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Diabetes, Obesity and Metabolism
Reference Values for Skeletal Muscle Mass at the Third Lumbar Vertebral Level Measured by Computed Tomography in a Healthy Korean Population
Ja Kyung Yoon, Sunyoung Lee, Kyoung Won Kim, Ji Eun Lee, Jeong Ah Hwang, Taeyong Park, Jeongjin Lee
Endocrinol Metab. 2021;36(3):672-677.   Published online June 8, 2021
DOI: https://doi.org/10.3803/EnM.2021.1041
  • 4,315 View
  • 158 Download
  • 13 Web of Science
  • 11 Crossref
AbstractAbstract PDFPubReader   ePub   
Background
Sarcopenia is defined as the loss of skeletal muscle mass and is associated with negative clinical outcomes. This study aimed to establish sex-specific cutoff values for the skeletal muscle area (SMA) and skeletal muscle index (SMI) at the third lumbar vertebral (L3) level using computed tomography (CT) imaging to identify sarcopenia in healthy Korean liver donors.
Methods
This retrospective study included 659 healthy liver donors (408 men and 251 women) aged 20 to 60 years who had undergone abdominal CT examinations between January 2017 and December 2018. Assessment of body composition was performed with an automated segmentation technique using a deep-learning system. Sex-specific SMA and SMI distributions were assessed, and cutoff values for determining sarcopenia were defined as values at either two standard deviations (SDs) below the mean reference value or below the fifth percentile.
Results
Using the SD definition, cutoff values for SMA and SMI were 117.04 cm2 and 39.33 cm2/m2, respectively, in men and 71.39 cm2 and 27.77 cm2/m2, respectively, in women. Using the fifth percentile definition, cutoff values for SMA and SMI were 126.88 cm2 and 40.96 cm2/m2, respectively, in men and 78.85 cm2 and 30.60 cm2/m2, respectively, in women.
Conclusion
Our data provide sex-specific cutoff values for the SMA and SMI at the L3 level measured by CT imaging in a healthy Korean population, which may be applicable for identifying sarcopenia in this population.

