Predictor Of Sudden Cardiac Death Research Articles

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.

Arrhythmic risk stratification in non-ischemic cardiomyopathy using cardiovascular magnetic resonance

Abstract Background Myocardial fibrosis (MF) is an essential component of the arrhythmic substrate for ventricular arrhythmias (VAs). Aims To determine whether total myocardial fibrosis (TF) and gray zone fibrosis (GZF), assessed using cardiovascular magnetic resonance, are better than LVEF in predicting ventricular arrhythmias in patients with non-ischemic cardiomyopathy (NICM). Methods and results 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 (SCD) or VAs (ventricular fibrillation or sustained ventricular tachycardia). The primary endpoint was met by 52/866 (6.0%) patients in the derivation cohort (follow-up of 7.5 years [interquartile range, IQR] 5.2-9.3). In competing risk analyses, MF on visual assessment (MFVA) predicted the primary endpoint (hazard ratio [HR] 5.83, 95% confidence intervals [CI] 3.15-10.8). Quantified MF measures permitted categorization into 3 risk groups: a TF >0 ≤ 10 g was associated with an intermediate risk (HR: 4.03 [95% CI 1.99-8.16]) and a TF > 10g with the highest risk (HR: 9.17 [95% CI 4.64-18.1]) compared to no MFVA (lowest risk) (Figure). Similar trends were observed in the validation cohort. Categorization into 3 risk groups was achievable using TF or GZF in combination or in isolation. In contrast, LVEF<35% was a poor predictor of the primary endpoint (validation cohort HR:1.99, 95% CI 0.99-0.41). Conclusions MFVA is a strong predictor of SCD and VAs in NICM. TF and GZF mass added incremental value to MFVA. In contrast, LVEF was not useful in arrhythmic risk stratification.

Development and validation of a machine learning-based prediction model for sudden cardiac death in the general population: insights from the community cardiovascular cohort

Abstract Background/Introduction Accurately predicting and managing the risk of sudden cardiac death (SCD) in the general population is a formidable challenge. Purpose This study aimed to develop and validate a machine learning (ML)-based prediction model for SCD using data from the Community Cardiovascular Cohort (CCCC) in Taiwan. Methods A community-based cohort study was used for model construction . Four ML algorithms, including extreme gradient boosting (XGBoost), random forests (RF), logistic regression, and deep neural network (DNN), underwent meticulous evaluation. Performance assessment encompassed receiver operating characteristic (ROC) curves, area under the curves (AUC), and accuracy metrics. Significant risk factors were identified through feature importance analysis. Results We employed a random partitioning strategy, allocating 1744 participants (55%) to the training dataset, 952 participants (30%) to the test dataset, and 476 participants (15%) to the validation dataset. In the data training stage, the XGBoost algorithm demonstrated outstanding prediction performance for SCD (AUC: 1.000); In the validation stage, the XGBoost algorithm demonstrated good prediction performance for SCD prediction (AUC: 0.791, 95%CI: 0.617-0.964; Accuracy: 0.971). Using XGBoost-generated predicted probabilities (P(XGB)), we identified individuals with P(XGB) ≥ 0.5 (Group 1) who displayed significantly higher SCD risk (HR 32.0; 95% CI: 9.29-109.9) compared to those with P(XGB) < 0.5 (Group 0). Conclusions Our study demonstrates the effectiveness of ML algorithms, particularly XGBoost, in predicting event of SCD in the general population. The identification of these pivotal risk factors holds profound implications, empowering the identification of high-risk individuals and facilitating the implementation of precisely tailored preventive strategies.Figure 1:KM sruvival curveFigure 2:Feature importance analysis

The Prognostic Value of Left Ventricular Entropy From T1 Mapping in Patients With Hypertrophic Cardiomyopathy

