Ming Kong1, Nan Geng1, Ying Zhou2, Ning Lin1, Wenyan Song3, Manman Xu1, Shanshan Li1, Yuetong Piao4, Zuoqing Han4, Rong Guo4, Chao Yang5, Nan Luo6, Zhong Wang7, Mengyuan Jiang7, Lili Wang8, Wanchun Qiu9, Junfeng Li10, Daimeng Shi7, Rongkuan Li6, Eddie C Cheung11, Yu Chen12, Zhongping Duan13. 1. Fourth Department of Liver Disease, Beijing Youan Hospital, Capital Medical University, Beijing Municipal Key Laboratory of Liver Failure and Artificial Liver Treatment Research, Beijing 100069, China. 2. Postgraduate Training Base of Jinzhou Medical University. Department of Gastroenterology and Hepatology, The PLA Rocket Force Characteristic Medical Center, Beijing 100088, China. 3. Department of Radiology, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China. 4. Dalian Medical University, Dalian 116027, China. 5. Department of Radiology, The Second Hospital of Dalian Medical University, Dalian 116027, China. 6. Department of Infection, The Second Hospital of Dalian Medical University, Dalian 116027, China. 7. Diagnosis and Treatment Center of Hepatobiliary Diseases, Nanyang First People's Hospital, Nanyang 473000, China. 8. The Department of Radiology, The First Hospital of Lanzhou University, Lanzhou 730000, China. 9. The First Clinical Medical School of Lanzhou University, Lanzhou 730000, China. 10. Institute of Infectious Diseases & Department of Infectious Diseases, The First Hospital of Lanzhou University, Lanzhou 730000, China. 11. Division of Gastroenterology, School of Medicine, University of California Davis, Davis, CA, USA; Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China. 12. Fourth Department of Liver Disease, Beijing Youan Hospital, Capital Medical University, Beijing Municipal Key Laboratory of Liver Failure and Artificial Liver Treatment Research, Beijing 100069, China. Electronic address: chybeyond1071@ccmu.edu.cn. 13. Fourth Department of Liver Disease, Beijing Youan Hospital, Capital Medical University, Beijing Municipal Key Laboratory of Liver Failure and Artificial Liver Treatment Research, Beijing 100069, China. Electronic address: duan@ccmu.edu.cn.
Abstract
BACKGROUND & AIMS: Skeletal muscle mass loss is an important aspect of malnutrition and is closely related to adverse clinical outcomes. Computed tomography (CT) is the gold standard for analysing muscle mass, and the skeletal muscle index at the third lumbar vertebra (L3-SMI), measured using CT, is an important indicator to evaluate total skeletal tissue. The aims of this study were to establish reference values for low L3-SMI in Northern China, and to investigate the correlation between L3-SMI and age, and the correlation between L3-SMI and body mass index (BMI). METHODS: This was a multicentre, retrospective, cross-sectional study. A search of abdominal CT imaging reports, using specific keywords, was conducted in four representative cities in northern China, from January 2016 to March 2021. Transverse CT images at the level of the third lumbar vertebra (L3) were identified, exported from the Radiology Information System, and measured using the analysis software SliceOmatic. Statistical analyses were performed using SPSS 24.0, and significance level was set at p < 0.05. Mean, standard deviations (SD) and percentiles (p5, p10, p25, p50, p75, p90, p95) were used to describe the distribution of L3-SMI in the study population. Low skeletal muscle index was defined as a 5% percentile, or two standard deviations below the mean value of younger healthy individuals (age 20-39 years). RESULTS: The study included 1787 healthy individuals, with a median age of 45 (25) years (range 20-88 years), and a median BMI of 23.1 (4.1) kg/m2 (range 18.5-38.7 kg/m2). Among them, 700 healthy individuals (39.1%) were aged 20-39 years. L3-SMI had a negative linear correlation with age, and a positive linear correlation with BMI. The L3-SMI reference values used to define low skeletal muscle mass loss in the Northern Chinese population, using the 5% percentile, were 40.2 cm2/m2 in men, and 31.6 cm2/m2 in women. Using the mean minus two standard deviations protocol, the reference values were 37.9 cm2/m2 and 28.6 cm2/m2 in men and women, respectively. CONCLUSIONS: This study analysed the human body composition of 1787 healthy people in four cities in northern China, using CT, and established diagnostic thresholds of skeletal muscle mass depletion based on 700 younger healthy adults, using the 5% percentile and mean-2SD methods. These reference values can be used to diagnose malnutrition in patients and may aide clinicians in predicting prognosis and improving nutritional therapy. Further research is warranted to determine the prognostic role of reference values against clinical outcomes in different disease populations.
BACKGROUND & AIMS: Skeletal muscle mass loss is an important aspect of malnutrition and is closely related to adverse clinical outcomes. Computed tomography (CT) is the gold standard for analysing muscle mass, and the skeletal muscle index at the third lumbar vertebra (L3-SMI), measured using CT, is an important indicator to evaluate total skeletal tissue. The aims of this study were to establish reference values for low L3-SMI in Northern China, and to investigate the correlation between L3-SMI and age, and the correlation between L3-SMI and body mass index (BMI). METHODS: This was a multicentre, retrospective, cross-sectional study. A search of abdominal CT imaging reports, using specific keywords, was conducted in four representative cities in northern China, from January 2016 to March 2021. Transverse CT images at the level of the third lumbar vertebra (L3) were identified, exported from the Radiology Information System, and measured using the analysis software SliceOmatic. Statistical analyses were performed using SPSS 24.0, and significance level was set at p < 0.05. Mean, standard deviations (SD) and percentiles (p5, p10, p25, p50, p75, p90, p95) were used to describe the distribution of L3-SMI in the study population. Low skeletal muscle index was defined as a 5% percentile, or two standard deviations below the mean value of younger healthy individuals (age 20-39 years). RESULTS: The study included 1787 healthy individuals, with a median age of 45 (25) years (range 20-88 years), and a median BMI of 23.1 (4.1) kg/m2 (range 18.5-38.7 kg/m2). Among them, 700 healthy individuals (39.1%) were aged 20-39 years. L3-SMI had a negative linear correlation with age, and a positive linear correlation with BMI. The L3-SMI reference values used to define low skeletal muscle mass loss in the Northern Chinese population, using the 5% percentile, were 40.2 cm2/m2 in men, and 31.6 cm2/m2 in women. Using the mean minus two standard deviations protocol, the reference values were 37.9 cm2/m2 and 28.6 cm2/m2 in men and women, respectively. CONCLUSIONS: This study analysed the human body composition of 1787 healthy people in four cities in northern China, using CT, and established diagnostic thresholds of skeletal muscle mass depletion based on 700 younger healthy adults, using the 5% percentile and mean-2SD methods. These reference values can be used to diagnose malnutrition in patients and may aide clinicians in predicting prognosis and improving nutritional therapy. Further research is warranted to determine the prognostic role of reference values against clinical outcomes in different disease populations.