Cardiac Arrest Research Articles

Sudden cardiac arrest during marathons among young, middle-aged, and senior runners

AimThere is limited evidence showing a relationship with age in the incidence of sudden cardiac arrest during exercise, which can be lethal at times MethodsTo examine the incidence by age group in sudden cardiac arrest, we prospectively observed cases of sudden cardiac arrest in full marathons certified by the Japan Association of Athletics Federations held between April 2011 and March 2019. Sudden cardiac arrest was defined as collapse during or 1 h after the race requiring chest compressions or the use of an automatic electrical defibrillation. Results4.1 million persons ran in 516 marathons. Of the participants, 78.6 % were men. By age group, 37.4 %, 34.7 %, 19.6 %, and 8.3 % belonged to the < 40 s, 40 s, 50 s, and ≥ 60 s groups, respectively. During the study period, 69 sudden cardiac arrests (1.7 per 100,000 participants, 95 % confidence interval [CI]: 1.3–2.1) were observed, of which 66 were men. The incidence per 100,000 runners of sudden cardiac arrest was 0.9 (95 % CI: 0.4, 1.4), 0.9 (95 % CI: 0.4, 1.4), 2.6 (95 % CI: 1.5, 3.8), and 5.5 (95 % CI: 2.9, 8.2) for those in their under 40 s, 40 s, 50 s, and over 60 s, respectively, with higher rates for older age groups. Compared to men, the cases of SCA among women were less common (only three cases), and the incidence did not differ by age group. ConclusionsMen, unlike women, had a higher incidence of sudden cardiac arrest during marathons according to age. Identification of this high-risk population could be important information in encouraging marathoners pre-participation self-screening.

Cardiac arrest in adult cardiology patients receiving anaesthetic care: analysis from the 7th National Audit Project (NAP7) of the Royal College of Anaesthetists.

The 7th National Audit Project of the Royal College of Anaesthetists studied peri-operative cardiac arrest because of existing knowledge gaps in this important topic. This applies in particular to cardiology patients receiving anaesthetic care, because numbers, types and complexity of minimally invasive interventional procedures requiring planned and unplanned anaesthesia in the cardiac intervention suite is increasing. We analysed collected data to determine the epidemiology, clinical features, management and outcomes of peri-operative cardiac arrest in adult patients receiving anaesthetic care for cardiology procedures. There were 54 reports of peri-operative cardiac arrest in adult patients receiving anaesthetic care for cardiology procedures, accounting for 54/881 (6.1%) of all reports to NAP7. The estimated incidence (95%CI) of cardiac arrests in this group was 1/450 or 0.22 (0.17-0.29)%. These patients were older than other adult patients in the NAP7 population, with a notably high proportion of patients of Asian ethnicity when compared with the remaining NAP7 cohort (9/54, 17% vs. 35/709, 5%). Rates of extracorporeal membrane oxygenation cardiopulmonary resuscitation were low (3/53, 6%). A common theme was that of logistical issues and teamworking, with reporters commenting on the difficulties of remote and/or unfamiliar locations and communication issues between specialties, on occasion resulting in poor teamworking and a lack of focus. The NAP7 panel review identified several other common themes which included: cardiogenic shock; late involvement of anaesthesia in the case; and transcatheter aortic valve implantation. Cardiology procedures requiring anaesthesia care account for < 1% of anaesthesia activity but generate 6% of all peri-operative cardiac arrests. The incidence of cardiac arrest was disproportionately high in cardiological procedures requiring anaesthetic care. The nature of the cardiac arrest reports to NAP7 indicate that logistical and human factors in multidisciplinary teams in the cardiac intervention suite merit addressing to improve care.

The impact of door to extracorporeal cardiopulmonary resuscitation time on mortality and neurological outcomes among out-of-hospital cardiac arrest acute myocardial infarction patients treated by primary percutaneous coronary intervention

BackgroundFew previous studies evaluated the impact of time from the hospital arrival to the implementation of extracorporeal cardiopulmonary resuscitation (ECPR) (door to ECPR time) on outcomes among out-of-hospital cardiac arrest (OHCA) acute myocardial infarction (MI) patients. Methods50 patients with OHCA who received both ECPR and percutaneous coronary intervention (PCI) at Cardiovascular Division, NHO Osaka National Hospital were analyzed. Patients were divided into 2 groups according to the median of door to ECPR time. The primary outcome was all-cause death. Survival analyses were conducted to compare all-cause mortality at 90 days between 2 groups. Neurological outcome at 30 days was also compared between 2 groups using the Cerebral Performance Category (CPC). ResultsThe multivariable Cox proportional-hazards model showed that all-cause mortality at 90 days was significantly higher among patients with door to ECPR time ≥ 25 min compared with those with door to ECPR time < 25 min (adjusted hazard ratio [HR]: 3.14; 95 % confidence interval [CI]: 1.21–8.18). The proportion of patients with CPC at 30 days ≤ 2 was significantly higher among patients with shorter door to ECPR time (P = 0.048). ConclusionAmong patients with OHCA due to acute MI who received ECPR and PCI, the shorter door to ECPR time was associated with the lower mortality and favorable neurological outcomes.