BackgroundThe prognostic value of left ventricular (LV) entropy in hypertrophic cardiomyopathy (HCM) is unclear. ObjectivesThis study aimed to assess the prognostic value of LV entropy from T1 mapping in HCM. MethodsA total of 748 participants with HCM, who underwent cardiovascular magnetic resonance (CMR), were consecutively enrolled. LV entropy was quantified by native T1 mapping. A competing risk analysis and a Cox proportional hazards regression analysis were performed to identify potential associations of LV entropy with sudden cardiac death (SCD) and cardiovascular death (CVD), respectively. ResultsA total of 40 patients with HCM experienced SCD, and 65 experienced CVD during a median follow-up of 43 months. Participants with increased LV entropy (≥4.06) were more likely to experience SCD and CVD (all P < 0.05) in the entire study cohort or the subgroup with low late gadolinium enhancement (LGE) extent (<15%). After adjustment for the European Society of Cardiology predictors and the presence of high LGE extent (≥15%), LV mean entropy was an independent predictor for SCD (HR: 1.03; all P < 0.05) by the multivariable competing risk analysis and CVD (HR: 1.06; 95% CI: 1.03-1.09; P < 0.001) by multivariable Cox regression analysis. ConclusionsLV mean entropy derived from native T1 mapping, reflecting myocardial tissue heterogeneity, was an independent predictor of SCD and CVD in participants with HCM. (Cardiac Magnetic Resonance Imaging Clinical Application Registration Study; ChiCTR1900024094)

What Do We Know So Far About Ventricular Arrhythmias and Sudden Cardiac Death Prediction in the Mitral Valve Prolapse Population? Could Biomarkers Help Us Predict Their Occurrence?

To summarize currently available data on the topic of mitral valve prolapse (MVP) and its correlation to the occurrence of atrial and ventricular arrhythmias. To assess the prognostic value of several diagnostic methods such as transthoracic echocardiography, transesophageal echocardiography, cardiac magnetic resonance, cardiac computed tomography, electrocardiography, and electrophysiology concerning arrhythmic episodes. To explore intra and extracellular biochemistry of the cardiovascular system and its biomarkers as diagnostic tools to predict rhythm disturbances in the MVP population. MVP is a common and mainly benign valvular disorder. It affects 2-3% of the general population. MVP is a heterogeneous and highly variable phenomenon with three structural phenotypes: myxomatous degeneration, fibroelastic deficiency, and forme fruste. Exercise intolerance, supraventricular tachycardia, and chest discomfort are the symptoms that are often paired with psychosomatic components. Though MVP is thought to be benign, the association between isolated MVP without mitral regurgitation (MR) or left ventricle dysfunction, with ventricular arrhythmia (VA) and sudden cardiac death (SCD) has been observed. The incidence of SCD in the MVP population is around 0.6% per year, which is 6 times higher than the occurrence of SCD in the general population. Often asymptomatic MVP population poses a challenge to screen for VA and prevent SCD. Therefore, it is crucial to carefully assess the risk of VA and SCD in patients with MVP with the use of various tools such as diagnostic imaging and biochemical and genetic screening.

TBX5 genetic variants and SCD-CAD susceptibility: insights from Chinese Han cohorts.

The prevention and prediction of sudden cardiac death (SCD) present persistent challenges, prompting exploration into common genetic variations for potential insights. T-box 5 (TBX5), a critical cardiac transcription factor, plays a pivotal role in cardiovascular development and function. This study systematically examined variants within the 500-bp region downstream of the TBX5 gene, focusing on their potential impact on susceptibility to SCD associated with coronary artery disease (SCD-CAD) in four different Chinese Han populations. In a comprehensive case-control analysis, we explored the association between rs11278315 and SCD-CAD susceptibility using a cohort of 553 controls and 201 SCD-CAD cases. Dual luciferase reporter assays and genotype-phenotype correlation studies using human cardiac tissue samples as well as integrated in silicon analysis were applied to explore the underlining mechanism. Binary logistic regression results underscored a significantly reduced risk of SCD-CAD in individuals harboring the deletion allele (odds ratio = 0.70, 95% CI [0.55-0.88], p = 0.0019). Consistent with the lower transcriptional activity of the deletion allele observed in dual luciferase reporter assays, genotype-phenotype correlation studies on human cardiac tissue samples affirmed lower expression levels associated with the deletion allele at both mRNA and protein levels. Furthermore, our investigation revealed intriguing insights into the role of rs11278315 in TBX5 alternative splicing, which may contribute to alterations in its ultimate functional effects, as suggested by sQTL analysis. Gene ontology analysis and functional annotation further underscored the potential involvement of TBX5 in alternative splicing and cardiac-related transcriptional regulation. In summary, our current dataset points to a plausible correlation between rs11278315 and susceptibility to SCD-CAD, emphasizing the potential of rs11278315 as a genetic risk marker for aiding in molecular diagnosis and risk stratification of SCD-CAD.

