Literature DB >> 2292255

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

J A Kors1, G van Herpen, A C Sittig, J H van Bemmel.   

Abstract

Three methods for reconstructing the Frank VCG from the standard 12-lead ECG were studied. The first was based on multivariate regression, the second on a model of the cardio-electrical activity, and the third method used a quasi-orthogonal set of ECG leads. The methods were evaluated on a test set of 90 cases by a numerical distance measure and by the agreement in diagnostic classification of the original and reconstructed VCGs. The original and reconstructed VCGs were presented separately and in random order to three referees. Eighteen of the original VCGs were presented three times to estimate the intra-observer agreement. Kappa statistics were used to quantify the agreement between diagnostic classifications. Separately, one referee was simultaneously presented the original VCG and its three reconstructions for all cases. Each reconstruction VCG was classified as either diagnostically 'same' as the original, 'borderline' or 'different'. The performance of the regression method and the model-based method was comparable. Both methods were preferable to the quasi-orthogonal method. The kappa values for the preferred methods indicated a good to excellent diagnostic agreement between the original and reconstructed VCGs. Only one out of ninety VCGs that were reconstructed with the regression method was classified as 'different' compared with the original VCGs; three VCGs were classified as 'different' with the model-based method. It was also found that estimation of similarity by a distance measure could not replace diagnostic evaluation by skilled observers.

Mesh:

Year:  1990        PMID: 2292255     DOI: 10.1093/oxfordjournals.eurheartj.a059647

Source DB:  PubMed          Journal:  Eur Heart J        ISSN: 0195-668X            Impact factor:   29.983


  67 in total

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2.  Methodology of QT-interval measurement in the modular ECG analysis system (MEANS).

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4.  Screening entire health system ECG databases to identify patients at increased risk of death.

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Journal:  Circ Arrhythm Electrophysiol       Date:  2013-10-12

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6.  Global Electrical Heterogeneity: Mechanisms and Clinical Significance.

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Journal:  Comput Cardiol (2010)       Date:  2019-06-24

7.  Comparison of the prognostic significance of the electrocardiographic QRS/T angles in predicting incident coronary heart disease and total mortality (from the atherosclerosis risk in communities study).

Authors:  Zhu-Ming Zhang; Ronald J Prineas; Douglas Case; Elsayed Z Soliman; Pentti M Rautaharju
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8.  The utility of routine clinical 12-lead ECG in assessing eligibility for subcutaneous implantable cardioverter defibrillator.

Authors:  Jason A Thomas; Erick Andres Perez-Alday; Christopher Hamilton; Muammar M Kabir; Eugene A Park; Larisa G Tereshchenko
Journal:  Comput Biol Med       Date:  2018-05-08       Impact factor: 4.589

9.  Improving sudden cardiac death risk stratification by evaluating electrocardiographic measures of global electrical heterogeneity and clinical outcomes among patients with implantable cardioverter-defibrillators: rationale and design for a retrospective, multicenter, cohort study.

Authors:  Jonathan W Waks; Christopher Hamilton; Saumya Das; Ashkan Ehdaie; Jessica Minnier; Sanjiv Narayan; Mark Niebauer; Merritt Raitt; Christine Tompkins; Niraj Varma; Sumeet Chugh; Larisa G Tereshchenko
Journal:  J Interv Card Electrophysiol       Date:  2018-03-14       Impact factor: 1.900

10.  Accuracy of advanced versus strictly conventional 12-lead ECG for detection and screening of coronary artery disease, left ventricular hypertrophy and left ventricular systolic dysfunction.

Authors:  Todd T Schlegel; Walter B Kulecz; Alan H Feiveson; E Carl Greco; Jude L DePalma; Vito Starc; Bojan Vrtovec; M Atiar Rahman; Michael W Bungo; Matthew J Hayat; Terry Bauch; Reynolds Delgado; Stafford G Warren; Tulio Núñez-Medina; Rubén Medina; Diego Jugo; Håkan Arheden; Olle Pahlm
Journal:  BMC Cardiovasc Disord       Date:  2010-06-16       Impact factor: 2.298

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