Implantable cardioverter defibrillator use in arrhythmogenic right ventricular cardiomyopathy in North America and Europe.

BACKGROUND AND AIMS: Implantable cardioverter-defibrillators (ICDs) are critical for preventing sudden cardiac death (SCD) in arrhythmogenic right ventricular cardiomyopathy (ARVC). This study aims to identify cross-continental differences in utilization of primary prevention ICDs and survival free from sustained ventricular arrhythmia (VA) in ARVC. METHODS: This was a retrospective analysis of ARVC patients without prior VA enrolled in clinical registries from 11 countries throughout Europe and North America. Patients were classified according to whether they received treatment in North America or Europe and were further stratified by baseline predicted VA risk into low- (<10%/5 years), intermediate- (10%-25%/5 years), and high-risk (>25%/5 years) groups. Differences in ICD implantation and survival free from sustained VA events (including appropriate ICD therapy) were assessed. RESULTS: One thousand ninety-eight patients were followed for a median of 5.1 years; 554 (50.5%) received a primary prevention ICD, and 286 (26.0%) experienced a first VA event. After adjusting for baseline risk factors, North Americans were more than three times as likely to receive ICDs {hazard ratio (HR) 3.1 [95% confidence interval (CI) 2.5, 3.8]} but had only mildly increased risk for incident sustained VA [HR 1.4 (95% CI 1.1, 1.8)]. North Americans without ICDs were at higher risk for incident sustained VA [HR 2.1 (95% CI 1.3, 3.4)] than Europeans. CONCLUSIONS: North American ARVC patients were substantially more likely than Europeans to receive primary prevention ICDs across all arrhythmic risk strata. A lower rate of ICD implantation in Europe was not associated with a higher rate of VA events in those without ICDs.

Flexible Approaches Based on Multistate Models and Microsimulation to Perform Real-World Cost-Effectiveness Analyses: An Application to Proprotein Convertase Subtilisin-Kexin Type 9 Inhibitors.

OBJECTIVES: This study aims to show the application of flexible statistical methods in real-world cost-effectiveness analyses applied in the cardiovascular field, focusing specifically on the use of proprotein convertase subtilisin-kexin type 9 inhibitors for hyperlipidemia. METHODS: The proposed method allowed us to use an electronic health database to emulate a target trial for cost-effectiveness analysis using multistate modeling and microsimulation. We formally established the study design and provided precise definitions of the causal measures of interest while also outlining the assumptions necessary for accurately estimating these measures using the available data. Additionally, we thoroughly considered goodness-of-fit assessments and sensitivity analyses of the decision model, which are crucial to capture the complexity of individuals' healthcare pathway and to enhance the validity of this type of health economic models. RESULTS: In the disease model, the Markov assumption was found to be inadequate, and a "time-reset" timescale was implemented together with the use of a time-dependent variable to incorporate past hospitalization history. Furthermore, the microsimulation decision model demonstrated a satisfying goodness of fit, as evidenced by the consistent results obtained in the short-term horizon compared with a nonmodel-based approach. Notably, proprotein convertase subtilisin-kexin type 9 inhibitors revealed their favorable cost-effectiveness only in the long-term follow-up, with a minimum willingness to pay of 39 000 Euro/life years gained. CONCLUSIONS: The approach demonstrated its significant utility in several ways. Unlike nonmodel-based or alternative model-based methods, it enabled to (1) investigate long-term cost-effectiveness comprehensively, (2) use an appropriate disease model that aligns with the specific problem under study, and (3) conduct subgroup-specific cost-effectiveness analyses to gain more targeted insights.

Comparison of discrimination and calibration performance of ECG-based machine learning models for prediction of new-onset atrial fibrillation.

