OUP accepted manuscript

Characteristics and Causes of Sports-Related Sudden Death in the General Population during the COVID-19 Pandemic

PURPOSE

COVID-19 is an independent risk factor for cardiovascular disease. The aim of this study is to determine the burden, characteristics, and causes of sudden death in sport (SrSD) before and after the COVID-19 pandemic in the general population.

METHODS

Retrospective observational study. Autopsied SrSD studied in Catalonia was consecutively included. Two periods were considered: before lockdown (January 2019-March 2020) and after lockdown (March 2020-December 2021). Initial care variables and causes of death were collected. Periods were compared, and logistic regression analyses were performed.

RESULTS

A total of 156 SrSD were collected, with no differences in the incidence between the study periods. Of the cases, 98.7% were male, with a mean age of 55.8 yr (SD, 12.1). Cycling was practiced by 40.0%. Coronary artery disease was the leading cause of death, with no difference before and after lockdown. No cases of myocarditis were described. Of the total number of SrSD, 98 (62.8%) received a cardiopulmonary resuscitation (CPR) attempt. After lockdown, the SrSD that occurred in country areas decreased (40.6% vs 24.4%, P = 0.032), and the rate of CPR attempts (54.3% vs 69.8%, P = 0.034) and hands-only CPR increased (76.6% vs 57.9%, P = 0.048).

CONCLUSIONS

There were no changes in the burden and causes of SrSD before and after the COVID-19 lockdown. Differences were found in the SrSD initial care received due to the change of basic life support recommendations and the sport activity habits.

From rare events to systematic data collection: the RESCUED registry for sudden cardiac death in the young in Germany

BACKGROUND

Approximately one-third of sudden cardiac deaths in the young (SCDY) occur due to a structural cardiac disease. Forty to fifty percent of SCDY cases remain unexplained after autopsy (including microscopic and forensic-toxicological analyses), suggesting arrhythmia syndromes as a possible cause of death. Due to the possible inheritability of these diseases, blood relatives of the deceased may equally be carriers of the causative genetic variations and therefore may have an increased cardiac risk profile. A better understanding of the forensic, clinical, and genetic data might help identify a subset of the general population that is at increased risk of sudden cardiac death.

STUDY DESIGN

The German registry RESCUED (REgistry for Sudden Cardiac and UnExpected Death) comprises information about SCDY fatalities and clinical and genetic data of both the deceased and their biological relatives. The datasets collected in the RESCUED registry will allow for the identification of leading causes of SCDY in Germany and offer unique possibilities of scientific analyses with the aim of detecting unrecognized trends, risk factors, and clinical warning signs of SCDY. In a pilot phase of 24 months, approximately 180 SCDY cases (< 50 years of age) and 500 family members and clinical patients will be included.

CONCLUSION

RESCUED is the first registry in Germany collecting comprehensive data of SCDY cases and clinical data of the biological relatives reviewed by cardiac experts. RESCUED aims to improve individual risk assessment and public health approaches by directing resources towards early diagnosis and evidence-based, personalized therapy and prevention in affected families. Trial registration number (TRN): DRKS00033543.

Novel Protein-Based Biomarkers of Out-of-hospital Sudden Cardiac Death After Myocardial Infarction

BACKGROUND

Early identification of out-of-hospital high-risk sudden cardiac death (SCD) after acute myocardial infarction is crucial for timely therapeutic interventions. However, left ventricular ejection fraction as a standalone clinical stratification tool has major limitations, necessitating improved risk stratification strategies.

METHODS

Mass spectrometry measured 6592 peptides and 522 proteins, from which targeted proteomics identified the optimal protein combination to assess out-of-hospital SCD risk. ELISA validated its predictive value by comparing it with a clinical stratification tool (left ventricular ejection fraction ≤35%) and 2 reported models (risk score and out-of-hospital cardiac arrest score) in 3 case-control cohorts nested within diverse contemporary postinfarction populations.

RESULTS

In the discovery cohort (105 SCD cases and 105 survivors), mass spectrometry discovered 44 differential proteins associated with SCD, unveiling early circulating features characterized by inflammatory response and complement activation in out-of-hospital SCD cases. Targeted proteomics identified the optimal SCD-warning 3-protein combination, including coronin-1A, haptoglobin, and CFD (complement factor D), to assess out-of-hospital SCD risk. An ELISA-based SCD-warning 3-protein combination model significantly outperformed left ventricular ejection fraction alone (C statistic: 0.752 versus 0.548; P<0.001) and improved their performance (ΔC statistic, 0.281; categorical net reclassification improvement, 0.095; continuous net reclassification improvement, 0.952; integrated discrimination improvement, 0.291). Similar incremental discrimination metrics were observed in 2 reported stratification models (risk score and out-of-hospital cardiac arrest score), particularly within the left ventricular ejection fraction-preserved population. These findings were repeatably validated in 2 independent cohorts (n=234 and 48, respectively). CFD inhibition protection for mortality and pro-malignant arrhythmias in acute myocardial infarction mice supported the biological plausibility of the critical protein in SCD-warning 3-protein combination.

