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Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients

AIMS: Reduction in appendicular skeletal muscle mass index (ASMI) assessed by dual‐energy X‐ray absorptiometry (DEXA) has been shown to be independently associated with a higher mortality rate in patients with heart failure (HF). However, DEXA is not suitable for measurement of muscle mass in a dail...

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Autores principales: Katano, Satoshi, Honma, Suguru, Nagaoka, Ryohei, Numazawa, Ryo, Yamano, Kotaro, Fujisawa, Yusuke, Ohori, Katsuhiko, Kouzu, Hidemichi, Hashimoto, Akiyoshi, Katayose, Masaki, Yano, Toshiyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9773643/
https://www.ncbi.nlm.nih.gov/pubmed/36065759
http://dx.doi.org/10.1002/ehf2.14121
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author Katano, Satoshi
Honma, Suguru
Nagaoka, Ryohei
Numazawa, Ryo
Yamano, Kotaro
Fujisawa, Yusuke
Ohori, Katsuhiko
Kouzu, Hidemichi
Hashimoto, Akiyoshi
Katayose, Masaki
Yano, Toshiyuki
author_facet Katano, Satoshi
Honma, Suguru
Nagaoka, Ryohei
Numazawa, Ryo
Yamano, Kotaro
Fujisawa, Yusuke
Ohori, Katsuhiko
Kouzu, Hidemichi
Hashimoto, Akiyoshi
Katayose, Masaki
Yano, Toshiyuki
author_sort Katano, Satoshi
collection PubMed
description AIMS: Reduction in appendicular skeletal muscle mass index (ASMI) assessed by dual‐energy X‐ray absorptiometry (DEXA) has been shown to be independently associated with a higher mortality rate in patients with heart failure (HF). However, DEXA is not suitable for measurement of muscle mass in a daily clinical setting and in large population‐based studies. The aim of this study was to determine whether ASMI predicted from anthropometric indicators (predicted ASMI) serves as an alternative to DEXA‐measured ASMI for predicting all‐cause death in HF patients. METHODS AND RESULTS: Data for 539 HF patients who received a DEXA scan and measurements of calf circumferences (CC) and mid‐arm circumferences (MAC) in our hospital were analysed. Predicted ASMI was calculated as we previously reported: predicted ASMI (kg/m(2)) = [0.214 × weight (kg) + 0.217 × CC (cm) − 0.189 × MAC (cm) + 1.098 (male = 1, female = −1) + 0.576]/height(2) (m(2)). Low ASMI values were defined as <7.00 kg/m(2) and <5.40 kg/m(2) for men and women, respectively, according to the criteria of the Asian Working Group for Sarcopenia. The median follow‐up period was 1.75 years (interquartile range, 0.96–2.37 years), and 79 patients (15%) died. Kaplan–Meier survival curves showed that patients with low DEXA‐measured ASMI and patients with low predicted ASMI had significantly lower survival rates than those for patients with high ASMI. In multivariate Cox proportional hazard analyses adjusted for age, sex, logarithmic B‐type natriuretic peptide, cystatin C based‐estimated glomerular filtration rate, and gait speed, DEXA‐measured ASMI [hazard ratio (HR), 0.982; 95% confidence interval (CI), 0.967–0.998; P = 0.026] and predicted ASMI (HR, 0.979; 95% CI, 0.962–0.996; P = 0.018) were independent predictors of all‐cause mortality. Inclusion of predicted ASMI into the adjustment model significantly improved continuous net reclassification improvement (0.338; 95% CI, 0.103–0.572; P < 0.01) and integrated discrimination improvement (0.020; 95% CI, 0.004–0.035; P < 0.05) for predicting mortality after discharge. CONCLUSIONS: Predicted ASMI, as well as DEXA‐measured ASMI, can predict all‐cause death in HF patients, and calculation of predicted ASMI will be useful for detecting high‐risk patients in a daily clinical setting and in large population‐based studies.
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spelling pubmed-97736432022-12-23 Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients Katano, Satoshi Honma, Suguru Nagaoka, Ryohei Numazawa, Ryo Yamano, Kotaro Fujisawa, Yusuke Ohori, Katsuhiko Kouzu, Hidemichi Hashimoto, Akiyoshi Katayose, Masaki Yano, Toshiyuki ESC Heart Fail Short Communications AIMS: Reduction in appendicular skeletal muscle mass index (ASMI) assessed by dual‐energy X‐ray absorptiometry (DEXA) has been shown to be independently associated with a higher mortality rate in patients with heart failure (HF). However, DEXA is not suitable for measurement of muscle mass in a daily clinical setting and in large population‐based studies. The aim of this study was to determine whether ASMI predicted from anthropometric indicators (predicted ASMI) serves as an alternative to DEXA‐measured ASMI for predicting all‐cause death in HF patients. METHODS AND RESULTS: Data for 539 HF patients who received a DEXA scan and measurements of calf circumferences (CC) and mid‐arm circumferences (MAC) in our hospital were analysed. Predicted ASMI was calculated as we previously reported: predicted ASMI (kg/m(2)) = [0.214 × weight (kg) + 0.217 × CC (cm) − 0.189 × MAC (cm) + 1.098 (male = 1, female = −1) + 0.576]/height(2) (m(2)). Low ASMI values were defined as <7.00 kg/m(2) and <5.40 kg/m(2) for men and women, respectively, according to the criteria of the Asian Working Group for Sarcopenia. The median follow‐up period was 1.75 years (interquartile range, 0.96–2.37 years), and 79 patients (15%) died. Kaplan–Meier survival curves showed that patients with low DEXA‐measured ASMI and patients with low predicted ASMI had significantly lower survival rates than those for patients with high ASMI. In multivariate Cox proportional hazard analyses adjusted for age, sex, logarithmic B‐type natriuretic peptide, cystatin C based‐estimated glomerular filtration rate, and gait speed, DEXA‐measured ASMI [hazard ratio (HR), 0.982; 95% confidence interval (CI), 0.967–0.998; P = 0.026] and predicted ASMI (HR, 0.979; 95% CI, 0.962–0.996; P = 0.018) were independent predictors of all‐cause mortality. Inclusion of predicted ASMI into the adjustment model significantly improved continuous net reclassification improvement (0.338; 95% CI, 0.103–0.572; P < 0.01) and integrated discrimination improvement (0.020; 95% CI, 0.004–0.035; P < 0.05) for predicting mortality after discharge. CONCLUSIONS: Predicted ASMI, as well as DEXA‐measured ASMI, can predict all‐cause death in HF patients, and calculation of predicted ASMI will be useful for detecting high‐risk patients in a daily clinical setting and in large population‐based studies. John Wiley and Sons Inc. 2022-09-06 /pmc/articles/PMC9773643/ /pubmed/36065759 http://dx.doi.org/10.1002/ehf2.14121 Text en © 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Short Communications
Katano, Satoshi
Honma, Suguru
Nagaoka, Ryohei
Numazawa, Ryo
Yamano, Kotaro
Fujisawa, Yusuke
Ohori, Katsuhiko
Kouzu, Hidemichi
Hashimoto, Akiyoshi
Katayose, Masaki
Yano, Toshiyuki
Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients
title Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients
title_full Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients
title_fullStr Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients
title_full_unstemmed Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients
title_short Anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients
title_sort anthropometric parameters‐derived estimation of muscle mass predicts all‐cause mortality in heart failure patients
topic Short Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9773643/
https://www.ncbi.nlm.nih.gov/pubmed/36065759
http://dx.doi.org/10.1002/ehf2.14121
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