Literature DB >> 11326349

2:1 Atrioventricular block: order from chaos.

S S Barold1.   

Abstract

2:1 AV block can occur in either the AV node or the His-Purkinje system and cannot be classified into type I or type II second-degree AV block because there is only one PR interval to examine before the blocked P wave. It is inappropriate to use terms such as 2:1 or 3:1 type I or type II AV block because this characterization violates the accepted traditional definitions of type I and type II block based on electrocardiographic patterns and not on the anatomical site of block. Type I and type II second-degree AV block can progress to 2:1 AV block, and 2:1 AV block can regress to type I or type II block. Consequently, the site of the lesion in 2:1 block can often be determined by seeking the company 2:1 AV block keeps. An association with type I block and a narrow QRS complex almost always reflects AV nodal block but type I block with a wide QRS complex occurs more commonly in the His-Purkinje system than the AV node. Type II block, if correctly defined, is always infranodal. Outside of acute myocardial infarction, sustained 2:1 and 3:1 AV block with a wide QRS complex occurs in the His-Purkinje system in 80% of cases and 20% in the AV node. Administration of atropine in patients with His-Purkinje disease may increase the degree of AV block.

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Year:  2001        PMID: 11326349     DOI: 10.1053/ajem.2001.21715

Source DB:  PubMed          Journal:  Am J Emerg Med        ISSN: 0735-6757            Impact factor:   2.469


  3 in total

Review 1.  Second-degree atrioventricular block revisited.

Authors:  S Serge Barold; Bengt Herweg
Journal:  Herzschrittmacherther Elektrophysiol       Date:  2012-12-07

2.  General anesthesia in a patient with asymptomatic second-degree two-to-one atrioventricular block.

Authors:  Marie Shigematsu-Locatelli; Takashi Kawano; Atsushi Nishigaki; Daiki Yamanaka; Bun Aoyama; Hiroki Tateiwa; Noriko Kitaoka; Masataka Yokoyama
Journal:  JA Clin Rep       Date:  2017-05-10

3.  Expert-enhanced machine learning for cardiac arrhythmia classification.

Authors:  Sebastian Sager; Felix Bernhardt; Florian Kehrle; Maximilian Merkert; Andreas Potschka; Benjamin Meder; Hugo Katus; Eberhard Scholz
Journal:  PLoS One       Date:  2021-12-23       Impact factor: 3.240

  3 in total

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