Sarcopenia is defined as the loss of muscle mass and strength that occurs with aging. Although the etiology, pathogenesis, and diagnosis of sarcopenia are obscure, sarcopenia has been suggested to play a pivotal role in the pathogenesis of frailty and functional impairment in diabetes. The aim of this article was to provide an overview of the pathogenesis, diagnosis, epidemiology, and clinical implications of sarcopenia and the relationship between diabetes and sarcopenia.
Aging ; Diabetes Mellitus ; Diagnosis ; Epidemiology ; Sarcopenia*

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In this study, we aimed to develop a machine learning model for sarcopenia diagnosis using clinical characteristics and laboratory indicators of aging cohorts. METHODS: We developed models of sarcopenia using the baseline data from the West China Health and Aging Trend (WCHAT) study. For external validation, we used the Xiamen Aging Trend (XMAT) cohort. We compared the support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGB), and Wide and Deep (W&D) models. The area under the receiver operating curve (AUC) and accuracy (ACC) were used to evaluate the diagnostic efficiency of the models. RESULTS: The WCHAT cohort, which included a total of 4057 participants for the training and testing datasets, and the XMAT cohort, which consisted of 553 participants for the external validation dataset, were enrolled in this study. Among the four models, W&D had the best performance (AUC = 0.916 ± 0.006, ACC = 0.882 ± 0.006), followed by SVM (AUC =0.907 ± 0.004, ACC = 0.877 ± 0.006), XGB (AUC = 0.877 ± 0.005, ACC = 0.868 ± 0.005), and RF (AUC = 0.843 ± 0.031, ACC = 0.836 ± 0.024) in the training dataset. Meanwhile, in the testing dataset, the diagnostic efficiency of the models from large to small was W&D (AUC = 0.881, ACC = 0.862), XGB (AUC = 0.858, ACC = 0.861), RF (AUC = 0.843, ACC = 0.836), and SVM (AUC = 0.829, ACC = 0.857). In the external validation dataset, the performance of W&D (AUC = 0.970, ACC = 0.911) was the best among the four models, followed by RF (AUC = 0.830, ACC = 0.769), SVM (AUC = 0.766, ACC = 0.738), and XGB (AUC = 0.722, ACC = 0.749). CONCLUSIONS: The W&D model not only had excellent diagnostic performance for sarcopenia but also showed good economic efficiency and timeliness. It could be widely used in primary health care institutions or developing areas with an aging population. TRIAL REGISTRATION Chictr.org, ChiCTR 1800018895.
Humans ; Aged ; Sarcopenia/diagnosis* ; Deep Learning ; Aging ; Algorithms ; Biomarkers

BACKGROUND: The Global Leadership Initiative on Malnutrition (GLIM) criteria were published to build a global consensus on nutritional diagnosis. Reduced muscle mass is a phenotypic criterion with strong evidence to support its inclusion in the GLIM consensus criteria. However, there is no consensus regarding how to accurately measure and define reduced muscle mass in clinical settings. This study aimed to investigate the optimal reference values of skeletal muscle mass index for diagnosing sarcopenia and GLIM-defined malnutrition, as well as the prevalence of GLIM-defined malnutrition in hospitalized cirrhotic patients. METHODS: This retrospective study was conducted on 1002 adult patients with liver cirrhosis between January 1, 2018, and February 28, 2022, at Beijing You-An Hospital, Capital Medical University. Adult patients with a clinical diagnosis of liver cirrhosis and who underwent an abdominal computed tomography (CT) examination during hospitalization were included in the study. These patients were randomly divided into a modeling group (cohort 1, 667 patients) and a validation group (cohort 2, 335 patients). In cohort 1, optimal cut-off values of skeletal muscle index at the third lumbar skeletal muscle index (L3-SMI) were determined using receiver operating characteristic analyses against in-hospital mortality in different gender groups. Next, patients in cohort 2 were screened for nutritional risk using the Nutritional Risk Screening 2002 (NRS-2002), and malnutrition was diagnosed by GLIM criteria. Additionally, the reference values of reduced muscle mass in GLIM criteria were derived from the L3-SMI values from cohort 1. Multivariate logistic regression analysis was used to analyze the association between GLIM-defined malnutrition and clinical outcomes. RESULTS: The optimal cut-off values of L3-SMI were 39.50 cm 2 /m 2 for male patients and 33.06 cm 2 /m 2 for female patients. Based on the cut-off values, 31.63% (68/215) of the male patients and 23.3% (28/120) of the female patients had CT-determined sarcopenia in cohort 2. The prevalence of GLIM-defined malnutrition in cirrhotic patients was 34.3% (115/335) and GLIM-defined malnutrition was an independent risk factor for in-hospital mortality in patients with liver cirrhosis ( Wald = 6.347, P  = 0.012). CONCLUSIONS This study provided reference values for skeletal muscle mass index and the prevalence of GLIM-defined malnutrition in hospitalized patients with liver cirrhosis. These reference values will contribute to applying the GLIM criteria in cirrhotic patients.
Adult ; Female ; Humans ; Male ; Leadership ; Liver Cirrhosis ; Malnutrition/diagnosis* ; Nutritional Status ; Retrospective Studies ; Sarcopenia/diagnosis*

