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Background: Myocardial strain using cardiac magnetic resonance (CMR) is a sensitive marker for predicting adverse outcomes in many cardiac disease states, but the prognostic value in the general population has not been studied conclusively., Objectives: The goal of this study was to assess the independent prognostic value of CMR feature tracking (FT)-derived LV global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) metrics in predicting adverse outcomes (heart failure, myocardial infarction, stroke, and death)., Methods: Participants from the UK Biobank population imaging study were included. Univariable and multivariable Cox models were used for each outcome and each strain marker (GLS, GCS, GRS) separately. The multivariable models were tested with adjustment for prognostically important clinical features and conventional global LV imaging markers relevant for each outcome., Results: Overall, 45,700 participants were included in the study (average age 65 ± 8 years), with a median follow-up period of 3 years. All univariable and multivariable models demonstrated that lower absolute GLS, GCS, and GRS were associated with increased incidence of heart failure, myocardial infarction, stroke, and death. All strain markers were independent predictors (incrementally above some respective conventional LV imaging markers) for the morbidity outcomes, but only GLS predicted death independently: (HR: 1.18; 95% CI: 1.07-1.30)., Conclusions: In the general population, LV strain metrics derived using CMR-FT in radial, circumferential, and longitudinal directions are strongly and independently predictive of heart failure, myocardial infarction, and stroke, but only GLS is independently predictive of death in an adult population cohort., Competing Interests: Funding Support and Author Disclosures This work acknowledges the support of the National Institute for Health and Care Research Barts Biomedical Research Centre (NIHR203330); a delivery partnership of Barts Health NHS Trust, Queen Mary University of London, St George’s University Hospitals NHS Foundation Trust and St George’s University of London. Barts Charity (G-002346) contributed to fees required to access UK Biobank data [access application #2964]. This paper is supported by the London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare (AI4VBH), which is funded from the Data to Early Diagnosis and Precision Medicine strand of the government’s Industrial Strategy Challenge Fund, managed and delivered by Innovate UK on behalf of UK Research and Innovation (UKRI). Views expressed are those of the authors and not necessarily those of the AI4VBH Consortium members, the NHS, Innovate UK, or UKRI. The funders did not have any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Dr Petersen acknowledges the British Heart Foundation for funding the manual analysis to create a cardiovascular magnetic resonance imaging reference standard for the UK Biobank imaging resource in 5,000 CMR scans (PG/14/89/31194). Dr Aung acknowledges the Medical Research Council for supporting his Clinician Scientist Fellowship (MR/X020924/1). Dr Chadalavada was funded by European Union's Horizon 2020 research and innovation program under grant agreement no. 825903 (euCanSHare project). Dr Rauseo is supported by the mini-Centre for Doctoral Training (CDT) award through the Faculty of Science and Engineering, Queen Mary University of London, United Kingdom. Dr Naderi was supported by the British Heart Foundation Pat Merriman Clinical Research Training Fellowship (FS/20/22/34640). Dr Petersen and Dr Lee acknowledge support from the SmartHeart EPSRC program grant (EP/P001009/1) and the European Union's Horizon 2020 research and innovation program under grant agreement No 825903 (euCanSHare project). Dr Petersen has served as a consultant for Cardiovascular Imaging Inc, Calgary, Alberta, Canada. