ECG Measures Research Articles

The added value of deep learning to submaximal exercise electrocardiogram for the 10-year prediction of major adverse cardiovascular and cerebrovascular events

Abstract Background The added value of exercise ECG data to traditional risk factors in predicting cardiovascular events remains unclear. Deep learning of ECG signals has demonstrated state-of-the-art performance in detecting subtle abnormalities indicative of cardiovascular disease. We investigated whether deep learning analysis of exercise ECGs could improve the prediction of major cardiovascular and cerebrovascular events (MACCE) with respect to established risk models in a large population-based cohort. Purpose To assess the added value of submaximal exercise ECG measurements to established cardiovascular risk prediction models. Methods We obtained ECG recordings from 41,076 UK Biobank participants without cardiovascular disease (CVD) who underwent a submaximal exercise ECG test. We obtained ECG recordings from 41,076 UK Biobank participants without cardiovascular disease (CVD) who underwent a submaximal exercise ECG test. We created two deep neural network ECG risk scores: one derived from conventional ECG parameters, measured at rest, peak exercise and late-stage recovery, and another based on the complete ECG (Q-ECG). We assessed the added value of conventional ECG parameters and Q-ECG risk scores to the UK's current prediction algorithm (QRISK3). We estimate the association between ECG parameters and MACCE, using Cox Proportional hazard models, following adjustment for traditional risk factors. All models were internally validated via 5-fold cross-validation and 1000 bootstrap iterations. Predictive performance was evaluated using Harrel's C-index, Net Reclassification Index (NRI) and net benefit. Findings: Incident MACCE was reported in 4,082 (9.9%) individuals in the study population and 3,463(9.7%) individuals with valid ECG parameters over a median follow-up period of 12.5 years. We found combined conventional ECG and Q-ECG scores were independently associated with MACCE, following adjustment for multiple testing: adjusted hazard ratio [HZ] = 1.76 (95% CI:1.63-1.91); HZ = 1.14 (95% CI:1.10-1.18), respectively, per standard deviation increase. Both conventional ECG parameters and Q-ECG were predictive of MACCE, independent of clinical risk factors, C-index = 0.64 (95%CI 0.63-0.65); net benefit = 0.09(95% CI 0.07 - 0.11) and C-index = 0.56 (95% CI 0.55-0.57); net benefit = 0.07(95% CI 0.05 - 0.09). ECG measurement's modestly improved model discrimination over the bassline QRISK3 risk score when combined with QRISK3 risk factors for conventional markers and Q-ECG score, respectively; ΔC-index 0.03 (95% CI: 0.02 – 0.04) and ΔC-index 0.03 (95% CI: 0.02 – 0.03); However, we observed no significant improvements in classification at the current recommended threshold of 10%. Conclusion In individuals without a history of prior cardiovascular disease, ECG measures independently predict the risk of MACCE. When combined with QRISK3, neural-network-derived ECG risk scores marginally improve cardiovascular risk prediction over QRISK3.

ECG changes following balloon pulmonary angioplasty in patients with chronic thromboembolic pulmonary hypertension: a retrospective study

PurposeThis research evaluates the effect of balloon pulmonary angioplasty (BPA) on cardiac electrophysiological changes in patients with chronic thromboembolic pulmonary hypertension (CTEPH).MethodsInvolving a retrospective analysis of 39 CTEPH patients (average age 61 ± 11), who had at least two BPAs and paired ECGs pre- and post-surgery, we examined changes in ECG indicators of right ventricular hypertrophy and their correlation with hemodynamic results.Results BPA yielded marked improvements in cardiac function and hemodynamics. ECG parameters, specifically the Lewis criteria and Butler-Leggett score, correlated strongly with hemodynamics and were predictive of a mean pulmonary arterial pressure (mPAP) ≥ 35mmHg. Notably, QRS complex axis normalization was observed in 25 patients, with 14 fully normalizing (range − 30° to + 90°). The qR pattern in V1 vanished in 9 cases, and 75% of the patients in qR pattern in V1 group had QRS complex electrical axis completely returned to normal range. The qR V1 group had higher mPAP and pulmonary vascular resistance (PVR), and lower cardiac output and index compared to the non-qR V1 group, alongside a higher Butler-Leggett score.ConclusionsBPA enhances cardiac function and hemodynamics in CTEPH patients, with certain ECG measures such as Lewis criteria and Butler-Leggett score reflecting the severity of hemodynamic impairment. The reversal of QRS axis deviation and the disappearance of the qR pattern in lead V1 may serve as valuable indicators for assessing post-BPA satisfaction in CTEPH patients.