CONCLUSIONS

In high-risk individuals for out-of-hospital SCD, the SCD-warning 3-protein combination may contribute to enhanced early identification for timely intensive management. These findings suggest pivotal proteins for improving understanding SCD pathophysiology.

Near-term prediction of sustained ventricular arrhythmias applying artificial intelligence to single-lead ambulatory electrocardiogram

BACKGROUND AND AIMS

Accurate near-term prediction of life-threatening ventricular arrhythmias would enable pre-emptive actions to prevent sudden cardiac arrest/death. A deep learning-enabled single-lead ambulatory electrocardiogram (ECG) may identify an ECG profile of individuals at imminent risk of sustained ventricular tachycardia (VT).

METHODS

This retrospective study included 247 254, 14 day ambulatory ECG recordings from six countries. The first 24 h were used to identify patients likely to experience sustained VT occurrence (primary outcome) in the subsequent 13 days using a deep learning-based model. The development set consisted of 183 177 recordings. Performance was evaluated using internal (n = 43 580) and external (n = 20 497) validation data sets. Saliency mapping visualized features influencing the model's risk predictions.

RESULTS

Among all recordings, 1104 (.5%) had sustained ventricular arrhythmias. In both the internal and external validation sets, the model achieved an area under the receiver operating characteristic curve of .957 [95% confidence interval (CI) .943-.971] and .948 (95% CI .926-.967). For a specificity fixed at 97.0%, the sensitivity reached 70.6% and 66.1% in the internal and external validation sets, respectively. The model accurately predicted future VT occurrence of recordings with rapid sustained VT (≥180 b.p.m.) in 80.7% and 81.1%, respectively, and 90.0% of VT that degenerated into ventricular fibrillation. Saliency maps suggested the role of premature ventricular complex burden and early depolarization time as predictors for VT.

CONCLUSIONS

A novel deep learning model utilizing dynamic single-lead ambulatory ECGs accurately identifies patients at near-term risk of ventricular arrhythmias. It also uncovers an early depolarization pattern as a potential determinant of ventricular arrhythmias events.

Sports-Related Sudden Cardiac Arrest in Canada: Incidence and Survival

BACKGROUND

Sports-related (Sr-) sudden cardiac arrest (SCA) is widely recognized in young competitive athletes, yet occurs more frequently in middle-aged, recreational athletes. Our objective was to describe the epidemiology and characteristics of Sr-SCA in 5 Canadian Provinces (population: 10.9 million).

METHODS

We conducted a retrospective cohort study using emergency medical services records from consecutive out of hospital SCAs, for patients aged 18-85 years, who were treated, and whose SCA was from a presumed cardiac cause, during or ≤ 1 hour after sports activity.

RESULTS

A total of 18,769 SCAs occurred between January 1, 2016 and December 31, 2020, of which 339 (1.8%) were sport-related. Most patients were male (93.8%; 318/339), with an average age of 58.1 ± 14.3 years old. The incidence of Sr-SCA was 1.2 per 100,000 person-years (95% confidence interval [CI], 1.1-1.4). Men had an almost 16-fold greater incidence than women (2.3 [95% CI, 2.1-2.6] vs 0.2 [95% CI, 0.1-0.2] per 100,000 person-years). Sr-SCAs occurred during 52 unique sports. Almost two-thirds occurred in recreational facilities (60.2%; 204/339), with high rates of bystander witnessed (75.6%; 256/339) and bystander cardiopulmonary resuscitation (73.6%; 248/337). Bystanders delivered automated external defibrillator shocks in 121 of 335 (36.1%) cases. Median emergency medical services response time was 6.2 (interquartile range, 4.8-8.9) minutes, with an initial shockable rhythm reported in 76.9% (249/324). More than half of those with known final vital status (52.0%; 167/321) survived to hospital discharge, which varied on the basis of sport.

CONCLUSIONS

Sr-SCA occurs infrequently, attracts high rates of bystander intervention, and has high survivability.

Declining Trend of Sudden Cardiac Death in Younger Individuals: A 20-Year Nationwide Study

BACKGROUND

Declining cardiovascular mortality rates have been well-documented, yet temporal trends of sudden cardiac death (SCD) in young individuals remain unclear. We provide contemporary nationwide estimates of the temporal trends of SCD in young individuals (1-35 years of age) from 2000 through 2019 and correlate these trends to changes in out-of-hospital cardiac arrest (OHCA) patterns, rates of inherited cardiac diseases, and implantations of implantable cardioverter defibrillators (ICD).