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: It has been previously reported during the first COVID-19 outbreak that patients presenting with ST-segment elevation myocardial infarction (STEMI) and concurrent COVID-19 infection have increased thrombus burden and poorer outcomes. To date, there have been no reports comparing the outcomes of COVID-19-positive STEMI patients across all waves of the pandemic., Objectives: This study compared the baseline demographic, procedural, and angiographic characteristics alongside the clinical outcomes of patients presenting with STEMI and concurrent COVID-19 infection across the COVID-19 pandemic in the United Kingdom., Methods: This was a single-center, observational study of 1,269 consecutive patients admitted with confirmed STEMI treated with percutaneous coronary intervention (between January 3, 2020 and October 3, 2022). COVID-19-positive patients were split into 3 groups based upon the time course of the pandemic, and a comparison was made between waves., Results: A total of 154 COVID-19-positive patients with STEMI were included in the present analysis and were compared with 1,115 COVID-19-negative patients. Early during the pandemic (wave 1), STEMI patients presenting with concurrent COVID-19 infection had high rates of cardiac arrest, evidence of increased thrombus burden, bigger infarcts, and worse outcomes. However, by wave 3, no differences existed in outcomes between COVID-19-positive and -negative patients, with significant differences compared with earlier COVID-19-positive patients. Poor outcomes later in the study period were predominantly in unvaccinated individuals., Conclusions: Significant changes have occurred in the clinical characteristics, angiographic features, and outcomes of STEMI patients with COVID-19 infection treated by primary percutaneous coronary intervention during the course of the pandemic. Importantly, outcomes of recent waves and in vaccinated individuals are no different to a non-COVID-19 population., Competing Interests: Funding Support and Author Disclosures Dr Rathod has received funding from the National Institute for Health and Research (NIHR) in the form of an Academic Clinical Lectureship. Dr Jones has received funding from the Barts Charity. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Causes and precipitating factors of sudden cardiac death (SCD) in adolescents are poorly understood., Objectives: The authors sought to investigate the etiologies of SCD and their association with physical activity in a large cohort of adolescents., Methods: Between 1994 and June 2022, 7,675 cases of SCD were consecutively referred to our national cardiac pathology center; 756 (10%) were adolescents. All cases underwent detailed autopsy evaluation by expert cardiac pathologists. Clinical information was obtained from referring coroners., Results: A structurally normal heart, indicative of sudden arrhythmic death syndrome was the most common autopsy finding (n = 474; 63%). Myocardial diseases were detected in 163 cases (22%), including arrhythmogenic cardiomyopathy (n = 36; 5%), hypertrophic cardiomyopathy (n = 31; 4%), idiopathic left ventricular hypertrophy (n = 31; 4%), and myocarditis (n = 30; 4%). Coronary artery anomalies were identified in 17 cases (2%). Decedents were competitive athletes in 128 cases (17%), and 159 decedents (21%) died during exercise. Arrhythmogenic cardiomyopathy was diagnosed in 8% of athletes compared with 4% of nonathletes (P = 0.05); coronary artery anomalies were significantly more common in athletes (9% vs 1%; P < 0.001), as well as commotio cordis (5% compared with 1% in nonathletes; P = 0.001). The 3 main comorbidities were asthma (n = 58; 8%), epilepsy (n = 44; 6%), and obesity (n = 40; 5%)., Conclusions: Sudden arrhythmic death syndrome and myocardial diseases are the most common conditions diagnosed at autopsy in adolescent victims of SCD. Among causes of SCD, arrhythmogenic cardiomyopathy, coronary artery anomalies, and commotio cordis are more common in young athletes than in similar age sedentary individuals., Competing Interests: Funding Support and Author Disclosures The charity Cardiac Risk in the Young fund the Cardiac Risk in the Young Cardiovascular Pathology Laboratories. Dr Finocchiaro is partly funded by the charity Cardiac Risk in the Young. Dr Westaby is funded by the National Institute for Health and Care Research. