Electrocardiography scar quantification correlates with scar size of hypertrophic cardiomyopathy seen by multidetector computed tomography

Selvester QRS Score is a Predictor of Mortality in Heart Failure with Preserved Ejection Fraction

BACKGROUND

The Selvester QRS (S-QRS) score on a 12-lead electrocardiogram (ECG) is associated with both the amount of myocardial scar and poor prognosis in myocardial infarction patients. However, its prognostic value in heart failure (HF) with preserved ejection fraction (HFpEF) is unknown.

OBJECTIVE

This study aims to investigate the predictive value of the S-QRS score for mortality in HFpEF.

METHODS

359 patients were retrospectively enrolled in this study. Electrocardiographic, echocardiographic, and laboratory features of the patients were recorded. The simplified S-QRS score was measured and recorded. The mean follow-up time of the patients was 38.1±9.5 months. Statistical significance was set at p < 0.05.

RESULTS

Of 359 patients, 270 were in the survivor group, and 89 were in the deceased group. Age, Hs-CRP, troponin, pro-BNP, left atrial (LA) diameter, LA volume index, QRS duration, Tpe, and S-QRS score were statistically high in the deceased group. In multivariate logistic regression analysis, age, Hs-CRP, NT-proBNP, LA diameter, LA volume index, Tpe, and S-QRS score were shown to be independent risk factors for mortality. In the receiver-operating characteristic (ROC) analysis, the cut-off value of the S-QRS score was 5.5, the sensitivity was 80.8%, and the specificity was 77.2% (AUC:0.880, p:0.00). In Kaplan-Meier analysis, it was found that mortality was higher in the group with S-QRS score ≥ 5.5 than in the group with S-QRS score < 5.5. (Long-rank, p:0.00).

CONCLUSIONS

We think that the S-QRS score can be used as a prognostic indicator of long-term mortality in patients with HFpEF.

Obstructive - Nonobstructive hypertrophic cardiomyopathy: differences and predictors

INTRODUCTION

Hypertrophic cardiomyopathy(HCM) is a genetic cardiomyopathy with a prevalence of 1/500 and causes adverse outcomes, usually due to left ventricular outflow tract obstruction.

AIM

In this study, we aimed to determine the possible differences and predictors of obstructive hypertrophic cardiomyopathy HCM (Obs-HCM) and nonobstructive HCM (Nonobs-HCM) by electrocardiographic (ECG) and echocardiographic (ECHO) evaluations with clinical, demographic, and biochemical characteristics.

METHODS

This study is a subgroup analysis of a multicentre, national, and observational 'LVH-TR study' that included 886 left ventricular hypertrophy(LVH) patients in 22 centres between February 2020 and August 2021. After excluding six patients with atrial fibrillation, pace rhythm, bundle branch blocks, and second, and third-degree atrioventricular(AV) block, 60 HCM patients were included, 23 of whom were obstructive, and 37 were nonobstructive.

RESULTS

Body surface area(BSA) (2.01 ± 0.17, 1.89 ± 0.19; p = .01), ST-segment depression (%82.6, %54.1; p = .02), QT and QTc durations (436.3 ± 58.3, 398.0 ± 65.5; p = .02/470.6 ± 58.7, 432.8 ± 74.7; p = .04), left ventricular mass index(LVMI) (176.4 ± 47.0, 152.7 ± 10.2; p = .004), and systolic anterior motion(SAM) rates (%82.6, %18.9; p < 0.001) were significantly higher in the obstructive HCM compared to nonobstructive HCM. Furthermore, the significance of ST-segment depression, QT duration, LVMI, and SAM continued in the univariate analyses to assess obstruction prediction (all p values < .05).

CONCLUSION

In multivariate and correlation analyses, ST segment depression (rho = 0.29), QT prolongation (rho = 0.34), and SAM (rho = 0.62) are found as predictors for obstruction (all p values < .05). Our study will guide future studies since it has detailed ECG and ECHO comparisons of Obs-HCM and Nonobs-HCM patients over 18 are made.

Prediction of Nonviable Myocardium by ECG Q-Wave Parameters: A 3.0 T Cardiovascular Magnetic Resonance Study

Introduction

The presence of a Q-wave on a 12-lead electrocardiogram (ECG) has been considered a marker of a large myocardial infarction (MI). However, the correlation between the presence of Q-waves and nonviable myocardium is still controversial. The aims of this study were to 1) test QWA, a novel ECG approach, to predict transmural extent and scar volume using a 3.0 Tesla scanner, and 2) assess the accuracy of QWA and transmural extent.

Methods

Consecutive patients with a history of coronary artery disease who came for myocardial viability assessment by CMR were retrospectively enrolled. Q-wave measurements parameters including duration and maximal amplitude were performed from each surface lead. A 3.0 Tesla CMR was performed to assess LGE and viability.

