Improvements in ECG accuracy for diagnosis of left ventricular hypertrophy in obesity

Left ventricular hypertrophy: an ECG-based study of prevalence and risk factors in a multiethnic population

BACKGROUND

Left ventricular hypertrophy (LVH) is frequently seen in association with arterial hypertension and indicates poor prognosis. This study aimed to determine the prevalence of LVH and associated factors in a multiethnic population from Mauritius.

METHODS

Population-based health surveys were performed in 2009 and 2015 and included in total 8961 individuals aged 35-75 years with recorded 12-lead ECG. LVH was defined according to three criteria: Sokolow-Lyon, Cornell voltage and Cornell product. Data were collected about health and lifestyle behaviour. Anthropometry and blood pressure were measured. Fasting levels of blood lipids and glucose were determined, oral glucose tolerance test was performed in people without glucose-lowering medications.

RESULTS

The age-standardised prevalence of LVH was 9% (n=875) according to any of the three ECG criteria. Individuals with LVH were older, more likely to have hypertension, diabetes, known cardiovascular disease (CVD) and elevated levels of cholesterol and creatinine. Further, they were more likely to be of African descent (Creole) and have lower educational level. In a multivariable model, Creole (OR (95% CI)) (1.56 (1.33 to 1.83)), low educational level (1.49 (1.28 to 1.75)), hypertension (3.01 (2.55 to 3.56)), known CVD (1.42 (1.11 to 1.83)) and elevated creatinine (1.08 (1.03 to 1.14)) remained associated with LVH. Individuals with non-treated or uncontrolled hypertension had a higher risk for LVH (3.09 (95% CI 2.57 to 3.71) and 4.07 (95% CI 3.29 to 5.05), respectively), than individuals with well controlled hypertension or normotension.

CONCLUSION

LVH occurs more frequently in individuals with hypertension, as well as in individuals with African ancestry and/or low education level.

CoAt-Mixer: Self-attention deep learning framework for left ventricular hypertrophy using electrocardiography

Left ventricular hypertrophy is a significant independent risk factor for all-cause mortality and morbidity, and an accurate diagnosis at an early stage of heart change is clinically significant. Electrocardiography is the most convenient, economical, and non-invasive method for screening in primary care. However, the coincidence rate of the actual left ventricular hypertrophy and diagnostic findings was low, consequently increasing the interest in algorithms using big data and deep learning. We attempted to diagnose left ventricular hypertrophy using big data and deep learning algorithms, and aimed to confirm its diagnostic power according to the differences between males and females. This retrospective study used electrocardiographs obtained at Yonsei University Wonju Severance Christian Hospital, Wonju, Korea, from October 2010 to February 2020. Binary classification was performed for primary screening for left ventricular hypertrophy. Three datasets were used for the experiment: the male, female, and entire dataset. A cutoff for binary classification was defined as the meaningful as a screening test (<132 g/m2 vs. ≥132 g/m2, <109 g/m2 vs. ≥109 g/m2). Six types of input were used for the classification tasks. We attempted to determine whether electrocardiography had predictive power for left ventricular hypertrophy diagnosis. For the entire dataset, the model achieved an area under the receiver operating characteristic (AUROC) curve of 0.836 (95% CI, 0.833-838) with a sensitivity of 78.37% (95% CI, 76.79-79.95). For the male dataset, the AUROC was 0.826 (95% CI, 0.822-830) with a sensitivity of 76.73% (95% CI, 75.14-78.33). For the female dataset, the AUROC was 0.772 (95% CI, 0.769-775) with a sensitivity of 72.90% (95% CI, 70.33-75.46). Our model confirmed that left ventricular hypertrophy can be classified to some extent using electrocardiography, demographics, and electrocardiography features. In particular, a learning environment that considered gender differences was constructed. Consequently, the difference in diagnostic power between men and women was confirmed. Our model will help patients with suspected left ventricular hypertrophy to undergo screening tests at a low cost. In addition, our research and attempts will show the expected effect that gender-consideration approaches can help with various currently proposed diagnostic methods.

Changes in epicardial and visceral adipose tissue depots following bariatric surgery and their effect on cardiac geometry

Introduction

Obesity affects cardiac geometry, causing both eccentric (due to increased cardiac output) and concentric (due to insulin resistance) remodelling. Following bariatric surgery, reversal of both processes should occur. Furthermore, epicardial adipose tissue loss following bariatric surgery may reduce pericardial restraint, allowing further chamber expansion. We investigated these changes in a serial imaging study of adipose depots and cardiac geometry following bariatric surgery.