Electrocardiographic predictors of haemodynamic benefit from biventricular pacing: the role of atrioventricular timing measures

Abstract Background Patients with heart failure (HF) and left bundle branch block (LBBB) are selected for biventricular pacing (BVP) cardiac resynchronisation therapy (CRT) based on their 12-lead ECG QRS complex duration (QRSd). This is due to the long-held belief that BVP delivers its beneficial effects almost exclusively by reducing ventricular dyssynchrony. Recent work (1) suggests that atrioventricular delay (AVD) shortening is another key mechanism of benefit and, therefore, that atrioventricular timing may be an important CRT substrate. The ideal 12-lead ECG measure to facilitate patient selection that yields benefits from this mechanism is yet to be elucidated. Purpose We set out to establish whether incorporating a measure of AV delay provides additional benefit over and above using QRSd when using the 12-lead ECG to select patients who are likely to obtain haemodynamic benefit from BVP. Methods We identified patients in sinus rhythm with HF and LBBB meeting clinical criteria for CRT who had undergone implantation of a BVP device and had also undergone high-precision haemodynamic assessment of BVP. This is where pacing is alternated between atrium-only pacing (AAI) and DDD pacing using BVP multiple times for each of a full range of AVDs during continuous beat-by-beat blood pressure recording to determine the peak haemodynamic benefit of BVP in each patient. We extracted potentially predictive, pre-specified intrinsic (unpaced) ECG features that incorporated left or right AV timing to varying extents: PR interval (PR), end-of-p-wave-to-R-wave-peak-time-V6 (Pend-RWPTV6), start-of-p-wave-to-end-of-QRS (P-QRSend) as well as conventional QRSd. Pearson's test assessed the unadjusted correlation between intrinsic ECG intervals and BVP haemodynamic benefit(∆SBP). A multiparametric regression analysis model was constructed to account for confounders and interactions between different ECG features. Results 53 eligible patients were identified. 39 were male (73.6%), 31 had non-ischaemic aetiology (58.5%), mean LVEF was 27.6% ± SD 4.79 and mean LVEDD was 57.9± SD 9.4mm. Unadjusted correlations between intrinsic ECG features were not strong but favoured P-QRSend as a potentially predictive feature; R2 values: PR 0.28 (p=0.04), Pend-RWPTV6 0.19 (p=0.18), P-QRSend 0.27 (p=0.054), QRSd 0.045 (p=0.75). However, the multiparametric model revealed that utilising both PR interval and Pend-RWPTV6 in a predictive model showed better-adjusted correlation with BVP haemodynamic benefit (R2 0.54, p=0.04). Conclusion ECG features that incorporate either right (PR interval) or left (Pend-RWPTV6) AVD or both (P-QRSend) are superior to QRSd for predicting haemodynamic benefit from BVP in patients with HF and LBBB. This further reinforces the role of AVD shortening as a mechanism of benefit of BVP and suggests that selecting patients on the basis of AV timing may yield more overall benefit from CRT delivered by BVP or potentially conduction system pacing.ECG interval measurementCorrelation Graphs

ECG waveform generation from radar signals: A deep learning perspective

Cardiovascular diagnostics relies heavily on the ECG (ECG), which reveals significant information about heart rhythm and function. Despite their significance, traditional ECG measures employing electrodes have limitations. As a result of extended electrode attachments, patients may experience skin irritation or pain, and motion artifacts may interfere with signal accuracy. Additionally, ECG monitoring usually requires highly trained professionals and specialized equipment, which increases the treatment's complexity and cost. In critical care scenarios, such as continuous monitoring of hospitalized patients, wearable sensors for collecting ECG data may be difficult to use. Although there are issues with ECG, it remains a valuable tool for diagnosing and monitoring cardiac disorders due to its non-invasive nature and the detailed information it provides about the heart. The goal of this study is to present an innovative method for generating continuous ECG waveforms from non-contact radar data by using Deep Learning. The method can eliminate the need for invasive or wearable biosensors and expensive equipment to collect ECGs. In this paper, we propose the MultiResLinkNet, a one-dimensional convolutional neural network (1D CNN) model for generating ECG signals from radar waveforms. With the help of a publicly accessible radar benchmark dataset, an end-to-end DL architecture is trained and assessed. There are six ports of raw radar data in this dataset, along with ground truth physiological signals collected from 30 participants in five distinct scenarios: Resting, Valsalva, Apnea, Tilt-up, and Tilt-down. By using strong temporal and spectral measurements, we assessed our proposed framework's ability to convert ECG data from Radar signals in three distinct scenarios, namely Resting, Valsalva, and Apnea (RVA). ECG segmentation performed better by MultiResLinkNet than by state-of-the-art networks in both combined and individual cases. As a result of the simulations, the resting, valsalva, and RVA scenarios showed the highest average temporal values, respectively: 66.09523 ± 19.33, 60.13625 ± 21.92, and 61.86265 ± 21.37. In addition, it exhibited the highest spectral correlation values (82.4388 ± 18.42 (Resting), 77.05186 ± 23.26 (Valsalva), 74.65785 ± 23.17 (Apnea), and 79.96201 ± 20.82 (RVA)), along with minimal temporal and spectral errors in almost every case. The qualitative evaluation revealed strong similarities between generated and actual ECG waveforms. As a result of our method of forecasting ECG patterns from remote radar data, we can monitor high-risk patients, especially those undergoing surgery.

