Association between comorbidities and the effects of exercise training among patients with heart failure with preserved ejection fraction
Notice bibliographique
Résumé
Abstract Background Patients with heart failure with preserved ejection fraction (HFpEF) often have multiple cardiac and/or non-cardiac comorbidities that may contribute to exercise intolerance, the hallmark symptom in HFpEF. Exercise training is one of the most effective treatments to improve exercise tolerance but it is unclear whether individual comorbidities or the comorbidity burden are associated with altered exercise training effects in HFpEF. Purpose To evaluate the association between baseline comorbidities and the change in peak oxygen consumption (VO2) in patients with HFpEF. Methods This is a pooled analysis of the two largest randomized controlled exercise training trials performed in HFpEF to date. In the OptimEx-Clin trial, 180 patients were randomized (1:1:1) to 12 months of high-intensity interval training (3× per week), moderate continuous training (5× per week) or usual care (UC). In the Ex-DHF trial, 322 patients were randomized (1:1) to 12 months of endurance and resistance training (3× per week) or UC. For the present analysis, all exercise training groups and both UC groups were combined into one exercise and one UC group. Peak V̇O2 was defined as the highest 30-sec average during symptom-limited incremental cardiopulmonary exercise testing. Comorbidity burden was evaluated by a simple score assigning 1 point to each assessed comorbidity (arterial hypertension, hyperlipidaemia, obesity, coronary heart disease, atrial fibrillation, diabetes mellitus, chronic kidney disease, cancer, anaemia, sleep apnoea, cerebrovascular disease, depression, chronic obstructive pulmonary disease, primary valve disease, peripheral vascular disease, congenital heart disease). The associations between baseline comorbidities and change in peak VO2 after 12 months were analysed using linear regression analyses adjusted for sex, age at inclusion and baseline peak VO2. All analyses were performed using R Statistical Software with significant levels of α=0.05. Results A total of 400 patients with available peak VO2 measurements at baseline and 12 months (60.7% women; mean age: 70 years; median no. of comorbidities: 4 [range: 0-10; IQR: 2-5]) were included in this analysis. Change in peak VO2 at 12 months was significantly higher following exercise training vs. UC (mean difference, 1.22 mL/kg/min [95% CI, 0.58-1.86], P<0.001). There was no significant interaction between any of the investigated comorbidities and treatment group for the change in peak VO2 (Figure 1). Comorbidity burden was also not significantly associated with the change in peak VO2 (P-interaction = 0.99) with mean between-group differences of 1.26 mL/kg/min (95%CI, -0.25-2.77) for ≤2 comorbidities, 1.37 mL/kg/min (95%CI, 0.44-2.31) for 3-4 comorbidities and 1.27 mL/kg/min (95%CI, 0.19-2.36) for ≥5 comorbidities. Conclusions In patients with HFpEF, exercise training significantly improved peak VO2 over 12 months, regardless of individual comorbidities and overall comorbidity burden.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| 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 ».