BACKGROUND: Machine learning (ML) methods to build prediction models starting from electrocardiogram (ECG) signals are an emerging research field. The aim of the present study is to investigate the performances of two ML approaches based on ECGs for the prediction of new-onset atrial fibrillation (AF), in terms of discrimination, calibration and sample size dependence. METHODS: We trained two models to predict new-onset AF: a convolutional neural network (CNN), that takes as input the raw ECG signals, and an eXtreme Gradient Boosting model (XGB), that uses the signal's extracted features. A penalized logistic regression model (LR) was used as a benchmark. Discrimination was evaluated with the area under the ROC curve, while calibration with the integrated calibration index. We investigated the dependence of models' performances on the sample size and on class imbalance corrections introduced with random under-sampling. RESULTS: CNN's discrimination was the most affected by the sample size, outperforming XGB and LR only around n = 10.000 observations. Calibration showed only a small dependence on the sample size for all the models considered. Balancing the training set with random undersampling did not improve discrimination in any of the models. Instead, the main effect of imbalance corrections was to worsen the models' calibration (for CNN, integrated calibration index from 0.014 [0.01, 0.018] to 0.17 [0.16, 0.19]). The sample size emerged as a fundamental point for developing the CNN model, especially in terms of discrimination (AUC = 0.75 [0.73, 0.77] when n = 10.000, AUC = 0.80 [0.79, 0.81] when n = 150.000). The effect of the sample size on the other two models was weaker. Imbalance corrections led to poorly calibrated models, for all the approaches considered, reducing the clinical utility of the models. CONCLUSIONS: Our results suggest that the choice of approach in the analysis of ECG should be based on the amount of data available, preferring more standard models for small datasets. Moreover, imbalance correction methods should be avoided when developing clinical prediction models, where calibration is crucial.

The Key Role of a Psychoactive Substance Use History in Comprehensive Cardiovascular Risk Assessment, Diagnosis, Treatment, and Prevention.

BACKGROUND: Psychoactive substances have toxic effects resulting different cardiovascular and non-cardiovascular organ damage. Through a variety of mechanisms, they can trigger the onset of various forms of cardiovascular disease: acute or chronic, transient or permanent, subclinical or symptomatic. Hence, a thorough knowledge of the patient's drug habits is essential for a more complete clinical-etiopathogenetic diagnosis and consequent therapeutic, preventive, and rehabilitative management. SUMMARY: The prime reason for taking a psychoactive substance use history in the cardiovascular context is to identify those people who use substances (whether habitual or occasional users, symptomatic or not) and adequately assess their overall cardiovascular risk profile in terms of "user status" and type of substance(s) used. A psychoactive substance history could also alert the physician to suspect, and eventually diagnose, cardiovascular disease related to the intake of psychoactive substances, so optimizing the medical management of users. This anamnesis could finally assess the likelihood of patients persisting in the habit as a user or relapse, while maintaining high their cardiovascular risk profile. Taking such a history should be mandatory when a causal connection is suspected between intake of psychoactive substances and the observed symptoms or pathology, regardless of whether the individual is a declared user or not. KEY MESSAGES: The purpose of this article was to provide practical information on when, how, and why to perform a psychoactive substance use history.

Predicting left ventricular functional recovery in ischaemic cardiomyopathy: needs and challenges.

Left ventricular (LV) systolic function is an essential parameter for the evaluation of patients with ischaemic heart disease, and therapeutic choices are significantly driven by LV ejection fraction (LVEF) in the early stage of the disease and during follow-up. After an acute coronary syndrome, ventricular dysfunction may be reversible when caused by transient myocardial stunning. Therefore, the identification of clinical, laboratory, and instrumental predictors of improvement in LV systolic function (in addition to LVEF) is essential for an adequate prognostic stratification. In the setting of chronic ischaemic heart disease, there is no evidence that an improvement in LV systolic function is invariably associated with a better prognosis and LVEF is only one of many parameters that should be considered for the risk stratification. This state-of-the-art review will critically analyse the scientific evidence regarding known predictors of LVEF recovery, trying to elucidate their pathophysiological principles and clinical value.

Importance of genotype for risk stratification in arrhythmogenic right ventricular cardiomyopathy using the 2019 ARVC risk calculator.

