Development and Validation of a Sudden Cardiac Death Prediction Model for the General Population

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.

Prediction of sudden cardiac death using artificial intelligence: Current status and future directions

Sudden cardiac death (SCD) remains a pressing health issue, affecting hundreds of thousands each year globally. The heterogeneity among SCD victims, ranging from individuals with severe heart failure to seemingly healthy individuals, poses a significant challenge for effective risk assessment. Conventional risk stratification, which primarily relies on left ventricular ejection fraction, has resulted in only modest efficacy of implantable cardioverter-defibrillators (ICD) for SCD prevention. In response, artificial intelligence (AI) holds promise for personalised SCD risk prediction and tailoring preventive strategies to the unique profiles of individual patients. Machine and deep learning algorithms have the capability to learn intricate non-linear patterns between complex data and defined endpoints, and leverage these to identify subtle indicators and predictors of SCD that may not be apparent through traditional statistical analysis. However, despite the potential of AI to improve SCD risk stratification, there are important limitations that need to be addressed. We aim to provide an overview of the current state-of-the-art of AI prediction models for SCD, highlight the opportunities for these models in clinical practice, and identify the key challenges hindering widespread adoption.

Comparison of the impact of longitudinal body mass index changes on cardiac arrest risk between normal and overweight populations

BACKGROUND

Being overweight is a key modifiable risk factor for cardiovascular disease. However, the impact of longitudinal changes in body mass index (BMI) on the risk of out-of-hospital cardiac arrests (OHCA) remains unclear, especially among overweight populations.

METHODS

This nested case-control study utilized data from the Korean National Health Information Database between 2009 and 2018. A total of 23 453 OHCA patients, who underwent national health check-ups within 1 and 2-4 years before OHCA occurrence, and 31 686 controls, who underwent similar national health check-ups, were included. The study population was matched for sex, age and survival status. Conditional logistic regression was employed to analyse the odds ratios (ORs) and 95% confidence intervals (CIs) of each BMI per cent change in assessing the risk of OHCA occurrence within 1 year.

RESULTS

A reverse J-shaped association between BMI per cent change and OHCA risk was observed, even among overweight populations. Among the overweight populations, weight loss significantly increased OHCA risk, with ORs (95% CI) of 4.10 (3.23-5.20) for severe weight loss (BMI decrease > 15%), 2.72 (2.33-3.17) for moderate weight loss (BMI decrease 10-15%) and 1.46 (1.35-1.59) for mild weight loss (BMI decrease 5-10%). Conversely, mild weight gain (BMI increase 5-10%) did not significantly increase OHCA risk. The impact of weight changes on the occurrence of OHCA differed by sex, being more prominent in males.

CONCLUSIONS

Significant weight changes within a 4-year period increase the risk of OHCA with a reverse J-shaped association, even among overweight and obese individuals. Maintaining a stable weight could be a reliable public health strategy irrespective of the weight status, particularly for males.

Predicting Out-of-Hospital Cardiac Arrest in the General Population Using Electronic Health Records

BACKGROUND

The majority of out-of-hospital cardiac arrests (OHCAs) occur among individuals in the general population, for whom there is no established strategy to identify risk. In this study, we assess the use of electronic health record (EHR) data to identify OHCA in the general population and define salient factors contributing to OHCA risk.

METHODS

The analytical cohort included 2366 individuals with OHCA and 23 660 age- and sex-matched controls receiving health care at the University of Washington. Comorbidities, electrocardiographic measures, vital signs, and medication prescription were abstracted from the EHR. The primary outcome was OHCA. Secondary outcomes included shockable and nonshockable OHCA. Model performance including area under the receiver operating characteristic curve and positive predictive value were assessed and adjusted for observed rate of OHCA across the health system.

RESULTS

There were significant differences in demographic characteristics, vital signs, electrocardiographic measures, comorbidities, and medication distribution between individuals with OHCA and controls. In external validation, discrimination in machine learning models (area under the receiver operating characteristic curve 0.80-0.85) was superior to a baseline model with conventional cardiovascular risk factors (area under the receiver operating characteristic curve 0.66). At a specificity threshold of 99%, correcting for baseline OHCA incidence across the health system, positive predictive value was 2.5% to 3.1% in machine learning models compared with 0.8% for the baseline model. Longer corrected QT interval, substance abuse disorder, fluid and electrolyte disorder, alcohol abuse, and higher heart rate were identified as salient predictors of OHCA risk across all machine learning models. Established cardiovascular risk factors retained predictive importance for shockable OHCA, but demographic characteristics (minority race, single marital status) and noncardiovascular comorbidities (substance abuse disorder) also contributed to risk prediction. For nonshockable OHCA, a range of salient predictors, including comorbidities, habits, vital signs, demographic characteristics, and electrocardiographic measures, were identified.

CONCLUSIONS

In a population-based case-control study, machine learning models incorporating readily available EHR data showed reasonable discrimination and risk enrichment for OHCA in the general population. Salient factors associated with OCHA risk were myriad across the cardiovascular and noncardiovascular spectrum. Public health and tailored strategies for OHCA prediction and prevention will require incorporation of this complexity.

Autopsy of all young sudden death cases is important to increase survival in family members left behind

Sudden cardiac death (SCD) is an important public health problem worldwide, accounting for an estimated 6-20% of total mortality. A significant proportion of SCD is caused by inherited heart disease, especially among the young. An autopsy is crucial to establish a diagnosis of inherited heart disease, allowing for subsequent identification of family members who require cardiac evaluation. Autopsy of cases of unexplained sudden death in the young is recommended by both the European Society of Cardiology and the American Heart Association. Overall autopsy rates, however, have been declining in many countries across the globe, and there is a lack of skilled trained pathologists able to carry out full autopsies. Recent studies show that not all cases of sudden death in the young are autopsied, likely due to financial, administrative, and organizational limitations as well as awareness among police, legal authorities, and physicians. Consequently, diagnoses of inherited heart disease are likely missed, along with the opportunity for treatment and prevention among surviving relatives. This article reviews the evidence for the role of autopsy in sudden death, how the cardiologist should interpret the autopsy-record, and how this can be integrated and implemented in clinical practice. Finally, we identify areas for future research along with potential for healthcare reform aimed at increasing autopsy awareness and ultimately reducing mortality from SCD.

Chronic nicotine exposure is associated with electrophysiological and sympathetic remodeling in the intact rabbit heart

Nicotine is the primary addictive component of tobacco products. Through its actions on the heart and autonomic nervous system, nicotine exposure is associated with electrophysiological changes and increased arrhythmia susceptibility. To assess the underlying mechanisms, we treated rabbits with transdermal nicotine (NIC, 21 mg/day) or control (CT) patches for 28 days before performing dual optical mapping of transmembrane potential (RH237) and intracellular Ca2+ (Rhod-2 AM) in isolated hearts with intact sympathetic innervation. Sympathetic nerve stimulation (SNS) was performed at the first to third thoracic vertebrae, and β-adrenergic responsiveness was additionally evaluated following norepinephrine (NE) perfusion. Baseline ex vivo heart rate (HR) and SNS stimulation threshold were higher in NIC versus CT (P = 0.004 and P = 0.003, respectively). Action potential duration alternans emerged at longer pacing cycle lengths (PCL) in NIC versus CT at baseline (P = 0.002) and during SNS (P = 0.0003), with similar results obtained for Ca2+ transient alternans. SNS shortened the PCL at which alternans emerged in CT but not in NIC hearts. NIC-exposed hearts tended to have slower and reduced HR responses to NE perfusion, but ventricular responses to NE were comparable between groups. Although fibrosis was unaltered, NIC hearts had lower sympathetic nerve density (P = 0.03) but no difference in NE content versus CT. These results suggest both sympathetic hypoinnervation of the myocardium and regional differences in β-adrenergic responsiveness with NIC. This autonomic remodeling may contribute to the increased risk of arrhythmias associated with nicotine exposure, which may be further exacerbated with long-term use.NEW & NOTEWORTHY Here, we show that chronic nicotine exposure was associated with increased heart rate, increased susceptibility to alternans, and reduced sympathetic electrophysiological responses in the intact rabbit heart. We suggest that this was due to sympathetic hypoinnervation of the myocardium and diminished β-adrenergic responsiveness of the sinoatrial node following nicotine treatment. Though these differences did not result in increased arrhythmia propensity in our study, we hypothesize that prolonged nicotine exposure may exacerbate this proarrhythmic remodeling.