Limited Relationship Between Echocardiographic Measures and Electrocardiographic Markers of Left Ventricular Size in Healthy Children.

Pediatric ECG standards have been defined without echocardiographic confirmation of normal anatomy. The Pediatric Heart Network Normal Echocardiogram Z-score Project provides a racially diverse group of healthy children with normal echocardiograms. We hypothesized that ECG and echocardiographic measures of left ventricular (LV) dimensions are sufficiently correlated in healthy children to imply a clinically meaningful relationship. This was asecondary analysis of a previously described cohort including 2170 digital ECGs. The relationship between 6 ECG measures associated with LV size were analyzed with LV Mass (LVMass-z) and left ventricular end-diastolic volume (LVEDV-z) along with 11 additional parameters. Pearson or Spearman correlations were calculated for the 78 ECG-echocardiographic pairs with regression analyses assessing the variance in ECG measures explained by variation in LV dimensions and demographic variables. ECG/echocardiographic measurement correlations were significant and concordant in 41/78 (53%), though many were significant and discordant (13/78). Of the 6 ECG parameters, 5 correlated in the clinically predicted direction for LV Mass-z and LVEDV-z. Even when statistically significant, correlations were weak (0.05-0.24). R2 was higher for demographic variables than for echocardiographic measures or body surface area in all pairs, but remained weak (R2 ≤ 0.17). In a large cohort of healthy children, there was a positive association between echocardiographic measures of LV size and ECG measures of LVH. These correlations were weak and dependent on factors other than echocardiographic or patient derived variables. Thus, our data support deemphasizing the use of solitary, traditional measurement-based ECG markers traditionally thought to be characteristic of LVH as standalone indications for further cardiac evaluation of LVH in children and adolescents.

Reduction in atrial and ventricular electrical heterogeneity following pulmonary vein isolation in patients with atrial fibrillation

Pulmonary vein isolation (PVI) modulates the intrinsic cardiac autonomic nervous system and reduces atrial fibrillation (AF) recurrence. In this retrospective analysis, we investigated the impact of PVI on ECG interlead P-wave, R-wave, and T-wave heterogeneity (PWH, RWH, TWH) in 45 patients in sinus rhythm undergoing clinically indicated PVI for AF. We measured PWH as a marker of atrial electrical dispersion and AF susceptibility and RWH and TWH as markers of ventricular arrhythmia risk along with standard ECG measures. PVI acutely (16 ± 8.9h) reduced PWH by 20.7% (from 31 ± 1.9 to 25 ± 1.6µV, p < 0.001) and TWH by 27% (from 111 ± 7.8 to 81 ± 6.5µV, p < 0.001). RWH was unchanged after PVI (p = 0.068). In a subgroup of 20 patients with longer follow-up (mean = 47 ± 3.7days after PVI), PWH remained low (25 ± 1.7µV, p = 0.01), but TWH partially returned to the pre-ablation level (to 93 ± 10.2, p = 0.16). In three individuals with early recurrence of atrial arrhythmia in the first 3months after ablation, PWH increased acutely by 8.5%, while in patients without early recurrence, PWH decreased acutely by 22.3% (p = 0.048). PWH was superior to other contemporary P-wave metrics including P-wave axis, dispersion, and duration in predicting early AF recurrence. The rapid time course of decreased PWH and TWH after PVI suggests a beneficial influence likely mediated via ablation of the intrinsic cardiac nervous system. Acute responses of PWH and TWH to PVI suggest a favorable dual effect on atrial and ventricular electrical stability and could be used to track individual patients' electrical heterogeneity profile.

