Simple electrocardiographic measures improve sudden arrhythmic death prediction in coronary disease

Noninvasive prediction of coronary artery disease severity: Comparative analysis of electrocardiographic findings and risk factors with SYNTAX and Gensini score

OBJECTIVE

Coronary artery disease (CAD) remains a significant global health burden, characterized by the narrowing or blockage of coronary arteries. Treatment decisions are often guided by angiography-based scoring systems, such as the Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) and Gensini scores, although these require invasive procedures. This study explores the potential of electrocardiography (ECG) as a noninvasive diagnostic tool for predicting CAD severity, alongside traditional risk factors.

METHODS

This retrospective cross-sectional study was conducted on 348 CAD patients who underwent coronary angiography. Demographic data, ECG findings, SYNTAX, and Gensini scores were collected. The association between ECG findings and demographic information with the severity of coronary artery stenosis, as assessed by SYNTAX and Gensini scores, was investigated using SPSS software, version 23.

RESULTS

Significant associations were observed between CAD severity and risk factors such as male gender, diabetes mellitus (DM), and smoking. Additionally, certain ECG indicators, including Q waves and ST depression (STD), showed significant correlations with CAD severity, particularly according to the Gensini score.

CONCLUSION

This study underscores the utility of ECG and clinical factors in identifying severe CAD, offering cost-effective diagnostic alternatives to angiography. Integrating various parameters into a single score is crucial in clinical practice, providing a stronger diagnostic and prognostic tool without increasing costs. Further comprehensive studies are warranted to refine risk prediction models and improve CAD management strategies.

Sudden Death in Obesity: Mechanisms and Management

In recent decades, the prevalence of obesity has increased significantly, leading to an epidemic at the global level. Obesity is associated with various metabolic alterations and increases the risk of cardiovascular disease. The most devastating manifestation of cardiovascular disease is sudden cardiac death (SCD), leading to substantial years of potential life lost worldwide. Obesity-related SCD is an increasingly important public health problem and warrants a specific investigative focus on improved risk stratification and prevention. In this review, we summarize the current evidence regarding management of SCD in obesity and discuss knowledge gaps as well as future directions in this field.

The association between GRACE score at admission for myocardial infarction and the incidence of sudden cardiac arrests in long-term follow-up - the MADDEC study

Background. Sudden cardiac arrest (SCA), often also leading to sudden cardiac death (SCD), is a common complication in coronary artery disease. Despite the effort there is a lack of applicable prediction tools to identify those at high risk. We tested the association between the validated GRACE score and the incidence of SCA after myocardial infarction. Material and methods. A retrospective analysis of 1,985 patients treated for myocardial infarction (MI) between January 1st 2015 and December 31st 2018 and followed until the 31st of December of 2021. The main exposure variable was patients' GRACE score at the point of admission and main outcome variable was incident SCA after hospitalization. Their association was analyzed by subdistribution hazard (SDH) model analysis. The secondary endpoints included SCA in patients with no indication to implantable cardioverter-defibrillator (ICD) device and incident SCD. Results. A total of 1985 patients were treated for MI. Mean GRACE score at baseline was 118.7 (SD 32.0). During a median follow-up time of 5.3 years (IQR 3.8-6.1 years) 78 SCA events and 52 SCDs occurred. In unadjusted analyses one SD increase in GRACE score associated with over 50% higher risk of SCA (SDH 1.55, 95% CI 1.29-1.85, p < 0.0001) and over 40% higher risk for SCD (1.42, 1.12-1.79, p = 0.0033). The associations between SCA and GRACE remained statistically significant even with patients without indication for ICD device (1.57, 1.30-1.90, p < 0.0001) as well as when adjusting with patients LVEF and omitting the age from the GRACE score to better represent the severity of the cardiac event. The association of GRACE and SCD turned statistically insignificant when adjusting with LVEF. Conclusions. GRACE score measured at admission for MI associates with long-term risk for SCA.

Predicting long-term risk of sudden cardiac death with automatic computer-interpretations of electrocardiogram

Background

Computer-interpreted electrocardiogram (CIE) data is provided by almost all commercial software used to capture and store digital electrocardiograms. CIE is widely available, inexpensive, and accurate. We tested the potential of CIE in long-term sudden cardiac death (SCD) risk prediction.

Methods

This is a retrospective of 8,568 consecutive patients treated for acute coronary syndrome. The primary endpoint was five-year occurrence of SCDs or equivalent events (SCDs aborted by successful resuscitation or adequate ICD therapy). CIE statements were extracted from summary statements and measurements made by the GE Muse 12SL algorithm from ECGs taken during admission. Three supervised machine learning algorithms (logistic regression, extreme gradient boosting, and random forest) were then used for analysis to find risk features using a random 70/30% split for discovery and validation cohorts.

Results

Five-year SCD occurrence rate was 3.3% (n = 287). Regardless of the used ML algorithm, the most significant risk ECG risk features detected by the CIE included known risk features such as QRS duration and factors associated with QRS duration, heart rate-corrected QT time (QTc), and the presence of premature ventricular contractions (PVCs). Risk score formed by using most significant CIE features associated with the risk of SCD despite adjusting for any clinical risk factor (including left ventricular ejection fraction). Sensitivity of CIE data to correctly identify patients with high risk of SCD (over 10% 5-year risk of SCD) was usually low, but specificity and negative prediction value reached up to 96.9% and 97.3% when selecting only the most significant features identified by logistic regression modeling (p-value threshold <0.01 for accepting features in the model). Overall, CIE data showed a modest overall performance for identifying high risk individuals with area under the receiver operating characteristic curve values ranging between 0.652 and 0.693 (highest for extreme gradient boosting and lowest for logistic regression).

