Risk Factor For Sudden Cardiac Death Research Articles

Short-term exposures to temperature and risk of sudden cardiac death in women: A case-crossover analysis in the Nurses' Health Study.

Sudden cardiac death (SCD) is a major source of mortality and is the first manifestation of heart disease for most cases. Thus, there is a definite need to identify risk factors for SCD that can be modified on the population level. Short-term exposures to temperature have been implicated as a potential risk factor. Our objective was to determine if short-term temperature exposures were associated with increased risk of SCD in a US-based time-stratified case-crossover study. A total of 465 cases of SCD were identified among participants of the prospective Nurses' Health Study (NHS). Control days were selected from all other matching days of the week within the same month as the case day. Average ambient temperature on the current day (Lag0) and preceding 27 days (Lags1-27) was determined at the residence level using 800-m resolution estimates. Conditional logistic distributed lag nonlinear models (DLNMs) were used to assess the relative risk (RR) of the full range of temperature exposures over the lag period. Warmer exposures in the days before event and colder temperatures 21-28 days prior were associated with increased risks of SCD. These results were driven by associations in regions other than the Northeast and among married women. Both warm and cold ambient temperatures are suggestively associated with risks of SCD among middle-aged and older women living across the United States.

Risk factors for mortality in post-myocardial infarction patients: insights from the improve SCA bridge study

BackgroundUnderutilization of implantable cardioverter defibrillators (ICD) to prevent sudden cardiac death (SCD) in post-myocardial infarction (MI) patients remains an issue across several geographies. A better understanding of risk factors for SCD in post-MI patients from regions with low ICD adoption rates will help identify those who will benefit from an ICD. This analysis assessed risk factors for all-cause and cardiovascular-related mortality in post-MI patients from the Improve Sudden Cardiac Arrest (SCA) Bridge Trial.ResultsFor the entire cohort, the overall 1-year mortality rate was 5.9% (88/1491) and 3.4% (51/1491) for all-cause and cardiovascular mortality, respectively, with 76.5% of all cardiac deaths being from SCD. A multivariate model determined increased age, reduced left ventricular ejection fraction (LVEF), increased time from myocardial infarction to hospital admission, being female, being from Southeast Asia (SEA), and having coronary artery disease to be significant risk factors for all-cause mortality. The risk factors for cardiovascular-related mortality revealed increased age, reduced LVEF, and being from SEA as significant risk factors.ConclusionsWe show several characteristics as being predictors of cardiovascular-related mortality in post-MI patients from the Improve SCA Bridge study. Patients who experience an MI and present with these characteristics would benefit from a referral to an electrophysiologist for further SCD risk stratification and management and possible subsequent ICD implantation to reduce unnecessary death.

Sudden Cardiac Death Risk Stratification in Heart Failure With Preserved Ejection Fraction.

Heart failure with preserved ejection fraction (HFpEF) poses a significant clinical challenge, with sudden cardiac death (SCD) emerging as one of the leading causes of mortality. Despite advancements in cardiovascular medicine, predicting and preventing SCD in HFpEF remains complex due to multifactorial pathophysiological mechanisms and patient heterogeneity. Unlike heart failure with reduced ejection fraction, where impaired contractility and ventricular remodeling predominate, HFpEF pathophysiology involves heavy burden of comorbidities such as hypertension, obesity, and diabetes. Diverse mechanisms, including diastolic dysfunction, microvascular abnormalities, and inflammation, also contribute to distinct disease and SCD risk profiles. Various parameters such as clinical factors and electrocardiogram features have been proposed in SCD risk assessment. Advanced imaging modalities and biomarkers offer promise in risk prediction, yet comprehensive risk stratification models specific to HFpEF ar0e lacking. This review offers recent evidence on SCD risk factors and discusses current therapeutic strategies aimed at reducing SCD risk in HFpEF.

