Correlation of ultrasound-assessed muscle mass with muscle function during resistance training in the elderly: a systematic review with meta-analysis
Notice bibliographique
Résumé
Future research should prioritise more frequent and targeted assessments of specific muscles using both ultrasound and functional testing. This approach may provide clearer and more precise evidence of the relationship between muscle mass and functional capacity. By refining these assessment protocols, researchers can better understand the nuances of muscle adaptation and its impact on overall physical function. This systematic review was conducted according to the PRISMA guidelines. We searched the PubMed, Cochrane, Web of Science and Embase databases for relevant studies. Key search terms included 'aged', 'resistance training', 'musculoskeletal ultrasound', 'muscle quality', etc. Three independent reviewers screened titles, abstracts, keywords and full texts. Data were extracted into tables, and the methodological quality of the studies was assessed using the Newcastle-Ottawa Scale (NOS). A qualitative analysis was performed to better assess the relationship between ultrasound-assessed muscle changes and observed changes in muscle function during resistance training in older people. The meta-analysis integrated data from different methodologies to account for heterogeneity and potential bias. Linear regression models were used to assess associations, and results were assessed based on the significance of their P values. Ultrasound (US) assessment plays a valuable role in monitoring structural and qualitative changes in skeletal muscle during resistance training. However, observed differences in results between studies suggest that factors such as participant age, duration of exercise, data collection methods and technical staff expertise may influence results. In addition, while US provides specific insight into individual muscles, functional assessments typically evaluate broader movement patterns, which may account for discrepancies between muscle-specific and overall functional outcomes. Further research is needed to reconcile these assessment methods for a more comprehensive understanding of muscle adaptation in older adults. A total of 7,577 articles were initially retrieved. After excluding irrelevant studies and those that did not meet the inclusion criteria, seven studies were selected for analysis. The primary data for the meta-analysis were the effect sizes of the correlations between muscle changes (assessed by ultrasound) and strength or functional capacity after resistance training in older adults. The meta-analysis showed weak correlations between muscle thickness (MT) (r = 0.058 [-0.32; 0.43], p = 0.126), cross-sectional area (CSA) (r = 0.054 [0.003; 0.11], p < 0.1) and echogenicity index (EI) (r = 0.047 [0.003; 0.06], p < 0.1) with muscle strength. The aim of this systematic review is to evaluate the relationship between ultrasound-assessed muscle changes and functional improvements observed during resistance training in older people. To determine the reliability of musculoskeletal ultrasound as an objective tool for monitoring changes in muscle function in response to resistance training interventions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,022 | 0,059 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,022 | 0,042 |
| Bibliométrie | 0,008 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».