Appendicular skeletal muscle in hospitalised hip-fracture patients: development and cross-validation of anthropometric prediction equations against dual-energy X-ray absorptiometry
accurate and practical assessment methods for assessing appendicular skeletal muscle (ASM) is of clinical importance for the diagnosis of geriatric syndromes associated with skeletal muscle wasting. the purpose of this study was to develop and cross-validate novel anthropometric prediction equations...
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Veröffentlicht in: | Age and ageing 2014-11, Vol.43 (6), p.857-862 |
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description | accurate and practical assessment methods for assessing appendicular skeletal muscle (ASM) is of clinical importance for the diagnosis of geriatric syndromes associated with skeletal muscle wasting.
the purpose of this study was to develop and cross-validate novel anthropometric prediction equations for the estimate of ASM in older adults post-surgical fixation for hip fracture, using dual-energy X-ray absorptiometry (DEXA) as the criterion measure.
community-dwelling older adults (aged ≥65 years) recently hospitalised for hip fracture.
participants were recruited from hospital in the acute phase of recovery.
validation measurement study.
a total of 79 hip fracture patients were involved in the development of the regression models (MD group). A further 64 hip fracture patients also recruited in the early phase of recovery were used in the cross-validation of the regression models (CV group). Multiple linear regression analyses were undertaken in the MD group to identify the best performing prediction models. The linear coefficient of determination (R(2)) in addition to the standard error of the estimate (SEE) were calculated to determine the best performing model. Agreement between estimated ASM and ASMDEXA in the CV group was assessed using paired t-tests with the 95% limits of agreement (LOA) assessed using Bland-Altman analyses.
the mean age of all the participants was 82.1 ± 7.3 years. The best two prediction models are presented as follows: ASMPRED-EQUATION_1: 22.28 - (0.069 * age) + (0.407 * weight) - (0.807 * BMI) - (0.222 * MAC) (adjusted R(2): 0.76; SEE: 1.80 kg); ASMPRED-EQUATION_2: 16.77 - (0.036 * age) + (0.385 * weight) - (0.873 * BMI) (adjusted R(2): 0.73; SEE: 1.90 kg). The mean bias from the CV group between ASMDEXA and the predictive equations is as follows: ASMDEXA - ASMPRED-EQUATION_1: 0.29 ± 2.6 kg (LOA: -4.80, 5.40 kg); ASMDEXA - ASMPRED-EQUATION_2: 0.13 ± 2.5 kg (LOA: -4.77, 5.0 kg). No significant difference was observed between measured ASMDEXA and estimated ASM (ASMDEXA: 16.4 ± 3.9 kg; ASMPRED-EQUATION_1: 16.7 ± 3.2 kg (P = 0.379); ASMPRED-EQUATION_2: 16.6 ± 3.2 kg (P = 0.670)).
we have developed and cross-validated novel anthropometric prediction equations against DEXA for the estimate of ASM designed for application in older orthopaedic patients. Our equation may be of use as an alternative to DEXA in the diagnosis of skeletal muscle wasting syndromes. Further validation studies are required to determine the clinical utility of o |
doi_str_mv | 10.1093/ageing/afu106 |
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the purpose of this study was to develop and cross-validate novel anthropometric prediction equations for the estimate of ASM in older adults post-surgical fixation for hip fracture, using dual-energy X-ray absorptiometry (DEXA) as the criterion measure.
community-dwelling older adults (aged ≥65 years) recently hospitalised for hip fracture.
participants were recruited from hospital in the acute phase of recovery.
validation measurement study.
a total of 79 hip fracture patients were involved in the development of the regression models (MD group). A further 64 hip fracture patients also recruited in the early phase of recovery were used in the cross-validation of the regression models (CV group). Multiple linear regression analyses were undertaken in the MD group to identify the best performing prediction models. The linear coefficient of determination (R(2)) in addition to the standard error of the estimate (SEE) were calculated to determine the best performing model. Agreement between estimated ASM and ASMDEXA in the CV group was assessed using paired t-tests with the 95% limits of agreement (LOA) assessed using Bland-Altman analyses.
