Diagnostic and prognostic values of the QRS‐T angle in patients with suspected acute decompensated heart failure

Abstract

Aims The aim of this study was to investigate the diagnostic and prognostic utility of the QRS-T angle, an electrocardiogram (ECG) marker quantifying depolarization-repolarization heterogeneity, in patients with suspected acute decompensated heart failure (ADHF). Methods and results We prospectively enrolled unselected patients presenting to the emergency department with symptoms suggestive of ADHF. The QRS-T angle was automatically derived from a standard 12-lead ECG recorded at presentation. The primary diagnostic endpoint was a final adjudicated diagnosis of ADHF. The primary prognostic endpoint was all-cause mortality during 2 years of follow-up. Among the 1915 patients enrolled, those with higher QRS-T angles were older, were more commonly male, and had a higher rate of co-morbidities such as arterial hypertension, coronary artery disease, or chronic kidney disease. ADHF was the final adjudicated diagnosis in 1140 (60%) patients. The QRS-T angle in patients with ADHF was significantly larger than in patients with non-cardiac causes of dyspnoea {median 110°[inter-quartile range (IQR) 46-156°] vs. median 33°[IQR 15-57°], P < 0.001}. The diagnostic accuracy of the QRS-T angle as quantified by the area under the receiver operating characteristic curve (AUC) was 0.75 [95% confidence interval (CI) 0.73-0.77, P < 0.001], which was inferior to N-terminal pro-B-type natriuretic peptide (AUC 0.93, 95% CI 0.92-0.94, P < 0.001), but similar to that of high-sensitivity troponin T (AUC 0.78, 95% CI 0.76-0.80, P = 0.09). The AUC of the QRS-T angle for discrimination between ADHF and non-cardiac dyspnoea remained similarly high in subgroups of patients known to be diagnostically challenging, including patients older than 75 years [0.71 (95% CI 0.67-0.74)], renal failure [0.79 (95% CI 0.71-0.87)], and atrial fibrillation at presentation [0.68 (95% CI 0.60-0.76)]. Mortality rates according to QRS-T angle tertiles were 4%, 6%, and 10% after 30 days (P < 0.001) and 24%, 31%, and 43% after 2 years (P < 0.001). After adjustment for clinical, laboratory, and ECG parameters, the QRS-T angle remained an independent predictor for 2 year mortality with a 4% increase in mortality for every 20°increase in QRS-T angle (P = 0.02). Conclusions The QRS-T angle is a readily available and inexpensive marker that can assist in the discrimination between ADHF and non-cardiac causes of acute dyspnoea and may aid in the risk stratification of these patients.

Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy

“… 27 Similarly, prolonged P-wave duration >120 ms, indicating interatrial myopathy, has been linked to supraventricular arrhythmias, stroke, and mortality. 28 In addition, the QRS-T angle, 29 JTc interval, 30 and T-wave area 31 have been raised as potentially important determinants of response or outcome. However, various other subtle markers of ischaemia, dyssynchrony, or risk of arrhythmia may be represented by FactorECG.…”

Frontal QRS/T angle can predict mortality in COVID-19 patients

“…Non-ischaemic cardiomyopathy, myocarditis, acute coronary syndrome, and acute decompensated heart failure were predictive of mortality for >90°, >100°, >104°, and > 114° values in the literature [ 3 , 5 , 11 , 13 , 14 ]. We evaluated all of these angle values, including the normal range (45–60°) to predict mortality and need for MV support in COVID-19 patients.…”

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

“…Unfortunately, the answer to the posed questions remains open and falls beyond the scope of our research. Nevertheless, considering that intra-subject inaccuracies up to 10° are to be expected [ 27 ] and that a 20° increase in the spatial QRS-T angle is associated with a 4% aggravated risk of mortality [ 55 ], the estimation errors obtained from the subset { I , II , aVF , V2 } may suffice for detecting abnormal QRS-T angles without compromising patient comfortability. Furthermore, measuring the spatial QRS-T angle from subsets of solely frontal leads looks plausible in the future with further refinements of our deep learning prototype model.…”