Cardiac troponin I as predictor for cardiac and other mortality in the German randomized lung cancer screening trial (LUSI)

Cardiac Troponin I (cTnI) could be used to identify individuals at elevated risk of cardiac death in lung cancer (LC) screening settings. In a population-based, randomized LC screening trial in Germany ("LUSI" study) serum cTnI was measured by high-sensitivity assay in blood samples collected at baseline, and categorized into unquantifiable/low (< 6 ng/L), intermediate (≥ 6-15 ng/L), and elevated (≥ 16 ng/L). Cox proportional-hazard models were used to estimate risk of all-cause and cardiac mortality with cTnI levels. After exclusion criteria, 3653 participants were included for our analyses, of which 82.4% had low, 12.8% intermediate and 4.8% elevated cTnI, respectively. Over a median follow up of 11.87 years a total of 439 deaths occurred, including 67 caused by cardiac events. Within the first 5 years after cTnI measurement, intermediate or elevated cTnI levels showed approximately 1.7 (HR = 1.69 [95% CI 0.57-5.02) and 4.7-fold (HR = 4.66 [1.73-12.50]) increases in risk of cardiac death relative to individuals with unquantifiable/low cTnI, independently of age, sex, smoking and other risk factors. Within this time interval, a risk model based on age, sex, BMI, smoking history and cTnI showed a combined area under the ROC curve (AUC) of 73.6 (58.1-87.3), as compared to 70.4 (53.3-83.5) for a model without cTnI. Over the time interval of > 5-10 years after blood donation, the relative risk associations with cTnI and were weaker. cTnI showed no association with mortality from any other (non-cardiac) cause. Our findings show that cTnI may be of use for identifying individuals at elevated risk specifically of short-term cardiac mortality in the context of LC screening.

Risk Prediction for Sudden Cardiac Death in the General Population: A Systematic Review and Meta-Analysis

Objective: Identification of SCD risk is important in the general population from a public health perspective. The objective is to summarize and appraise the available prediction models for the risk of SCD among the general population. Methods: Data were obtained searching six electronic databases and reporting prediction models of SCD risk in the general population. Studies with duplicate cohorts and missing information were excluded from the meta-analysis. Results: Out of 8,407 studies identified, fifteen studies were included in the systematic review, while five studies were included in the meta-analysis. The Cox proportional hazards model was used in thirteen studies (96.67%). Study locations were limited to Europe and the United States. Our pooled meta-analyses included four predictors: diabetes mellitus (ES = 2.69, 95%CI: 1.93, 3.76), QRS duration (ES = 1.16, 95%CI: 1.06, 1.26), spatial QRS-T angle (ES = 1.46, 95%CI: 1.27, 1.69) and factional shortening (ES = 1.37, 95%CI: 1.15, 1.64). Conclusion: Risk prediction model may be useful as an adjunct for risk stratification strategies for SCD in the general population. Further studies among people except for white participants and more accessible factors are necessary to explore.

Deep learning-based prediction of major arrhythmic events in dilated cardiomyopathy: A proof of concept study

Prediction of major arrhythmic events (MAEs) in dilated cardiomyopathy represents an unmet clinical goal. Computational models and artificial intelligence (AI) are new technological tools that could offer a significant improvement in our ability to predict MAEs. In this proof-of-concept study, we propose a deep learning (DL)-based model, which we termed Deep ARrhythmic Prevention in dilated cardiomyopathy (DARP-D), built using multidimensional cardiac magnetic resonance data (cine videos and hypervideos and LGE images and hyperimages) and clinical covariates, aimed at predicting and tracking an individual patient's risk curve of MAEs (including sudden cardiac death, cardiac arrest due to ventricular fibrillation, sustained ventricular tachycardia lasting ≥30 s or causing haemodynamic collapse in <30 s, appropriate implantable cardiac defibrillator intervention) over time. The model was trained and validated in 70% of a sample of 154 patients with dilated cardiomyopathy and tested in the remaining 30%. DARP-D achieved a 95% CI in Harrell's C concordance indices of 0.12-0.68 on the test set. We demonstrate that our DL approach is feasible and represents a novelty in the field of arrhythmic risk prediction in dilated cardiomyopathy, able to analyze cardiac motion, tissue characteristics, and baseline covariates to predict an individual patient's risk curve of major arrhythmic events. However, the low number of patients, MAEs and epoch of training make the model a promising prototype but not ready for clinical usage. Further research is needed to improve, stabilize and validate the performance of the DARP-D to convert it from an AI experiment to a daily used tool.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Seasonal Variation in Sudden Cardiac Death: Insights from a Large United Kingdom Registry

BACKGROUND

Sudden cardiac death (SCD) is relatively common and may occur in apparently healthy individuals. The role of seasonal variation as a risk factor for SCD is poorly understood. The aim of this study was to investigate whether SCD exhibits a predilection for specific seasons.

METHODS

We reviewed a database of 4751 cases of SCD (mean age 38 ± 17 years) referred to our Center for Cardiac Pathology at St George's University of London between 2000 and 2018. Clinical information was obtained from referring coroners who were asked to complete a detailed questionnaire. All cases underwent macroscopic and histological evaluation of the heart, by expert cardiac pathologists.

RESULTS

SCD was more common during winter (26%) and rarer during summer (24%), p = 0.161. Significant seasonal variation was not observed among cases of sudden arrhythmic death syndrome (SADS, 2910 cases) in which the heart is structurally normal. In contrast, a significant difference in seasonal distribution among decedents exhibiting cardiac structural abnormalities at the post-mortem examination (n = 1841) was observed. In this subgroup, SCDs occurred more frequently during winter (27 %) compared to summer (22%) (p = 0.007). In cases diagnosed with a myocardial disease (n = 1399), SCD was most common during the winter (27%) and least common during the summer (22%) (p = 0.027).

CONCLUSIONS

While SADS occurs throughout the year with no seasonal variation, SCD due to structural heart disease appears to be more common during the winter. Bio-meteorological factors may be potential triggers of SCD in individuals with an underlying structural cardiac abnormality.

Predicting 1-, 3-, 5-, and 8-year all-cause mortality in a community-dwelling older adult cohort: relevance for predictive, preventive, and personalized medicine

BACKGROUND

Population aging is a global public health issue involving increased prevalence of age-related diseases, and concomitant burden on medical resources and the economy. Ninety-two diseases have been identified as age-related, accounting for 51.3% of the global adult disease burden. The economic cost per capita for older people over 60 years is 10 times that of the younger population. From the aspects of predictive, preventive, and personalized medicine (PPPM), developing a risk-prediction model can help identify individuals at high risk for all-cause mortality and provide an opportunity for targeted prevention through personalized intervention at an early stage. However, there is still a lack of predictive models to help community-dwelling older adults do well in healthcare.

OBJECTIVES

This study aims to develop an accurate 1-, 3-, 5-, and 8-year all-cause mortality risk-prediction model by using clinical multidimensional variables, and investigate risk factors for 1-, 3-, 5-, and 8-year all-cause mortality in community-dwelling older adults to guide primary prevention.

METHODS

This is a two-center cohort study. Inclusion criteria: (1) community-dwelling adult, (2) resided in the districts of Chaonan or Haojiang for more than 6 months in the past 12 months, and (3) completed a health examination. Exclusion criteria: (1) age less than 60 years, (2) more than 30 incomplete variables, (3) no signed informed consent. The primary outcome of the study was all-cause mortality obtained from face-to-face interviews, telephone interviews, and the medical death database from 2012 to 2021. Finally, we enrolled 5085 community-dwelling adults, 60 years and older, who underwent routine health screening in the Chaonan and Haojiang districts, southern China, from 2012 to 2021. Of them, 3091 participants from Chaonan were recruited as the primary training and internal validation study cohort, while 1994 participants from Haojiang were recruited as the external validation cohort. A total of 95 clinical multidimensional variables, including demographics, lifestyle behaviors, symptoms, medical history, family history, physical examination, laboratory tests, and electrocardiogram (ECG) data were collected to identify candidate risk factors and characteristics. Risk factors were identified using least absolute shrinkage and selection operator (LASSO) models and multivariable Cox proportional hazards regression analysis. A nomogram predictive model for 1-, 3-, 5- and 8-year all-cause mortality was constructed. The accuracy and calibration of the nomogram prediction model were assessed using the concordance index (C-index), integrated Brier score (IBS), receiver operating characteristic (ROC), and calibration curves. The clinical validity of the model was assessed using decision curve analysis (DCA).