Citations

Citations to this article as recorded by  
  • Myosteatosis is associated with poor survival after kidney transplantation: a large retrospective cohort validation
    Jie Chen, Yue Li, Chengjie Li, Turun Song
    Abdominal Radiology.2024; 49(4): 1210.     CrossRef
  • The effect of biological agent on body composition in patients with Crohn’s disease
    Eun Jeong Choi, Dong Hoon Baek, Hong Sub Lee, Geun Am Song, Tae Oh Kim, Yong Eun Park, Chang Min Lee, Jong Hoon Lee
    BMC Gastroenterology.2023;[Epub]     CrossRef
  • The Association between the L3 Skeletal Muscle Index Derived from Computed Tomography and Clinical Outcomes in Patients with Urinary Tract Infection in the Emergency Department
    Jinjoo An, Seung Pill Choi, Jae Hun Oh, Jong Ho Zhu, Sung Wook Kim, Soo Hyun Kim
    Journal of Clinical Medicine.2023; 12(15): 5024.     CrossRef
  • Validity of computed tomography defined body composition as a prognostic factor for functional outcome after kidney transplantation
    Tim D. A. Swaab, Evelien E. Quint, Lisa B. Westenberg, Marcel Zorgdrager, Dorry L. Segev, Mara A. McAdams‐DeMarco, Stephan J. L. Bakker, Alain R. Viddeleer, Robert A. Pol
    Journal of Cachexia, Sarcopenia and Muscle.2023; 14(6): 2532.     CrossRef
  • Assessment of the Diaphragm Thickness Decrease in Critically Ill COVID-19 Patients: Could Computed Tomography Be of Aid Regarding Diaphragm Muscle Mass?
    Oana-Elena Branea, Sanda Maria Copotoiu, Diana Andreea Becica, AnaMaria Romina Budeanu, Razvan Gabriel Budeanu, Mihai Emanuel Becica, Dragos Constantin Cucoranu, Septimiu Voidazan, Monica Chis, Alexandra Elena Lazar
    Cureus.2023;[Epub]     CrossRef
  • Clinical implication of thoracic skeletal muscle volume as a predictor of ventilation-weaning failure in brain-injured patients: A retrospective observational study
    Jimi Oh, Hyun Lim, Chang Won Jeong, Min Su Kim, Jinseok Lee, Wu Seong Kang, Ui Ri An, Joo Un Park, Youngick Ahn, Youe Ree Kim, Chul Park
    Medicine.2023; 102(43): e35847.     CrossRef
  • Estimation of Muscle Mass Using Creatinine/Cystatin C Ratio in Japanese Community-Dwelling Older People
    Hiroshi Kusunoki, Yasuharu Tabara, Shotaro Tsuji, Yosuke Wada, Kayoko Tamaki, Koutatsu Nagai, Masako Itoh, Kyoko Sano, Manabu Amano, Hatsuo Maeda, Hideyuki Sugita, Yoko Hasegawa, Hiromitsu Kishimoto, Soji Shimomura, Michiya Igase, Ken Shinmura
    Journal of the American Medical Directors Association.2022; 23(5): 902.e21.     CrossRef
  • Defining reference values for low skeletal muscle index at the L3 vertebra level based on computed tomography in healthy adults: A multicentre study
    Ming Kong, Nan Geng, Ying Zhou, Ning Lin, Wenyan Song, Manman Xu, Shanshan Li, Yuetong Piao, Zuoqing Han, Rong Guo, Chao Yang, Nan Luo, Zhong Wang, Mengyuan Jiang, Lili Wang, Wanchun Qiu, Junfeng Li, Daimeng Shi, Rongkuan Li, Eddie C. Cheung, Yu Chen, Zho
    Clinical Nutrition.2022; 41(2): 396.     CrossRef
  • The Value of Artificial Intelligence-Assisted Imaging in Identifying Diagnostic Markers of Sarcopenia in Patients with Cancer
    Ying-Tzu Huang, Yi-Shan Tsai, Peng-Chan Lin, Yu-Min Yeh, Ya-Ting Hsu, Pei-Ying Wu, Meng-Ru Shen, Zhongjie Shi
    Disease Markers.2022; 2022: 1.     CrossRef
  • Assessment of Muscle Quantity, Quality and Function
    Bo Kyung Koo
    Journal of Obesity & Metabolic Syndrome.2022; 31(1): 9.     CrossRef
  • Computed Tomography-Derived Skeletal Muscle Radiodensity Is an Early, Sensitive Marker of Age-Related Musculoskeletal Changes in Healthy Adults
    Yeon Woo Jung, Namki Hong, Joon Chae Na, Woong Kyu Han, Yumie Rhee
    Endocrinology and Metabolism.2021; 36(6): 1201.     CrossRef
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Obesity and Metabolism
Variation in Serum Creatinine Level Is Correlated to Risk of Type 2 Diabetes
Jun Sung Moon, Ji Eun Lee, Ji Sung Yoon
Endocrinol Metab. 2013;28(3):207-213.   Published online September 13, 2013
DOI: https://doi.org/10.3803/EnM.2013.28.3.207
  • 4,174 View
  • 47 Download
  • 19 Crossref
AbstractAbstract PDFPubReader   
Background

Skeletal muscle is well established as a major target organ of insulin action, and is associated with the pathogenesis of type 2 diabetes. Therefore, we attempted to determine whether a variation in serum creatinine is related to the development of type 2 diabetes and other risk factors for diabetes.

Methods

A total of 2,676 nondiabetic subjects with stable and normal renal function (estimated glomerular filtration rate >60 mL/min/1.73 m2) were followed up for approximately 4.5 years. New onset diabetes was defined as fasting plasma glucose (FPG) ≥7.0 mmol/L, glycated hemoglobin (HbA1c) ≥6.5%, or subjects taking antidiabetic agents. Variation of serum creatinine (ΔCre) was defined as a difference between follow-up and baseline creatinine. In subgroup analysis, body composition was examined by bioelectric impedance analysis method.

Results

A total of 106 subjects were diagnosed with new-onset diabetes during the follow-up period. Baseline serum creatinine was not different between the new-onset diabetes and no diabetes groups. Negative ΔCre (ΔCre <0) showed an association with increased risk of type 2 diabetes after adjusting for age, sex, body mass index, systolic blood pressure, FPG, HbA1c, triglyceride, high density lipoprotein cholesterol, and γ-glutamyl transpeptidase (odds ratio, 1.885; 95% confidence interval, 1.127 to 3.153). Serum creatinine level demonstrated positive correlation with muscle mass and negative correlation with percentage of body fat in body composition analysis.

