Literature DB >> 33537064

A Method to Minimise the Impact of ECG Marker Inaccuracies on the Spatial QRS-T angle: Evaluation on 1,512 Manually Annotated ECGs.

William J Young1,2, Stefan van Duijvenboden1,3, Julia Ramírez1,3, Aled Jones1, Andrew Tinker1, Patricia B Munroe1, Pier D Lambiase3,2, Michele Orini3,2.   

Abstract

The spatial QRS-T angle (QRS-Ta) derived from the vectorcardiogram (VCG) is a strong risk predictor for ventricular arrhythmia and sudden cardiac death with potential use for mass screening. Accurate QRS-Ta estimation in the presence of ECG delineation errors is crucial for its deployment as a prognostic test. Our study assessed the effect of inaccurate QRS and T-wave marker placement on QRS-Ta estimation and proposes a robust method for its calculation. Reference QRS-Ta measurements were derived from 1,512 VCGs manually annotated by three expert reviewers. We systematically changed onset and offset timings of QRS and T-wave markers to simulate inaccurate placement. The QRS-Ta was recalculated using a standard approach and our proposed algorithm, which limits the impact of VCG marker inaccuracies by defining the vector origin as an interval preceding QRS-onset and redefines the beginning and end of QRS and T-wave loops. Using the standard approach, mean absolute errors (MAE) in peak QRS-Ta were >40% and sensitivity and precision in the detection of abnormality (>105°) were <80% and <65% respectively, when QRS-onset was delayed or QRS-offset anticipated >15 ms. Using our proposed algorithm, MAE for peak QRS-Ta were reduced to <4% and sensitivity and precision of abnormality were >94% for inaccuracies up to ±15 ms. Similar results were obtained for mean QRS-Ta. In conclusion, inaccuracies of QRS and T-wave markers can significantly influence the QRS-Ta. Our proposed algorithm provides robust QRS-Ta measurements in the presence of inaccurate VCG annotation, enabling its use in large datasets.
© 2020 The Author(s).

Entities:  

Keywords:  Automatic analysis; Electrocardiogram; Population distribution; Spatial QRS-T angle; Vectorcardiogram

Year:  2021        PMID: 33537064      PMCID: PMC7762839          DOI: 10.1016/j.bspc.2020.102305

Source DB:  PubMed          Journal:  Biomed Signal Process Control        ISSN: 1746-8094            Impact factor:   3.880


  21 in total

1.  Reconstruction of the Frank vectorcardiogram from standard electrocardiographic leads: diagnostic comparison of different methods.

Authors:  J A Kors; G van Herpen; A C Sittig; J H van Bemmel
Journal:  Eur Heart J       Date:  1990-12       Impact factor: 29.983

2.  Variability of Ventricular Repolarization Dispersion Quantified by Time-Warping the Morphology of the T-Waves.

Authors:  Julia Ramirez; Michele Orini; J Derek Tucker; Esther Pueyo; Pablo Laguna
Journal:  IEEE Trans Biomed Eng       Date:  2016-10-04       Impact factor: 4.538

3.  Global Electric Heterogeneity Risk Score for Prediction of Sudden Cardiac Death in the General Population: The Atherosclerosis Risk in Communities (ARIC) and Cardiovascular Health (CHS) Studies.

Authors:  Jonathan W Waks; Colleen M Sitlani; Elsayed Z Soliman; Muammar Kabir; Elyar Ghafoori; Mary L Biggs; Charles A Henrikson; Nona Sotoodehnia; Tor Biering-Sørensen; Sunil K Agarwal; David S Siscovick; Wendy S Post; Scott D Solomon; Alfred E Buxton; Mark E Josephson; Larisa G Tereshchenko
Journal:  Circulation       Date:  2016-04-14       Impact factor: 29.690

4.  Spatial QRS-T angle predicts cardiac death in a general population.

Authors:  Isabella Kardys; Jan A Kors; Irene M van der Meer; Albert Hofman; Deirdre A M van der Kuip; Jacqueline C M Witteman
Journal:  Eur Heart J       Date:  2003-07       Impact factor: 29.983

Review 5.  QRS-T angle: a review.