Additional factors associated with sudden cardiac death in HCM patients

Abstract Background Hypertrophic cardiomyopathy (HCM) is a primary myocardial disease characterized by an increase in the thickness of the left ventricular (LV) wall, which is not explained only by abnormal loading conditions. Sudden cardiac death (SCD) is the most devastating complication of HCM occurring in asymptomatic or younger patients without warning. Purpose To evaluate additional SCD risk factors in Ukrainian population of HCM patients. Materials and methods We retrospectively evaluated 350 consecutive HCM patients that were followed from 2006 to 2021 in our Cardiological Department. General clinical examination, standard 12-lead ECG, transthoracic echocardiography and 24 hours Holter ECG monitoring data were estimated. The 5-year SCD risk was calculated according to the HCM Risk-SCD score. The endpoint of the study was SCD and its surrogates, including adequate performance of the implantable cardioverter-defibrillator and successful resuscitation. Results Follow-up time was 5.0 (1.5-9.5) years. During this time, 16 patients (4.6%) reached the end point, which was 0.9%/year. According to the HCM Risk-SCD score, 5 (31.3%) of this group had a high risk of SCD (≥ 6%) and 3 (18.8%) had an intermediate risk (≥ 4% and < 6%). In multivariable Cox regression analysis adjusted for conventional SCD risk factors it was found that independent predictors of SCD were unexplained syncope (HR 3.81, 95% CI 1.11-13.12, p=0.034), systolic blood pressure (SBP) (HR 0.97 , 95% CI 0.94- 0.99, p=0.026), "infarct-like" ST elevation on ECG (HR 6.81, 95% CI 2.09-22.16, p=0.001) and PQ interval duration (HR 1.03, 95% CI 1.01-1.05, p=0.002), Harrell's C-index 0.84, 95% CI 0.73-0.95, p < 0.0001). Conclusions In our study HCM Risk-SCD score predicted SCD or surrogates only in 50% of cases. In order to improve the risk stratification some additional independent predictors of SCD can be proposed. ECG parameters ("infarct-like" ST elevation and PQ interval duration) and level of SBP were found to have SCD predictive value.

The Feasibility of Left Ventricular Strain and Strain Rate for Evaluating Hypertrophic Cardiomyopathy with Risk Factors of Sudden Cardiac Death by Feature-Tracking CMR

Sudden cardiac death (SCD) represents the most severe complication of hypertrophic cardiomyopathy (HCM). However, the relation between strain, strain rate (SR), and risk factors in SCD risk stratification remains elusive. The study aimed to assess the attenuation of strain and SR in HCM by feature tracking cardiac magnetic resonance. All strain and SRs were obtained automatically by feature tracking, with manual adjustment of endocardial and epicardial borders. Strain indicators included left ventricular global longitudinal, circumferential, global radial strain (GRS), peak diastolic-longitudinal, circumferential, and radial SR. Patients were categorized into high-risk and low-risk groups for SCD based on the 2020 American Heart Association/American College HCM risk-SCD model. The correlation between strain/SR and SCD risk factors was assessed through Spearman correlation analysis. Furthermore, a multivariate logistic regression analysis was conducted to explore the factors that influence SCD risk in HCM patients. A total of 105 HCM patients were analyzed in this study, including 38 patients in the high-risk group, and 67 patients in the low-risk group. Compared with the low-risk group, the high-risk group exhibited significantly worse strain and SR (p <0.001). Furthermore, both circumferential and GRS and SR exhibited meaningful associations with risk factors for SCD. Additionally, GRS emerged as an independent risk factor for predicting heightened SCD risk in HCM patients (p <0.001). In conclusion, left ventricular strain and SR based on feature tracking-cardiac magnetic resonance can be evaluated for SCD risk and are strongly associated with SCD risk factors.

Family history of sudden cardiac death among vctims of sudden death in yazd, iran

Objectives: A positive family history of Sudden Cardiac Death (SCD) is an independent risk factor for mortality. This study aimed to determine the prevalence of a positive family history of SCD and its associated risk factors among victims of sudden death in Yazd.&#x0D; Methods: This cross-sectional study investigated SCD cases in Yazd, Iran, in 2011. The study included victims who were aged 20 years or older, and the cause of death was the cardiac arrest within one hour of symptom onset. The data obtained from families of SCD victims through verbal autopsy interviews.&#x0D; Results: A total of 317 cases of SCD occurred among victims, resulting in an incidence rate of 139.4 per 100,000 population 26.2% had a positive family history of SCD, with a mean age of 60.4 ± 12.3 years. Individuals with a positive family history of SCD had a significantly younger mean age at the time of death (60.9 ± 12.3 vs. 66.9 ± 16.5 years, P = 0.018). The prevalence of diabetes mellitus (odds ratio 1.43, CI 95% = 1.03–1.99, P = 0.042), dyslipidemia (odds ratio 1.47, CI 95% = 1.07–2.1, P = 0.038), chronic coronary artery disease (P =0.027), and revascularization (P = 0.049) had a significant association with positive family history of SCD.&#x0D; Conclusions: This study highlights the importance of assessing family history as a risk factor for SCD, along with other risk factors such as diabetes, dyslipidemia, and chronic coronary artery disease.