Electrical Instability of the Myocardium in Children and Adolescents

Currently, there is no doubt that the problem of electrical instability of the myocardium in pediatric cardiology is relevant. The determination of various indicators of electrical instability of the myocardium, which are predictors of life-threatening rhythm disorders and sudden cardiac death, presents an underdeveloped task not only for functional diagnostics specialists, but also for pediatricians, neonatologists, pediatric cardiologists and doctors of other specialties. Non-invasive research methods such as electrocardiography (ECG), Holter ECG monitoring (HM ECG), available in almost all pediatric treatment and prevention institutions, are quite informative in terms of detecting electrophysiological heterogeneity of the myocardium as a predictor of sudden cardiac death, which is especially important in children at risk, as well as young athletes. Thus, the determination of indicators of electrical instability of the myocardium is of great interest, it is a promising direction in modern clinical practice, allowing to predict the risk of developing fatal arrhythmias in children and adolescents.

Natural history and outcomes in paediatric RASopathy-associated hypertrophic cardiomyopathy.

This study aimed to describe the natural history and predictors of all-cause mortality and sudden cardiac death (SCD)/equivalent events in children with a RASopathy syndrome and hypertrophic cardiomyopathy (HCM). This is a retrospective cohort study from 14 paediatric cardiology centres in the United Kingdom and Ireland. We included children <18years with HCM and a clinical and/or genetic diagnosis of a RASopathy syndrome [Noonan syndrome (NS), NS with multiple lentigines (NSML), Costello syndrome (CS), cardiofaciocutaneous syndrome (CFCS), and NS with loose anagen hair (NS-LAH)]. One hundred forty-nine patients were recruited [111 (74.5%) NS, 12 (8.05%) NSML, 6 (4.03%) CS, 6 (4.03%) CFCS, 11 (7.4%) Noonan-like syndrome, and 3 (2%) NS-LAH]. NSML patients had higher left ventricular outflow tract (LVOT) gradient values [60 (36-80) mmHg, P=0.004]. Over a median follow-up of 197.5 [inter-quartile range (IQR) 93.58-370] months, 23 patients (15.43%) died at a median age of 24.1 (IQR 5.6-175.9) months. Survival was 96.45% [95% confidence interval (CI) 91.69-98.51], 90.42% (95% CI 84.04-94.33), and 84.12% (95% CI 75.42-89.94) at 1, 5, and 10years, respectively, but this varied by RASopathy syndrome. RASopathy syndrome, symptoms at baseline, congestive cardiac failure (CCF), non-sustained ventricular tachycardia (NSVT), and maximal left ventricular wall thickness were identified as predictors of all-cause mortality on univariate analysis, and CCF, NSVT, and LVOT gradient were predictors for SCD or equivalent event. These findings highlight a distinct category of patients with Noonan-like syndrome with a milder HCM phenotype but significantly worse survival and identify potential predictors of adverse outcome in patients with RASopathy-related HCM.