Toluene Inhalant Addiction and Cardiac Functions in Young Adults: A Comparison of Electrocardiographic and Echocardiographic Parameters.

Volatile substance (thinner) addiction can cause serious cardiac events, such as malignant ventricular arrhythmias, acute coronary syndromes, sudden death syndrome, and dilated cardiomyopathy, as reported in many case studies. We aimed to find echocardiographic and electrocardiographic parameters that could foresee these adverse outcomes in clinical settings. We enrolled 32 healthy young adult patients with at least 1 year of thinner addiction and no cardiac symptoms. We also recruited a control group of 30 healthy individuals without any medical problems. Both groups received standard echocardiography and ECG tests. We analyzed the following echocardiographic parameters: LVEDd (left ventricular end-diastolic diameter), LVESd (left ventricular end-systolic diameter), mitral valve EF slope, E/A ratio, and aortic and pulmonary valve VTI (velocity time integral). We also measured the corrected (QTc), uncorrected QT intervals, and widest P-wave values in the ECG. We used the SPSS 13 software for statistical analysis. The echocardiographic findings did not differ significantly between the groups. However, the ECG results showed that the thinner addicts had higher values of corrected (QTc), uncorrected QT intervals, and widest P-wave values than the control group, according to Mann-Whitney U and Student's T test. Corrected QT (QTc) and P-wave duration are increased in individuals with a thinner addiction. These findings may suggest a higher risk of sudden cardiac death, atrial, and ventricular dysrhythmias in the future.

Evolutionary Stress Detection Framework through Machine Learning and IoT (MLIoT-ESD)

Background: Life nowadays is full of stress due to lifestyle changes and the modernera race. Almost everyone around us is suffering from stress and anxiety. Mostly, stress identification is done by medical practitioners in a very late stage in which suitable help measures cannot be provided and hence result in suicides or early age deaths due to cardiac arrest, etc. One major reason behind the delay is the time required in stress identification by traditional approaches, and above that, the amount of time and financial support expected is always not feasible to be available. Hence, in this paper, we proposed an evolutionary research framework for stress identification by the usage of both machine learning and IoT. Here, we also conducted a pilot study on 83 records available over the decade since 2014 using PRISMA guidelines, and a bibliographic network visualization was also performed using VOS viewer. Objectives: This study aimed to develop a stress detection framework using Machine Learning and the Internet of Things (IoT) as technology advanced over a decade. Methods: More than 80 research papers from honorable repositories like Scopus and Web of Science were gathered according to the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020, and the VOSviewer tool was further applied to construct the bibliographic depictions. Various datasets and methods used over ten years with their performance were also discussed. Results: This research was conducted to gather various types of stressors, the impact of various Machine Learning and IoT algorithms and concepts on various datasets and their respective results. Conclusion: Various available datasets and results with multiple algorithms were discussed in a crisp tabular form for better understanding. A methodology based on an amalgamation of Machine Learning and IoT was also proposed due to various research gaps available so that stress detection could be done in a cost-effective way.

Outcomes in patients with out-of-hospital cardiac arrest according to prehospital advanced airway management timing: a retrospective observational study.

In patients with out-of-hospital cardiac arrest (OHCA), guidelines recommend advanced airway (AA) management at the advanced cardiovascular life support stage; however, the ideal timing remains controversial. Therefore, we evaluated the prognosis according to the timing of AA in patients with OHCA. We conducted a retrospective observational study of patients with OHCA at six major hospitals in Daegu Metropolitan City, South Korea, from August 2019 to June 2022. We compared groups with early and late AA and evaluated prognosis, including recovery of spontaneous circulation (ROSC), survival to discharge, and neurological evaluation, according to AA timing. Of 2,087 patients with OHCA, 945 underwent early AA management and 1,142 underwent late AA management. The timing of AA management did not influence ROSC in the emergency department (5-6 minutes: adjusted odds ratio [aOR], 0.97; p=0.914; 7-9 minutes: aOR, 1.37; p=0.223; ≥10 minutes: aOR, 1.32; p=0.345). The timing of AA management also did not influence survival to discharge (5-6 minutes: aOR, 0.79; p=0.680; 7-9 minutes: aOR, 1.04; p=0.944; ≥10 minutes: aOR, 1.86; p=0.320) or good neurological outcomes (5-6 minutes: aOR, 1.72; p=0.512; 7-9 minutes: aOR, 0.48; p=0.471; ≥10 minutes: aOR, 0.96; p=0.892). AA timing in patients with OHCA was not associated with ROSC, survival to hospital discharge, or neurological outcomes.

Influence of Right and Left Bundle Branch Block in Patients With Cardiogenic Shock and Cardiac Arrest.