METHODS

All individuals between 1 and 35 years of age living in Denmark from 2000 through 2019 were included, with annual re-evaluation of the at-risk population in regard to age. Adjudication of SCD cases relied on multiple sources, including death certificates, medical files, and autopsy reports. Information on OHCA, diagnostic rates, and ICD implantations were captured from nationwide administrative registries. Annual incidence rates of SCD were calculated, and temporal trends in SCD incidence were computed as percentage change annualized. Trends in OHCA survival and characteristics, diagnostic rates of inherited cardiac diseases, and ICD implantations were assessed.

RESULTS

During the 20-year study period (47.5 million person-years), 1057 SCDs were identified (median age, 29 years; 69% male). The overall incidence of SCD was 2.2 per 100 000 person-years and declined by 3.31% (95% CI, 2.42-4.20) annually, corresponding to a 49% (95% CI, 38.7-57.6) reduction during the study. Rates of witnessed SCD declined markedly (percentage change annualized -7.03% [95% CI, -8.57 to -5.48]), but we observed no changes in the rate of unwitnessed SCD (percentage change annualized -0.09% [95% CI, -1.48 to 1.31]). Therefore, the proportion of unwitnessed SCD increased by 79% (P<0.001). Survival after OHCA in young individuals (1 to 35 years of age) increased from 3.9% to 28%, mainly because of increased bystander cardiopulmonary resuscitation and defibrillation rates. Diagnostic rates of inherited cardiac diseases increased 10-fold (incidence rate ratio, 10.4 [95% CI, 8.46-12.90]) and the ICD implantation rate increased 2-fold (incidence rate ratio, 1.97 [95% CI, 1.51-2.60]).

CONCLUSIONS

SCD incidence rates in young individuals declined by 49% over the past 2 decades. The decline was paralleled by improved survival of OHCA, higher diagnostic rates of inherited cardiac diseases, and higher ICD implantation rates. However, rates of unwitnessed SCD were unchanged, which calls for new perspectives in preventive strategies.

Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease: A Retrospective Study

Background: Fatal coronary heart disease (FCHD) affects ~650,000 people yearly in the US. Electrocardiographic artificial intelligence (ECG-AI) models can predict adverse coronary events, yet their application to FCHD is understudied. Objectives: The study aimed to develop ECG-AI models predicting FCHD risk from ECGs. Methods (Retrospective): Data from 10 s 12-lead ECGs and demographic/clinical data from University of Tennessee Health Science Center (UTHSC) were used for model development. Of this dataset, 80% was used for training and 20% as holdout. Data from Atrium Health Wake Forest Baptist (AHWFB) were used for external validation. We developed two separate convolutional neural network models using 12-lead and Lead I ECGs as inputs, and time-dependent Cox proportional hazard models using demographic/clinical data with ECG-AI outputs. Correlation of the predictions from the 12- and 1-lead ECG-AI models was assessed. Results: The UTHSC cohort included data from 50,132 patients with a mean age (SD) of 62.50 (14.80) years, of whom 53.4% were males and 48.5% African American. The AHWFB cohort included data from 2305 patients with a mean age (SD) of 63.04 (16.89) years, of whom 51.0% were males and 18.8% African American. The 12-lead and Lead I ECG-AI models resulted in validation AUCs of 0.84 and 0.85, respectively. The best overall model was the Cox model using simple demographics with Lead I ECG-AI output (D1-ECG-AI-Cox), with the following results: AUC = 0.87 (0.85-0.89), accuracy = 83%, sensitivity = 69%, specificity = 89%, negative predicted value (NPV) = 92% and positive predicted value (PPV) = 55% on the AHWFB validation cohort. For this, the 2-year FCHD risk prediction accuracy was AUC = 0.91 (0.90-0.92). The 12-lead versus Lead I ECG FCHD risk prediction showed strong correlation (R = 0.74). Conclusions: The 2-year FCHD risk can be predicted with high accuracy from single-lead ECGs, further improving when combined with demographic information.

A Call to Action to Improve Cardiac Arrest Outcomes: A Report From the National Summit for Cardiac Arrest

Sudden cardiac arrest (SCA) represents a major cause of premature mortality globally, with enormous impact and financial cost to victims, families, and communities. SCA prevention should be considered a health priority in Australia. National Cardiac Arrest Summits were held in June 2022 and March 2023, with inclusion from multi-faceted endeavours related to SCA prevention. It was agreed to establish a multidisciplinary Australian Sudden Cardiac Arrest Alliance (AuSCAA) working group charged with developing a national unified strategy, with clear and measurable quality indicators and standardised outcome measures, to amplify the goal of SCA prevention throughout Australia. A multi-faceted prevention strategy will include i) endeavours to progress community awareness, ii) improved fundamental mechanistic understanding, iii) implementation of best-practice resuscitation strategies for all demographics and locations, iv) secondary risk assessment directed to family members, and v) development of (near) real-time registry of cardiac arrest cases to inform areas of need and effectiveness of interventions. Together, we can and should reduce the impact of SCA in Australia.