Conclusion

Serum creatinine reflected body muscle mass and the decrease of serum creatinine might be regarded as a risk factor for type 2 diabetes.

Citations

Citations to this article as recorded by  
  • Low serum creatinine, a surrogate marker of muscle mass, correlates with insulin sensitivity in nonhuman primates
    Uddhav K. Chaudhari, Barbara C. Hansen
    Journal of Medical Primatology.2023; 52(2): 100.     CrossRef
  • Identification of Novel Biomarkers of Spinal Muscular Atrophy and Therapeutic Response by Proteomic and Metabolomic Profiling of Human Biological Fluid Samples
    Megi Meneri, Elena Abati, Delia Gagliardi, Irene Faravelli, Valeria Parente, Antonia Ratti, Federico Verde, Nicola Ticozzi, Giacomo P. Comi, Linda Ottoboni, Stefania Corti
    Biomedicines.2023; 11(5): 1254.     CrossRef
  • Association of serum creatinine levels and risk of type 2 diabetes mellitus in Korea: a case control study
    Do Kyeong Song, Young Sun Hong, Yeon-Ah Sung, Hyejin Lee
    BMC Endocrine Disorders.2022;[Epub]     CrossRef
  • Impact of Female Sex on the Susceptibility to Hypernatremia Among Older Community-Dwelling Individuals in Japan
    Sho Tanaka, Midori Fujishiro, Kazuhiro Imatake, Yasuyuki Suzuki, Hisamitsu Ishihara, Shigemasa Tani
    International Journal of General Medicine.2022; Volume 15: 777.     CrossRef
  • Ameliorative Effect of Oxytocin on FBN1 and PEPCK Gene Expression, and Behavioral Patterns in Rats' Obesity-Induced Diabetes
    Asmaa Elnagar, Khalifa El-Dawy, Hussein I. El-Belbasi, Ibrahim F. Rehan, Hamdy Embark, Zeinab Al-Amgad, Obeid Shanab, Elsayed Mickdam, Gaber E. Batiha, Salman Alamery, Samer S. Fouad, Simona Cavalu, Mohammed Youssef
    Frontiers in Public Health.2022;[Epub]     CrossRef
  • Time to doubling of serum creatinine in patients with diabetes in Ethiopian University Hospital: Retrospective follow-up study
    Adeladlew Kassie Netere, Ashenafi Kibret Sendekie, Donovan Anthony McGrowder
    PLOS ONE.2022; 17(9): e0274495.     CrossRef
  • Deep Learning for Integrated Analysis of Insulin Resistance with Multi-Omics Data
    Eunchong Huang, Sarah Kim, TaeJin Ahn
    Journal of Personalized Medicine.2021; 11(2): 128.     CrossRef
  • Arsenic Secondary Methylation Capacity Is Inversely Associated with Arsenic Exposure-Related Muscle Mass Reduction
    Md. Khalequzzaman Sarker, Selim Reza Tony, Abu Eabrahim Siddique, Md. Rezaul Karim, Nazmul Haque, Zohurul Islam, Md. Shofikul Islam, Moriom Khatun, Jahidul Islam, Shakhawoat Hossain, Zahangir Alam Saud, Hideki Miyataka, Daigo Sumi, Aaron Barchowsky, Seiic
    International Journal of Environmental Research and Public Health.2021; 18(18): 9730.     CrossRef
  • Creatinine to Body Weight Ratio Is Associated with Incident Diabetes: Population-Based Cohort Study
    Yoshitaka Hashimoto, Takuro Okamura, Masahide Hamaguchi, Akihiro Obora, Takao Kojima, Michiaki Fukui
    Journal of Clinical Medicine.2020; 9(1): 227.     CrossRef
  • ¿Debemos prestar más atención a la creatinina baja?
    Carlos A. Amado Diago, José A. Amado Señaris
    Endocrinología, Diabetes y Nutrición.2020; 67(7): 486.     CrossRef
  • Arsenic exposure-related hyperglycemia is linked to insulin resistance with concomitant reduction of skeletal muscle mass
    Victor Mondal, Zubaer Hosen, Faruk Hossen, Abu Eabrahim Siddique, Selim Reza Tony, Zohurul Islam, Md. Shofikul Islam, Shakhawoat Hossain, Khairul Islam, Md. Khalequzzaman Sarker, M.M. Hasibuzzaman, Ling-Zhi Liu, Bing-Hua Jiang, Md Mominul Hoque, Zahangir
