Number of comorbidities is associated with symptom severity and arrhythmia progression in paroxysmal atrial fibrillation - Data from the RACE V study
Notice bibliographique
Résumé
Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): We acknowledge the support from the Netherlands Cardiovascular Research Initiative: an initiative with support of the Dutch Heart Foundation, CVON 2014-9: Reappraisal of Atrial Fibrillation: interaction between hyperCoagulability, Electrical remodelling, and Vascular destabilisation in the progression of AF (RACE V). Unrestricted grant support from Medtronic Trading NL B.V. Background Atrial fibrillation (AF) progression is associated with morbidity and mortality. Both comorbidities and symptom severity are pillars in the ABC treatment pathway as proposed by the ESC guidelines. Interaction between comorbidities, symptom severity and AF progression seems evident, but evidence is lacking. Aims The aim of the present study is to investigate whether the number of comorbidities is related with severity of AF symptoms, and whether AF symptom severity is associated with AF progression in patients with paroxysmal AF. Methods Patients Underwent extensive phenotyping at baseline and received continuous rhythm monitoring with an implantable loop recorder during follow-up. We studied the relation between comorbidities, AF symptom severity [quantified with the Toronto AF Severity Scale (AFSS)], and AF progression in patients with paroxysmal AF included in the RACE V study. Multivariate regression analysis was performed to study the association between comorbidities and AFSS tertiles, and the association between AF progression and AFSS tertiles. Results Of 417 paroxysmal AF patients, AFSS questionnaires at baseline were available in 403 patients (97%). Mean age was 65 (IQR 58-71) years, 174 (43%) were women. 132 patients (33%) reported a low score [score 0–2; lowest tertile (T1)], 129 patients (32%) reported a moderate score [score 3–7; middle tertile (T2)], and 142 (35%) reported a high score [score 8–35; highest tertile (T3)]. Patients with the most severe symptoms were older, more often women, more often had coronary artery disease, kidney dysfunction, and a higher body mass index (BMI). The number of comorbidities [defined as hypertension, heart failure, age >65 years, diabetes mellitus; coronary artery disease, BMI >25kg/m2, moderate or severe mitral valve regurgitation and kidney dysfunction (estimated glomerular rate (eGFR) <60)] was a significant determinant of higher AFSS scores [2 (1-3) in T1, 2 (2-3) in T2, 3 (2-4) in T3, respectively P <0.001], with a coefficient of 1.417 (P <0.001) for each extra comorbidity. AF progression occurred most frequently in T3 of the AFSS [10 (7%) in T1, 19 (15%) in T2, 21 (15%) in T3, respectively, P = 0.01]. After adjusting the AFSS tertile for age, coronary artery disease, BMI and eGFR there was no significant association for AFSS with AF progression, AFSS T2 versus T1 OR 2.19 (CI 0.92 - 5.63, P = 0.087), and AFSS T3 versus T1 OR 2.23 (CI 0.92 - 5.84, P = 0.085). AF progression occurred in 14% of AF patients with multimorbidity, defined as ≥2 comorbidities, in comparison to 5% in the AF patients with ≤1 comorbidity (P = 0.023) Conclusions In paroxysmal AF, multimorbidity was associated with symptom severity and AF progression. However, symptom severity was not associated with AF progression.
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 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) | 0,000 | 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 ».