AIMS: To study the impact of genotype on the performance of the 2019 risk model for arrhythmogenic right ventricular cardiomyopathy (ARVC). METHODS AND RESULTS: The study cohort comprised 554 patients with a definite diagnosis of ARVC and no history of sustained ventricular arrhythmia (VA). During a median follow-up of 6.0 (3.1,12.5) years, 100 patients (18%) experienced the primary VA outcome (sustained ventricular tachycardia, appropriate implantable cardioverter defibrillator intervention, aborted sudden cardiac arrest, or sudden cardiac death) corresponding to an annual event rate of 2.6% [95% confidence interval (CI) 1.9-3.3]. Risk estimates for VA using the 2019 ARVC risk model showed reasonable discriminative ability but with overestimation of risk. The ARVC risk model was compared in four gene groups: PKP2 (n = 118, 21%); desmoplakin (DSP) (n = 79, 14%); other desmosomal (n = 59, 11%); and gene elusive (n = 160, 29%). Discrimination and calibration were highest for PKP2 and lowest for the gene-elusive group. Univariable analyses revealed the variable performance of individual clinical risk markers in the different gene groups, e.g. right ventricular dimensions and systolic function are significant risk markers in PKP2 but not in DSP patients and the opposite is true for left ventricular systolic function. CONCLUSION: The 2019 ARVC risk model performs reasonably well in gene-positive ARVC (particularly for PKP2) but is more limited in gene-elusive patients. Genotype should be included in future risk models for ARVC.

Using marginal structural joint models to estimate the effect of a time-varying treatment on recurrent events and survival: An application on arrhythmogenic cardiomyopathy.

In many clinical applications to evaluate the effect of a treatment, randomized control trials are difficult to carry out. On the other hand, clinical observational registries are often available and they contain longitudinal data regarding clinical parameters, drug therapies, and outcomes. In the past, much research has addressed causal methods to estimate treatment effects from observational studies. In the context of time-varying treatments, marginal structural models are often used. However, most analyses have focused on binary outcomes or time-to-the-first event analyses. The novelty of our approach is to combine the marginal structural methodology with the case where correlated recurrent events and survival are the outcomes of interest. Our work focuses on solving the nontrivial problem of defining the measures of effect, specifying the model for the time-dependent weights and the model to estimate the outcome, implementing them, and finally estimating the final treatment effects in this life-history setting. Our approach provides a strategy that allows obtaining treatment effect estimates both on the recurrent events and the survival with a clear causal and clinical interpretation. At the same time, the strategy we propose is based on flexible modeling choices such as the use of joint models to capture the correlation within events from the same subject and the specification of time-dependent treatment effects. The clinical problem which motivated our work is the evaluation of the treatment effect of beta-blockers in arrhythmogenic right ventricular cardiomyopathy (ARVC/D), and the dataset comes from the Trieste Heart Muscle Disease Registry.

The Arrhythmic Phenotype in Cardiomyopathy.

In the wide phenotypic spectrum of cardiomyopathies, sudden cardiac death (SCD) has always been the most visible and devastating disease complication. The introduction of implantable cardioverter-defibrillators for SCD prevention by the late 1980s has moved the question from how to whom we should protect from SCD, leaving clinicians with a measure of uncertainty regarding the most reliable option to guide identification of the highest-risk patients. In this review, we will go through all the available evidence in the field of arrhythmic expression and arrhythmic risk stratification in the different phenotypes of cardiomyopathies to provide practical suggestions in daily clinical management.

Focus on arrhythmogenic right ventricular cardiomyopathy.

Arrhythmogenic right ventricular cardiomyopathy is a myocardial disease generally caused by desmosomal mutations and characterized by progressive replacement of cardiomyocites with fibro-adipose tissue. In the classic form of the disease right ventricle is predominantly affected. However, biventricular and left-dominant variants have been recently recognized, leading to the new nosological definition of arrhythmogenic cardiomyopathy. The condition affects mostly young adults and athletes and is clinically characterized by ventricular arrhythmias, heart failure and sudden cardiac death. The diagnosis is based on clinical-instrumental criteria, including family history, morpho-functional and electrocardiographic abnormalities, ventricular arrhythmias and genetic defects (Task Force Criteria, 2010). The main goal in the management of patients is the prevention of sudden cardiac death, where implantable cardioverter-defibrillator is the only effective therapeutic strategy. Many arrhythmic risk factors have been described. Recently, an on-line calculator has been proposed, but it needs further validation.