Authors:  Andrew Oehler; Trevor Feldman; Charles A Henrikson; Larisa G Tereshchenko
Journal:  Ann Noninvasive Electrocardiol       Date:  2014-09-09       Impact factor: 1.468

6.  Sympathetic activity-associated periodic repolarization dynamics predict mortality following myocardial infarction.

Authors:  Konstantinos D Rizas; Tuomo Nieminen; Petra Barthel; Christine S Zürn; Mika Kähönen; Jari Viik; Terho Lehtimäki; Kjell Nikus; Christian Eick; Tim O Greiner; Hans P Wendel; Peter Seizer; Jürgen Schreieck; Meinrad Gawaz; Georg Schmidt; Axel Bauer
Journal:  J Clin Invest       Date:  2014-03-18       Impact factor: 14.808

7.  Cardiovascular Predictive Value and Genetic Basis of Ventricular Repolarization Dynamics.

Authors:  Julia Ramírez; Stefan van Duijvenboden; Nay Aung; Pablo Laguna; Esther Pueyo; Andrew Tinker; Pier D Lambiase; Michele Orini; Patricia B Munroe
Journal:  Circ Arrhythm Electrophysiol       Date:  2019-10-14

8.  Spatial/Frontal QRS-T Angle Predicts All-Cause Mortality and Cardiac Mortality: A Meta-Analysis.

Authors:  Xinlin Zhang; Qingqing Zhu; Li Zhu; He Jiang; Jun Xie; Wei Huang; Biao Xu
Journal:  PLoS One       Date:  2015-08-18       Impact factor: 3.240

9.  Thirty loci identified for heart rate response to exercise and recovery implicate autonomic nervous system.

Authors:  Julia Ramírez; Stefan van Duijvenboden; Ioanna Ntalla; Borbala Mifsud; Helen R Warren; Evan Tzanis; Michele Orini; Andrew Tinker; Pier D Lambiase; Patricia B Munroe
Journal:  Nat Commun       Date:  2018-05-16       Impact factor: 14.919

10.  Evaluation of the reentry vulnerability index to predict ventricular tachycardia circuits using high-density contact mapping.

Authors:  Michele Orini; Adam J Graham; Neil T Srinivasan; Fernando O Campos; Ben M Hanson; Anthony Chow; Ross J Hunter; Richard J Schilling; Malcolm Finlay; Mark J Earley; Simon Sporton; Mehul Dhinoja; Martin Lowe; Bradley Porter; Nicholas Child; Christopher A Rinaldi; Jaswinder Gill; Martin Bishop; Peter Taggart; Pier D Lambiase
Journal:  Heart Rhythm       Date:  2019-11-18       Impact factor: 6.343

View more
  3 in total

1.  Reproducibility of global electrical heterogeneity measurements on 12-lead ECG: The Multi-Ethnic Study of Atherosclerosis.

Authors:  Kazi T Haq; Katherine J Lutz; Kyle K Peters; Natalie E Craig; Evan Mitchell; Anish K Desai; Nathan W L Stencel; Elsayed Z Soliman; João A C Lima; Larisa G Tereshchenko
Journal:  J Electrocardiol       Date:  2021-10-02       Impact factor: 1.438

2.  Deep-Learning-Based Estimation of the Spatial QRS-T Angle from Reduced-Lead ECGs.

Authors:  Ana Santos Rodrigues; Rytis Augustauskas; Mantas Lukoševičius; Pablo Laguna; Vaidotas Marozas
Journal:  Sensors (Basel)       Date:  2022-07-20       Impact factor: 3.847

Review 3.  Analysing electrocardiographic traits and predicting cardiac risk in UK biobank.

Authors:  Julia Ramírez; Stefan van Duijvenboden; William J Young; Michele Orini; Aled R Jones; Pier D Lambiase; Patricia B Munroe; Andrew Tinker
Journal:  JRSM Cardiovasc Dis       Date:  2021-06-12
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.