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Enregistrement W3176144478 · doi:10.1093/ptj/pzab162

Exercise Training to Decrease Ectopic Intermuscular Adipose Tissue in Individuals With Chronic Diseases: A Systematic Review and Meta-Analysis

2021· review· en· W3176144478 sur OpenAlexaff
Mauro Tuñón‐Suárez, Álvaro Reyes, Rodrigo Godoy-Órdenes, Nicolás Quezada, Marcelo Flores‐Opazo

Notice bibliographique

RevuePhysical Therapy · 2021
Typereview
Langueen
DomaineMedicine
ThématiqueHIV-related health complications and treatments
Établissements canadiensCanadian Society for Exercise Physiology
Organismes subventionnairesnon disponible
Mots-clésMedicineMeta-analysisSubgroup analysisRandomized controlled trialAerobic exercisePublication biasPopulationPhysical therapyPsychological interventionInternal medicine

Résumé

récupéré en direct d'OpenAlex

OBJECTIVE: The purpose of this study was to evaluate the effect of exercise training on ectopic fat within skeletal muscle (intermuscular adipose tissue [IMAT]) in adult populations with chronic diseases. METHODS: A literature search was conducted in relevant databases to identify randomized controlled trials (RCTs) from inception. Selected studies examined the effect of aerobic training (AET), resistance training (RT), or combined training (COM) on IMAT as assessed by noninvasive magnetic resonance imagery or computed tomography. Eligibility was determined using Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Data extraction was performed using the population (P), intervention (I), comparison (C), outcome (O), timing (T), and settings (S) approach. Methodological quality was analyzed by the Cochrane risk of bias assessment. Standardized effect sizes (ES) with 95% CIs were calculated. Heterogeneity among studies was quantified using I2 statistics. Subgroup and meta-regression analyses were included. Risk of publication bias was examined by the Egger regression test. RESULTS: Nineteen RCTs included 962 adults (628 women; age range = 34.8-93.4 years) with different chronic conditions that participated in 10 AET, 12 RT, and 5 COM interventions. The quality of studies was deemed moderate. Overall, the effect of exercise on IMAT was small (ES = 0.24; 95% CI = 0.10 to 0.37; heterogeneity I2 = 0.0%) compared with no exercise or control interventions. Moderate-intensity AET and COM had larger ES compared with RT regardless of intensity. This effect was associated with exercise-induced body weight and fat mass losses. Subgroup analysis revealed larger ES in studies assessing IMAT by magnetic resonance imagery compared with computed tomography in adults and middle-aged individuals compared with older adults and in participants who were HIV+ compared with other diagnoses. CONCLUSION: AET and COM of moderate intensity reduce IMAT in individuals from 18 to 65 years of age who are affected by chronic diseases. This effect is associated with exercise-induced body weight and fat mass losses. In older individuals who are frail and patients at an advanced disease stage, exercise may result in a paradoxical IMAT accumulation. IMPACT: In people affected by chronic conditions, IMAT accumulation induces muscle mass and strength losses, decline in physical performance, inflammation, and metabolic alterations. The present study shows that moderate-intensity AET or COM prevent or reduce IMAT in these conditions. Thus, the deleterious effect of IMAT on skeletal muscle homeostasis may be reverted by a properly prescribed exercise regime. The findings of the present systematic review are critical for physical therapists and health care professionals because they emphasize the therapeutic role of exercise and provide recommendations for exercise prescription that ultimately may have a positive impact on the course of disease, recovery of functionality, and independence. LAY SUMMARY: Aerobic exercise (eg, walking/jogging, cycling) alone or combined with resistance exercise (strength training with free-weights, kettle bells, or gym equipment) is effective in reducing fat streaks that infiltrate muscles and impair muscle function and growth, particularly in adults affected by chronic diseases.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,635
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0100,001
Bibliométrie0,0000,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,089
Tête enseignante GPT0,413
Écart entre enseignants0,324 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeMéta-analyse
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations28
Publié2021
Routes d'admission1
Résumé présentoui

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