Results

Total of 248 patients were enrolled in the study (with presence (n = 76) and absence of pathologic Q-wave (n = 172)). Overall prevalence of pathologic Q-waves was 27.2% (for LAD infarction patients), 20.0 % (for LCX infarction patients), and 16.8% (for RCA infarction patients). Q-wave area demonstrated high performance for predicting the presence of a nonviable segment in LAD territory (AUC 0.85, 0.77–0.92) and a lower, but still significant performance in LCX (0.63, 0.51–0.74) and RCA territory (0.66, 0.55–0.77). Q-wave area greater than 6 ms mV demonstrated high performance in predicting the presence of myocardium scar larger than 10% (AUC 0.82, 0.76–0.89).

Conclusion

Q-wave area, a novel Q-wave parameter, can predict non-viable myocardial territories and the presence of a significant myocardial scar extension.

Predictive role of Frontal QRS-T angle and Selvester QRS Score in determining angiographic slow flow phenomenon following percutaneous coronary intervention in patients with Non-ST elevation myocardial infarction

AIM

Slow flow (SF) that develops after percutaneous coronary intervention (PCI) is significantly associated with poor prognosis in Non-ST elevation myocardial infarction (Non-STEMI) patients. Increased Selvester QRS score and Frontal QRS-T angle [f(QRS-T)] are related to adverse cardiovascular outcomes. We aimed to investigate the predictive role of the Selvester QRS score and f(QRS-T) for the development of post-PCI SF in patients with Non-STEMI.

METHOD AND RESULTS

In a retrospective study, 210 patients with Non-STEMI were divided into two groups as SF (29) and Non-SF (181) according to their TIMI coronary flow grade. For all patients the Selvester QRS score and f(QRS-T) were calculated from automatic electrocardiography (ECG) reports. The mean age of the study population was 63 (55-75) years and 102 (68.6%) of patients were male. The Selvester QRS score and f(QRS-T) were higher in the SF group than in the Non-SF group [(5[3-8], 3[2-5]); (67° [42°-88°], 39° [24°-59°]), respectively, all p <0.01]. In a logistic regression analysis, the Selvester QRS score (OR = 4,862; 95% (CI) = 1,131-20,904, p =0.03) and f(QRS-T) (OR = 5,489; 95% (CI)= 11,433-21,034, p =0.01) were found independent predictors of post-PCI SF in Non-STEMI patients. Receiver operating characteristic (ROC) analysis was performed to assess the diagnostic values of the Selvester QRS score [86% sensitivity; 44% specificity; cut off 2; (AUC, 0.693)] and f(QRS-T) [62% sensitivity; 73% specificity; cut off 58°; (AUC, 0.778)].

CONCLUSION

The Selvester QRS score and f(QRS-T), both easy-to-calculate ECG parameters, are predictors of post-PCI SF in Non-STEMI patients.

Detecting myocardial scar using electrocardiogram data and deep neural networks

Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischaemic heart disease and can be detected with high diagnostic precision by magnetic resonance imaging. However, magnetic resonance imaging scanners are expensive and of limited availability. It is known that presence of myocardial scar has an impact on the well-established, reasonably low cost, and almost ubiquitously available electrocardiogram. However, this impact is non-specific and often hard to detect by a physician. We present an artificial intelligence based approach - namely a deep learning model - for the prediction of myocardial scar based on an electrocardiogram and additional clinical parameters. The model was trained and evaluated by applying 6-fold cross-validation to a dataset of 12-lead electrocardiogram time series together with clinical parameters. The proposed model for predicting the presence of scar tissue achieved an area under the curve score, sensitivity, specificity, and accuracy of 0.89, 70.0, 84.3, and 78.0%, respectively. This promisingly high diagnostic precision of our electrocardiogram-based deep learning models for myocardial scar detection may support a novel, comprehensible screening method.

Electrocardiography scar quantification correlates with scar size of hypertrophic cardiomyopathy seen by multidetector computed tomography

BACKGROUND

Hypertrophic cardiomyopathy (HCM), a genetically transmitted disease, is the most common genetic cardiovascular disease. Current strategies to stratify risk are expensive and concentrated in wealthy centers. Twelve-lead electrocardiography (ECG) is inexpensive, universally available, and can be readily used for Selvester QRS scoring, which estimates scar size. This study aimed to establish the relation between ECG scar quantification and myocardial fibrosis (extent of myocardial delayed enhancement) in multidetector computed tomography (MDCT).

HYPOTHESIS

There is a significant association between ECG scar quantification and the extent of myocardial delayed enhancement in MDCT.

METHODS

Seventy-five patients with HCM underwent a routine clinical evaluation and echocardiography, 12-lead ECG, and MDCT study. Patients with and without an implantable cardioverter-defibrillator were included.

RESULTS

The estimated Selvester QRS score of myocardial fibrosis was correlated significantly (R = 0.70; P < 0.01) with the quantified MDCT fibrosis. Compared with MDCT, the QRS score had 84.8% sensitivity and 88.8% specificity. Myocardial fibrosis was present in 88% of these patients with HCM (fibrotic mass, 9.87 ±10.8 g) comprising 5.66% ±6.16% of the total myocardial mass seen on the MDCT images. The Selvester QRS score reliably predicted the fibrotic mass in 76% of patients, which estimated 8.44% ±7.39% of the total myocardial mass.

CONCLUSIONS

The Selvester QRS score provides reliable quantification of myocardial fibrosis and was well correlated with MDCT in patients with HCM.