Classification of Free-Living Body Posture with ECG Patch Accelerometers: Application to the Multicenter AIDS Cohort Study.

Purpose: As health studies increasingly monitor free-living heart performance via ECG patches with accelerometers, researchers will seek to investigate cardio-electrical responses to physical activity and sedentary behavior, increasing demand for fast, scalable methods to process accelerometer data. We extend a posture classification algorithm for accelerometers in ECG patches when researchers do not have ground-truth labels or other reference measurements (i.e., upright measurement). Methods: Men living with and without HIV in the Multicenter AIDS Cohort study wore the Zio XT® for up to two weeks (n = 1,250). Our novel extensions for posture classification include (1) estimation of an upright posture for each individual without a reference upright measurement; (2) correction of the upright estimate for device removal and re-positioning using novel spherical change-point detection; and (3) classification of upright and recumbent periods using a clustering and voting process rather than a simple inclination threshold used in other algorithms. As no posture labels exist in the free-living environment, we perform numerous sensitivity analyses and evaluate the algorithm against labelled data from the Towson Accelerometer Study, where participants wore accelerometers at the waist. Results: On average, 87.1% of participants were recumbent at 4am and 15.5% were recumbent at 1pm. Participants were recumbent 54 minutes longer on weekends compared to weekdays. Performance was good in comparison to labelled data in a separate, controlled setting (accuracy = 96.0%, sensitivity = 97.5%, specificity = 95.9%). Conclusions: Posture may be classified in the free-living environment from accelerometers in ECG patches even without measuring a standard upright position. Furthermore, algorithms that fail to account for individuals who rotate and re-attach the accelerometer may fail in the free-living environment.

Complementing the United States Household Food Security Survey Module with Items Reflecting Social Unacceptability.

BACKGROUND: Social unacceptability of food access is part of the lived experience of food insecurity but is not assessed as part of the United States Household Food Security Survey Module (HFSSM). OBJECTIVES: The objectives were as follows: 1) to determine the psychometric properties of 2 additional items on social unacceptability in relation to the HFSSM items and 2) to test whether these 2 items provided added predictive accuracy to that of the HFSSM items for mental health outcomes. METHODS: Cross-sectional data used were from the Intersection of Material-Need Insecurities and HIV and Cardiovascular Health substudy of the Multicenter AIDS Cohort Study/Women's Interagency HIV Study Combined Cohort Study. Data on the 10-item HFSSM and 2 new items reflecting social unacceptability were collected between Fall 2020 and Fall 2021 from 1342 participants from 10 United States cities. The 2 social unacceptability items were examined psychometrically in relation to the HFSSM-10 items using models from item response theory. Linear and logistic regression was used to examine prediction of mental health measured by the 20-item Center for Epidemiologic Studies Depression scale and the 10-item Perceived Stress Scale. RESULTS: The social unacceptability items were affirmed throughout the range of severity of food insecurity but with increasing frequency at higher severity of food insecurity. From item response theory models, the subconstructs reflected in the HFSSM-10 and the subconstruct of social unacceptability were distinct, not falling into one dimension. Regression models confirmed that social unacceptability was distinct from the subconstructs reflected in the HFSSM-10. The social unacceptability items as a separate scale explained more (∼1%) variation in mental health than when combined with the HFSSM-10 items in a single scale, and the social unacceptability subconstruct explained more (∼1%) variation in mental health not explained by the HFSSM-10. CONCLUSIONS: Two social unacceptability items used as a separate scale along with the HFSSM-10 predicted mental health more accurately than did the HFSSM-10 alone.

Proteomic Signature of HIV-Associated Subclinical Left Atrial Remodeling and Incident Heart Failure.