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    Manoj Kumar Sarma, Andres Saucedo, Christine Hema Darwin, Ely Richard Felker, Kavya Umachandran, Daniel Kohanghadosh, Edward Xu, Steve Raman, Michael Albert Thomas
    Magnetic Resonance Imaging.2020; 72: 95.     CrossRef
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    Carlos A. Amado Diago, José A. Amado Señaris
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    Mamoru Takeuchi, Hironori Imano, Isao Muraki, Yuji Shimizu, Mina Hayama-Terada, Akihiko Kitamura, Takeo Okada, Masahiko Kiyama, Hiroyasu Iso
    BMJ Open Diabetes Research & Care.2018; 6(1): e000492.     CrossRef
  • Assessment of kidney dysfunction with cystatin C- and creatinine-based estimated glomerular filtration rate and predicting type 2 diabetes: Toranomon Hospital Health Management Center Study 21
    Yoriko Heianza, Shigeko Hara, Kazumi Saito, Hiroshi Tsuji, Shiro Tanaka, Satoru Kodama, Tetsuro Kobayashi, Yasuji Arase, Hirohito Sone
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  • Profiling human blood serum metabolites by nuclear magnetic resonance spectroscopy: a comprehensive tool for the evaluation of hemodialysis efficiency
    Marika Kromke, Martina Palomino-Schätzlein, Horst Mayer, Stefan Pfeffer, Antonio Pineda-Lucena, Burkhard Luy, Martin Hausberg, Claudia Muhle-Goll
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  • Safety evaluation of the consumption of high dose milk fat globule membrane in healthy adults: a double-blind, randomized controlled trial with parallel group design
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  • Brief Review of Articles in 'Endocrinology and Metabolism' in 2013
    Won-Young Lee
    Endocrinology and Metabolism.2014; 29(3): 251.     CrossRef
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Case Report
Pregnancy-induced Osteoporosis Combined with Multiple Compression Fractures: A Case Report.
Ji Eun Lee, Jin Sun Jang, Sun Hee Ko, Min Hee Kim, Dong Jun Lim, Moo Il Kang, Bong Yun Cha, Sook Hee Hong, Ja seong Bae, Kyeoung Sik Ryu
Endocrinol Metab. 2011;26(2):150-154.   Published online June 1, 2011
DOI: https://doi.org/10.3803/EnM.2011.26.2.150
  • 2,093 View
  • 28 Download
  • 1 Crossref
AbstractAbstract PDF
Pregnancy associated osteoporosis (PAO) is a rare condition. It may affect women during pregnancy or after the delivery and it can induce severe back pain. Physicians can find multiple compression fractures on the plain images of these patients. However, little is known about PAO, including the prevalence, the cause, the risk factors and the prognosis. Herein we report on a case of PAO in a 38-year-old female who suffered from severe back pain induced by multiple vertebral compression fractures. After excluding the possibility of unknown malignancy, the patient underwent vertebroplasty to improve the clinical symptom. The bone biopsy results confirmed multiple benign acute compression fractures. The patient was treated with oral bisphosphonate, calcium and vitamin D. She showed clinical improvement without developing any additional vertebral fracture. When young women during pregnancy or just after the delivery complain of persistent back pain, PAO should be considered in the differential diagnosis, and early recognition and treatment are needed for PAO.

Citations

Citations to this article as recorded by  
  • Effect of teriparatide on pregnancy and lactation-associated osteoporosis with multiple vertebral fractures
    Eun Yeong Choe, Je Eun Song, Kyeong Hye Park, Hannah Seok, Eun Jig Lee, Sung-Kil Lim, Yumie Rhee
    Journal of Bone and Mineral Metabolism.2012; 30(5): 596.     CrossRef
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