Evaluation of Selvester QRS score for use in presence of conduction abnormalities in a broad population

Association of electrocardiographic markers with myocardial fibrosis as assessed by cardiac magnetic resonance in different clinical settings

BACKGROUND

Cardiac magnetic resonance (CMR) is a unique tool for non-invasive tissue characterization, especially for identifying fibrosis.

AIM

To present the existing data regarding the association of electrocardiographic (ECG) markers with myocardial fibrosis identified by CMR - late gadolinium enhancement (LGE).

METHODS

A systematic search was performed for identifying the relevant studies in Medline and Cochrane databases through February 2021. In addition, we conducted a relevant search by Reference Citation Analysis (RCA) (https://www.referencecitationanalysis.com).

RESULTS

A total of 32 studies were included. In hypertrophic cardiomyopathy (HCM), fragmented QRS (fQRS) is related to the presence and extent of myocardial fibrosis. fQRS and abnormal Q waves are associated with LGE in ischemic cardiomyopathy patients, while fQRS has also been related to fibrosis in myocarditis. Selvester score, abnormal Q waves, and notched QRS have also been associated with LGE. Repolarization abnormalities as reflected by increased Tp-Te, negative T-waves, and higher QT dispersion are related to myocardial fibrosis in HCM patients. In patients with Duchenne muscular dystrophy, a significant correlation between fQRS and the amount of myocardial fibrosis as assessed by LGE-CMR was observed. In atrial fibrillation patients, advanced inter-atrial block is defined as P-wave duration ≥ 120 ms, and biphasic morphology in inferior leads is related to left atrial fibrosis.

CONCLUSION

Myocardial fibrosis, a reliable marker of prognosis in a broad spectrum of cardiovascular diseases, can be easily understood with an easily applicable ECG. However, more data is needed on a specific disease basis to study the association of ECG markers and myocardial fibrosis as depicted by CMR.

ECG Enhancement and R-Peak Detection Based on Window Variability

In ECG applications, the correct recognition of R-peaks is extremely important for detecting abnormalities, such as arrhythmia and ventricular hypertrophy. In this work, a novel ECG enhancement and R-peak detection method based on window variability is presented, and abbreviated as SQRS. Firstly, the ECG signal corrupted by various high or low-frequency noises is denoised by moving-average filtering. Secondly, the window variance transform technique is used to enhance the QRS complex and suppress the other components in the ECG, such as P/T waves and noise. Finally, the signal, converted by window variance transform, is applied to generate the R-peaks candidates, and the decision rules, including amplitude and kurtosis adaptive thresholds, are applied to determine the R-peaks. A special squared window variance transform (SWVT) is proposed to measure the signal variability in a certain time window, and this technique reduces false detection rate caused by the various types of interference presented in ECG signals. For the MIT-BIH arrhythmia database, the sensitivity of R-peak detection can reach 99.6% using the proposed method.

Low lead one ratio predicts clinical outcomes in left bundle branch block

INTRODUCTION

We evaluated the association between a novel electrocardiographic (ECG) marker of late, rightward electrocardiographic forces (termed the lead one ratio [LOR]), and left ventricular ejection fraction (LVEF), myocardial scar, and clinical outcomes in patients with left bundle branch block (LBBB).

METHODS AND RESULTS

LOR was calculated in patients with LBBB from a derivation cohort (n = 240) and receiver operator characteristic curves identified optimal threshold values for predicting myocardial scar and LVEF less than 35%. An independent validation cohort of patients with LBBB (n = 196) was used to test the association of LOR with the myocardial scar, LVEF, and the likelihood of death, heart transplant or left ventricular assist device (LVAD) implantation. The optimal thresholds in the derivation cohort were LOR less than 13.7 for identification of scar (sensitivity 55%, specificity 80%), and LOR less than 12.1 for LVEF less than 35% (sensitivity 49%, specificity 80%). In the validation cohort, LOR less than 13.7 was not associated with scar size or presence (P > 0.05 for both). LOR less than 12.1 was associated with lower LVEF (30 [20-40] versus 40 [25-55]%; P = 0.002) and predicted LVEF less than 35% in univariable (odds ratio [OR], 2.2 [1.2-4.1]; P = 0.01) and multivariable analysis (OR, 2.2 [1.2-4.3]; P = 0.02). LOR less than 12.1 was associated with scar presence when patients with nonischemic cardiomyopathy were excluded (OR = 7.2 [1.5-33.2]; P = 0.002). LOR less than 12.1 had an adjusted hazard ratio of 1.53 ([1.05-2.21]; P = 0.03) for death, transplant or LVAD implantation.

