The aim of the Special Issue \"Molecular study of sudden cardiac death\" was to gather new studies on the molecular biology of cardiac death, from both a fundamental and clinical perspective [...].

UNASSIGNED: Sudden cardiac death in athletes is a rare occurrence, the most common cause being hypertrophic cardiomyopathy, which increases the risk of sustained ventricular tachycardia or ventricular fibrillation. Most of these young athletes are asymptomatic prior to the cardiac arrest. Several electrocardiogram criteria such as the European Society of Cardiology group 2 Criteria changes, Seattle Criteria, Refined Criteria, and most recently the 2017 International Criteria, have sought to improve the accuracy of identifying these at-risk athletes during pre-participation screening while minimising unnecessary investigations for the majority of athletes at low risk.We aimed to compare the above four criteria in our Singapore athlete population to identify which criterion performed the best in detecting cardiac abnormalities on echocardiography.
UNASSIGNED: Out of 1,515 athletes included in Changi General Hospital, Singapore registry between June 2007 and June 2014, the electrocardiograms of 270 athletes with further cardiac investigations were analysed. We compared the above four electrocardiographic criteria to evaluate which performed best for detecting cardiac abnormalities on echocardiography in our Southeast Asian athlete population.
UNASSIGNED: The European Society of Cardiology, Seattle, Refined and 2017 International Criteria had a sensitivity of 20%, 0%, 20% and 5%, respectively; a specificity of 64%, 93%, 84% and 97%, respectively; a positive predictive value of 4%, 0%, 9% and 11%, respectively; and a negative predictive value of 91%, 92%, 93% and 93%, respectively for detecting abnormalities on echocardiography.
UNASSIGNED: The latest 2017 International Criteria performed the best as it had the highest specificity and positive predictive value, joint highest negative predictive value, and lowest false positive rate.

暂无摘要。

BACKGROUND: Cardiac fibrosis plays a major pathophysiological role in any form of chronic heart disease, and high levels are associated with poor outcome. Diffuse and focal cardiac fibrosis are different subtypes, which have different pathomechanisms and prognostic implications. The total fibrosis burden in endomyocardial biopsy tissue was recently proved to play an independent prognostic role in aortic stenosis patients after transcatheter aortic valve implantation (TAVI).
OBJECTIVE: Here, for the first time, we aim to assess the specific impact of different fibrosis subtypes on sudden cardiac death (SCD) as a primary reason for cardiovascular mortality after TAVI.
METHODS: The fibrosis pattern was assessed histologically in the left ventricular biopsies obtained during TAVI interventions in 161 patients, who received a structured follow-up thereafter.
RESULTS: Receiver operating characteristic analyses, performed 6, 12, 24 and 48 months after TAVI, showed diffuse, but not focal, fibrosis as a significant predictor for SCD at all timepoints, with the highest area under the curve at the first time point and a decrease in its SCD predictivity over time. In both multivariate Cox proportional hazards and Fine-Gray competing risk models, including both fibrosis subtypes, as well as age, sex and ejection fraction, high diffuse fibrosis remained statistically significant. Accordingly, it represents an independent SCD predictor, most importantly for the occurrence of early events.
CONCLUSIONS: The burden of diffuse cardiac fibrosis plays an important and independent prognostic role regarding SCD early after TAVI. Therefore, the histological evaluation of fibrosis topography has value as a prognostic tool for TAVI patients and may help to tailor individualised approaches to optimise their postinterventional management.

The evidence about the associations of leukocyte telomere length (LTL) and intermediary cardiovascular phenotypes with adverse cardiovascular outcomes is inconclusive. This study assessed these relationships with cardiovascular imaging, electrocardiography, and the risks of sudden cardiac death (SCD), coronary events, and heart failure (HF) admission. We conducted a cross-sectional analysis of UK Biobank participants enrolled between 2006 and 2010. LTL was measured using quantitative polymerase chain reactions. Electronic health records were used to determine the incidence of SCD, coronary events, and HF admission. Cardiovascular measurements were made using cardiovascular magnetic resonance imaging and machine learning. The associations of LTL with SCD, coronary events, and HF admission and cardiac magnetic resonance imaging, electrocardiogram parameters of 33,043 and 19,554 participants were evaluated by multivariate regression. The median (interquartile range) follow-up period was 11.9 (11.2-12.6) years. Data was analyzed from January to May 2023. Among the 403,382 white participants without coronary artery disease or HF, 181,637 (45.0%) were male with a mean age of 57.1 years old. LTL was independently negatively associated with a risk of SCD (LTL third quartile vs first quartile: hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.72-0.92), coronary events (LTL third quartile vs first quartile: HR: 0.88, 95% CI: 0.84-0.92), and HF admission (LTL fourth quartile vs first quartile: HR: 0.84, 95% CI: 0.74-0.95). LTL was also independently positively associated with cardiac remodeling, specifically left ventricular mass index, left-ventricular-end systolic and diastolic volumes, mean left ventricular myocardial wall thickness, left ventricular stroke volume, and with electrocardiogram changes along the negative degree of T-axis. Cross-sectional study results showed that LTL was positively associated with heart size and cardiac function in middle age, but electrocardiography results did not show these associations, which could explain the negative association between LTL and risk of SCD, coronary events, and HF admission in UK Biobank participants.