The association between leptin and subclinical cardiovascular disease explained by body fat: Observational and Mendelian randomization analyses

Background and aimsLeptin has been associated with adverse effects on cardiovascular disease, but the effect of confounding by body fat in these associations remains unclear. To investigate associations between leptin and heart function and subclinical cardiovascular disease adjusted for total body fat, and to investigate the causal relation between leptin and cardiovascular disease using Mendelian randomisation. Methods and resultsLeptin concentrations, total body fat and diverse measures of subclinical cardiovascular disease were determined in participants of the Netherlands Epidemiology of Obesity study. Linear regression between leptin concentration and measures of heart function, ECG measures, and carotid intima media thickness as a measure of subclinical atherosclerosis was adjusted for potential confounding factors, and additionally including total body fat. We analysed the combined effects of genetic variants from a GWAS on leptin concentrations in publicly-available summary statistics of coronary heart disease GWAS (CARDIoGRAMplusC4D, n = 184,305). As many as 6107 men and women, mean (SD) age 56 (6) years, BMI 26 (4) kg/m2, and median leptin concentration 12.1 μg (IQR: 6.7–22.6) were included.In observational analyses, leptin was weakly associated with heart function and subclinical cardiovascular disease, but these associations attenuated when adjusting for total body fat. A doubling of genetically-determined leptin concentration was associated with an odds ratio of cardiovascular disease of 0.69 (0.37, 1.27). ConclusionObservational associations between leptin and subclinical measures of cardiovascular disease were largely explained by differences in total body fat. Results of analyses of genetically-determined leptin and coronary heart disease risk were inconclusive due to a large confidence interval.

PR interval duration is associated with the presence of white matter hyperintensities: Insights from the epidemiologic LIFE-Adult Study.

BackgroundPR interval prolongation is a preliminary stage of atrial cardiomyopathy which is considered as an intermediate phenotype for atrial fibrillation (AF). AF is a known risk factor for cerebrovascular adverse outcomes including stroke. Cerebral ischemia is one cause of white matter hyperintensities (WMHs), and cognitive dysfunction.AimTo analyze the relationship between PR interval and WMHs.Materials and methodsWe performed a cross-sectional analysis with individuals from the LIFE-Adult-Study (a population-based cohort study of randomly selected individuals from Leipzig, Germany) with available brain MRI and ECG. The Fazekas stages were used to quantify WMHs (0 = none; 1 = punctate foci; 2 = beginning confluence; 3 = large confluent areas). Stages 2–3 were defined as advanced WMHs. The PR interval was measured from resting 12-lead ECG. PR duration >200ms was defined as PR interval prolongation. We used a binary logistic regression for statistical analysis. We examined the relationship between MRI and ECG measures and adjusted them for clinical risk factors.ResultsWe included 2464 individuals (age 59±15 years, 47% women) into analyses. The median PR interval was 160ms (interquartile range 143–179), and 319 (13%) individuals with advanced WMHs, were significantly older, had more cardiovascular comorbidities and risk factors compared to individuals without WMHs (all p<0.005). On univariable analysis, PR interval duration (OR 1.01, 95%CI 1.01–1.02, p≤0.001) and PR interval ≥160 ms (OR 2.1, 95%CI 1.6–2.7, p≤0.001) were associated with advanced WMHs. In multivariable analysis, while PR interval duration was not associated with WMHs in the whole cohort, individuals with PR ≥160ms had higher risk for WMHs.ConclusionPR interval duration is associated with advanced WMHs beside advanced age, hypertension, and history of stroke. Further research is needed to determine whether changes in PR interval indices are clinically relevant for changes in WMHs.

Digitalised ECG measure of p-wave duration predicts incident heart failure

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Uppsala University Hospital Background and purpose Early identification of patients at risk of congestive heart failure (HF) may potentially alter their poor prognosis. The aim was therefore to test whether the P-wave and PR-interval, simple non-invasive ECG measures reflecting systolic and diastolic atrial function, could predict incident HF. Methods The PIVUS (Prospective Investigation of the Vasculature in Seniors) study including all individuals aged 70 years (1016 individuals, 50% women) was used to identify predictors of HF. Subjects with prevalent HF, QRS duration ≥ 130 msec or atrial arrhythmias on baseline ECG were excluded. Cox proportional hazard analysis was used to relate P-wave duration (Pdur), amplitude (Pamp) and PR interval in lead V1, to incident HF. Adjustment was performed for gender, RR-interval, beta-blocking agents, systolic blood pressure, body mass index and smoking. Results A total of 107 of 836 (12,8%) subjects at risk, developed HF during 15 years follow-up. The multivariate analysis, showed a strong U-shaped correlation between Pdur and incident HF (p=0.0001), which was significant for a Pdur&amp;lt; 60 msec [HR 2.75 (95% CI 1.87-4.06) at Pdur 40 msec]. There was no significant relationship between incident HF and the PR-interval, or the Pamp. A Pdur&amp;lt;60 msec improved discrimination by 3.7% when added to the confounders described above (p=0.048). Conclusions A short P-duration, a simple and easy ECG measure, may potentially be a useful predictor of developing HF, enabling early detection and treatment of HF.