Methods

62 patients underwent cardiac magnetic resonance (CMR) before and after bariatric surgery, including 36 with short-term (median 212 days), 37 medium-term (median 428 days) and 32 long-term (median 1030 days) follow-up. CMR was used to assess cardiac geometry (left atrial volume (LAV) and left ventricular end-diastolic volume (LVEDV)), LV mass (LVM) and LV eccentricity index (LVei - a marker of pericardial restraint). Abdominal visceral (VAT) and epicardial (EAT) adipose tissue were also measured.

Results

Patients on average had lost 21kg (38.9% excess weight loss, EWL) at 212 days and 36kg (64.7% EWL) at 1030 days following bariatric surgery. Most VAT and EAT loss (43% and 14%, p<0.0001) occurred within the first 212 days, with non-significant reductions thereafter. In the short-term LVM (7.4%), LVEDV (8.6%) and LAV (13%) all decreased (all p<0.0001), with change in cardiac output correlated with LVEDV (r=0.35,p=0.03) and LAV change (r=0.37,p=0.03). Whereas LVM continued to decrease with time (12% decrease relative to baseline at 1030 days, p<0.0001), both LAV and LVEDV had returned to baseline by 1030 days. LV mass:volume ratio (a marker of concentric hypertrophy) reached its nadir at the longest timepoint (p<0.001). At baseline, LVei correlated with baseline EAT (r=0.37,p=0.0040), and decreased significantly from 1.09 at baseline to a low of 1.04 at 428 days (p<0.0001). Furthermore, change in EAT following bariatric surgery correlated with change in LVei (r=0.43,p=0.0007).

Conclusions

Cardiac volumes show a biphasic response to weight loss, initially becoming smaller and then returning to pre-operative sizes by 1030 days. We propose this is due to an initial reversal of eccentric remodelling followed by reversal of concentric remodelling. Furthermore, we provide evidence for a role of EAT contributing to pericardial restraint, with EAT loss improving markers of pericardial restraint.

Clinical applicability and diagnostic performance of electrocardiographic criteria for left ventricular hypertrophy diagnosis in older adults

Recently, a new ECG criterion, the Peguero-Lo Presti (PLP), improved overall accuracy in the diagnosis of left ventricular hypertrophy (LVH)—compared to traditional ECG criteria, but with few patients with advanced age. We analyzed patients with older age and examined which ECG criteria would have better overall performance. A total of 592 patients were included (83.1% with hypertension, mean age of 77.5 years) and the PLP criterion was compared against Cornell voltage (CV), Sokolow-Lyon voltage (SL) and Romhilt-Estes criteria (cutoffs of 4 and 5 points, RE4 and RE5, respectively) using LVH defined by the echocardiogram as the gold standard. The PLP had higher AUC than the CV, RE and SL (respectively, 0.70 vs 0.66 vs 0.64 vs 0.67), increased sensitivity compared with the SL, CV and RE5 (respectively, 51.9% [95% CI 45.4–58.3%] vs 28.2% [95% CI 22.6–34.4%], p < 0.0001; vs 35.3% [95% CI 29.2–41.7%], p < 0.0001; vs 44.4% [95% CI 38.0–50.9%], p = 0.042), highest F1 score (58.3%) and net benefit for most of the 20–60% threshold range in the decision curve analysis. Overall, despite the best diagnostic performance in older patients, the PLP criterion cannot rule out LVH consistently but can potentially be used to guide clinical decision for echocardiogram ordering in low-resource settings.

Electrocardiographic Versus Echocardiographic Left Ventricular Hypertrophy in Severe Aortic Stenosis

Although ECG used to be a traditional method to detect left ventricular hypertrophy (LVH), its importance has decreased over the years and echocardiography has emerged as a routine technique to diagnose LVH. Intriguingly, an independent negative prognostic effect of the "electrical" LVH (i.e., by ECG voltage criteria) beyond echocardiographic LVH was demonstrated both in hypertension and aortic stenosis (AS), the most prevalent heart valve disorder. Our aim was to estimate associations of the ECG-LVH voltage criteria with echocardiographic LVH and indices of AS severity. We retrospectively manually analyzed ECG tracings of 50 patients hospitalized in our center for severe isolated aortic stenosis, including 32 subjects with echocardiographic LVH. The sensitivity of single traditional ECG-LVH criteria in detecting echocardiographic LVH was 9-34% and their respective specificity averaged 78-100%. The ability to predict echocardiographic LVH was higher for S-waves than R-waves (mean area under the receiver operating curve (AUC): 0.62-0.70 vs. 0.58-0.65). Among combinations of R- and S-waves, the discriminating ability was highest for the Cornell voltage (AUC: 0.71) compared to the Sokolow-Lyon, Romhilt and Gubner-Ungerleider voltage (AUC: 0.62-0.68). By multiple regression, peak aortic pressure gradient was positively related to the Sokolow-Lyon (β = 1.7 ± 0.5, p = 0.002) and Romhilt voltage (β = 1.3 ± 0.5, p = 0.01), but not Cornell (0.5 ± 0.3, p = 0.2) or Gubner-Ungerleider voltage (β = 0.0 ± 0.5, p > 0.9), regardless of LV mass index. In conclusion, echocardiographic LVH and stenosis severity appear to have distinct associations with traditional ECG-LVH criteria in AS. A moderate diagnostic superiority of the Cornell voltage criterion with regard to anatomic LVH might result from its unique ability to include depolarization vectors in both the frontal and horizontal plane with consequent lesser sensitivity to the confounding effect of obesity.