Risk of Sudden Cardiac Death in Patients Undergoing Cancer Treatment

The risk of sudden cardiac death (SCD) in patients with cancer receiving cancer therapies is not well defined. In this study we aimed to (1) evaluate the risk of SCD during the first 6months of cancer treatment and (2) identify risk factors (RFs) for SCD in patients who underwent active cancer treatment. The study population comprised 8,356 patients who received any cancer treatment at the University of Rochester Medical Center from 2011 to 2020. The primary end point was the occurrence of SCD within 6months of cancer treatment. SCD was defined by using the modified Hinkle-Thaler classification. The mean age at the time of cancer treatment was 64 ± 14years and 49% were women. All-cause mortality occurred in 834 patients (10%), of whom 51 (6%) were identified as SCD. The cumulative probability of SCD at 6months was 0.6%. Age <74 years (0.042) and history of congestive heart failure (0.058) and lung cancer (0.004) were identified as independent RFs for SCD in the multivariate Cox regression models. The cumulative probability of SCD at 6months from cancer treatment initiation was significantly higher in patients with ≥2 RFs (1.6%) than in patients with 0 or 1 RF (0.5%) (log-rank p <0.001). In conclusion, our findings suggest that active cancer treatment is associated with SCD risk that is more pronounced in younger patients, patients with cancer with a history of heart failure, and those who underwent treatment for lung cancer. Future studies should address appropriate modalities for prevention and protection in this high-risk population.

Incidence, risk assessment and prevention of sudden cardiac death in cardiomyopathies.

Cardiomyopathies are a significant contributor to cardiovascular morbidity and mortality, mainly due to the development of heart failure and increased risk of sudden cardiac death (SCD). Despite improvement in survival with contemporary treatment, SCD remains an important cause of mortality in cardiomyopathies. It occurs at a rate ranging between 0.15% and 0.7% per year (depending on the cardiomyopathy), which significantly surpasses SCD incidence in the age- and sex-matched general population. The risk of SCD is affected by multiple factors including the aetiology, genetic basis, age, sex, physical exertion, the extent of myocardial disease severity, conduction system abnormalities, and electrical instability, as measured by various metrics. Over the past decades, the knowledge on the mechanisms and risk factors for SCD has substantially improved, allowing for a better-informed risk stratification. However, unresolved issues still challenge the guidance of SCD prevention in patients with cardiomyopathies. In this review, we aim to provide an in-depth discussion of the contemporary concepts pertinent to understanding the burden, risk assessment and prevention of SCD in cardiomyopathies (dilated, non-dilated left ventricular, hypertrophic, arrhythmogenic right ventricular, and restrictive). The review first focuses on SCD incidence in cardiomyopathies and then summarizes established and emerging risk factors for life-threatening arrhythmias/SCD. Finally, it discusses validated approaches to the risk assessment and evidence-based measures for SCD prevention in cardiomyopathies, pointing to the gaps in evidence and areas of uncertainties that merit future clarification.

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

Electrocardiogram (ECG) abnormalities have been evaluated as static risk markers for sudden cardiac death (SCD), but the potential importance of dynamic ECG remodelling has not been investigated. In this study, the nature and prevalence of dynamic ECG remodelling were studied among individuals who eventually suffered SCD. The study population was drawn from two prospective community-based SCD studies in Oregon (2002, discovery cohort) and California, USA (2015, validation cohort). For this present sub-study, 231 discovery cases (2015-17) and 203 validation cases (2015-21) with ≥2 archived pre-SCD ECGs were ascertained and were matched to 234 discovery and 203 validation controls based on age, sex, and duration between the ECGs. Dynamic ECG remodelling was measured as progression of a previously validated cumulative six-variable ECG electrical risk score. Oregon SCD cases displayed greater electrical risk score increase over time vs. controls [+1.06 (95% confidence interval +0.89 to +1.24) vs. -0.05 (-0.21 to +0.11); P < .001]. These findings were successfully replicated in California [+0.87 (+0.7 to +1.04) vs. -0.11 (-0.27 to 0.05); P < .001]. In multivariable models, abnormal dynamic ECG remodelling improved SCD prediction over baseline ECG, demographics, and clinical SCD risk factors in both Oregon [area under the receiver operating characteristic curve 0.770 (95% confidence interval 0.727-0.812) increased to area under the receiver operating characteristic curve 0.869 (95% confidence interval 0.837-0.902)] and California cohorts. Dynamic ECG remodelling improved SCD risk prediction beyond clinical factors combined with the static ECG, with successful validation in a geographically distinct population. These findings introduce a novel concept of SCD dynamic risk and warrant further detailed investigation.