Aging process can be characterized as a spontaneous decrease of function in various organs with age. Muscle, as a big organ of human body, undergoes aging process presenting with loss of muscle mass, "sarcopenia". Recently, several working groups have tried to make consensus about sarcopenia for definition and diagnosis. Muscle mass is known to be closely related with bone, brain, fat, cardiovascular and metabolic systems. With increased understanding, clinical and basic researches about sarcopenia have been also increased rapidly from various areas of health science and technology. In this paper, the history and recent concepts of sarcopenia were reviewed and brief discussion of its prospect in the field of neurosurgery was done.
Aging ; Brain ; Consensus ; Diagnosis ; Human Body ; Muscles ; Neurosurgery* ; Sarcopenia* ; Spine ; Stroke

Aging processes are inevitably accompanied by structural and functional changes in vital organs. Skeletal muscle, which accounts for 40% of total body weight, deteriorates quantitatively and qualitatively with aging. Skeletal muscle is known to play diverse crucial physical and metabolic roles in humans. Sarcopenia is a condition characterized by significant loss of muscle mass and strength. It is related to subsequent frailty and instability in the elderly population. Because muscle tissue is involved in multiple functions, sarcopenia is closely related to various adverse health outcomes. Along with increasing recognition of the clinical importance of sarcopenia, several international study groups have recently released their consensus on the definition and diagnosis of sarcopenia. In practical terms, various skeletal muscle mass indices have been suggested for assessing sarcopenia: appendicular skeletal muscle mass adjusted for height squared, weight, or body mass index. A different prevalence and different clinical implications of sarcopenia are highlighted by each definition. The discordances among these indices have emerged as an issue in defining sarcopenia, and a unifying definition for sarcopenia has not yet been attained. This review aims to compare these three operational definitions and to introduce an optimal skeletal muscle mass index that reflects the clinical implications of sarcopenia from a metabolic perspective.
Aged ; Aging ; Body Mass Index ; Body Weight ; Consensus ; Diagnosis ; Humans ; Muscle, Skeletal* ; Prevalence ; Sarcopenia*

BACKGROUND: This study aimed to evaluate the effectiveness of lean body mass analysis using dual-energy X-ray absorptiometry (DEXA) for diagnosing sarcopenia. METHODS: We conducted a systematic review by searching eight Korean databases and international databases, including Ovid-MEDLINE, Embase, and Cochrane Library. Twenty-five studies using DEXA were included in the final assessment. Two reviewers independently assessed the quality of the included studies and extracted data. The quality of the studies was assessed according to the Scottish Intercollegiate Guidelines Network tool. RESULTS: The effectiveness of lean body mass analysis using DEXA was assessed by means of correlations with comparators, relevance to clinical symptoms, and forecasting of prognosis. The correlations with comparators (magnetic resonance imaging, computed tomography, bioelectrical impedance analysis, and anthropometry) took different positions. The risk ratio (RR) or odds ratio (OR) of the decrease in physical functions was 0.57-2.48, and the RR of osteoporosis was 1.15-9.4. The hazard ratio of death was 1.24-3.12, OR of cardiovascular disease was 1.768, and RR of survival was 0.85. CONCLUSION: Lean body mass analysis using DEXA for diagnosing sarcopenia seems promising, but more studies are needed to clarify the diagnostic criteria for sarcopenia and cut-off for DEXA.
Absorptiometry, Photon* ; Cardiovascular Diseases ; Diagnosis* ; Electric Impedance ; Forecasting ; Odds Ratio ; Osteoporosis ; Prognosis ; Sarcopenia*

Sarcopenia (Greek ‘sarx’ or flesh+‘penia’ or loss) originally is proposed as the term to describe age-related decrease of muscle mass. These days, sarcopenia is defined as a syndrome characterized by progressive loss of skeletal muscle mass and strength with a risk of adverse outcomes such as poor quality of life, physical disability, and death. In the recent decade, there are a few of consensus; European, international, and Asian consensus panels have published definitions. Additionally, measurement techniques that can be used for research and clinical practice settings according to their suitability are suggested. Many studies are reported about the association with sarcopenia and neurologic diseases, however, the results are heterogenous due to lack of sufficient studies. Some pharmacologic and non-pharmacologic methods are suggested as the intervention of sarcopenia, although there are not enough studies, yet. In this review, we summarize current understanding of the diagnostic sarcopenia and neurological point of view of sarcopenia.
Asian Continental Ancestry Group ; Consensus ; Diagnosis* ; Humans ; Muscle, Skeletal ; Quality of Life ; Sarcopenia*

