Atrial electrocardiography in obesity and hypertension: Clinical insights from the Polish-Norwegian Study (PONS)

Impact of Obesity on Atrial Electrophysiological Substrate

(1) Background. Obesity is a well-established worldwide recognised risk factor for atrial fibrillation (AF). Prior review papers reported on the associations between obesity and AF development, but not on the relation between obesity and atrial electrophysiology. We therefore conducted a systematic review to describe the current knowledge of the characteristics of the atrial electrophysiological substrate in obese individuals and how they relate to the development of AF. (2) Methods. A search was conducted in Pubmed, Embase, and the Cochrane Library for publications evaluating the impact of obesity on atrial electrophysiology, electrical substrates, and their relation to the development of AF. (3) Results. A systematic literature search retrieved 477 potential publications based on the inclusion criteria; 76 full-text articles were selected for the present systematic review. The literature demonstrated that obesity predisposes to not only a higher AF incidence but also to more extensive atrial electrophysiological abnormalities increasing susceptibility to AF development. (4) Conclusion. Obesity may predispose to an overall increase in atrial electropathology, consisting of an increase in the slowing of the conduction, conduction block, low-voltage areas, and complex fractionated electrograms. To determine the impact of obesity-induced atrial electrical abnormalities on the long-term clinical outcome, further prospective studies are mandatory.

Artificial Intelligence-Enabled Electrocardiography Predicts Left Ventricular Dysfunction and Future Cardiovascular Outcomes: A Retrospective Analysis

BACKGROUND: The ejection fraction (EF) provides critical information about heart failure (HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for cardiac electrophysiological activities that has been used to detect patients with low EF based on a deep learning model (DLM) trained via large amounts of data. However, no studies have widely investigated its clinical impacts. OBJECTIVE: This study developed a DLM to estimate EF via ECG (ECG-EF). We further investigated the relationship between ECG-EF and echo-based EF (ECHO-EF) and explored their contributions to future cardiovascular adverse events. METHODS: There were 57,206 ECGs with corresponding echocardiograms used to train our DLM. We compared a series of training strategies and selected the best DLM. The architecture of the DLM was based on ECG12Net, developed previously. Next, 10,762 ECGs were used for validation, and another 20,629 ECGs were employed to conduct the accuracy test. The changes between ECG-EF and ECHO-EF were evaluated. The primary follow-up adverse events included future ECHO-EF changes and major adverse cardiovascular events (MACEs). RESULTS: The sex-/age-matching strategy-trained DLM achieved the best area under the curve (AUC) of 0.9472 with a sensitivity of 86.9% and specificity of 89.6% in the follow-up cohort, with a correlation of 0.603 and a mean absolute error of 7.436. In patients with accurate prediction (initial difference < 10%), the change traces of ECG-EF and ECHO-EF were more consistent (R-square = 0.351) than in all patients (R-square = 0.115). Patients with lower ECG-EF (≤35%) exhibited a greater risk of cardiovascular (CV) complications, delayed ECHO-EF recovery, and earlier ECHO-EF deterioration than patients with normal ECG-EF (>50%). Importantly, ECG-EF demonstrated an independent impact on MACEs and all CV adverse outcomes, with better prediction of CV outcomes than ECHO-EF. CONCLUSIONS: The ECG-EF could be used to initially screen asymptomatic left ventricular dysfunction (LVD) and it could also independently contribute to the predictions of future CV adverse events. Although further large-scale studies are warranted, DLM-based ECG-EF could serve as a promising diagnostic supportive and management-guided tool for CV disease prediction and the care of patients with LVD.

Neural networks applied to 12-lead electrocardiograms predict body mass index, visceral adiposity and concurrent cardiometabolic ill-health

Background

Obesity is associated with electrophysiological remodeling, which manifests as detectable changes on the surface electrocardiogram (ECG).

Objective

To develop neural networks (NN) to predict body mass index (BMI) from ECGs and test the hypothesis that discrepancies between NN-predicted BMI and measured BMI are indicative of underlying adiposity and/or concurrent cardiometabolic ill-health.