Cardiac Tumors: Diagnosis, Prognosis, and Treatment.

PURPOSE OF REVIEW: Cardiac masses frequently present significant diagnostic and therapeutic clinical challenges and encompass a broad set of lesions that can be either neoplastic or non-neoplastic. We sought to provide an overview of cardiac tumors using a cardiac chamber prevalence approach and providing epidemiology, imaging, histopathology, diagnostic workup, treatment, and prognoses of cardiac tumors. RECENT FINDINGS: Cardiac tumors are rare but remain an important component of cardio-oncology practice. Over the past decade, the advances in imaging techniques have enabled a noninvasive diagnosis in many cases. Indeed, imaging modalities such as cardiac magnetic resonance, computed tomography, and positron emission tomography are important tools for diagnosing and characterizing the lesions. Although an epidemiological and multimodality imaging approach is useful, the definite diagnosis requires histologic examination in challenging scenarios, and histopathological characterization remains the diagnostic gold standard. A comprehensive clinical and multimodality imaging evaluation of cardiac tumors is fundamental to obtain a proper differential diagnosis, but histopathology is necessary to reach the final diagnosis and subsequent clinical management.

Electrocardiographic differentiation between 'benign T-wave inversion' and arrhythmogenic right ventricular cardiomyopathy.

AIMS: To characterize the most common electrocardiographic (ECG) abnormalities in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC), including anterior T-wave inversion (TWI) and to compare the characteristics of TWI in patients with ARVC and in a cohort of young healthy athletes and sedentary individuals. METHODS AND RESULTS: The study population consisted of 162 patients with a definite diagnosis of ARVC and 129 young controls with anterior TWI. Cardiac disease was excluded in all controls after a comprehensive diagnostic work-up. The ECG was abnormal in 131 patients with ARVC (81%). Abnormalities included anterior TWI (n = 82, 51%), QRS duration ratio V2:V5 >1.2 (n = 51, 31%), prolonged terminal S wave activation duration in V2 >55 ms (n = 42, 26%), inferior TWI (n = 30, 18%), and lateral TWI (n = 26, 16%). The J-point preceding anterior TWI was <0.1 mV in 80/82 (98%) patients with ARVC and in 98 (76%) controls. Among the ARVC patients with anterior TWI, 62 (77%) showed at least one additional abnormal feature, most commonly QRS duration ratio V2:V5 > 1.2 (52%) and inferior or lateral TWI (47%). CONCLUSION: The ECG is frequently abnormal in patients with ARVC and anterior TWI is the most common feature. Anterior TWI is usually accompanied by other abnormalities in ARVC, which are uncommon in healthy individuals. J point <0.1 mV preceding anterior TWI is not specific to ARVC and is observed in the majority of healthy individuals, including athletes, indicating a limited role for differentiating physiology or normal variants from ARVC.

Lifelong arrhythmic risk stratification in arrhythmogenic right ventricular cardiomyopathy: distribution of events and impact of periodical reassessment.

