Atrial fibrillation fingerprinting; spotting bio‐electrical markers to early recognize atrial fibrillation by the use of a bottom‐up approach (AFFIP): Rationale and design. Issue 6 (18th April 2020)

• Record Type: Journal Article
• Authors: Starreveld, Roeliene; Knops, Paul; Ramos, Kennedy S.; Roos‐Serote, Maarten C.; Bogers, Ad J.J.C.; Brundel, Bianca J.J.M.; de Groot, Natasja M.S.
• Is Part Of: Clinical cardiology. Volume 43:Issue 6(2020)
• Page Start: 546
• Page End: 552
• Publication Date: 2020-04-18
• Subjects: atrial fibrillation -- biomarkers -- cardiac electrophysiology -- electrogram fractionation -- high density mapping -- signal modeling; Cardiology -- Periodicals; 616.12005
• DOI: 10.1002/clc.23370
• Languages: English
• ISSNs: 0160-9289

Abstract

Abstract: Background: The exact pathophysiology of atrial fibrillation (AF) remains incompletely understood and treatment of AF is associated with high recurrence rates. Persistence of AF is rooted in the presence of electropathology, defined as complex electrical conduction disorders caused by structural damage of atrial tissue. The atrial fibrillation fingerprinting (AFFIP) study aims to characterize electropathology, enabling development of a novel diagnostic instrument to predict AF onset and early progression. Hypotheses: History of AF, development of post‐operative AF, age, gender, underlying heart disease, and other clinical characteristics impact the degree of electropathology. Methods: This study is a prospective observational study with a planned duration of 48 months. Three study groups are defined: (1) patients with (longstanding) persistent AF, (2) patients with paroxysmal AF, and (3) patients without a history of AF, all undergoing open‐chest cardiac surgery. Intra‐operative high‐resolution epicardial mapping is performed to identify the patient‐specific electrical profile, whereas the patient‐specific biological profile is assessed by evaluating proteostasis markers in blood samples and atrial appendage tissue samples. Post‐operative continuous rhythm monitoring is performed for detection of early post‐operative AF. Late post‐operative AF (during 5‐year follow‐up) is documented by either electrocardiogram or 24‐hour Holter registration. Results: The required sample size for this study is estimated at 447 patients. Up till now, 105 patients were included, of whom 36 have a history of AF. Conclusion: The AFFIP study will elucidate whether electrophysiological and structural characteristics represent a novel diagnostic tool, the AF fingerprint, to predict onset and early progression of AF in cardiac surgery patients.