The study investigates the prognostic impact of right bundle branch block (RBBB) and left bundle branch block (LBBB) in patients with cardiogenic shock (CS) compared with no bundle branch block (BBB). In patients with heart failure, existence of RBBB and LBBB has influence on prognosis. Prospective registry-study. ICU of a tertiary academic hospital in Germany. Adult patients with CS. None. Consecutive patients with CS were included. The prognostic impact of RBBB and LBBB on 30-day all-cause mortality was tested within the entire cohort and in the subgroup of CS patients with cardiac arrest at admission. The final study cohort comprised 248 patients. Patients with RBBB showed the highest 30-day all-cause mortality followed by LBBB and no BBB (72.5% vs. 52.9% vs. 50.0%; log-rank p = 0.015). These findings were consistent even after solely including CS patients with cardiac arrest (90.0% vs. 73.3% vs. 62.2%; log-rank p = 0.008). After adjustment for lactate, norepinephrine, troponin I, Acute Physiology Score, Society of Cardiovascular Angiography & Interventions shock stage, and heart rate in a multivariable Cox regression analysis, RBBB still revealed a negative impact on 30-day all-cause mortality (hazard ratio [HR], 1.807; 95% CI, 1.107-2.947; p = 0.018), whereas LBBB was not associated with 30-day all-cause mortality. In this multivariable Cox regression model lactate (HR, 1.065; 95% CI, 1.018-1.115; p = 0.006), troponin I (HR, 1.003; 95% CI, 1.001-1.005; p = 0.001), and Acute Physiology Score (HR, 1.033; 95% CI, 1.001-1.066; p = 0.041) were as well associated with 30-day all-cause mortality. Finally, no association of RBBB was found with the incidence of liver or severe renal failure. Besides the Acute Physiology Score, lactate, and troponin levels, RBBB was associated with an increased 30-day all-cause mortality in consecutive CS patients with and without cardiac arrest, whereas LBBB showed no prognostic impact.

Outcomes of odontoid fractures with associated cardiac arrest: retrospective bi-center case series and systematic literature review

Abstract Background Odontoid fractures from high-energy trauma are associated with significant morbidity and mortality, including spinal cord injury, neurological damage, and cardiac arrest. The literature on odontoid fractures leading to cardiac arrest is limited to isolated case reports. This study aims to conduct a retrospective bi-center case series and a systematic review of existing literature. Methods We conducted a retrospective bi-center case series on patients with odontoid fractures from high-energy trauma who experienced post-traumatic cardiac arrest with return of spontaneous circulation (ROSC) after CPR from two Level 1 Trauma Centers (2008–2024). The primary outcome was in-hospital mortality; secondary outcomes included epidemiological, pre-hospital, and in-hospital data, and CT and MRI findings. Additionally, we performed a systematic literature review to summarize existing evidence. Results The study included 25 patients (mean age 71.1 ± 12.3 years, SD; 8 females). The mortality rate was 92% (23 patients). Median downtime before CPR was 5.0 min (IQR: 7.0), with CPR lasting 17.0 min (IQR: 13.0), primarily initiated by professionals (60%). All patients were quadriplegic. Type II Anderson d’Alonzo fractures were most common (88%), with all patients showing myelopathy on MRI. Only three patients (12%) underwent surgical intervention due to favorable prognosis. Our literature review identified seven case reports, with two patients surviving and one achieving full recovery. Conclusions In this case series, patients experiencing cardiac arrest after odontoid fractures exhibited high mortality rates despite comprehensive management at Level 1 trauma centers. Survivors faced significant and enduring morbidity.

Novel real-time automation of combined frequency and low voltage substrate mapping to guide ablation for Brugada syndrome: a case report

Abstract Background Brugada syndrome (BrS) is an inherited cardiac condition that increases the risk of sudden cardiac death (SCD) due to ventricular arrhythmias. Catheter ablation has been shown to effectively reduce recurrent ventricular fibrillation (VF) episodes through targeting of abnormal electrograms predominantly located within the anterior surface of the right ventricular outflow tract. Signal frequency mapping is an emerging concept that provides further definition of pathological ventricular substrate. Case summary A 66-year-old male with BrS was admitted to our institution with ICD shocks for VF. Electro-anatomical mapping (EAM) and ablation was performed utilising a novel automated frequency-based strategy. Combined automated frequency and low voltage maps were generated to define high frequency, low voltage (HF-LVo) depolarisation abnormalities within the QRS complex. Low frequency, low voltage (LF-LVo) regions from the QRS terminal notch to the T-wave offset were also identified. The combined HF-LVo and LF-LVo map areas totalled 12.4cm2, compared to the conventional low voltage and late potential map areas, which were 44cm2 and 27.8cm2 respectively. The ablation strategy targeted HF-LVo and LF-LVo regions only. Following ablation, re-mapping demonstrated near complete abolition of HF-LVo and LF-LVo regions, with no inducible ventricular arrhythmias during extra-stimulation testing. During follow-up, ECG normalisation was observed, with no further ventricular arrhythmias and a negative ajmaline challenge at 6 months. Discussion Catheter ablation for BrS utilising a novel automated combined frequency and low voltage EAM approach can objectively identify relevant substrate. The results demonstrate adequate substrate modification with comparable ablation target areas to previous studies and encouraging clinical outcomes.

