{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T19:46:27Z","timestamp":1773431187352,"version":"3.50.1"},"reference-count":57,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,2,19]],"date-time":"2021-02-19T00:00:00Z","timestamp":1613692800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000274","name":"British Heart Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000274","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Physiol."],"abstract":"<jats:p>Paroxysmal atrial fibrillation (PAF) is the most common cardiac arrhythmia, conveying a stroke risk comparable to persistent AF. It poses a significant diagnostic challenge given its intermittency and potential brevity, and absence of symptoms in most patients. This pilot study introduces a novel biomarker for early PAF detection, based upon analysis of sinus rhythm ECG waveform complexity. Sinus rhythm ECG recordings were made from 52 patients with (<jats:italic>n<\/jats:italic> = 28) or without (<jats:italic>n<\/jats:italic> = 24) a subsequent diagnosis of PAF. Subjects used a handheld ECG monitor to record 28-second periods, twice-daily for at least 3 weeks. Two independent ECG complexity indices were calculated using a Lempel-Ziv algorithm: R-wave interval variability (beat detection, BD) and complexity of the entire ECG waveform (threshold crossing, TC). TC, but not BD, complexity scores were significantly greater in PAF patients, but TC complexity alone did not identify satisfactorily individual PAF cases. However, a composite complexity score (<jats:italic>h<\/jats:italic>-score) based on within-patient BD and TC variability scores was devised. The <jats:italic>h<\/jats:italic>-score allowed correct identification of PAF patients with 85% sensitivity and 83% specificity. This powerful but simple approach to identify PAF sufferers from analysis of brief periods of sinus-rhythm ECGs using hand-held monitors should enable easy and low-cost screening for PAF with the potential to reduce stroke occurrence.<\/jats:p>","DOI":"10.3389\/fphys.2021.570705","type":"journal-article","created":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T23:36:19Z","timestamp":1613864179000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Prediction of Paroxysmal Atrial Fibrillation From Complexity Analysis of the Sinus Rhythm ECG: A Retrospective Case\/Control Pilot Study"],"prefix":"10.3389","volume":"12","author":[{"given":"Vadim","family":"Alexeenko","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philippa J.","family":"Howlett","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James A.","family":"Fraser","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Abasolo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thang S.","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David S.","family":"Fluck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher H.","family":"Fry","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rita I.","family":"Jabr","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2021,2,19]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1299","DOI":"10.1016\/j.clinph.2017.04.026","article-title":"Seizure prediction in patients with focal hippocampal epilepsy.","volume":"128","author":"Aarabi","year":"2017","journal-title":"Clin. Neurophysiol."},{"key":"B2","doi-asserted-by":"publisher","first-page":"2742","DOI":"10.1152\/jn.00575.2014","article-title":"Lempel-Ziv complexity of cortical activity during sleep and waking in rats.","volume":"113","author":"Ab\u00e1salo","year":"2015","journal-title":"J. Neurophysiol."},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-63343-7","article-title":"The complexity of clinically-normal sinus-rhythm ECGs is decreased in equine athletes with a diagnosis of paroxysmal atrial fibrillation.","volume":"10","author":"Alexeenko","year":"2020","journal-title":"Sci. Rep."},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-38935-7","article-title":"The application of Lempel-Ziv and Titchener complexity analysis for equine telemetric electrocardiographic recordings.","volume":"9","author":"Alexeenko","year":"2019","journal-title":"Sci. Rep."},{"key":"B5","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.1161\/CIRCRESAHA.117.311312","article-title":"Cardiovascular event prediction by machine learning: the multi-ethnic study of atherosclerosis.","volume":"121","author":"Ambale-Venkatesh","year":"2017","journal-title":"Circ. Res."},{"key":"B6","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1162\/089976604322860677","article-title":"Estimating the entropy rate of spike trains via Lempel-Ziv complexity.","volume":"16","author":"Amigo","year":"2004","journal-title":"Neural Comput."