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Chronobiology International
The Journal of Biological and Medical Rhythm Research
Volume 19, 2002 - Issue 3
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Original

Circadian rhythm of atrioventricular conduction predicts long-term survival in patients with chronic atrial fibrillation

Junichiro Hayano Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan
,
Shinji Ishihara Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan
,
Hidekatsu Fukuta Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan
,
Seiichiro Sakata Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan
,
Seiji Mukai Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan
,
Nobuyuki Ohte Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan
&
Genjiro Kimura Third Department of Internal Medicine, Nagoya City University Medical School, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan
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Pages 633-648 | Received 05 Dec 2001, Accepted 04 Jan 2002, Published online: 07 Jul 2009

Citations (11)

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Tomás Fernández Alfonso, Ana María Celentano, Stella Maris Gonzalez Cappa & Diego A. Golombek. (2003) The Circadian System of Trypanosoma cruzi-Infected Mice. Chronobiology International 20:1, pages 49-64.
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Articles from other publishers (10)

Junichiro Hayano, Masaya Kisohara, Yuto Masuda & Emi Yuda. (2019) Detection of paroxysmal atrial fibrillation by Lorenz plot imaging of ECG R-R intervals. Detection of paroxysmal atrial fibrillation by Lorenz plot imaging of ECG R-R intervals.
Raúl Alcaraz & José J. Rieta. 2019. Cardiovascular Computing—Methodologies and Clinical Applications. Cardiovascular Computing—Methodologies and Clinical Applications 331 350 .
Ryo Matsuoka, Kohzoh Yoshino, Eiichi Watanabe & Ken Kiyono. (2017) Association between Multiscale Entropy Characteristics of Heart Rate Variability and Ischemic Stroke Risk in Patients with Permanent Atrial Fibrillation. Entropy 19:12, pages 672.
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Junichiro Hayano. 2017. Clinical Assessment of the Autonomic Nervous System. Clinical Assessment of the Autonomic Nervous System 109 127 .
Raúl Alcaraz & José J. Rieta. 2017. Complexity and Nonlinearity in Cardiovascular Signals. Complexity and Nonlinearity in Cardiovascular Signals 387 426 .
Valentina D. A. CorinoPyotr G. Platonov, Steve Enger, Arnljot Tveit & Sara R. Ulimoen. (2015) Circadian variation of variability and irregularity of heart rate in patients with permanent atrial fibrillation: relation to symptoms and rate control drugs. American Journal of Physiology-Heart and Circulatory Physiology 309:12, pages H2152-H2157.
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Amany Ahmed, Sreedevi Gondi, Casey Cox, Suwei Wang, Igor V. Stupin, K.J. Shankar, Shahzeb M. Munir, Ed Sobash, Alan Brewer, James J. Ferguson, MaCarthur A. Elayda, S. Ward Casscells & James M. Wilson. (2010) Circadian Body Temperature Variability is an Indicator of Poor Prognosis in Cardiomyopathic Hamsters. Journal of Cardiac Failure 16:3, pages 268-274.
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Luca Mainardi, Leif Sörnmo & Sergio CeruttiValentina Corino, Andreu Climent, Luca Mainardi & Andreas Bollmann. 2008. Understanding Atrial Fibrillation. Understanding Atrial Fibrillation 105 126 .
Luca Mainardi, Leif Sörnmo & Sergio Cerutti. 2008. Understanding Atrial Fibrillation. Understanding Atrial Fibrillation.
Stanley Nattel & Philippe Comtois. (2007) Teasing out circadian variability in heart rate turbulence: A new approach to detecting biorhythms underlying cardiac function. Heart Rhythm 4:3, pages 301-303.
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