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Defining and diagnosing sarcopenia: Is the glass now half full?

Barazzoni R.
•
Cederholm T.
•
Zanetti M.
•
Gortan Cappellari G.
2023
  • journal article

Periodico
METABOLISM, CLINICAL AND EXPERIMENTAL
Abstract
Low muscle mass and function exert a substantial negative impact on quality of life, health and ultimately survival, but their definition, identification and combination to define sarcopenia have suffered from lack of universal consensus. Methodological issues have also contributed to incomplete agreement, as different approaches, techniques and potential surrogate measures inevitably lead to partly different conclusions. As a consequence: 1) awareness of sarcopenia and implementation of diagnostic procedures in clinical practice have been limited; 2) patient identification and evaluation of therapeutic strategies is largely incomplete. Significant progress has however recently occurred after major diagnostic algorithms have been developed, with common features and promising perspectives for growing consensus. At the same time, the need for further refinement of the sarcopenia concept has emerged, to address its increasingly recognized clinical heterogeneity. This includes potential differential underlying mechanisms and clinical features for age- and disease-driven sarcopenia, and the emerging challenge of sarcopenia in persons with obesity. Here, we will review existing algorithms to diagnose sarcopenia, and major open methodological issues to assess skeletal muscle mass and function under different clinical conditions, in order to highlight similarities and differences. Potential for consensus on sarcopenia diagnosis as well as emerging new challenges will be discussed.
DOI
10.1016/j.metabol.2023.155558
WOS
WOS:001042664500001
Archivio
https://hdl.handle.net/11368/3046065
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85152132689
https://www.sciencedirect.com/science/article/pii/S0026049523001610?via=ihub
Diritti
open access
license:copyright editore
license:creative commons
license uri:iris.pri02
license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/
FVG url
https://arts.units.it/request-item?handle=11368/3046065
Soggetti
  • Algorithm

  • Diagnostic criteria

  • Sarcopenia

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