},{"key":"B7","doi-asserted-by":"publisher","first-page":"1453","DOI":"10.1161\/CIRCRESAHA.114.303211","article-title":"The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms.","volume":"114","author":"Andrade","year":"2014","journal-title":"Circ. Res."},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1063\/1.5023588","article-title":"Is human atrial fibrillation stochastic or deterministic? Insights from missing ordinal patterns and causal entropy-complexity plane analysis.","volume":"28","author":"Aronis","year":"2018","journal-title":"Chaos"},{"key":"B9","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/S0140-6736(19)31721-0","article-title":"An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.","volume":"394","author":"Attia","year":"2019","journal-title":"Lancet"},{"key":"B10","doi-asserted-by":"publisher","first-page":"2682","DOI":"10.1016\/j.ijcard.2012.06.118","article-title":"Pattern of atrial fibrillation and risk of outcomes: the Loire Valley Atrial Fibrillation Project.","volume":"167","author":"Banerjee","year":"2013","journal-title":"Int. J. Cardiol."},{"key":"B11","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1016\/j.amjcard.2015.06.012","article-title":"A comparison of atrial fibrillation monitoring strategies after cryptogenic stroke.","volume":"116","author":"Choe","year":"2015","journal-title":"Am. J. Cardiol."},{"key":"B12","doi-asserted-by":"publisher","first-page":"244","DOI":"10.1111\/ene.14061","article-title":"Ultra-early continuous cardiac monitoring improves atrial fibrillation detection and prognosis of patients with cryptogenic stroke.","volume":"27","author":"Cuadrado-Godia","year":"2020","journal-title":"Eur. J. Neurol."},{"key":"B13","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1159\/000068743","article-title":"Atrial fibrillation is associated with severe acute ischemic stroke.","volume":"22","author":"Dulli","year":"2003","journal-title":"Neuroepidemiology"},{"key":"B14","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1093\/eurheartj\/ehw007","article-title":"The impact of atrial fibrillation type on the risk of thrombo-embolism, mortality, and bleeding: a systematic review and meta-analysis.","volume":"37","author":"Ganesan","year":"2016","journal-title":"Eur. Heart J."},{"key":"B15","first-page":"601","article-title":"RR interval analysis for detection of atrial fibrillation in ECG monitors.","volume":"2008","author":"Ghodrati","year":"2008","journal-title":"Conf. Proc. IEEE Eng. Med. Biol. Soc."},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1063\/1.3156832","article-title":"Introduction to controversial topics in nonlinear science: is the normal heart rate chaotic?","volume":"19","author":"Glass","year":"2009","journal-title":"Chaos"},{"key":"B17","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1152\/physiologyonline.1991.6.2.87","article-title":"Is the normal heartbeat chaotic or homeostatic?","volume":"6","author":"Goldberger","year":"1991","journal-title":"Physiology"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2018-022558","article-title":"Anticoagulation therapy in patients with stroke and atrial fibrillation: a registry-based study of acute stroke care in Surrey, UK.","volume":"8","author":"Han","year":"2018","journal-title":"BMJ Open"},{"key":"B19","author":"Hand","year":"1981","journal-title":"Discrimination and Classification. Wiley Series in Probability in Mathematical Statistics."},{"key":"B20","doi-asserted-by":"publisher","first-page":"857","DOI":"10.7326\/0003-4819-146-12-200706190-00007","article-title":"Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation.","volume":"146","author":"Hart","year":"2007","journal-title":"Ann. Intern. Med."},{"key":"B21","doi-asserted-by":"publisher","first-page":"2191","DOI":"10.1056\/NEJMoa1802686","article-title":"Rivaroxaban for stroke prevention after embolic stroke of undetermined source.","volume":"378","author":"Hart","year":"2018","journal-title":"N. Engl. J. Med."},{"key":"B22","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1056\/NEJMoa1105575","article-title":"Subclinical atrial fibrillation and the risk of stroke.","volume":"366","author":"Healey","year":"2012","journal-title":"N. Engl. J. Med."},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0224582","article-title":"Predicting atrial fibrillation in primary care using machine learning.","volume":"14","author":"Hill","year":"2019","journal-title":"PLoS One"},{"key":"B24","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1098\/rsta.2008.0197","article-title":"Nonlinear analysis of electro-encephalogram and magnetoencephalogram recordings in patients with Alzheimer\u2019s disease.","volume":"367","author":"Hornero","year":"2009","journal-title":"Philos. Trans. A Math. Phys. Eng. Sci."