the mean age of all the participants was 82.1 ± 7.3 years. The best two prediction models are presented as follows: ASMPRED-EQUATION_1: 22.28 - (0.069 * age) + (0.407 * weight) - (0.807 * BMI) - (0.222 * MAC) (adjusted R(2): 0.76; SEE: 1.80 kg); ASMPRED-EQUATION_2: 16.77 - (0.036 * age) + (0.385 * weight) - (0.873 * BMI) (adjusted R(2): 0.73; SEE: 1.90 kg). The mean bias from the CV group between ASMDEXA and the predictive equations is as follows: ASMDEXA - ASMPRED-EQUATION_1: 0.29 ± 2.6 kg (LOA: -4.80, 5.40 kg); ASMDEXA - ASMPRED-EQUATION_2: 0.13 ± 2.5 kg (LOA: -4.77, 5.0 kg). No significant difference was observed between measured ASMDEXA and estimated ASM (ASMDEXA: 16.4 ± 3.9 kg; ASMPRED-EQUATION_1: 16.7 ± 3.2 kg (P = 0.379); ASMPRED-EQUATION_2: 16.6 ± 3.2 kg (P = 0.670)).
we have developed and cross-validated novel anthropometric prediction equations against DEXA for the estimate of ASM designed for application in older orthopaedic patients. Our equation may be of use as an alternative to DEXA in the diagnosis of skeletal muscle wasting syndromes. Further validation studies are required to determine the clinical utility of our equation across other settings, including hip fracture patients admitted from residential care, and also with a longer-term follow-up.</description><identifier>ISSN: 0002-0729</identifier><identifier>EISSN: 1468-2834</identifier><identifier>DOI: 10.1093/ageing/afu106</identifier><identifier>PMID: 25049262</identifier><identifier>CODEN: AANGAH</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Absorptiometry, Photon ; Age Factors ; Aged ; Aged, 80 and over ; Anthropometry - methods ; Body Composition ; Body Mass Index ; Body Weight ; Care and treatment ; Female ; Fracture Fixation ; Fractures ; Health aspects ; Hip fractures ; Hip Fractures - diagnosis ; Hip Fractures - diagnostic imaging ; Hip Fractures - physiopathology ; Hip Fractures - surgery ; Hip joint ; Hospitalization ; Humans ; Joint replacement surgery ; Linear Models ; Male ; Models, Biological ; Muscle, Skeletal - diagnostic imaging ; Muscle, Skeletal - physiopathology ; Muscles ; Muscular Atrophy - diagnosis ; Muscular Atrophy - diagnostic imaging ; Muscular Atrophy - physiopathology ; Prediction (Logic) ; Predictive Value of Tests ; Randomized Controlled Trials as Topic ; Recovery of Function ; Regression analysis ; Reproducibility of Results ; Skeletal muscle ; Time Factors ; Treatment Outcome ; Validation studies ; Weight ; X-rays</subject><ispartof>Age and ageing, 2014-11, Vol.43 (6), p.857-862</ispartof><rights>The Author 2014. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</rights><rights>Copyright Oxford Publishing Limited(England) Nov 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c398t-de8250d074a9e8eb5a1c07d54ffbf322f8c0323a6177a89bde6419104fe16f663</citedby><cites>FETCH-LOGICAL-c398t-de8250d074a9e8eb5a1c07d54ffbf322f8c0323a6177a89bde6419104fe16f663</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902,30976</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25049262$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Villani, Anthony Michael</creatorcontrib><creatorcontrib>Crotty, Maria</creatorcontrib><creatorcontrib>Cameron, Ian D</creatorcontrib><creatorcontrib>Kurrle, Susan E</creatorcontrib><creatorcontrib>Skuza, Pawel P</creatorcontrib><creatorcontrib>Cleland, Leslie G</creatorcontrib><creatorcontrib>Cobiac, Lynne</creatorcontrib><creatorcontrib>Miller, Michelle D</creatorcontrib><title>Appendicular skeletal muscle in hospitalised hip-fracture patients: development and cross-validation of anthropometric prediction equations against dual-energy X-ray absorptiometry</title><title>Age and ageing</title><addtitle>Age Ageing</addtitle><description>accurate and practical assessment methods for assessing appendicular skeletal muscle (ASM) is of clinical importance for the diagnosis of geriatric syndromes associated with skeletal muscle wasting.
the purpose of this study was to develop and cross-validate novel anthropometric prediction equations for the estimate of ASM in older adults post-surgical fixation for hip fracture, using dual-energy X-ray absorptiometry (DEXA) as the criterion measure.