ECG changes and their prognostic value for the development of sudden cardiac death in HCM patients

Background. Hypertrophic cardiomyopathy (HCM) is a primary myocardial disease characterized by an increase in the left ventricular (LV) wall thickness, which is not explained only by abnormal loading conditions. The development of sudden cardiac death (SCD) is one of the most dangerous complications of HCM. The aim of our study was to evaluate the prognostic value of electrocardiography (ECG) changes for the development of SCD in the Ukrainian population of patients with HCM. Materials and methods. We evaluated 350 patients with HCM who were examined in the City Clinical Hospital 8 (Kharkiv, Ukraine) from 2006 to 2021. The diagnosis of HCM was made in accordance with the current guidelines of the European Society of Cardiology. Clinical and instrumental data of patients with HCM were analyzed retrospectively, including general clinical data, 12-lead ECG, echocardiography, Holter monitoring, calculation of the 5-year risk of SCD according to the HCM Risk-SCD tool. The endpoint of the study was SCD and its surrogates, including adequate performance of the implantable cardioverter-defibrillator and the state after a successful resuscitation. Results. Follow-up was 5.0 (1.5–9.5) years. During this time, 16 patients (4.6 %) reached the endpoint, which was 0.9 %/year. According to the HCM Risk-SCD, 5 (31.3 %) patients in this group were at a high (≥ 6 %) and 3 (18.8 %) were at an intermediate risk of SCD (≥ 4 and &lt; 6 %). A multivariable Cox regression analysis has shown that independent predictors of SCD are syncope (hazard ratio (HR) 3.81, 95% confidence interval (CI) 1.11–13.12, p = 0.034), systolic blood pressure (HR 0.97, 95% CI 0.94–0.99, p = 0.026), ECG with “infarction-like” ST elevation (HR 6.81, 95% CI 2.09–22.16, p = 0.001) and PQ interval value (HR 1.03, 95% CI 1.01–1.05, p = 0.002), Harrell’s C-index (HR 0.84, 95% CI 0.73–0.95, p &lt; 0.0001). Conclusions. The proposed HCM Risk-SCD tool was not effective enough in predicting SCD in our study. In order to improve the risk stratification, ECG changes (“infarction-like” ST elevation and PQ interval prolongation) and systolic blood pressure lowering can be used, which were found to be independent predictors of SCD risk.

Kiosk 4R-FA-02 - A Simplified Scoring System for the Prediction of Sudden Cardiac Death in Pediatric Patients with Hypertrophic Cardiomyopathy

Kiosk 4R-FA-02 - A Simplified Scoring System for the Prediction of Sudden Cardiac Death in Pediatric Patients with Hypertrophic Cardiomyopathy

ЭЛЕКТРОКАРДИОГРАФИЧЕСКИЕ СИНДРОМЫ

Introduction. Sudden cardiac death (SCD) is a global health concern, often associated with specific clinical and electrocardiographic syndromes. While electrocardiography (ECG) is a crucial diagnostic tool in cardiology, it does not always provide a direct diagnosis or prediction of SCD. However, there are indirect criteria and syndromes that aid in diagnosing complex clinical cases in cardiology. Aim. This study aims to review various electrocardiographic syndromes known to predict sudden cardiac death, drawing from both domestic and foreign literature. Results. Wellens syndrome (WS) is an ECG pattern indicating a high risk of anterior wall myocardial infarction caused by anterior interventricular artery occlusion or critical stenosis. The de Winter pattern is an ECG sign associated with proximal LAD occlusion and the absence of ST segment elevation. Aslanger pattern is linked to coronary artery occlusion in patients with multivessel coronary artery disease, reflecting a combination of inferior MI and diffuse ischemia. Chaterrier's phenomenon (cardiac memory phenomenon) manifests as abnormal T wave inversion during normal sinus rhythm after myocardial electrical stimulation cessation.The Sgarbossa criteria aid in diagnosing acute myocardial infarction in patients with previous left bundle branch block. ECG signs of arrhythmogenic dysplasia of the right ventricle include negative T-waves in leads V1-V3 and an "epsilon" wave in lead V1, reflecting delayed depolarization of the right ventricle. Conclusion. Early recognition of these ECG patterns can aid in secondary prevention of AMI, fatal rhythm disturbances, and SCD, while also preventing overdiagnosis of myocardial ischemia in patients with implanted devices.

