Second statement of the working group on electrocardiographic diagnosis of left ventricular hypertrophy

Electrocardiography versus Echocardiography in Severe Aortic Stenosis with the Consideration of Coexistent Coronary Artery Disease

(1) Background: Coexistent coronary artery disease (CAD) might influence the ability of electrocardiogram (ECG) to identify echocardiographic left ventricular hypertrophy (ECHO-LVH) in patients with aortic stenosis (AS). We aimed to assess the relation between ECG-LVH (by the Sokolov-Lyon or Cornell criteria) and ECHO-LVH considering coexistent CAD. (2) Methods: We retrospectively analyzed the medical records of 74 patients (36 males) with severe AS who were hospitalized in the University Hospital in Cracow from 2021 to 2022. (3) Results: ECHO-LVH was present in 49 (66%) patients, whereas 35 (47.3%) patients had ECG-LVH. There was no difference between the rate of ECG-LVH in patients with vs. without ECHO-LVH. Single-vessel and multi-vessel CAD were diagnosed by invasive coronary angiography in 18% and 11% of patients, respectively. The sensitivity of the classical ECG-LVH criteria with regard to ECHO-LVH was low, reaching at best 41% for the Sokolov-Lyon and Cornell criteria. The results were similar and lacked a pattern when considering patients without significant stenosis, with single- and multi-vessel disease separately. Correlations between the left ventricular mass index and ECG-derived parameters were weak and present solely for the Lewis index (r = 0.31), R wave's amplitude >1.1 mV in aVL (r = 0.36), as well as the Cornell (r = 0.32) and Sokolov-Lyon (r = 0.31) voltage criteria (p < 0.01). The presence, location of stenoses, and CAD extent were not associated with the presence of either ECHO-LVH or ECG-LVH, irrespective of individual ECG-LVH criteria. (4) Conclusions: The sensitivity of classical ECG criteria for echocardiographic LVH in severe AS is low, regardless of coexistent CAD or its angiographic extent.

Improved evaluation of left ventricular hypertrophy using the spatial QRS-T angle by electrocardiography

Electrocardiographic (ECG) signs of left ventricular hypertrophy (LVH) lack sensitivity. The aim was to identify LVH based on an abnormal spatial peaks QRS-T angle, evaluate its diagnostic performance compared to conventional ECG criteria for LVH, and its prognostic performance. This was an observational study with four cohorts with a QRS duration < 120 ms. Based on healthy volunteers (n = 921), an abnormal spatial peaks QRS-T angle was defined as ≥ 40° for females and ≥ 55° for males. In other healthy volunteers (n = 461), the specificity of the QRS-T angle to detect LVH was 96% (females) and 98% (males). In patients with at least moderate LVH by cardiac imaging (n = 225), the QRS-T angle had a higher sensitivity than conventional ECG criteria (93–97% vs 13–56%, p < 0.001 for all). In clinical consecutive patients (n = 783), of those who did not have any LVH, 238/556 (43%) had an abnormal QRS-T angle. There was an association with hospitalization for heart failure or all-cause death in univariable and multivariable analysis. An abnormal QRS-T angle rarely occurred in healthy volunteers, was a mainstay of moderate or greater LVH, was common in clinical patients without LVH but with cardiac co-morbidities, and associated with outcomes.

Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach

The electrocardiogram (ECG) is the most common tool used to predict left ventricular hypertrophy (LVH). However, it is limited by its low accuracy (<60%) and sensitivity (30%). We set forth the hypothesis that the Machine Learning (ML) C5.0 algorithm could optimize the ECG in the prediction of LVH by echocardiography (Echo) while also establishing ECG-LVH phenotypes. We used Echo as the standard diagnostic tool to detect LVH and measured the ECG abnormalities found in Echo-LVH. We included 432 patients (power = 99%). Of these, 202 patients (46.7%) had Echo-LVH and 240 (55.6%) were males. We included a wide range of ventricular masses and Echo-LVH severities which were classified as mild (n = 77, 38.1%), moderate (n = 50, 24.7%) and severe (n = 75, 37.1%). Data was divided into a training/testing set (80%/20%) and we applied logistic regression analysis on the ECG measurements. The logistic regression model with the best ability to identify Echo-LVH was introduced into the C5.0 ML algorithm. We created multiple decision trees and selected the tree with the highest performance. The resultant five-level binary decision tree used only six predictive variables and had an accuracy of 71.4% (95%CI, 65.5-80.2), a sensitivity of 79.6%, specificity of 53%, positive predictive value of 66.6% and a negative predictive value of 69.3%. Internal validation reached a mean accuracy of 71.4% (64.4-78.5). Our results were reproduced in a second validation group and a similar diagnostic accuracy was obtained, 73.3% (95%CI, 65.5-80.2), sensitivity (81.6%), specificity (69.3%), positive predictive value (56.3%) and negative predictive value (88.6%). We calculated the Romhilt-Estes multilevel score and compared it to our model. The accuracy of the Romhilt-Estes system had an accuracy of 61.3% (CI95%, 56.5-65.9), a sensitivity of 23.2% and a specificity of 94.8% with similar results in the external validation group. In conclusion, the C5.0 ML algorithm surpassed the accuracy of current ECG criteria in the detection of Echo-LVH. Our new criteria hinge on ECG abnormalities that identify high-risk patients and provide some insight on electrogenesis in Echo-LVH.