Background: People living with HIV (PLWH) are at higher risk of heart failure (HF) and preceding subclinical cardiac abnormalities, including left atrial dilation, compared to people without HIV (PWOH). Hypothesized mechanisms include premature aging linked to chronic immune activation. We leveraged plasma proteomics to identify potential novel contributors to HIV-associated differences in indexed left atrial volume (LAVi) among PLWH and PWOH and externally validated identified proteomic signatures with incident HF among a cohort of older PWOH. Methods: We performed proteomics (Olink Explore 3072) on plasma obtained concurrently with cardiac magnetic resonance imaging among PLWH and PWOH in the United States. Proteins were analyzed individually and as agnostically defined clusters. Cross-sectional associations with HIV and LAVi were estimated using multivariable regression with robust variance. Among an independent general population cohort, we estimated associations between identified signatures and LAVi using linear regression and incident HF using Cox regression. Results: Among 352 participants (age 55±6 years; 25% female), 61% were PLWH (88% on ART; 73% with undetectable HIV RNA) and mean LAVi was 29±9 mL/m 2 . Of 2594 analyzed proteins, 439 were associated with HIV serostatus, independent of demographics, hepatitis C virus infection, renal function, and substance use (FDR<0.05). We identified 73 of these proteins as candidate contributors to the independent association between positive HIV serostatus and higher LAVi, enriched in tumor necrosis factor (TNF) signaling and immune checkpoint proteins regulating T cell, B cell, and NK cell activation. We identified one protein cluster associated with LAVi and HIV regardless of HIV viral suppression status, which comprised 42 proteins enriched in TNF signaling, ephrin signaling, and extracellular matrix (ECM) organization. This protein cluster and 30 of 73 individual proteins were associated with incident HF among 2273 older PWOH (age 68±9 years; 52% female; 8.5±1.4 years of follow-up). Conclusion: Proteomic signatures that may contribute to HIV-associated LA remodeling were enriched in immune checkpoint proteins, cytokine signaling, and ECM organization. These signatures were also associated with incident HF among older PWOH, suggesting specific markers of chronic immune activation, systemic inflammation, and fibrosis may identify shared pathways in HIV and aging that contribute to risk of HF.

Identification of high-risk imaging features in hypertrophic cardiomyopathy using electrocardiography: A deep-learning approach.

BACKGROUND: Patients with hypertrophic cardiomyopathy (HCM) are at risk of sudden death, and individuals with ≥1 major risk markers are considered for primary prevention implantable cardioverter-defibrillators. Guidelines recommend cardiac magnetic resonance (CMR) imaging to identify high-risk imaging features. However, CMR imaging is resource intensive and is not widely accessible worldwide. OBJECTIVE: The purpose of this study was to develop electrocardiogram (ECG) deep-learning (DL) models for the identification of patients with HCM and high-risk imaging features. METHODS: Patients with HCM evaluated at Tufts Medical Center (N = 1930; Boston, MA) were used to develop ECG-DL models for the prediction of high-risk imaging features: systolic dysfunction, massive hypertrophy (≥30 mm), apical aneurysm, and extensive late gadolinium enhancement. ECG-DL models were externally validated in a cohort of patients with HCM from the Amrita Hospital HCM Center (N = 233; Kochi, India). RESULTS: ECG-DL models reliably identified high-risk features (systolic dysfunction, massive hypertrophy, apical aneurysm, and extensive late gadolinium enhancement) during holdout testing (c-statistic 0.72, 0.83, 0.93, and 0.76) and external validation (c-statistic 0.71, 0.76, 0.91, and 0.68). A hypothetical screening strategy using echocardiography combined with ECG-DL-guided selective CMR use demonstrated a sensitivity of 97% for identifying patients with high-risk features while reducing the number of recommended CMRs by 61%. The negative predictive value with this screening strategy for the absence of high-risk features in patients without ECG-DL recommendation for CMR was 99.5%. CONCLUSION: In HCM, novel ECG-DL models reliably identified patients with high-risk imaging features while offering the potential to reduce CMR testing requirements in underresourced areas.

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.

Association of epicardial and intramyocardial fat with ventricular arrhythmias.

BACKGROUND: Among patients with ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM), myocardial fibrosis is associated with an increased risk for ventricular arrhythmia (VA). Growing evidence suggests that myocardial fat contributes to ventricular arrhythmogenesis. However, little is known about the volume and distribution of epicardial adipose tissue and intramyocardial fat and their relationship with VAs. OBJECTIVE: The purpose of this study was to assess the association of contrast-enhanced computed tomography (CE-CT)-derived left ventricular (LV) tissue heterogeneity, epicardial adipose tissue volume, and intramyocardial fat volume with the risk of VA in ICM and NICM patients. METHODS: Patients enrolled in the PROSE-ICD registry who underwent CE-CT were included. Intramyocardial fat volume (voxels between -180 and -5 Hounsfield units [HU]), epicardial adipose tissue volume (between -200 and -50 HU), and LV tissue heterogeneity were calculated. The primary endpoint was appropriate ICD shocks or sudden arrhythmic death. RESULTS: Among 98 patients (47 ICM, 51 NICM), LV tissue heterogeneity was associated with VA (odds ratio [OR] 1.10; P = .01), particularly in the ICM cohort. In the NICM subgroup, epicardial adipose tissue and intramyocardial fat volume were associated with VA (OR 1.11, P = .01; and OR = 1.21, P = .01, respectively) but not in the ICM patients (OR 0.92, P =.22; and OR = 0.96, P =.19, respectively). CONCLUSION: In ICM patients, increased fat distribution heterogeneity is associated with VA. In NICM patients, an increased volume of intramyocardial fat and epicardial adipose tissue is associated with a higher risk for VA. Our findings suggest that fat's contribution to VAs depends on the underlying substrate.

