Title |
Maximal Pre-Excitation Based Algorithm for Localization of Manifest Accessory Pathways in Adults
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Published in |
JACC: Clinical Electrophysiology, May 2018
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DOI | 10.1016/j.jacep.2018.03.018 |
Pubmed ID | |
Authors |
Thomas Pambrun, Rim El Bouazzaoui, Nicolas Combes, Stéphane Combes, Pedro Sousa, Mathieu Le Bloa, Grégoire Massoullié, Ghassen Cheniti, Ruairidh Martin, Xavier Pillois, Josselin Duchateau, Frédéric Sacher, Mélèze Hocini, Pierre Jaïs, Nicolas Derval, Agustín Bortone, Serge Boveda, Arnaud Denis, Michel Haïssaguerre, Jean-Paul Albenque |
Abstract |
This study evaluated a new algorithm relying on maximal pre-excitation. Prior knowledge of accessory pathway (AP) location facilitates an individual ablation strategy. Delta-wave analysis on a 12-lead electrocardiogram is recognized as crucial for predicting ablation site, but can be ambiguous at basal state. An algorithm based on maximal pre-excitation, as induced by atrial pacing during an electrophysiological study, was initially developed in 132 patients with a single manifest AP. The maximally pre-excited QRS features included the global polarity in lead V1 (step 1), inferior leads (step 2), and leads V3 or I (step 3), as well as the morphology in lead II (step 4). Three investigators prospectively tested the new algorithm in 207 consecutive patients by comparing its efficacy to a control algorithm relying on basal pre-excitation. The accuracy, defined as the percent of patients with an exact prediction of AP location, was significantly greater with the new algorithm (90% vs. 63%; p < 0.001). The reproducibility, defined as the level of agreement between investigators in determining AP location, was excellent (κ > 0.75; p < 0.05) with the new algorithm and fair (0.40 < κ < 0.75; p < 0.05) with the control algorithm. An algorithm based on maximal pre-excitation allows accurate and reproducible localization of manifest APs. When ablation is indicated, the analysis of maximal pre-excitation is a sensible approach for giving a head start in endocardial mapping. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 13% |
Turkey | 5 | 8% |
Spain | 5 | 8% |
United Kingdom | 3 | 5% |
Chile | 2 | 3% |
Germany | 2 | 3% |
Uruguay | 2 | 3% |
Guatemala | 1 | 2% |
Peru | 1 | 2% |
Other | 8 | 13% |
Unknown | 23 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 36 | 60% |
Practitioners (doctors, other healthcare professionals) | 13 | 22% |
Scientists | 8 | 13% |
Science communicators (journalists, bloggers, editors) | 3 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 96 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 15 | 16% |
Researcher | 10 | 10% |
Student > Postgraduate | 10 | 10% |
Student > Doctoral Student | 8 | 8% |
Student > Ph. D. Student | 7 | 7% |
Other | 24 | 25% |
Unknown | 22 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 56 | 58% |
Biochemistry, Genetics and Molecular Biology | 2 | 2% |
Veterinary Science and Veterinary Medicine | 1 | 1% |
Nursing and Health Professions | 1 | 1% |
Unspecified | 1 | 1% |
Other | 2 | 2% |
Unknown | 33 | 34% |