Office and Home Blood Pressures as Determinants of Electrocardiographic Left Ventricular Hypertrophy Among Black Nigerians Compared With White Flemish

BACKGROUND

The association of electrocardiographic left ventricular hypertrophy (ECG-LVH) with blood pressure (BP) in Blacks living in sub-Saharan Africa remains poorly documented.

METHODS

In 225 Black Nigerians and 729 White Flemish, we analyzed QRS voltages and voltage-duration products and 12 criteria diagnostic of ECG-LVH in relation to office BP (mean of 5 consecutive readings) and home BP (duplicate morning and evening readings averaged over 1 week).

RESULTS

In multivariable analyses, QRS voltage and voltage-duration indexes were generally higher in Blacks than Whites. By using any of 12 criteria, ECG-LVH was more prevalent among Black than White men (54.4% vs. 36.0%) with no ethnic difference among women (17.1%). Precordial voltages and voltage-duration products increased with office and home systolic BP (SBP), and increases were up to 3-fold steeper in Blacks. In Blacks vs. Whites, increases in the Sokolow–Lyon voltage associated with a 10-mm Hg higher SBP were 0.18 mV (95% confidence interval [CI], 0.09–0.26) vs. 0.06 mV (0.02–0.09) and 0.17 mV (0.07–0.28) vs. 0.11 mV (CI, 0.07–0.15) for office and home BP, respectively, with a significant ethnic gradient (P < 0.05). The risk of ECG-LVH increased more with office and home BP in Blacks than Whites.

CONCLUSIONS

Associations of ECG voltages and voltage-duration products and risk of ECG-LVH with BP are steeper in Black Nigerians compared with a White reference population. In resource-poor settings of sub-Saharan Africa, the ECG in combination with office and home BP is an essential instrument in risk stratification across the entire BP range.

Diffuse Myocardial Fibrosis Reduces Electrocardiographic Voltage Measures of Left Ventricular Hypertrophy Independent of Left Ventricular Mass

Background

Myocardial fibrosis quantified by myocardial extracellular volume fraction (ECV) and left ventricular mass (LVM) index (LVMI) measured by cardiovascular magnetic resonance might represent independent and opposing contributors to ECG voltage measures of left ventricular hypertrophy (LVH). Diffuse myocardial fibrosis can occur in LVH and interfere with ECG voltage measures. This phenomenon could explain the decreased sensitivity of LVH detectable by ECG, a fundamental diagnostic tool in cardiology.

Methods and Results

We identified 77 patients (median age, 53 [interquartile range, 26–60] years; 49% female) referred for contrast‐enhanced cardiovascular magnetic resonance with ECV measures and 12‐lead ECG. Exclusion criteria included clinical confounders that might influence ECG measures of LVH. We evaluated ECG voltage‐based LVH measures, including Sokolow‐Lyon index, Cornell voltage, 12‐lead voltage, and the vectorcardiogram spatial QRS voltage, with respect to LVMI and ECV. ECV and LVMI were not correlated (R²=0.02; P=0.25). For all voltage‐related parameters, higher LVMI resulted in greater voltage (r=0.33–0.49; P<0.05 for all), whereas increased ECV resulted in lower voltage (r=−0.32 to −0.57; P<0.05 for all). When accounting for body fat, LV end‐diastolic volume, and mass‐to‐volume ratio, both LVMI (β=0.58, P=0.03) and ECV (β=−0.46, P<0.001) were independent predictors of QRS voltage (multivariate adjusted R²=0.39; P<0.001).