Growth Differentiation Factor-15 Predicts Mortality and Heart Failure Exacerbation But Not Ventricular Arrhythmias in Patients With Cardiomyopathy.

Background Heart failure (HF) has been increasing in prevalence, and a need exists for biomarkers with improved predictive and prognostic ability. GDF-15 (growth differentiation factor-15) is a novel biomarker associated with HF mortality, but no serial studies of GDF-15 have been conducted. This study aimed to investigate the association between GDF-15 levels over time and the occurrence of ventricular arrhythmias, HF hospitalizations, and all-cause mortality. Methods and Results We used a retrospective case-control design to analyze 148 patients with ischemic and nonischemic cardiomyopathies and primary prevention implantable cardioverter-defibrillator (ICD) from the PROSe-ICD (Prospective Observational Study of the ICD in Sudden Cardiac Death Prevention) cohort. Patients had blood drawn every 6 months and after each appropriate ICD therapy and were followed for a median follow-up of 4.6 years, between 2005 to 2019. We compared serum GDF-15 levels within ±90 days of an event among those with a ventricular tachycardia/fibrillation event requiring ICD therapies and those hospitalized for decompensated HF. A comparator/control group comprised patients with GDF-15 levels available during 2-year follow-up periods without events. Median follow-up was 4.6 years in the 148 patients studied (mean age 58±12, 27% women). The HF cohort had greater median GDF-15 values within 90 days (1797 pg/mL) and 30 days (2039 pg/mL) compared with the control group (1062 pg/mL, both P<0.0001). No difference was found between the ventricular tachycardia/fibrillation subgroup within 90 days (1173 pg/mL, P=0.60) or 30 days (1173 pg/mL, P=0.78) and the control group. GDF-15 was also significantly predictive of mortality (hazard ratio, 3.17 [95% CI, 2.33-4.30]). Conclusions GDF-15 levels are associated with HF hospitalization and mortality but not ventricular arrhythmic events.

Association Between Left Ventricular Scar and Ventricular Ectopy in People Living With and Without HIV.

BACKGROUND: People living with HIV (PLWH) have greater risk for arrhythmic sudden death and heart failure than people without HIV (PWOH), though risk identifiers remain understudied. Higher ventricular ectopy (VE) burden reflects increased arrhythmic susceptibility and cardiomyopathy risk. OBJECTIVES: The purpose of this study was to test if myocardial scar measured by late gadolinium-enhancement cardiovascular magnetic resonance (LGE-CMR) associates with VE by ambulatory electrocardiographic monitoring among PLWH and PWOH with risk factors for HIV, and if the association differs by HIV. METHODS: Participants from 3 cohorts of PLWH and PWOH underwent electrocardiographic monitoring (median wear time 8.3 days) and CMR. Using multivariable regression, we assessed: 1) associations between scar metrics and VE, adjusting for demographics, HIV serostatus, substance use, cardiovascular risk factors, and left ventricular (LV) function/structure; and 2) effect measure modification by HIV. RESULTS: Of 329 participants (median age 55 years, 30% women, 62% PLWH), 109 had LGE (62% PLWH). Ischemic or major nonischemic pattern LGE was associated with high VE burden (adjusted OR: 2.32, P = 0.004) and more PVCs/day (141% higher, P < 0.001). Among people with LGE, greater scar mass correlated with more PVCs/day (P = 0.028). Associations persisted after adjustment for LV function/structure and when excluding PLWH with HIV viremia and showed no effect measure modification by HIV. CONCLUSIONS: Ischemic or major nonischemic pattern LGE and greater scar mass correlated with higher VE burden, independently of LV structure/function, HIV serostatus, and HIV viremia. The findings highlight specific scar characteristics common to PLWH and PWOH with risk factors for HIV that may portend higher risk for arrhythmias and heart failure.

