Autopsy of all young sudden death cases is important to increase survival in family members left behind.

Sudden cardiac death (SCD) is an important public health problem worldwide, accounting for an estimated 6 to 20% of total mortality. A significant proportion of SCD is caused by inherited heart disease, especially among the young. An autopsy is crucial to establish a diagnosis of inherited heart disease, allowing for subsequent identification of family members who require cardiac evaluation. Autopsy of cases of unexplained sudden death in the young is recommended by both the European Society of Cardiology and the American Heart Association. Overall autopsy rates, however, have been declining in many countries across the globe and there is a lack of skilled trained pathologists able to carry out full autopsies. Recent studies show that not all cases of sudden death in the young are autopsied, likely due to financial, administrative, and organizational limitations as well as awareness among police, legal authorities, and physicians. Consequently, diagnoses of inherited heart disease are likely missed, along with the opportunity for treatment and prevention among surviving relatives. This article reviews the evidence for the role of autopsy in sudden death, how the cardiologist should interpret the autopsy-record and how this can be integrated and implemented in clinical practice. Finally, we identify areas for future research along with potential for healthcare reform aimed at increasing autopsy awareness and ultimately reducing mortality from SCD.

A qualitative analysis of post-hoc interviews with multilevel participants of a randomized controlled trial of a community-based intervention.

INTRODUCTION: Community-based health interventions often demonstrate efficacy in clinical trial settings but fail to be implemented in the real-world. We sought to identify the key operational and contextual elements of the Los Angeles Barbershop Blood Pressure Study (LABBPS), an objectively successful community-based health intervention primed for real-world implementation. LABBPS was a cluster randomized control trial that paired the barbers of Black-owned barbershops with clinical pharmacists to manage uncontrolled hypertension in Black male patrons, demonstrating a substantial 21.6 mmHg reduction in systolic blood pressure. Despite this success, the LABBPS intervention has not expanded beyond the original clinical trial setting. The aim of this study was to determine the facilitating and limiting factors to expansion of the LABBPS intervention. METHODS: We undertook a qualitative assessment of semi-structured interviews with study participants performed after trial completion. Interviews included a total of 31 participants including 20 (6%) of the 319 LABBPS program participants ("patrons"), 10 (19%) barbers, and one (50%) clinical pharmacist. The semi-structured interviews were focused on perceptions of the medical system, study intervention, and influence of social factors on health. RESULTS: Several common themes emerged from thematic analysis of interview responses including: importance of care provided in a convenient and safe environment, individual responsibility for health and health-related behaviors, and engagement of trusted community members. In particular, patrons reported that receiving the intervention from their barber in a familiar environment positively influenced the formation of relationships with clinical pharmacists around shared efforts to improve medication adherence and healthy habits. All interviewee groups identified the trust diad, comprising the familiar environment and respected community member, as instrumental in increasing health-related behaviors to a degree not usually achieved by traditional healthcare providers. DISCUSSION: In conclusion, participants of an objectively successful community-based intervention trial consistently identified key features that could facilitate wider implementation and efficacy: social trust relationships, soliciting insights of trust bearers, and consistent engagement in a familiar community setting. These findings can help to inform the design and operations of future community-based studies and programs aiming to achieve a broad and sustainable impact.

Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes.

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.

Deep learning evaluation of echocardiograms to identify occult atrial fibrillation.

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0.96 (0.95-0.96), AUPRC 0.91 (0.90-0.92)). Among TTEs in sinus rhythm, the model predicted the presence of concurrent paroxysmal AF (AUC 0.74 (0.71-0.77), AUPRC 0.19 (0.16-0.23)). Model discrimination remained similar in an external cohort of 10,203 TTEs (AUC of 0.69 (0.67-0.70), AUPRC 0.34 (0.31-0.36)). Performance held across patients who were women (AUC 0.76 (0.72-0.81)), older than 65 years (0.73 (0.69-0.76)), or had a CHA2DS2VASc ≥2 (0.73 (0.79-0.77)). The model performed better than using clinical risk factors (AUC 0.64 (0.62-0.67)), TTE measurements (0.64 (0.62-0.67)), left atrial size (0.63 (0.62-0.64)), or CHA2DS2VASc (0.61 (0.60-0.62)). An ensemble model in a cohort subset combining the TTE model with an electrocardiogram (ECGs) deep learning model performed better than using the ECG model alone (AUC 0.81 vs. 0.79, p = 0.01). Deep learning using TTEs can predict patients with active or occult AF and could be used for opportunistic AF screening that could lead to earlier treatment.