Conclusions

Myocardial mass and diffuse myocardial fibrosis have independent and opposing effects upon ECG voltage measures of LVH. Diffuse myocardial fibrosis quantified by ECV can obscure the ECG manifestations of increased LVM. This provides mechanistic insight, which can explain the limited sensitivity of the ECG for detecting increased LVM.

The 4th Report of the Working Group on ECG diagnosis of Left Ventricular Hypertrophy

The 4th Report provides a brief review of publications focused on the electrocardiographic diagnosis of left ventricular hypertrophy published during the period of 2010 to 2016 by the members of the Working Group on ECG diagnosis of Left Ventricular Hypertrophy. The Working Group recommended that ECG research and clinical attention be redirected from the estimation of LVM to the identification of electrical remodeling, to better understanding the sequence of events connecting electrical remodeling to outcomes. The need for a re-definition of terms and for a new paradigm is also stressed.

Electrophysiologic Substrate and Risk of Mortality in Incident Hemodialysis

The single leading cause of mortality on hemodialysis is sudden cardiac death. Whether measures of electrophysiologic substrate independently associate with mortality is unknown. We examined measures of electrophysiologic substrate in a prospective cohort of 571 patients on incident hemodialysis enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease Study. A total of 358 participants completed both baseline 5-minute and 12-lead electrocardiogram recordings on a nondialysis day. Measures of electrophysiologic substrate included ventricular late potentials by the signal-averaged electrocardiogram and spatial mean QRS-T angle measured on the averaged beat recorded within a median of 106 days (interquartile range, 78-151 days) from dialysis initiation. The cohort was 59% men, and 73% were black, with a mean±SD age of 55±13 years. Transthoracic echocardiography revealed a mean±SD ejection fraction of 65.5%±12.0% and a mean±SD left ventricular mass index of 66.6±22.3 g/m^2.7 During 864.6 person-years of follow-up, 77 patients died; 35 died from cardiovascular causes, of which 15 were sudden cardiac deaths. By Cox regression analysis, QRS-T angle ≥75° significantly associated with increased risk of cardiovascular mortality (hazard ratio, 2.99; 95% confidence interval, 1.31 to 6.82) and sudden cardiac death (hazard ratio, 4.52; 95% confidence interval, 1.17 to 17.40) after multivariable adjustment for demographic, cardiovascular, and dialysis factors. Abnormal signal-averaged electrocardiogram measures did not associate with mortality. In conclusion, spatial QRS-T angle but not abnormal signal-averaged electrocardiogram significantly associates with cardiovascular mortality and sudden cardiac death independent of traditional risk factors in patients starting hemodialysis.

Electrocardiographic Versus Echocardiographic Left Ventricular Hypertrophy in Prediction of Congestive Heart Failure in the Elderly

BACKGROUND

Left ventricular hypertrophy (LVH) is an established risk factor for heart failure (HF) and is a component of the Framingham Heart Failure Risk Score (FHFRS). Whether LVH detected by electrocardiogram (ECG-LVH) is equally predictive of HF as LVH detected by echocardiography (echo-LVH) is unclear.

HYPOTHESIS

ECG-LVH and echo-LVH are equally predictive of HF.

METHODS

This analysis included 4543 participants (85% white; 41% male) age ≥ 65 years from the Cardiovascular Health Study who were free of HF at baseline. Incident HF was identified during a median follow-up of 12 years. ECG-LVH was defined by the Cornell criteria. Echo-LVH was defined as left ventricular mass > 95th percentile (male, > 212 g; female, > 175 g). Cox proportional hazard regression was used to examine the association between ECG-LVH and echo-LVH, separately with incident HF. Harrell's concordance C-index was calculated for the FHFRS with inclusion of ECG-LVH and echo-LVH, separately.

RESULTS

At baseline, 168 participants had ECG-LVH and 226 had echo-LVH. A total of 1380 incident HF events occurred during follow-up. Both ECG-LVH and echo-LVH were predictive of incident HF (for ECG-LVH, hazard ratio: 1.39, 95% confidence interval [CI]: 1.08-1.77; for echo-LVH, hazard ratio: 1.52, 95% CI: 1.22-1.89). The ability of the FHFRS to predict HF was similar when ECG-LVH (C-index: 0.772, 95% CI: 0.726-0.815) and echo-LVH (C-index: 0.772, 95% CI: 0.727-0.814) were included into the model separately.

CONCLUSIONS

Both LVH-ECG and echo-LVH are equally predictive of incident HF and can be used interchangeably in HF risk-prediction models.