Clinical Applications, Methodology, and Scientific Reporting of Electrocardiogram Deep-Learning Models: A Systematic Review.

BACKGROUND: The electrocardiogram (ECG) is one of the most common diagnostic tools available to assess cardio-vascular health. The advent of advanced computational techniques such as deep learning has dramatically expanded the breadth of clinical problems that can be addressed using ECG data, leading to increasing popularity of ECG deep-learning models aimed at predicting clinical endpoints. OBJECTIVES: The purpose of this study was to define the current landscape of clinically relevant ECG deep-learning models and examine practices in the scientific reporting of these studies. METHODS: We performed a systematic review of PubMed and EMBASE databases to identify clinically relevant ECG deep-learning models published through July 1, 2022. RESULTS: We identified 44 manuscripts including 53 unique, clinically relevant ECG deep-learning models. The rate of publication of ECG deep-learning models is increasing rapidly. The most common clinical applications of ECG deep learning were identification of cardiomyopathy (14/53 [26%]), followed by arrhythmia detection (9/53 [17%]). Methodologic reporting varied; while 33/44 (75%) publications included model architecture diagrams, complete information required to reproduce these models was provided in only 10/44 (23%). Saliency analysis was performed in 20/44 (46%) of publications. Only 18/53 (34%) models were tested within external validation cohorts. Model code or resources allowing for model implementation by external groups were available for only 5/44 (11%) publications. CONCLUSIONS: While ECG deep-learning models are increasingly clinically relevant, their reporting is highly variable, and few publications provide sufficient detail for methodologic reproduction or model validation by external groups. The field of ECG deep learning would benefit from adherence to a set of standardized scientific reporting guidelines.

Temporal trends of arrhythmias at delivery hospitalizations in the United States: Analysis from the National Inpatient Sample, 2009-2019.

Background: Cardiac arrhythmias are associated with increased maternal morbidity. There are limited data on trends of arrhythmias among women hospitalized for delivery. Materials and methods: We used the National Inpatient Sample (NIS) database to identify delivery hospitalizations for individuals aged 18-49 years between 2009 to 2019 and utilized coding data from the 9th and 10th editions of the International Classification of Diseases to identify supraventricular tachycardias (SVT), atrial fibrillation (AF), atrial flutter, ventricular tachycardia (VT), and ventricular fibrillation (VF). Arrhythmia trends were analyzed by age, race-ethnicity, hospital setting, and hospital geographic regions. Multivariable logistic regression was used to evaluate the association of demographic, clinical, and socioeconomic characteristics with arrhythmias. Results: Among 41,576,442 delivery hospitalizations, the most common arrhythmia was SVT (53%), followed by AF (31%) and VT (13%). The prevalence of arrhythmia among delivery hospitalizations increased between 2009 and 2019. Age > 35 years and Black race were associated with a higher arrhythmia burden. Factors associated with an increased risk of arrhythmias included valvular disease (OR: 12.77; 95% C1:1.98-13.61), heart failure (OR:7.13; 95% CI: 6.49-7.83), prior myocardial infarction (OR: 5.41, 95% CI: 4.01-7.30), peripheral vascular disease (OR: 3.19, 95% CI: 2.51-4.06), hypertension (OR: 2.18; 95% CI: 2.07-2.28), and obesity (OR 1.69; 95% CI: 1.63-1.76). Delivery hospitalizations complicated by arrhythmias compared with those with no arrhythmias had a higher proportion of all-cause in-hospital mortality (0.95% vs. 0.01%), cardiogenic shock (0.48% vs. 0.00%), preeclampsia (6.96% vs. 3.58%), and preterm labor (2.95% vs. 2.41%) (all p < 0.0001). Conclusion: Pregnant individuals with age > 35 years, obesity, hypertension, valvular heart disease, or severe pulmonary disease are more likely to have an arrhythmia history or an arrhythmia during a delivery hospitalization. Delivery hospitalizations with a history of arrhythmia are more likely to be complicated by all-cause in-hospital mortality, cardiovascular, and adverse pregnancy outcomes (APOs). These data highlight the increased risk associated with pregnancies among individuals with arrhythmias.

Association of HIV infection with clinical features and outcomes of patients with aortic aneurysms.