Methods

NN models were developed using 36,856 12-lead resting ECGs from the UK Biobank. Two architectures were developed for continuous and categorical BMI estimation (normal weight [BMI <25 kg/m²] vs overweight/obese [BMI ≥25 kg/m²]). Models for male and female participants were trained and tested separately. For each sex, data were randomly divided into 4 folds, and models were evaluated in a leave-1-fold-out manner.

Results

ECGs were available for 17,807 male and 19,049 female participants (mean ages: 61 ± 7 and 63 ± 8 years; mean BMI 26 ± 5 kg/m² and 27 ± 4 kg/m², respectively). NN models detected overweight/obese individuals with average accuracies of 75% and 73% for male and female subjects, respectively. The magnitudes of difference between NN-predicted BMI and actual BMI were significantly correlated with visceral adipose tissue volumes. Concurrent hypertension, diabetes, dyslipidemia, and/or coronary heart disease explained false-positive classifications (ie, calculated BMI <25 kg/m² misclassified as ≥25 kg/m² by NN model, P < .001).

Conclusion

NN models applied to 12-lead ECGs predict BMI with a reasonable degree of accuracy. Discrepancies between NN-predicted and calculated BMI may be indicative of underlying visceral adiposity and concomitant cardiometabolic perturbation, which could be used to identify individuals at risk of cardiometabolic disease.

The relationship between demographic features, anthropometric parameters, sleep duration, and physical activity with ECG parameters in Fasa Persian cohort study

Backgrounds

Cardiovascular Diseases (CVDs) are the first leading cause of death worldwide. The present study aimed to investigate the relationship between demographics, anthropometrics, sleep duration, physical activity, and ECG parameters in the Fasa Persian cohort study.

Methods

In this cross-sectional study, the basic information of 10,000 participants aged 35–70 years in the Fasa cohort study was used. The data used in this study included demographic data, main Electrocardiogram (ECG) parameters, anthropometric data, sleep duration, and physical activity. Data analysis was performed using t-test, chi-square, and linear regression model.

Results

Based on multivariate linear regression analysis results, increased age was significantly associated with all study parameters. Nevertheless, gender and body mass index showed no significant relationship with SV3 and PR. Wrist circumference, hip circumference and waist circumference significantly increased the mean values of the ECG parameters. However, sleep duration was not significantly associated with the ECG parameters. In addition, hypertension was major comorbidity, which was shown to increase the mean values of the ECG parameters.

Conclusion

Several factors affected the ECG parameters. Thus, to interpret ECGs, in addition to age and gender, anthropometric indices, physical activity, and previous history of comorbidities, such as hypertension and ischemic heart disease, should be taken into consideration.

Electrocardiographic QRS duration is influenced by body mass index and sex

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In a large group of subjects without overt conduction system disease, there was a positive association between increasing BMI and electrocardiographic QRS duration that was independent of other covariates such as sex and age.

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Females had narrower QRS complex than the males at similar age and in the similar BMI category.

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Findings of this research should prompt further studies to explore the underlying mechanisms for these observations and potential reversibility of the conduction abnormality with weight loss

Background

Electrocardiogram (ECG) measured QRS duration has been shown to influence cardiovascular outcomes. However, there is paucity of data on whether ECG QRS duration is influenced by obesity and sex in large populations.

Methods

All ECGs performed by a pathology provider over a 2-year period were included. ECGs with confounding factors and those not in sinus rhythm were excluded from the primary analysis.

