{'fraction_non_alphanumeric': 0.019313304721030045, 'fraction_numerical': 0.005722460658082976, 'mean_word_length': 5.960199004975125, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Classification of persistent and long-standing persistent atrial fibrillation by means of surface electrocardiograms

Abstract Atrial fibrillation, which is the most common cardiac arrhythmia, is typically classified into four clinical subtypes: paroxysmal, persistent, long-standing persistent and permanent. The ability to distinguish between them is of crucial significance in choosing the most suitable therapy for each patient. Nevertheless, classification is currently established once the natural history of the arrhythmia has been disclosed as it is not possible to make an early differentiation. This paper presents a novel method to discriminate persistent and long-standing atrial fibrillation patients by means of a time-frequency analysis of the surface electrocardiogram. Classification results provide approximately 75% accuracy when evaluating ECGs of consecutive unselected patients from a tertiary center and higher than 80% when patients are not under antiarrhythmic treatment or do not have structural heart disease (76% sensitivity and 88% specificity). Moreover, to our knowledge, this is the first study that discriminates between persistent and long-standing persistent subtypes in a heterogeneous population sample and without discontinuing antiarrhythmic therapy to patients. Thus, it can help clinicians to address the most suitable therapeutic approach for each patient.