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study.

BACKGROUND: Preoperative risk assessments used in clinical practice are insufficient in their ability to identify risk for postoperative mortality. Deep-learning analysis of electrocardiography can identify hidden risk markers that can help to prognosticate postoperative mortality. We aimed to develop a prognostic model that accurately predicts postoperative mortality in patients undergoing medical procedures and who had received preoperative electrocardiographic diagnostic testing. METHODS: In a derivation cohort of preoperative patients with available electrocardiograms (ECGs) from Cedars-Sinai Medical Center (Los Angeles, CA, USA) between Jan 1, 2015 and Dec 31, 2019, a deep-learning algorithm was developed to leverage waveform signals to discriminate postoperative mortality. We randomly split patients (8:1:1) into subsets for training, internal validation, and final algorithm test analyses. Model performance was assessed using area under the receiver operating characteristic curve (AUC) values in the hold-out test dataset and in two external hospital cohorts and compared with the established Revised Cardiac Risk Index (RCRI) score. The primary outcome was post-procedural mortality across three health-care systems. FINDINGS: 45 969 patients had a complete ECG waveform image available for at least one 12-lead ECG performed within the 30 days before the procedure date (59 975 inpatient procedures and 112 794 ECGs): 36 839 patients in the training dataset, 4549 in the internal validation dataset, and 4581 in the internal test dataset. In the held-out internal test cohort, the algorithm discriminates mortality with an AUC value of 0·83 (95% CI 0·79-0·87), surpassing the discrimination of the RCRI score with an AUC of 0·67 (0·61-0·72). The algorithm similarly discriminated risk for mortality in two independent US health-care systems, with AUCs of 0·79 (0·75-0·83) and 0·75 (0·74-0·76), respectively. Patients determined to be high risk by the deep-learning model had an unadjusted odds ratio (OR) of 8·83 (5·57-13·20) for postoperative mortality compared with an unadjusted OR of 2·08 (0·77-3·50) for postoperative mortality for RCRI scores of more than 2. The deep-learning algorithm performed similarly for patients undergoing cardiac surgery (AUC 0·85 [0·77-0·92]), non-cardiac surgery (AUC 0·83 [0·79-0·88]), and catheterisation or endoscopy suite procedures (AUC 0·76 [0·72-0·81]). INTERPRETATION: A deep-learning algorithm interpreting preoperative ECGs can improve discrimination of postoperative mortality. The deep-learning algorithm worked equally well for risk stratification of cardiac surgeries, non-cardiac surgeries, and catheterisation laboratory procedures, and was validated in three independent health-care systems. This algorithm can provide additional information to clinicians making the decision to perform medical procedures and stratify the risk of future complications. FUNDING: National Heart, Lung, and Blood Institute.

Risk Factors for the Development of New-Onset Persistent Atrial Fibrillation: Subanalysis of the VITAL Study.

