QRS‐T Angle: A Review

Oehler, Andrew; Feldman, Benjamin; Henrikson, M.P.H. Charles A.; Tereshchenko, Larisa G.

doi:10.1111/anec.12206

Cited by 210 publications

(230 citation statements)

References 30 publications

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“…The spatial mean QRS-T angle reflects the spatial angle between depolarization and repolarization and was calculated as [18]:…”

Section: Quantitative Evaluationmentioning

confidence: 99%

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects

Nguyên¹,

Potse²,

Regoli³

et al. 2015

Journal of Electrocardiology

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Aim: The aim of this study was to investigate the influence of geometrical factors on the ECG morphology and vectorcardiogram (VCG) parameters. Methods: Patient-tailored models based on five heart-failure patients with intraventricular conduction defects (IVCDs) were created. The heart was shifted up to 6 cm to the left, right, up, and down and rotated ±30°around the anteroposterior axis. Precordial electrodes were shifted 3 cm down.Results: Geometry modifications strongly altered ECG notching/slurring and intrinsicoid deflection time. Maximum VCG parameter changes were small for QRS duration (− 6% to + 10%) and QRS-T angle (− 6% to + 3%), but considerable for QRS amplitude (− 36% to + 59%), QRS area (− 37% to + 42%), T-wave amplitude (− 41% to + 36%), and T-wave area (− 42% to + 33%). Conclusion:The position of the heart with respect to the electrodes is an important factor determining notching/slurring and voltage-dependent parameters and therefore must be considered for accurate diagnosis of IVCDs.

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“…The spatial mean QRS-T angle reflects the spatial angle between depolarization and repolarization and was calculated as [18]:…”

Section: Quantitative Evaluationmentioning

confidence: 99%

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects

Nguyên¹,

Potse²,

Regoli³

et al. 2015

Journal of Electrocardiology

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“…SAI QRST was calculated as the arithmetic sum of areas under the QRS‐T curve 15, 17. Spatial mean QRS‐T angle was measured as the 3‐dimensional angle between the mean QRS‐vector and the mean T‐vector 9. The magnitude, azimuth, and elevation of the SVG vector were measured as previously defined 12…”

Section: Methodsmentioning

confidence: 99%

“…SVG is a vector sum of spatial QRS and T vectors, reflecting implication of the spatial QRS‐T angle 9. Spatial QRS‐T angle is a well‐known marker9 of the risk of ventricular tachyarrhythmias10 and sudden cardiac death (SCD)11, 12 in the general population, heart failure (HF) patients, and other populations 13, 14…”

Section: Introductionmentioning

confidence: 99%

Genome‐Wide Associations of Global Electrical Heterogeneity ECG Phenotype: The ARIC (Atherosclerosis Risk in Communities) Study and CHS (Cardiovascular Health Study)

Tereshchenko

Sotoodehnia

Sitlani

et al. 2018

JAHA

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Background ECG global electrical heterogeneity (GEH) is associated with sudden cardiac death. We hypothesized that a genome‐wide association study would identify genetic loci related to GEH.Methods and ResultsWe tested genotyped and imputed variants in black (N=3057) and white (N=10 769) participants in the ARIC (Atherosclerosis Risk in Communities) study and CHS (Cardiovascular Health Study). GEH (QRS‐T angle, sum absolute QRST integral, spatial ventricular gradient magnitude, elevation, azimuth) was measured on 12‐lead ECGs. Linear regression models were constructed with each GEH variable as an outcome, adjusted for age, sex, height, body mass index, study site, and principal components to account for ancestry. GWAS identified 10 loci that showed genome‐wide significant association with GEH in whites or joint ancestry. The strongest signal (rs7301677, near TBX3) was associated with QRS‐T angle (white standardized β+0.16 [95% CI 0.13–0.19]; P=1.5×10−26), spatial ventricular gradient elevation (+0.11 [0.08–0.14]; P=2.1×10−12), and spatial ventricular gradient magnitude (−0.12 [95% CI −0.15 to −0.09]; P=5.9×10−15). Altogether, GEH‐SNPs explained 1.1% to 1.6% of GEH variance. Loci on chromosomes 4 (near HMCN2), 5 (IGF1R), 11 (11p11.2 region cluster), and 7 (near ACTB) are novel ECG phenotype‐associated loci. Several loci significantly associated with gene expression in the left ventricle (HMCN2 locus—with HMCN2;IGF1R locus—with IGF1R), and atria (RP11‐481J2.2 locus—with expression of a long non‐coding RNA and NDRG4).ConclusionsWe identified 10 genetic loci associated with ECG GEH. Replication of GEH GWAS findings in independent cohorts is warranted. Further studies of GEH‐loci may uncover mechanisms of arrhythmogenic remodeling in response to cardiovascular risk factors.

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“…They concluded that the spatial QRS-T angle is an important prognostic predictor and that it is superior to more conventional ECG parameters. While it is known that the spatial QRS-T angle varies with age and gender [5], to our knowledge there is less information available regarding dependence on race. The present study compares the normal limits of the spatial QRS-T angle in four cohorts of apparently healthy, different racial groups.…”

Section: Introductionmentioning

confidence: 98%