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Automatic QRS Selvester scoring system in patients with left bundle branch block.
Xia, Xiaojuan; Wieslander, Björn; Strauss, David G; Wagner, Galen S; Zareba, Wojciech; Moss, Arthur J; Couderc, Jean-Philippe.
Afiliação
  • Xia X; Heart Research Follow-Up Program, Cardiology Division, University of Rochester Medical Center, 265 Crittenden Boulevard, PO Box 653, Rochester, NY 14642, USA heartjxx@heart.rochester.edu.
  • Wieslander B; Clinical Physiology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden.
  • Strauss DG; Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, United States Food and Drug Administration, Silver Spring, MD, USA.
  • Wagner GS; Duke Clinical Research Institute, Duke University, Durham, NC, USA.
  • Zareba W; Heart Research Follow-Up Program, Cardiology Division, University of Rochester Medical Center, 265 Crittenden Boulevard, PO Box 653, Rochester, NY 14642, USA.
  • Moss AJ; Heart Research Follow-Up Program, Cardiology Division, University of Rochester Medical Center, 265 Crittenden Boulevard, PO Box 653, Rochester, NY 14642, USA.
  • Couderc JP; Heart Research Follow-Up Program, Cardiology Division, University of Rochester Medical Center, 265 Crittenden Boulevard, PO Box 653, Rochester, NY 14642, USA.
Europace ; 18(2): 308-14, 2016 Feb.
Article em En | MEDLINE | ID: mdl-25805156
ABSTRACT

AIMS:

The Selvester QRS scoring system uses quantitative criteria from the standard 12-lead electrocardiogram (ECG) to estimate the myocardial scar size of patients, including those with left bundle branch block (LBBB). Automation of the scoring system could facilitate the clinical use of this technique which requires a set of multiple QRS patterns to be identified and measured. METHODS AND

RESULTS:

We developed a series of algorithms to automatically detect and measure the QRS parameters required for Selvester scoring. The 'QUantitative and Automatic REport of Selvester Score' was designed specifically for the analysis of ECGs from patients meeting new strict criteria for complete LBBB. The algorithms were designed using a training (n = 36) and a validation (n = 180) set of ECGs, consisting of signal-averaged 12-lead ECGs (1000 Hz sampling) recorded from 216 LBBB patients from the MADIT-CRT. We assessed the performance of the methods using expert manually adjudicated ECGs. The average of absolute differences between automatic and adjudicated Selvester scoring was 1.2 ± 1.5 points. The range of average differences for continuous measurements of wave locations and interval durations varied between 0 and 6 ms. Erroneous detection of Q, R, S, R', and S' waves (oversensed or missed) were 3, 1, 1, 16, and 6%, respectively. Seven percent of notches detected in the first 40 ms were misdetected.

CONCLUSION:

We propose an efficient computerized method for the automatic measurement of the Selvester score in patients with the strict LBBB.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Sinais Assistido por Computador / Bloqueio de Ramo / Eletrocardiografia / Sistema de Condução Cardíaco / Infarto do Miocárdio / Miocárdio Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Europace Assunto da revista: CARDIOLOGIA / FISIOLOGIA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Processamento de Sinais Assistido por Computador / Bloqueio de Ramo / Eletrocardiografia / Sistema de Condução Cardíaco / Infarto do Miocárdio / Miocárdio Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Europace Assunto da revista: CARDIOLOGIA / FISIOLOGIA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos