The effects of high-intensity interval training on glucose variability and symptom severity in patients with atrial fibrillation and diabetes: a pilot randomized controlled trial
Notice bibliographique
Résumé
Abstract Background Atrial fibrillation (AF) is the most common heart rhythm disorder. Type 2 diabetes (T2D) increases a risk of developing AF and is present in approximately 20% of patients with non-permanent AF (paroxysmal and persistent AF). Many patients with T2D have high blood glucose levels and high glucose variability (GV). Greater GV is independently associated with inflammation, oxidative stress, and autonomic nervous system dysfunction, all of which contribute to the underlying pathophysiology of AF and AF symptom severity. GV has also been associated with poorer quality of life (QoL) in patients with T2D. Exercise improves GV, and high-intensity interval training (HIIT) has emerged as a superior and time-efficient approach to improve GV. However, the effects of HIIT on GV, AF symptom severity, and AF-related QoL in patients with AF living with T2D remain unknown. Purposes This pilot randomized controlled trial compared the impact of HIIT and no exercise training (Control) on GV (primary outcome), AF symptom severity, and AF-related QoL in patients with non-permanent AF living with T2D. The associations between GV and AF symptom severity and QoL were also examined. Methods Eligible patients had diagnosed non-permanent AF and T2D, and were ≥40 years of age, non-smokers, with resting heart rates ≤110 bpm, and no contraindications to performing high-intensity exercise. Included participants were randomized to a 4-week supervised HIIT program or Control. The HIIT group exercised thrice weekly for 12 weeks. Each HIIT session included 16x30-seconds high-intensity intervals at 80-100% of peak power output interspersed with 30-seconds active recovery. At baseline (prior to randomization) and follow-up (after the intervention), participants’ glucose concentrations were measured over three days using a continuous glucose monitoring system, on which percent coefficient of variation (%CV) was calculated for GV. Participants also completed the AF Severity Scale (AFSS) and AF Effect on Quality of Life (AEFQT) questionnaires. Results Due to recruitment challenges imposed by the COVID-19 pandemic, fewer than anticipated participants (N=11 vs. N=36, age: 70±6 years, 25% females) were randomised into HIIT (n=6) or Control (n=5). There were no differences between HIIT and Control in changes in GV (Baseline [B] 20.0±2.5 to follow-up [FU] 18.9±7.9 % vs. B: 21.9±5.5 to FU: 21.5±6.8 %, time x group interaction effect: p=0.988), AFEQT (B: 87.7±7.4 to FU: 88.8±11.5 points vs. B: 68.6±9.9 to FU: 80.5±9.6 points, interaction effect: p=0.123), or AFSS (B: 9.1±2.9 to FU: 9.3±2.1 vs. B: 18.2±6.1 vs. FU: 18.2±6.6 points, interaction effect: p=0.801). No significant correlations were found between GV and AF symptom severity or AF-related QoL. Conclusions Four weeks of HIIT did not improve GV, AF symptom severity or AF-related QoL in patients with non-permanent AF and T2D. However, these findings should be interpreted with caution given the smaller than desired sample size.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».