High-intensity exercise-related sudden cardiac death in hypertrophy cardiomyopathy

Abstract Background Whether exercise provokes sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM) is uncertain. Current European guidelines recommend against high-intensity exercise in individuals with high SCD risk or obstructive physiology. Purpose We investigated the factors associated with exercise-related SCD in HCM. Methods We retrospectively analyzed of 2,844 consecutive patients with HCM who underwent evaluation between 2005 and 2023 at a high-volume tertiary center. SCD events were defined as a composite of aborted SCD, appropriate implantable cardioverter-defibrillator (ICD) shock, and SCD. Among 80 first SCD events (2.8%), 75 events had a description of the physical activity at the time of the event. Patients were classified into two groups according to physical activity level at the time of the SCD event. Group 1 included patients with high-intensity exercise-related SCD events, defined as happening during or immediately after high-intensity exercise or physical activity, while Group 2 included patients with SCD events happening at rest or during light or moderate physical activity. Results The 75 first SCD events included 44 aborted SCD, 22 appropriate ICD shocks, and 9 SCD. Median age at SCD event was 54 (IQR 39.5–62.5) years and 60 (80%) were men. Patients in Group 1 (n=14) were younger than patients in Group 2 (n=61) (23.5 [IQR 16–48] vs. 55 [IQR 44–64] years, p&amp;lt;0.001), and most patients in group 1 (92.9%) were under the age of 60 years. Patients in Group 1 had slightly smaller left ventricular (LV) end-diastolic dimension and had higher ESC SCD risk scores (3.6 [IQR 2.5–6.7] vs. 2.4 [IQR 1.7–4.8], p=0.044) than patients in Group 2; however, there were no significant differences in the proportion of high-risk patients (28.6% vs. 14.8%, p=0.396) or patients with AHA major SCD risk factors (57.1% vs. 55.7%, p=0.999). Otherwise, there were no significant differences in the presence of obstructive physiology, apical HCM, and apical aneurysm, LV systolic and diastolic function, and comorbidities between the two groups. Furthermore, of the 29 patients who underwent genetic testing, there was no difference in the proportion of patients with pathogenic sarcomeric variants according to exercise-related SCD (50.0% vs. 65.2%, p=0.683). To note, there was a non-significant tendency towards higher proportion of thin filament variants in Group 1 than Group 2 among those with pathogenic sarcomeric variants (100% [3/3] vs 26.7% [4/15], p=0.084). Conclusions Most high-intensity exercise-related SCD events happened under the age of 60. The ESC SCD risk score was higher in patients with high-intensity exercise-related SCD events, although the SCD risk categories or AHA risk factors could not discriminate patients at higher risk of events. These results suggest that exercise recommendations should not be based on SCD risk category, presence of obstruction, or degree of LV hypertrophy.

Quantifying late gadolinium enhancement improved sudden cardiac death risk prediction in non-ischemic dilated cardiomyopathy

Abstract Background While previous studies have proved the late gadolinium enhancement (LGE) was associated with poor prognosis in non-ischemic dilated cardiomyopathy (DCM), the optimal method for LGE quantification and the ability of LGE extent in identifying sudden cardiac death (SCD) remain less clarified. Purpose This study sought to compare the reproducibility of LGE quantification methods and explore the asssociation between LGE extent and SCD endpoint in DCM patients. Methods In this prospective study, LGE was quantified by the 2-6 standard deviations (SD) above the remote myocardium and full-wide half-maximum (FWHM) methods. The primary endpoint was SCD and arrythmia endpoint included SCD and aborted SCD. Reproducibility of LGE quantification was measured by Bland-Altman analysis and intra-class correlation coefficients (ICC). Competing risk regression analysis, C-index and area under the curve (AUC) were performed to identify the prognostic value. Results Among the 770 patients, 336 (44%) patients had LGE. FWHM demonstrated the best reproducibility compared with other quantification methods (intraobserver variability: ICC = 0.94, mean bias: -0.43 ± 4.89%; interobserver variability: ICC = 0.90, mean bias: -2.65 ± 6.40%). After a median follow-up of 49 months, SCD occurred in 61 (8%) patients and arrythmia endpoint occurred in 87 (11%) patients. Among all quantification method, LGE extent measured by FWHM showed the highest predictive value of SCD (C index: 0.72) and arrythmia events (C index: 0.71) than other methods. In the competing risk analysis, LGE extent was independently association with SCD (Hazard ratio [HR] 1.05, 95% confidence interval [CI] 1.03 - 1.07, P &amp;lt; 0.001) and arrythmia endpoint (HR 1.05, 95% CI 1.03 - 1.06, P &amp;lt; 0.001). LGE extent &amp;gt;8% showed significantly higher risk of SCD and arrythmia endpoint than those with LGE extent ≤8% (P &amp;lt; 0.001). Incoporating LGE exent and 35% left ventricular ejection fraction (LVEF) significantly improved the SCD (C index: 0.74 vs 0.61, P &amp;lt; 0.001) and arrythmia endpoint (C index: 0.73 vs 0.59, P &amp;lt; 0.001) prediction compared with LVEF. Conclusions FWHM demonstrated best reproducibility and highest SCD prediction ability among LGE quantification methods. Adding LGE extent to LVEF significantly improved the predictive value of SCD and arrythmia endpoint.Figure 1