Perfomance of sudden cardiac death prediction strategies before and after Septal Reduction Strategies in patients with Hypertrophic Cardiomyopathy

Abstract Background Actual sudden death (SD) risk stratification strategies for Hypertrophic Cardiomyopathy have not been validated for patients after a septal reduction treatment (SRT). Therefore, it is largely unresolved the quantification of the ventricular arrhythmias (VA) burden after an SRT and how risk stratification should be performed in such patients. Purpose To evaluate the performance of ESC SD Risk stratification model and AHA ACC Risk Factors for SD in the identification of patients with lethal ventricular arrhythmias after SRT. Methods Data from 11 high-volume HCM specialty centers from the international SHaRe Registry were used to describe the natural history of patients with SRT. Patients were followed from SRT until last follow-up or meeting the composite outcome of ventricular arrhythmias (sudden cardiac death (SCD), resuscitated cardiac arrest, or appropriate implantable cardioverter-defibrillator (ICD) therapy). Cox proportional hazards models were used to identify predictors of prognosis and incident development. Calculation of SD score was performed before the SRT and at 1 year from the procedure. Results Of the 10385 patients part of the ShaRe Registry, 1835 (18%, 968 (53%) males) underwent a SRT during a median follow-up of 6.8 (IQR 3.4-9.8). A total of 455 (25%) had Alcohol Septal Ablation (ASA) and 1377 (75%) had myectomy. Patients who underwent myectomy were younger (49±18 vs 56±15 years, p&amp;lt;0.01), more frequent with a sarcomeric mutation (396 (29%) vs 111 (24%), p&amp;lt;0.01). Over 6.8 years after the procedure, 77 (4%) died because of HCM (0.6%/year) and 87 (5%) presented a composite VA outcome (0.7%/year). Development of the composite VA event was associated with younger age at procedure (38±20 vs 54±18 years, p&amp;lt;0.01), the development of a LV EF&amp;lt; 50% (29 (33%) vs 351 (20%), p&amp;lt;0.01), a more severely dilated LA (47±7 vs 43±11 years, p&amp;lt;0.01) and greater LV maximal wall thickness (24±6 vs 21±6 years, p&amp;lt;0.01). Significant predictor of the composite VA outcome was the presence of a LA diameter ³ 45 mm (HR, 2.6 [95% CI, 1.7–3.5]). Patients who presented the VA outocome were classified according to ESC SCD Risk pre and post SRT as: 40 (46%) as high risk, 31 (36%) as intermidiate risk, 16 (18%) as low risk pre intervention and 26 (46%) as high risk, 41 (47%) as intermidiate risk, 20 (18%) as low risk post procedure. AHA ACC SCD risk factors pre and post SRT classified patients as: 56 (64%) as class IIA 25 (29%) as Clas IIB, 6 (7%) as Class III and post SRT 42 (48%) as Class IIA, 31(36%) as Class IIB, 14 (16%) as Class III. Conclusions Current stratification strategies potentially underestimate the risk of SD pre and post SRT. Specifically, ESC SD risk strategies underperformed in the identification of intermidiate high risk patient, whereas AHA ACC were capable of identifying 84% of patients who had a malignant VA.

Association of left atrial strain with long-term cardiovascular mortality in hypertrophic cardiomyopathy

