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Prediction Model for Sciatic Nerve Procedures: A Cross-Sectional Study
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DOI：10.3390/jcm13247851.png)
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Objectives: 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. Methods: 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. Results: 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. Conclusions: 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.
Keyword:
sciatic nerve
ultrasound
regression model
anthropometric data
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2.9
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5.1W
被引数:
9.8W
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