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Low-Density Lipoprotein (LDL) cholesterol is one of the main target for cardiovascular (CV) prevention and therapy. In the last years, Proprotein Convertase Subtilisin-Kexin type 9 inhibitors (PCSK9-i) has emerged as a key therapeutic target to lower LDL and were introduced for prevention of CV events. Recently (June 2022) the Italian Medicines Agency (AIFA) modified the eligibility criteria for the use of PCSK9-i. We designed an observational study to estimate the prevalence of eligible subjects and evaluate the effectiveness of PCSK9-i applying a Target Trial Emulation (TTE) approach based on Electronic Health Records (EHR). Subjects meeting the eligibility criteria were identified from July 2017 (when PCSK9-i became available) to December 2020. Outcomes were all-cause death and the first hospitalization. Among eligible subjects, we identified those treated at date of the first prescription. Inverse Probability of Treatment Weights (IPTW) were estimated including demographic and clinical covariates, history of treatment with statins and the month/year eligibility date. Competing risk models on weighted cohorts were used to derive the Average Treatment Effect (ATE) and the Conditional Average Treatment Effect (CATE) in subgroups of interest. Out of 1976 eligible subjects, 161 (8%) received treatment with PCSK9-i. Treated individuals were slightly younger, predominantly male, had more severe CV conditions, and were more often treated with statin compared to the untreated subjects. The latter exhibited a higher prevalence of non-CV comorbidities. A significant absolute and relative risk reduction of death and a lower relative risk for the first hospitalization was observed. The risk reduction for death was confirmed in CATE analysis. PCSk9-i were prescribed to a minority of eligible subjects. Within the TTE framework, the analysis confirmed the association between PCSK9-i and lower risk of events, aligning with findings from randomized clinical trials (RCTs). In our study, PCSK9-i provided protection specifically against all-cause death, expanding upon the evidence from RCTs that had primarily focused on composite CV outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Barbati et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., Competing Interests: The Johns Hopkins ARVC program (Dr James, Gasperetti, Calkins, Carrick, Murray, and Tondo) is supported by the Leonie-Wild Foundation, the Leyla Erkan Family Fund for ARVD Research, the Hugh Calkins, Marvin H. Weiner, and Jacqueline J. Bernstein Cardiac Arrhythmia Center, the Dr Francis P. Chiramonte Private Foundation, the Dr Satish, Rupal, and Robin Shah ARVD Fund at 10.13039/100007880Johns Hopkins, the Bogle Foundation, the Campanella family, the Patrick J. Harrison family, the 10.13039/501100019817Peter French Memorial Foundation, and the Wilmerding Endowments and 10.13039/100000002NIH/10.13039/100006108NCATS UL1 TR003098. ASJMtR and PVT acknowledge support from the Netherlands Cardiovascular Research Initiative, an initiative with support of the Netherlands Heart Foundation, grant nos. CVON2018-30 PREDICT2, CVON2015-12 eDETECT, 2020B005 Double Dose. ASJMtR is supported by the 10.13039/501100001826ZonMW Off-Road Grant 2021. The Zurich ARVC Program is supported by the 10.13039/501100011561Georg und Bertha Schwyzer-Winiker Foundation, 10.13039/501100007252Baugarten Foundation, Wild Foundation, 10.13039/501100001711Swiss National Science Foundation (SNF), and the 10.13039/501100004362Swiss Heart Foundation. The Bologna Cardiomyopathy Registry has received funding support from the 10.13039/501100003196Italian Ministry of Health, RC-2022-2773270 project AAMW received funding from CVON Predict-2. Dr Mestroni is supported by 10.13039/100000002NIH R01HL69071, R01HL116906, R01HL147064, 10.13039/100000002NIH/10.13039/100006108NCATS UL1 TR002535 and UL1 TR001082. Dr Yazdani is supported by 10.13039/501100000274British Heart Foundation FS/CRTF/23/24448 and Alexander Jansons Myocarditis UK. Dr Prasad has received funding from Alexander Jansons Myocarditis UK, 10.13039/501100000833Rosetrees Trust, and 10.13039/501100000274British Heart Foundation. Dr Medo is supported by the 10.13039/100001825Rose Foundation. This work was supported by the 10.13039/501100000265Medical Research Council (UK), 10.13039/501100000274British Heart Foundation [RE/18/4/34215], the 10.13039/501100013342NIHR Imperial College Biomedical Research Centre, the 10.13039/501100000272NIHR Royal Brompton Biomedical Research Centre, and the 10.13039/501100000282Sir Jules Thorn Charitable Trust [21JTA]. Dr Saguner has received educational grants through his institution from Abbott, Bayer Healthcare, Biosense Webster, Biotronik, Boston Scientific, BMS/Pfizer, and Medtronic; and speaker/advisory board/consulting fees from Abbott, Bayer Healthcare, Daiichi-Sankyo, Medtronic, Novartis, and Pfizer. Dr Lakdawala has received unrestricted research support from Pfizer and the O’Hare and Steggall Family Foundations and consulting fees from BMS, Pfizer, Cytokinetics, Sarepta, and Tenaya. Dr Mestroni received educational grant from Greenstone; and advisory board/consulting fees from Tenaya, StrideBio, and Unicure. Dr Gasperetti received advisory board/consulting fees from Lexeo, and has served as an unpaid consultant for StrideBio. Dr James has received research grants from StrideBio Inc and Lexeo Inc; has received advisory board/consulting fees from Pfizer and Lexeo; and has served as an unpaid consultant for StrideBio and Tenaya. Dr Ware has received research support from Bristol-Myers Squibb; and advisory board/consultancy fees from Bristol-Myers Squibb, Foresite Labs, and Pfizer. Dr Calkins is a consultant for Medtronic Inc, Biosense Webster, Pfizer, StrideBio, Rocket, and Abbott. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