A wide QRS/T angle in bundle branch blocks is associated with increased risk for coronary heart disease and all-cause mortality in the Atherosclerosis Risk in Communities (ARIC) Study

BACKGROUND

Repolarization abnormality in bundle branch blocks (BBB) is traditionally ignored. This study evaluated the prognostic value of QRS/T angle for mortality in the presence and absence of BBB.

METHODS AND RESULTS

Total 15,408 participants (mean age 54 years, 55.2% women, 26.9% blacks, 2.8% with BBB) were from the Arteriosclerosis Risk in Communities Study. Sex stratified Cox regression models were used to compute hazard ratios (HRs) with 95% confidence intervals (CIs) for coronary heart disease (CHD) and all-cause mortality for wide spatial QRS/T angle with and without BBB including right BBB (RBBB), left BBB (LBBB) and indetermined-type ventricular conduction defect (IVCD) and RBBB combined with left anterior fascicular block. During a median 22-year follow-up, 4767 deaths occurred, 728 of them CHD deaths. Using the No-BBB with QRS/T angle below median value as gender-specific reference groups, the mortality risk increase was significant for both women and men with No-BBB and QRS/T angle above the median value. In the pooled ICVD/LBBB group, the risk for CHD death was increased 15.9-fold in women and 6.04 fold in men, and for all-cause deaths 3.01-fold in women and 1.84-fold in men. However, the mortality risk in isolated RBBB group was only significantly increased in women but not in men.

CONCLUSION

A wide spatial QRS/T angle in BBB is associated with increased risk for CHD and all-cause mortality over and above the predictive value for BBB alone. The risk for women is as high as or higher than that in men.

Determinants of discrepancies in detection and comparison of the prognostic significance of left ventricular hypertrophy by electrocardiogram and cardiac magnetic resonance imaging

Despite the low sensitivity of the electrocardiogram (ECG) in detecting left ventricular hypertrophy (LVH), ECG-LVH is known to be a strong predictor of cardiovascular risk. Understanding reasons for the discrepancies in detection of LVH by ECG versus imaging could help improve the diagnostic ability of ECG. We examined factors associated with false-positive and false-negative ECG-LVH, using cardiac magnetic resonance imaging (MRI) as the gold standard. We also compared the prognostic significance of ECG-LVH and MRI-LVH as predictors of cardiovascular events. This analysis included 4,748 participants (mean age 61.9 years, 53.5% females, 61.7% nonwhites). Logistic regression with stepwise selection was used to identify factors associated with false-positive (n = 208) and false-negative (n = 387), compared with true-positive (n = 208) and true-negative (n = 4,041) ECG-LVH, respectively. A false-negative ECG-LVH status was associated with increased odds of Hispanic race/ethnicity, current smoking, hypertension, increased systolic blood pressure, prolongation of QRS duration, and higher body mass index and with lower odds of increased ejection fraction (model-generalized R(2) = 0.20). A false-positive ECG-LVH status was associated with lower odds of black race, Hispanic race/ethnicity, minor ST-T abnormalities, increased systolic blood pressure, and presence of any major electrocardiographic abnormalities (model-generalized R(2) = 0.29). Both ECG-LVH and MRI-LVH were associated with an increased risk of cardiovascular disease events (hazard ratio 1.51, 95% confidence interval 1.03 to 2.20 and hazard ratio 1.81, 95% confidence interval 1.33 to 2.46, respectively). In conclusion, discrepancy in LVH detection by ECG and MRI can be relatively improved by considering certain participant characteristics. Discrepancy in diagnostic performance, yet agreement on predictive ability, suggests that LVH by ECG and LVH by imaging are likely to be two distinct but somehow related phenotypes.

Left ventricular hypertrophy: The relationship between the electrocardiogram and cardiovascular magnetic resonance imaging

