{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T05:38:11Z","timestamp":1792561091397,"version":"4.5.0"},"reference-count":34,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T00:00:00Z","timestamp":1792454400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T00:00:00Z","timestamp":1792454400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aspenjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nut in Clin Prac"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Low muscle mass is common in patients on hemodialysis (HD), and bioelectrical impedance analysis (BIA) predictive equations have been proposed as an alternative for estimating muscle mass. This study aimed to analyze the validity and agreement of different BIA\u2010based prediction equations against dual energy X\u2010ray absorptiometry (DXA) for estimating skeletal muscle mass (SMM) and appendicular skeletal muscle mass (ASMM) in patients on HD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross\u2010sectional study enrolled patients on HD. Clinical and laboratory data and body composition by BIA and DXA were collected. The accuracy of six prediction equations (Janssen, Barbosa\u2010Silva, Kyle, Lin, Macdonald, and Sergi) for estimating SMM and ASMM was tested against DXA as the reference standard. Agreement was assessed using Lin's Concordance Correlation Coefficient (CCC), Bland\u2010Altman analysis, Kappa statistics, Receiver Operating Characteristic (ROC) curves, and Passing\u2010Bablok regression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The sample consisted of 57 participants, age 52\u2009\u00b1\u200913 years, 32 (56%) male, median dialysis vintage 14 (4\u201340) months, 17 (30%) with diabetes, and 48 (84%) with hypertension. The best agreement with DXA was observed for the Lin (CCC\u2009=\u20090.911), Sergi (CCC\u2009=\u20090.902) and Kyle (CCC\u2009=\u20090.902) equations. For low muscle mass diagnosis, Kappa values ranged from moderate to substantial, with the Lin equation showing the highest agreement (\n                      <jats:italic>\u03ba<\/jats:italic>\n                      \u2009=\u20090.734). Additionally, the Lin equation demonstrated good accuracy (AUC\u2009=\u20090.794, 95% CI 0.68\u20130.91), with 68,4% sensitivity and 89.5% specificity.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The Lin equation provided the most accurate and reproducible estimates of muscle mass compared with DXA and showed good diagnostic performance for low muscle mass in patients on HD.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ncp.70192","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T04:39:32Z","timestamp":1792557572000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Validity and agreement of bioelectrical impedance equations against dual energy X\u2010ray absorptiometry for muscle mass assessment in patients on hemodialysis: A cross\u2010sectional study"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5407-0421","authenticated-orcid":false,"given":"Sheila","family":"Borges","sequence":"first","affiliation":[{"name":"Health Sciences and Technologies Graduate Program, University of Bras\u00edlia (UnB) Bras\u00edlia Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8548-5079","authenticated-orcid":false,"given":"Ta\u00eds Ferreira","family":"Martins","sequence":"additional","affiliation":[{"name":"Rehabilitation Sciences Program, University of Bras\u00edlia (UnB) Bras\u00edlia Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1910-7695","authenticated-orcid":false,"given":"Felipe Vila\u00e7a Cavallari","family":"Machado","sequence":"additional","affiliation":[{"name":"Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University Diepenbeek Belgium"},{"name":"Biomedical Research Institute (BIOMED), Faculty of Medicine and Life Sciences, Hasselt University Diepenbeek Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6323-7003","authenticated-orcid":false,"given":"Gerson Cipriano","family":"J\u00fanior","sequence":"additional","affiliation":[{"name":"Health Sciences and Technologies Graduate Program, University of Bras\u00edlia (UnB) Bras\u00edlia Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9560-6520","authenticated-orcid":false,"given":"Graziella Fran\u00e7a Bernardelli","family":"Cipriano","sequence":"additional","affiliation":[{"name":"Health Sciences and Technologies Graduate Program, University of Bras\u00edlia (UnB) Bras\u00edlia Brazil"},{"name":"Rehabilitation Sciences Program, University of Bras\u00edlia (UnB) Bras\u00edlia 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