Diagnostic Accuracy of the Electrocardiography Criteria for Left Ventricular Hypertrophy (Cornell Voltage Criteria, Sokolow-Lyon Index, Romhilt-Estes, and Peguero-Lo Presti Criteria) Compared to Transthoracic Echocardiography

Objective/Aim: We aimed to evaluate the diagnostic utility of the widely used left ventricular hypertrophy (LVH) electrocardiography (ECG) criteria (Cornell Voltage Criteria [CVC], Sokolow-Lyon Index [SLI], Romhilt-Estes [REC], and Peguero-Lo Presti [PLP] Criteria) compared with the left ventricular mass measured by echocardiography.

Methods: In this prospective diagnostic accuracy study, we screened all consecutive adults (18 to 65 years) who presented to our academic emergency department (ED) with increased blood pressure (≥130/85 mmHg) between January 2016 and January 2017, and we enrolled a convenience sample of 165 patients in our study. The attending emergency physician managed all patients as per their primary complaint. The consulting cardiologist performed a transthoracic echocardiogram (TTE) of the patient and calculated the left ventricular mass (LVM) according to the American Society of Echocardiography (ASE) formula. After completing the patient recruitment phase, researchers evaluated all ECGs and calculated scores for SLI, CVC, REC, and PLP. We used contingency tables to calculate the diagnostic utility metrics of all ECG criteria.

Results: The prevalence of LVH by TTE was 31.5%. CVC, SLI, REC, and PLP criteria correctly identified (true positive rate) abnormal LVM in only 3.9%, 1.9%, 9.6%, and 19.2% of the patients, respectively. CVC, SLI, REC score and PLP criteria performed poorly with extremely low sensitivities (3.9%, 1.9%, 10%, 19.2%) and poor accuracies (67.3%, 64.9%, 57.7%, 69.7%).

Conclusion: ECG voltage criteria's clinical utility in estimating LVM and LVH is low, and it should not be used for this purpose.

T-wave and its association with myocardial fibrosis on cardiovascular magnetic resonance examination

Background

Risk stratification in non‐ischemic myocardial disease poses a challenge. While cardiovascular magnetic resonance (CMR) is a comprehensive tool, the electrocardiogram (ECG) provides quick impactful clinical information. Studying the relationships between CMR and ECG can provide much‐needed risk stratification. We evaluated the electrocardiographic signature of myocardial fibrosis defined as presence of late gadolinium enhancement (LGE) or extracellular volume fraction (ECV) ≥29%.

Methods

We evaluated 240 consecutive patients (51% female, 47.1 ± 16.6 years) referred for a clinical CMR who underwent 12‐lead ECGs within 90 days. ECG parameters studied to determine association with myocardial fibrosis included heart rate, QRS amplitude/duration, T‐wave amplitude, corrected QT and QT peak, and Tpeak‐Tend. Abnormal T‐wave was defined as low T‐wave amplitude ≤200 µV or a negative T wave, both in leads II and V5.

Results

Of the 147 (61.3%) patients with myocardial fibrosis, 67 (28.2%) had ECV ≥ 29%, and 132 (54.6%) had non‐ischemic LGE. An abnormal T‐wave was more prevalent in patients with versus without myocardial fibrosis (66% versus 42%, p < .001). Multivariable analysis demonstrated that abnormal T‐wave (OR 1.95, 95% CI 1.09–3.49, p = .03) was associated with myocardial fibrosis (ECV ≥ 29% or LGE) after adjustment for clinical covariates (age, gender, history of hypertension, and heart failure). Dynamic nomogram for predicting myocardial fibrosis using clinical parameters and the T‐wave was developed: https://normogram.shinyapps.io/CMR_Fibrosis/.