Arrhythmic Risk Stratification by Cardiovascular Magnetic Resonance Imaging in Patients With Nonischemic Cardiomyopathy

BACKGROUND

Myocardial fibrosis (MF) forms part of the arrhythmic substrate for ventricular arrhythmias (VAs).

OBJECTIVES

This study sought to determine whether total myocardial fibrosis (TF) and gray zone fibrosis (GZF), assessed using cardiovascular magnetic resonance, are better than left ventricular ejection fraction (LVEF) in predicting ventricular arrhythmias in patients with nonischemic cardiomyopathy (NICM).

METHODS

Patients with NICM in a derivation cohort (n = 866) and a validation cohort (n = 848) underwent quantification of TF and GZF. The primary composite endpoint was sudden cardiac death or VAs (ventricular fibrillation or ventricular tachycardia).

RESULTS

The primary endpoint was met by 52 of 866 (6.0%) patients in the derivation cohort (median follow-up: 7.5 years; Q1-Q3: 5.2-9.3 years). In competing-risks analyses, MF on visual assessment (MFVA) predicted the primary endpoint (HR: 5.83; 95% CI: 3.15-10.8). Quantified MF measures permitted categorization into 3 risk groups: a TF of >0 g and ≤10 g was associated with an intermediate risk (HR: 4.03; 95% CI: 1.99-8.16), and a TF of >10 g was associated with the highest risk (HR: 9.17; 95% CI: 4.64-18.1) compared to patients with no MFVA (lowest risk). Similar trends were observed in the validation cohort. Categorization into these 3 risk groups was achievable using TF or GZF in combination or in isolation. In contrast, LVEF of <35% was a poor predictor of the primary endpoint (validation cohort HR: 1.99; 95% CI: 0.99-4.01).

CONCLUSIONS

MFVA is a strong predictor of sudden cardiac death and VAs in NICM. TF and GZF mass added incremental value to MFVA. In contrast, LVEF was a poor discriminator of arrhythmic risk.

Pre-emptive treatment of heart failure exacerbations in patients managed with the HeartLogic™ algorithm

AIMS

Heart failure (HF) is a chronic disease affecting 64 million people worldwide and places a severe burden on society because of its mortality, numerous re-hospitalizations and associated costs. HeartLogic™ is an algorithm programmed into implanted devices incorporating several biometric parameters which aims to predict HF episodes. It provides an index which can be monitored remotely, allowing pre-emptive treatment of congestion to prevent acute decompensation. We aim to assess the impact and security of pre-emptive HF management, guided by the HeartLogic™ index.

METHODS AND RESULTS

The HeartLogic™ France Cohort Study is an investigator-initiated, prospective, multi-centre, non-randomized study. Three hundred ten patients with a history of HF (left ventricular ejection fraction ≤40%; or at least one episode of clinical HF with elevated NT-proBNP ≥450 ng/L) and implanted with a cardioverter defibrillator enabling HeartLogic™ index calculation will be included across 10 French centres. The HeartLogic™ index will be monitored remotely for 12 months and in the event of a HeartLogic™ index ≥16, the local investigator will contact the patient for assessment and adjust HF treatment as necessary. The primary endpoint is unscheduled hospitalization for HF. Secondary endpoints are all-cause mortality, cardiovascular death, HF-related death, unscheduled hospitalizations for ventricular or atrial arrhythmia and HeartLogic™ index evolution over time. Blood samples will be collected for biobanking, and quality of life will be assessed. Finally, the safety of a HeartLogic™-triggered strategy for initiating or increasing diuretic therapy will be assessed. A blind and independent committee will adjudicate the events.

CONCLUSIONS

The HeartLogic™ France Cohort Study will provide robust real-world data in a cohort of HF patients managed with the HeartLogic™ algorithm allowing pre-emptive treatment of heart failure exacerbations.

Length of hospital stay for elective electrophysiological procedures: a survey from the European Heart Rhythm Association

AIMS

Electrophysiological (EP) operations that have traditionally involved long hospital lengths of stay (LOS) are now being undertaken as day case procedures. The coronavirus disease-19 pandemic served as an impetus for many centres to shorten LOS for EP procedures. This survey explores LOS for elective EP procedures in the modern era.

METHODS AND RESULTS

An online survey consisting of 27 multiple-choice questions was completed by 245 respondents from 35 countries. With respect to de novo cardiac implantable electronic device (CIED) implantations, day case procedures were reported for 79.5% of implantable loop recorders, 13.3% of pacemakers (PMs), 10.4% of implantable cardioverter defibrillators (ICDs), and 10.2% of cardiac resynchronization therapy (CRT) devices. With respect to CIED generator replacements, day case procedures were reported for 61.7% of PMs, 49.2% of ICDs, and 48.2% of CRT devices. With regard to ablations, day case procedures were reported for 5.7% of atrial fibrillation (AF) ablations, 10.7% of left-sided ablations, and 17.5% of right-sided ablations. A LOS ≥ 2 days for CIED implantation was reported for 47.7% of PM, 54.5% of ICDs, and 56.9% of CRT devices and for 54.5% of AF ablations, 42.2% of right-sided ablations, and 46.1% of left-sided ablations. Reimbursement (43-56%) and bed availability (20-47%) were reported to have no consistent impact on the organization of elective procedures.

