- Titel
- Inzidenz und Prädiktoren von Thermoläsionen des Ösophagus und Nervus Vagus bei der High-Power-Short-Duration Ablation von Vorhofflimmern
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa2-978445
- Datum der Einreichung
- 07.05.2024
- Datum der Verteidigung
- 15.05.2025
- Abstract (EN)
- Aims High-power-short-duration (HPSD) ablation is an effective treatment for atrial fibrillation but poses risks of thermal injuries to the oesophagus and vagus nerve. This study aims to investigate incidence and predictors of thermal injuries, employing machine learning. Methods and results A prospective observational study was conducted at Leipzig Heart Centre, Germany, excluding patients with multiple prior ablations. All patients received Ablation Index guided HPSD ablation and subsequent oesophagogastroduodenoscopy. A machine learning algorithm categorized ablation points by atrial location and analysed ablation data, including Ablation Index, focusing on the posterior wall. The study is registered in clinicaltrials.gov (NCT05709756). Between February 2021 and August 2023, 238 patients were enrolled, of whom 18 (7.6%; nine oesophagus, eight vagus nerve, one both) developed thermal injuries, including eight oesophageal erythemata, two ulcers, and no fistula. Higher mean force (15.8 ± 3.9 g vs. 13.6 ± 3.9 g, P = 0.022), ablation point quantity (61.50 ± 20.45 vs. 48.16 ± 19.60, P = 0.007), and total and maximum Ablation Index (24 114 ± 8765 vs. 18 894 ± 7863, P = 0.008; 499 ± 95 vs. 473 ± 44, P = 0.04, respectively) at the posterior wall, but not oesophagus location, correlated significantly with thermal injury occurrence. Patients with thermal injuries had significantly lower distances between left atrium and oesophagus (3.0 ± 1.5 mm vs. 4.4 ± 2.1 mm, P = 0.012) and smaller atrial surface areas (24.9 ± 6.5 cm2 vs. 29.5 ± 7.5 cm2, P = 0.032). Conclusion The low thermal lesion’s rate (7.6%) during Ablation Index-guided HPSD ablation for atrial fibrillation is noteworthy. Machine learning based ablation data analysis identified several potential predictors of thermal injuries. The correlation between machine learning output and injury development suggests the potential for a clinical tool to enhance procedural safety.
- Forschungsdatenverweis
- Incidence and predictors of thermal oesophageal and vagus nerve injuries in Ablation Index-guided high-power-short-duration ablation of atrial fibrillation: a prospective study
DOI: https://doi.org/10.1093/europace/euae107
Link: https://academic.oup.com/europace/article/26/5/euae107/7655713 - Freie Schlagwörter (DE)
- Vorhofflimmern, Machine Learning, Pulmonalveneninsolation, Themoläsionen
- Klassifikation (DDC)
- 610
- GutachterIn
- Prof. Dr. med. Rolf Wachter
- Prof. Michael Borger
- Den akademischen Grad verleihende / prüfende Institution
- Universität Leipzig, Leipzig
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa2-978445
- Veröffentlichungsdatum Qucosa
- 08.07.2025
- Dokumenttyp
- Dissertation
- Sprache des Dokumentes
- Deutsch
- Lizenz / Rechtehinweis
- Inhaltsverzeichnis
Abkürzungsverzeichnis Abbildungsverzeichnis Einführung Vorhofflimmern Pulmonalvenenisolation Thermoläsionen des Ösophagus und Nervus vagus Machine Learning Hypothesen und Methoden Ablationsstrategie der Studie Machine Learning-basierte Auswertung der Ablationsdaten Fragestellung und Zielsetzung Publikationserklärung Publikationsmanuskript Supplementary Material Zusammenfassung der Arbeit Literaturverzeichnis Erklärung über den wissenschaftlichen Beitrag des Promovenden zur Publikation Erklärung über die eigenständige Abfassung der Arbeit Lebenslauf Danksagung