Conclusion

Low T‐wave amplitude ≤ 200 µV or negative T‐waves are independently associated with myocardial fibrosis. Prospective evaluation of T‐wave amplitude may identify patients with a high probability of myocardial fibrosis and guide further indication for CMR.

Prognostic significance of body mass index-adjusted criteria for left ventricular hypertrophy

Electrocardiographic left ventricular hypertrophy (ECG-LVH) is associated with both cardiovascular and all-cause mortality. Obesity attenuates the sensitivity of several ECG-LVH criteria, so body mass index (BMI) adjusted criteria have been developed. However, the prognostic significance of BMI-adjusted ECG-LVH criteria is not known. This analysis included 7812 participants (59.8 ± 13.4 years, 53% women, 50% non-Hispanic-whites) from the Third National Health and Nutrition Examination Survey. The Cornell criteria (R in aVL + S in V3 ≥ 2800 µV in men or ≥2200 µV in women) and Sokolow-Lyon criteria (S in V1 + R in V5 or R in V6 ≥ 3500 µV) criteria were used for LVH. To account for the effects of obesity, the BMI-adjusted Cornell criteria (product of R in aVL + S in V3 and BMI > 60 400 µV kg m^-2 ) and the BMI-adjusted Sokolow-Lyon criteria (add 400 µV if overweight, add 800 µV if obese) were used. Compared to traditional ECG-LVH criteria, more participants met criteria for ECG-LVH with BMI-adjusted Cornell voltage (9.9% vs 2.9%) and BMI-adjusted Sokolow-Lyon (13.1% vs 6.4%) criteria. In multivariable-adjusted Cox proportional hazards models, the BMI-adjusted Sokolow-Lyon criteria performed no better than traditional criteria (HR 1.18, 95% CI 1.06-1.32 for all-cause, HR 1.38, 95% CI 1.17-1.62 for cardiovascular mortality) and the BMI-adjusted Cornell voltage criteria attenuated the association with all-cause (HR 1.16, 95% CI 1.03-1.32) and cardiovascular mortality (HR 1.34, 95% CI 1.13-1.60). Despite potential improvements in the detection of LVH using BMI-adjusted ECG-LVH criteria, adjusting for BMI may result in the loss of prognostic information.

A meta-analytic evaluation of the diagnostic accuracy of the electrocardiographic Peguero-Lo Presti criterion for left ventricular hypertrophy

Although electrocardiography (ECG) is a cost-effective and convenient tool for routine screening of left ventricular hypertrophy (LVH), its performance has been shown to be poor. The Peguero-Lo Presti, a novel voltage criterion, was found to be potentially better than the most commonly used criteria. We conducted a systematic review and meta-analysis of its diagnostic accuracy compared to Cornell and Sokolow-Lyon voltage criteria. Bibliographic databases were searched to identify relevant articles. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic (ROC) curves were performed for comparison. Ten studies reporting data from 5984 individuals were included in the meta-analysis. Peguero-Lo Presti had the highest pooled sensitivity (43.0%, 95% confidence interval [CI]: 30.2-56.9) followed by Cornell (26.1%; 95% CI: 16.9-37.9) and Sokolow Lyon (22.0%; 95% CI: 14.1-32.7). However, Peguero-Lo Presti had the lesser pooled specificity (90.5%; 95% CI: 86.3-93.5) and Cornell the highest (94.9%; 95% CI: 90.3-97.3). The pooled DOR was 6.63 (95% CI: 3.95-11.13), 5.50 (95% CI: 3.64-8.30), and 2.94 (95% CI: 2.20-3.92) for Peguero-Lo Presti, Cornell, and Sokolow-Lyon, respectively. Peguero-Lo Presti had the best accuracy according to summary ROC curves, with an area under the curve of 0.827 compared to 0.715 for Cornell, and 0.623 for Sokolow-Lyon. In conclusion, according to this meta-analysis, Peguero-Lo Presti has a better diagnostic performance than Cornell and Sokolow-Lyon and might be more useful in routine clinical practice as a screening tool for LVH.

The use of cardiovascular magnetic resonance for the assessment of left ventricular hypertrophy

Cardiovascular magnetic resonance (CMR) is a powerful tool to assess and diagnose the cause of left ventricular hypertrophy (LVH). This review provides an overview of the typical CMR findings in the various causes of LVH, focusing mainly on late gadolinium enhancement (LGE) imaging. It will also cover the more novel techniques of T1 mapping, extracellular volume (ECV) fraction estimation and diffusion tensor imaging (DTI) and their role in the imaging assessment of LVH.