BACKGROUND: Sarcopenia is considering important disease entity in elderly. Several study groups define the sum of the muscle masses of the four limbs as appendicular skeletal mass (ASM) to calculate skeletal muscle index (SMI). The purpose of this study was to determine cut point of SMI for sarcopenia in Korean women. METHODS: This study was based on data obtained from the 2008 to 2011 Korean National Health and Nutrition Examination Survey (KNHANES) IV and V. A whole body dual energy X-ray absorptiometry scan were performed on individuals of > or =10 years old from July 2008 to May 2011. In the analysis, 11,633 women were included. ASM was calculated and SMI was obtained as ASM/height2. Cutoff value was defined two standard deviations below mean values for young reference group. RESULTS: Of 11,633 women aged 10 to 97 years, mean and standard deviation of year was 46.73+/-18.54 years. The highest level of height was noted in 20's and the highest total sum of skeletal mass was seen 14.87 kg in 40's. The highest value of SMI was noted in 60's in Korean women. Cutoff value as mean value of young women was decided with SMI of 30's and 40's that have peak ASM. Mean and standard deviation of SMI in those ages was 5.9+/-0.7 kg/m2. A SMI of two standard deviations below the mean SMI of reference groups was 4.4 kg/m2 as cutoff value. CONCLUSIONS: This study shows that 4.4 kg/m2 of SMI in Korean women was cutoff value of sarcopenia. Further study is clearly required to decide cutoff value of SMI for sarcopenia, especially for Korean women.
Absorptiometry, Photon ; Aged ; Diagnosis ; Extremities ; Female ; Humans ; Korea ; Muscle, Skeletal* ; Nutrition Surveys ; Reference Values* ; Sarcopenia*

BACKGROUND/AIMS: The most widely used method for diagnosing sarcopenia is the skeletal muscle index (SMI). Several studies have suggested that psoas muscle thickness per height (PMTH) is also effective for detecting sarcopenia and predicting prognosis in patients with cirrhosis. The aim of this study was to evaluate the optimal cutoff values of PMTH for detecting sarcopenia in cirrhotic patients. METHODS: All cirrhotic patients who underwent abdominal computed tomography (CT) scan including L3 and umbilical levels for measuring SMI and transverse psoas muscle thickness, respectively, were included. Two definitions of sarcopenia were used: (1) sex-specific cutoffs of SMI (≤52.4 cm² /m² in men and ≤38.5 cm² /m² in women) for SMI-sarcopenia and (2) cutoff of PMTH ( < 16.8 mm/m) for PMTH-sarcopenia. RESULTS: Six hundred fifty-three patients were included. The average age was 53.6 ± 10.2 years, and 499 patients (76.4%) were men. PMTH correlated well with SMI in both men and women (P < 0.001). Two hundred forty-one (36.9%) patients met the criteria for SMI-sarcopenia. The best PMTH cutoff values for predicting SMI-sarcopenia were 17.3 mm/m in men and 10.4 mm/m in women, and these were defined as sex-specific cutoffs of PMTH (SsPMTH). The previously published cutoff of PMTH was defined as sex-nonspecific cutoff of PMTH (SnPMTH). Two hundred thirty (35.2%) patients were diagnosed with SsPMTH-sarcopenia, and 280 (44.4%) patients were diagnosed with SnPMTH-sarcopenia. On a multivariate Cox regression analysis, SsPMTH-sarcopenia (hazard ratio [HR], 1.944; 95% confidence interval [CI], 1.144–3.304; P=0.014) was significantly associated with mortality, while SnPMTH-sarcopenia was not (HR, 1.446; 95% CI, 0.861–2.431; P=0.164). CONCLUSIONS: PMTH was well correlated with SMI in cirrhotic patients. SsPMTH-sarcopenia was an independent predictor of mortality in these patients and more accurately predicted mortality compared to SnPMTH-sarcopenia.
Diagnosis* ; Female ; Fibrosis ; Humans ; Liver Cirrhosis* ; Liver* ; Male ; Methods ; Mortality ; Muscle, Skeletal ; Prognosis ; Psoas Muscles* ; Sarcopenia*

BACKGROUND: The aim of this study was to determine the accuracy and error range of hand grip strength measurement using various methods. METHODS: Methods used for measurement of hand grip strength in 34 epidemiologic studies on sarcopenia were analyzed. Maximum grip strength was measured in a sitting position with the elbow flexed at 90 degrees, the shoulder in 0 degrees flexion, and the wrist in neutral position (0 degrees). Maximum grip strength in standing position was measured with the shoulder in 180 degrees flexion, the elbow fully extended, and the wrist in neutral position (0 degrees). Three measurements were taken on each side at 30 sec intervals. The uncertainty of measurement was calculated. RESULTS: The combined uncertainty in sitting position on the right and left sides was 1.14% and 0.38%, respectively, and the combined uncertainty in standing position on the right and left sides was 0.35 and 1.20, respectively. The expanded uncertainty in sitting position on the right and left sides was 2.28 and 0.79, respectively, and the expanded uncertainty in standing position on the right and left sides was 0.71 and 2.41, respectively (k=2). CONCLUSIONS: Uncertainty of hand grip strength measurement was identified in this study, and a significant difference was observed between measurement. For more precise diagnosis of sarcopenia, dynamometers need to be corrected to overcome uncertainty.
Diagnosis ; Elbow ; Epidemiologic Studies ; Hand Strength* ; Hand* ; Humans ; Posture ; Sarcopenia* ; Shoulder ; Uncertainty* ; Wrist