Results

Of the 76,220 who met the inclusion criteria, 41,685 (55%) were females. The median age of the study cohort was 61 years (interquartile [IQR] range 48–71 years). The median QRS duration was 86 ms (IQR 80–94 ms). The median BMI was 27.6 kg/m² (IQR 24.2–31.8 kg/m²). When stratified according to the World Health Organization classification of BMI < 18.50 kg/m², 18.50–24.99 kg/m², 25.00–29.99 kg/m², and ≥ 30.00 kg/m², the median QRS durations were 82 ms (IQR 76–88 ms), 86 ms (IQR 80–92 ms), 88 ms (IQR 80–94 ms) and 88 ms (IQR 82–94 ms), respectively (p < 0.001 for linear trend). Median QRS duration for females was 84 ms (IQR 78–88 ms); for males, it was 92 ms (IQR 86–98 ms), p < 0.001. Compared to males, females had narrower QRS complexes at similar age and similar BMI. In multiple linear regression analysis, BMI correlated positively with QRS duration (standardized beta 0.095, p < 0.001) independent of age, sex, and heart rate.

Conclusions

In this large cohort there was a positive association between increasing BMI and QRS duration. Females had narrower QRS duration than males at similar age and similar BMI.

Assessment of Hypertension Using Clinical Electrocardiogram Features: A First-Ever Review

Hypertension affects an estimated 1.4 billion people and is a major cause of morbidity and mortality worldwide. Early diagnosis and intervention can potentially decrease cardiovascular events later in life. However, blood pressure (BP) measurements take time and require training for health care professionals. The measurements are also inconvenient for patients to access, numerous daily variables affect BP values, and only a few BP readings can be collected per session. This leads to an unmet need for an accurate, 24-h continuous, and portable BP measurement system. Electrocardiograms (ECGs) have been considered as an alternative way to measure BP and may meet this need. This review summarizes the literature published from January 1, 2010, to January 1, 2020, on the use of only ECG wave morphology to monitor BP or identify hypertension. From 35 articles analyzed (9 of those with no listed comorbidities and confounders), the P wave, QTc intervals and TpTe intervals may be promising for this purpose. Unfortunately, with the limited number of articles and the variety of participant populations, we are unable to make conclusions about the effectiveness of ECG-only BP monitoring. We provide 13 recommendations for future ECG-only BP monitoring studies and highlight the limited findings in pregnant and pediatric populations. With the advent of convenient and portable ECG signal recording in smart devices and wearables such as watches, understanding how to apply ECG-only findings to identify hypertension early is crucial to improving health outcomes worldwide.

Association of Obesity Phenotypes with Electrocardiographic Markers of Poor Outcomes in the General Population

OBJECTIVE

This study aimed to investigate the association of metabolically healthy obesity (MHO) and other obesity phenotypes with electrocardiographic (ECG) markers to understand the pathophysiological basis of increased cardiovascular disease (CVD) risk associated with these phenotypes.

METHODS

A total of 3,700 participants (58.7 ± 13.6 years, 52% women) without CVD from the third National Health and Nutrition Examination Survey (NHANES III) were included. Logistic regression was used to examine the cross-sectional association between obesity phenotypes (metabolically healthy without obesity [MHNO; reference], metabolically unhealthy without obesity, MHO, and metabolically unhealthy obesity) with ECG markers (PR interval, P-wave duration, QRS duration, and QT interval).

RESULTS

Higher odds of prolonged PR interval, P-wave duration, and QRS duration were observed among all phenotypes compared with MHNO, with the highest in participants with obesity with or without metabolic syndrome. However, for QT interval, the trend of association with obesity phenotypes was as follows, from the strongest to the least strong: metabolically unhealthy obesity, metabolically healthy without obesity, and then MHO, compared with MHNO.

CONCLUSIONS

An association of obesity phenotypes with ECG abnormalities further raises doubt about the concept of MHO as a healthy state. Variations in associations with ECG markers may suggest that metabolic syndrome and obesity have a different relationship with different CVD outcomes and may explain some of the inconsistent CVD estimates for MHO.