Data on the characteristics and outcomes of hospitalized patients with aortic aneurysms (AA) and HIV remain scarce. This is a cohort study of hospitalized adult patients with a diagnosis of AA from 2013 to 2019 using the US National Inpatient Readmission Database. Patients with a diagnosis of HIV were identified. Our outcomes included trends in hospitalizations and comparison of clinical characteristics, complications, and mortality in patients with AA and HIV compared to those without HIV. Among 1,905,837 hospitalized patients with AA, 4416 (0.23%) were living with HIV. There was an overall age-adjusted increase in the rate of HIV among patients hospitalized with AA over the years (14-29 per 10,000 person-years; age-adjusted p-trend < 0.001). Patients with AA and HIV were younger than those without HIV (median age: 60 vs 76 years, p < 0.001) and were less likely to have a history of smoking, hypertension, dyslipidemia, diabetes mellitus, and obesity. Thoracic aortic aneurysms were more prevalent in those with HIV (37.5% vs 26.7%, p < 0.001). On multivariable logistic regression, HIV was not associated with increased risk of aortic rupture (OR: 0.79; 95% CI: 0.61-1.01, p = 0.06), acute aortic dissection (OR: 0.73; 95% CI: 0.51-1.06, p = 0.3), readmissions (OR: 1.04; 95% CI: 0.95-1.13, p = 0.4), or aortic repair (OR: 0.89; 95% CI: 0.79-1.00, p = 0.05). Hospitalized patients with AA and HIV had a lower crude mortality rate compared to those without HIV (OR: 0.75 (0.63-0.91), p = 0.003). Hospitalized patients with AA and HIV likely constitute a distinct group of patients with AA; they are younger, have fewer traditional cardiovascular risk factors, and a higher rate of thoracic aorta involvement. Differences in clinical features may account for the lower mortality rate observed in patients with AA and HIV compared to those without HIV.

Longitudinal Prediction of Ventricular Arrhythmic Risk in Patients With Arrhythmogenic Right Ventricular Cardiomyopathy.

BACKGROUND: The arrhythmogenic right ventricular cardiomyopathy (ARVC) risk calculator stratifies risk for incident sustained ventricular arrhythmias (VA) at the time of ARVC diagnosis. However, included risk factors change over time, and how well the ARVC risk calculator performs at follow-up is unknown. METHODS: This was a retrospective analysis of patients with definite ARVC and without prior sustained VA. Risk factors for VA including age, nonsustained ventricular tachycardia, premature ventricular complex burden, T-wave inversions on electrocardiogram, cardiac syncope, right ventricular function, therapeutic medication use, and exercise intensity were assessed at the time of 2010 Task Force Criteria based ARVC diagnosis and upon repeat evaluations. Changes in these risk factors were analyzed over 5-year follow-up. The 5-year risk of VA was predicted longitudinally using (1) the baseline ARVC risk calculator prediction, (2) the ARVC risk prediction calculated using updated risk factors, and (3) time-varying Cox regression. Discrimination and calibration were assessed in comparison to observed VA event rates. RESULTS: Four hundred eight patients with ARVC experiencing 132 primary VA events were included. Matched comparison of risk factors at baseline versus at 5 years of follow-up revealed decreased burdens of premature ventricular complexes (-1200/day) and nonsustained ventricular tachycardia (-14%). Presence of significant right ventricular dysfunction and number of T-wave inversions on electrocardiogram were unchanged. Observed risk for VA decreased by 13% by 5 years follow-up. The baseline ARVC risk calculator's ability to predict 5-year VA risk worsened during follow-up (C statistics, 0.83 at diagnosis versus 0.68 at 5 years). Both the updated ARVC risk calculator (C statistics of 0.77) and time-varying Cox regression model (C statistics, 0.77) had strong discrimination. The updated ARVC risk calculator overestimated 5-year VA risk by an average of +6%. CONCLUSIONS: Risk factors for VA in ARVC are dynamic, and overall risk for incident sustained VA decreases during follow-up. Up-to-date risk factor assessment improves VA risk stratification.

Circulating biomarker correlates of left atrial size and myocardial extracellular volume fraction among persons living with and without HIV.

