age, sex, height, weight, and BMI) on patellofemoral kinematics. Patellar shift was significantly influenced by weight (p = 0.009) and BMI (p = 0.009). Patellar flexion was influenced by height (p = 0.020) and weight (p = 0.040). Patellar tilt and superior displacement were not influence by demographic variables. Age and sex did not influence kinematics. This study supports the hypothesis that demographic parameters influence PF kinematics. The fact that weight, a modifiable measure, influences both patellar shift and flexion has strong implications for future research and clinical interventions. Clinically, weight loss may have a dual benefit of reducing joint stress and maltracking in patients who are overweight and experiencing patellofemoral pain. The influence of key demographics on patellofemoral kinematics, reinforces the clear need to control for population characteristics in future studies. As such, going forward, improved demographic matching between control and patient cohorts or more advanced statistical techniques that compensate for confounding variables are necessary.
由于髌股疼痛的多因素性质，通常很难确定个体患者疼痛的确切原因。了解人口统计学变异性如何影响这些不同因素将有助于在髌股疼痛的病因学方面达成更好的共识。因此，在这项回顾性研究中，我们检验了以下假设，即性别、身高、体重、体重指数（BMI）和年龄会影响髌股运动学分组间差异的确定。我们纳入了 41 名骨骼成熟的髌股疼痛患者和 79 名健康对照者。通过动态磁共振成像对髌股运动学进行了三维定量。我们进行了多元回归分析，以确定人口统计学协变量（年龄、性别、身高、体重和 BMI）对髌股运动学的影响。髌骨移位明显受到体重（p=0.009）和 BMI（p=0.009）的影响。髌骨屈曲受身高（p=0.020）和体重（p=0.040）影响。髌骨倾斜和上移不受人口统计学变量的影响。年龄和性别不影响运动学。这项研究支持以下假设，即人口统计学参数会影响髌股运动学。体重是一个可改变的指标，它会同时影响髌骨移位和屈曲，这对未来的研究和临床干预具有重要意义。临床上，对于超重且患有髌股疼痛的患者，减肥可能具有双重益处，即减轻关节压力和减少髌骨的不良轨迹。关键人口统计学因素对髌股运动学的影响，进一步强调了在未来研究中需要控制人群特征的明确需求。因此，未来需要在对照组和患者组之间更好地匹配人口统计学数据，或者采用更先进的统计学技术来补偿混杂变量。