Electrocardiogram (ECG) risk score model in heart failure with reduced ejection fraction (HFrEF): Predictor of sudden cardiac death

Electrocardiogram (ECG) risk score model in heart failure with reduced ejection fraction (HFrEF): Predictor of sudden cardiac death

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.

Sudden cardiac death in childhood RASopathy-associated hypertrophic cardiomyopathy: validation of HCM Risk-Kids model and predictors of events

Abstract RASopathies represent an important proportion of hypertrophic cardiomyopathy (HCM) cases presenting in childhood. Despite this, there are no published risk factors for sudden cardiac death (SCD) in this cohort of patients. Our primary aim was to validate the HCM Risk-Kids model in children with RASopathy-associated HCM and to investigate additional predictors of SCD in a cohort of 169 patients from 15 international paediatric cardiology centres (UK, Ireland and Germany). Eleven (6.5%) patients experienced a SCD equivalent event [5 (45.5%) an aborted cardiac arrest; 3 (27.3%) SCD; 2 (18.2%) sustained ventricular tachycardia (VT); and 1 (9.1%) appropriate implantable cardioverter-defibrillator (ICD) shock] 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 a SCD equivalent event were in the low-risk category according to the HCM Risk-Kids model. Harrell’s C index was 0.5959 (95% CI 0.26-1.22) with a sensitivity of 9.09%, specificity of 63.92%, positive predictive value of 1.72%, and negative predictive value of 90.99%; there was poor distinction between the different risk groups. Unexplained syncope (HR 102.63 (95% CI 14.94 – 704.99), p&amp;lt;0.001) and non-sustained VT [NSVT (HR 5.67 (95% CI 1.30 – 24.70), p=0.021)] were independent predictors of SCD. The HCM Risk-Kids model should not be used for patients with RASopathy-associated HCM but NSVT and unexplained syncope appear to be predictors of SCD in this population. Larger multicentre collaborative studies are required to further investigate predictors of SCD in this group of patients.

The prognostic value of left ventricular entropy derived from native T1 mapping in patients with hypertrophic cardiomyopathy

Abstract Background The prognostic value of Left ventricular (LV) entropy in hypertrophic cardiomyopathy (HCM) is unclear. Objectives This study aimed to assess the prognostic value of LV entropy from T1 mapping in HCM. Methods In this prospective study, 748 participants with HCM, who underwent cardiovascular MRI, were consecutively enrolled. LV entropy was quantified by native T1 mapping to estimate tissue heterogeneity. A multivariable Cox proportional hazards regression was performed to identify potential associations of LV entropy with sudden cardiac death (SCD) and cardiovascular death (CVD). Results Among the 748 participants (mean age, 51 ± 14.2 years; 454 men), 40 (5.3%) experienced SCD, and 65 (8.7%) experienced CVD during a median follow-up of 43 months. Participants with increased LV entropy (≥ 5.86) were more likely to suffer from SCD (P &amp;lt; 0.001 and P = 0.03) and CVD (P &amp;lt; 0.001 and P = 0.02) in the entire cohort and the subgroup with low late gadolinium enhancement (LGE) extent (&amp;lt;10%), respectively. In multivariable Cox analysis, following adjustment for the European Society of Cardiology predictors and the presence or absence of high LGE extent (≥10%), LV mean entropy was an independent predictor of SCD (hazard ratio [HR] 1.04, 95% CI 1.0 - 1.08, P = 0.03) and CVD (HR 1.06, 95% CI 1.04 - 1.09, P &amp;lt; 0.001). An SCD and CVD predictive model that encompassed a combination of LV entropy and LGE was developed, and an internal validation showed that the derived models retained good predictive ability with a C-index of 0.71 to 0.74 and 0.81 ± 0.03 for SCD and CVD, respectively. Conclusions LV mean entropy derived from native T1 mapping, reflecting myocardial tissue heterogeneity, was an independent predictor of SCD and CVD in participants with HCM and could help improve risk stratification.Figure 1Kaplan-Meier Analyses.Figure 2Incremental Value of LV entropy

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.

