Cardiac magnetic resonance using late gadolinium enhancement and atrial T1 mapping predicts poor outcome in patients with atrial fibrillation after catheter ablation therapy
Abstract To determine the pre-procedural value of different fibrotic biomarkers and comprehensive cardiac magnetic resonance (CMR) for the prediction of poor response to ablation therapy in patients with atrial fibrillation (AF). Left atrial (LA) late gadolinium enhancement (LGE) and native LA T1 re...
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| Autores principales: | , , , , , , , , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/a791bc9426054598af890b1907253b3b |
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| Sumario: | Abstract To determine the pre-procedural value of different fibrotic biomarkers and comprehensive cardiac magnetic resonance (CMR) for the prediction of poor response to ablation therapy in patients with atrial fibrillation (AF). Left atrial (LA) late gadolinium enhancement (LGE) and native LA T1 relaxation times were assessed using CMR. Plasma levels of relaxin, myeloperoxidase and serum levels of matrix metalloproteinase (MMP)-mediated cardiac specific titin fragmentation and MMP-mediated type IV collagen degradation were obtained. Poor outcome was defined by the recurrence of AF during 1-year follow-up. 61 patients were included in final analysis. Twenty (32.8%) patients had recurrence of AF. Patients with a recurrence of AF had a higher percentage of LA LGE (26.7 ± 12.5% vs. 17.0 ± 7.7%; P < 0.001), higher LA T1 relaxation times (856.7 ± 112.2 ms vs. 746.8 ± 91.0 ms; P < 0.001) and higher plasma levels of relaxin (0.69 ± 1.34 pg/ml vs. 0.37 ± 0.88 pg/ml; P = 0.035). In the multivariate Cox regression analysis, poor ablation outcome was best predicted by advanced LGE stage (hazard ratio (HR):5.487; P = 0.001) and T1 relaxation times (HR:1.007; P = 0.001). Pre-procedural CMR is a valuable tool for prediction of poor response to catheter ablation therapy in patients with AF. It offers various imaging techniques for outcome prediction and might be valuable for a better patient selection prior to ablation therapy. |
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