A novel translational stratification system for electrophysiological characterization: evaluating arrhythmia complexity from the lab to the clinic. (10th June 2022)

• Record Type: Journal Article
• Authors: Sanchez De La Nava, AM; Gomez-Cid, L; Fernandez-Santos, ME; Arenal, A; Atienza, F; Fernandez-Aviles, F
• Is Part Of: Cardiovascular research. Volume 118(2022)Supplement 1
• Publication Date: 2022-06-10
• Subjects: Cardiovascular system -- Diseases -- Periodicals; Cardiovascular system -- Periodicals; 616.1
• DOI: 10.1093/cvr/cvac066.090
• Languages: English
• ISSNs: 0008-6363

Abstract

Abstract: Funding Acknowledgements: Type of funding sources: Public Institution(s). Main funding source(s): Instituto de Salud Carlos III CIBERCV Introduction: Cardiac arrhythmias can originate as a consequence of the proarrhythmic effects of some therapeutical regenerative products. In vitro studies have demonstrated different levels of electrophysiological complexity but these models usually lack of direct translation into the clinical practice. Objective: To develop an arrhythmia complexity evaluation method that enables to characterize electrophysiological complexity in translational scenarios. Methodology: To build a new evaluation method, frequency and rotor biomarkers from in vitro cell cultures presenting fibrillatory activity (N=15) were evaluated using optical mapping recordings (Rhod-2AM Ca2+ transient dye, 30-minute incubation, excited with green light). The patterns observed at in vitro level were analyzed and characterized by means of frequency and rotor biomarkers. Next, we performed a forward translational study to evaluate these electrophysiological biomarkers at a clinical level. In 206 patients with atrial fibrillation (AF) with non-invasive body surface recordings using the Acorys system from Corify (67 electrodes, 4 second segments) (STRATIFY-AF study) were evaluated to analyze the same frequency and rotor biomarkers previously explored in vitro. Moreover, we build a complexity score that described from 0 to 1 the complexity at electrophysiological level, where 0 corresponded to simple scenarios and 1 to complex arrhythmic patterns. Patients were followed for 12 months to evaluate long term evolution. Results: Complexity evaluation method identified the highest dominant frequency, median frequency and rotor time as the most important predictors for arrhythmia complexity definition. In vitro cultures results showed that samples presenting higher dominant frequency were also associated with small dominant frequency area extension and lower rotor time maintenance, i.e., with a high value of the complexity biomarker (Figure 1B). At clinical level, patients with high values of the complexity score were identified with Persistent AF patients showing complex patterns in whom AF recurred after ablation at 12 months (Figure 1D). Conclusions: We developed a translational approach that enables to characterize arrhythmia complexity in different frameworks, which is crucial to evaluate potential undesirable effects of therapeutical regenerative products during the complete development and validation of the product.