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The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease
The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease
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The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease
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The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease
The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease

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The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease
The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease
Journal Article

The cross-sectional area of gluteal muscle on multiaxial CT scan as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease

2024
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Overview
Purpose This study examined the predictive value of the gluteal muscle index (GMI) for diagnosing sarcopenia in patients with degenerative lumbar disease (DLD), highlighting the need for effective diagnostic markers in this population. Methods This prospective observational study included 202 elderly patients scheduled for lumbar spine surgery. Muscle indices for psoas, paraspinal, and gluteal muscles were measured using multiaxial computed tomography. Sarcopenia was diagnosed per the 2019 Asian Working Group for Sarcopenia (AWGS) criteria. Statistical analysis comprised univariate and multivariate logistic regression to identify predictors of sarcopenia. Results Of patients, 77% were diagnosed with sarcopenia. The GMI and psoas muscle index (PMI) were identified as significant predictors of sarcopenia in the univariate analysis. Multivariate analysis confirmed their predictive value, with higher indices correlating with a reduced risk of sarcopenia (GMI odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.92–0.97; PMI OR = 0.95, 95% CI = 0.92–0.98, both P  < .001). Conclusion The GMI serves as a reliable predictor of sarcopenia in elderly patients undergoing lumbar spine surgery for DLD, suggesting a significant role of gluteal muscles in diagnosing sarcopenia. Incorporating GMI into clinical assessments is critical to better manage and diagnose sarcopenia in this population.