Circulating biomarkers in the early detection of hypertensive heart disease: usefulness in the developing world

Although the varying phenotypic spectra of hypertensive heart disease (HHD) can be assessed by electrocardiography (ECG), echocardiography and cardiovascular magnetic resonance (CMR), ECG criteria for left ventricular hypertrophy (LVH) are insensitive, while echocardiography and CMR are expensive, less readily available and often lack requisite expertise. Consequently, the use of circulating biomarkers in the diagnosis and prognostication of HHD beyond the traditional N-terminal pro- b-type natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP) have become an attractive alternative. We carried out a PubMed and Google Scholar databases' search of original articles on circulating biomarkers used in the diagnosis of the different spectrum of HHD over the last 10 years [2005-2015] in humans. Fourteen studies met the inclusion criteria with NT-pro BNP being the most studied circulating biomarker in HHD followed by soluble ST2 (sST2). There is a lack of data on the use of circulating biomarkers in HHD. There is a need to explore further this area of investigative cardiology.

Optimized electrocardiographic criteria for the detection of left ventricular hypertrophy in obesity patients

Background

Despite a generally high specificity, electrocardiographic (ECG) criteria for the detection of left ventricular hypertrophy (LVH) lack sensitivity, particularly in obesity patients.

Objectives

The aim of the study was to evaluate the accuracy of the most commonly used ECG criteria (Cornell voltage and Sokolow‐Lyon index), the recently introduced Peguero‐Lo Presti criteria and the correction of these criteria by body mass index (BMI) to detect LVH in obesity patients and to propose adjusted ECG criteria with optimal accuracy.

Methods

The accuracy of the ECG criteria for the detection of LVH was retrospectively tested in a cohort of obesity patients referred for a transthoracic echocardiogram based on clinical grounds (test cohort, n = 167). Adjusted ECG criteria with optimal sensitivity for the detection of LVH were developed. Subsequently, the value of these criteria was prospectively tested in an obese population without known cardiovascular disease (validation cohort, n = 100).

Results

Established ECG criteria had a poor sensitivity in obesity patients in both the test cohort and the validation cohort. The adjusted criteria showed improved sensitivity, with optimal values for males using the Cornell voltage corrected for BMI, (RaVL+SV3)*BMI ≥700 mm*kg/m²; sensitivity 47% test cohort, 40% validation cohort; for females, the Sokolow‐Lyon index corrected for BMI, (SV1 + RV5/RV6)*BMI ≥885 mm*kg/m²; sensitivity 26% test cohort, 23% validation cohort.

Conclusions

Established ECG criteria for the detection of LVH lack sufficient sensitivity in obesity patients. We propose new criteria for the detection of LVH in obesity patients with improved sensitivity, approaching known sensitivity of the most commonly used ECG criteria in lean subjects.

Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography

Aims 

Although left ventricular hypertrophy (LVH) has a high incidence and clinical importance, the conventional diagnosis criteria for detecting LVH using electrocardiography (ECG) has not been satisfied. We aimed to develop an artificial intelligence (AI) algorithm for detecting LVH.

Methods and results

This retrospective cohort study involved the review of 21 286 patients who were admitted to two hospitals between October 2016 and July 2018 and underwent 12-lead ECG and echocardiography within 4 weeks. The patients in one hospital were divided into a derivation and internal validation dataset, while the patients in the other hospital were included in only an external validation dataset. An AI algorithm based on an ensemble neural network (ENN) combining convolutional and deep neural network was developed using the derivation dataset. And we visualized the ECG area that the AI algorithm used to make the decision. The area under the receiver operating characteristic curve of the AI algorithm based on ENN was 0.880 (95% confidence interval 0.877–0.883) and 0.868 (0.865–0.871) during the internal and external validations. These results significantly outperformed the cardiologist’s clinical assessment with Romhilt-Estes point system and Cornell voltage criteria, Sokolov-Lyon criteria, and interpretation of ECG machine. At the same specificity, the AI algorithm based on ENN achieved 159.9%, 177.7%, and 143.8% higher sensitivities than those of the cardiologist’s assessment, Sokolov-Lyon criteria, and interpretation of ECG machine.

Conclusion 

An AI algorithm based on ENN was highly able to detect LVH and outperformed cardiologists, conventional methods, and other machine learning techniques.

Plasma protein thiolation index (PTI) as a potential biomarker for left ventricular hypertrophy in humans

Background

Left ventricular hypertrophy (LVH) has been associated with oxidative stress, although not with the protein thiolation index (PTI). This study explored the potential use of PTI as a biomarker of oxidative stress in patients with LVH.

Methods

We recruited 70 consecutive patients (n = 35 LVH and n = 35 non-LVH) based on an echocardiography study in our institution (left ventricular mass indexed to body surface area). Plasma levels of both S-thiolated protein and total thiols were measured as biomarkers of oxidative stress by spectrophotometry, and PTI was calculated as the molar ratio between S-thiolated proteins and the total thiol concentration.