Abstract Background Hypertrophic cardiomyopathy (HCM) is a relatively common genetic cardiac disease affecting 1 in 200 people. Although sudden cardiac death (SCD) is considered the most devastating event in patients with HCM, cardiovascular death (CVD) is the leading cause of death in this population. Little is known about the predictors of cardiovascular mortality. Purpose The aim of this study was to investigate prognostic implication of left atrial (LA) strain on long-term cardiovascular mortality in patients with HCM. Methods Peak longitudinal LA strain was measured on echocardiography at initial evaluation using vendor-independent speckle-tracking software. Among a prospective cohort of 865 HCM patients collected at two large tertiary centers, 697 with adequate echocardiographic images to measure biplane LA strain were included in the analysis. The primary endpoint was CVD during 10 years after initial evaluation. Results The median age was 56.0 years and 74.6% were male. Among the 697 patients, 25 died due to cardiovascular cause for 10 years. Among clinical and echocardiographic variables, older age, female sex, previous myocardial infarction, previous stroke, higher SCD risk score by European Society of Cariology, presence of SCD risk factors by American College of Cardiology, obstructive HCM, larger LA diameter, and lower LA strain were associated with CVD. LA strain had the highest predictive power for CVD occurrence, with a c-statistic of 0.79 (Figure 1). In multivariable Cox analysis, LA strain remains an independent predictor of CVD (hazard ratio [HR] 0.88, 95% confidence interval [CI] 0.82–0.94). Patients with LA strain &amp;lt;19.4% (the lowest quartile), compared with those with LAS ≥19.4%, had a significantly higher risk of CVD (19.5% vs. 2.1%, HR 7.31, 95% CI 3.15–16.95), as well as death by any cause, SCD, and a composite of CVD, heart failure admission, and stroke (Figure 2). Conclusions In patients with HCM, LA strain is an independent predictor of long-term CVD.

Abstract 12857: Electrocardiographic Findings in Women With Ischemic Sudden Cardiac Death and Anatomic Left Ventricular Hypertrophy

Background: Sudden cardiac death (SCD) is a major mode of death worldwide. Previous SCD studies have shown that left ventricular hypertrophy (LVH) is a risk factor for SCD, especially in the presence of myocardial scarring or ischemia. Due to the lower incidence, women are often underrepresented in SCD studies and therefore, most recognized SCD risk factors are biased towards men. Aim: The aim of this study was to investigate sex-specific ECG findings in subjects with ischemic SCD and LVH. Methods: The study population was derived from the FinGesture study, which has collected all SCD cases from Northern Finland 1998-2017. All SCD cases underwent medicolegal autopsy to determine the cause of death. In the present study, we selected SCD cases with coronary artery disease (CAD) and anatomic LVH at autopsy, of whom antemortem electrocardiogram (ECG) was available for 483 subjects (24.4 % women; 75.6 % men). Antemortem recorded ECGs were obtained from medical records and independently analyzed by two investigators. Results: The prevalence of pathological Q-waves (11.9 % vs. 22.1 %, p = 0.016) and fragmented QRS (fQRS) (43.9 % vs. 56.4 %, p = 0.033) was lower in women compared to men. In addition, women were less likely to have prolonged QTc duration (17.8 % in women vs. 32.3 % in men, p = 0.003). The only ECG finding that appeared as more prevalent in women with anatomic LVH was ECG-LVH by Cornell’s criteria (26.4 % vs. 12.4 %, p = 0.002). The prevalence of having abnormal ECG was slightly lower in women (82.2 %) compared to men (89.2 %), p = 0.054. There were no significant differences between sexes when comparing the prevalence of anatomic LVH in subjects with ECG-LVH and ischemic SCD (90.6 % in women vs. 84.9 % in men, p = 0.524). Conclusions: Except for ECG-LVH by Cornell’s criteria, women with ischemic SCD and anatomic LVH were less likely than men to have ECG findings that are often associated with an increased risk of SCD.

Abstract 12785: Abnormal Dynamic Remodeling of the 12-Lead Electrocardiogram is a Risk Marker for Sudden Cardiac Death

