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Fully automated QRS area measurement for predicting response tocardiac resynchronization therapy
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SYSNO ASEP 0536110 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Fully automated QRS area measurement for predicting response tocardiac resynchronization therapy Author(s) Plešinger, Filip (UPT-D) RID, ORCID, SAI
van Stipdonk, A. M. W. (NL)
Smíšek, Radovan (UPT-D) RID, ORCID, SAI
Halámek, Josef (UPT-D) RID, ORCID, SAI
Jurák, Pavel (UPT-D) RID, ORCID, SAI
Maass, A. H. (NL)
Meine, M. (NL)
Vernooy, K. (NL)
Prinzen, F. W. (NL)Number of authors 9 Source Title Journal of Electrocardiology. - : Churchill Livingstone - ISSN 0022-0736
Roč. 63, NOV-DEC (2020), s. 159-163Number of pages 5 s. Publication form Print - P Language eng - English Country US - United States Keywords heart failure ; cardiac resynchronization therapy ; vectorcardiography ; QRS area ; software ; signal averaging Subject RIV FS - Medical Facilities ; Equipment OECD category Medical engineering R&D Projects GA17-13830S GA ČR - Czech Science Foundation (CSF) LO1212 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Method of publishing Open access Institutional support UPT-D - RVO:68081731 UT WOS 000600694400036 EID SCOPUS 85068892628 DOI 10.1016/j.jelectrocard.2019.07.003 Annotation Background: Cardiac resynchronization therapy (CRT) is an established treatment in patients with heart failureand conduction abnormalities. However, a significant number of patients do not respond to CRT. Currentlyemployed criteria for selection of patients for this therapy (QRS duration and morphology) have several short-comings. QRS area was recently shown to provide superior association with CRT response. However, its assess-ment was not fully automated and required the presence of an expert. Objective: Our objective was to develop a fully automated method for the assessment of vector-cardiographic(VCG) QRS area from electrocardiographic (ECG) signals. Methods: Pre-implantation ECG recordings (N = 864, 695 left-bundle-branch block, 589 men) in PDFfiles wereconverted to allow signal processing. QRS complexes were found and clustered into morphological groups. Sig-nals were converted from 12‑lead ECG to 3‑lead VCG and an average QRS complex was built. QRS area was com-putedfrom individualareasinthe X, Y and Z leads. Practical usability wasevaluatedusing Kaplan-Meierplots and5-year follow-up data. Results:The automatically calculated QRS area values were 123 ± 48μV.s (mean values and SD), while the man-ually determined QRS area values were 116 ± 51 ms, the correlation coefficient between the two was r = 0.97.The automated and manual methods showed the same ability to stratify the population (hazard ratios 2.09 vs2.03, respectively).Conclusion:The presented approach allows the fully automatic and objective assessment of QRS area values.Significance:Until this study, assessing QRS area values required an expert, which means both additional costsand a risk of subjectivity. The presented approach eliminates these disadvantages and is publicly available aspart of free signal-processing software. Workplace Institute of Scientific Instruments Contact Martina Šillerová, sillerova@ISIBrno.Cz, Tel.: 541 514 178 Year of Publishing 2021 Electronic address https://www.sciencedirect.com/science/article/pii/S0022073619303437
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