BACKGROUND: Sustained forms of atrial fibrillation (AF) are associated with lower treatment success rates and poorer prognosis compared with paroxysmal AF. Yet, little is known about risk factors that predispose to persistent AF on initial presentation. Our objective was to define risk factors associated with new-onset persistent AF. METHODS: We prospectively examined the differential associations between lifestyle, clinical, and socioeconomic risk factors and AF pattern (persistent versus paroxysmal) at the time of diagnosis among 25 119 participants without a history of cardiovascular disease, AF, or cancer in the VITAL rhythm study (Vitamin D and Omega-3). RESULTS: During a median follow-up of 5.3 years, 900 participants developed AF and 346 (38.4%) were classified as persistent at the time of diagnosis. In multivariable competing risk models, increasing age, male sex, White race, height, weight, body mass index ≥30 kg/m2, hypertension, current or past smoking, alcohol intake ≥2 drinks/day, postcollege education, and randomized treatment with vitamin D were significantly associated with incident persistent AF. Compared with paroxysmal AF, increasing age, male sex, weight, body mass index ≥30 kg/m2, and postcollege education were more strongly associated with persistent AF in multivariable models regardless of whether interim cardiovascular disease and heart failure events were censored. CONCLUSIONS: In a prospective cohort without baseline AF or cardiovascular disease, over one-third of AF at the time of diagnosis is persistent. Older age, male sex, postcollege education, and obesity were preferentially associated with persistent AF and represent a high-risk AF subset for population-based intervention.

Air Pollution and Temperature: a Systematic Review of Ubiquitous Environmental Exposures and Sudden Cardiac Death.

PURPOSE OF REVIEW: Environmental exposures have been associated with increased risk of cardiovascular mortality and acute coronary events, but their relationship with out-of-hospital cardiac arrest (OHCA) and sudden cardiac death (SCD) remains unclear. SCD is an important contributor to the global burden of cardiovascular disease worldwide. RECENT FINDINGS: Current literature suggests a relationship between environmental exposures and cardiovascular disease, but their relationship with OHCA/SCD remains unclear. A literature search was conducted in PubMed, Embase, Web of Science, and Global Health. Of 5138 studies identified by our literature search, this review included 30 studies on air pollution, 42 studies on temperature, 6 studies on both air pollution and temperature, and 1 study on altitude exposure and OHCA/SCD. Particulate matter air pollution, ozone, and both hot and cold temperatures are associated with increased risk of OHCA/SCD. Pollution and other exposures related to climate change play an important role in OHCA/SCD incidence.

Marine n-3 Fatty Acids and Prevention of Cardiovascular Disease: A Novel Analysis of the VITAL Trial Using Win Ratio and Hierarchical Composite Outcomes.

This study aimed to investigate whether n-3 fatty acid supplementation reduced cardiovascular disease (CVD) events in a novel analysis using hierarchical composite CVD outcomes based on win ratio in the VITamin D and OmegA-3 TriaL (VITAL). This was a secondary analysis of our VITAL randomized trial, which assessed the effects of marine n-3 fatty acids (1 g/day) and vitamin D3 on incident CVD and cancer among healthy older adults (n = 25,871). The primary analysis estimated win ratios of a composite of major CVD outcomes prioritized as fatal coronary heart disease, other fatal CVD including stroke, non-fatal myocardial infarction (MI), and non-fatal stroke, comparing n-3 fatty acids to placebo. The primary result was a nonsignificant benefit of this supplementation for the prioritized primary CVD outcome (reciprocal win ratio [95% confidence interval]: 0.90 [0.78-1.04]), similar to the 0.92 (0.80-1.06) hazard ratio in our original time-to-first event analysis without outcome prioritization. Its benefits came from reducing MI (0.71 [0.57-0.88]) but not stroke (1.01 [0.80 to 1.28]) components. For the primary CVD outcome, participants with low fish consumption at baseline benefited (0.79 [0.65-0.96]) more than those with high consumption (1.05 [0.85-1.30]). These results are consistent with, but slightly stronger than, those without outcome prioritization.

Risk stratification of sudden cardiac death: a review.

Sudden cardiac death (SCD) is responsible for several millions of deaths every year and remains a major health problem. To reduce this burden, diagnosing and identification of high-risk individuals and disease-specific risk stratification are essential. Treatment strategies include treatment of the underlying disease with lifestyle advice and drugs and decisions to implant a primary prevention implantable cardioverter-defibrillator (ICD) and perform ablation of the ventricles and novel treatment modalities such as left cardiac sympathetic denervation in rare specific primary electric diseases such as long QT syndrome and catecholaminergic polymorphic ventricular tachycardia. This review summarizes the current knowledge on SCD risk according to underlying heart disease and discusses the future of SCD prevention.