Introduction: The ECG has always been evaluated as static risk factor for sudden cardiac death (SCD). The importance of dynamic ECG remodeling has not been investigated. Hypothesis: Abnormal ECG remodeling over time is associated with increased risk of SCD. Methods: We investigated pre-SCD ECG remodeling in SCD cases from 2 ongoing population-based studies of out-of-hospital SCD in Portland, OR (discovery) and Ventura County, CA (validation). Two archived pre-SCD ECGs performed at least 1 year apart were obtained from lifetime health records. Controls were matched on geographical region, age, sex, and duration between the 2 ECG recordings. Dynamic ECG remodeling was measured as the change in a previously validated cumulative 6-variable ECG electrical risk score (ERS) between the 1st and 2nd ECG. Results: A total of 231 SCD cases (66.5±13.6 years, 61% male), and 234 controls (65.8±11.1 years, 61% male) were included in the discovery cohort, and 203 SCD cases (70.3±14.4 years, 54% male), and 203 controls (68.4±11.8 years, 54% male) in the validation cohort. The mean time between the 2 ECG recordings in SCD cases and controls was 6.0±4.0 years vs 6.2±4.5 years (discovery) and 3.7±2.6 years vs. 3.7±1.6 years (validation), respectively. In both cohorts, SCD cases compared to controls had greater dynamic ECG remodeling over time: Discovery cohort ERS change +1.06 (95% CI +0.89 to +1.24) vs. -0.05 (-0.21 to +0.11; p&lt;0.001) and validation cohort ERS change +0.87 (+0.7 to +1.04) vs. -0.11 (-0.27 to 0.05; p&lt;0.001). In a multivariate model including clinical SCD risk factors, a 1-unit increase in the ERS was an independent risk marker for SCD: Discovery cohort OR 1.89 (95% CI 1.58-2.26; p&lt;0.001), validation cohort OR 2.17 (95% CI 1.63-2.91; p&lt;0.001). Conclusions: SCD cases were observed to have abnormal dynamic ECG remodeling prior to the SCD event, not observed in matched controls. These findings warrant further investigation of dynamic ECG remodeling as a novel risk marker for SCD.

Reversed Septal Curvature Is Associated With Nonsustained Ventricular Tachycardia in Hypertrophic Cardiomyopathy

Sudden cardiac death (SCD) is associated with nonsustained ventricular tachycardia (NSVT) in patients with hypertrophic cardiomyopathy (HCM). Recently, differences regarding septal morphology have been reported, with an increased probability of sudden death in HCM patients who had reverse septal curvature (RSC). The aim of this study was to examine the relationship between RSC and NSVT in HCM. A total of 138 patients with HCM were enrolled. Of 138 patients, 47 (34.1%) were diagnosed with RSC and 42 patients (30.4%) had NSVT. Compared with the non-RSC group, those with RSC were much younger and had an increased incidence of NSVT, thicker septal thickness, larger mass, and a higher proportion of HCM or SCD family history. Furthermore, patients with RSC had a higher risk of SCD according to the European Society of Cardiology calculator (2.5 (1.6, 4.6) vs. 1.6(1.1, 2.3)(%/5 year), p <0.001). Multivariate analysis showed that RSC was a strong and independent risk factor for NSVT (odds ratio = 2.756, 95% confidence interval: 1.164-6.525, p = 0.021). In conclusion, the presence of RSC in HCM patients is independently associated with NSVT. Further studies are needed to evaluate the role of RSC as a risk factor for SCD in this population.

Sudden cardiac death in childhood RASopathy-associated hypertrophic cardiomyopathy: Validation of the HCM risk-kids model and predictors of events

BackgroundRASopathies account for nearly 20% of cases of childhood hypertrophic cardiomyopathy (HCM). Sudden cardiac death (SCD) occurs in patients with RASopathy-associated HCM, but the risk factors for SCD have not been systematically evaluated. AimTo validate the HCM Risk-Kids SCD risk prediction model in children with RASopathy-associated HCM and investigate potential specific SCD predictors in this population. MethodsValidation of HCM Risk-Kids was performed in a retrospective cohort of 169 patients with a RASopathy-associated HCM from 15 international paediatric cardiology centres. Multiple imputation by chained equations was used for missing values related to the HCM Risk-Kids parameters. ResultsEleven patients (6.5%) experienced a SCD or equivalent event at a median age of 12.5 months (IQR 7.7–28.64). The calculated SCD/equivalent event incidence was 0.78 (95% CI 0.43–1.41) per 100 patient years. Six patients (54.54%) with an event were in the low-risk category according to the HCM Risk-Kids model. Harrell's C index was 0.60, with a sensitivity of 9.09%, specificity of 63.92%, positive predictive value of 1.72%, and negative predictive value of 91%; with a poor distinction between the different risk groups. Unexplained syncope (HR 42.17, 95% CI 10.49–169.56, p < 0.001) and non-sustained ventricular tachycardia (HR 5.48, 95% CI 1.58–19.03, p < 0.007) were predictors of SCD on univariate analysis. ConclusionUnexplained syncope and the presence of NSVT emerge as predictors for SCD in children with RASopathy-associated HCM. The HCM Risk-Kids model may not be appropriate to use in this population, but larger multicentre collaborative studies are required to investigate this further.

Sudden Cardiac Death: A Systematic Review.