RESULTS

Nine independent risk factors for 1-, 3-, 5-, and 8-year all-cause mortality were identified, including increased age, male, alcohol status, higher daily liquor consumption, history of cancer, elevated fasting glucose, lower hemoglobin, higher heart rate, and the occurrence of heart block. The acquisition of risk factor criteria is low cost, easily obtained, convenient for clinical application, and provides new insights and targets for the development of personalized prevention and interventions for high-risk individuals. The areas under the curve (AUC) of the nomogram model were 0.767, 0.776, and 0.806, and the C-indexes were 0.765, 0.775, and 0.797, in the training, internal validation, and external validation sets, respectively. The IBS was less than 0.25, which indicates good calibration. Calibration and decision curves showed that the predicted probabilities were in good agreement with the actual probabilities and had good clinical predictive value for PPPM.

CONCLUSION

The personalized risk prediction model can identify individuals at high risk of all-cause mortality, help offer primary care to prevent all-cause mortality, and provide personalized medical treatment for these high-risk individuals from the PPPM perspective. Strict control of daily liquor consumption, lowering fasting glucose, raising hemoglobin, controlling heart rate, and treatment of heart block could be beneficial for improving survival in elderly populations.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13167-023-00342-4.

Family history, socioeconomic factors, comorbidities, health behaviors, and the risk of sudden cardiac arrest

Genetic, environment, and behaviour factors have a role in causing sudden cardiac arrest (SCA). We aimed to determine the strength of the association between various risk factors and SCA incidence. We conducted a multicentre case-control study at 17 hospitals in Korea from September 2017 to December 2020. The cases included out-of-hospital cardiac arrest aged 19-79 years with presumed cardiac aetiology. Community-based controls were recruited at a 1:1 ratio after matching for age, sex, and urban residence level. Multivariable conditional logistic regression analysis was conducted. Among the 1016 cases and 1731 controls, 948 cases and 948 controls were analysed. A parental history of SCA, low educational level, own heart disease, current smoking, and non-regular exercise were associated with SCA incidence (Adjusted odds ratio [95% confidence interval]: 2.51 [1.48-4.28] for parental history of SCA, 1.37 [1.38-2.25] for low edication level, 3.77 [2.38-5.90] for non-coronary artery heart disease, 4.47 [2.84-7.03] for coronary artery disease, 1.39 [1.08-1.79] for current smoking, and 4.06 [3.29-5.02] for non-regular exercise). Various risk factors related to genetics, environment, and behaviour were independently associated with the incidence of SCA. Establishing individualised SCA prevention strategies in addition to general prevention strategies is warranted.

Out-of-Hospital Cardiac Arrest in Individuals With Human Immunodeficiency Virus: A Nationwide Population-Based Cohort Study

BACKGROUND

Little data exist on the risk and outcomes of out-of-hospital cardiac arrest (OHCA) in people with HIV (PWH). We aimed to describe OHCA in PWH as compared with the general population in terms of incidence, characteristics, and survival.

METHODS

This nationwide study assessed all individuals aged 18-85 years between 2001 and 2019 in Denmark. The cumulative incidence of OHCA was computed using cause-specific Cox models accounting for competing risk of death.

RESULTS

Among 6 565 309 individuals, 6 925 (median age: 36; interquartile range [IQR]: 28-44 y; 74% males) were infected at some point with HIV. The incidence of OHCA was 149 (95% CI: 123-180)/100 000 person-years in PWH versus 64 (95% CI: 64-65)/100 000 person-years in people without HIV (P < .001). Age at the time of cardiac arrest was 52 (IQR: 44-61) years in PWH versus 69 (IQR: 59-77) years in individuals without HIV (P < .001). In a multivariable model adjusted for age, sex, hypertension, diabetes, heart failure, ischemic heart disease, atrial fibrillation, chronic obstructive pulmonary disease, cancer, and renal failure, PWH had a 2-fold higher risk of OHCA (hazard ratio: 2.84; 95% CI: 2.36-3.43; P < .001). Thirty-day mortality (89% vs 88%; P = .80) was comparable to individuals without HIV.

CONCLUSIONS

HIV is an independent risk factor for OHCA, and those who experience OHCA with HIV are much younger than those without HIV. Almost 90% of PWH died 1 month after OHCA. Further research should strive to find out how to reduce OHCA occurrence in this population.

Chronic nicotine exposure is associated with electrophysiological and sympathetic remodeling in the intact rabbit heart

Nicotine is the primary addictive component in tobacco products. Through its actions on the heart and autonomic nervous system, nicotine exposure is associated with electrophysiological changes and increased arrhythmia susceptibility. However, the underlying mechanisms are unclear. To address this, we treated rabbits with transdermal nicotine (NIC, 21 mg/day) or control (CT) patches for 28 days prior to performing dual optical mapping of transmembrane potential (RH237) and intracellular Ca 2+ (Rhod-2 AM) in isolated hearts with intact sympathetic innervation. Sympathetic nerve stimulation (SNS) was performed at the 1 st - 3 rd thoracic vertebrae, and β-adrenergic responsiveness was additionally evaluated as changes in heart rate (HR) following norepinephrine (NE) perfusion. Baseline ex vivo HR and SNS stimulation threshold were increased in NIC vs. CT ( P = 0.004 and P = 0.003 respectively). Action potential duration alternans emerged at longer pacing cycle lengths (PCL) in NIC vs. CT at baseline ( P = 0.002) and during SNS ( P = 0.0003), with similar results obtained for Ca 2+ transient alternans. SNS reduced the PCL at which alternans emerged in CT but not NIC hearts. NIC exposed hearts also tended to have slower and reduced HR responses to NE perfusion. While fibrosis was unaltered, NIC hearts had lower sympathetic nerve density ( P = 0.03) but no difference in NE content vs. CT. These results suggest both sympathetic hypo-innervation of the myocardium and diminished β-adrenergic responsiveness with NIC. This autonomic remodeling may underlie the increased risk of arrhythmias associated with nicotine exposure, which may be further exacerbated with continued long-term usage.

NEW & NOTEWORTHY

Here we show that chronic nicotine exposure was associated with increased heart rate, lower threshold for alternans and reduced sympathetic electrophysiological responses in the intact rabbit heart. We suggest that this was due to the sympathetic hypo-innervation of the myocardium and diminished β- adrenergic responsiveness observed following nicotine treatment. Though these differences did not result in increased arrhythmia propensity in our study, we hypothesize that prolonged nicotine exposure may exacerbate this pro-arrhythmic remodeling.

Risk Factors for Sudden Cardiac Arrest Among Hispanic or Latino Adults in Southern California: Ventura PRESTO and HCHS/SOL

Background Out-of-hospital sudden cardiac arrest (SCA) is a leading cause of mortality, making prevention of SCA a public health priority. No studies have evaluated predictors of SCA risk among Hispanic or Latino individuals in the United States. Methods and Results In this case-control study, adult SCA cases ages 18-85 (n=1,468) were ascertained in the ongoing Ventura Prediction of Sudden Death in Multi-Ethnic Communities (PRESTO) study (2015-2021) in Ventura County, California. Control subjects were selected from 3033 Hispanic or Latino participants who completed Visit 2 examinations (2014-2017) at the San Diego site of the HCHS/SOL (Hispanic Community Health Survey/Study of Latinos). We used logistic regression to evaluate the association of clinical factors with SCA. Among Hispanic or Latino SCA cases (n=295) and frequency-matched HCHS/SOL controls (n=590) (70.2% men with mean age 63.4 and 61.2 years, respectively), the following clinical variables were associated with SCA in models adjusted for age, sex, and other clinical variables: chronic kidney disease (odds ratio [OR], 7.3 [95% CI, 3.8-14.3]), heavy drinking (OR, 4.5 [95% CI, 2.3-9.0]), stroke (OR, 3.1 [95% CI, 1.2-8.0]), atrial fibrillation (OR, 3.7 [95% CI, 1.7-7.9]), coronary artery disease (OR, 2.9 [95% CI, 1.5-5.9]), heart failure (OR, 2.5 [95% CI, 1.2-5.1]), and diabetes (OR, 1.5 [95% CI, 1.0-2.3]). Conclusions In this first population-based study, to our knowledge, of SCA risk predictors among Hispanic or Latino adults, chronic kidney disease was the strongest risk factor for SCA, and established cardiovascular disease was also important. Early identification and management of chronic kidney disease may reduce SCA risk among Hispanic or Latino individuals, in addition to prevention and treatment of cardiovascular disease.