Conclusion

This proof-of-concept study shows that automatic interpretation of ECG identifies previously validated risk features for SCD.

Predicting angiographic coronary artery disease using machine learning and high-frequency QRS

AIM

Exercise stress ECG is a common diagnostic test for stable coronary artery disease, but its sensitivity and specificity need to be further improved. In this paper, we construct a machine learning model for the prediction of angiographic coronary artery disease by HFQRS analysis of cycling exercise ECG.

METHODS AND RESULTS

This study prospectively included 140 inpatients and 59 healthy volunteers undergoing cycling exercise ECG. The CHD group (N=104) and non-CHD group (N=95) were determined by coronary angiography gold standard. Automated HF QRS analysis was performed by the blinded method. The coronary group was predominantly male, with a higher prevalence of age, BMI, hypertension, and diabetes than the non-coronary group ( P < 0.001 ), higher lipid levels in the coronary group ( P < 0.005 ), significantly longer QRS duration during exercise testing ( P < 0.005 ), more positive leads ( P < 0.001 ), and a greater proportion of significant changes in HFQRS ( P < 0.001 ). Age, Gender, Hypertension, Diabetes, and HF QRS Conclusions were screened by correlation analysis and multifactorial retrospective analysis to construct the machine learning models of the XGBoost Classifier, Logistic Regression, LightGBM Classifier, RandomForest Classifier, Artificial Neural Network and Support Vector Machine, respectively.

CONCLUSION

Male, elderly, with hypertension, diabetes mellitus, and positive exercise stress test HFQRS conclusions suggested a high risk of CHD. The best performance of the Logistic Regression model was compared, and a column line graph for assessing the risk of CHD was further developed and validated.

QRS-T angle: is it a specific parameter associated with sudden cardiac death in type 2 diabetes? Results from the SURDIAGENE and the Mini-Finland prospective cohorts

AIMS/HYPOTHESIS

Type 2 diabetes is associated with a high risk of sudden cardiac death (SCD), but the risk of dying from another cause (non-SCD) is proportionally even higher. The aim of the study was to identify easily available ECG-derived features associated with SCD, while considering the competing risk of dying from non-SCD causes.

METHODS

In the SURDIAGENE (Survie, Diabete de type 2 et Genetique) French prospective cohort of individuals with type 2 diabetes, 15 baseline ECG parameters were interpreted among 1362 participants (mean age 65 years; HbA1c 62±17 mmol/mol [7.8±1.5%]; 58% male). Competing risk models assessed the prognostic value of clinical and ECG parameters for SCD after adjusting for age, sex, history of myocardial infarction, N-terminal pro b-type natriuretic peptide (NT-proBNP), HbA1c and eGFR. The prospective Mini-Finland cohort study was used to externally validate our findings.

RESULTS

During median follow-up of 7.4 years, 494 deaths occurred including 94 SCDs. After adjustment, frontal QRS-T angle ≥90° (sub-distribution HR [sHR] 1.68 [95% CI 1.04, 2.69], p=0.032) and NT-proBNP level (sHR 1.26 [95% CI 1.06, 1.50] per 1 log, p=0.009) were significantly associated with a higher risk of SCD. Nevertheless, frontal QRS-T angle was the only marker not to be associated with causes of death other than SCD (sHR 1.08 [95% CI 0.84, 1.39], p=0.553 ). These findings were replicated in the Mini-Finland study subset of participants with diabetes (sHR 2.22 [95% CI 1.05, 4.71], p=0.04 for SCD and no association for other causes of death).

CONCLUSIONS/INTERPRETATION

QRS-T angle was specifically associated with SCD risk and not with other causes of death, opening an avenue for refining SCD risk stratification in individuals with type 2 diabetes.

Dynamic electrocardiogram changes are a novel risk marker for sudden cardiac death

BACKGROUND AND AIMS

Electrocardiogram (ECG) abnormalities have been evaluated as static risk markers for sudden cardiac death (SCD), but the potential importance of dynamic ECG remodelling has not been investigated. In this study, the nature and prevalence of dynamic ECG remodelling were studied among individuals who eventually suffered SCD.

METHODS

The study population was drawn from two prospective community-based SCD studies in Oregon (2002, discovery cohort) and California, USA (2015, validation cohort). For this present sub-study, 231 discovery cases (2015-17) and 203 validation cases (2015-21) with ≥2 archived pre-SCD ECGs were ascertained and were matched to 234 discovery and 203 validation controls based on age, sex, and duration between the ECGs. Dynamic ECG remodelling was measured as progression of a previously validated cumulative six-variable ECG electrical risk score.

RESULTS

Oregon SCD cases displayed greater electrical risk score increase over time vs. controls [+1.06 (95% confidence interval +0.89 to +1.24) vs. -0.05 (-0.21 to +0.11); P < .001]. These findings were successfully replicated in California [+0.87 (+0.7 to +1.04) vs. -0.11 (-0.27 to 0.05); P < .001]. In multivariable models, abnormal dynamic ECG remodelling improved SCD prediction over baseline ECG, demographics, and clinical SCD risk factors in both Oregon [area under the receiver operating characteristic curve 0.770 (95% confidence interval 0.727-0.812) increased to area under the receiver operating characteristic curve 0.869 (95% confidence interval 0.837-0.902)] and California cohorts.

CONCLUSIONS

Dynamic ECG remodelling improved SCD risk prediction beyond clinical factors combined with the static ECG, with successful validation in a geographically distinct population. These findings introduce a novel concept of SCD dynamic risk and warrant further detailed investigation.