CONCLUSION

There is a wide variation in the LOS for elective EP procedures. The LOS for some procedures appears disproportionate to their complexity. Neither reimbursement nor bed availability consistently influenced LOS.

Toward advanced diagnosis and management of inherited arrhythmia syndromes: Harnessing the capabilities of artificial intelligence and machine learning

The use of advanced computational technologies, such as artificial intelligence (AI), is now exerting a significant influence on various aspects of life, including health care and science. AI has garnered remarkable public notice with the release of deep learning models that can model anything from artwork to academic papers with minimal human intervention. Machine learning, a method that uses algorithms to extract information from raw data and represent it in a model, and deep learning, a method that uses multiple layers to progressively extract higher-level features from the raw input with minimal human intervention, are increasingly leveraged to tackle problems in the health sector, including utilization for clinical decision support in cardiovascular medicine. Inherited arrhythmia syndromes are a clinical domain where multiple unanswered questions remain despite unprecedented progress over the past 2 decades with the introduction of large panel genetic testing and the first steps in precision medicine. In particular, AI tools can help address gaps in clinical diagnosis by identifying individuals with concealed or transient phenotypes; enhance risk stratification by elevating recognition of underlying risk burden beyond widely recognized risk factors; improve prediction of response to therapy, and further prognostication. In this contemporary review, we provide a summary of the AI models developed to solve challenges in inherited arrhythmia syndromes and also outline gaps that can be filled with the development of intelligent AI models.

Effect of a national awareness campaign on ambulance attendances for chest pain and out-of-hospital cardiac arrest

AIM

Awareness of heart attack symptoms may enhance health-seeking behaviour and prevent premature deaths from out-of-hospital cardiac arrest (OHCA). We sought to investigate the impact of a national awareness campaign on emergency medical service (EMS) attendances for chest pain and OHCA.

METHODS

Between January 2005 and December 2017, we included registry data for 97,860 EMS-attended OHCA cases from 3 Australian regions and dispatch data for 1,631,217 EMS attendances for chest pain across 5 Australian regions. Regions were exposed to between 11 and 28 months of television, radio, and print media activity. Multivariable negative binomial models were used to explore the effect of campaign activity on the monthly incidence of EMS attendances for chest pain and OHCA.

RESULTS

Months with campaign activity were associated with an 8.8% (IRR 1.09, 95% CI: 1.07, 1.11) increase in the incidence of EMS attendances for chest pain and a 5.6% (IRR 0.94, 95% CI: 0.92, 0.97) reduction in OHCA attendances. Larger intervention effects were associated with increasing months of campaign activity, increasing monthly media spending and media exposure in 2013. In stratified analyses of OHCA cases, the largest reduction in incidence during campaign months was observed for unwitnessed arrests (IRR 0.93, 95% CI: 0.90, 0.96), initial non-shockable arrests (IRR 0.93, 95% CI: 0.90, 0.97) and arrests occurring in private residences (IRR 0.95, 95% CI: 0.91, 0.98).

CONCLUSION

A national awareness campaign targeting knowledge of heart attack symptoms was associated with an increase in EMS use for chest pain and a reduction in OHCA incidence and may serve as an effective primary prevention strategy for OHCA.

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.

Characterization of global research trends and prospects on sudden coronary death: A literature visualization analysis

Background

Sudden coronary death is a major global public health issue that has a significant impact on both individuals and society. Nowadays, scholars are active in sudden coronary death all over the world. However, no relevant bibliometric studies have been published. Here, we aim to gain a better understanding the current state of research and to explore potential new research directions through bibliometric analysis.

Methods

Articles and reviews on sudden coronary death from 2012 to 2023 were retrieved from the Web of Science Core Collection (WoSCC). The topic search was conducted using the following keywords: ((("sudden cardiac death" OR "sudden death") AND (coronary OR "myocardial infarction")) OR "sudden coronary death"). Knowledge maps of authors, countries, institutions, journals, keywords, and citations were conducted by CiteSpace. Publication dynamics, hotspots, and frontiers were analyzed independently by authors.

Results

A total of 2914 articles were identified from January 1, 2012 to June 20, 2023. The USA (n = 972) contributed the greatest absolute productivity and UK (centrality = 0.13) built a robust global collaboration. Harvard University was the institution with the highest number of publications (n = 143). Huikuri HV and Junttila MJ were the most published authors who devoted to searching for biomarkers of sudden coronary death. American Journal of Cardiology was the journal with the most publications, and Circulation was the most cited journal. Left ventricular ejection fraction, society, inflammation, and fractional flow reserve became novel burst words that lasted until 2023. Research on etiology and pathology, role of early risk factors in risk stratification, potential predictive biomarkers and novel measurement methods for the prevention and management of sudden coronary death were identified as the research hotspots and frontiers.