Abstract 347: Artificial Intelligence for Targeted and Personalized Prediction of Sudden Cardiac Death in the General Population: A Machine Learning Study Based on Electronic Health Records

Background: Identification of subjects from the general population with an increased risk of Sudden Cardiac Death (SCD) remains highly challenging, particularly at an individual level. Methods: Every case of SCD + 18 y.o. that occurred since 2011 in Paris and its inner suburbs was prospectively included in the Paris Sudden Death Expertise Center (SDEC) registry (6.7M inhabitants). SCD cases were matched by age, sex, and residence area with a control group (70000) sampled from the general population. All data from the French National Health Insurance database (SNDS) were collected: prescribed drugs, examinations and diagnoses that occurred up to 10 y. before the event, including cardiovascular and non-cardiovascular variables (10000). We provide a detailed explanation of the prediction at the individual level. For each subject, we computed the Shapley scores from the supervised learning model (CatBoost) to evaluate the contribution of variables to its predicted risk. The model used was derived from 12338 SCD cases and matched controls cohort (2011-15) and validated on 11620 cases cohort (2016-20). Results: A total of 23958 equations have been built with personalized variables and coefficients, achieving an AUC of 0.80 in the derivation cohort (with a PPV=77%, sensitivity=68%). One example is shown below, with an individual predicted risk of SCD at 3 months (89.3%), and the most important factors that increase (red) or decrease (blue) the risk of SCD. Conclusions: For the first time, we provide a personalized prediction model of SCD, which explains the predicted risk at the individual level. These findings offer a new step toward personalized prevention and global public health interventions

Abstract 15106: Echocardiography versus Cardiac Magnetic Resonance-Quantification of Right Ventricular Function to Stratify the Risk of Appropriate Defibrillator Therapy

Background: Right ventricular dysfunction is recently referred as an independent predictor of sudden cardiac death. The purpose of this study was to evaluate the efficiency of risk stratification methods for appropriate implantable cardiac defibrillator (ICD) therapy using two different modalities to quantify the right ventricular function. Methods: Consecutive patients undergoing ICD implantations who completed both preprocedural echocardiography and cardiac magnetic resonance (CMR) were retrospectively enrolled. Any channelopathy or arrhythmogenic right ventricular disease were excluded. The right ventricular fractional area change (RVFAC) and estimated pulmonary artery pressure (EPAP) were calculated from echocardiography. The contraction-pressure index (CPI) was defined as the quotient of the RVFAC divided by EPAP. The right ventricular ejection fraction (RVEF) was automatically provided by CMR. Both were evaluated to predict the initial appropriate ICD therapy. Results: In total, 111 patients (59.5±14.9 years, 79 males) including 20 with ischemic cardiomyopathy were retrospectively enrolled. Fifty-six patients received an ICD as secondary prophylaxis. The mean RVFAC, CPI, and RVEF were 36.7±8.9%, 1.4±0.7%, and 39.9±13.8%, respectively. Regarding appropriate ICD therapy events, the best cut-off value of the RVFAC was 34.8 (specificity 0.63, sensitivity 0.65, ROC-AUC 0.64), CPI 1.59 (specificity 0.42, sensitivity 0.94, ROC-AUC 0.61) and RVEF 43.0 (specificity 0.48, sensitivity 0.87, ROC-AUC 0.64). The hazard ratio of a low RVFAC was 3.13 (95%CI: 1.32-7.44, P&lt;0.01, concordance=0.62), that of low CPI was 9.60 (95%CI: 1.27-72.4, P=0.03, c=0.65), and that of reduced RVEF was 5.55 (95%CI: 1.64-18.7, P&lt;0.01, c=0.67). Conclusion: CPI and RVEF were similarly associated with an increased appropriate ICD therapy. The CPI seemed to provide an equivalent stratification for the risk of appropriate ICD therapy as compared to a CMR indicator.