Aims: The arrhythmic risk stratification of arrhythmogenic right ventricular cardiomyopathy (ARVC) remains controversial. We evaluated the long-term distribution of life-threatening arrhythmic events assessing the impact of periodical risk reassessment. Methods and results: Ninety-eight ARVC patients with no previous major ventricular arrhythmias were retrospectively analysed. Patients were assessed at baseline, at 22 [inter-quartile range (IQR) 16-26], 49 (IQR 41-55) and 97 months (IQR 90-108). The primary endpoint was a composite of sudden cardiac death, ventricular fibrillation, sustained ventricular tachycardia or appropriate implanted cardioverter-defibrillator intervention. During a median follow-up of 91 months (IQR 34-222) 28 patients (29%) experienced the composite endpoint. The median time for the primary event was 35 months (IQR 18-86 months), and 39% of events occurred beyond 49 months of follow-up. History of syncope (HR 4.034; 95% CI, 1.488 to 10.932; P-value = 0.006), non-sustained ventricular tachycardia (NSVT; HR 3.534; 95% CI 1.265-9.877; P-value = 0.016), premature ventricular contractions (PVC) >1000/24h (HR 2.761; 95% CI 1.120-6.807; P-value = 0.027), and right ventricular fractional area change (RVFAC; HR 0.945; 95% CI 0.906-0.985; P-value = 0.008) were found as independent predictors at baseline multivariate analysis. Nevertheless, when the prognostic impact of each variable was reassessed overtime only NSVT (HR 3.282; 95% CI, 1.122 to 9.598, P-value = 0.023) and RVFAC (HR 0.351, 95% CI, 0.157 to 0.780; P-value = 0.010) remained independent predictors throughout the whole follow-up. Conclusion: In our cohort of ARVC patients only NSVT and RVFAC maintained their independent prognostic impact in predicting arrhythmic events during the long-term follow-up. Periodical re-assessment of risk in these patients is strongly recommended.

The additive prognostic value of end-systolic pressure-volume relation by stress CMR in patients with known or suspected coronary artery disease.

PURPOSE: The difference between rest and peak stress end-systolic pressure-volume relation (ΔESPVR) is an afterload-independent index of left ventricular (LV) contractility. We assessed the independent prognostic value of ΔESPVR index by dipyridamole stress-cardiovascular magnetic resonance (CMR) in patients with known/suspected coronary artery disease (CAD). METHODS: We considered 196 consecutive patients (62.74 ± 10.66 years, 49 females). Wall motion and perfusion abnormalities at rest and peak stress were analysed. Replacement myocardial fibrosis was detected by late gadolinium enhancement (LGE) technique. The ESPVR was evaluated at rest and peak stress from raw measurement of systolic arterial pressure and end-systolic volume by biplane Simpson's method. RESULTS: A reduced ΔESPVR index (≤ 0.02 mmHg/mL/m2) was found in 88 (44.9%) patients and it was associated with a lower LV ejection fraction (EF) and with a higher frequency of abnormal stress CMR and myocardial fibrosis. During a mean follow-up of 53.17 ± 28.21 months, 50 (25.5%) cardiac events were recorded: 5 cardiac deaths, 17 revascularizations, one myocardial infarction, 23 hospitalisations for heart failure or unstable angina, and 4 ventricular arrhythmias. According to Cox regression analysis, diabetes, family history, LVEF, abnormal stress CMR, myocardial fibrosis, and reduced ΔESPVR were significant univariate prognosticators. In the multivariate analysis the independent predictors were ΔESPVR index ≤ 0.02 mmHg/mL/m2 (hazard ratio-HR = 2.58, P = 0.007), myocardial fibrosis (HR = 2.13, P = 0.036), and diabetes (HR = 2.33, P = 0.012). CONCLUSION: ΔESPVR index by stress-CMR was independently associated with cardiac outcomes in patients with known/suspected CAD, in addition to replacement myocardial fibrosis and diabetes. Thus, the assessment of ΔESPVR index may be included into the standard stress-CMR exam to further stratify the patients.

Long-Term Arrhythmic Follow-Up and Risk Stratification of Patients With Desmoplakin-Associated Arrhythmogenic Right Ventricular Cardiomyopathy.

Background: Patients with likely pathogenic/pathogenic desmoplakin (DSP) variants are poorly characterized. Some of them meet diagnostic criteria for arrhythmogenic right ventricular cardiomyopathy (ARVC), but it is unclear how risk stratification strategies for ARVC perform in this setting. Objectives: The purpose of this study was to characterize arrhythmic outcomes and to test the performance of the recently validated ARVC risk calculator in patients with DSP likely pathogenic/pathogenic variants fulfilling definite 2010 ARVC Task Force Criteria (DSP-TFC+). Methods: DSP-TFC+ patients were enrolled from 20 institutions across 3 continents. Ventricular arrhythmias (VA), defined as a composite of sustained ventricular tachycardia (VT), appropriate implantable cardioverter defibrillator therapies, and ventricular fibrillation/sudden cardiac death events in follow-up, were reported as the primary outcome. We tested the performance of the ARVC risk calculator for VA prediction, reporting c-statistics. Results: Among 252 DSP-TFC+ patients (age 39.6 ± 16.9 years, 35.3% male), 94 (37.3%) experienced VA over 44.5 [IQR: 19.6-78.3] months. Patients with left ventricle involvement (n = 194) were at higher VA risk (log-rank P = 0.0239). History of nonsustained VT (aHR 2.097; P = 0.004) showed the strongest association with VA occurrence during the first 5-year follow-up. Neither age (P = 0.723) nor male sex (P = 0.200) was associated with VAs at follow-up. In 204 patients without VA at diagnosis, incident VA rate was high (32.8%; 7.37%/y). The ARVC risk calculator performed poorly overall (c-statistic 0.604 [0.594-0.614]) and very poorly in patients with left ventricular disease (c-statistic 0.558 [0.556-0.560]). Conclusions: DSP-TFC+ patients are at substantial risk for VAs. The ARVC risk calculator performs poorly in DSP-TFC+ patients suggesting need for a gene-specific risk algorithm. Meanwhile, DSP-TFC+ patients with nonsustained VT should be considered as high-risk.

Deep-learning-based prognostic modeling for incident heart failure in patients with diabetes using electronic health records: A retrospective cohort study.

Patients with type 2 diabetes mellitus (T2DM) have more than twice the risk of developing heart failure (HF) compared to patients without diabetes. The present study is aimed to build an artificial intelligence (AI) prognostic model that takes in account a large and heterogeneous set of clinical factors and investigates the risk of developing HF in diabetic patients. We carried out an electronic health records- (EHR-) based retrospective cohort study that included patients with cardiological clinical evaluation and no previous diagnosis of HF. Information consists of features extracted from clinical and administrative data obtained as part of routine medical care. The primary endpoint was diagnosis of HF (during out-of-hospital clinical examination or hospitalization). We developed two prognostic models using (1) elastic net regularization for Cox proportional hazard model (COX) and (2) a deep neural network survival method (PHNN), in which a neural network was used to represent a non-linear hazard function and explainability strategies are applied to estimate the influence of predictors on the risk function. Over a median follow-up of 65 months, 17.3% of the 10,614 patients developed HF. The PHNN model outperformed COX both in terms of discrimination (c-index 0.768 vs 0.734) and calibration (2-year integrated calibration index 0.008 vs 0.018). The AI approach led to the identification of 20 predictors of different domains (age, body mass index, echocardiographic and electrocardiographic features, laboratory measurements, comorbidities, therapies) whose relationship with the predicted risk correspond to known trends in the clinical practice. Our results suggest that prognostic models for HF in diabetic patients may improve using EHRs in combination with AI techniques for survival analysis, which provide high flexibility and better performance with respect to standard approaches.

Use of and association between heart failure pharmacological treatments and outcomes in obese versus non-obese patients with heart failure with reduced ejection fraction: data from the Swedish Heart Failure Registry.

AIMS: To investigate the use of guideline-directed medical therapies (GDMT) and associated outcomes in obese (body mass index ≥30 kg/m2 ) versus non-obese patients with heart failure (HF) with reduced ejection fraction (HFrEF). METHODS AND RESULTS: Patients with HFrEF from the Swedish HF Registry were included. Of 16 116 patients, 24% were obese. In obese versus non-obese patients, use of treatments was 91% versus 86% for renin-angiotensin system inhibitors (RASi)/angiotensin receptor-neprilysin inhibitors (ARNi), 94% versus 91% for beta-blockers, 53% versus 43% for mineralocorticoid receptor antagonists. Obesity was shown to be independently associated with more likely use of each treatment, triple combination therapy, and the achievement of target dose by multivariable logistic regressions. Multivariable Cox regressions showed use of RASi/ARNi and beta-blockers being independently associated with lower risk of all-cause/cardiovascular death regardless of obesity, although, when considering competing risks, a lower risk of cardiovascular death with RASi/ARNi in obese versus non-obese patients was observed. RASi/ARNi were associated with lower risk of HF hospitalization in obese but not in non-obese patients, whereas beta-blockers were not associated with the risk of HF hospitalization regardless of obesity. At the competing risk analysis, RASi/ARNi use was associated with higher risk of HF hospitalization regardless of obesity. CONCLUSION: Obese patients were more likely to receive optimal treatments after adjustment for factors affecting tolerability, suggesting that perceived beyond actual tolerance issues limit GDMT implementation. RASi/ARNi and beta-blockers were associated with lower mortality regardless of obesity, with a greater association between RASi/ARNi and lower cardiovascular death in obese versus non-obese patients when considering competing risk.

