{"title":"一种更准确估计肌肉质量的方法:一种新的估计方程","authors":"Shanshan Shi, Weihua Chen, Yizhou Jiang, Kaihong Chen, Ying Liao, Kun Huang","doi":"10.1002/jcsm.13254","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Measurement of muscle mass is important in the diagnosis of sarcopenia. Current measurement equipment are neither cost-effective nor standardized and cannot be used in a variety of medical settings. Some simple measurement tools have been proposed that are subjective and unvalidated. We aimed to develop and validate a new estimation equation in a more objective and standardized way, based on current proven variables that accurately reflect muscle mass.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Cross-sectional analysis with The National Health and Nutrition Examination Survey database for equation development and validation. Overall, 9875 participants were included for development (6913 participants) and validation (2962 participants), for whom the database included demographic data, physical measurements, and main biochemical indicators. Appendicular skeletal muscle mass (ASM) was estimated by dual-energy x-ray absorptiometry (DXA) and low muscle mass was defined by reference to five international diagnostic criteria. Linear regression was used to estimate the logarithm of the actual ASM from demographic data, physical measurements, and biochemical indicators.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>This study of 9875 participants comprised 4492 females (49.0%), with a weighted mean (SE) age of 41.83 (0.36) years and range of 12 to 85 years. The estimated ASM equations performed well in the validation data set. The variability in estimated ASM was low compared with the actual ASM (<i>R</i><sup>2</sup>: Equation 1 = 0.91, Equation 4 = 0.89), with low bias (median difference: Equation 1 = −0.64, Equation 4 = 0.07; root mean square error: Equation 1 = 1.70 [1.69–1.70], Equation 4 = 1.85 [1.84–1.86]), high precision (interquartile range of the differences: Equation 1 = 1.87, Equation 4 = 2.17), and high efficacy in diagnosing low muscle mass (area under the curve: Equation 1 = 0.91 to 0.95, Equation 4 = 0.90 to 0.94).</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The estimated ASM equations are accurate and simple and can be routinely applied clinically to estimate ASM and thus assess sarcopenia.</p>\n </section>\n </div>","PeriodicalId":186,"journal":{"name":"Journal of Cachexia, Sarcopenia and Muscle","volume":"14 4","pages":"1753-1761"},"PeriodicalIF":8.9000,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcsm.13254","citationCount":"0","resultStr":"{\"title\":\"A more accurate method to estimate muscle mass: A new estimation equation\",\"authors\":\"Shanshan Shi, Weihua Chen, Yizhou Jiang, Kaihong Chen, Ying Liao, Kun Huang\",\"doi\":\"10.1002/jcsm.13254\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Measurement of muscle mass is important in the diagnosis of sarcopenia. Current measurement equipment are neither cost-effective nor standardized and cannot be used in a variety of medical settings. Some simple measurement tools have been proposed that are subjective and unvalidated. We aimed to develop and validate a new estimation equation in a more objective and standardized way, based on current proven variables that accurately reflect muscle mass.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>Cross-sectional analysis with The National Health and Nutrition Examination Survey database for equation development and validation. Overall, 9875 participants were included for development (6913 participants) and validation (2962 participants), for whom the database included demographic data, physical measurements, and main biochemical indicators. Appendicular skeletal muscle mass (ASM) was estimated by dual-energy x-ray absorptiometry (DXA) and low muscle mass was defined by reference to five international diagnostic criteria. Linear regression was used to estimate the logarithm of the actual ASM from demographic data, physical measurements, and biochemical indicators.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>This study of 9875 participants comprised 4492 females (49.0%), with a weighted mean (SE) age of 41.83 (0.36) years and range of 12 to 85 years. The estimated ASM equations performed well in the validation data set. The variability in estimated ASM was low compared with the actual ASM (<i>R</i><sup>2</sup>: Equation 1 = 0.91, Equation 4 = 0.89), with low bias (median difference: Equation 1 = −0.64, Equation 4 = 0.07; root mean square error: Equation 1 = 1.70 [1.69–1.70], Equation 4 = 1.85 [1.84–1.86]), high precision (interquartile range of the differences: Equation 1 = 1.87, Equation 4 = 2.17), and high efficacy in diagnosing low muscle mass (area under the curve: Equation 1 = 0.91 to 0.95, Equation 4 = 0.90 to 0.94).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>The estimated ASM equations are accurate and simple and can be routinely applied clinically to estimate ASM and thus assess sarcopenia.</p>\\n </section>\\n </div>\",\"PeriodicalId\":186,\"journal\":{\"name\":\"Journal of Cachexia, Sarcopenia and Muscle\",\"volume\":\"14 4\",\"pages\":\"1753-1761\"},\"PeriodicalIF\":8.9000,\"publicationDate\":\"2023-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcsm.13254\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cachexia, Sarcopenia and Muscle\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jcsm.13254\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cachexia, Sarcopenia and Muscle","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jcsm.13254","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A more accurate method to estimate muscle mass: A new estimation equation
Background
Measurement of muscle mass is important in the diagnosis of sarcopenia. Current measurement equipment are neither cost-effective nor standardized and cannot be used in a variety of medical settings. Some simple measurement tools have been proposed that are subjective and unvalidated. We aimed to develop and validate a new estimation equation in a more objective and standardized way, based on current proven variables that accurately reflect muscle mass.
Methods
Cross-sectional analysis with The National Health and Nutrition Examination Survey database for equation development and validation. Overall, 9875 participants were included for development (6913 participants) and validation (2962 participants), for whom the database included demographic data, physical measurements, and main biochemical indicators. Appendicular skeletal muscle mass (ASM) was estimated by dual-energy x-ray absorptiometry (DXA) and low muscle mass was defined by reference to five international diagnostic criteria. Linear regression was used to estimate the logarithm of the actual ASM from demographic data, physical measurements, and biochemical indicators.
Results
This study of 9875 participants comprised 4492 females (49.0%), with a weighted mean (SE) age of 41.83 (0.36) years and range of 12 to 85 years. The estimated ASM equations performed well in the validation data set. The variability in estimated ASM was low compared with the actual ASM (R2: Equation 1 = 0.91, Equation 4 = 0.89), with low bias (median difference: Equation 1 = −0.64, Equation 4 = 0.07; root mean square error: Equation 1 = 1.70 [1.69–1.70], Equation 4 = 1.85 [1.84–1.86]), high precision (interquartile range of the differences: Equation 1 = 1.87, Equation 4 = 2.17), and high efficacy in diagnosing low muscle mass (area under the curve: Equation 1 = 0.91 to 0.95, Equation 4 = 0.90 to 0.94).
Conclusions
The estimated ASM equations are accurate and simple and can be routinely applied clinically to estimate ASM and thus assess sarcopenia.
期刊介绍：
The Journal of Cachexia, Sarcopenia, and Muscle is a prestigious, peer-reviewed international publication committed to disseminating research and clinical insights pertaining to cachexia, sarcopenia, body composition, and the physiological and pathophysiological alterations occurring throughout the lifespan and in various illnesses across the spectrum of life sciences. This journal serves as a valuable resource for physicians, biochemists, biologists, dieticians, pharmacologists, and students alike.
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