Appropriate time for ejection fraction reassessment after revascularization in patients with left ventricular dysfunction for risk stratification of sudden cardiac death.

Appropriate time for ejection fraction (EF) reassessment after revascularization in patients with left ventricular dysfunction has not been investigated comprehensively, although 3 months after revascularization is recommended to stratify the risk of sudden cardiac death (SCD). EF reassessed within different timeframe after revascularization may have incosistent contribution for risk stratification of SCD. Patients who had EF ≤ 40% before revascularization and had EF reassessment at least once during follow-up were included. The role of early (<3 months) versus late (3-12 months) EF measurements in prediction of all-cause mortality and SCD were compared. A total of 1589 patients were identified. EF reassessed <3 months was lower than EF reassessed within 3-12 months (42.1 ± 9.7% vs. 45.8 ± 10.8%; p < .01). Among 1069 patients who had EF reassessed <3 months, EF ≤ 35% was associated with a higher risk of all-cause mortality (hazard ratio [HR], 1.67; 95% confidence interval [CI], 1.22-2.29; p < .01), but had no association with the risk of SCD (HR, 1.44; 95% CI, 0.84-2.48; p = .18). By contrast, among 595 patients who had EF reassessed within 3-12 months, EF ≤ 35% was associated with higher risks of both all-cause death (HR, 1.81; 95% CI, 1.06-3.10; p = .03) and SCD (HR, 2.71; 95% CI, 1.31-5.61; p < .01). The relative contribution of SCD to all-cause death was higher in patients with EF ≤ 35% than patients with EF > 35% when EF was reassessed within 3-12 months (p = .04). However, when EF was reassessed <3 months, the mode of death was similar in patients with EF ≤ 35% versus >35% (p = .85). 3 to 12 months after revascularization may be appropriate for cardiac function reassessment and SCD risk stratification.

Abstract 17497: Natural History of the Left Ventricular Ejection Fraction in Heart Failure and Sudden Cardiac Death

Background: A clinical diagnosis of heart failure (HF) is associated with increased risk of sudden cardiac death (SCD), but only HF with severely reduced LV ejection fraction (HFrEF, EF ≤35%) is utilized for risk stratification. Guideline-directed medical therapy and heart disease processes may improve or reduce the LVEF. Hypothesis: There is significant variation of LVEF over time among HF patients with SCD. Methods: From a large, prospective population-based study of SCD in the Northwest US (catchment population 1 million, 2002-2018), we identified all consecutive patients with a diagnosis of HF and prior assessment of LVEF. The sub-group of patients with at least 2 prior LVEF evaluations (earliest and latest in relation to SCD) was determined. Results: A total of 1622 individuals suffered SCD with a known diagnosis of HF (65% male, age 72±14) of which 434 had 2 LVEF evaluations at least 1 yr apart prior to their SCD. At earliest evaluation, 100 (23%) had HFrEF (73% male, age 67±13), 88 (20%) had HF with moderately reduced EF (HFmrEF, 35&lt;ef&amp;lt;50) (71% male, age 72±12), and 246 (57%) had hf with preserved ef (hfpef, ef≥50) (57% 72±12). comparing the earliest latest assessment of lvef, mean lvef in hfref increased by 9±14 percentage points (p&amp;lt;0.001) from 27±6 to 36±14; hfmref decreased over time -4±14 (p="0.003)" 43±4 39±14; hfpef -8±13, 62±7 54±14. each subtype changed substantially (mean 2.9±1.5 yrs), sizeable proportions re-classified into different subtypes (Figure). Overall, the HF LVEF subtype was unchanged in 58% and altered in 42% (p&amp;lt;0.001). Conclusions: Based on the LVEF, at least 40% of HF sub-types were re-classified prior to SCD and risk assessment would be variable depending on when LVEF was measured. These findings highlight the limitations of using the LVEF as the only risk predictor of SCD.