community-dwelling older adults (aged ≥65 years) recently hospitalised for hip fracture.
participants were recruited from hospital in the acute phase of recovery.
validation measurement study.
a total of 79 hip fracture patients were involved in the development of the regression models (MD group). A further 64 hip fracture patients also recruited in the early phase of recovery were used in the cross-validation of the regression models (CV group). Multiple linear regression analyses were undertaken in the MD group to identify the best performing prediction models. The linear coefficient of determination (R(2)) in addition to the standard error of the estimate (SEE) were calculated to determine the best performing model. Agreement between estimated ASM and ASMDEXA in the CV group was assessed using paired t-tests with the 95% limits of agreement (LOA) assessed using Bland-Altman analyses.
the mean age of all the participants was 82.1 ± 7.3 years. The best two prediction models are presented as follows: ASMPRED-EQUATION_1: 22.28 - (0.069 * age) + (0.407 * weight) - (0.807 * BMI) - (0.222 * MAC) (adjusted R(2): 0.76; SEE: 1.80 kg); ASMPRED-EQUATION_2: 16.77 - (0.036 * age) + (0.385 * weight) - (0.873 * BMI) (adjusted R(2): 0.73; SEE: 1.90 kg). The mean bias from the CV group between ASMDEXA and the predictive equations is as follows: ASMDEXA - ASMPRED-EQUATION_1: 0.29 ± 2.6 kg (LOA: -4.80, 5.40 kg); ASMDEXA - ASMPRED-EQUATION_2: 0.13 ± 2.5 kg (LOA: -4.77, 5.0 kg). No significant difference was observed between measured ASMDEXA and estimated ASM (ASMDEXA: 16.4 ± 3.9 kg; ASMPRED-EQUATION_1: 16.7 ± 3.2 kg (P = 0.379); ASMPRED-EQUATION_2: 16.6 ± 3.2 kg (P = 0.670)).
we have developed and cross-validated novel anthropometric prediction equations against DEXA for the estimate of ASM designed for application in older orthopaedic patients. Our equation may be of use as an alternative to DEXA in the diagnosis of skeletal muscle wasting syndromes. Further validation studies are required to determine the clinical utility of our equation across other settings, including hip fracture patients admitted from residential care, and also with a longer-term follow-up.</description><subject>Absorptiometry, Photon</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Anthropometry - methods</subject><subject>Body Composition</subject><subject>Body Mass Index</subject><subject>Body Weight</subject><subject>Care and treatment</subject><subject>Female</subject><subject>Fracture Fixation</subject><subject>Fractures</subject><subject>Health aspects</subject><subject>Hip fractures</subject><subject>Hip Fractures - diagnosis</subject><subject>Hip Fractures - diagnostic imaging</subject><subject>Hip Fractures - physiopathology</subject><subject>Hip Fractures - surgery</subject><subject>Hip joint</subject><subject>Hospitalization</subject><subject>Humans</subject><subject>Joint replacement surgery</subject><subject>Linear Models</subject><subject>Male</subject><subject>Models, Biological</subject><subject>Muscle, Skeletal - diagnostic imaging</subject><subject>Muscle, Skeletal - physiopathology</subject><subject>Muscles</subject><subject>Muscular Atrophy - diagnosis</subject><subject>Muscular Atrophy - diagnostic imaging</subject><subject>Muscular Atrophy - physiopathology</subject><subject>Prediction (Logic)</subject><subject>Predictive Value of Tests</subject><subject>Randomized Controlled Trials as Topic</subject><subject>Recovery of Function</subject><subject>Regression analysis</subject><subject>Reproducibility of Results</subject><subject>Skeletal muscle</subject><subject>Time Factors</subject><subject>Treatment Outcome</subject><subject>Validation studies</subject><subject>Weight</subject><subject>X-rays</subject><issn>0002-0729</issn><issn>1468-2834</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><recordid>eNpdkU1vFDEMhkcIRLeFI1cUiQuX0CST-eK2WkFBqtQLSNxGmcSZTckkaZKpuv-LH0i6W0DiZNl5bL_xW1VvKPlAyVBfihmMmy-FXilpn1Ubytses77mz6sNIYRh0rHhrDpP6baktKHsZXXGGsIH1rJN9WsbAjhl5GpFROknWMjComVN0gIyDu19CqaUTAKF9iZgHYXMawQURDbgcvqIFNyD9WEpGRJOIRl9Svi-NKnCeIe8LvW8jz74BXI0EoUIZenxEe7WI5WQmIVxKSO1CovBQZwP6AeO4oDElHwMhXpsP7yqXmhhE7x-ihfV98-fvu2-4Oubq6-77TWW9dBnrKAvH1Wk42KAHqZGUEk61XCtJ10zpntJalaLlnad6IdJQcvpQAnXQFvdtvVF9f40N0R_t0LK42KSBGuFA7-mkba06Xg5Ninou__QW79GV9QVijHStZywQuETNQsLo3HSuwwPWXprYYaxiN_djNt6qAnlnJN__PGiEfQYollEPIyUjI_2jyf7x5P9hX_7pGKdFlB_6T9-178BHmuxuQ</recordid><startdate>201411</startdate><enddate>201411</enddate><creator>Villani, Anthony