Personalized prediction model specific for sudden cardiac death in the population: a machine learning study based on EHR

Abstract Background Predicting sudden cardiac death (SCD) in the general population remains a significant challenge, particularly at the individual level. SCD and myocardial infarction (MI) share similar pattern of characteristics and risk factors, making their specific prediction highly difficult. As a result, the current prediction models exhibit low specificity. Methods To estimate the specific risk of SCD over three months, we trained a machine learning model on electronic health record (EHR) data representing 8,566,229 drug prescriptions and 801,352 of hospital diagnoses up to five years prior to SCD. The data were obtained from a French cohort of 12,338 SCD and from a cohort of 12,338 controls from 2011 to 2015. We then validated the results on two external cohorts: one temporal cohort in the same area between 2016 and 2020 with 11,620 SCD cases and 11,620 controls and one geographical cohort from the USA with 892 SCD cases and 892 controls from 2013 to 2021. In order to address the specificity of our prediction model for SCD, SCD cases collected between 2016 and 2020 were also matched with a group of 35 000 controls who had myocardial infarction, with no SCD, following the same protocol as for the controls issued from the general population. Findings: The analysis reveals three distinct patterns of distribution for SCD cases, controls, and MI cases. We observed a semi linear increase of SCD cases over the deciles of predicted risk, and our model detected 24% (2,908) of SCD cases with a predicted risk exceeding 90% (highest decile). We observed the opposite among the controls that decreased linearly with increasing deciles of predicted risk: most of the controls were accurately identified in the lowest deciles, and there were only 214 controls (2%) in the highest decile. Interestingly, we observed a relatively stable distribution of MI cases across the deciles, with 10% of MI cases in the highest decile (Figure 1). Interpretation: We developed and validated a personalized prediction model that is able to identify subjects at high-risk for SCD specifically. Figure 1: Histogram of predicted risks for sudden cardiac death cases, controls and myocardial infarction cases in the validation cohort.Figure 1

Novel protein-based biomarkers of out-of-hospital sudden cardiac death after myocardial infarction

Abstract Background Risk stratification of out-of-hospital sudden cardiac death (SCD) patients after acute myocardial infarction (AMI) is crucial for timely therapeutic interventions. However, left ventricular ejection fraction (LVEF) as a traditional clinical tool has major limitations, necessitating improved risk stratification strategies. High-throughput proteomic offers the potential to detect novel biomarkers to improve risk assessment. Purpose To identifiy optimal circulating protein combination predicting out-of-hospital SCD post-AMI. Methods We conducted a two-center retrospective nested case-control study of cases with out-of-hospital SCD and controls with AMI who discharged alive. In a discovery cohort, we carried out plasma proteomics profiling of 6,592 peptides and 522 proteins using mass spectrometry. The proteins associated to SCD were further assessed using targeted quantitative proteomics, and the optimal protein combination for predicting out-of-hospital SCD post-AMI was identified by predictor selection classifier. Finally, ELISA validated its predictive value by comparing with a clinical stratification tool (LVEF ≤35%) and two reported risk stratification models within discovery and two independent validation cohorts. Results In the discovery cohort (Figure 1, 210 participants including 105 SCD cases [median age: 68.0 years, 59.05% men]), mass spectrometry discovered 44 differential proteins not previously associated to SCD. Targeted proteomics quantified these proteins and identified optimal protein combination, SCD-warning three protein combination (SCD-W3P), including coronin-1A, haptoglobin, and complement factor D (CFD). A model based on expression levels of SCD-W3P outperformed LVEF alone (Figure 2, C-statistic: 0.752 vs. 0.548, P&amp;lt;0.001), improving its risk prediction (ΔC-statistic = 0.281, P&amp;lt;0.001) and net reclassification improvement (9.5%, P&amp;lt;0.001). Similar incremental discrimination metrics were observed in two reported stratification models combined with SCD-W3P, particularly within the LVEF-preserved population. These findings were repeatably validated in two independent cohorts (Figure 1 and 2, validation 1: 160 participants including 40 SCD cases [median age: 72.5 years, 67.50% men]; validation 2: 96 participants including 24 SCD cases [median age: 74.5 years, 79.17% men]). Finally, CFD inhibition protection for mortality and pro-malignant arrhythmias in AMI mice supported biological plausibility of the critical protein in SCD-W3P. Conclusions This two-center retrospective nested case-control study with two independent validation serves as the largest-scale investigation with the most comprehensive proteomics profiling in out-of-hospital SCD after AMI, identifying an optimal protein combination which may contribute to enhance early identification for timely intensive management. These findings suggest pivotal proteins for improving understanding SCD pathophysiology.Methods overview.Comparison of model performances for pre

Validation of the HCM Risk-SCD model in patients with hypertrophic cardiomyopathy and future perspectives

