Medicine (Baltimore). 2025 May 16;104(20):e42469. doi: 10.1097/MD.0000000000042469.
ABSTRACT
This study aimed to quantify the lumbar skeletal muscle index (SMI) to predict the incidence and risk of lower back pain and to develop preventive strategies to reduce the incidence of sarcopenia and lower back pain. A total of 29 patients with low back pain in our hospital between September 2022 and March 2024 were enrolled, and lumbar computed tomography data were collected, including age, sex, and visual analog scale (VAS) score for low back pain. This study included 29 patients with an average age of (53.72 ± 18.82) years and an average height of (1.65 ± 0.43) m. The degree of lower back pain was evaluated using the visual analog scoring method, with an average score of (5.14 ± 1.382). Using AutoCAD drawing software, the total cross-sectional area of the skeletal muscles at the level of the lumbar vertebrae was calculated, with an average area of (105.63 ± 27.73) cm2. The SMI at the level of the lumbar vertebrae 3 was calculated as the ratio of the total cross-sectional area of the skeletal muscles at the level of the lumbar vertebrae to height2, (38.27 ± 8.07). Statistical analysis showed a significant negative correlation (P < .01) between SMI, age, and VAS score in patients with sarcopenia, whereas there was no significant difference in SMI between the sexes in patients with sarcopenia(P > .05). There was a significant negative correlation between SMI and age as well as VAS score, indicating that lower back pain is caused by a decrease in SMI. As people age, their muscle mass and strength gradually decreases.
PMID:40388778 | DOI:10.1097/MD.0000000000042469