Michael</creator><creator>Crotty, Maria</creator><creator>Cameron, Ian D</creator><creator>Kurrle, Susan E</creator><creator>Skuza, Pawel P</creator><creator>Cleland, Leslie G</creator><creator>Cobiac, Lynne</creator><creator>Miller, Michelle D</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>7T5</scope><scope>7TK</scope><scope>7U9</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope></search><sort><creationdate>201411</creationdate><title>Appendicular skeletal muscle in hospitalised hip-fracture patients: development and cross-validation of anthropometric prediction equations against dual-energy X-ray absorptiometry</title><author>Villani, Anthony Michael ; Crotty, Maria ; Cameron, Ian D ; Kurrle, Susan E ; Skuza, Pawel P ; Cleland, Leslie G ; Cobiac, Lynne ; Miller, Michelle D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c398t-de8250d074a9e8eb5a1c07d54ffbf322f8c0323a6177a89bde6419104fe16f663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Absorptiometry, Photon</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Anthropometry - methods</topic><topic>Body Composition</topic><topic>Body Mass Index</topic><topic>Body Weight</topic><topic>Care and treatment</topic><topic>Female</topic><topic>Fracture Fixation</topic><topic>Fractures</topic><topic>Health aspects</topic><topic>Hip fractures</topic><topic>Hip Fractures - diagnosis</topic><topic>Hip Fractures - diagnostic imaging</topic><topic>Hip Fractures - physiopathology</topic><topic>Hip Fractures - surgery</topic><topic>Hip joint</topic><topic>Hospitalization</topic><topic>Humans</topic><topic>Joint replacement surgery</topic><topic>Linear Models</topic><topic>Male</topic><topic>Models, Biological</topic><topic>Muscle, Skeletal - diagnostic imaging</topic><topic>Muscle, Skeletal - physiopathology</topic><topic>Muscles</topic><topic>Muscular Atrophy - diagnosis</topic><topic>Muscular Atrophy - diagnostic imaging</topic><topic>Muscular Atrophy - physiopathology</topic><topic>Prediction (Logic)</topic><topic>Predictive Value of Tests</topic><topic>Randomized Controlled Trials as Topic</topic><topic>Recovery of Function</topic><topic>Regression analysis</topic><topic>Reproducibility of Results</topic><topic>Skeletal muscle</topic><topic>Time Factors</topic><topic>Treatment Outcome</topic><topic>Validation studies</topic><topic>Weight</topic><topic>X-rays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Villani, Anthony Michael</creatorcontrib><creatorcontrib>Crotty, Maria</creatorcontrib><creatorcontrib>Cameron, Ian D</creatorcontrib><creatorcontrib>Kurrle, Susan E</creatorcontrib><creatorcontrib>Skuza, Pawel P</creatorcontrib><creatorcontrib>Cleland, Leslie G</creatorcontrib><creatorcontrib>Cobiac, Lynne</creatorcontrib><creatorcontrib>Miller, Michelle D</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Age and ageing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Villani, Anthony Michael</au><au>Crotty, Maria</au><au>Cameron, Ian D</au><au>Kurrle, Susan E</au><au>Skuza, Pawel P</au><au>Cleland, Leslie G</au><au>Cobiac, Lynne</au><au>Miller, Michelle D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Appendicular skeletal muscle in hospitalised hip-fracture patients: development and cross-validation of anthropometric prediction equations against dual-energy X-ray absorptiometry</atitle><jtitle>Age and ageing</jtitle><addtitle>Age Ageing</addtitle><date>2014-11</date><risdate>2014</risdate><volume>43</volume><issue>6</issue><spage>857</spage><epage>862</epage><pages>857-862</pages><issn>0002-0729</issn><eissn>1468-2834</eissn><coden>AANGAH</coden><abstract>accurate and practical assessment methods for assessing appendicular skeletal muscle (ASM) is of clinical importance for the diagnosis of geriatric syndromes associated with skeletal muscle wasting.