The Lancet Commission to reduce the global burden of sudden cardiac death: a call for multidisciplinary action

Despite major advancements in cardiovascular medicine, sudden cardiac death (SCD) continues to be an enormous medical and societal challenge, claiming millions of lives every year. Efforts to prevent SCD are hampered by imperfect risk prediction and inadequate solutions to specifically address arrhythmogenesis. Although resuscitation strategies have witnessed substantial evolution, there is a need to strengthen the organisation of community interventions and emergency medical systems across varied locations and health-care structures. With all the technological and medical advances of the 21st century, the fact that survival from sudden cardiac arrest (SCA) remains lower than 10% in most parts of the world is unacceptable. Recognising this urgent need, the Lancet Commission on SCD was constituted, bringing together 30 international experts in varied disciplines. Consistent progress in tackling SCD will require a completely revamped approach to SCD prevention, with wide-sweeping policy changes that will empower the development of both governmental and community-based programmes to maximise survival from SCA, and to comprehensively attend to survivors and decedents' families after the event. International collaborative efforts that maximally leverage and connect the expertise of various research organisations will need to be prioritised to properly address identified gaps. The Commission places substantial emphasis on the need to develop a multidisciplinary strategy that encompasses all aspects of SCD prevention and treatment. The Commission provides a critical assessment of the current scientific efforts in the field, and puts forth key recommendations to challenge, activate, and intensify efforts by both the scientific and global community with new directions, research, and innovation to reduce the burden of SCD worldwide.

Elevated serum albumin-to-creatinine ratio as a protective factor on outcomes after heart transplantation

Background

The purpose of this study was to investigate the prognostic significance of serum albumin to creatinine ratio (ACR) in patients receiving heart transplantation of end-stage heart failure.

Methods

From January 2015 to December 2020, a total of 460 patients who underwent heart transplantation were included in this retrospective analysis. According to the maximum Youden index, the optimal cut-off value was identified. Kaplan-Meier methods were used to describe survival rates, and multivariable analyses were conducted with Cox proportional hazard models. Meanwhile, logistic regression analysis was applied to evaluate predictors for postoperative complications. The accuracy of risk prediction was evaluated by using the concordance index (C-index) and calibration plots.

Results

The optimal cut-off value was 37.54 for ACR. Univariable analysis indicated that recipient age, IABP, RAAS, BB, Hb, urea nitrogen, D-dimer, troponin, TG, and ACR were significant prognostic factors of overall survival (OS). Multivariate analysis showed that preoperative ACR (HR: 0.504, 95% = 0.352-0.722, P < 0.001) was still an independent prognostic factor of OS. The nomogram for predicting 1-year and 5-year OS in patients who underwent heart transplantation without ACR (C-index = 0.631) and with ACR (C-index = 0.671). Besides, preoperative ACR level was a significant independent predictor of postoperative respiratory complications, renal complications, liver injury, infection and in-hospital death. Moreover, the calibration plot showed good consistency between the predictions by the nomogram for OS and the actual outcomes.

Conclusion

Our research showed that ACR is a favorable prognostic indicator in patients of heart transplantation.

Incremental Value of Right Ventricular Outflow Tract Diameter in Risk Assessment of Chronic Heart Failure Patients with Implantable Cardioverter Defibrillators: Development of RVOTD-ICD Benefit Score in Real-World Setting

Background

Left ventricular ejection fraction (LVEF) remains the basic reference for the prevention of sudden cardiac death (SCD) patients, while right ventricular (RV) abnormalities have now been associated with SCD risk. A modified benefit assessment tool incorporating RV function parameters in consideration of implantable cardioverter defibrillators (ICD) insertion should be taken into account.

Methods

We enrolled 954 chronic heart failure (CHF) patients (age 58.8 ± 13.1 years; 79.0% male) with quantitative measurements of right ventricular outflow tract diameter (RVOTD) before ICD implantation and then divided them according to the median level of RVOTD. The predictive value of RVOTD in life-threatening ventricular tachycardia (VT)/ventricular fibrillation (VF) vs. non-arrhythmic mortality (defined as death without prior sustained VT/VF), was evaluated respectively. Based on RVOTD and other identified risk factors, a simple risk assessment tool, RVOTD-ICD benefit score, was developed.

Results

A higher RVOTD level was significantly associated with an increased risk of VT/VF (per 1 standard deviation (SD) increase, hazard ratio [HR], 1.22; 95% confidence interval [CI], 1.11-1.33; p = 0.002) but not non-arrhythmic mortality (per 1 SD increase, hazard ratio, 0.93; 95% CI, 0.66-1.33; p = 0.709) after multivariable adjustment. Three benefit groups were created based on RVOTD-ICD benefit score, which was calculated from VT/VF score (younger age, higher RVOTD, diuretic use, prior non-sustainable VT, prior sustainable VT/VF) and non-arrhythmic mortality scores (older age, renin-angiotensin-aldosterone system inhibitors use, diabetes, higher left ventricular end-diastolic diameter, New York Heart Association III/IV, higher N-terminal pro-B-type natriuretic peptide levels). In the highest RVOTD-ICD benefit group, the 3-year risk of VT/VF was nearly 8-fold higher than the corresponding risk of non-arrhythmic mortality (39.2% vs. 4.8%, p < 0.001). On the contrary, the 3-year risk of VT/VF was similar to the risk of non-arrhythmic mortality (21.9% vs. 21.3%, p = 0.405) in the lowest benefit group. RVOTD-ICD benefit score system yielded improvement in discrimination for VT/VF, non-arrhythmic mortality, and all-cause mortality than Multicenter Automatic Defibrillator Implantation Trial (MADIT)-ICD benefit score in this cohort.

Conclusions

Higher RVOTD was associated with significantly increased risk of sustained VT/VF in CHF patients. A simple risk assessment tool incorporating RVOTD (RVOTD-ICD benefit score) could be generalized to ICD populations, and optimize the decision-making process of ICD implantation.

Proteomic cardiovascular risk assessment in chronic kidney disease

AIMS

Chronic kidney disease (CKD) is widely prevalent and independently increases cardiovascular risk. Cardiovascular risk prediction tools derived in the general population perform poorly in CKD. Through large-scale proteomics discovery, this study aimed to create more accurate cardiovascular risk models.

METHODS AND RESULTS

Elastic net regression was used to derive a proteomic risk model for incident cardiovascular risk in 2182 participants from the Chronic Renal Insufficiency Cohort. The model was then validated in 485 participants from the Atherosclerosis Risk in Communities cohort. All participants had CKD and no history of cardiovascular disease at study baseline when ∼5000 proteins were measured. The proteomic risk model, which consisted of 32 proteins, was superior to both the 2013 ACC/AHA Pooled Cohort Equation and a modified Pooled Cohort Equation that included estimated glomerular filtrate rate. The Chronic Renal Insufficiency Cohort internal validation set demonstrated annualized receiver operating characteristic area under the curve values from 1 to 10 years ranging between 0.84 and 0.89 for the protein and 0.70 and 0.73 for the clinical models. Similar findings were observed in the Atherosclerosis Risk in Communities validation cohort. For nearly half of the individual proteins independently associated with cardiovascular risk, Mendelian randomization suggested a causal link to cardiovascular events or risk factors. Pathway analyses revealed enrichment of proteins involved in immunologic function, vascular and neuronal development, and hepatic fibrosis.

CONCLUSION

In two sizeable populations with CKD, a proteomic risk model for incident cardiovascular disease surpassed clinical risk models recommended in clinical practice, even after including estimated glomerular filtration rate. New biological insights may prioritize the development of therapeutic strategies for cardiovascular risk reduction in the CKD population.