Risk of Arrhythmic Death in Patients With Nonischemic Cardiomyopathy: JACC Review Topic of the Week.

Nonischemic cardiomyopathy (NICM) is common and patients are at significant risk for early mortality secondary to ventricular arrhythmias. Current guidelines recommend implantable cardioverter-defibrillator (ICD) therapy to decrease sudden cardiac death (SCD) in patients with heart failure and reduced left ventricular ejection fraction. However, in randomized clinical trials comprised solely of patients with NICM, primary prevention ICDs did not confer significant mortality benefit. Moreover, left ventricular ejection fraction has limited sensitivity and specificity for predicting SCD. Therefore, precise risk stratification algorithms are needed to define those at the highest risk of SCD. This review examines mechanisms of sudden arrhythmic death in patients with NICM, discusses the role of ICD therapy and treatment of heart failure for prevention of SCD in patients with NICM, examines the role of cardiac magnetic resonance imaging and computational modeling for SCD risk stratification, and proposes new strategies to guide future clinical trials on SCD risk assessment in patients with NICM.

The Lancet Commission to reduce the global burden of sudden cardiac death: a call for multidisciplinary action.

Despite major advancements in cardiovascular medicine, sudden cardiac death (SCD) continues to be an enormous medical and societal challenge, claiming millions of lives every year. Efforts to prevent SCD are hampered by imperfect risk prediction and inadequate solutions to specifically address arrhythmogenesis. Although resuscitation strategies have witnessed substantial evolution, there is a need to strengthen the organisation of community interventions and emergency medical systems across varied locations and health-care structures. With all the technological and medical advances of the 21st century, the fact that survival from sudden cardiac arrest (SCA) remains lower than 10% in most parts of the world is unacceptable. Recognising this urgent need, the Lancet Commission on SCD was constituted, bringing together 30 international experts in varied disciplines. Consistent progress in tackling SCD will require a completely revamped approach to SCD prevention, with wide-sweeping policy changes that will empower the development of both governmental and community-based programmes to maximise survival from SCA, and to comprehensively attend to survivors and decedents' families after the event. International collaborative efforts that maximally leverage and connect the expertise of various research organisations will need to be prioritised to properly address identified gaps. The Commission places substantial emphasis on the need to develop a multidisciplinary strategy that encompasses all aspects of SCD prevention and treatment. The Commission provides a critical assessment of the current scientific efforts in the field, and puts forth key recommendations to challenge, activate, and intensify efforts by both the scientific and global community with new directions, research, and innovation to reduce the burden of SCD worldwide.

Omega-3 Fatty Acid Biomarkers and Incident Atrial Fibrillation.

BACKGROUND: The relationship between omega-3 fatty acids and atrial fibrillation (AF) remains controversial. OBJECTIVES: This study aimed to determine the prospective associations of blood or adipose tissue levels of eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with incident AF. METHODS: We used participant-level data from a global consortium of 17 prospective cohort studies, each with baseline data on blood or adipose tissue omega-3 fatty acid levels and AF outcomes. Each participating study conducted a de novo analyses using a prespecified analytical plan with harmonized definitions for exposures, outcome, covariates, and subgroups. Associations were pooled using inverse-variance weighted meta-analysis. RESULTS: Among 54,799 participants from 17 cohorts, 7,720 incident cases of AF were ascertained after a median 13.3 years of follow-up. In multivariable analysis, EPA levels were not associated with incident AF, HR per interquintile range (ie, the difference between the 90th and 10th percentiles) was 1.00 (95% CI: 0.95-1.05). HRs for higher levels of DPA, DHA, and EPA+DHA, were 0.89 (95% CI: 0.83-0.95), 0.90 (95% CI: 0.85-0.96), and 0.93 (95% CI: 0.87-0.99), respectively. CONCLUSIONS: In vivo levels of omega-3 fatty acids including EPA, DPA, DHA, and EPA+DHA were not associated with increased risk of incident AF. Our data suggest the safety of habitual dietary intakes of omega-3 fatty acids with respect to AF risk. Coupled with the known benefits of these fatty acids in the prevention of adverse coronary events, our study suggests that current dietary guidelines recommending fish/omega-3 fatty acid consumption can be maintained.