An ECG-based artificial intelligence model for assessment of sudden cardiac death risk

BACKGROUND

Conventional ECG-based algorithms could contribute to sudden cardiac death (SCD) risk stratification but demonstrate moderate predictive capabilities. Deep learning (DL) models use the entire digital signal and could potentially improve predictive power. We aimed to train and validate a 12 lead ECG-based DL algorithm for SCD risk assessment.

METHODS

Out-of-hospital SCD cases were prospectively ascertained in the Portland, Oregon, metro area. A total of 1,827 pre- cardiac arrest 12 lead ECGs from 1,796 SCD cases were retrospectively collected and analyzed to develop an ECG-based DL model. External validation was performed in 714 ECGs from 714 SCD cases from Ventura County, CA. Two separate control group samples were obtained from 1342 ECGs taken from 1325 individuals of which at least 50% had established coronary artery disease. The DL model was compared with a previously validated conventional 6 variable ECG risk model.

RESULTS

The DL model achieves an AUROC of 0.889 (95% CI 0.861-0.917) for the detection of SCD cases vs. controls in the internal held-out test dataset, and is successfully validated in external SCD cases with an AUROC of 0.820 (0.794-0.847). The DL model performs significantly better than the conventional ECG model that achieves an AUROC of 0.712 (0.668-0.756) in the internal and 0.743 (0.711-0.775) in the external cohort.

CONCLUSIONS

An ECG-based DL model distinguishes SCD cases from controls with improved accuracy and performs better than a conventional ECG risk model. Further detailed investigation is warranted to evaluate how the DL model could contribute to improved SCD risk stratification.

Relationship between baseline electrocardiographic measurements and outcomes in patients with high-risk heart failure: Insights from the VerICiguaT Global Study in Subjects with Heart Failure with Reduced Ejection Fraction (VICTORIA) trial

AIMS

Whether electrocardiographic (ECG) measurements predict mortality in chronic heart failure with reduced ejection fraction (HFrEF) is unknown.

METHODS AND RESULTS

We studied 4880 patients from the Vericiguat Global Study in Subjects with Heart Failure with Reduced Ejection Fraction (VICTORIA) trial with a baseline 12-lead ECG. Associations between ECG measurements and mortality were estimated as hazard ratios (HR) and adjusted for the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score, N-terminal pro-B-type natriuretic peptide, and index event. Select interactions between ECG measurements, patient characteristics and mortality were examined. Over a median of 10.8 months, there were 824 cardiovascular (CV) deaths (214 sudden) and 1005 all-cause deaths. Median age was 68 years (interquartile range [IQR] 60-76), 24% were women, median ejection fraction was 30% (IQR 23-35), 41% had New York Heart Association class III/IV, and median MAGGIC score was 24 (IQR 19-28). After multivariable adjustment, significant associations existed between heart rate (per 5 bpm: HR 1.02), QRS duration (per 10 ms: HR 1.02), absence of left ventricular hypertrophy (HR 0.64) and CV death, and similarly so with all-cause death (HR 1.02; HR 1.02; HR 0.61, respectively). Contiguous pathologic Q waves were significantly associated with sudden death (HR 1.46), and right ventricular hypertrophy with all-cause death (HR 1.44). The only sex-based interaction observed was for pathologic Q waves on CV (men: HR 1.05; women: HR 1.64, pinteraction  = 0.024) and all-cause death (men: HR 0.99; women: HR 1.57; pinteraction  = 0.010). Whereas sudden death doubled in females, it did not differ among males (male: HR 1.25, 95% confidence interval [CI] 0.87-1.79; female: HR 2.50, 95% CI 1.23-5.06; pinteraction  = 0.141).

CONCLUSION

Routine ECG measurements provide additional prognostication of mortality in high-risk HFrEF patients, particularly in women with contiguous pathologic Q waves.

In-hospital predictors for primary prevention of sudden death after acute myocardial infarction with cardiac dysfunction

BACKGROUND

Current guidelines recommend prophylactic defibrillator implantation in patients with acute myocardial infarction (AMI) and left ventricular ejection fraction (LVEF) ≤40 % or LVEF ≤35 % plus heart failure symptoms or inducible ventricular tachyarrhythmias during an electrophysiology study at 40 days after AMI or 90 days after revascularization. In-hospital predictors of sudden cardiac death (SCD) after AMI during the index hospitalization remain unsettled. We sought to examine in-hospital predictors of SCD in patients with AMI and LVEF ≤40 % evaluated during the index hospitalization.

METHODS

We retrospectively evaluated 441 consecutive patients with AMI and LVEF ≤40 % admitted to our hospital between 2001 and 2014 (77 % male gender; median age: 70 years; median hospitalization length: 23 days). The primary endpoint was a composite of SCD or aborted SCD at ≥30 days after AMI onset (composite arrhythmic event). LVEF and QRS duration (QRSd) on electrocardiography were measured at a median of 12 days and 18 days, respectively.

RESULTS

During a median follow-up of 7.6 years, the incidence of composite arrhythmic events was 7.3 % (32 of 441 patients). In multivariable analysis, QRSd ≥100 msec (beta-coefficient = 1.54, p = 0.003), LVEF ≤23 % (beta-coefficient = 1.14, p = 0.007), and onset-reperfusion time > 5.5 h (beta-coefficient = 1.16, p = 0.035) were independent predictors of composite arrhythmic events. The combination of these 3 factors was associated with the highest rate of composite arrhythmic events compared with 0-2 factors (p < 0.001).

