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Performance of an External Transtelephonic Loop Recorder for Automated Detection of Paroxysmal Atrial Fibrillation
Author(s) -
Velthuis Bob Oude,
Bos Jorieke,
Kraaier Karin,
Stevenhagen Jeroen,
Opstal Jurren M.,
Palen Job,
Scholten Marcoen F.
Publication year - 2013
Publication title -
annals of noninvasive electrocardiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.494
H-Index - 48
eISSN - 1542-474X
pISSN - 1082-720X
DOI - 10.1111/anec.12075
Subject(s) - medicine , atrial fibrillation , implantable loop recorder , stroke (engine) , cardiology , paroxysmal atrial fibrillation , emergency medicine , mechanical engineering , engineering
Background Although atrial fibrillation (AF) is the most commonly encountered arrhythmia, some of the properties make its detection challenging. In daily practice, underdiagnosis can lead to less effective treatment in prevention of stroke. Based on data from studies on treatment of AF, more intensive follow‐up strategies, including 7‐day Holter recording, 30‐day event recording, and even implantable cardiac monitoring devices, are suggested. The study purpose is to evaluate the performance of a continuous single‐channel loop recorder with automatic AF detection and transtelephonic electrocardiogram (ECG) transmission capabilities. Methods and Results A consecutive cohort of 153 patients admitted to the stroke unit with a presumptive diagnosis of ischemic cerebrovascular accident was screened for AF. Twenty‐four‐hour rhythm observation was performed using a single‐channel external loop recorder (ELR) configured for automated AF detection. A total of 45 patients with a known history of AF, AF on the admission ECG, or incomplete registrations were excluded. Extensive additional frequency‐based settings were used to establish a reference registration. In total, 2923 recordings were transmitted. We evaluated all events, of which 1190 were designated by the device as AF. The sensitivity, specificity, PPV, and NPV for identifying AF using the ELR were, respectively, 93%, 51%, 5%, and 99%. Conclusions In this ELR validation study, the dedicated AF detection algorithm showed to be highly sensitive but not specific for AF. Applicability of an ELR might be limited for efficacious detection of AF, as manual verification is mandatory for a vast amount of recordings.

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