Conventional assessment of left ventricular hypertrophy (LVH) using the electrocardiogram (ECG), for example, by the Sokolow-Lyon, Romhilt-Estes or Cornell criteria, have relied on assessing changes in the amplitude and/or duration of the QRS complex of the ECG to quantify LV mass. ECG measures of LV mass have typically been validated by imaging with echocardiography or cardiovascular magnetic resonance imaging (CMR). However, LVH can be the result of diverse etiologies, and LVH is also characterized by pathological changes in myocardial tissue characteristics on the genetic, molecular, cellular, and tissue level beyond a pure increase in the number of otherwise normal cardiomyocytes. For example, slowed conduction velocity through the myocardium, which can be due to diffuse myocardial fibrosis, has been shown to be an important determinant of conventional ECG LVH criteria regardless of LV mass. Myocardial tissue characterization by CMR has emerged to not only quantify LV mass, but also detect and quantify the extent and severity of focal or diffuse myocardial fibrosis, edema, inflammation, myocarditis, fatty replacement, myocardial disarray, and myocardial deposition of amyloid proteins (amyloidosis), glycolipids (Fabry disease), or iron (siderosis). This can be undertaken using CMR techniques including late gadolinium enhancement (LGE), T1 mapping, T2 mapping, T2* mapping, extracellular volume fraction (ECV) mapping, fat/water-weighted imaging, and diffusion tensor CMR. This review presents an overview of current and emerging concepts regarding the diagnostic possibilities of both ECG and CMR for LVH in an attempt to narrow gaps in our knowledge regarding the ECG diagnosis of LVH.

The role of ECG in the diagnosis of left ventricular hypertrophy

The traditional approach to the ECG diagnosis of left ventricular hypertrophy (LVH) is focused on the best estimation of left ventricular mass (LVM) i.e. finding ECG criteria that agree with LVM as detected by imaging. However, it has been consistently reported that the magnitude of agreement is rather low as reflected in the low sensitivity of ECG criteria. As a result, the majority of cases with true anatomical LVH could be misclassified by using ECG criteria of LVH. Despite this limitation, it has been reported that the ECG criteria for LVH provide independent information on the cardiovascular risk even after adjusting for LVM. Understanding possible reasons for the frequent discrepancy between common ECG LVH criteria and LVH by echo or MRI would help understanding the genesis of ECG changes that occur as a consequence of increased LV mass.

Hypertrophic reprogramming of the left ventricle: translation to the ECG

Hypertrophic growth of the heart occurs in many clinical scenarios, and it confers substantially increased risk of untoward sequelae. Among them, transition to ventricular dilation, wall thinning, contractile dysfunction, and a clinical syndrome of heart failure are paramount. Left ventricular hypertrophy (LVH) is typically diagnosed by either electrocardiography or echocardiography. However, these two means of assessing hypertrophic transformation of the left ventricle can sometimes disagree. At one level, this may not be surprising as the two methodologies are based on entirely divergent signals: electrical potential between two places on the surface of the skin and ultrasound energy reflected from the ventricle itself. Echocardiography is an effective means of assessing ventricular mass, which is a cardinal feature of LVH. Importantly, however, LVH is characterized by a wide range of remodeling events beyond simple increases in muscle mass. Electrocardiographic changes in LVH are reflective of the electrophysiological aspects of hypertrophic transformation. Here, I present an overview of the complex biology of left ventricular hypertrophy with an eye toward enhancing our understanding of its ECG manifestations.

Alterations in the QRS complex in the offspring of patients with metabolic syndrome and diabetes mellitus: early evidence of cardiovascular pathology

OBJECTIVE

This study was undertaken to evaluate the nature and onset of changes in the QRS complex in the offspring of patients with diabetes mellitus (DM) and metabolic syndrome (MetS).

METHODS AND METHODS

A total of 529 subjects, divided into 5 groups, were included in the study: (i) group DM (n = 92), patients with DM; (ii) group MetS (n = 125), patients with MetS; (iii) group O-DM (n = 109), offspring of patients with DM; (iv) group O-MetS (n = 122), offspring of patients with MetS; and (v) group HO (n = 81), offspring of healthy subjects. QRS parameters analyzed included amplitude, maximum QRS spatial vector magnitude, electrical axis (EA), and 3 electrocardiogram (ECG) criteria for left ventricular hypertrophy based on amplitude criteria: Sokolow-Lyon index, Cornell voltage, and Gubner criterion.

RESULTS

Patients with DM and MetS showed a significant leftward shift of the EA when compared with the control group. A modest but significant leftward shift of EA was also observed in both offspring groups. These EA and maximum QRS spatial vector magnitude changes were reflected in the individual leads of the 12-lead ECG. The prevalence of a positive diagnosis by accepted electrocardiographic criteria (ECG left ventricular hypertrophy) was low.

CONCLUSION

Patients with DM and MetS displayed significant changes in QRS complex that suggest depolarization sequence deterioration. Similar changes were observed also in the offspring of patients with DM and MetS, which suggests early subclinical cardiovascular damage. These findings have implications for prevention, early diagnosis, and treatment in the offspring of patients with DM and MetS.