},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.3390\/s20072136","article-title":"Detection of atrial fibrillation using 1D convolutional neural network.","volume":"20","author":"Hsieh","year":"2020","journal-title":"Sensors"},{"key":"B26","doi-asserted-by":"publisher","first-page":"863","DOI":"10.2459\/JCM.0000000000000181","article-title":"Cryptogenic ischemic stroke and prevalence of asymptomatic atrial fibrillation: a prospective study.","volume":"17","author":"Jorfida","year":"2016","journal-title":"J. Cardiovasc. Med."},{"key":"B27","doi-asserted-by":"publisher","first-page":"1514","DOI":"10.1161\/STROKEAHA.110.582437","article-title":"Cost-effectiveness of outpatient cardiac monitoring to detect atrial fibrillation after ischemic stroke.","volume":"41","author":"Kamel","year":"2010","journal-title":"Stroke"},{"key":"B28","doi-asserted-by":"publisher","first-page":"842","DOI":"10.1103\/physreva.36.842","article-title":"Easily calculable measure for the complexity of spatiotemporal patterns.","volume":"36","author":"Kaspar","year":"1987","journal-title":"Phys. Rev. A Gen. Phys."},{"key":"B29","doi-asserted-by":"publisher","first-page":"1609","DOI":"10.1093\/eurheartj\/ehw210","article-title":"ESC guidelines for the management of atrial fibrillation developed in collaboration with EACTS.","volume":"18","author":"Kirchhof","year":"2016","journal-title":"Europace"},{"key":"B30","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1109\/TIT.1976.1055501","article-title":"Complexity of finite sequences.","volume":"22","author":"Lempel","year":"1976","journal-title":"IEEE Trans. Inf. Theory"},{"key":"B31","doi-asserted-by":"crossref","first-page":"2731","DOI":"10.1161\/STROKEAHA.110.590257","article-title":"Identifying patients at high risk for stroke despite anticoagulation: a comparison of contemporary stroke risk stratification schemes in an anticoagulated atrial fibrillation cohort.","volume":"41","author":"Lip","year":"2010","journal-title":"Stroke"},{"key":"B32","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1161\/CIRCULATIONAHA.118.035411","article-title":"Refining prediction of atrial fibrillation-related stroke using the P2-CHA2DS2-VASc score.","volume":"139","author":"Maheshwari","year":"2019","journal-title":"Circulation"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.3390\/s20123570","article-title":"Artificial neural network for atrial fibrillation identification in portable devices.","volume":"20","author":"Marinucci","year":"2020","journal-title":"Sensors"},{"key":"B34","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.cmpb.2010.07.011","article-title":"Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal.","volume":"105","author":"Mohebbi","year":"2012","journal-title":"Comput. Methods Programs Biomed."},{"key":"B35","doi-asserted-by":"publisher","first-page":"2335","DOI":"10.1016\/j.jacc.2014.02.555","article-title":"Atrial remodeling and atrial fibrillation: recent advances and translational perspectives.","volume":"63","author":"Nattel","year":"2014","journal-title":"J. Am. Coll. Cardiol."},{"key":"B36","year":"2018","journal-title":"Research Summaries."},{"key":"B37","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1109\/MeMeA.2017.7985881","article-title":"Application of Savitzky-Golay digital differentiator for QRS complex detection in an electrocardiographic monitoring system","author":"Nishida","year":"2017","journal-title":"Proceedings of the 2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)"},{"key":"B38","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.future.2020.07.021","article-title":"Robust detection of atrial fibrillation from short-term electrocardiogram using convolutional neural networks.","volume":"113","author":"Nurmaini","year":"2020","journal-title":"Fut. Gen. Comput. Syst."},{"key":"B39","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1161\/01.cir.89.1.224","article-title":"Asymptomatic arrhythmias in patients with symptomatic paroxysmal atrial fibrillation and paroxysmal supraventricular tachycardia.","volume":"89","author":"Page","year":"1994","journal-title":"Circulation"},{"key":"B40","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1109\/TBME.1985.325532","article-title":"A real-time QRS detection algorithm.","volume":"32","author":"Pan","year":"1985","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2014.00168","article-title":"Assessing randomness and complexity in human motion trajectories through analysis of symbolic sequences.","volume":"8","author":"Peng","year":"2014","journal-title":"Front. Hum. Neurosci."