CONCLUSIONS

The combination of QRSd ≥100 msec, LVEF ≤23 %, and onset-reperfusion time > 5.5 h during the index hospitalization provides precise risk stratification for SCD in patients early after AMI.

Risk stratification of sudden cardiac death: a review

Sudden cardiac death (SCD) is responsible for several millions of deaths every year and remains a major health problem. To reduce this burden, diagnosing and identification of high-risk individuals and disease-specific risk stratification are essential. Treatment strategies include treatment of the underlying disease with lifestyle advice and drugs and decisions to implant a primary prevention implantable cardioverter-defibrillator (ICD) and perform ablation of the ventricles and novel treatment modalities such as left cardiac sympathetic denervation in rare specific primary electric diseases such as long QT syndrome and catecholaminergic polymorphic ventricular tachycardia. This review summarizes the current knowledge on SCD risk according to underlying heart disease and discusses the future of SCD prevention.

Out-of-hospital cardiac arrest: A data-driven visualization of collaboration, frontier identification, and future trends

One of the main causes of death is out-of-hospital cardiac arrest (OHCA), which has a poor prognosis and poor neurological outcomes. This phenomenon has attracted increasing attention. However, there is still no published bibliometric analysis of OHCA. This bibliometric analysis of publications on OHCA aimed to visualize the current status of research, determine the frontiers of research, and identify future trends. Publications on OHCA were downloaded from the web of science database. The data elements included year, countries/territories, institutions, authors, journals, research areas, citations of publications, etc. Joinpoint regression and exponential models were used to identify and predict the trend of publications, respectively. Knowledge domain maps were applied to conduct contribution and collaboration, cooccurrence, cocitation, and coupled analyses. Timeline and burst detection analysis were used to identify the frontiers in the field. A total of 3 219 publications on OHCA were found from 1998 to 2022 (average annual percentage change = 16.7; 95% CI 14.4, 19.1). It was estimated that 859 articles and reviews would be published in 2025. The following research hotpots were identified: statement, epidemiology, clinical care, factors influencing prognosis and emergency medical services. The research frontier identification revealed that 7 categories were classified, including therapeutic hypothermia, emergency medical services, airway management, myocardial infarction, extracorporeal cardiopulmonary resuscitation, stroke foundation and trial. The burst detection analysis revealed that percutaneous coronary intervention, neurologic outcome, COVID-19 and extracorporeal cardiopulmonary resuscitation are issues that should be given continual attention in the future. This bibliometric analysis may reflect the current status and future frontiers of OHCA research.

A randomized clinical trial of omega-3 fatty acid and vitamin D supplementation on electrocardiographic risk profiles

Beneficial and adverse associations with arrhythmias have been reported for omega-3 fatty acids (omega-3 FA) and Vitamin D. The 12 lead electrocardiogram (ECG) contains quantitative measures reflecting diverse aspects of electrophysiology that might provide insights into mechanisms underlying these associations. In a pre-specified ancillary study of the VITaminD and omegA-3 (VITAL) trial, we examined the effect of 1 g of marine omega-3 FA per day, comprised of 460 mg eicosapentanoic acid and 380 mg of docosahexaenoic acid, and 2000 IU VitaminD3 per day on ECG characteristics associated with atrial and ventricular arrhythmias among individuals age 50 years or greater. A total of 911 study participants underwent ECGs at baseline and again at 2 years after the randomization. Individuals randomized to active omega-3 FA demonstrated significant net increase in PR-interval duration (p = 0.005) and P-wave duration (p = 0.03) as well significant net decrease in P-wave amplitude (p = 0.037) as compared to placebo. RMSSD increased to a greater extent in the omega-3 FA arm compared to placebo (p = 0.040). For Vitamin D3, the Cornell voltage increased to a lesser extent in the participants assigned to active treatment as compared to placebo (p = 0.044). There were no other significant differences in QRS, QTc, Cornell voltage or heart rate. Thus, randomized treatment with omega-3 FA supplements resulted in changes on the ECG that are potentially reflective of heightened vagal tone and/or slowing of intraatrial and AV conduction. Vitamin D3 supplementation resulted in modest reductions in progressive LV voltage suggestive of a potential antihypertrophic effect.Trial registration ClinicalTrials.gov Identifiers: NCT01169259, NCT02178410 (06/26/2010 and 06/30/2014).

Artificial Intelligence in Ventricular Arrhythmias and Sudden Death

Sudden cardiac arrest due to lethal ventricular arrhythmias is a major cause of mortality worldwide and results in more years of potential life lost than any individual cancer. Most of these sudden cardiac arrest events occur unexpectedly in individuals who have not been identified as high-risk due to the inadequacy of current risk stratification tools. Artificial intelligence tools are increasingly being used to solve complex problems and are poised to help with this major unmet need in the field of clinical electrophysiology. By leveraging large and detailed datasets, artificial intelligence-based prediction models have the potential to enhance the risk stratification of lethal ventricular arrhythmias. This review presents a synthesis of the published literature and a discussion of future directions in this field.