Conclusion

Our knowledge and understanding of sudden coronary death have significantly improved. Ongoing efforts should focus on the various etiologies and pathologies of sudden coronary death. Furthermore, a novel sudden coronary death risk model, large-scale population studies, and the rational use of multiple indicators to individualize the assessment of sudden coronary death and other risk factors are other emerging research trends.

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.

Dynamic changes in nocturnal heart rate predict short-term cardiovascular events in patients using the wearable cardioverter-defibrillator: from the WEARIT-France cohort study

AIMS

While elevated resting heart rate measured at a single point of time has been associated with cardiovascular outcomes, utility of continuous monitoring of nocturnal heart rate (NHR) has never been evaluated. We hypothesized that dynamic NHR changes may predict, at short term, impending cardiovascular events in patients equipped with a wearable cardioverter-defibrillator (WCD).

METHODS AND RESULTS

The WEARIT-France prospective cohort study enrolled heart failure patients with WCD between 2014 and 2018. Night-time was defined as midnight to 7 a.m. NHR initial trajectories were classified into four categories based on mean NHR in the first week (High/Low) and NHR evolution over the second week (Up/Down) of WCD use. The primary endpoint was a composite of cardiovascular death and heart failure hospitalization. A total of 1013 [61 (interquartile range, IQR 53-68) years, 16% women, left ventricular ejection fraction 26% (IQR 22-30)] were included. During a median WCD wear duration of 68 (IQR 44-90) days, 58 patients (6%) experienced 69 events. After considering potential confounders, High-Up NHR trajectory was significantly associated with the primary endpoint compared to Low-Down [adjusted hazard ratio (HR) 6.08, 95% confidence interval (CI) 2.56-14.45, P < 0.001]. Additionally, a rise of >5 bpm in weekly average NHR from the preceding week was associated with 2.5 higher composite event risk (HR 2.51, 95% CI 1.22-5.18, P = 0.012) as well as total mortality (HR 11.21, 95% CI 3.55-35.37, P < 0.001) and cardiovascular hospitalization (HR 2.70, 95% CI 1.51-4.82, P < 0.001).

CONCLUSION

Dynamic monitoring of NHR may allow timely identification of impending cardiovascular events, with the potential for 'pre-emptive' action.

REGISTRATION NUMBER

Clinical Trials.gov Identifier: NCT03319160.

Incidence of Cardiac Arrest During Sports Among Women in the European Union

BACKGROUND

Women represent a growing proportion of sports participants. Still, few original data regarding sudden cardiac arrest during sports (Sr-SCA) in women are available.

OBJECTIVES

The authors sought to assess the incidence, characteristics, and outcomes of women presenting with Sr-SCA.

METHODS

Data were analyzed from 3 population-based European registries (ESCAPE-NET 2020 Horizon Program) that prospectively and exhaustively collect every case of SCA: SDEC (Paris-Sudden Death Expertise Center), ARREST (AmsteRdam REsuscitation Studies), and SRCR (Swedish Register for Cardiopulmonary Resuscitation). Sr-SCA was defined as SCA during or ≤1 hour after cessation of sports activity.

RESULTS

Of 34,826 SCA between 2006 and 2017, 760 Sr-SCA (2.2%) were identified, including 54 in women. The average annual incidence of Sr-SCA in women in the 3 registries ranged from 0.10 per million (95% CI: 0.01-0.71 per million) to 0.38 per million (95% CI: 0.14-1.04 per million). Overall, the average annual incidence rate of Sr-SCA in women was 0.19 per million (95% CI: 0.14-0.24 per million), >10-fold lower compared with men (2.63 per million [95% CI: 2.45-2.83 per million]; P < 0.0001). When extrapolating to the total European population and accounting for age and sex, this yields 98 cases per year (95% CI: 72-123 cases per year) in women and 1,350 cases per year (95% CI: 1,256-1,451 cases per year) in men. Subject characteristics and circumstances of occurrence were similar in women vs men. Bystander response, time to defibrillation, and survival rate at hospital admission (58.8% vs 58.5%; P = 0.99) and 30 days did not differ significantly between women and men.

CONCLUSIONS

These findings emphasize the dramatically lower risk of Sr-SCA in women compared with men, despite similar subject characteristics. This should be considered in designing preparticipation screening strategies in the future.

Predicting recurrent cardiac arrest in individuals surviving Out-of-Hospital cardiac arrest

BACKGROUND

Despite improvements in short-term survival for Out-of-Hospital Cardiac Arrest (OHCA) in the past two decades, long-term survival is still not well studied. Furthermore, the contribution of different variables on long-term survival have not been fully investigated.

