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Accessory pathway localization with probabilistic density maps generated by a mobile application: Validation of a full preexcitation net-vector method
  • +8
  • Marek Jastrzebski,
  • Kamil Fijorek,
  • Piotr Futyma,
  • Michal Orczykowski,
  • Maciej Pitak,
  • Łukasz Zarębski,
  • Piotr Sajdak,
  • Sebastian Góreczny,
  • Łukasz Szumowski,
  • Rajzer Marek,
  • Pawel Moskal
Marek Jastrzebski
Uniwersytet Jagiellonski w Krakowie I Klinika Kardiologii i Nadcisnienia Tetniczego

Corresponding Author:[email protected]

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Kamil Fijorek
Uniwersytet Ekonomiczny w Krakowie
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Piotr Futyma
Uniwersytet Rzeszowski
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Michal Orczykowski
National Institute of Cardiology
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Maciej Pitak
Uniwersytet Jagiellonski w Krakowie Collegium Medicum
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Łukasz Zarębski
Uniwersytet Rzeszowski
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Piotr Sajdak
Uniwersytet Rzeszowski
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Sebastian Góreczny
Uniwersytet Jagiellonski w Krakowie Collegium Medicum
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Łukasz Szumowski
National Institute of Cardiology
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Rajzer Marek
Uniwersytet Jagiellonski w Krakowie I Klinika Kardiologii i Nadcisnienia Tetniczego
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Pawel Moskal
Szpital Uniwersytecki w Krakowie
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Abstract

Introduction. Precise electrocardiographic localization of accessory pathways (AP) can be challenging. Seminal AP localization studies were limited by complexity of algorithms and sample size.We aimed to create a non-algorithmic method for AP localization based on color-coded maps of AP distribution generated by a web-based application. Methods. APs were categorized into 19 regions/types based on invasive electrophysiologic mapping. Preexcited QRS complexes were categorized into 6 types based on polarity and notch/slur. For each QRS type in each lead the distribution of APs was visualized on a gradient map. The principle of common set was used to combine the single lead maps to create the distribution map for AP with any combination of QRS types in several leads. For the validation phase, a separate cohort of APs was obtained. Results. A total of 804 patients with overt APs were studied. The application used the exploratory dataset of 552 consecutive APs and the corresponding QRS complexes to generate AP localization maps for any possible combination of QRS types in 12 leads. Optimized approach (on average 3 steps) for evaluation of preexcited ECG was developed. The area of maximum probability of AP localization was pinpointed by providing the QRS type for the subsequent leads. The exploratory dataset was validated with the separate cohort of APs (n = 260); p = 0.23 for difference in AP distribution. Conclusions. In the largest dataset of APs to-date, a novel probabilistic and semi-automatic approach to electrocardiographic localization of APs was highly predictive for anatomic localization.
Submitted to Journal of Cardiovascular Electrophysiology
24 Jan 2024Reviewer(s) Assigned
31 Jan 2024Review(s) Completed, Editorial Evaluation Pending
24 Feb 20241st Revision Received
27 Feb 2024Review(s) Completed, Editorial Evaluation Pending
27 Feb 2024Submission Checks Completed
27 Feb 2024Assigned to Editor
27 Feb 2024Reviewer(s) Assigned
03 Mar 2024Editorial Decision: Revise Minor
05 Mar 20242nd Revision Received
05 Mar 2024Submission Checks Completed
05 Mar 2024Assigned to Editor
05 Mar 2024Review(s) Completed, Editorial Evaluation Pending
07 Mar 2024Editorial Decision: Accept