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Enregistrement W2801268278 · doi:10.1113/ep087063

Functional high‐intensity training: A HIT to improve insulin sensitivity in type 2 diabetes

2018· letter· en· W2801268278 sur OpenAlexaff
Martin J. Gibala

Notice bibliographique

RevueExperimental Physiology · 2018
Typeletter
Langueen
DomaineMedicine
ThématiqueCardiovascular and exercise physiology
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicinePhysical therapyType 2 diabetesRowingAerobic exerciseRating of perceived exertionOverweightInsulin resistanceBlood pressureDiabetes mellitusInternal medicineHeart rateInsulinObesityEndocrinology

Résumé

récupéré en direct d'OpenAlex

The paper by Fealy et al. (2018) in this issue of Experimental Physiology sheds new light on the potential for brief, vigorous exercise to improve insulin sensitivity and other indices of cardiometabolic health in overweight and obese individuals with type 2 diabetes. Thirteen men and women, aged 53 ± 7 years, performed a functional high-intensity training programme consisting of aerobic and resistance exercises. Participants completed a total of 18 training sessions over 6 weeks at an established Crossfit™ gym under the supervision of a certified coach. Each workout entailed a distinct combination of calisthenics, gymnastics, weightlifting and other ‘cardio’ exercises, such as rowing. The sessions ranged from 8 to 20 min in duration, including a warm-up and cool-down, and the main high-intensity phase elicited a heart rate >85% of maximum. Insulin sensitivity, determined using oral glucose tolerance tests performed before the intervention and ≥24 h after the final exercise session, improved after training. The programme also reduced fat mass, diastolic blood pressure, blood lipids (triglyceride and very low-density lipoprotein cholesterol) and metabolic syndrome z-score, and increased basal fat oxidation and plasma adiponectin. Training compliance was >95%, and no injuries or adverse events were reported. The timely report by Fealy et al. (2018) will no doubt stimulate additional research on the potential for practical, time-efficient exercise protocols to enhance health-related markers in deconditioned individuals and people with cardiometabolic diseases. The findings demonstrate the feasibility and efficacy of functional high-intensity training in a small group of carefully screened participants under controlled conditions. The subjects were non-smokers with no contraindications for elevated levels of physical activity, based on a detailed medical history and completion of an exercise stress test with 12-lead ECG before participation. The new results build on data from other small, proof-of-concept studies that have revealed the potential for high-intensity interval training (HIIT) to improve indices of glycaemic control in a time-efficient manner in people with type 2 diabetes (Little et al., 2011). Larger, longer and more comprehensive randomized controlled studies are warranted to advance our understanding of the effectiveness of brief, intense exercise training and how it compares with traditional physical activity recommendations advocated by public health agencies. Adherence to current guidelines are poor, with ‘lack of time’ being a key barrier cited to regular participation in physical activity. At the same time, there are legitimate safety concerns regarding the appropriateness of high-intensity exercise in certain circumstances and conditions. The risk of acute myocardial infarction and sudden cardiac death is known to be increased after vigorous activity in susceptible individuals, which emphasizes the need for appropriate medical prescreening (Thompson et al., 2007). The relative risk should not be overstated, however, as evidenced by a recent comprehensive review that concluded: ‘mounting clinical evidence supports HIIT as a safe therapy for the majority of individuals with elevated cardiometabolic risk’ (Cassidy, Thoma, Houghton, & Trenell, 2017). A resurgence of scientific interest over the past decade into the potential for brief, vigorous exercise to improve cardiometabolic health has been accompanied by increased attention from fitness enthusiasts. For the past 5 years, HIIT and body weight training have ranked among the top fitness trends worldwide in an annual survey by the American College of Sports Medicine. The functional high-intensity training programme used by Fealy et al. (2018) effectively integrated both trends, and the resultant method is particularly appealing because of its versatility. Variations of the protocol can be done almost anywhere, with minimal need for specialized equipment. In addition to benefiting people with type 2 diabetes, the training method could be effective for the prevention and management of other lifestyle-induced cardiometabolic diseases and inactivity-related disorders. Crossfit™ and other workout programmes of a similar style have proved extremely popular, but translational studies are warranted to establish the effectiveness of functional high-intensity training scientifically in the ‘real world’. Some dismiss the method outright owing to the high degree of motivation and volitional effort required to perform such training. Such criticism tends to ignore the reality that fewer than one-quarter of adults meet current physical activity guidelines, and there is an obvious need for practical, time-efficient substitutes that broaden the available options from which to choose. The determinants of physical activity behaviour are complex, but emerging data support the viability of brief, vigorous exercise as an alternative to traditional forms of training from a psychological perspective (Stork, Banfield, Gibala, & Martin Ginis, 2017).

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,023
Tête enseignante GPT0,260
Écart entre enseignants0,237 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai non randomisé
Domainenon disponible
GenreEmpirique

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

En bref

Citations2
Publié2018
Routes d'admission1
Résumé présentoui

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