AIM

Examine the 1-year prognosis of patients discharged from hospital after an OHCA. Furthermore, identify factors predicting re-arrest and/or death during 1-year follow-up.

METHODS

All patients 18 years or older surviving an OHCA and discharged from the hospital were identified from the Swedish Register for Cardiopulmonary Resuscitation (SRCR). Data on diagnoses, medications and socioeconomic factors was gathered from other Swedish registers. A machine learning model was constructed with 886 variables and evaluated for its predictive capabilities. Variable importance was gathered from the model and new models with the most important variables were created.

RESULTS

Out of the 5098 patients included, 902 (∼18%) suffered a recurrent cardiac arrest or death within a year. For the outcome death or re-arrest within 1 year from discharge the model achieved an ROC (receiver operating characteristics) AUC (area under the curve) of 0.73. A model with the 15 most important variables achieved an AUC of 0.69.

CONCLUSIONS

Survivors of an OHCA have a high risk of suffering a re-arrest or death within 1 year from hospital discharge. A machine learning model with 15 different variables, among which age, socioeconomic factors and neurofunctional status at hospital discharge, achieved almost the same predictive capabilities with reasonable precision as the full model with 886 variables.

Incidence of sudden cardiac arrest and sudden cardiac death after unstable angina pectoris and myocardial infarction

BACKGROUND

Sudden cardiac arrests (SCA) and sudden cardiac deaths (SCD) are believed to account for a large proportion of deaths due to cardiovascular causes. The purpose of this study is to provide comprehensive information on the epidemiology of SCAs and SCDs after acute coronary syndrome.

METHODS

The incidence of SCA (including SCDs) was studied retrospectively among 10,316 consecutive patients undergoing invasive evaluation for acute coronary syndrome (ACS) between 2007 and 2018 at Tays Heart Hospital (sole provider of specialized cardiac care for a catchment area of over 0.5 million residents). Baseline and follow-up information was collected by combining information from the hospital's electronic health records, death certificate data, and a full-disclosure review of written patient records and accounts of the circumstances leading to death.

RESULTS

During 12 years of follow-up, the cumulative incidence of SCAs (including SCDs) was 9.8% (0.8% annually) and that of SCDs 5.4% (0.5% annually). Cumulative incidence of SCAs in patients with ST-elevation myocardial infarction, non-ST-elevation myocardial infarction and unstable angina pectoris were: 11.9%,10.2% and 5.7% at 12 years. SCAs accounted for 30.5% (n = 528/1,732) of all deaths due to cardiovascular causes. The vast majority of SCAs (95.6%) occurred in patients without implantable cardioverter defibrillator (ICD) devices or among patients with no recurrent hospitalizations for coronary artery disease (89.1%).

CONCLUSIONS

SCAs accounted for less than a third of all deaths due to cardiovascular causes among patients with previous ACS. Incidence of SCA is highest among STEMI and NSTEMI patients. After the hospital discharge, most of SCAs happen to NSTEMI patients.

Time Trend in Incidence of Sudden Cardiac Death After Percutaneous Coronary Intervention from 2009 to 2017 (from the Japanese Multicenter Registry)

The advances in the integrated management of patients with coronary artery disease undergoing percutaneous coronary intervention (PCI) have reduced subsequent cardiovascular events. Nonetheless, sudden cardiac death (SCD) remains a major concern. Therefore, we aimed to investigate the time trend in SCD incidence after PCI and to identify the clinical factors contributing to SCD. From a prospective, multicenter cohort registry in Japan, 8,723 consecutive patients with coronary artery disease undergoing PCI between 2009 and 2017 were included. We evaluated the SCD incidence 2 years after PCI; all death events were adjudicated, and SCD was defined as unexpected death without a noncardiovascular cause in a previously stable patient within 24 hours from the onset. The Fine and Gray method was used to identify the factors associated with SCD. Overall, the mean age of the patients was 68.3 ± 11.3 years, and 1,173 patients (13.4%) had heart failure (HF). During the study period, the use of second-generation drug-eluting stents increased. The 2-year cumulative incidence of all-cause mortality and SCD was 4.29% and 0.45%, respectively. All-cause mortality remained stable during the study period (p for trend = 0.98), whereas the crude incidence of SCD tended to decrease over the study period (p for trend = 0.052). HF was the strongest predictor associated with the risk of SCD (crude incidence [vs non-HF] 2.13% vs 0.19%; p <0.001). In conclusion, the incidence of SCD after PCI decreased over the last decade, albeit the high incidence of SCD among patients with HF remains concerning.