Blood pressure-related electrocardiographic findings in healthy young individuals

Purpose: Elevated blood pressure induces electrocardiographic changes and is associated with an increase in cardiovascular disease later in life compared to normal blood pressure levels. The purpose of this study was to evaluate the association between normal to high normal blood pressure values (90-139/50-89 mmHg) and electrocardiographic parameters related to cardiac changes in hypertension in healthy young adults.Methods: Data from 1449 volunteers aged 18-30 years collected at our centre were analyzed. Only subjects considered healthy by a physician after review of collected data with systolic blood pressure values between 90 and 139 mmHg and diastolic blood pressure values between 50 and 89 mmHg were included. Subjects were divided into groups with 10 mmHg systolic blood pressure increment between groups for analysis of electrocardiographic differences. Backward multivariate regression analysis with systolic and diastolic blood pressure as a continuous variable was performed.Results: The mean age was 22.7 ± 3.0 years, 73.7% were male. P-wave area, ventricular activation time, QRS-duration, Sokolow-Lyon voltages, Cornell Product, J-point-T-peak duration corrected for heart rate and maximum T-wave duration were significantly different between systolic blood pressure groups. In the multivariate model with gender, body mass index and cholesterol, ventricular rate (standardized coefficient (SC): +0.182, p < .001), ventricular activation time in lead V6 (SC= +0.065, p = .048), Sokolow-Lyon voltage (SC= +0.135, p < .001), and Cornell product (SC= +0.137, p < .001) were independently associated with systolic blood pressure, while ventricular rate (SC= +0.179, p < .001), P-wave area in lead V1 (SC= +0.079, p = .020), and Cornell product (SC= +0.091, p = .006) were independently associated with diastolic blood pressure.Conclusion: Blood pressure-related electrocardiographic changes were observed incrementally in a healthy young population with blood pressure in the normal range. These changes were an increased ventricular rate, increased atrial surface area, ventricular activation time and increased ventricular hypertrophy indices on a standard 12 lead electrocardiogram.

Obesity and hypertension contribute to prolong QRS complex duration among middle-aged adults

BACKGROUND

Obesity and hypertension are comorbid diseases, which influence cardiac structure, and are associated with increased risk for cardiovascular events. The QRS duration (QRSd) reflects ventricular depolarization, and increased QRSd is associated with poor cardiovascular outcomes. QRS duration may be influenced by obesity and HTN, and reflect the increased risk factor for poor cardiovascular outcomes. The purpose of this analysis was to assess the relations between obesity, hypertension, and the interaction between them on QRSd.

METHODS

In this secondary data analysis, firefighters without documented cardiovascular disease in normal sinus rhythm were included. Twelve-lead 24-hr ECG Holter monitors measured mean QRSd. Body mass index (BMI) and resting blood pressure (BP) were measured and categorized. Univariate linear regression models were produced using BMI, BP, and the interaction between BMI and BP as factors associated with QRSd. Multivariate models adjusting for multiple covariates were also produced.

RESULTS

Seventy-seven firefighters were included and most (89.4%) were overweight or obese. After covariate adjustment, BMI (p = 0.028), BMI categorization (p = 0.020), and the interaction between BMI and systolic BP (p = 0.021) were associated with prolong QRSd.

CONCLUSIONS

Increased BMI and an interaction between BMI and systolic BP were independently associated with prolongation of the QRS complex. Determination of the underlying cardiac structures responsible prolongation of the QRSd is recommended for further research.

Lipidomics, Atrial Conduction, and Body Mass Index

BACKGROUND

Lipids are increasingly involved in cardiovascular risk prediction as potential proarrhythmic influencers. However, knowledge is limited about the specific mechanisms connecting lipid alterations with atrial conduction.

METHODS

To shed light on this issue, we conducted a broad assessment of 151 sphingo- and phospholipids, measured using mass spectrometry, for association with atrial conduction, measured by P wave duration (PWD) from standard electrocardiograms, in the MICROS study (Microisolates in South Tyrol) (n=839). Causal pathways involving lipidomics, body mass index (BMI), and PWD were assessed using 2-sample Mendelian randomization analyses based on published genome-wide association studies of lipidomics (n=4034) and BMI (n=734 481), and genetic association analysis of PWD in 5 population-based studies (n=24 236).