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 V 1 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 V 1 plus R-wave in V 6  ≤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 V 1 , and inferolateral T-wave inversion, and a ringlike pattern correlated to fragmented QRS, SV 1 +RV 6  ≤12 mm, low QRS voltage, and desmoplakin alterations., Conclusions: Pathological Q waves, LPFB, and a prominent R-wave in V 1 were common ECG signs in ALVC. An R-wave sum in I to II ≤8 mm and SV 1 +RV 6  ≤12 mm were specific findings for ALVC phenotypes compared with controls., Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. All rights reserved.)

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., (© 2023. The Author(s).)

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., Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Cervical spondylotic myelopathy (CSM) is a progressively growing pathology to afford by a spinal surgeon due to the aging of the population, associated with better treatment management and the best diagnosis and treatment solutions are greatly discussed. Nowadays that scientific literature is progressively increasing to identify the gold standard in diagnosis and treatment can be very challenging. This is particularly evident in spinal surgery with many different indications not only in different countries but also in the same local reality. In this scenario, many neurosurgical societies works to identify some guideline or recommendations to help spinal surgeons in daily practice. Furthermore, in an era in which legal issues are increasingly present in clinical practice to have some indications globally accepted can be very useful. World Federation of Neurosurgical Societies (WFNS) few years ago starts this process creating a list of recommendations originating from a worldwide steering committee to respect all the local reality. The spinal section of Italian Neurosurgical Society decides to adopt the WFNS recommendations with some revision basing on Italian scenario. The steering committee of the Spinal Section of Italian Neurosurgical Society identify 7 groups to review the literature of the last 10 years about different topics on CSM and to analyses the WFNS recommendations to adapt it to the Italian daily practice. The statements were discussed and voted in 2 sessions to obtain the final version. A list of recommendations on natural course and clinical presentation; diagnostic tests; conservative and surgical treatment; anterior, posterior and combined surgical treatment; role of neurophysiological monitoring and follow-up and outcome was created with only few new or revised statements respect the ones of WFNS. The Spine Section of Italian Neurosurgical Society create a list of recommendations that represent the more contemporary treatment concepts for CSM as presented in the highest quality clinical literature and best clinical practices available on this subject.