A randomized clinical trial of omega-3 fatty acid and vitamin D supplementation on electrocardiographic risk profiles.

Beneficial and adverse associations with arrhythmias have been reported for omega-3 fatty acids (omega-3 FA) and Vitamin D. The 12 lead electrocardiogram (ECG) contains quantitative measures reflecting diverse aspects of electrophysiology that might provide insights into mechanisms underlying these associations. In a pre-specified ancillary study of the VITaminD and omegA-3 (VITAL) trial, we examined the effect of 1 g of marine omega-3 FA per day, comprised of 460 mg eicosapentanoic acid and 380 mg of docosahexaenoic acid, and 2000 IU VitaminD3 per day on ECG characteristics associated with atrial and ventricular arrhythmias among individuals age 50 years or greater. A total of 911 study participants underwent ECGs at baseline and again at 2 years after the randomization. Individuals randomized to active omega-3 FA demonstrated significant net increase in PR-interval duration (p = 0.005) and P-wave duration (p = 0.03) as well significant net decrease in P-wave amplitude (p = 0.037) as compared to placebo. RMSSD increased to a greater extent in the omega-3 FA arm compared to placebo (p = 0.040). For Vitamin D3, the Cornell voltage increased to a lesser extent in the participants assigned to active treatment as compared to placebo (p = 0.044). There were no other significant differences in QRS, QTc, Cornell voltage or heart rate. Thus, randomized treatment with omega-3 FA supplements resulted in changes on the ECG that are potentially reflective of heightened vagal tone and/or slowing of intraatrial and AV conduction. Vitamin D3 supplementation resulted in modest reductions in progressive LV voltage suggestive of a potential antihypertrophic effect.Trial registration ClinicalTrials.gov Identifiers: NCT01169259, NCT02178410 (06/26/2010 and 06/30/2014).

[Practicing bad news]. / S'entraîner à l'annonce de mauvaises nouvelles.

Simulation has been in full expansion in France for the last ten years. In many teams, the use of procedural or high-tech simulation has been a new pedagogical means of training teams to manage emergency situations in different contexts. But simulation is also useful in other situations such as bad news.

Deep learning-enabled analysis of medical images identifies cardiac sphericity as an early marker of cardiomyopathy and related outcomes.

BACKGROUND: Quantification of chamber size and systolic function is a fundamental component of cardiac imaging. However, the human heart is a complex structure with significant uncharacterized phenotypic variation beyond traditional metrics of size and function. Examining variation in cardiac shape can add to our ability to understand cardiovascular risk and pathophysiology. METHODS: We measured the left ventricle (LV) sphericity index (short axis length/long axis length) using deep learning-enabled image segmentation of cardiac magnetic resonance imaging data from the UK Biobank. Subjects with abnormal LV size or systolic function were excluded. The relationship between LV sphericity and cardiomyopathy was assessed using Cox analyses, genome-wide association studies, and two-sample Mendelian randomization. FINDINGS: In a cohort of 38,897 subjects, we show that a one standard deviation increase in sphericity index is associated with a 47% increased incidence of cardiomyopathy (hazard ratio [HR]: 1.47, 95% confidence interval [CI]: 1.10-1.98, p = 0.01) and a 20% increased incidence of atrial fibrillation (HR: 1.20, 95% CI: 1.11-1.28, p < 0.001), independent of clinical factors and traditional magnetic resonance imaging (MRI) measurements. We identify four loci associated with sphericity at genome-wide significance, and Mendelian randomization supports non-ischemic cardiomyopathy as causal for LV sphericity. CONCLUSIONS: Variation in LV sphericity in otherwise normal hearts predicts risk for cardiomyopathy and related outcomes and is caused by non-ischemic cardiomyopathy. FUNDING: This study was supported by grants K99-HL157421 (D.O.) and KL2TR003143 (S.L.C.) from the National Institutes of Health.