CONCLUSIONS

In conclusion, ECG LOR less than 12.1 predicts reduced-LV systolic function and poorer prognosis in patients with LBBB.

The ability of the electrocardiogram in left bundle branch block to detect myocardial scar determined by cardiovascular magnetic resonance

AIMS

We aimed to improve the electrocardiographic 2009 left bundle branch block (LBBB) Selvester QRS score (2009 LBSS) for scar assessment.

METHODS

We retrospectively identified 325 LBBB patients with available ECG and cardiovascular magnetic resonance imaging (CMR) with late gadolinium enhancement from four centers (142 [44%] with CMR scar). Forty-four semi-automatically measured ECG variables pre-selected based on the 2009 LBSS yielded one multivariable model for scar detection and another for scar quantification.

RESULTS

The 2009 LBSS achieved an area under the curve (AUC) of 0.60 (95% confidence interval 0.54-0.66) for scar detection, and R² = 0.04, p < 0.001, for scar quantification. Multivariable modeling improved scar detection to AUC 0.72 (0.66-0.77) and scar quantification to R² = 0.21, p < 0.001.

CONCLUSIONS

The 2009 LBSS detects and quantifies myocardial scar with poor accuracy. Improved models with extensive comparison of ECG and CMR had modest performance, indicating limited room for improvement of the 2009 LBSS.

Automatically computed ECG algorithm for the quantification of myocardial scar and the prediction of mortality

BACKGROUND

Myocardial scar is associated with adverse cardiac outcomes. The Selvester QRS-score was developed to estimate myocardial scar from the 12-lead ECG, but its manual calculation is difficult. An automatically computed QRS-score would allow identification of patients with myocardial scar and an increased risk of mortality.

OBJECTIVES

To assess the diagnostic and prognostic value of the automatically computed QRS-score.

METHODS

The diagnostic value of the QRS-score computed automatically from a standard digital 12-lead was prospectively assessed in 2742 patients with suspected myocardial ischemia referred for myocardial perfusion imaging (MPI). The prognostic value of the QRS-score was then prospectively tested in 1151 consecutive patients presenting to the emergency department (ED) with suspected acute heart failure (AHF).

RESULTS

Overall, the QRS-score was significantly higher in patients with more extensive myocardial scar: the median QRS-score was 3 (IQR 2-5), 4 (IQR 2-6), and 7 (IQR 4-10) for patients with 0, 5-20 and > 20% myocardial scar as quantified by MPI (p < 0.001 for all pairwise comparisons). A QRS-score ≥ 9 (n = 284, 10%) predicted a large scar defined as > 20% of the LV with a specificity of 91% (95% CI 90-92%). Regarding clinical outcomes in patients presenting to the ED with symptoms suggestive of AHF, mortality after 1 year was 28% in patients with a QRS-score ≥ 3 as opposed to 20% in patients with a QRS-score < 3 (p = 0.001).

CONCLUSIONS

The QRS-score can be computed automatically from the 12-lead ECG for simple, non-invasive and inexpensive detection and quantification of myocardial scar and for the prediction of mortality. TRIAL-REGISTRATION: http://www.clinicaltrials.gov . Identifier, NCT01838148 and NCT01831115.

Reservations about the Selvester QRS score in left bundle branch block - Experience in patients with transcatheter aortic valve implantation

BACKGROUND

The Selvester QRS score (S-score) estimates myocardial scar using electrocardiographic criteria. We evaluated the S-score for left bundle branch block (LBBB).

MATERIAL AND METHODS

Studied were 36 patients who developed persistent LBBB upon transcatheter aortic valve implantation (TAVI, TAVI-LBBB group) and 36 matched patients with persistent narrow QRS (TAVI-nQRS group). Electrocardiograms were recorded before and briefly after TAVI and during ~6months follow-up. S-score was calculated using criteria for hypertrophic (in absence of LBBB) or LBBB hearts.

RESULTS

In TAVI-LBBB patients correlation between S-scores pre-TAVI and post-TAVI was absent (R²=0.023). High S-scores post-TAVI occurred in patients with low pre-TAVI scores. Pre-post TAVI scores correlated weakly in TAVI-nQRS (R²=0.182), indicating a possible influence of ventricular unloading by TAVI. In both groups S-scores at post-TAVI and follow-up compared reasonably (R²=0.389 and R²=0.386), indicating reproducibility in more stable conditions.

CONCLUSION

This study indicates that the use of the LBBB S-score criteria overestimates scar size and that caution is recommended in the use of the score in patients with LBBB.