Advanced electrocardiography predicts early cardiac involvement and incident arrhythmias in Fabry disease

Abstract Funding Acknowledgements Type of funding sources: None. Background Fabry disease is an X-linked disorder, with cardiovascular involvement characterised by progressive myocardial sphingolipid deposition. Cardiac disease is a major contributor to morbidity and mortality. Cardiac magnetic resonance (CMR) with T1 mapping and advanced electrocardiography (A-ECG) offer both diagnostic and prognostic potential. Purpose To evaluate the predictive power of A-ECG markers in identifying: 1) early cardiac involvement defined as low myocardial T1 on CMR, and 2) adverse cardiovascular outcomes defined as any arrhythmia requiring therapy, atrial fibrillation, hospitalisation for heart failure or mortality. Methods Patients included in this longitudinal, multi-centre study underwent same-day standard resting 12-lead ECG and CMR. CMR included standard cine imaging, T1 mapping with modified Look Locker inversion recovery (MOLLI, 5s(3s)3s), and late gadolinium enhancement (LGE). ECG digital files were analysed using in-house A-ECG software. A-ECG analysis included conventional ECG measures, derived vectorcardiographic measures, and singular value decomposition measures of waveform complexity. Significant A-ECG variables were identified using stepwise forward regression and incorporated in a multivariable logistic regression A-ECG score. A Youden index was applied to identify best threshold score and bootstrapping performed to calculate the area under the receiver operating characteristics curve (AUC), sensitivity, specificity, and 95% confidence intervals (CI). Results Among included patients (n=155, 40% male, age 46±14 years, 39% on enzyme replacement therapy), left ventricular mass index was higher in males compared to females (106 vs. 59 g/m2, p&amp;lt;0.001), 80% of patients had myocardial native T1 below the local reference range (933 vs. 968 ms, p=0.06), and 51% (70/136) had focal LGE. Multivariable A-ECG scores for detecting low T1, any arrhythmia, or atrial fibrillation had an AUC [95%CI], sensitivity, and specificity of 0.82 [0.75-0.89], 72 [55-95]%, 85 [66-71]%; 0.89 [0.82-0.95], 82 [68-94]%, 88 [70-96]%; and 0.89 [0.80-0.96], 92 [77-100]%, 83 [76-92]%, respectively, Figure 1. No predictors of heart failure hospitalisation or mortality were found. Conclusion A-ECG analysis of the resting 12-lead ECG has good diagnostic performance for predicting early myocardial involvement and the occurrence of arrhythmias in Fabry disease. This supports the use of A-ECG both as a screening tool to diagnose early cardiac disease, and for identifying those at risk of adverse arrhythmic outcomes.

Non-invasive Vagus Nerve Stimulation in Treatment of Disorders of Consciousness - Longitudinal Case Study.

Neuromodulatory electroceuticals such as vagus nerve stimulation have been recently gaining traction as potential rehabilitation tools for disorders of consciousness (DoC). We present a longitudinal case study of non-invasive auricular vagus nerve stimulation (taVNS) in a patient diagnosed with chronic unresponsive wakefulness syndrome (previously known as vegetative state). Over a period of 6 months we applied taVNS daily and regularly evaluated the patient’s behavioral outcomes using Coma Recovery Scale – Revised. We also took electrophysiological measures: resting state electroencephalography (EEG), heart rate (HR) and heart rate variability (HRV). All these methods revealed signs of improvement in the patient’s condition. The total CRS-R scores fluctuated but rose from 4 and 6 at initial stages to the heights of 12 and 13 in the 3rd and 5th month, which would warrant a change in diagnosis to a Minimally Conscious State. Scores obtained in a 2 months follow-up period, though, suggest this may not have been a lasting improvement. Behavioral signs of recovery are triangulated by EEG frequency spectrum profiles with re-emergence of a second oscillatory peak in the alpha range, which has been shown to characterize aware people. However, sustained spontaneous theta oscillations did not predictably diminish, which most likely reflects structural brain damage. ECG measures revealed a steady decrease in pre-stimulation HR combined with an increase in HRV-HR. This suggests a gradual withdrawal of sympathetic and an increase in parasympathetic control of the heart, which the previous literature has also linked with DoC improvements. Together, this study suggests that taVNS stimulation holds promise as a DoC treatment.

Cardiovascular phenotype of long-term anabolic-androgenic steroid abusers compared with strength-trained athletes.

