Assessing muscle quality as a key predictor to differentiate fallers from non-fallers in older adults.

Autor: Michel E; Department of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France. michel.e2@chu-nice.fr.; Université Côte d'Azur, LAMHESS, Nice, France. michel.e2@chu-nice.fr., Zory R; Université Côte d'Azur, LAMHESS, Nice, France.; Institut Universitaire de France (IUF), Paris, France., Guerin O; Department of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.; Université Côte d'Azur, INSERM, CNRS, Nice, France., Prate F; Department of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France., Sacco G; Department of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.; Université Côte d'Azur, UPR 7276 CoBTek, Nice, France., Chorin F; Department of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.; Université Côte d'Azur, LAMHESS, Nice, France.
Jazyk: angličtina
Zdroj: European geriatric medicine [Eur Geriatr Med] 2024 Aug 03. Date of Electronic Publication: 2024 Aug 03.
DOI: 10.1007/s41999-024-01020-y
Abstrakt: Background: Falling is an important public health issue because of its prevalence and severe consequences. Evaluating muscle performance is important when assessing fall risk. The study aimed to identify factors [namely muscle capacity (strength, quality, and power) and spatio-temporal gait attributes] that best discriminate between fallers and non-fallers in older adults. The hypothesis is that muscle quality, defined as the ratio of muscle strength to muscle mass, is the best predictor of fall risk.
Methods: 184 patients were included, 81% (n = 150) were women and the mean age was 73.6 ± 6.83 years. We compared body composition, mean grip strength, spatio-temporal parameters, and muscle capacity of fallers and non-fallers. Muscle quality was calculated as the ratio of maximum strength to fat-free mass. Mean handgrip and power were also controlled by fat-free mass. We performed univariate analysis, logistic regression, and ROC curves.
Results: The falling patients had lower muscle quality, muscle mass-controlled power, and mean weighted handgrip than the non-faller. Results showing that lower muscle quality increases fall risk (effect size = 0.891). Logistic regression confirmed muscle quality as a significant predictor (p < .001, OR = 0.82, CI [0.74; 0.89]). ROC curves demonstrated muscle quality as the most predictive factor of falling (AUC = 0.794).
Conclusion: This retrospective study showed that muscle quality is the best predictor of fall risk, above spatial and temporal gait parameters. Our results underscore muscle quality as a clinically meaningful assessment and may be a useful complement to other assessments for fall prevention in the aging population.
(© 2024. The Author(s).)
Databáze: MEDLINE
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