RESULTS

We identified an association with relative phosphatidylcholine 38:3 (%PC 38:3) concentration, which was replicated in the ORCADES (Orkney Complex Disease Study; n=951), with a pooled association across studies of 2.59 (95% CI, 1.3-3.9; P=1.1×10^-4) ms PWD per mol% increase. While being independent of cholesterol, triglycerides, and glucose levels, the %PC 38:3-PWD association was mediated by BMI. Results supported a causal effect of BMI on both PWD ( P=8.3×10^-5) and %PC 38:3 ( P=0.014).

CONCLUSIONS

Increased %PC 38:3 levels are consistently associated with longer PWD, partly because of the confounding effect of BMI. The causal effect of BMI on PWD reinforces evidence of BMI's involvement into atrial electrical activity.

Body mass index related electrocardiographic findings in healthy young individuals with a normal body mass index

INTRODUCTION

An increased body mass index (BMI) (>25 kg/m²) is associated with a wide range of electrocardiographic changes. However, the association between electrocardiographic changes and BMI in healthy young individuals with a normal BMI (18.5-25 kg/m²) is unknown. The aim of this study was to evaluate the association between BMI and electrocardiographic parameters.

METHODS

Data from 1,290 volunteers aged 18 to 30 years collected at our centre were analysed. Only subjects considered healthy by a physician after review of collected data with a normal BMI and in sinus rhythm were included in the analysis. Subjects with a normal BMI (18.5-25 kg/m²) were divided into BMI quartiles analysis and a backward multivariate regression analysis with a normal BMI as a continuous variable was performed.

RESULTS

Mean age was 22.7 ± 3.0 years, mean BMI was 22.0, and 73.4% were male. There were significant differences between the BMI quartiles in terms of maximum P-wave duration, P-wave balance, total P-wave area in lead V1, PR-interval duration, and heart axis. In the multivariate model maximum P-wave duration (standardised coefficient (SC) = +0.112, P < 0.001), P-wave balance in lead V1 (SC = +0.072, P < 0.001), heart axis (SC = -0.164, P < 0.001), and Sokolow-Lyon voltage (SC = -0.097, P < 0.001) were independently associated with BMI.

CONCLUSION

Increased BMI was related with discrete electrocardiographic alterations including an increased P-wave duration, increased P-wave balance, a leftward shift of the heart axis, and decreased Sokolow-Lyon voltage on a standard twelve lead electrocardiogram in healthy young individuals with a normal BMI.

Comprehensive identification of pleiotropic loci for body fat distribution using the NHGRI-EBI Catalog of published genome-wide association studies

We conducted a hypothesis-free cross-trait analysis for waist-to-hip ratio adjusted for body mass index (WHR_adjBMI ) loci derived through genome-wide association studies (GWAS). Summary statistics from published GWAS were used to capture all WHR_adjBMI single-nucleotide polymorphisms (SNPs), and their proxy SNPs were identified. These SNPs were used to extract cross-trait associations between WHR_adjBMI SNPs and other traits through the NHGRI-EBI GWAS Catalog. Pathway analysis was conducted for pleiotropic WHR_adjBMI SNPs. We found 160 WHR_adjBMI SNPs and 3675 proxy SNPs. Cross-trait analysis identified 239 associations, of which 100 were for obesity traits. The remaining 139 associations were filtered down to 101 unique linkage disequilibrium block associations, which were grouped into 13 categories: lipids, red blood cell traits, white blood cell counts, inflammatory markers and autoimmune diseases, type 2 diabetes-related traits, adiponectin, cancers, blood pressure, height, neuropsychiatric disorders, electrocardiography changes, urea measurement, and others. The highest number of cross-trait associations were found for triglycerides (n = 10), high-density lipoprotein cholesterol (n = 9), and reticulocyte counts (n = 8). Pathway analysis for WHR_adjBMI pleiotropic SNPs found immune function pathways as the top canonical pathways. Results from our original methodology indicate a novel genetic association between WHR_adjBMI and reticulocyte counts and highlight the pleiotropy between abdominal obesity, immune pathways, and other traits.