Temporal trends in the utilization, referral patterns, and complications of catheter ablation for atrial fibrillation in the Netherlands, 2013-2021
Notice bibliographique
Résumé
Abstract Background Over the past decade, atrial fibrillation (AF) ablation technologies have evolved, operator experience has improved, and indications for referral to AF ablation has expanded. A recent population-level assessment is warranted to assess the impact of these changes on trends in the utilization, referrals, and adverse events (AEs) of AF ablation. Purpose Our aim was to describe temporal trends in the population-level incidence, patients referred, and AEs of AF ablation in the Netherlands from 2013 to 2021. Methods Temporal trend analyses were conducted using the AF ablation population in the Netherlands Heart Registration and included all consecutive patients treated with catheter ablation for AF between 2013 and 2021 at 16 hospitals in the Netherlands. Annual crude, sex- and age-standardized incidence rates of AF ablation were calculated. Poisson regression models with robust variances were used to evaluate trends in the incidence of AF ablation. Trends in patient characteristics, AEs, and repeat ablations over the study period were evaluated with ANOVA tests. Results Between 2013 and 2021, 37,538 AF ablations were performed in the Netherlands, of which 27,027 (72.0%) were index ablations. Repeat ablations (10,511 procedures) were performed within a median time to repeat ablation of 1 (IQR 1-2) year. AF ablation patients were a median age 63 (IQR 56-69) years, 32.8% women, 70.7% had paroxysmal AF, and median CHA2DS2-VASC score was 1 (IQR 1-2). Most patients underwent radiofrequency ablation (55.4%), followed by cryoballoon (33.4%), PVAC (0.6%), pulse-field (0.3%), laser balloon ablation (0.1%), and other (0.1%) (10.1% missing). Over the 9-year period, there was a statistically significant increase in index [incidence rate ratio (IRR) 1.07 (95% CI 1.05-1.08)] and repeat [IRR 1.09 (95% CI 1.05-1.12)] ablations from 2013 to 2021 (Figure 1). The annual sex-standardized incidence rates of AF ablations were approximately double for men compared to women throughout follow-up (Figure 2). In recent years, AF ablation patients had more persistent AF, higher CHA2DS2-VASC scores, and lower LVEF (p<0.05 for all). Minor vascular AEs within 30 days were the most frequent AE of AF ablation (1.1%), followed by phrenic nerve paralysis (0.6%), in-hospital bleeding (0.6%), cardiac tamponade (0.5%), thrombosis (0.3%), major vascular AEs (0.2%) and all-cause mortality (0.1%). Incidence of most AEs remained stable over time (p>0.05 for all). CONCLUSION In the Netherlands, the utilization of AF ablation increased by 7% from 2013 to 2021. In recent years, populations referred for AF ablation were increasingly older, had more persistent AF, higher CHA2DS2-VASC scores, and lower LVEF; however, men remained twice as likely to undergo AF ablation compared to women. Reasons for the lower rate of AF ablation among women requires further investigation.
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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».