Results

Values for plasma S-thiolated proteins were higher in patients with LVH than in the control group (P = 0.01). There were no differences in total thiols between the LVH group and the control group. Finally, PTI was higher in patients with LVH than in the control group (P = 0.001). The area under the ROC curve was 0.75 (95% CI, 0.63–0.86; P<0.001), sensitivity was 70.6%, and specificity was 68.6%, thus suggesting that PTI could be used to screen for LVH. A multivariable logistic regression model showed a positive association (P = 0.02) between PTI and LVH (OR = 1.24 [95% CI, 1.03–1.49]) independently of gender (OR = 3.39 [95% CI, 0.60–18.91]), age (OR = 1.03 [95% CI, 0.96–1.10]), smoking (OR = 5.15 [95% CI, 0.51–51.44]), glucose (OR = 0.99 [95% CI, 0.97–1.01]), systolic arterial pressure (OR = 1.10 [CI 1.03–1.17]), diastolic arterial pressure (OR = 0.94 [CI 0.87–1.02]), dyslipidemia (OR = 1.46 [95% CI, 0.25–8.55]), estimated glomerular filtration rate (OR = 0.98 [95% CI, 0.96–1.01]), body mass index (OR = 1.03 [95% CI, 0.90–1.10]), and valvular and/or coronary disease (OR = 5.27 [95% CI, 1.02–27.21]).

Conclusions

The present study suggests that PTI could be a new biomarker of oxidative stress in patients with LVH.

Electrocardiographic criteria for left ventricular hypertrophy in aortic valve stenosis: Correlation with echocardiographic parameters

BACKGROUND

Aortic valve stenosis (AS) generates a chronic pressure overload that induces left ventricular hypertrophy (LVH). The aim of this study was to assess the prevalence of the electrocardiographic criteria for LVH in patients with clinically significant AS and to evaluate the relationship between the ECG criteria for LVH and echocardiographic parameters.

METHODS

The clinical data of 95 patients with moderate to severe AS were retrospectively analyzed. Eight ECG criteria for LVH were used and compared to the results of transthoracic echocardiography (TTE).

RESULTS

In 59% of patients, at least one of the ECG criteria for LVH was found. These patients had a greater LVMI (142.1 ± 35.6 vs. 124.1 ± 22.5 g/m² , p = 0.01) and peak aortic jet velocity (4.2 ± 0.8 vs. 3.8 ± 0.9 m/s, p = 0.01) along with smaller aortic valve area (0.72 ± 0.28 vs. 0.86 ± 0.22 cm² , p = 0.02) compared to patients with a negative ECG for LVH. The ECG parameters had a low sensitivity (6%-36.9%) with a specificity of up to 100%. The Cornell Voltage criteria had the best sensitivity with a specificity of 63.6% and the highest correlation with the LVMI (r = 0.38, p < 0.001). All of the ECG parameters correlated positively with the peak aortic jet velocity as well as with the mean aortic gradient.

CONCLUSION

The electrocardiographic criteria for LVH in patients with moderate or severe AS have a poor sensitivity in identifying LVH confirmed by TTE. The values of the selected ECG criteria for LVH correlate weakly with both the TTE indices of LVH and the markers of AS severity.

A Fortified Method to Screen and Detect Left Ventricular Hypertrophy in Asymptomatic Hypertensive Adults: A Korean Retrospective, Cross-Sectional Study

Purpose

Left ventricular (LV) mass is determined by the wall thickness and diameter. LV hypertrophy (LVH), the increase in LV mass, is usually screened with electrocardiography but is often insensitive. We tried to fortify the rule to detect LVH using cardiothoracic ratio (CTR) in chest X-ray and well-known risk factors besides electrocardiography.

Materials and Methods

This retrospective cross-sectional study included asymptomatic hypertensive individuals aged ≥40 y who underwent voluntary checkups including echocardiography. Independent variables to explain LVH (LV mass index>115 g/m² for men and >95 g/m² for women calculated on echocardiography) were chosen among Sokolow-Lyon voltage amplitude (SLVA), CTR and cardiovascular risk factors by multiple logistic regression analysis. The diagnostic rule to detect LVH was made by summing up the rounded-off odds ratio of each independent variable and was validated using bootstrapping method.