IntroductionAbuse of anabolic‐androgenic steroids (AAS) has been linked to a variety of different cardiovascular (CV) side effects, but still the clinical effects of AAS abuse on CV risk are not clear. The aim of this study was to assess the CV phenotype of a large cohort of men with long‐term AAS use compared with strength‐trained athletes without AAS use.MethodsFifty one strength‐trained men with ≥3 years of AAS use was compared with twenty one strength‐trained competing athletes. We verified substance abuse and non‐abuse by blood and urine analyses. The participants underwent comprehensive CV evaluation including laboratory analyses, 12‐lead ECG with measurement of QT dispersion, exercise ECG, 24 h ECG with analyses of heart rate variability, signal averaged ECG, basic transthoracic echocardiography, and coronary computed tomography angiography (CCTA).ResultsHemoglobin levels and hematocrit were higher among the AAS users compared with non‐users (16.8 vs. 15.0 g/dl, and 0.50% vs. 0.44%, respectively, both p < 0.01) and HDL cholesterol significantly lower (0.69 vs. 1.25 mmol/L, p < 0.01). Maximal exercise capacity was 270 and 280 W in the AAS and the non‐user group, respectively (p = 0.04). Echocardiography showed thicker intraventricular septum and left ventricular (LV) posterior wall among AAS users (p < 0.01 for both), while LV ejection fraction was lower (50 vs. 54%, p = 0.02). Seven AAS users (17%) had evidence of coronary artery disease on CCTA. There were no differences in ECG measures between the groups.ConclusionsA divergent CV phenotype dominated by increased CV risk, accelerated coronary artery disease, and concentric myocardial hypertrophy was revealed among the AAS users.

PO-671-08 SPATIAL VENTRICULAR GRADIENT CAN DIFFERENTIATE HYPERTROPHIC CARDIOMYOPATHY FROM OTHER FORMS OF LEFT VENTRICULAR HYPERTROPHY

Diagnosis of hypertrophic cardiomyopathy (HCM) has far-reaching clinical implications. The gold standard non-invasive test for diagnosing HCM is cardiac MRI (CMR), but this is expensive and not readily available. Standard ECG measures of left ventricular hypertrophy may not differentiate HCM from other more benign causes of cardiac hypertrophy. The spatial ventricular gradient (SVG), a vectorcardiographic measure of global electrical heterogeneity (GEH), reflects global abnormalities in cardiac depolarization and repolarization, and may be able to distinguish HCM from other disorders.

Sudden Death and Cardiac Arrythmia With Lamotrigine: A Rapid Systematic Review.

A recent Food and Drug Administration warning concerning an arrhythmogenic potential of lamotrigine created concern in the neurologic community. This warning was based on in vitro studies, but no clinically relevant risk was considered. This rapid systematic review aims to elucidate the risk of lamotrigine on sudden death or ECG abnormalities. We conducted a systematic search of Ovid Medline and Ovid Embase, including randomized controlled trials and observational studies and studies of people with or without epilepsy, with the outcome measures sudden unexpected death in epilepsy (SUDEP) or sudden cardiac death as well as the development or worsening of ECG abnormalities. We evaluated the sudden death definitions used in all included studies, as some could have used unclear or overlapping definitions. We used the American Academy of Neurology risk of bias tool to evaluate the class of evidence and the GRADE approach to evaluate our confidence in the evidence. We included 26 studies with 24,962 participants, of whom 2,326 used lamotrigine. Twelve studies showed no significant risk of SUDEP for lamotrigine users. One study reporting on sudden cardiac death and 3 studies with unclear sudden death definitions did not report an elevated risk of death in lamotrigine users compared to controls. In 10 studies reporting on ECG measures, there was no statistically significant increased risk among lamotrigine users except in 2 studies. These 2 studies reported either "slight increases" in PR interval or an increased PQ interval that the primary study authors believed to be related to structural cardiac differences rather than an effect of lamotrigine. One study was rated Class II; all others were Class III or IV. We had very low confidence in the evidence following the GRADE assessment. None of the studies examined the risk of lamotrigine in people with preexisting cardiac conditions. There is insufficient evidence to support or refute that lamotrigine is associated with sudden death or ECG changes in people with or without epilepsy as compared to antiseizure medication or placebo, due to the high risk of bias in most studies and low precision and inconsistency in the reported results.