Prognostic Implications of Left Ventricular Ejection Fraction and Left Ventricular End-Diastolic Diameter on Clinical Outcomes in Patients with ICD

Background: Left ventricular ejection fraction (LVEF) is a suboptimal indicator of risk stratification for patients with an implantable cardioverter defibrillator (ICD). Studies have shown that left ventricular end-diastolic diameter (LVEDD) was associated with all-cause mortality and ventricular arrhythmias. We examined the quantified prognostic value of LVEF and LVEDD for clinical outcomes, respectively. Method: This study retrospectively enrolled patients with ICD implantation in a single center. The associations between LVEF or LVEDD and all-cause mortality and appropriate shocks were analyzed using Cox regression and Fine-gray competing risk regression, respectively. Result: During a median follow up of 59.6 months, 168/630 (26.7%) patients died. LVEF and LVEDD were strongly associated with all-cause mortality (LVEF per 10%: HR 0.77, 95%CI 0.64−0.93, p = 0.006; LVEDD per 10 mm: HR 1.54, 95%CI 1.27−1.85, p < 0.001). After a median interrogation time of 37.1 months, 156 (24.8%) patients received at least one shock. LVEF was not associated with appropriate shock, whereas larger LVEDD (per 10 mm) was significantly associated with a higher risk of shock (HR: 1.27, 95%CI 1.06−1.52, p = 0.008). The addition of LVEF or LVEDD to clinical factors provided incremental prognostic value and discrimination improvement for all-cause mortality, while only the addition of LVEDD to clinical factors improved prognostic value for shock intervention. Conclusions: Baseline LVEF and LVEDD show a linear relationship with all-cause mortality in patients with ICD. However, whereas LVEF is not associated with shock, a linear relationship exists between LVEDD and appropriate shock. LVEDD adds more predictive value in relation to all-cause mortality and appropriate shocks than LVEF.

The Role of Genetics in Risk Stratification Strategy of Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is a heart disorder of diverse etiologies that affects millions of people worldwide, associated with increased mortality rate and high risk of sudden cardiac death. Patients with DCM are characterized by a wide range of clinical and pre-clinical phenotypes which are related with different outcomes. Dominant studies have failed to demonstrate the value of the left ventricular ejection fraction as the only indicator for patients' assessment and arrhythmic events prediction, thus making sudden cardiac death (SCD) risk stratification strategy improvement, more crucial than ever. The multifactorial two-step approach, examining non-invasive and invasive risk factors, represents an alternative process that enhances the accurate diagnosis and the individualization of patients' management. The role of genetic testing, regarding diagnosis and decision making, is of great importance, as pathogenic variants have been detected in several patients either they had a disease relative family history or not. At the same time there are specific genes mutations that have been associated with the prognosis of the disease. The aim of this review is to summarize the latest data regarding the genetic substrate of DCM and the value of genetic testing in patients' assessment and arrhythmic risk evaluation. Undoubtedly, the appropriate application of genetic testing and the thoughtful analysis of the results will contribute to the identification of patients who will receive major benefit from an implantable defibrillator as preventive treatment of SCD.

Trends in survival after cardiac arrest: a Swedish nationwide study over 30 years

AIMS

Trends in characteristics, management, and survival in out-of-hospital cardiac arrest (OHCA) and in-hospital cardiac arrest (IHCA) were studied in the Swedish Cardiopulmonary Resuscitation Registry (SCRR).

METHODS AND RESULTS

The SCRR was used to study 106 296 cases of OHCA (1990-2020) and 30 032 cases of IHCA (2004-20) in whom resuscitation was attempted. In OHCA, survival increased from 5.7% in 1990 to 10.1% in 2011 and remained unchanged thereafter. Odds ratios [ORs, 95% confidence interval (CI)] for survival in 2017-20 vs. 1990-93 were 2.17 (1.93-2.43) overall, 2.36 (2.07-2.71) for men, and 1.67 (1.34-2.10) for women. Survival increased for all aetiologies, except trauma, suffocation, and drowning. OR for cardiac aetiology in 2017-20 vs. 1990-93 was 0.45 (0.42-0.48). Bystander cardiopulmonary resuscitation increased from 30.9% to 82.2%. Shockable rhythm decreased from 39.5% in 1990 to 17.4% in 2020. Use of targeted temperature management decreased from 42.1% (2010) to 18.2% (2020). In IHCA, OR for survival in 2017-20 vs. 2004-07 was 1.18 (1.06-1.31), showing a non-linear trend with probability of survival increasing by 46.6% during 2011-20. Myocardial ischaemia or infarction as aetiology decreased during 2004-20 from 67.4% to 28.3% [OR 0.30 (0.27-0.34)]. Shockable rhythm decreased from 37.4% to 23.0% [OR 0.57 (0.51-0.64)]. Approximately 90% of survivors (IHCA and OHCA) had no or mild neurological sequelae.

CONCLUSION

Survival increased 2.2-fold in OHCA during 1990-2020 but without any improvement in the final decade, and 1.2-fold in IHCA during 2004-20, with rapid improvement the last decade. Cardiac aetiology and shockable rhythms were halved. Neurological outcome has not improved.