Sudden cardiac death (SCD) is a condition that accounts for a high percentage of cardiovascular fatalities, with ventricular tachyarrhythmias being the most common cause. There are signs and symptoms of SCD that occur spontaneously without any warning and are deadly. Despite preventative efforts focusing on the use of subcutaneous implanted cardioverter defibrillators (S-ICD) in the highest-risk population categories, a high number of SCDs occur in the normal population and in people who do not have a documented cardiac condition. Therefore, primary prevention for SCD should be a more viable strategy for the general population, considering measures in the form of preventive medicine such as knowing more about any genetic predisposition, family history of any fatal arrhythmia, continuous surveillance after any syncope with unknown causes, etc. However, little data about SCD risk factors are known in comparison with other well-known diseases like ischemic heart disease and stroke.In search of medical databases for relevant medical literature, we looked at PubMed/Medline, the Cochrane Library, and Google Scholar. Thirteen publications were discovered after the papers were located, assessed, and qualifying criteria were applied. The finished articles were done to give an overview of SCD. Some others have shown that the major predisposition for SCD is related to the male gender, which increases the incidence if they have a family history of SCD. We described the importance of obstructive sleep apnea (OSA) as a comorbid condition. Patients with S-ICD and young athletes with a history of ventricular arrhythmia showed us that the predisposition for SCD can be higher than in the normal population. Based on the above, we concluded that more study is required to establish the most important approach for eachof the risk factors mentioned in this systematic review in order to apply them in daily practice and have more knowledge about how to apply preventive and therapeutic medicine to the population at risk and the ones that already develop the disease.

Accurate Prediction of Sudden Cardiac Death Based on Heart Rate Variability Analysis Using Convolutional Neural Network.

Sudden cardiac death (SCD) is a significant global health issue that affects individuals with and without a history of heart disease. Early identification of SCD risk factors is crucial in reducing mortality rates. This study aims to utilize electrocardiogram (ECG) tools, specifically focusing on heart rate variability (HRV), to detect early SCD risk factors. In this study, we expand the comparison group dataset to include five groups: Normal Sinus Rhythm (NSR), coronary artery disease (CAD), Congestive Heart Failure (CHF), Ventricular Tachycardia (VT), and SCD. ECG signals were recorded for 30 min and segmented into 5 min intervals, following the recommended HRV feature analysis guidelines. We introduce an innovative approach to HRV signal analysis by utilizing Convolutional Neural Networks (CNN). The CNN model was optimized by tuning hyperparameters such as the number of layers, learning rate, and batch size, significantly impacting the prediction accuracy. The findings demonstrate that the HRV approach, in conjunction with linear features and the DL method, achieved a higher accuracy rate, averaging 99.30%, reaching 97% sensitivity, 99.60% specificity, and 97.87% precision. Future research should focus on further exploring and refining DL methods in the context of HRV analysis to improve SCD prediction.

Increased Epicardial Adipose Tissue and Heart Characteristics Are Correlated with BMI and Predict Silent Myocardial Infarction in Sudden Cardiac Death Subjects: An Autopsy Study.

Sudden cardiac death (SCD) is a significant global public health issue and the leading cause of death worldwide. Its etiopathogenesis is complex and multilayered, involving dynamic factors interacting with a preexistent cardiovascular pathology, frequently unknown, and resulting in cardiac rhythm disorders and cardiac arrest; Methods: This study conducted a retrospective descriptive analysis over a one-year period, identifying 321 autopsy cases of sudden deaths from the Institute of Legal Medicine in Mures County, Romania, in 2019. From the 321 sudden death cases, 189 autopsy reports were selected for analysis based on inclusion and exclusion; Results: The autopsies had a mean age of 61.16 years and included 140 males and 49 females. No significant differences were found between the silent myocardial infarction (SMI) and no-SMI groups regarding demographic data. The SMI group exhibited higher thickness of LV (left ventricle), IV (interventricular septum), EAT LCx (epicardial adipose tissue at left circumflex artery), EAT LAD (epicardial adipose tissue at left anterior descending artery), heart weight, and BMI (body mass index). The left coronary artery showed a higher incidence of type V plaques, while the right coronary artery showed higher incidences of type V and type VI plaque. The SMI group also exhibited a higher incidence of moderate and severe valvular atherosclerosis, severe left ventricle dilatation, and a lower incidence of mild left ventricle dilatation. In addition, the SMI group showed a higher presence of contraction band necrosis on histological examination. Multivariate analysis revealed that type V and type VI plaques for the right and left coronary arteries, moderate and severe valvular atherosclerosis, severe left ventricle dilatation, heart weight, EAT LCx, EAT LAD, LV thickness, IV thickness, BMI, and the presence of contraction band necrosis are all independent predictors of SMI; Conclusions: The findings suggest that SCD is a complex condition, and its etiopathogenesis involves dynamic factors interacting with pre-existing cardiovascular pathology. The risk factors of SCD are similar to those of ischemic heart disease. The findings of this study could guide clinicians in identifying patients at risk of SCD and implementing preventive measures.