High-Throughput Assessment of Real-World Medication Effects on QT Interval Prolongation: Observational Study.

BACKGROUND: Drug-induced prolongation of the corrected QT interval (QTc) increases the risk for Torsades de Pointes (TdP) and sudden cardiac death. Medication effects on the QTc have been studied in controlled settings but may not be well evaluated in real-world settings where medication effects may be modulated by patient demographics and comorbidities as well as the usage of other concomitant medications. OBJECTIVE: We demonstrate a new, high-throughput method leveraging electronic health records (EHRs) and the Surescripts pharmacy database to monitor real-world QTc-prolonging medication and potential interacting effects from demographics and comorbidities. METHODS: We included all outpatient electrocardiograms (ECGs) from September 2008 to December 2019 at a large academic medical system, which were in sinus rhythm with a heart rate of 40-100 beats per minute, QRS duration of <120 milliseconds, and QTc of 300-700 milliseconds, determined using the Bazett formula. We used prescription information from the Surescripts pharmacy database and EHR medication lists to classify whether a patient was on a medication during an ECG. Negative control ECGs were obtained from patients not currently on the medication but who had been or would be on that medication within 1 year. We calculated the difference in mean QTc between ECGs of patients who are on and those who are off a medication and made comparisons to known medication TdP risks per the CredibleMeds.org database. Using linear regression analysis, we studied the interaction of patient-level demographics or comorbidities on medication-related QTc prolongation. RESULTS: We analyzed the effects of 272 medications on 310,335 ECGs from 159,397 individuals. Medications associated with the greatest QTc prolongation were dofetilide (mean QTc difference 21.52, 95% CI 10.58-32.70 milliseconds), mexiletine (mean QTc difference 18.56, 95% CI 7.70-29.27 milliseconds), amiodarone (mean QTc difference 14.96, 95% CI 13.52-16.33 milliseconds), rifaximin (mean QTc difference 14.50, 95% CI 12.12-17.13 milliseconds), and sotalol (mean QTc difference 10.73, 95% CI 7.09-14.37 milliseconds). Several top QT prolonging medications such as rifaximin, lactulose, cinacalcet, and lenalidomide were not previously known but have plausible mechanistic explanations. Significant interactions were observed between demographics or comorbidities and QTc prolongation with many medications, such as coronary disease and amiodarone. CONCLUSIONS: We demonstrate a new, high-throughput technique for monitoring real-world effects of QTc-prolonging medications from readily accessible clinical data. Using this approach, we confirmed known medications for QTc prolongation and identified potential new associations and demographic or comorbidity interactions that could supplement findings in curated databases. Our single-center results would benefit from additional verification in future multisite studies that incorporate larger numbers of patients and ECGs along with more precise medication adherence and comorbidity data.

Epidemiology and modifiable risk factors for atrial fibrillation.

The global prevalence of atrial fibrillation (AF) has increased substantially over the past three decades and is currently approximately 60 million cases. Incident AF and its clinical consequences are largely the result of risk factors that can be modified by lifestyle changes. In this Review, we provide evidence that the lifetime risk of AF is modified not only by sex and race but also through the clinical risk factor and comorbidity burden of individual patients. We begin by summarizing the epidemiology of AF, focusing on non-modifiable and modifiable risk factors, as well as targets and strategies for the primary prevention of AF. Furthermore, we evaluate the role of modifiable risk factors in the secondary prevention of AF as well as the potential effects of risk factor interventions on the frequency and severity of subsequent AF episodes. We end the Review by proposing strategies that require evaluation as well as global policy changes that are needed for the prevention of incident AF and the management of recurrent episodes in patients already affected by AF.