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.

Validation of the ARIC prediction model for sudden cardiac death in the European population: The ESCAPE-NET project: Predicting sudden cardiac death in European adults

BACKGROUND

Sudden cardiac death is responsible for 10-20% of all deaths in Europe. The current study investigates how well the risk of sudden cardiac death can be predicted. To this end, we validated a previously developed prediction model for sudden cardiac death from the Atherosclerosis Risk in Communities study (USA).

METHODS

Data from participants of the Copenhagen City Heart Study (CCHS) (n=9988) was used to externally validate the previously developed prediction model for sudden cardiac death. The model's performance was assessed through discrimination (C-statistic) and calibration by the Hosmer-Lemeshow goodness-of-fit (HL) statistics suited for censored data and visual inspection of calibration plots. Additional validation was performed using data from the Hoorn Study (N=2045), employing the same methods.

RESULTS

During ten years of follow-up of CCHS participants (mean age: 58.7 years, 56.2% women), 425 experienced SCD (4.2%). The prediction model showed good discrimination for sudden cardiac death risk (C-statistic: 0.81, 95% CI:0.79-0.83). Calibration was robust (HL statistic: p=0.8). Visual inspection of the calibration plot showed that the calibration could be improved. Sensitivity was 89.8%, and specificity was 60.6%. The positive and negative predictive values were 10.1% and 99.2%. Model performance was similar in the Hoorn Study (C-statistic: 0.81, 95% CI: 0.77-0.85 and the HL statistic: 1.00).

CONCLUSION

Our study showed that the previously developed prediction model in North American adults performs equally well in identifying those at risk for sudden cardiac death in a general North-West European population. However, the positive predictive value is low.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Increased Epicardial Adipose Tissue (EAT), Left Coronary Artery Plaque Morphology, and Valvular Atherosclerosis as Risks Factors for Sudden Cardiac Death from a Forensic Perspective

Background: In sudden cardiac deaths (SCD), visceral adipose tissue has begun to manifest interest as a standalone cardiovascular risk factor. Studies have shown that epicardial adipose tissue can be seen as a viable marker of coronary atherosclerosis. This study aimed to evaluate, from a forensic perspective, the correlation between body mass index (BMI), heart weight, coronary and valvular atherosclerosis, left ventricular morphology, and the thickness of the epicardial adipose tissue (EAT) in sudden cardiac deaths, establishing an increased thickness of EAT as a novel risk factor. Methods: This is a retrospective case−control descriptive study that included 80 deaths that were autopsied, 40 sudden cardiac deaths, and 40 control cases who hanged themselves and had unknown pathologies prior to their death. In all the autopsies performed, the thickness of the epicardial adipose tissue was measured in two regions of the left coronary artery, and the left ventricular morphology, macro/microscopically quantified coronary and valvular atherosclerosis, and weight of the heart were evaluated. Results: This study revealed a higher age in the SCD group (58.82 ± 9.67 vs. 53.4 ± 13.00; p = 0.03), as well as a higher incidence in females (p = 0.03). In terms of heart and coronary artery characteristics, there were higher values of BMI (p = 0.0009), heart weight (p < 0.0001), EAT of the left circumflex artery (LCx) (p < 0.0001), and EAT of the left anterior descending artery (LAD) (p < 0.0001). In the multivariate analysis, a high baseline value of BMI (OR: 4.05; p = 0.004), heart weight (OR: 5.47; p < 0.001), EAT LCx (OR: 23.72; p < 0.001), and EAT LAD (OR: 21.07; p < 0.001) were strong independent predictors of SCD. Moreover, age over 55 years (OR: 2.53; p = 0.045), type Vb plaque (OR: 17.19; p < 0.001), mild valvular atherosclerosis (OR: 4.88; p = 0.002), and moderate left ventricle dilatation (OR: 16.71; p = 0.008) all act as predictors of SCD. Conclusions: The data of this research revealed that higher baseline values of BMI, heart weight, EAT LCx, and EAT LAD highly predict SCD. Furthermore, age above 55 years, type Vb plaque, mild valvular atherosclerosis, and left ventricle dilatation were all risk factors for SCD.

Incidence of Sudden Cardiac Death in the European Union

BACKGROUND

Although sudden cardiac death (SCD) is recognized as a high-priority public health topic, reliable estimates of the incidence of SCD or, more broadly, out-of-hospital cardiac arrest (OHCA), in the population are scarce, especially in the European Union.

OBJECTIVES

The study objective was to determine the incidence of SCD and OHCA in the European Union.

METHODS

The study examined 4 large (ie, >2 million inhabitants) European population-based prospective registries collecting emergency medical services (EMS)-attended (ie, with attempted resuscitation) OHCA and SCD (OHCA without obvious extracardiac causes) for >5 consecutive years from January 2012 to December 2017 in the Paris region (France), the North Holland region (the Netherlands), the Stockholm region (Sweden), and in all of Denmark.

RESULTS

The average annual incidence of SCD in the 4 registries ranged from 36.8 per 100,000 (95% CI: 23.5-50.1 per 100,000) to 39.7 per 100,000 (95% CI: 32.6-46.8 per 100,000). When extrapolating to each European country and accounting for age and sex, this yields to 249,538 SCD cases per year (95% CI: 155,377-343,719 SCD cases per year). The average annual incidence of OHCA in the 4 registries ranged from 47.8 per 100,000 (95% CI: 21.2-74.4 per 100,000) to 57.9 per 100,000 (95% CI: 19.6-96.3 per 100,000), corresponding to 343,496 OHCA cases per year (95% CI: 216,472-464,922 OHCA cases per year) in the European Union. Incidence rates of SCD and OHCA increased with age and were systematically higher in men compared with women.

CONCLUSIONS

By combining data from 4 large, population-based registries with at least 5 years of data collection, this study provided an estimate of the incidence of SCD and OHCA in the European Union.

Prediction of Sudden Cardiac Death Manifesting With Documented Ventricular Fibrillation or Pulseless Ventricular Tachycardia

OBJECTIVES

This study aimed to develop a novel clinical prediction algorithm for avertable sudden cardiac death.

BACKGROUND

Sudden cardiac death manifests as ventricular fibrillation (VF)/ ventricular tachycardia (VT) potentially treatable with defibrillation, or nonshockable rhythms (pulseless electrical activity/asystole) with low likelihood of survival. There are no available clinical risk scores for targeted prediction of VF/VT.

METHODS

Subjects with out-of-hospital sudden cardiac arrest presenting with documented VF or pulseless VT (33% of total cases) were ascertained prospectively from the Portland, Oregon, metro area with population ≈1 million residents (n = 1,374, 2002-2019). Comparisons of lifetime clinical records were conducted with a control group (n = 1,600) with ≈70% coronary disease prevalence. Prediction models were constructed from a training dataset using backwards stepwise logistic regression and applied to an internal validation dataset. Receiver operating characteristic curves (C statistic) were used to evaluate model discrimination. External validation was performed in a separate, geographically distinct population (Ventura County, California, population ≈850,000, 2015-2020).

RESULTS

A clinical algorithm (VFRisk) constructed with 13 clinical, electrocardiogram, and echocardiographic variables had very good discrimination in the training dataset (C statistic = 0.808; [95% CI: 0.774-0.842]) and was successfully validated in internal (C statistic = 0.776 [95% CI: 0.725-0.827]) and external (C statistic = 0.782 [95% CI: 0.718-0.846]) datasets. The algorithm substantially outperformed the left ventricular ejection fraction (LVEF) ≤35% (C statistic = 0.638) and performed well across the LVEF spectrum.

CONCLUSIONS

An algorithm for prediction of sudden cardiac arrest manifesting with VF/VT was successfully constructed using widely available clinical and noninvasive markers. These findings have potential to enhance primary prevention, especially in patients with mid-range or preserved LVEF.

Sex differences in sudden cardiac death in a nationwide study of 54 028 deaths

Objective

Sudden cardiac death (SCD) is a leading cause of death and is more common among males than females. Epidemiological studies of sex differences in SCD cases of all ages are sparse. The aim of this study was to examine differences in incidence rates, clinical characteristics, comorbidities and autopsy findings between male and female SCD cases.