Sudden death in ischemic heart disease: looking for new predictors: polygenic risk

The phenomenon of sudden death (SD) occurs, in 70% of cases, in people who do not fall within the indications of the guidelines relating to the implantation of the defibrillator. There is a way of inheriting the risk condition by genetic means, the polygenic one, in which mutations are not found, but an increase in alleles of common variations called polymorphisms. The PRE-DETERMINE cohort study has the primary objective of determining whether biological markers, and electrocardiogram can be used to identify individuals more likely to experience SD. Within the study, we investigated the utility of the genome-wide polygenic score for coronary artery disease (GPSCAD) for SD risk stratification in an intermediate-risk population with stable coronary artery disease without severe systolic dysfunction and/or indication for an implantable cardioverter defibrillator in primary prevention. Over a mean follow-up period of 8.0 years, patients in the top decile of GPSCAD were at higher absolute (8.0% vs. 4.8%; P < 0.005) and relative (29% vs. 16%; P < 0.0003) risk of SD compared to the rest of the cohort. No association was found between the highest decile of GPSCAD and other forms of death, cardiac, and non-cardiac. The data on the increase in absolute and relative terms of SD can be used, at this stage, only for a theoretical estimate on the possible efficacy of the defibrillator in the population with chronic coronary artery disease and moderately depressed left ventricular function as number needed to treat and possible reduction of mortality in high-risk patients (those included in the top decile of GPSCAD).

Association between sensitivity to thyroid hormones and risk of arrhythmia in patients with coronary heart disease: a RCSCD-TCM study in China

BACKGROUND

Thyroid dysfunction is closely related to arrhythmia. However, the relationship between sensitivity to thyroid hormone and risk of arrhythmia remains unknown. This study aimed to investigate the association between the thyroid system complex index and risk of arrhythmia in patients with coronary heart disease (CHD).

METHODS

This large, multicenter study included 28,413 patients with CHD. Central sensitivity to thyroid hormone was assessed by calculating the thyroid feedback quantile-based index (TFQI). Logistic regression was used to analyze the relationship between sensitivity to thyroid hormone and risk of arrhythmia. This study also assessed the relationship between sensitivity to thyroid hormone and risk of arrhythmia in different sexes, ages, and glucose regulation and blood lipid states.

RESULTS

Of the 28,413 participants, 8935 (31.4%) patients with CHD had arrhythmia. There was a remarkable association between TFQI and risk of arrhythmia (odds ratio [OR]: 0.783; 95% confidence interval [CI], 0.735-0.836). Furthermore, the association between the TFQI and risk of arrhythmia in women (OR: 0.731; 95% CI: 0.667-0.802) was stronger than that in men (OR: 0.894; 95% CI: 0.816-0.910), as well as higher in elder (OR: 0.779; 95% CI: 0.721-0.843) than middle-aged (OR: 0.789; 95% CI: 0.703-0.886) patients. Furthermore, the association was strong in the state of diabetes (OR: 0.635; 95% 0.569-0.709) and dyslipidemia (OR: 0.706; 95% CI: 0.644-0.774).

CONCLUSION

There is a remarkable association between sensitivity to thyroid hormone and risk of arrhythmia in patients with CHD, which is more pronounced among women and the elderly. The association is also stronger in CHD patients with dyslipidemia or diabetes.

The role of β-adrenergic stimulation in QT interval adaptation to heart rate during stress test

The adaptation lag of the QT interval after heart rate (HR) has been proposed as an arrhythmic risk marker. Most studies have quantified the QT adaptation lag in response to abrupt, step-like changes in HR induced by atrial pacing, in response to tilt test or during ambulatory recordings. Recent studies have introduced novel methods to quantify the QT adaptation lag to gradual, ramp-like HR changes in stress tests by evaluating the differences between the measured QT series and an estimated, memoryless QT series obtained from the instantaneous HR. These studies have observed the QT adaptation lag to progressively reduce when approaching the stress peak, with the underlying mechanisms being still unclear. This study analyzes the contribution of β-adrenergic stimulation to QT interval rate adaptation in response to gradual, ramp-like HR changes. We first quantify the QT adaptation lag in Coronary Artery Disease (CAD) patients undergoing stress test. To uncover the involved mechanisms, we use biophysically detailed computational models coupling descriptions of human ventricular electrophysiology and β-adrenergic signaling, from which we simulate ventricular action potentials and ECG signals. We characterize the adaptation of the simulated QT interval in response to the HR time series measured from each of the analyzed CAD patients. We show that, when the simulated ventricular tissue is subjected to a time-varying β-adrenergic stimulation pattern, with higher stimulation levels close to the stress peak, the simulated QT interval presents adaptation lags during exercise that are more similar to those measured from the patients than when subjected to constant β-adrenergic stimulation. During stress test recovery, constant and time-varying β-adrenergic stimulation patterns render similar adaptation lags, which are generally shorter than during exercise, in agreement with results from the patients. In conclusion, our findings support the role of time-varying β-adrenergic stimulation in contributing to QT interval adaptation to gradually increasing HR changes as those seen during the exercise phase of a stress test.

ECG T-Wave Morphologic Variations Predict Ventricular Arrhythmic Risk in Low- and Moderate-Risk Populations

Background Early identification of individuals at risk of sudden cardiac death (SCD) remains a major challenge. The ECG is a simple, common test, with potential for large-scale application. We developed and tested the predictive value of a novel index quantifying T-wave morphologic variations with respect to a normal reference (TMV), which only requires one beat and a single-lead ECG. Methods and Results We obtained reference T-wave morphologies from 23 962 participants in the UK Biobank study. With Cox models, we determined the association between TMV and life-threatening ventricular arrhythmia in an independent data set from UK Biobank study without a history of cardiovascular events (N=51 794; median follow-up of 122 months) and SCD in patients with coronary artery disease from ARTEMIS (N=1872; median follow-up of 60 months). In UK Biobank study, 220 (0.4%) individuals developed life-threatening ventricular arrhythmias. TMV was significantly associated with life-threatening ventricular arrhythmias (hazard ratio [HR] of 1.13 per SD increase [95% CI, 1.03-1.24]; P=0.009). In ARTEMIS, 34 (1.8%) individuals reached the primary end point. Patients with TMV ≥5 had an HR for SCD of 2.86 (95% CI, 1.40-5.84; P=0.004) with respect to those with TMV <5, independently from QRS duration, corrected QT interval, and left ventricular ejection fraction. TMV was not significantly associated with death from a cause other than SCD. Conclusions TMV identifies individuals at life-threatening ventricular arrhythmia and SCD risk using a single-beat single-lead ECG, enabling inexpensive, quick, and safe risk assessment in large populations.