Inflammation on Endomyocardial Biopsy Predicts Risk of MACE in Undefined Left Ventricular Arrhythmogenic Cardiomyopathy.

BACKGROUND: Predictors of major adverse cardiovascular events (MACE) in patients with undefined left ventricular arrhythmogenic cardiomyopathy (ULVACM) have not been described. OBJECTIVES: The purpose of this study was to investigate the prognostic value of genetic testing and histology in a cohort of ULVACM patients. METHODS: We identified 313 patients with ULVACM defined by new-onset ventricular arrhythmia (VA), nonischemic pattern of late gadolinium enhancement limited to the left ventricle (LV), and no severe dilated cardiomyopathy (LV ejection fraction ≥40%) from a retrospective multicenter registry. Patients undergoing next generation sequencing (NGS) for cardiomyopathy genes and endomyocardial biopsy (EMB) were compared with subjects without these studies. The primary endpoint was the occurrence of MACE, defined as the composite of cardiac death, heart transplantation, and malignant VA (ventricular tachycardia, ventricular fibrillation, appropriate implantable cardioverter-defibrillator treatment), at 60 months after clinical presentation. RESULTS: Of the whole cohort (age 46 ± 14 years, 63% men, LV ejection fraction 55% ± 7%), 160 (51%) and 198 patients (63%), respectively, underwent NGS and EMB. NGS identified pathogenic or likely-pathogenic cardiomyopathy variants (pathogenic variants/likely pathogenic variants) in 25 of 160 cases (16%). EMB showed active myocardial inflammation (AM) in 102 of 198 patients (52%), 47 of whom (46%) received immunosuppressive therapy. After 58-month median follow-up, 93 of 313 patients (30%) experienced MACE. On multivariable analysis, presentation with malignant VA and EMB-proven AM were positively associated with the primary endpoint (HR: 2.8; 95% CI: 1.4-5.5; P = 0.003; and HR: 3.9; 95% CI: 1.9-7.5; P < 0.001, respectively), whereas immunosuppressive therapy showed a reverse association with MACE at 60 months (HR: 0.10; 95% CI: 0.05-0.40; P < 0.001). CONCLUSIONS: Presentation with malignant VA or AM associates with MACE in ULVACM patients.

Short- and long-term survival in patients over 90 years old undergoing pacemaker implantation.

AIMS: In Italy, 12-month survival in the general population between 90 and 94 years old is 26%. In very old patients, the benefit of pacemaker implantation in terms of quality and duration of life is unclear. The aim of our study was to analyse clinical characteristics, outcome and factors associated with survival in patients at least 90 years old at the time of the first pacemaker implant. METHODS: Clinical parameters, device characteristics, survival and predictors of outcome in patients at least 90 years old treated with a pacemaker in our centre in 2019-2020 were evaluated. RESULTS: Among the 554 patients undergoing pacemaker implantation in our centre during the study interval, 69 (12%) were at least 90 years old; a complete/advanced atrioventricular block was present in 65%. A cardiological comorbidity (excluding atrial fibrillation) was present in 22 patients (32%). Oncological, pulmonary and neurological comorbidities were present in 12 (17%), 19 (28%) and 32 (46%), respectively. Renal impairment was present in 25 patients (36%). After pacemaker implantation, a pneumothorax developed in two patients and lead dislodgment in one. During follow-up (median 17 months, interquartile range: 13-24), 32 patients died (46%), with a 12-month mortality probability of 24.6%. At multivariate analysis, the presence of oncological (hazard ratio (HR) 5.31; P < 0.001) and neurological (HR 6.44; P < 0.001) comorbidities was associated with mortality. Truncating the outcome at 6 months, renal impairment (HR 8.01; P = 0.003), anticoagulant therapy (HR 8.14; P = 0.003), oncological comorbidities (HR 14.1; P < 0.001) and left ventricular function (5% increase of left ventricular ejection fraction: HR 0.66; P < 0.001) were significantly associated with outcome. CONCLUSION: At our centre, patients at least 90 years old underwent pacemaker implantation mainly for advanced atrioventricular block. One-year survival was excellent, even better than expected in the general population.