Methods

All deaths in Denmark in 2010 (54 028) were reviewed. Autopsy reports, death certificates, discharge summaries and nationwide health registries were reviewed to identify cases of SCD. Based on the available information, all deaths were subcategorised into definite, probable and possible SCD.

Results

A total of 6867 SCD cases were identified, of which 3859 (56%) were males and 3008 (44%) were females. Incidence rates increased with age and were higher for male population across all age groups in the adult population. Average age at time of SCD was 71 years among males compared with 79 among females (p<0.01). The greatest difference in SCD incidence between males and females was found among the 35–50 years group with an incidence rate ratio of 3.7 (95% CI: 2.8 to 4.8). Compared with female SCD victims, male SCD victims more often had cardiovascular diseases and diabetes mellitus (p<0.01).

Conclusion

This is the first nationwide study of sex differences in SCD across all ages. Differences in incidence rates between males and females were greatest among young adults and the middle-aged. Incidence rates of SCD among older female population approached that of the male population, despite having significantly more cardiovascular disease and diabetes in male SCD cases.

Strategies for Sudden Cardiac Death Prevention

Sudden cardiac death (SCD) represents a major challenge in modern medicine. The prevention of SCD orbits on two levels, the general population level and individual level. Much research has been done with the aim to improve risk stratification of SCD, although no radical changes in evidence and in therapeutic strategy have been achieved. Artificial intelligence (AI), and in particular machine learning (ML) models, represent novel technologic tools that promise to improve predictive ability of fatal arrhythmic events. In this review, firstly, we analyzed the electrophysiological basis and the major clues of SCD prevention at population and individual level; secondly, we reviewed the main research where ML models were used for risk stratification in other field of cardiology, suggesting its potentiality in the field of SCD prevention.

N-Terminal Pro-B-Type Natriuretic Peptide in Risk Stratification of Heart Failure Patients With Implantable Cardioverter-Defibrillator

Background

The prognostic value of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in heart failure (HF) is well-established. However, whether it could facilitate the risk stratification of HF patients with implantable cardioverter-defibrillator (ICD) is still unclear.

Objective

To determine the associations between baseline NT-proBNP and outcomes of all-cause mortality and first appropriate shock due to sustained ventricular tachycardia/ventricular fibrillation (VT/VF) in ICD recipients.

Methods and results

N-terminal pro-B-type natriuretic peptide was measured before ICD implant in 500 patients (mean age 60.2 ± 12.0 years; 415 (83.0%) men; 231 (46.2%) Non-ischemic dilated cardiomyopathy (DCM); 136 (27.2%) primary prevention). The median NT-proBNP was 854.3 pg/ml (interquartile range [IQR]: 402.0 to 1,817.8 pg/ml). We categorized NT-proBNP levels into quartiles and used a restricted cubic spline to evaluate its nonlinear association with outcomes. The incidence rates of mortality and first appropriate shock were 5.6 and 9.1%, respectively. After adjusting for confounding factors, multivariable Cox regression showed a rise in NT-proBNP was associated with an increased risk of all-cause mortality. Compared with the lowest quartile, the hazard ratios (HRs) with 95% CI across increasing quartiles were 1.77 (0.71, 4.43), 3.98 (1.71, 9.25), and 5.90 (2.43, 14.30) for NT-proBNP (p for trend &lt; 0.001). A restricted cubic spline demonstrated a similar pattern with an inflection point found at 3,231.4 pg/ml, beyond which the increase in NT-proBNP was not associated with increased mortality (p for nonlinearity &lt; 0.001). Fine-Gray regression was used to evaluate the association between NT-proBNP and first appropriate shock accounting for the competing risk of death. In the unadjusted, partial, and fully adjusted analysis, however, no significant association could be found regardless of NT-proBNP as a categorical variable or log-transformed continuous variable (all p &gt; 0.05). No nonlinearity was found, either (p = 0.666). Interactions between NT-proBNP and predefined factors were not found (all p &gt; 0.1).

Conclusion

In HF patients with ICD, the rise in NT-proBNP is independently associated with increased mortality until it reaches the inflection point. However, its association with the first appropriate shock was not found. Patients with higher NT-proBNP levels might derive less benefit from ICD implant.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Cardiovascular Events and Long-Term Risk of Sudden Death Among Stabilized Patients After Acute Coronary Syndrome: Insights From IMPROVE-IT

Background

Unlike patients with low ejection fraction after an acute coronary syndrome (ACS), little is known about the long‐term incidence and influence of cardiovascular events before sudden death among stabilized patients after ACS.

Methods and Results

A total of 18 144 patients stabilized within 10 days after ACS in IMPROVE‐IT (Improved Reduction of Outcomes: Vytorin Efficacy International Trial) were studied. Cumulative incidence rates (IRs) and IRs per 100 patient‐years of sudden death were calculated. Using Cox proportional hazards, the association of ≥1 additional postrandomization cardiovascular events (myocardial infarction, stroke, and hospitalization for unstable angina or heart failure) with sudden death was examined. Early (≤1 year after ACS) and late sudden deaths (>1 year) were compared. Of 2446 total deaths, 402 (16%) were sudden. The median time to sudden death was 2.7 years, with 109 early and 293 late sudden deaths. The cumulative IR was 2.47% (95% CI, 2.23%–2.73%) at 7 years of follow‐up. The risk of sudden death following a postrandomization cardiovascular event (150/402 [37%] sudden deaths; median 1.4 years) was greater (IR/100 patient‐years, 1.45 [95% CI, 1.23–1.69]) than the risk with no postrandomization cardiovascular event (IR/100 patient‐years, 0.27 [95% CI, 0.24–0.30]). Postrandomization myocardial infarction (hazard ratio [HR], 3.64 [95% CI, 2.85–4.66]) and heart failure (HR, 4.55 [95% CI, 3.33–6.22]) significantly increased future risk of sudden death.

Conclusions

Patients stabilized within 10 days of an ACS remain at long‐term risk of sudden death with the greatest risk in those with an additional cardiovascular event. These results refine the long‐term risk and risk effectors of sudden death, which may help clinicians identify opportunities to improve care.

Registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00202878.

Diagnostic and therapeutic characteristics of diabetes mellitus and risk of out-of-hospital cardiac arrest

This study aimed to evaluate the risks of diabetes mellitus (DM) on out-of-hospital cardiac arrest (OHCA) and to investigate whether the risks of DM on OHCA varied according to the diagnostic and therapeutic characteristics of diabetes. We conducted a multicenter prospective case–control study in 17 University hospitals in Korea from September 2017 to December 2020. Cases were EMS-treated OHCA patients aged 20 to 79 with a presumed cardiac etiology. Community-based controls were recruited at a 1:2 ratio after matching for age, sex, and urbanization level of residence. A structured questionnaire and laboratory findings were collected from cases and controls. Multivariable conditional logistic regression analyses were conducted to estimate the risk of DM on OHCA by characteristics. A total of 772 OHCA cases and 1544 community-based controls were analyzed. A total of 242 (31.3%) OHCAs and 292 (18.9%) controls were previously diagnosed with DM. The proportions of type I DM (10.7% vs. 2.1%) and insulin therapy (15.3% vs. 6.5%) were higher in OHCAs with DM than in controls with DM. The duration of DM was longer in OHCAs than in controls (median 12 vs. 7 years). DM was associated with an increased risk of OHCA (aOR (95% CI), 2.13 (1.64–2.75)). Compared to the no diabetes group, the risks of OHCA increased in the diabetes patients with type I DM (5.26 (1.72–16.08)) and type II DM group (1.63 (1.18–2.27)), a long duration of DM prevalence (1.04 (1.02–1.06) per 1-year prevalence duration), and a high HbA1c level (1.38 (1.19–1.60) per 1% increase). By treatment modality, the aOR (95% CI) was lowest in the oral hypoglycemic agent (1.47 (1.08–2.01)) and highest in the insulin (6.63 (3.04–14.44)) groups. DM was associated with an increased risk of OHCA, and the risk magnitudes varied according to the diagnostic and therapeutic characteristics.

Epidemiology and risk factors of sudden cardiac arrest

PURPOSE OF REVIEW

Sudden cardiac arrest (SCA) remains a major health burden around the globe, most often occurring in the community (out-of-hospital cardiac arrest [OHCA]). SCA accounts for 15-20% of all natural deaths in adults in the USA and Western Europe, and up to 50% of all cardiovascular deaths. To reduce this burden, more knowledge is needed about its key facets such as its incidence in various geographies, its risk factors, and the populations that may be at risk.