BACKGROUND: Infection with human immunodeficiency virus (HIV) is associated with higher risk for myocardial disease despite modern combination antiretroviral therapy (cART). Factors contributing to this excess risk, however, remain poorly characterized. We aimed to assess cross-sectional relationships between elevations of left atrial volume index (LAVI) and myocardial extracellular volume (ECV) fraction that have been reported in persons living with HIV and levels of circulating biomarkers of inflammation, fibrosis, and myocyte stretch among persons living with and without HIV (PLWH, PLWOH). METHODS: Participants from three cohorts of PLWH and PLWOH underwent cardiovascular magnetic resonance imaging for measurement of LAVI and ECV. Levels of circulating proteins (IL-6, sCD14, galectin-3, NT-proBNP, GDF-15, TIMP-2, MMP-2, and hsTnI) were measured using immunoassays. Associations were assessed using logistic and linear regression, adjusting for demographics, substance use, and clinical characteristics. RESULTS: Among 381 participants with and without HIV, median age (IQR) was 55.1 (51.2, 58.4) years, 28% were female, 69% were Black, and 46% were current smokers. Sixty-two percent were PLWH (n = 235), of whom 88% were receiving cART and 72% were virally suppressed. PLWH had higher levels of sCD14 (p = < 0.001), GDF-15 (p = < 0.001), and NT-proBNP (p = 0.03) compared to PLWOH, while levels of other biomarkers did not differ by HIV serostatus, including IL-6 (p = 0.84). Among PLWH, higher sCD14, GDF-15, and NT-proBNP were also associated with lower CD4 + cell count, and higher NT-proBNP was associated with detectable HIV viral load. NT-proBNP was associated with elevated LAVI (OR: 1.79 [95% CI: 1.31, 2.44]; p < 0.001) with no evidence of effect measure modification by HIV serostatus. Other associations between HIV-associated biomarkers and LAVI or ECV were small or imprecise. CONCLUSIONS: Our findings suggest that elevated levels of sCD14, GDF-15, and NT-proBNP among PLWH compared to PLWOH observed in the current cART era may only minimally reflect HIV-associated elevations in LAVI and ECV. Future studies of excess risk of myocardial disease among contemporary cohorts of PLWH should investigate mechanisms other than those connoted by the studied biomarkers.

Advanced imaging for risk stratification for ventricular arrhythmias and sudden cardiac death.

Sudden cardiac death (SCD) is a leading cause of mortality, comprising approximately half of all deaths from cardiovascular disease. In the US, the majority of SCD (85%) occurs in patients with ischemic cardiomyopathy (ICM) and a subset in patients with non-ischemic cardiomyopathy (NICM), who tend to be younger and whose risk of mortality is less clearly delineated than in ischemic cardiomyopathies. The conventional means of SCD risk stratification has been the determination of the ejection fraction (EF), typically via echocardiography, which is currently a means of determining candidacy for primary prevention in the form of implantable cardiac defibrillators (ICDs). Advanced cardiac imaging methods such as cardiac magnetic resonance imaging (CMR), single-photon emission computerized tomography (SPECT) and positron emission tomography (PET), and computed tomography (CT) have emerged as promising and non-invasive means of risk stratification for sudden death through their characterization of the underlying myocardial substrate that predisposes to SCD. Late gadolinium enhancement (LGE) on CMR detects myocardial scar, which can inform ICD decision-making. Overall scar burden, region-specific scar burden, and scar heterogeneity have all been studied in risk stratification. PET and SPECT are nuclear methods that determine myocardial viability and innervation, as well as inflammation. CT can be used for assessment of myocardial fat and its association with reentrant circuits. Emerging methodologies include the development of "virtual hearts" using complex electrophysiologic modeling derived from CMR to attempt to predict arrhythmic susceptibility. Recent developments have paired novel machine learning (ML) algorithms with established imaging techniques to improve predictive performance. The use of advanced imaging to augment risk stratification for sudden death is increasingly well-established and may soon have an expanded role in clinical decision-making. ML could help shift this paradigm further by advancing variable discovery and data analysis.

Prevention of heart failure, tachyarrhythmias and sudden cardiac death in HIV.

