MétaCan
Menu
Retour à la cohorte
Enregistrement W4402066996 · doi:10.1016/j.jacc.2024.08.023

Atrial Fibrillation and Semaglutide Effects in Obesity-Related Heart Failure With Preserved Ejection Fraction

2024· article· en· W4402066996 sur OpenAlexafffund
Subodh Verma, Javed Butler, Barry A. Borlaug, Melanie J. Davies, Dalane W. Kitzman, Mark C. Petrie, Sanjiv J. Shah, Thomas Jensen, Søren Rasmussen, Cecilia Rönnbäck, Béla Merkely, Evan L. O’Keefe, Mikhail Kosiborod

Notice bibliographique

RevueJournal of the American College of Cardiology · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueCardiovascular Function and Risk Factors
Établissements canadiensUniversity of TorontoSt. Michael's Hospital
Organismes subventionnairesNational Heart, Lung, and Blood InstituteAmerican RegentDaiichi-SankyoBritish Heart FoundationHorizon TherapeuticsImpulse DynamicsNovo NordiskMyoKardiaNational Institutes of HealthRegeneron PharmaceuticalsDexcomReCor MedicalAstellas PharmaCytokineticsSanofiNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchCanadian Institutes of Health ResearchProthenaAstraZenecaAmarin CorporationBoston Scientific CorporationEli Lilly and CompanyU.S. Department of DefenseArrowhead PharmaceuticalsHLS TherapeuticsLivaNovaGlaxoSmithKlineNational Institute on AgingNational Institute for Health and Care ResearchCSL BehringBristol-Myers SquibbEdwards LifesciencesAmgenTenax TherapeuticsHeart and Stroke Foundation of CanadaModernaPfizerEsperion TherapeuticsAlnylam PharmaceuticalsGilead Sciences
Mots-clésSemaglutideMedicineHeart failureHeart failure with preserved ejection fractionAtrial fibrillationEjection fractionCardiologyInternal medicineObesityType 2 diabetesDiabetes mellitusEndocrinology

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Obesity is a key factor in the development and progression of both heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF). In the STEP-HFpEF Program (comprising the STEP-HFpEF [Research Study to Investigate How Well Semaglutide Works in People Living With Heart Failure and Obesity] and STEP-HFpEF DM [Research Study to Look at How Well Semaglutide Works in People Living With Heart Failure, Obesity and Type 2 Diabetes] trials), once-weekly semaglutide 2.4 mg improved HF-related symptoms, physical limitations, and exercise function and reduced body weight in patients with obesity-related HFpEF. Whether the effects of semaglutide in this patient group differ in participants with and without AF (and across various AF types) has not been fully examined. OBJECTIVES: The goals of this study were: 1) to evaluate baseline characteristics and clinical features of patients with obesity-related HFpEF with and without a history of AF; and 2) to determine if the efficacy of semaglutide across all key trial outcomes are influenced by baseline history of AF (and AF types) in the STEP-HFpEF Program. METHODS: , and Kansas City Cardiomyopathy Questionnaire-Clinical Summary Score (KCCQ-CSS) <90 points were randomized 1:1 to receive once-weekly semaglutide 2.4 mg or matching placebo for 52 weeks. Dual primary endpoints (change in KCCQ-CSS and percent change in body weight), confirmatory secondary endpoints (change in 6-minute walk distance; hierarchical composite endpoint comprising all-cause death, HF events, thresholds of change in KCCQ-CSS, and 6-minute walk distance; and C-reactive protein [CRP]), and exploratory endpoint (change in N-terminal pro-B-type natriuretic peptide [NT-proBNP]) were examined according to investigator-reported history of AF (yes/no). Responder analyses examined the proportions of patients who experienced a ≥5-, ≥10, ≥15, and ≥20-point improvement in KCCQ-CSS per history of AF. RESULTS: Of the 1,145 participants, 518 (45%) had a history of AF (40% paroxysmal, 24% persistent AF, and 35% permanent AF) and 627 (55%) did not. Participants with (vs without) AF were older, more often male, had higher NT-proBNP levels, included a higher proportion of those with NYHA functional class III symptoms, and used more antithrombotic therapies, beta-blockers, and diuretics. Semaglutide led to larger improvements in KCCQ-CSS (11.5 points [95% CI: 8.3-14.8] vs 4.3 points [95% CI: 1.3-7.2]; P interaction = 0.001) and the hierarchal composite endpoint (win ratio of 2.25 [95% CI: 1.79-2.83] vs 1.30 [95% CI: 1.06-1.59]; P interaction < 0.001) in participants with AF vs without AF, respectively. The proportions of patients receiving semaglutide vs those receiving placebo experiencing ≥5-, ≥10-, ≥15-, and ≥20-point improvement in KCCQ-CSS were also higher in those with (vs without) AF (all P interaction values <0.05). Semaglutide consistently reduced CRP, NT-proBNP, and body weight regardless of AF status (all P interaction values not significant). There were fewer serious adverse events and serious cardiac disorders in participants treated with semaglutide vs placebo irrespective of AF history. CONCLUSIONS: In the STEP-HFpEF Program, AF was observed in nearly one-half of patients with obesity-related HFpEF and was associated with several features of more advanced HF. Treatment with semaglutide led to significant improvements in HF-related symptoms, physical limitations, and exercise function, as well as reductions in weight, CRP, and NT-proBNP in people with and without AF and across AF types. The magnitude of semaglutide-mediated improvements in HF-related symptoms and physical limitations was more pronounced in those with AF vs without AF at baseline. (Research Study to Investigate How Well Semaglutide Works in People Living With Heart Failure and Obesity [STEP-HFpEF; NCT04788511]; Research Study to Look at How Well Semaglutide Works in People Living With Heart Failure, Obesity and Type 2 Diabetes [STEP-HFpEF DM; NCT04916470]).

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 candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,224

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
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 Opus0,006
Tête enseignante GPT0,238
Écart entre enseignants0,233 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations36
Publié2024
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueJournal of the American College of CardiologyMême sujetCardiovascular Function and Risk FactorsTravaux en français237 207