#3173 INCIDENCE AND RISK FACTORS OF SUDDEN CARDIAC DEATH IN END STAGE RENAL DISEASE PATIENTS UNDERGOING HAEMODIALYSIS: A RETROSPECTIVE STUDY

Abstract Background &amp; aims: End Stage Renal Disease (ESRD) patients undergoing haemodialysis are prone to suffer from Sudden Cardiac Death (SCD). The present study was sought to evaluate the incidence and risk factors of SCD in ESRD patients on haemodialysis in Pakistani population. Methods The study recruited 202 eligible ESRD patients undergoing haemodialysis. Baseline characteristics of the study participants with and without Sudden Cardiac Arrest (SCA) were recorded using self-reported questionnaires. SCA and SCD events were identified by reviewing medical records and death certificates. Results Out of 202 patients, 37 (18.3%) suffered from the episode of SCA, 18 (48.6%) of which succumbed to death. ESRD patients who endured SCA were statistically older in comparison with their non-SCA counterparts (58.2 ± 11.4 vs. 52.3 ± 9.3 years, P&amp;lt;0.001). The HTN (67.6% versus 64.8%, P = 0.001), DM (62.2% versus 59.4%, P = 0.004), CAD (45.9% versus 41.8%, P = 0.001) and Congestive Heart Failure (CHF) (35.1% versus 34.5%, P = 0.002) were significantly prevalent in ESRD cohort with SCA in contrast to non-SCA. We also found LVH (62.2% versus 48.5%, P&amp;lt;0.001), ventricular tachycardia (51.4% versus 30.9%, P&amp;lt;0.001) and ventricular fibrillation/flutter (56.8% versus 25.5%, P&amp;lt;0.001) to be statistically higher in ESRD patients on haemodialysis with SCA event. Through multivariate logistic regression analysis, we evidenced hypokalemia (OR = 1.247, CI 1.214 – 1.278, P&amp;lt;0.001); CAD (OR 1.886, CI 1.469 – 2.342, P&amp;lt;0.001); LVH (OR 1.861, CI 1.392 – 1.953, P&amp;lt;0.001); ventricular tachycardia (OR = 1.253, CI 1.012 – 1.386, P&amp;lt;0.001); and ventricular fibrillation/flutter (OR = 0.547, CI 0.518 – 0.773, P&amp;lt;0.001) to be significantly and independently associated with SCD in ESRD patients on haemodialysis. Conclusion The prevalence of SCD among ESRD patients on haemodialysis with SCA episode is very high. CAD and ventricular tachyarrhythmias were statistically significant among ESRD patients on haemodialysis with SCA in comparison with non-SCA and were independently associated with the prevalence of in-patient SCD among ESRD patients with SCA on haemodialysis.

Deep learning-based measurement of echocardiographic data and its application in the diagnosis of sudden cardiac death

ABSTRACT This study aimed to evaluate the potential of deep learning applied to the measurement of echocardiographic data in patients with sudden cardiac death (SCD). 320 SCD patients who met the inclusion and exclusion criteria underwent clinical evaluation, including age, sex, BMI, hypertension, diabetes, cardiac function classification, and echocardiography. The diagnostic value of deep learning model was observed by dividing the patients into two groups: training group (n=160) and verification group (n=160), as well as two groups of healthy volunteers (n=200 for each group) during the same period. Logistic regression analysis showed that MLVWT, LVEDD, LVEF, LVOT-PG, LAD, E/e' were all risk factors for SCD. Subsequently, a deep learning-based model was trained using the collected images of the training group. The optimal model was selected based on the identification accuracy of the validation group and showed an accuracy of 91.8%, sensitivity of 80.00%, and specificity of 91.90% in the training group. The AUC value of the ROC curve of the model was 0.877 for the training group and 0.995 for the validation groups. This approach demonstrates high diagnostic value and accuracy in predicting SCD, which is clinically important for the early detection and diagnosis of SCD.