PURPOSE OF REVIEW: To summarize the state-of-the-art literature on the epidemiology, disease progression, and mediators of heart failure, tachyarrhythmias, and sudden cardiac death in people living with HIV (PLWH) to inform prevention strategies. RECENT FINDINGS: Recent studies corroborate the role of HIV as a risk enhancer for heart failure and arrhythmias, which persists despite adjustment for cardiovascular risk factors and unhealthy behaviors. Immune activation and inflammation contribute to the risk. Heart failure occurs more frequently at younger ages, and among women and ethnic minorities living with HIV, highlighting disparities. Prospective outcome studies remain sparse in PLWH limiting prevention approaches. However, subclinical cardiac and electrophysiologic remodeling and dysfunction detected by noninvasive testing are powerful disease surrogates that inform our mechanistic understanding of HIV-associated cardiovascular disease and offer opportunities for early diagnosis. SUMMARY: Aggressive control of HIV viremia and cardiac risk factors and abstinence from unhealthy behaviors remain treatment pillars to prevent heart failure and arrhythmic complications. The excess risk among PLWH warrants heightened vigilance for heart failure and arrhythmic symptomatology and earlier testing as subclinical abnormalities are common. Future research needs include identifying novel therapeutic targets to prevent heart failure and arrhythmias and testing of interventions in diverse groups of PLWH.

Patterns of objectively measured physical activity differ between men living with and without HIV.

OBJECTIVE: To use accelerometers to quantify differences in physical activity (PA) by HIV serostatus and HIV viral load (VL) in the Multicenter AIDS Cohort Study (MACS). METHODS: MACS participants living with (PLWH, n = 631) and without (PWOH, n = 578) HIV wore an ambulatory electrocardiogram monitor containing an accelerometer for 1-14 days. PA was summarized as cumulative mean absolute deviation (MAD) during the 10 most active consecutive hours (M10), cumulative MAD during the six least active consecutive hours (L6), and daily time recumbent (DTR). PA summaries were compared by HIV serostatus and by detectability of VL (>20 vs. ≤20 copies/ml) using linear mixed models adjusted for sociodemographics, weight, height, substance use, physical function, and clinical factors. RESULTS: In sociodemographic-adjusted models, PLWH with a detectable VL had higher L6 (ß = 0.58 mg, P = 0.027) and spent more time recumbent (ß = 53 min/day, P = 0.003) than PWOH. PLWH had lower M10 than PWOH (undetectable VL ß = -1.62 mg, P = 0.027; detectable VL ß = -1.93 mg, P = 0.12). A joint test indicated differences in average PA measurements by HIV serostatus and VL (P = 0.001). However, differences by HIV serostatus in M10 and DTR were attenuated and no longer significant after adjustment for renal function, serum lipids, and depressive symptoms. CONCLUSIONS: Physical activity measures differed significantly by HIV serostatus and VL. Higher L6 among PLWH with detectable VL may indicate reduced amount or quality of sleep compared to PLWH without detectable VL and PWOH. Lower M10 among PLWH indicates lower amounts of physical activity compared to PWOH.

The Association of Clustered Ventricular Arrhythmia and Cycle Length With Scar Burden in Cardiomyopathy.

BACKGROUND: Patients with ≥2 ventricular arrhythmia (VA) events within 3 months (clustered VA) have increased risk for mortality. OBJECTIVES: The aim of this study was to examine the association of risk factors including scar characteristics on cardiovascular magnetic resonance imaging with clustered VA and VA cycle length in nonischemic cardiomyopathy (NICM) and ischemic cardiomyopathy (ICM). METHODS: Data from 329 primary prevention implantable cardioverter-defibrillator recipients (mean age 57 years, 26% women) were analyzed from the Left Ventricular Structural Predictors of Sudden Cardiac Death study. RESULTS: Twenty-one patients developed clustered VA (median time 2.7 years after implantable cardioverter-defibrillator placement). Men had the greatest risk for recurrent VA. Patients with NICM and scar had the highest incidence rate of clustered VA. In patients with NICM, each 1-g increase in core scar correlated with greater clustered VA risk (HR: 1.19; 95% CI: 1.07-1.32). Gray scar was similar among subgroups. Patients with NICM with clustered VA had the longest mean VA cycle length (297 ± 40 milliseconds). Higher core scar burden correlated with longer VA cycle length in patients with NICM (P = 0.002), and higher body mass index correlated with shorter VA cycle length in those with ICM (P = 0.02). Type of VA was similar between cardiomyopathy subgroups, and no scar pattern predominated. CONCLUSIONS: Clustered VA was most common in patients with NICM and scar, with greatest risk among those with larger core scar. Core scar correlated with slower VA in patients with NICM, and higher body mass index correlated with faster VA in those with ICM. Type of VA was similar by cardiomyopathy etiology, and no dominant scar pattern was associated with clustered VA.