135 - The evaluation of feasibility of psoas, paraspinal, and gluteal muscle index as a predictor for diagnosing sarcopenia in patients with degenerative lumbar disease

Introduction
Sarcopenia is characterized by a progressive and generalized loss of skeletal muscle mass and strength, resulting in decreased activity and physical function. In 2019, the Asian Working Group for Sarcopenia (AWGS) defined sarcopenia as “age-related loss of muscle mass, plus low muscle strength, and/or low physical performance” and suggested cutoffs for each diagnostic component. To our knowledge, no study has investigated psoas, paraspinal, and gluteal muscle indices as a predictor of diagnosing sarcopenia in patients with degenerative lumbar disease (DLD).

Aims/Objectives
Thus, this study aimed to investigate whether three muscle indices measured by computed tomography (CT) can be used to predict diagnosing sarcopenia in patients with DLD.

Materials & Methods
From December 2021 to June 2022, patients who planned to undergo surgery for DLD with documented physical performance test, hand grip strength (HGS), dual-energy X-ray absorptiometry (DEXA), and multiaxial CT scan results were enrolled. Patients' physical performance was evaluated by performing the following two tests, a 6-meter walking test, and a sit-to-stand test. The psoas (PMI), paraspinal (PaMI), and gluteal muscle indices (GMI) were calculated from the CT scan results, and the appendicular skeletal mass (ASM) was measured using DEXA. The diagnosis of sarcopenia was determined according to the 2019 AWGS criteria; low ASM (Male < 7.0 kg/m2, Female < 5.4kg/m2) with low muscle strength (HGS, Male < 29 kg, Female < 18 kg) or poor physical performance (6-meter walk < 1.0 m/s or sit-to-stand test ≥ 12 sec).

Results
A total of 164 patients were enrolled in this study. One hundred and twelve patients (68%) were diagnosed as sarcopenia. And 109 (66%) and 73 (45%) patients were fulfilled the criteria of low ASM with poor physical performance and low ASM with low HGS, respectively. The GMI of the patients diagnosed as sarcopenia was significantly lower than that of the normal patients (66.6 ± 16.0 vs 77.0 ± 16.4, P < 0.001, respectively). In the multivariate logistic regression analysis, the GMI was the only significant parameter for diagnosing sarcopenia among the three muscle indices (β = -0.034 and P = 0.008).

Conclusions
The present study highlights that GMI, rather than PMI, is a possible predictor for diagnosing sarcopenia among skeletal muscle indices in patients with DLD. In addition, the high prevalence of sarcopenia in this study population might suggest that the AWGS diagnostic criteria for sarcopenia may have been overfitted for the DLD patients, and further investigation is needed.