Polygenic Risk Score Predicts Sudden Death in Patients With Coronary Disease and Preserved Systolic Function

BACKGROUND

A familial predisposition to sudden and/or arrhythmic death (SAD) in the setting of coronary artery disease (CAD) exists; however, the genetic basis is poorly understood.

OBJECTIVES

The purpose of this study was to determine whether a genome-wide polygenic score for coronary artery disease (GPSCAD) might have utility in SAD risk stratification in CAD patients without severe systolic dysfunction.

METHODS

A previously validated GPSCAD was generated utilizing genome-wide genotyping in 4,698 PRE-DETERMINE participants of European ancestry with CAD and left ventricular ejection fraction >30%-35%. The population was dichotomized according to top GPSCAD decile as defined by the general population, and absolute, proportional, and relative risks for SAD and non-SAD were estimated using competing risk analyses.

RESULTS

Over a median follow-up of 8.0 years, participants in the top GPSCAD decile were at elevated absolute SAD risk (8.0%; 95% CI: 5.1%-12.4% vs 4.8%; 95% CI: 3.3%-7.0%; P = 0.005) and proportional SAD risk (29% vs 16%; P = 0.0003) compared with the remainder. After controlling for left ventricular ejection fraction, clinical factors, and electrocardiogram parameters, the top GPSCAD decile was associated with SAD (subdistribution HR: 1.77; 95% CI: 1.23-2.54; P = 0.002) but not non-SAD (subdistribution HR: 1.00; 95% CI: 0.80-1.25; P = 0.98) (P for Δ = 0.003). The addition of the top GPSCAD decile to the multivariable model significantly improved net reclassification indexes (NRIs) (continuous NRI: 14.0%; P = 0.024; and categorical NRI: 6.6%; P = 0.005) but not the C-index (difference in C-index: 0.007; P = 0.143).

CONCLUSIONS

Among CAD patients without severe systolic dysfunction, high GPSCAD specifically predicted SAD and enriched for both absolute and proportional SAD risk, identifying a population who might benefit from defibrillator therapy.

A Novel Electrocardiographic Score Predicts the Severity of Coronary Artery Disease and Clinical Outcomes in Patients with Non-ST Segment Elevation Myocardial Infarction

BACKGROUND

There are many electrocardiographic (ECG) changes in non-ST segment elevation myocardial infarction (NSTEMI). However, the diagnostic power is limited in determining the severity of coronary artery disease (CAD) and clinical outcomes.

OBJECTIVE

This study investigated the role of a risk-based ECG score in predicting the severity of CAD and clinical outcomes in NSTEMI patients.

METHODS

One hundred and fifty-two patients were enrolled in the study. Severe CAD was defined as; intermediate (> 22) or high SYNTAX score (> 32), three-vessel disease, and left main coronary artery lesions. A risk-based ECG score was calculated, and the patients were categorized. All patients were followed up, and mortality and repeat revascularizations were evaluated.

RESULTS

The severe CAD group had a significantly higher risk-based ECG score than the non-severe CAD group (p = 0.013). The patients with a high risk-based ECG score had more severe CAD (p = 0.013), higher SYNTAX score (p < 0.001), more three-vessel disease (p = 0.003), coronary artery calcification (p = 0.02), and one-year mortality (p = 0.006) than those with medium or low ECG scores. Multivariate logistic regression analysis showed that a 1-point increase in the risk-based ECG score was associated with a 1.573-fold [95% confidence interval (CI): 1.111-2.227, p = 0.011] increase probability of severe CAD. Kaplan-Meier analysis demonstrated that the high-risk group had a significantly higher one-year mortality rate than the low-risk and moderate-risk groups (hazard ratio: 2.383, 95% CI: 1.395-4.072, p = 0.001).

CONCLUSIONS

This study demonstrated that higher ECG scores were associated with a higher risk of severe CAD and worse clinical outcomes in NSTEMI patients.

Incidence and Risk Factors for Cerebrovascular-Specific Mortality in Patients with Colorectal Cancer: A Registry-Based Cohort Study Involving 563,298 Patients

Simple Summary

Previous studies have shown that the occurrence of cerebrovascular-specific diseases was common in cancer patients. However, the association between colorectal cancer and cerebrovascular-specific diseases remains to be fully elucidated. In this large-population cohort study, we found that the mortality of cerebrovascular-specific diseases mortality in colorectal cancer patients was significantly higher than the general US population. In addition, we investigated several potential predictors of cerebrovascular-specific diseases mortality in colorectal cancer. This study may be useful for the prevention, risk stratification and therapeutic optimization of cerebrovascular-specific diseases in colorectal cancer patients.