},{"key":"B42","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/j.pbiomolbio.2010.11.001","article-title":"Chaos in the genesis and maintenance of cardiac arrhythmias.","volume":"105","author":"Qu","year":"2011","journal-title":"Prog. Biophys. Mol. Biol."},{"key":"B43","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1109\/51.677174","article-title":"Estimating regularity in epileptic seizure time-series data: a complexity-measure approach.","volume":"17","author":"Radhakrishnan","year":"1998","journal-title":"IEEE Eng. Med. Biol. Mag."},{"key":"B44","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1212\/WNL.0b013e31829d8773","article-title":"High pro-BNP levels predict the occurrence of atrial fibrillation after cryptogenic stroke.","volume":"81","author":"Rodr\u00edguez-Y\u00e1\u00f1ez","year":"2013","journal-title":"Neurology"},{"key":"B45","article-title":"Optimum window length of Savitzky-Golay filters with arbitrary order.","author":"Sadeghi","year":"2018","journal-title":"arXiv"},{"key":"B46","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and differentiation of data by simplified least squares procedures.","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"B47","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0089328","article-title":"Improved detection of paroxysmal atrial fibrillation utilizing a software-assisted electrocardiogram approach.","volume":"9","author":"Schaefer","year":"2014","journal-title":"PLoS One"},{"key":"B48","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1161\/CIRCULATIONAHA.111.029801","article-title":"Prolonged rhythm monitoring for the detection of occult paroxysmal atrial fibrillation in ischemic stroke of unknown cause.","volume":"124","author":"Seet","year":"2011","journal-title":"Circulation"},{"key":"B49","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2017.00258","article-title":"An overview of heart rate variability metrics and norms.","volume":"5","author":"Shaffer","year":"2017","journal-title":"Front. Public Health"},{"key":"B50","first-page":"1","article-title":"Atrial fibrillation as a risk factor for cognitive decline and dementia.","volume":"33","author":"Singh-Manoux","year":"2017","journal-title":"Eur. Heart J."},{"key":"B51","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCEP.116.004662","article-title":"Incidence of idiopathic ventricular arrhythmias: a population-based study.","volume":"10","author":"Sirichand","year":"2017","journal-title":"Circ. Arrhythm. Electrophysiol."},{"key":"B52","doi-asserted-by":"publisher","first-page":"2176","DOI":"10.1161\/CIRCULATIONAHA.114.014343","article-title":"Mass screening for untreated atrial fibrillation: the STROKESTOP study.","volume":"131","author":"Svennberg","year":"2015","journal-title":"Circulation"},{"key":"B53","doi-asserted-by":"publisher","first-page":"3354","DOI":"10.1161\/STROKEAHA.115.010947","article-title":"Incidence of stroke or systemic embolism in paroxysmal versus sustained atrial fibrillation: the Fushimi atrial fibrillation registry.","volume":"46","author":"Takabayashi","year":"2015","journal-title":"Stroke"},{"key":"B54","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1109\/TBME.2003.821030","article-title":"Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes.","volume":"51","author":"Thong","year":"2004","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"B55","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.118.010756","article-title":"Divergent temporal trends in morbidity and mortality related to heart failure and atrial fibrillation: age, sex, race and geographic differences in the United States, 1991-2015.","volume":"8","author":"Vasan","year":"2019","journal-title":"J. Am. Heart Assoc."},{"key":"B56","doi-asserted-by":"publisher","DOI":"10.1186\/s12938-017-0406-z","article-title":"Paroxysmal atrial fibrillation recognition based on multi-scale wavelet \u03b1-entropy.","volume":"16","author":"Xin","year":"2017","journal-title":"Biomed. Eng. Online"},{"key":"B57","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1007\/s40846-016-0165-5","article-title":"Using Lempel\u2013Ziv complexity to assess ECG signal quality.","volume":"36","author":"Zhang","year":"2016","journal-title":"J. Med. Biol. Eng"}],"container-title":["Frontiers in Physiology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphys.2021.570705\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T23:36:30Z","timestamp":1613864190000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphys.2021.570705\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,19]]},"references-count":57,"alternative-id":["10.3389\/fphys.2021.570705"],"URL":"https:\/\/doi.org\/10.3389\/fphys.2021.570705","relation":{},"ISSN":["1664-042X"],"issn-type":[{"value":"1664-042X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,19]]},"article-number":"570705"}}