Minguez-Esteban Isabel, González-de-la-Flor Ángel, Villafañe Jorge Hugo, Valera-Calero Juan Antonio, Plaza-Manzano Gustavo, Belón-Pérez Pedro, Romero-Morales Carlos
Department of Physiotherapy, Faculty of Medicine, Health and Sports, European University of Madrid, Villaviciosa de Odón, 28670 Madrid, Spain.
Department of Radiology, Rehabilitation and Physiotherapy, Faculty of Nursery, Physiotherapy and Podiatry, Complutense University of Madrid, 28040 Madrid, Spain.
J Clin Med. 2024 Dec 23;13(24):7851. doi: 10.3390/jcm13247851.
We aimed to create a predictive model to estimate sciatic nerve depth using anthropometric and demographic data to enhance safety and precession in needle-based interventions. Setting: The study was conducted at Universidad Europea de Madrid, Spain. A Cross-sectional observational study was carried out between January and April 2024. The study included fifty volunteers aged 18-45 years, without any muscle tone affections, lower limb asymmetries, or history of lower limb surgeries. Demographic and anthropometric data were collected, including sex, age, height, weight, BMI, and leg length measure and thigh circumference at specific points. The sciatic nerve depth was measured using ultrasound imaging under the gluteal fold and in the posterior middle third of the thigh. Correlation analysis revealed significant associations between thigh circumference at the proximal and middle third and sciatic nerve depth. A multiple linear regression model identified that the proximal thigh circumference was a significant predictor of sciatic nerve depth, explaining 44.5% of the variance. The variance increased to 49.7% when gender was added. The depth of the sciatic nerve in the middle third explained 38.2% of the variance. And the inclusion of gender in the model explained 40.8% of the variance for the middle third. This study identify significant predictors such as the thigh girth at the proximal and mid-third levels, gender, and the BMI. These findings suggest that clinicians can use these anthropometric measurements to estimate sciatic nerve depth more accurately, reducing the risk of accidental nerve injury and improve the precision and safety of needling procedures during invasive procedures.
我们旨在创建一个预测模型,利用人体测量和人口统计学数据来估计坐骨神经深度,以提高基于针刺的干预措施的安全性和精确性。背景:该研究在西班牙马德里欧洲大学进行。于2024年1月至4月开展了一项横断面观察性研究。该研究纳入了50名年龄在18 - 45岁之间的志愿者,他们没有任何肌张力异常、下肢不对称或下肢手术史。收集了人口统计学和人体测量数据,包括性别、年龄、身高、体重、BMI、腿长测量值以及特定部位的大腿围度。使用超声成像在臀褶下方和大腿后中三分之一处测量坐骨神经深度。相关性分析显示,近端和中三分之一处的大腿围度与坐骨神经深度之间存在显著关联。多元线性回归模型确定近端大腿围度是坐骨神经深度的一个重要预测指标,解释了44.5%的方差。加入性别因素后,方差增加到49.7%。中三分之一处坐骨神经深度解释了38.2%的方差。在模型中加入性别因素后,中三分之一处解释了40.8%的方差。本研究确定了重要的预测指标,如近端和中三分之一水平的大腿围度、性别和BMI。这些发现表明,临床医生可以使用这些人体测量指标更准确地估计坐骨神经深度,降低意外神经损伤的风险,并提高侵入性操作过程中针刺程序的精确性和安全性。