Abstract

Background: Colorectal cancer (CRC) is one of the most prevalent diseases and the second leading cause of death worldwide. However, the relationship between CRC and cerebrovascular-specific mortality (CVSM) remains elusive, and less is known about the influencing factors associated with CVSM in CRC. Here, we aimed to analyze the incidence as well as the risk factors of CVSM in CRC. Methods: Patients with a primary CRC diagnosed between 1973 and 2015 were identified from the Surveillance Epidemiology and End Results database, with follow-up data available until 31 December 2016. Conditional standardized mortality ratios were calculated to compare the incidence of CVSM between CRC patients and the general U.S. population. Univariate and multivariate survival analyses with a competing risk model were used to interrogate the risk factors for CVSM. Results: A total of 563,298 CRC individuals were included. The CVSM in CRC patients was significantly higher than the general population in all age subgroups. Among the competing causes of death in patients, the cumulative mortality caused by cerebrovascular-specific diseases steadily increased during the study period. While age, surgery, other/unknown race and tumors located at the transverse colon positively influenced CVSM on both univariate and multivariate analyses, male patients and those who had radiotherapy, chemotherapy, a more recent year (2001–2015) of diagnosis, a grade II or III CRC, rectal cancer, or multiple primary or distant tumors experienced a lower risk of CVSM. Interpretation: Our data suggest a potential role for CRC in the incidence of CVSM and also identify several significant predictors of CVSM that may be helpful for risk stratification and the therapeutic optimization of cerebrovascular-specific diseases in CRC patients.

Diabetes and Risk of Sudden Death in Coronary Artery Disease Patients Without Severe Systolic Dysfunction

OBJECTIVES

This study sought to determine the absolute and relative associations of diabetes mellitus (DM) and hemoglobin A1c (HbA1c) with sudden and/or arrhythmic death (SAD) versus other modes of death in patients with coronary artery disease (CAD) who do not qualify for implantable cardioverter-defibrillators.

BACKGROUND

Patients with CAD and DM are at elevated risk for SAD; however, it is unclear whether these patients would benefit from implantable cardioverter-defibrillators given competing causes of death and/or whether HbA1c might augment SAD risk stratification.

METHODS

In the PRE-DETERMINE study of 5,764 patients with CAD with left ventricular ejection fraction (LVEF) of >30% to 35%, competing risk analyses were used to compare the absolute and relative risks of SAD versus non-SAD by DM status and HbA1c level and to identify risk factors for SAD among 1,782 patients with DM.

RESULTS

Over a median follow-up of 6.8 years, DM and HbA1c were significantly associated with SAD and non-SAD (P < 0.05 for all comparisons); however, the cumulative incidence of non-SAD (19.2%; 95% CI: 17.3%-21.2%) was almost 4 times higher than SAD (4.8%; 95% CI: 3.8%-5.9%) in DM patients. A similar pattern of absolute risk was observed across categories of HbA1c. In analyses limited to patients with DM, HbA1c was not associated with SAD, whereas low LVEF, atrial fibrillation, and electrocardiogram measurements were associated with higher SAD risk.

CONCLUSIONS

In patients with CAD and LVEF of >30% to 35%, patients with DM and/or elevated HbA1c are at much higher absolute risk of dying from non-SAD than SAD. Clinical risk markers, and not HbA1c, were associated with SAD risk in patients with DM. (PRE-DETERMINE: Biologic Markers and MRI SCD Cohort Study; NCT01114269).

Ventricular Arrhythmias in Ischemic Cardiomyopathy-New Avenues for Mechanism-Guided Treatment

Ischemic heart disease is the most common cause of lethal ventricular arrhythmias and sudden cardiac death (SCD). In patients who are at high risk after myocardial infarction, implantable cardioverter defibrillators are the most effective treatment to reduce incidence of SCD and ablation therapy can be effective for ventricular arrhythmias with identifiable culprit lesions. Yet, these approaches are not always successful and come with a considerable cost, while pharmacological management is often poor and ineffective, and occasionally proarrhythmic. Advances in mechanistic insights of arrhythmias and technological innovation have led to improved interventional approaches that are being evaluated clinically, yet pharmacological advancement has remained behind. We review the mechanistic basis for current management and provide a perspective for gaining new insights that centre on the complex tissue architecture of the arrhythmogenic infarct and border zone with surviving cardiac myocytes as the source of triggers and central players in re-entry circuits. Identification of the arrhythmia critical sites and characterisation of the molecular signature unique to these sites can open avenues for targeted therapy and reduce off-target effects that have hampered systemic pharmacotherapy. Such advances are in line with precision medicine and a patient-tailored therapy.

Diagnosis of Arrhythmia for Patients with Occult Coronary Heart Disease Guided by Intracavitary Electrocardiogram under Data Mining Algorithm

The objective of this study was to explore the application value of intracavitary electrocardiogram- (IEGM-) guided diagnosis of occult heart disease and conventional electrocardiogram (EGM) in the diagnosis of occult coronary heart disease (CHD) based on the classification and regression tree (CART) mining algorithm, hoping to provide a more effective basis for clinical diagnosis of the occult CHD. In this study, 100 patients with occult CHD admitted to our hospital from February 2016 to December 2020 were selected as the research objects. Based on the random number table method, 100 patients were randomly rolled into two groups, each with 50 cases. The patients diagnosed with conventional ECG were set as the control group, and patients in the experimental group were diagnosed with IEGM under the data mining algorithms. The diagnostic effects of the two groups were compared. The results showed that the processing effect of the CART algorithm (94%) was much better than that of the multiple linear regression algorithm (78%) and the random forest algorithm (69%) (P < 0.05), the agreement between the results of the experimental group and the results of coronary angiography (80%) and Kappa (0.7) was higher than those of the control group (55%, 0.45), and the difference was statistically significant (P < 0.05). In addition, the sensitivity (93%) and accuracy (80%) of the experimental group were obviously higher than those of the control group (62% and 55%), and the differences were remarkably significant (P < 0.05). In conclusion, the consistency ratio of the IEGM examination was higher, showing high accuracy; the intracavitary examination was invasive, so IEGM was not recommended when the diagnosis result of the examination may cause more harm than good.