Abstract Background/Introduction The fact that hypertrophic cardiomyopathy (HCM) is associated with sudden cardiac death (SCD) due to malignant ventricular arrhythmias underlies its clinical importance (1). SCD in patients with HCM is often an unpredictable event, occurring without previous warning signs or symptoms, and is most common in the young middle-aged group (2). The greatest dilemma in the management of HCM patients is to identify the high-risk population for SCD. The HCM risk- SCD model provides a useful convenience in determining the risk of SCD in patients with HCM even though some patients with low-risk scores still remain at risk of SCD (3). These results have increased the interest in additional strategies to improve the existing risk model. Purpose Hence, the aim of our study was to assess the performance of HCM Risk-SCD in a large series of consecutive patients with HCM who had been followed up in a tertiary centre. Methods The study population consisted of 389 consecutive HCM patients who had been followed up between 2004 and 2021. Demographic and clinical characteristics estimated 5-year risk using the HCM Risk-SCD model were compiled and survival data were collected during follow-up. Patients were divided into 2 groups according to their long-term survival and HCM risk-SCD scores of these two groups were compared. Results The long-term mortality was observed in 47 patients out of 389 patients in the mean follow-up of 55.5 ± 12.7 months. The mean HCM Risk-SCD of surviving patients was significantly lower than that of non-survivors (1.8% vs. 3.0%, p&amp;lt;0.001). The HCM Risk-SCD score was above 6% in 9 (2.6%) survivors and 9 (19.1%) non-survivors (p&amp;lt;0.001). Considering the Kaplan-Meier curve based on the 6% HCM Risk-SCD score, patients at ≥6% risk also had a significantly higher long-term risk of death compared to those with &amp;lt;6% (log-rank test value: 33.72, p&amp;lt;0.001) (Figure 1). The ROC curve based on the HCM Risk-SCD score had 61% sensitivity and 61% specificity for risk for 2.0%, 38% sensitivity and 99% specificity for ≥4%, 17% sensitivity and 99% specificity for ≥6% (Figure 2). Conclusion(s) In conclusion, the current study demonstrates that the HCM risk-SCD model, while easily calculable and clinically useful, does not reliably identify a significant subset of patients with HCM who will potentially be at lifetime risk of SCD. Identifying patients with hypertrophic cardiomyopathy at high risk for SCD who deserve ICD therapy is a critical management priority. A new risk algorithm that can detect the SCD risk of HCM patients with higher sensitivity is needed.Figure 1Figure 2

Temporal trends in sudden cardiac death after acute decompensation in HFrEF patients: a 13-year Japanese multicentre registry study

Abstract Background The implementation of guideline-based medical therapy (GBMT) for heart failure with reduced ejection fraction (HFrEF) has significantly contributed to reducing mortality risks. Yet, detailed analyses on temporal trends of sudden cardiac death (SCD) among these patients, especially post-discharge following acute decompensation, remain scarce. Purpose This study aimed to explore changes in the incidence of SCD over the last 13 years in patients with HFrEF discharged after acute decompensation treatment, and to identify clinical factors associated with SCD risk. Methods We analyzed 2,604 consecutive HFrEF (left ventricular ejection fraction [LVEF] ≤40%) patients enrolled in a Japanese multicentre acute heart failure (HF) registry from 2009 to 2021. SCD was defined as an unexpected and otherwise unexplained death in a previously stable patient or death due to documented or presumed cardiac arrhythmia without a clear non-cardiovascular cause. The determination of death cause (SCD, pump failure death, or other) was made by a central adjudicating committee. The Fine and Gray method was employed to analyze factors associated with SCD. The variables submitted to the model included age (≥70 years), gender, LVEF (&amp;lt;30%), ischaemic aetiology and prescription of GBMT (use of renin-angiotensin system inhibitors, β-blockers and mineralocorticoid receptor antagonist) at discharge. Results The mean age of studied patients was 70.9±14.2 years, and 70.0% were male. During the 1-year follow-up period, 262 deaths (10.1%) occurred, including 51 SCDs (2.0%). Older age was associated with an increased risk of SCD (adjusted hazard ratio [HR] 2.81, 95% confidence interval [CI] 1.40-5.64, P=0.004). Further, patients with an ischaemic aetiology had a higher risk of SCD (HR 1.84, 95% CI 1.06-3.22, P=0.032). During the study period, mean age remained constant (71.0 years to 70.7 years, P for trend =0.884). The proportion of ischaemic aetiology also remained constant (from 37.2% to 38.2%, P for trend =0.972). Overall, there were significant decreases in the incidence of all cause death and SCD (from 13.7% to 8.4%, P for trend =0.002; and from 3.5% to 1.0%, P for trend &amp;lt;0.001; Figure A). Notably, there was an increase in the prescription rate of three classes of GBMT at discharge (from 30.9% to 45.6%, P for trend &amp;lt;0.001; Figure B), and the rate of implantable cardioverter-defibrillator (ICD) use in eligible patients (New York Heart Association functional class II-III with LVEF ≤35%) remained constant (from 9.6% to 11.6%, P for trend =0.157; Figure B). Conclusions With the increasing use of GBMT, the incidence of SCD decreased in real-world patients with HFrEF registered in a Japanese acute HF registry over the past decade.