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Emerging evidence has linked sleep behaviors with the risk of cardiac arrhythmias. The various sleep behaviors are typically correlated; however, most of the previous studies only focused on the individual sleep behavior, without considering the overall sleep patterns., Objectives: The purpose of this study was to prospectively investigate the associations between a healthy sleep pattern with the risks of cardiac arrhythmias., Methods: A total of 403,187 participants from UK Biobank were included. A healthy sleep pattern was defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness. Weighted genetic risk score for atrial fibrillation was calculated., Results: The healthy sleep pattern was significantly associated with lower risks of atrial fibrillation/flutter (AF) (HR comparing extreme categories: 0.71; 95% CI: 0.64-0.80) and bradyarrhythmia (HR: 0.65; 95% CI: 0.54-0.77), but not ventricular arrhythmias, after adjustment for demographic, lifestyle, and genetic risk factors. Compared with individuals with a healthy sleep score of 0-1 (poor sleep group), those with a healthy sleep score of 5 had a 29% and 35% lower risk of developing AF and bradyarrhythmia, respectively. Additionally, the genetic predisposition to AF significantly modified the association of the healthy sleep pattern with the risk of AF (P interaction = 0.017). The inverse association of the healthy sleep pattern with the risk of AF was stronger among those with a lower genetic risk of AF., Conclusions: Our results indicate that a healthy sleep pattern is associated with lower risks of AF and bradyarrhythmia, independent of traditional risk factors, and the association with AF is modified by genetic susceptibility., Competing Interests: Funding Support and Author Disclosures The study has been conducted using the UK Biobank Resource under Application 29256. The study was supported by grants from the National Heart, Lung, and Blood Institute (HL071981, HL034594, HL126024), the National Institute of Diabetes and Digestive and Kidney Diseases (DK115679, DK091718, DK100383), the Fogarty International Center (TW010790), and Tulane Research Centers of Excellence Awards. Dr Li was the recipient of the American Heart Association Predoctoral Fellowship Award (19PRE34380036). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Treatment guidelines for prediabetes primarily focus on glycemic control and lifestyle management. Few evidence-based cardiovascular and kidney risk-reduction strategies are available in this population., Objectives: This study sought to characterize cardiovascular and kidney outcomes across the glycemic spectrum., Methods: Among participants in the UK Biobank without prevalent type 1 diabetes, cardiovascular disease, or kidney disease, Cox models tested the association of glycemic exposures (type 2 diabetes [T2D], prediabetes, normoglycemia) with outcomes (atherosclerotic cardiovascular disease [ASCVD], chronic kidney disease [CKD], and heart failure), adjusting for demographic, lifestyle, and cardiometabolic risk factors., Results: Among 336,709 individuals (mean age: 56.3 years, 55.4% female), 46,911 (13.9%) had prediabetes and 12,717 (3.8%) had T2D. Over median follow-up of 11.1 years, 6,476 (13.8%) individuals with prediabetes developed ≥1 incident outcome, of whom only 802 (12.4%) developed T2D prior to an incident diagnosis. Prediabetes and T2D were independently associated with ASCVD (prediabetes: adjusted HR [aHR]: 1.11; 95% CI: 1.08-1.15; P < 0.001; T2D: aHR: 1.44; 95% CI: 1.37-1.51; P < 0.001), CKD (prediabetes: aHR: 1.08; 95% CI: 1.02-1.14; P < 0.001; T2D: aHR: 1.57; 95% CI: 1.46-1.69; P < 0.001), and heart failure (prediabetes: aHR: 1.07; 95% CI: 1.01-1.14; P = 0.03; T2D: aHR: 1.25; 95% CI: 1.14-1.37; P < 0.001). Compared with hemoglobin A1c (HbA1c) <5.0%, covariate-adjusted risks increased significantly for ASCVD above HbA1c of 5.4%, CKD above HbA1c of 6.2%, and heart failure above HbA1c of 7.0%., Conclusions: Prediabetes and T2D were associated with ASCVD, CKD, and heart failure, but a substantial gradient of risk was observed across HbA 1c levels below the threshold for diabetes. These findings highlight the need to design risk-reduction strategies across the glycemic spectrum., Competing Interests: Funding Support and Author Disclosures Dr Honigberg is supported by a grant from the National Heart, Lung, and Blood Institute (T32HL094301-07). Dr Natarajan is supported by grants from the National Heart, Lung, and Blood Institute (R01HL142711, R01HL148050, R01HL148565, R01HL151283), Fondation Leducq (TNE-18CVD04), and a Hassenfeld Scholar Award from Massachusetts General Hospital; has received grant support from Amgen, Apple, Boston Scientific, and Novartis; has received personal fees from Apple, Blackstone Life Sciences, Genentech, and Novartis; and Dr Natarajan’s spouse has been employed by Vertex, all unrelated to the present work. Dr Vaduganathan has received research grant support or served on advisory boards for American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, Boehringer Ingelheim, Cytokinetics, Lexicon Pharmaceuticals, and Relypsa; has had speaking engagements with Novartis and Roche Diagnostics; and has participated on clinical endpoint committees for studies sponsored by Galmed and Novartis. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: In-hospital mortality is a rare, yet feared complication following cardiac surgery in adult congenital heart disease (ACHD). A risk score, developed and validated in ACHD, can be helpful to optimize risk assessment., Objectives: The purpose of this study was to assess the performance of EuroSCORE II components and procedure-related Adult Congenital Heart Surgery (ACHS) score, identify additional risk factors, and develop a novel risk score for predicting in-hospital mortality after ACHD surgery., Methods: We assessed perioperative survival in patients aged >16 years undergoing congenital heart surgery in a large tertiary center between 2003 and 2019. A risk variable-derived PEACH (PErioperative ACHd) score was calculated for each patient. Internal and external validation of the model was undertaken, including testing in a validation cohort of patients operated in a second European ACHD center., Results: The development cohort comprised 1,782 procedures performed during the study period. Re-sternotomy was undertaken in 897 (50.3%). There were 31 (1.7%) in-hospital deaths. The PEACH score showed excellent discrimination ability (area under the curve [AUC]: 0.88; 95% CI: 0.83-0.94), and performed better than the ACHS score in our population (ACHS AUC: 0.69; 95% CI: 0.6-0.78; P = 0.0003). A simple 3-tiered risk stratification was formed: PEACH score 0 (in-hospital mortality 0.2%), 1-2 (3.6%), and ≥3 (17.2%). In a validation cohort of 975 procedures, the PEACH score retained its discriminative ability (AUC: 0.75; 95% CI: 0.72-0.77) and was well calibrated (Hosmer-Lemeshow chi-square goodness-of-fit P = 0.55). There was agreement in expected and observed perioperative mortality between cohorts., Conclusions: The PEACH score is a simple, novel perioperative risk score developed and validated specifically for ACHD patients undergoing cardiac surgery., Competing Interests: Funding Support and Author Disclosures Dr Constantine has received educational grants, personal fees, and nonfinancial support from Janssen-Cilag Limited. Prof Babu-Narayan is supported by the British Heart Foundation. Prof Dimopoulos has received nonfinancial support from Janssen-Cilag Limited; and has been a consultant to and received grants and personal fees from Janssen-Cilag Limited, Pfizer, GlaxoSmithKline, and Bayer/Merck Sharp & Dohme. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. All rights reserved.)

An increasing number of people are now living with cardiovascular disease (CVD), with concomitant CVD-related hospitalizations, operations, and prescriptions. To ultimately deliver optimal cardiovascular care, access to population-based biobanks with data on multiomics, phenotypes, and lifestyle risk factors are crucial. UK Biobank is a cohort study that incorporated data between 2006 and 2010 from over half a million individuals (40 to 69 years of age) at recruitment from across the United Kingdom. As one of the most accessible, largest, and in-depth cohort studies in the world, UK Biobank continues to enhance the resource with the addition of data from various omics platforms (eg, genomics, metabolomics, proteomics), multimodal imaging, self-reported risk factors and health outcomes, and linkage to electronic health records. The vision of UK Biobank is to allow as many researchers as possible to apply their expertise and imagination to undertake research to prevent, diagnose, and treat a wide range of chronic conditions, including CVD., Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021. Published by Elsevier Inc.)