Early childhood lead exposure and adolescent heart rate variability: A longitudinal cohort study

Lead is a known neurotoxicant with many detrimental health effects, including neurocognitive deficits and cardiovascular and metabolic disorders. However, few studies have tested the association between lead exposure and the physiological stress response, which in and of itself may act as a precursor to and/or underlying mechanism of detrimental health outcomes. The purpose of this study was to examine the influence of early childhood and early adolescent low-level lead exposure on early adolescent heart rate variability, a widely-used measure of physiological stress. Participants were 408 children from Jintan, China for whom blood lead levels were measured between 3 and 5 years (early childhood) and again at 12 years (early adolescence). Heart rate variability was assessed at 12 years while participants underwent an induced stress task utilizing the ratio of low to high frequency (LF/HF) ECG measures. Mean blood lead levels in the cohort were 6.63 mcg/dl and 3.10 mcg/dl at 3–5 years and 12 years, respectively. Blood lead levels at 3–5 years of age (β 0.06, p = 0.027), but not at age 12 (β −0.05, p = 0.465), were significantly associated with LF/HF measures while controlling for multiple sociodemographic variables, potentially reflecting a dysregulated stress response with a shift towards sympathetic dominance. These findings suggest that early childhood lead exposure may have a detrimental influence on early adolescent autonomic responses to acute stress, which holds implications for cardiovascular health and overall growth and development.

Resting ECG measurements can identify abnormalities in children with catecholaminergic polymorphic ventricular tachycardia

Abstract Background Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) is a rare inherited disease characterized by exercise- or emotionally-triggered life-threatening ventricular arrhythmias. The resting ECG is considered to be normal and diagnosis has depended on exercise testing that is difficult acutely post-arrest or in young children. Purpose To identify resting ECG abnormalities in children with CPVT through assessment of measurement matrix parameters compared to a cohort of normal children. Methods A discovery cohort of 65 CPVT patients from the Electrophysiology program were identified. After excluding those on antiarrhythmics or in an arrhythmia at the time of their baseline ECG, 31 cases were matched 3:1 by age and sex with 93 healthy controls. Each individual had baseline ECG parameters and 180 machine-derived ECG amplitudes and durations (measurement matrix) measured. Statistical differences between ECG measures were assessed using Student's T-Test adjusted with a False Detection Rate of 1%. Significant measures were processed in a machine-learning algorithm to derive a Tree Model to differentiate individuals with and without CPVT. Results No significant differences were detected between CPVT patients who had and did not have a cardiac arrest. Comparing the CPVT and control cohorts, significant repolarization differences were seen in the amplitudes of lateral (I, negative aVR, V5, V6) and anterior leads (V2, V3, V4) at the J-point, ST midpoint, ST endpoint, and T-wave. Specifically, individuals with CPVT had significantly lower mean amplitudes in all aforementioned leads except aVR where the mean amplitudes were higher. These data were then used to create a Tree Model of the discovery cohort displayed in Figure 1 with a resulting R2 of 0.74, sensitivity of 0.81, and specificity of 0.98. Conclusions Baseline differences in repolarization are detectable in the left and anterior chest leads using machine-derived measurements of baseline ECGs in patients with CPVT, which may guide clinical suspicion when evaluating the resting ECG. These results warrant further analysis including testing of the Tree Model with a validation cohort. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): Scholar Award from the Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada to Trainee Dr. Taraneh TofighiCanadian Institute for Health Research Figure 1. CPVT Tree Model

Electrocardiographic biomarkers to predict atrial fibrillation in sinus rhythm electrocardiograms

ObjectiveEarly prediction of atrial fibrillation (AF) development would improve patient outcomes. We propose a simple and cheap ECG based score to predict AF development.MethodsA cohort of 16 316 patients was...

Abstract 027: Individual-level Fine Particulate Air Pollution Is Associated With Arrhythmia In Adolescents

Introduction: Fine particulate (PM 2.5 ) exposure has been related to higher propensity of arrhythmias in adults. However, the association between PM 2.5 exposure and arrhythmia in adolescents remains unclear. Hypothesis: PM 2.5 exposure is related to an acute increase in numbers of arrhythmic heartbeats in adolescents. Methods: We used data collected from 421 adolescents in the Penn State Child Cohort (PSCC) follow-up examination for this report. From each participant, we obtained 24-hour beat-to-beat ECG data using a 12-lead Holter ECG. From which, arrhythmias, including premature ventricular contraction (PVC) and premature atrial contraction (PAC), were identified. The number of PVCs and PACs every 30 minutes were analyzed with individual-level 30-minute average PM 2.5 concentrations obtained by using a personal minute-by-minute PM 2.5 monitor for 24 hours in parallel to the ECG. Thus, each participant contributed 48 30-minute segments of arrhythmia and PM 2.5 data. Polynomial distributed lag models within a framework of a negative binomial model were used to assess the segment-specific and cumulative effect of PM 2.5 concentration on numbers of PVC and PAC, adjusting for age, race, sex, BMI percentile, temperature, and humidity. Results: The mean (SD) age of PSCC was 16.9 (2.2) years, with 54% males, and 78% whites. The 30-minute mean (SD) of PM 2.5 concentration was 14.4 (45.4) μg/m 3 , while PVC and PAC counts were 0.2 (2.0) and 0.5 (4.0). As shown in the table, 10 μg/m 3 increases in PM 2.5 concentration 0.5-2.0 hours prior to the ECG measures (lags 1-3) each were associated with 2% increase in PVC counts (all p&lt;0.05). Cumulatively, a 10 μg/m 3 increment in PM 2.5 was associated with a 5% (1% - 10%) increase in PVC counts within 2 hours after exposure. PM 2.5 was not related to PAC counts. Conclusion: Individual-level exposure to PM 2.5 is associated with an acute increased number of ventricular arrhythmia in population-based adolescents. The time course of the effect of PM 2.5 on ventricular arrhythmia is within 2 hours after exposure.