Automated cardiac arrest DETECTion incorporated into a wristband: validation of a photoplethysmography algorithm in patients with spontaneous and induced cardiac arrest

Abstract Background Although survival from out-of-hospital cardiac arrest (OHCA) has improved, this does not apply to unwitnessed cases, as the arrest is often recognized too late. Automated cardiac arrest detection and alarming using a wristband is a promising technology to facilitate early assistance after cardiac arrest in a home setting. In the DETECT-1 study, a photoplethysmography(PPG) algorithm for circulatory arrest detection has been developed in patients with induced circulatory arrest. Purpose To assess the performance of the developed PPG algorithm for circulatory arrest detection in: 1) patients with spontaneous cardiac arrest; 2) subjects with induced circulatory arrest using blood pressure cuff inflation. Methods We selected patients with episodes of spontaneous cardiac arrest who participated in the DETECT-1 study and patients/healthy subjects with short-lasting induced circulatory arrest using blood pressure cuff inflations from the DETECT-1 and DETECT-2 studies. The DETECT-1 study included patients who underwent transcatheter aortic valve implantation (TAVI), subcutaneous ICD implantation, or ventricular tachycardia ablation. Included patients wore the PPG-wristband during the procedure. Continuous ECG and invasive blood pressure data were collected as reference standard. The DETECT-2 study included healthy volunteers who wore the PPG-wristband during physical exercise. Sensitivity for spontaneous and induced circulatory arrest and false positive alarms were assessed using the previously developed algorithm for circulatory arrest detection. All episodes were analyzed as individual events. Results A total of 39 individuals were included; nine patients with spontaneous cardiac arrests during TAVI and 20 subjects with 116 induced circulatory arrests. Of the patients with spontaneous cardiac arrest, two had ventricular fibrillation, five had pulseless electrical activity (figure), and two had asystole. Eight out of nine cardiac arrest events were detected by the circulatory arrest detection algorithm (sensitivity 89% [95% CI 51-99%]). Of the subjects with induced circulatory arrests, the PPG algorithm detected 114 induced circulatory arrests, yielding a sensitivity of 98% (95% CI 93-100%). In the entire group, there were no false positive alarms during 60 recording hours. Conclusions Automated cardiac arrest detection using a PPG-wristband is feasible with excellent sensitivity for both spontaneous and induced circulatory arrest. False positive alarms were absent in this controlled setting. Further study is warranted to assess algorithm performance in a larger sample of spontaneous cardiac arrests, and false positive alarms during daily life use. If available, automated cardiac arrest detection and alarming has the potential to markedly increase survival from OHCA in a home setting.Episode of spontaneous cardiac arrest

A 3-year retrospective exploration of predictors for cardiac arrest in atrial fibrillation

Abstract Background An increasing correlation between atrial fibrillation (AF) and a heightened risk of cardiac arrest is emerging. Yet, the specific predictors of cardiac arrest in hospitalized patients with AF remain unclear. Purpose This study aims to identify these predictors, providing essential insights for refined risk assessment and targeted clinical interventions. Methods Adult patients hospitalized between 2018 and 2020 with a primary diagnosis of AF with or without cardiac arrest were identified using the International Classification of Diseases, Tenth Revision (ICD-10) code. Demographics and comorbidities were recorded. Logistic regression was employed to identify predictors of increased cardiac arrest. Results In a study of 272,028 hospitalizations with AF, 2,352 patients suffered cardiac arrest, and 523 died during hospitalization. Factors associated with increased odds of cardiac arrest include heart failure (OR = 1.79, 95% CI: 1.60–2.00), cardiogenic shock (OR = 2.95, 95% CI: 2.35–3.71), history of coronary angioplasty or bypass (OR = 1.79, 95% CI: 1.59–2.02), chronic kidney disease (OR = 1.26, 95% CI: 1.12–1.42), end-stage kidney disease (OR = 2.34, 95% CI: 1.98–2.77), and septic shock (OR = 6.50, 95% CI: 4.80–8.80). Chronic obstructive pulmonary disease (COPD) and infection were associated with a 13% (OR = 1.13, 95% CI: 1.02–1.26) and 45% (OR = 1.45, 95% CI: 1.25–1.68) increase in odds for cardiac arrest, respectively. Increased age (OR = 0.99, 95% CI: 0.98–0.99) and female sex (OR = 0.83, 95% CI: 0.76–0.91) showed an inverse relation with cardiac arrest. Hypertension and obesity exhibited protective effects against cardiac arrest, with odds ratios of 0.85 (95% CI: 0.74–0.97) and 0.83 (95% CI: 0.75–0.93), respectively. Conclusion Our study underscores the intricate web of factors influencing cardiac arrest risk in AF patients. A personalized approach to risk assessment in the context of AF might be needed.