RECENT FINDINGS

SCA results from a complex interaction of inherited and acquired causes, specific to each individual. Resolving this complexity, and designing personalized prevention and treatment, requires an integrated approach in which big datasets that contain all relevant factors are collected, and a multimodal analysis. Such datasets derive from multiple data sources, including all players in the chain-of-care for OHCA. This recognition has led to recently started large-scale collaborative efforts in Europe.

SUMMARY

Our insights into the causes of SCA are steadily increasing thanks to the creation of big datasets dedicated to SCA research. These insights may be used to earlier recognize of individuals at risk, the design of personalized methods for prevention, and more effective resuscitation strategies for OHCA.

Predictors of Sudden Cardiac Arrest Among Patients With Post-Myocardial Infarction Ejection Fraction Greater Than 35

Background

Sudden cardiac arrest (SCA) risk increases after myocardial infarction (MI) in patients with a reduced ejection fraction (EF). However, the risk factors for SCA among patients with a post‐MI EF >35% remain poorly understood.

Methods and Results

Using the Optum de‐identified electronic health record data set from 2008 to 2017, we identified patients with an incident MI diagnosis and troponin elevation who had a post‐MI EF >35% and underwent coronary angiography. Primary outcome was SCA within 1 year post‐MI. The database was divided into derivation (70%) and validation (30%) cohorts by random selection. Cox proportional hazard regression was used to generate and validate a risk prediction model. Among 31 286 patients with an MI (median age 64.1; 39% female; 87% White), 499 experienced SCA within 1 year post‐MI (estimated probability 1.8%). Lack of revascularization at MI, post‐MI EF <50%, Black race, renal failure, chronic obstructive pulmonary disease, antiarrhythmic therapy, and absence of beta blocker therapy were independent predictors of SCA. A multivariable model consisting of these variables predicted SCA risk (C‐statistic 0.73). Based on this model, the estimated annual probability of SCA was 4.4% (95% CI, 3.9–4.9) in the highest quartile of risk versus 0.6% (95% CI, 0.4–0.8) in the lowest quartile.

Conclusions

Patients with a post‐MI EF >35% have a substantial annual risk of SCA. A risk model consisting of acute coronary revascularization, EF, race, renal failure, chronic obstructive pulmonary disease, antiarrhythmic therapy, and beta blocker therapy can identify patients with higher risk of SCA, who may benefit from further risk stratification and closer monitoring.

Nationwide burden of sudden cardiac death: A study of 54,028 deaths in Denmark

BACKGROUND

A large proportion of all deaths are sudden cardiac deaths (SCDs). Reliable estimates of nationwide incidence of SCD, however, are missing.

OBJECTIVES

The goals of this study were to estimate SCD burden across all age groups in Denmark and to compare it with the estimates of other common causes of death.

METHODS

All deaths in Denmark (population of 5.5 million) in 2010 were manually reviewed case by case. Autopsy reports, death certificates, and information from nationwide health registries were systematically examined to identify all SCD cases in 2010. According to the level of detail of the available information, all deaths were categorized as either non-SCD, definite SCD, probable SCD, or possible SCD.

RESULTS

There were 54,028 deaths in Denmark in 2010, of which 6867 (13%) were categorized as SCD (591 (9%) definite SCD, 1568 (23%) probable SCD, and 4708 (68%) possible SCD). The incidence rate of definite SCD was 11 (95% confidence interval 10-12) per 100,000 person-years. Including definite, probable, and possible SCD cases, the highest possible overall SCD incidence rate was 124 (95% confidence interval 121-127) per 100,000 person-years. Estimated SCD burden was similar to or greater than the estimates of all other common causes of death. Of all SCD cases, 49% were not diagnosed with cardiovascular disease before death.

CONCLUSION

SCD accounted for up to 13% of all deaths. Almost half of all SCD cases occurred in persons without a history of cardiovascular disease. Consequently, the optimization of risk stratification and prevention of SCD in the general population should be given high priority.

Changes in Cardiovascular Health Status and Risk of Sudden Cardiac Death in Older Adults

PURPOSE

Cardiovascular health (CVH) status is associated with several cardiovascular outcomes; however, correlations between changes in CVH status and risk of sudden cardiac death (SCD) are unknown. We aimed to evaluate associations between changes in CVH status and risk of SCD and all-cause death in older adults.

MATERIALS AND METHODS

We used data from the Korea National Health Insurance Service-Senior cohort database (2005-2012). Six metrics from the American Heart Association (smoking, body mass index, physical activity, blood pressure, total cholesterol, and fasting blood glucose) were used to calculate CVH scores. Changes in CVH status between two health checkups were categorized as low to low, low to high, high to low, and high to high.

RESULTS

We included 105200 patients whose CVH status for an initial and follow-up health checkup (2-year interval) was available. During a median of 5.2 years of follow-up after a second health checkup, 688 SCDs occurred. Compared to patients with a persistent low CVH status, those with a consistently high CVH status had a reduced risk of SCD [adjusted hazard ratio (HR), 0.69; 95% confidence interval (CI), 0.56-0.86] and all-cause death (adjusted HR, 0.74; 95% CI, 0.69-0.78). The risk of all-cause death followed similar trends. However, an inconsistent linear relationship was observed for changes in CVH status and the risk of SCD, but not of all-cause death.

CONCLUSION

Maintaining a high CVH status was associated with future risks of SCD and all-cause death among an older adult population.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Building clinical risk score systems for predicting the all-cause and expanded cardiovascular-specific mortality of patients with type 2 diabetes

AIM

To develop and validate risk score systems by examining the effects of glycaemic and blood pressure variabilities on the all-cause and expanded cardiovascular-specific mortality of people with type 2 diabetes.

MATERIALS AND METHODS

This retrospective cohort study consisted of 9692 patients aged 30-85 years, diagnosed with type 2 diabetes and enrolled in a managed care programme of a medical centre from 2002 to 2016. All the patients were randomly allocated into two groups, namely, training and validation sets (2:1 ratio), and followed up until death or August 2019. Cox's proportional hazard regression was performed to develop all-cause and expanded cardiovascular-specific mortality prediction models. The performance of the prediction model was assessed by using the area under the receiver operating characteristic curve (AUROC).

RESULTS

Overall, 2036 deaths were identified after a mean of 8.6 years of follow-up. The AUROC-measured prediction accuracies of 3-, 5-, 10- and 15-year all-cause mortalities based on a model containing the identified traditional risk factors, biomarkers and variabilities in fasting plasma glucose, HbA1c and blood pressure in the validation set were 0.79 (0.76-0.83), 0.78 (0.76-0.81), 0.80 (0.78-0.82) and 0.80 (0.78-0.82), respectively. The corresponding values of the expanded cardiovascular-specific mortalities were 0.85 (0.80-0.90), 0.83 (0.79-0.86), 0.80 (0.77-0.83) and 0.79 (0.77-0.82), respectively.

CONCLUSIONS

Our prediction models considering glycaemic and blood pressure variabilities had good prediction accuracy for the expanded cardiovascular-specific and all-cause mortalities of patients with type 2 diabetes.

Derivation and validation of 10-year all-cause and cardiovascular disease mortality prediction model for middle-aged and elderly community-dwelling adults in Taiwan

Prediction model mainly focused on specific diseases, such as diabetes, hypertension, cardiovascular disease, or patients with cancer, or populations of Europe and America, thereby limiting its generalization. This study aimed to develop and validate a 10-year mortality risk score by using data from a population-representative sample of adults. Data were collected from 2,221 Taichung Community Health study participants aged ≥40 years. The baseline period of the study was 2004, and all participants were followed up until death or in 2016. Cox’s proportional hazards regression analyses were used to develop the prediction model. A total of 262 deaths were ascertained during the 10-year follow-up. The all-cause mortality prediction model calculated the significant risk factors, namely, age, sex, marital status, physical activity, tobacco use, estimated glomerular filtration rate, and albumin-to-creatinine ratio, among the baseline risk factors. The expanded cardiovascular disease (CVD) mortality prediction model consisted of six variables: age, sex, body mass index, heart disease plus heart disease medication use, stroke plus medication use, and ankle–brachial index. The areas under receiver operating curves of the 3-, 5- and 10-year predictive models varied between 0.97, 0.96, and 0.88 for all-cause mortality, and between 0.97, 0.98, and 0.84 for expanded CVD mortality. These mortality prediction models are valid and can be used as tools to identify the increased risk for mortality.

