Long-term effects of exercise training in patients with heart failure with preserved ejection fraction - a follow-up study of two randomised controlled trials
Notice bibliographique
Résumé
Abstract Background Exercise training (ET) is an effective therapy to improve peak oxygen consumption (V̇O2) in patients with heart failure with preserved ejection fraction (HFpEF). However, it remains unknown if such an intervention has a sustainable effect beyond the active study period. Purpose To investigate peakV̇O2 in the long-term period after completing a one-year ET intervention in HFpEF. Methods This is a long-term follow-up (FU) study of patients enrolled in the OptimEx-Clin or Ex-DHF trial, the two largest randomised controlled trials of ET over one year in HFpEF. In the OptimEx-Clin trial, 180 patients (mean age: 70 years; 67% women) with HFpEF were randomised to high-intensity interval training, moderate continuous training or usual care (UC). In the Ex-DHF trial, 322 patients (mean age: 70 years; 60% women) were randomised to endurance plus resistance training or UC. All patients who were randomised in one centre and completed the respective trial were contacted to participate in this FU. Baseline assessments were conducted between May 2013 and April 2017 with the last active study visit in May 2018. Patients were reassessed for FU between December 2021 and August 2022. Primary endpoint was the absolute change in peakV̇O2 between the baseline and FU visit. All exercise and both control groups were combined into one ET and one UC group. PeakV̇O2 was assessed during symptom-limited cardiopulmonary exercise testing (CPET) on a cycle ergometer at baseline, 3, 6, 12 months and at FU. PeakV̇O2 was defined as the highest 30-second average within the last minute of CPET. Statistical analyses were performed using dependent and independent t-tests with α = 0.05. Results Among 142 initially randomised patients, 75 were recruited for FU and 67 (40 ET; 27 UC) had available CPET data both at baseline and FU (75% women; mean [SD] age at baseline: 66±7 years). Mean time between baseline and FU was 6.3 ± 1.3 and 6.6 ± 0.8 years in the ET and UC groups, respectively. During the active study phase, ET patients significantly increased peakV̇O2 from baseline to 3, 6 and 12 months (mean change [95% CI]: 1.5 [0.6 to 2.3], 1.5: [0.5 to 2.4] and 1.4: [0.3 to 2.5] mL/kg/min, respectively; Fig. 1). However, a statistically significant difference between groups was only observed at 3 months (P=0.03). The change in peakV̇O2 from baseline to FU was not significantly different between both groups (ET: -2.7 ± 3.3 mL/kg/min; UC: -2.5 ± 3.6 mL/kg/min; P=0.87) (Fig. 1). Finally, between 12 months and FU, change in peakV̇O2 was -4.2 ± 3.6 mL/kg/min for ET, and -3.4 ± 3.3 mL/kg/min for UC patients (P=0.35). Conclusions While patients with HFpEF had significantly improved peakV̇O2 between 3 and 12 months of ET (~1.5 mL/kg/min), these effects were not sustainable beyond the active study period. This finding highlights the importance of incorporating behavioural strategies to ensure long-term adherence to ET is maintained for optimal benefits in peakV̇O2 over time. Change in peakV̇O2 (mean and 95% CI)
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 | 0,021 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,011 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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.
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 ».