[Substances of abuse and cardiovascular risk: cannabinoids]. / Sostanze d'abuso e rischio cardiovascolare: i cannabinoidi.

Progressive legalization for medical conditions or recreational use has led to an increased use of cannabis and synthetic cannabinoids over the past years. Most consumers are young and healthy, without cardiovascular risk factors; however, this population is expected to include older individuals. Thus, concerns have arisen about safety and short- and long-term potential adverse effects, with special emphasis on vulnerable groups. Studies show that cannabis might be linked with thrombosis, inflammation, and atherosclerosis, and many reports have associated cannabis and synthetic cannabinoids use with serious adverse cardiovascular complications, including myocardial infarction, cardiomyopathy, arrhythmias, stroke, and cardiac arrest. A clearly defined causal role cannot be demonstrated, because of confounding variables. Physicians need to become aware of the possible spectrum of clinical presentations, not only for timely diagnosis and treatment, but also for effective counseling and prevention.In this review, we aim to provide a basic understanding of the physiological effects of cannabis, the role of the endocannabinoid system in cardiovascular disease, and the cardiovascular consequences of cannabis and synthetic cannabinoid use, including a comprehensive review of the studies and case reports that provide supportive evidence for cannabis as a trigger of adverse cardiovascular events according to the current literature.

The Diagnostic Value of the 12-Lead ECG in Arrhythmogenic Left Ventricular Cardiomyopathy: Novel ECG Signs.

BACKGROUND: Electrocardiographic (ECG) findings in arrhythmogenic left ventricular cardiomyopathy (ALVC) are limited to small case series. OBJECTIVES: This study aimed to analyze the ECG characteristics of ALVC patients and to correlate ECG with cardiac magnetic resonance and genotype data. METHODS: We reviewed data of 54 consecutive ALVC patients (32 men, age 39 ± 15 years) and compared them with 84 healthy controls with normal cardiac magnetic resonance. RESULTS: T-wave inversion was often noted (57.4%), particularly in the inferior and lateral leads. Low QRS voltages in limb leads were observed in 22.2% of patients. The following novel ECG findings were identified: left posterior fascicular block (LPFB) (20.4%), pathological Q waves (33.3%), and a prominent R-wave in V1 with a R/S ratio ≥0.5 (24.1%). The QRS voltages were lower in ALVC compared with controls, particularly in lead I and II. At receiver-operating characteristic analysis, the sum of the R-wave in I to II ≤8 mm (AUC: 0.909; P < 0.0001) and S-wave in V1 plus R-wave in V6 ≤12 mm (AUC: 0.784; P < 0.0001) effectively discriminated ALVC patients from controls. It is noteworthy that 4 of the 8 patients with an apparently normal ECG were recognized by these new signs. Transmural late gadolinium enhancement was associated to LPFB, a R/S ratio ≥0.5 in V1, and inferolateral T-wave inversion, and a ringlike pattern correlated to fragmented QRS, SV1+RV6 ≤12 mm, low QRS voltage, and desmoplakin alterations. CONCLUSIONS: Pathological Q waves, LPFB, and a prominent R-wave in V1 were common ECG signs in ALVC. An R-wave sum in I to II ≤8 mm and SV1+RV6 ≤12 mm were specific findings for ALVC phenotypes compared with controls.