Implications of Frailty among Men with Implantable Cardioverter Defibrillators

OBJECTIVES

Frailty is associated with adverse outcomes, but little is known of the impact of frailty on patients with implantable cardioverter defibrillators (ICDs). This study sought to determine the prevalence of frailty, based on quantitative assessment, and assessed its potential impact on outcomes among community-dwelling men with ICDs.

METHODS

A total of 124 ICD-treated men presenting for a routine device clinic appointment between May and October 2016 underwent frailty assessment consisting of three components: shrinking (weight loss ≥5% during the past year), weakness (inability to rise from a chair without using their arms), and self-reported poor energy level. Patients who had no components were considered robust, those with 1 component were intermediate stage, and those with ≥2 components were deemed frail.

RESULTS

Mean age was 70.4 (±9.7) years. Of the 124 men, 31 (25%) were considered to be frail, 65 (52%) were intermediate, and 28 (23%) were robust. Frail men were older and were more likely to have symptomatic heart failure, chronic kidney disease, and hypertension (P < 0.05 for all) compared with nonfrail men. During a follow-up of 16 months, frail men were significantly more likely to die compared with nonfrail men (29% vs 5.4%, P < 0.0003). The incidence of appropriate ICD shocks (16.1% vs 6.5%) or hospitalizations (38.7% vs 23.7%) tended to be higher among frail versus nonfrail patients, but neither reached statistical significance (P = 0.10).

CONCLUSIONS

Almost one-fourth of men with ICD are frail. Almost one-third of frail ICD patients died within 16 months. It may be useful to assess frailty in patients with ICD.

Sudden cardiac death in asymptomatic patients with aortic stenosis

OBJECTIVE

We retrospectively analysed outcome data from the Simvastatin and Ezetimibe in Aortic Stenosis (SEAS) study to assess the incidence and potential risk factors of sudden cardiac death (SCD) in this prospectively followed cohort of asymptomatic patients with aortic stenosis (AS).

METHODS

Of the 1873 patients included in SEAS, 1849 (99%) with mild to moderate AS (jet velocity 2.5-4.0 m/s at baseline) and available clinical, echocardiographic and follow-up data were analysed. Patients undergoing aortic valve replacement were censored at the time of operation.

RESULTS

During an overall follow-up of 46.1±14.6 months, SCD occurred in 27 asymptomatic patients (1.5%) after a mean of 28.3±16.6 months. The annualised event rate was 0.39%/year. The last follow-up echocardiography prior to the event showed mild to moderate stenosis in 22 and severe stenosis (jet velocity >4 m/s) in 5 victims of SCD. The annualised event rate after the diagnosis of severe stenosis was 0.60%/year compared with 0.46%/year in patients who did not progress to severe stenosis (p=0.79). Patients with SCD were older (p=0.01), had a higher left ventricular mass index (LVMI, p=0.001) and had a lower body mass index (BMI, p=0.02) compared with patients surviving follow-up. Cox regression analysis identified age (HR 1.06, 95% CI 1.01 to 1.11 per year, p=0.02), increased LVMI (HR 1.20, 95% CI 1.10 to 1.32 per 10 g/m², p<0.001) and lower BMI (HR 0.87, 95% CI 0.79 to 0.97 per kg/m², p=0.01) as independent risk factors of SCD.

CONCLUSION

SCD in patients with asymptomatic mild to moderate AS is rare and strongly related to left ventricular hypertrophy but not stenosis severity.

Markers of Myocardial Stress, Myocardial Injury, and Subclinical Inflammation and the Risk of Sudden Death

BACKGROUND

The majority of sudden cardiac deaths (SCDs) occur in low-risk populations often as the first manifestation of cardiovascular disease (CVD). Biomarkers are screening tools that may identify subclinical cardiovascular disease and those at elevated risk for SCD. We aimed to determine whether the total to high-density lipoprotein cholesterol ratio, high-sensitivity cardiac troponin I, NT-proBNP (N-terminal pro-B-type natriuretic peptide), or high-sensitivity C-reactive protein individually or in combination could identify individuals at higher SCD risk in large, free-living populations with and without cardiovascular disease.

METHODS

We performed a nested case-control study within 6 prospective cohort studies using 565 SCD cases matched to 1090 controls (1:2) by age, sex, ethnicity, smoking status, and presence of cardiovascular disease.

RESULTS

The median study follow-up time until SCD was 11.3 years. When examined as quartiles or continuous variables in conditional logistic regression models, each of the biomarkers was significantly and independently associated with SCD risk after mutually controlling for cardiac risk factors and other biomarkers. The mutually adjusted odds ratios for the top compared with the bottom quartile were 1.90 (95% CI, 1.30-2.76) for total to high-density lipoprotein cholesterol ratio, 2.59 (95% CI, 1.76-3.83) for high-sensitivity cardiac troponin I, 1.65 (95% CI, 1.12-2.44) for NT-proBNP, and 1.65 (95% CI, 1.13-2.41) for high-sensitivity C-reactive protein. A biomarker score that awarded 1 point when the concentration of any of those 4 biomarkers was in the top quartile (score range, 0-4) was strongly associated with SCD, with an adjusted odds ratio of 1.56 (95% CI, 1.37-1.77) per 1-unit increase in the score.

CONCLUSIONS

Widely available measures of lipids, subclinical myocardial injury, myocardial strain, and vascular inflammation show significant independent associations with SCD risk in apparently low-risk populations. In combination, these measures may have utility to identify individuals at risk for SCD.

Association Between Atrial Fibrillation and Sudden Cardiac Death

Emerging evidence suggests that atrial fibrillation (AF) may be associated with an increased risk of sudden cardiac death (SCD). However, AF shares risk factors with numerous cardiac conditions, including coronary heart disease and heart failure—the 2 most common substrates for SCD—making the AF-SCD relationship particularly challenging to address. A careful consideration of confounding factors is essential, since interventions for AF will be effective in reducing SCD only if there is a causal association between these 2 conditions. In this translational review, we detail the plausible underlying pathophysiological mechanisms through which AF may promote or lead to SCD, as well as the existing epidemiological evidence supporting an association between AF and SCD. While the role of AF in predicting SCD in the general population appears limited and not established, AF might be integrated to improve risk stratification in some specific phenotypes. Optimal AF management, including that of its associated conditions, appears to be of interest to prevent AF-related SCD, especially because the AF-SCD relationship is in part driven by heart failure.

Out-of-hospital cardiac arrest: Causes according to autopsy and electrocardiography - Analysis of 781 patients with neither hospital care nor prescribed medication during the preceding two years

BACKGROUND

There is a knowledge gap regarding aetiology of and potential for predicting out-of-hospital cardiac arrest (OHCA) among individuals who are healthy before the event.

AIM

To describe causes of OHCA and the potential for predicting OHCA in apparently healthy patients.

METHODS

Patients were recruited from the Swedish Register of Cardiopulmonary Resuscitation from November 2007 to January 2011. Inclusion criteria were: OHCA with attempted CPR but neither dispensed prescription medication nor hospital care two years before the event The register includes the majority of patients suffering OHCA in Sweden where cardiopulmonary resuscitation (CPR) was attempted. Medication status was defined by linkage to the Swedish Prescribed Drug Register. Cause of death was assessed based on autopsy and the Swedish Cause of Death Register. Prediction of OHCA was attempted based on available electrocardiograms (ECG) before the OHCA event.

RESULTS

Altogether 781 individuals (16% women) fulfilled the inclusion criteria. Survival to 30 days was 16%. Autopsy rate was 72%. Based on autopsy, 70% had a cardiovascular aetiology and 59% a cardiac aetiology. An ECG recording before the event was found in 23% of cases. The ECG was abnormal in 22% of them.

CONCLUSION

Among OHCA victims who appeared to be healthy prior to the event, the cause was cardiovascular in the great majority according to autopsy findings. A minority had a preceding abnormal ECG that could have been helpful in avoiding the event.