the purpose of this study was to develop and cross-validate novel anthropometric prediction equations for the estimate of ASM in older adults post-surgical fixation for hip fracture, using dual-energy X-ray absorptiometry (DEXA) as the criterion measure.
community-dwelling older adults (aged ≥65 years) recently hospitalised for hip fracture.
participants were recruited from hospital in the acute phase of recovery.
validation measurement study.
a total of 79 hip fracture patients were involved in the development of the regression models (MD group). A further 64 hip fracture patients also recruited in the early phase of recovery were used in the cross-validation of the regression models (CV group). Multiple linear regression analyses were undertaken in the MD group to identify the best performing prediction models. The linear coefficient of determination (R(2)) in addition to the standard error of the estimate (SEE) were calculated to determine the best performing model. Agreement between estimated ASM and ASMDEXA in the CV group was assessed using paired t-tests with the 95% limits of agreement (LOA) assessed using Bland-Altman analyses.
the mean age of all the participants was 82.1 ± 7.3 years. The best two prediction models are presented as follows: ASMPRED-EQUATION_1: 22.28 - (0.069 * age) + (0.407 * weight) - (0.807 * BMI) - (0.222 * MAC) (adjusted R(2): 0.76; SEE: 1.80 kg); ASMPRED-EQUATION_2: 16.77 - (0.036 * age) + (0.385 * weight) - (0.873 * BMI) (adjusted R(2): 0.73; SEE: 1.90 kg). The mean bias from the CV group between ASMDEXA and the predictive equations is as follows: ASMDEXA - ASMPRED-EQUATION_1: 0.29 ± 2.6 kg (LOA: -4.80, 5.40 kg); ASMDEXA - ASMPRED-EQUATION_2: 0.13 ± 2.5 kg (LOA: -4.77, 5.0 kg). No significant difference was observed between measured ASMDEXA and estimated ASM (ASMDEXA: 16.4 ± 3.9 kg; ASMPRED-EQUATION_1: 16.7 ± 3.2 kg (P = 0.379); ASMPRED-EQUATION_2: 16.6 ± 3.2 kg (P = 0.670)).
we have developed and cross-validated novel anthropometric prediction equations against DEXA for the estimate of ASM designed for application in older orthopaedic patients. Our equation may be of use as an alternative to DEXA in the diagnosis of skeletal muscle wasting syndromes. Further validation studies are required to determine the clinical utility of our equation across other settings, including hip fracture patients admitted from residential care, and also with a longer-term follow-up.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>25049262</pmid><doi>10.1093/ageing/afu106</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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source | Applied Social Sciences Index & Abstracts (ASSIA); Oxford University Press Journals All Titles (1996-Current); MEDLINE; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
subjects | Absorptiometry, Photon Age Factors Aged Aged, 80 and over Anthropometry - methods Body Composition Body Mass Index Body Weight Care and treatment Female Fracture Fixation Fractures Health aspects Hip fractures Hip Fractures - diagnosis Hip Fractures - diagnostic imaging Hip Fractures - physiopathology Hip Fractures - surgery Hip joint Hospitalization Humans Joint replacement surgery Linear Models Male Models, Biological Muscle, Skeletal - diagnostic imaging Muscle, Skeletal - physiopathology Muscles Muscular Atrophy - diagnosis Muscular Atrophy - diagnostic imaging Muscular Atrophy - physiopathology Prediction (Logic) Predictive Value of Tests Randomized Controlled Trials as Topic Recovery of Function Regression analysis Reproducibility of Results Skeletal muscle Time Factors Treatment Outcome Validation studies Weight X-rays |
title | Appendicular skeletal muscle in hospitalised hip-fracture patients: development and cross-validation of anthropometric prediction equations against dual-energy X-ray absorptiometry |
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