Abstract 15531: Limited Relationship Between Echocardiographic Measures and Electrocardiographic Markers of Left Ventricular Dimensions in Healthy Children

Background: Prior ECG standards in children have largely been defined without echo confirmation of normal anatomy. The Pediatric Heart Network Normal Echocardiogram Z-score Project provides a racially diverse age/sex classified group of healthy children with normal echos that included 2170 matched contemporaneous digitally acquired ECGs. We hypothesized that ECG measures and z-scores of left ventricular (LV) dimensions are correlated in healthy children. Methods: This was a secondary analysis of the previously described cohort. Six ECG measures historically associated with LV size (R V5, R V6, S V1, Q III, axis, R V6+S V1), and 13 paired echo measures were identified a-priori with LV Mass (LVMass-z) and left ventricular end diastolic volume (LVEDV-z) z-scores serving as primary echo measurement predictors. Pearson or Spearman correlations were calculated for each of the 78 ECG- echo pairs. Regression analyses were performed to assess how much variance in ECG measures was explained by variation in LV dimensions and by demographic variables (age, sex, race). Results: ECG and echo measurement correlations were significant and concordant in 41/78 (53%), though many were significant and discordant in 13, (17%) or not correlated in 24 (31%). Of the 6 ECG measures of LV size, 5 correlated in the clinically predicted direction for LV Mass-z and LVEDV-z. While many of the correlations were statistically significant, the correlations were weak (0.05-0.25). R 2 was higher for demographic variables than for echo measures in all pairs, but even with demographic variables included, the overall R 2 was &lt; 0.17. Conclusions: In a large, diverse cohort of healthy children, there was a positive association between echo measures of LV dimension and mass and the most commonly used ECG measures of LVH. However, these correlations were weak and most of the variability in ECG measures was explained by factors other than echo derived mass or volume or measured patient demographic variables. These data question the utility of traditional ECG measurements of LV size as standalone indications for further cardiac evaluation in healthy children.

Autonomic and Cardiac Repolarization Lability in Long QT Syndrome Patients.

Long QT-Syndrome (LQTS) patients are at risk of arrhythmias and seizures. We investigated whether autonomic and cardiac repolarization measures differed based on LQTS genotypes, and in LQTS patients with vs. without arrhythmias and seizures. We used 24-h ECGs from LQTS1 (n = 87), LQTS2 (n = 50), and LQTS genotype negative patients (LQTS(-), n = 16). Patients were stratified by LQTS genotype, and arrhythmias/seizures. Heart rate variability (HRV) and QT variability index (QTVI) measures were compared between groups during specific physiological states (minimum, middle, & maximum sympathovagal balance, LF/HF). Results were further tested using logistic regression for each ECG measure, and all HRV measures in a single multivariate model. Across multiple physiological states, total autonomic (SDNN) and vagal (RMSSD, pNN50) function were lower and repolarization dynamics (QTVI) were elevated in LQTS(+), LQTS1, and LQTS2, compared to LQTS(-). Many measures remained significant in the regression models. Multivariate modeling demonstrated that SDNN, RMSSD, and pNN50 were independent markers of LQTS(+) vs. LQTS(-), and SDNN and pNN50 were markers for LQTS1 vs. LQTS(-). During sympathovagal balance (middle LF/HF), RMSSD and pNN50 distinguished LQTS1 vs. LQTS2. LQTS1 patients with arrhythmias had lower total (SDNN) and vagal (RMSSD and pNN50) autonomic function, and SDNN remained significant in the models. In contrast, ECG measures did not differ in LQTS2 patients with vs. without arrhythmias, and LQTS1 and LQTS2 with vs. without seizures. Autonomic (HRV) and cardiac repolarization (QTVI) ECG measures differ based on LQTS genotype and history of arrhythmias in LQTS1. SDNN, RMSSD, and pNN50 were each independent markers for LQTS genotype.