Background: Risk stratification for ventricular arrhythmias (VA) and sudden death in nonischemic dilated cardiomyopathy (DCM) remains suboptimal., Objectives: The goal of this study was to provide an improved risk stratification algorithm for VA and sudden death in DCM., Methods: This was a retrospective cohort study of consecutive patients with DCM who underwent cardiac magnetic resonance with late gadolinium enhancement (LGE) at 2 tertiary referral centers. The combined arrhythmic endpoint included appropriate implantable cardioverter-defibrillator therapies, sustained ventricular tachycardia, resuscitated cardiac arrest, and sudden death., Results: In 1,165 patients with a median follow-up of 36 months, LGE was an independent and strong predictor of the arrhythmic endpoint (hazard ratio: 9.7; p < 0.001). This association was consistent across all strata of left ventricular ejection fraction (LVEF). Epicardial LGE, transmural LGE, and combined septal and free-wall LGE were all associated with heightened risk. A simple algorithm combining LGE and 3 LVEF strata (i.e., ≤20%, 21% to 35%, >35%) was significantly superior to LVEF with the 35% cutoff (Harrell's C statistic: 0.8 vs. 0.69; area under the curve: 0.82 vs. 0.7; p < 0.001) and reclassified the arrhythmic risk of 34% of patients with DCM. LGE-negative patients with LVEF 21% to 35% had low risk (annual event rate 0.7%), whereas those with high-risk LGE distributions and LVEF >35% had significantly higher risk (annual event rate 3%; p = 0.007)., Conclusions: In a large cohort of patients with DCM, LGE was found to be a significant, consistent, and strong predictor of VA or sudden death. Specific high-risk LGE distributions were identified. A new clinical algorithm integrating LGE and LVEF significantly improved the risk stratification for VA and sudden death, with relevant implications for implantable cardioverter-defibrillator allocation., Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: The "gray zone" of myocardial fibrosis (GZF) on cardiovascular magnetic resonance may be a substrate for ventricular arrhythmias (VAs)., Objectives: The purpose of this study was to determine whether GZF predicts sudden cardiac death (SCD) and VAs (ventricular fibrillation or sustained ventricular tachycardia) in patients with coronary artery disease (CAD) and a wide range of left ventricular ejection fractions (LVEFs)., Methods: In this retrospective study of CAD patients, the presence of myocardial fibrosis on visual assessment (MF VA ) and GZF mass in patients with MF VA were assessed in relation to SCD and the composite, arrhythmic endpoint of SCD or VAs., Results: Among 979 patients (mean age [± SD]: 65.8 ± 12.3 years), 29 (2.96%) experienced SCD and 80 (8.17%) met the arrhythmic endpoint over median 5.82 years (interquartile range: 4.1 to 7.3 years). In the whole cohort, MF VA was strongly associated with SCD (hazard ratio: 10.1; 95% confidence interval [CI]: 1.42 to 1,278.9) and the arrhythmic endpoint (hazard ratio: 28.0; 95% CI: 4.07 to 3,525.4). In competing risks analyses, associations between LVEF <35% and SCD (subdistribution hazard ratio [sHR]: 2.99; 95% CI: 1.42 to 6.31) and the arrhythmic endpoint (sHR: 4.71; 95% CI: 2.97 to 7.47) were weaker. In competing risk analyses of the MF VA subcohort (n = 832), GZF using the 3SD method (GZF 3SD ) >5.0 g was strongly associated with SCD (sHR: 10.8; 95% CI: 3.74 to 30.9) and the arrhythmic endpoint (sHR: 7.40; 95% CI: 4.29 to 12.8). Associations between LVEF <35% and SCD (sHR: 2.62; 95% CI: 1.24 to 5.52) and the arrhythmic endpoint (sHR: 4.14; 95% CI: 2.61 to 6.57) were weaker., Conclusions: In CAD patients, MF VA plus quantified GZF 3SD mass was more strongly associated with SCD and VAs than LVEF. In selecting patients for implantable cardioverter-defibrillators, assessment of MF VA followed by quantification of GZF 3SD mass may be preferable to LVEF., Competing Interests: Author Disclosures Medtronic provided support for this study in the form of an unrestricted educational grant. Medtronic provided funding for Dr. Zegard’s salary as a research fellow and had no participation in the study. Dr. Leyva has served as a consultant for and has received research funding from Medtronic Inc., Boston Scientific, Abbott, Microport, and Biotronik. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)