Global and national insights into the decline of hypertrophic cardiomyopathy as a cause of sudden death in the young

Abstract Background &amp; Objective Hypertrophic cardiomyopathy (HCM) has been reported as a leading cause of sudden cardiac death (SCD) in the young but appears less common in contemporary cohorts of young SCD. This research aimed to determine if HCM is a common cause of SCD in the young and whether this has changed over time. Methods We analysed three national databases, the National Echo Database Australia (NEDA), Centre for Disease Control Wide-ranging Online Data for Epidemiologic Research (CDC-WONDER) and the National Coronial Information System of Australia (NCIS) to determine incidence of SCD due to HCM in ≤ 35 years old from 1999-2017. Sub-analyses assessed for differences in sex and obstructive and non-obstructive HCM phenotypes. Results NEDA: Of 40,738 individual echocardiograms 2005-2017, 868 (2.13%) exhibited the HCM phenotype. 982 patients died ≤ 35 years, of which 4 deaths were attributable to HCM (0.4%). CDC-WONDER: 41% reduction in HCM related mortality/million people across 1999-2016 (p&amp;lt;.0001). Similar reduction was seen when stratified for age, sex and non-obstructive/obstructive HCM phenotype. NCIS: 36% reduction in HCM-related SCD was observed between 2001-2010 and 2011-2016 periods (p=.049). Conclusions HCM rarely causes SCD and accounts for &amp;lt;5% of SCD in the young. Rates of HCM-related SCD have been decreasing over the last two decades. Improved survival likely relates to improved case detection and medical management.Abstract Figure

Diabetes and sudden cardiac death in a nationwide, unselected population

Abstract Background and purpose Sudden cardiac death (SCD) remains a prominent cause of mortality, with individuals afflicted by diabetes mellitus (DM) bearing a heightened risk of ventricular arrhythmias and SCD. However, comprehensive investigations in a nationwide, unselected context are lacking. Therefore, this study aimed to compare the incidence rates (IR) of SCD among individuals with Type 1 Diabetes Mellitus (T1DM) and Type 2 Diabetes Mellitus (T2DM) to the general population. Methods The study included the entire Danish population (approximately 5.5 million individuals) in 2010. SCD cases were identified through the detailed Danish death certificates and discharge summaries, yielding 6851 cases of SCD. The Danish Register of Medicinal Product Statistics, containing comprehensive prescription data from Danish pharmacies, facilitated the identification of individuals with T1DM and T2DM. Loss of life years was estimated for both T1DM and T2DM patients. Results Among the identified 6851 SCD cases, 272 (4%) were diagnosed with T1DM, and 833 (12%) with T2DM. Incidence rates of SCD were consistently elevated across all age groups for individuals with diabetes, compared to the general population (Figure 1). Patients with T1DM exhibited higher incidence rates than patients with T2DM (Figure 1). Notably, individuals aged 30-40 years with DM showed the greatest differences in incidence rates of SCD compared to the general population, with incidence rate ratios of 20.0 (95% confidence interval: 11.8-80.0) and 5.6 (95% confidence interval: 2.7-14.0) for T1DM and T2DM, respectively. On average, each 30-year-old patient with either T1DM or T2DM experiences a reduction of 3.7 and 3 life-years, respectively, due to the increased risk of SCD in these groups (Figure 2). Conclusion This nationwide study examines the incidence rates of SCD among individuals with and without a history of DM across all age brackets. Notably, patients with DM display consistently elevated incidence rates across age groups, with a particularly pronounced risk observed in those with T1DM. For both T1DM and T2DM, SCD is an important contributing factor to their shorter life expectancy compared to the general population. The heightened risk among individuals with DM underscores the importance of improved risk stratification for these patients.Incidence rates of SCDStacked cumulative incidence curves

Spontaneous Coronary Artery Dissection (SCAD) with cardiac arrest at presentation: a subanalysis from the DISCO registry

Abstract Introduction Spontaneous coronary artery dissection (SCAD) is a rare cause of acute myocardial infarction (AMI), which primarily affects young women without traditional cardiovascular risk factors, often presenting as sudden cardiac death. This study aims to investigate the prevalence, characteristics, predictors, and outcomes of cardiac arrest in SCAD patients. Methods The DISCO IT/SPA registry, an international retrospective multicenter study, enrolled 375 SCAD patients from 26 centers in Italy and Spain. Patients were categorized based on the presence or absence of cardiac arrest at admission. Data on demographics, clinical presentation, treatment, angiographic findings, and outcomes were collected. Angiograms were independently reviewed, and outcomes included major adverse cardiovascular events (MACE) and in-hospital bleeding. Results Among 375 SCAD patients, 20 (5.3%) presented with cardiac arrest. Both groups were similar in age, gender distribution, and conventional risk factors, except for a lower prevalence of dyslipidemia in the cardiac arrest group. ST-segment elevation myocardial infarction (STEMI) presentation and angiographic type 2b were independent predictors of cardiac arrest. Revascularization was more frequent in the cardiac arrest group. In-hospital outcomes, except for longer hospitalization, did not differ. On follow-up (average 21 months), MACE rates were similar between groups. Conclusions Cardiac arrest is a notable complication in SCAD, mostly presenting with ventricular fibrillation. The prognosis of SCAD patients presenting with cardiac arrest did not differ from those without, reporting a similar rate of events both in-hospital and during long-term follow-up. STEMI presentation and angiographic type 2b were identified as independent predictors of cardiac arrest in SCAD.