Results

Among the 789 cases enrolled (202 females (25.6%), mean age 59.6±8.8 y), 168 (21.3%) had LVH. The diagnostic rule summed female, age≥65 y, BMI≥25 kg/m², SLVA≥35 mm, and CTR≥0.50 (scoring 1 per each). Its c-statistics was 0.700 (95% CI: 0.653, 0.747), significantly higher (p<0.001) than that of SLVA≥35 mm, 0.522 (95% CI: 0.472, 0.572). The sensitivity and specificity of the model were 61.9% and 72.1% for score≥2 and 30.4% and 92.9% for score≥3. The SLVA≥35 mm criteria showed sensitivity of 12.5% and specificity of 91.9%.

Conclusions

The rule to sum up the number of the risk factors of female, age≥65 y, BMI≥25 kg/m², SLVA≥35 mm, and CTR≥0.50 may be a better diagnostic tool for screening LVH, than the electrocardiography-only criteria, at the score≥2.

A different effect of obesity on ECG in premenopausal and postmenopausal women

Both obesity and menopause are significant cardiovascular risk factors. In postmenopausal women the protective effect of estrogens is reduced and menopause is frequently associated with occurrence of other significant cardiovascular factors including obesity. This study was focused on evaluating the effect of obesity on the QRS complex in pre- and postmenopausal women. We present results of analysis of 199 electrocardiograms of pre- and postmenopausal women analyzed in relation to the body mass index within normal limits (BMI 20 to 24.9 kg/m²) and obesity (BMI > 30 kg/m²), respectively. Obesity in premenopausal women and menopause significantly affected both the electrical axis (EA) and maximum QRS spatial vector magnitude (QRSmax). The highest QRSmax and electrical axis values were observed in premenopausal lean women, and they were significantly higher as than in the premenopausal obese women, postmenopausal lean and obese women (QRSmax: 1.66 ± 0.4 mV, 1.17 ± 0.35 mV, 1.4 ± 0.46 mV, and 1.35 ± 0.39 mV, resp.). (EA: 56.4 ± 18.0°, 38.22 ± 18.38°, 45.82 ± 18.63°, and 36.75 ± 17.51°). The differences between obese premenopausal women, lean and obese postmenopausal women were not statistically significant. These differences were reflected in 12-lead ECG amplitude. The presence of additional cardiovascular risk factors did not affect the ECG parameters. Obesity significantly affected QRS complex in premenopausal women. This effect was comparable with the effect of menopause. Because all QRS complex changes were within normal limits, these results suggest that ECG evaluation in women should go beyond traditional diagnostic categories and consider the relationship between ECG changes and two cardiovascular risk factors - obesity and menopause.

Registry report of the prevalence of ECG abnormalities and their relation to patient characteristics in an asymptomatic population

BACKGROUND

Cardiovascular disease is the leading cause of morbidity and mortality in developed countries. Many patients do not experience symptoms before a first major cardiovascular event. Resting electrocardiogram (ECG) may help identify asymptomatic individuals with a high risk of cardiovascular disease.

OBJECTIVE

We sought to determine the prevalence of ECG abnormalities in an apparently symptom-free adult population within a prospective registry.

METHODS

The registry consisted of 4739 consecutive apparently healthy individuals [age 62.8 ± 6.2 (SD) years; 54% female], referred by their General Practitioners between 2009 and 2013. Patient demographics, and clinical data were obtained, alongside blood tests and a resting ECG.

RESULTS

ECG abnormalities were present in 1509 (31.8%) subjects and were commoner with increasing age (F = 0.161, p = 0.01), systolic (F = 0.134, p = 0.01) and diastolic (F = 0.44, p = 0.01) blood pressure and waist circumference (F = 0.53, p = 0.01). Left ventricular hypertrophy (LVH) was the most common abnormality (n = 281) and was positively associated with systolic (F = 0.12, p = 0.01) and diastolic blood pressure (F = 0.99, p = 0.01) and male gender (X2 = 60.5, p < 0.01). All ECG abnormalities (except for LVH) were associated with an increasing age, while right bundle branch block (F = 0.041, p = 0.01) and atrial fibrillation (n = 29; F = 0.036, p = 0.05) were associated with the presence of diabetes mellitus (n = 211). Only left bundle branch block (n = 50) was associated with angina (F = 0.05, p = 0.01).

CONCLUSIONS

Unrecognized cardiac abnormalities are common in middle-aged men and women with no overt symptoms. ECG offers the potential to identify these abnormalities and provide earlier intervention and treatment, and possibly improve cardiovascular outcome.