The year in cardiovascular medicine 2020: arrhythmias

of the progress in arrhythmias in 2020. RACE4 and ALL-IN indicated that integrated nurse-led care improves outcomes in AF patients.3,4 The same was reported for early rhythm control therapy15 and cryoablation as initial AF treatment.25,26 Subcutaneous ICD was non-inferior to classical transvenous ICD therapy in PRAETORIAN.54 One mechanistic study showed that autoantibodies against misexpressed actin, keratin, and connexin-43 proteins create a blood-borne biomarker profile enhancing diagnosis of Brugada syndrome.50 Another mechanistic study indicated that transseptal LV pacing yields similar improvement in contractility as His bundle pacing whilst being more easy to execute.44 In PRE-DETERMINE a simple-to-use ECG risk score improved risk prediction in patients with ischemic heart disease possibly enhancing appropriate ICD therapy in high risk patients.58.

ECG Scoring for the Evaluation of Therapy-Naïve Cancer Patients to Predict Cardiotoxicity

Simple Summary

Due to improved survival upon effective anti-cancer therapies, the management of treatment-related side-effects is of increasing interest and importance. Cardiovascular side-effects of chemo-, targeted- and/or immunotherapies are common and can be harmful. To date, the identification of patients who could experience those cardiovascular side-effects prior to the anti-cancer therapy start is difficult. We show that the use of a simple electrocardiographic (ECG) score can help to predict the occurrence of cardiovascular toxicity of anti-cancer therapies.

Abstract

Objective: To evaluate a new electrocardiographic (ECG) score reflecting domains of electrical and structural alterations in therapy-naïve cancer patients to assess their risk of cardiotoxicity. Methods: We performed a retrospective analysis of 134 therapy-naïve consecutive cancer patients in our two university hospitals concerning four ECG score parameters: Contiguous Q-waves, markers of left ventricular (LV) hypertrophy, QRS duration and JTc prolongation. Cardiotoxicity was assessed after a short-term follow-up (up to 12 months). Results: Of all the patients (n = 25), 19% reached 0 points, 50% (n = 67) reached 1 point, 25% (n = 33) reached 2 points, 5% (n = 7) reached 3 points and 0.7% reached 4 or 5 points (n = 1 respectively). The incidence of cardiotoxicity (n = 28 [21%]) increased with the ECG score, with 0 points at 0%, 1 point 7.5%, 2 points 55%, 3 points 71% and ≥3 points 50%. In the ROC (Receiver operating curves) analysis, the best cut-off for predicting cardiotoxicity was an ECG score of ≥2 points (sensitivity 82%, specificity 82%, AUC 0.84, 95% CI 0.77–0.92, p < 0.0001) which was then defined as a high-risk score. High-risk patients did not differ concerning their age, LV ejection fraction, classical cardiovascular risk factors or cardiac biomarkers compared to those with a low-risk ECG score. Conclusion: ECG scoring prior to the start of anti-cancer therapies may help to identify therapy-naïve cancer patients at a higher risk for the development of cardiotoxicity.

Competing risks in patients with primary prevention implantable cardioverter-defibrillators: Global Electrical Heterogeneity and Clinical Outcomes study

BACKGROUND

Global electrical heterogeneity (GEH) is associated with sudden cardiac death in the general population. Its utility in patients with systolic heart failure who are candidates for primary prevention (PP) implantable cardioverter-defibrillators (ICDs) is unclear.

OBJECTIVE

The purpose of this study was to investigate whether GEH is associated with sustained ventricular tachycardia/ventricular fibrillation leading to appropriate ICD therapies in patients with heart failure and PP ICDs.

METHODS

We conducted a multicenter retrospective cohort study. GEH was measured by spatial ventricular gradient (SVG) direction (azimuth and elevation) and magnitude, QRS-T angle, and sum absolute QRST integral on preimplant 12-lead electrocardiograms. Survival analysis using cause-specific hazard functions compared the strength of associations with 2 competing outcomes: sustained ventricular tachycardia/ventricular fibrillation leading to appropriate ICD therapies and all-cause death without appropriate ICD therapies.

RESULTS

We analyzed 2668 patients (mean age 63 ± 12 years; 624 (23%) female; 78% white; 43% nonischemic cardiomyopathy; left ventricular ejection fraction 28% ± 11% from 6 academic medical centers). After adjustment for demographic, clinical, device, and traditional electrocardiographic characteristics, SVG elevation (hazard ratio [HR] per 1SD 1.14; 95% confidence interval [CI] 1.04-1.25; P = .004), SVG azimuth (HR per 1SD 1.12; 95% CI 1.01-1.24; P = .039), SVG magnitude (HR per 1SD 0.75; 95% CI 0.66-0.85; P < .0001), and QRS-T angle (HR per 1SD 1.21; 95% CI 1.08-1.36; P = .001) were associated with appropriate ICD therapies. Sum absolute QRST integral had different associations in infarct-related cardiomyopathy (HR 1.29; 95% CI 1.04-1.60) and nonischemic cardiomyopathy (HR 0.78; 95% CI 0.62-0.96) (P_interaction = .022).

CONCLUSION

In patients with PP ICDs, GEH is independently associated with appropriate ICD therapies. The SVG vector points in distinctly different directions in patients with 2 competing outcomes.

The electrocardiogram: are we at the dawn of a new era?

Collapse