肥厚型心肌病是常见的遗传性心脏疾病，也是引起年轻人心原性猝死的主要原因之一，经过谨慎评估后植入心律转复除颤器能够有效减少猝死发生。近年来，随着肥厚型心肌病新的猝死风险指标的不断出现，对猝死的评估也更加具体和精确，但是鉴于猝死发生的不确定性和低概率性，目前尚没有统一而全面的猝死风险评估标准。该文结合美国及欧洲最新指南，对肥厚型心肌病传统和新兴的风险预测因子进行综述，探讨进行室间隔切除术的梗阻性肥厚型心肌病患者的术后猝死风险，以期为心原性猝死的风险评估及预防提供参考。.

暂无摘要。

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

UNASSIGNED: Hypertrophic cardiomyopathy (HCM) is defined clinically by pathological left ventricular hypertrophy. We have previously developed a plasma proteomics biomarker panel that correlates with clinical markers of disease severity and sudden cardiac death risk in adult patients with HCM. The aim of this study was to investigate the utility of adult biomarkers and perform new discoveries in proteomics for childhood-onset HCM.
UNASSIGNED: Fifty-nine protein biomarkers were identified from an exploratory plasma proteomics screen in children with HCM and augmented into our existing multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay. The association of these biomarkers with clinical phenotypes and outcomes was prospectively tested in plasma collected from 148 children with HCM and 50 healthy controls. Machine learning techniques were used to develop novel pediatric plasma proteomic biomarker panels.
UNASSIGNED: Four previously identified adult HCM markers (aldolase fructose-bisphosphate A, complement C3a, talin-1, and thrombospondin 1) and 3 new markers (glycogen phosphorylase B, lipoprotein a and profilin 1) were elevated in pediatric HCM. Using supervised machine learning applied to training (n=137) and validation cohorts (n=61), this 7-biomarker panel differentiated HCM from healthy controls with an area under the curve of 1.0 in the training data set (sensitivity 100% [95% CI, 95-100]; specificity 100% [95% CI, 96-100]) and 0.82 in the validation data set (sensitivity 75% [95% CI, 59-86]; specificity 88% [95% CI, 75-94]). Reduced circulating levels of 4 other peptides (apolipoprotein L1, complement 5b, immunoglobulin heavy constant epsilon, and serum amyloid A4) found in children with high sudden cardiac death risk provided complete separation from the low and intermediate risk groups and predicted mortality and adverse arrhythmic outcomes (hazard ratio, 2.04 [95% CI, 1.0-4.2]; P=0.044).
UNASSIGNED: In children, a 7-biomarker proteomics panel can distinguish HCM from controls with high sensitivity and specificity, and another 4-biomarker panel identifies those at high risk of adverse arrhythmic outcomes, including sudden cardiac death.

BACKGROUND: Public training in cardiopulmonary resuscitation and treatment in emergency and intensive care unit have made tremendous progress. However, cardiac arrest remains a major health burden worldwide, with brain damage being a significant contributor to disability and mortality. Lipocalin-type prostaglandin D synthase (L-PGDS), which is mainly localised in the central nervous system, has been previously shown to inhibit postischemia neuronal apoptosis. Therefore, we aim to observe whether serum L-PGDS can serve as a potential biomarker and explore its role in determining the severity and prognosis of patients who have achieved restoration of spontaneous circulation (ROSC).
METHODS: This is a prospective observational study. The participants (n = 60) who achieve ROSC will be distributed into two groups (non-survivor and survivor) based on 28-day survival. Healthy volunteers (n = 30) will be enrolled as controls. Each individual\'s relevant information will be extracted from Electronic Medical Record System in Xinhua Hospital, including demographic characteristics, clinical data, laboratory findings and so on. On days 1, 3 and 7 after ROSC, blood samples will be drawn and batch tested on the level of serum neuron-specific enolase, soluble protein 100β, L-PGDS, procalcitonin, tumour necrosis factor-alpha and interleukin-6. The cerebral performance category score was assessed on the 28th day after ROSC.
BACKGROUND: This study was performed with the approval of the Clinical Ethical Committee of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (Approval No. XHEC-C-2023-130-1). The results will be published in a peer-reviewed journal.
BACKGROUND: Chinese Clinical Trial Registry (ChiCTR2300078564).