Comparison of Left Ventricular Hypertrophy by Electrocardiography and Echocardiography in Children Using Analytics Tool

Left ventricular hypertrophy (LVH) is a common finding on pediatric electrocardiography (ECG) leading to many referrals for echocardiography (echo). This study utilizes a novel analytics tool that combines ECG and echo databases to evaluate ECG as a screening tool for LVH. SQL Server 2012 data warehouse incorporated ECG and echo databases for all patients from a single institution from 2006 to 2016. Customized queries identified patients 0-18 years old with LVH on ECG and an echo performed within 24 h. Using data visualization (Tableau) and analytic (Stata 14) software, ECG and echo findings were compared. Of 437,699 encounters, 4637 met inclusion criteria. ECG had high sensitivity (≥ 90%) but poor specificity (43%), and low positive predictive value (< 20%) for echo abnormalities. ECG performed only 11-22% better than chance (AROC = 0.50). 83% of subjects with LVH on ECG had normal left ventricle (LV) structure and size on echo. African-Americans with LVH were least likely to have an abnormal echo. There was a low correlation between V₆R on ECG and echo-derived Z score of left ventricle diastolic diameter (r = 0.14) and LV mass index (r = 0.24). The data analytics client was able to mine a database of ECG and echo reports, comparing LVH by ECG and LV measurements and qualitative findings by echo, identifying an abnormal LV by echo in only 17% of cases with LVH on ECG. This novel tool is useful for rapid data mining for both clinical and research endeavors.

Peguero Electrocardiographic Left Ventricular Hypertrophy Criteria and Risk of Mortality

Background: Peguero electrocardiographic left ventricular hypertrophy (ECG-LVH) criteria are newly developed criteria that have shown better diagnostic performance than the traditional Cornell-voltage and Sokolow-Lyon criteria. However, prediction of poor outcomes rather than detection of increased left ventricular mass is becoming the primary use for ECG-LVH criteria which requires investigating any new ECG-LVH criteria in terms of prediction.

Aims: To examine the prognostic significance of the newly developed Peguero ECG-LVH criteria.

Methods: We compared the prognostic significance of Peguero ECG-LVH with Cornell-voltage and Sokolow-Lyon ECG-LVH criteria in 7,825 participants (age 59.8 ± 13.4 years; 52.7% women) from the third National Health and Nutrition Examination Survey who were free of major intraventricular conduction defects. ECG-LVH criteria were derived from digital ECG tracings processed at a central core laboratory.

Results: At baseline, ECG-LVH was detected in 11.8% by Peguero; in 4.3% by Cornell voltage and in 6.4% by Sokolow-Lyon. During a median follow up of 13.8 years, 2,796 all-cause mortality events occurred. In multivariable models adjusted for demographics and cardiovascular risk factors, presence of Peguero ECG-LVH was associated with increased risk of all-cause mortality [HR (95% CI): 1.29 (1.16, 1.44)]. This association was not significantly different from the associations of Cornell voltage-LVH or Sokolow-Lyon LVH with all-cause mortality [HR (95%CI): 1.32 (1.12, 1.55) and 1.24 (1.07, 1.43), respectively; p-values for comparisons of these HRs with the HR of Peguero ECG-LVH 0.817 and 0.667, respectively]. Similar patterns of associations were observed with cardiovascular, ischemic heart disease and heart failure mortalities.

Conclusion: Peguero ECG-LVH is predictive of increased risk of death similar to the traditional ECG-LVH criteria.

Causal Pathways from Blood Pressure to Larger Qrs Amplitudes a Mendelian Randomization Study

Abnormal QRS duration and amplitudes on the electrocardiogram are indicative of cardiac pathology and are associated with adverse outcomes. The causal nature of these associations remains uncertain and could be due to QRS abnormalities being a symptom of cardiac damage rather than a factor on the causal pathway. By performing Mendelian randomization (MR) analyses using summary statistics of genome wide association study consortia with sample sizes between 20,687 and 339,224 individuals, we aimed to determine which cardiovascular risk factors causally lead to changes in QRS duration and amplitude (Sokolow-Lyon, Cornell and 12-leadsum products). Additionally, we aimed to determine whether QRS traits have a causal relationship with mortality and longevity. We performed inverse-variance weighted MR as main analyses and MR-Egger regression and weighted median estimation as sensitivity analyses. We found evidence for a causal relationship between higher blood pressure and larger QRS amplitudes (systolic blood pressure on Cornell: 55SNPs, causal effect estimate per 1 mmHg = 9.77 millimeters·milliseconds (SE = 1.38,P = 1.20 × 10⁻¹²) and diastolic blood pressure on Cornell: 57SNPs, causal effect estimate per 1 mmHg = 14.89 millimeters·milliseconds (SE = 1.82,P = 3.08 × 10⁻¹⁶), but not QRS duration. Genetically predicted QRS traits were not associated with longevity, suggesting a more prominent role of acquired factors in explaining the well-known link between QRS abnormalities and outcome.