Aims: To investigate the use of guideline-directed medical therapies (GDMT) and associated outcomes in obese (body mass index ≥30 kg/m 2 ) 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., (© 2023 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

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., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Gandin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The aim of this study is to predict local failure after partial prostate re-irradiation for the treatment of isolated locally recurrent prostate cancer by using a machine learning classifier based on radiomic features from pre-treatment computed tomography (CT), positron-emission tomography (PET) and biological effective dose distribution (BED) of the radiotherapy plan. The analysis was conducted on a monocentric dataset of 43 patients with evidence of isolated intraprostatic recurrence of prostate cancer after primary external beam radiotherapy. All patients received partial prostate re-irradiation delivered by volumetric modulated arc therapy. The gross tumor volume (GTV) of each patient was manually contoured from planning CT, choline-PET and dose maps. An ensemble machine learning pipeline including unbalanced data correction and feature selection was trained using the radiomic and dosiomic features as input for predicting occurrence of local failure. The model performance was assessed using sensitivity, specificity, accuracy and area under receiver operating characteristic curves of the score function in 10-fold cross validation repeated 100 times. Local failure was observed in 13 patients (30%), with a median time to recurrence of 36.7 months (range = 6.1-102.4 months). A four variables ensemble machine learning model resulted in accuracy of 0.62 and AUC 0.65. According to our results, a dosiomic machine learning classifier can predict local failure after partial prostate re-irradiation.

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., Competing Interests: Conflict of interest: P.M.E. declares consultancies for Pfizer, Sarepta. G.S. declares consultancies at Novartis, Bayer, Astrazeneca, Boston Scientific, Vifor Pharma, Menarini, Akcea Therapeutics. The other authors declare that there is no conflict of interest., (© The Author(s) 2022. Published by Oxford University Press on behalf of European Society of Cardiology.)

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., (Published on behalf of the European Society of Cardiology. © The Author(s) 2020.)

Background: Recent trends of surgery for atrial fibrillation (AF) are towards more safe and effective energy sources, as well as to simplified sets of atrial lesions., Methods: One hundred eighteen (mean age, 67.4 ± 9.2 years) selected patients with paroxysmal/persistent AF and mitral valve (MV) disease underwent cryoablation of AF combined with conventional (not via mini-thoracotomy) MV surgery; the lesion set was limited to only the left atrium. Multivariable analyses identified predictors of cardiac rhythm at hospital discharge and follow-up., Results: There were 7 (5.9%) hospital deaths; 33 (28%) patients were discharged on AF. Higher values of preoperative left atrial volume index (odds ratio [OR] = 1.07, 95% confidence interval [95%CI]: 1.01-1.13) and mixed etiology of MV disease (OR = 4.19, 95%CI: 1.23-14.2) were predictors of hospital discharge on AF. Seventy-four (66.7%) patients were on stable sinus rhythm at follow-up (median period, 6.6 years); the 1, 5, and 10-year nonparametric estimates of adjusted freedom from AF were 98.1%, 89.2% and 45.6%, respectively. Higher values of preoperative systolic pulmonary artery pressure (hazard ratio [HR] = HR = 1.04, 95%CI: 1.01-1.08) and AF at hospital discharge (HR = 4.14, 95%CI: 1.50-11.4) were predictors of AF at follow-up., Conclusions: During conventional MV surgery, a cryo-lesion set limited to only the left atrium may give good, immediate and long-term results. Left atrial dilation and mixed etiology of MV disease were predictors of hospital discharge on AF. Preoperative pulmonary hypertension and AF at discharge combined with an increased risk of AF at follow-up., Competing Interests: The authors report no relationships that could be construed as a conflict of interest., (© 2020 Published by Elsevier B.V.)

Survivors after a myocardial infarction (MI), especially those with diabetes mellitus (DM),remain at high risk of further events. Identifying and treating factors that may influence survivalmay open new therapeutic strategies. We assessed the impact on prognosis of DM andhypovitaminosis D (hypovitD), alone or combined. In this prospective, observational study, 1081patients were enrolled surviving an MI and divided into four groups according to their diabetic andVitD status. The primary end-point was composite of all-cause mortality, angina/MI and heartfailure (HF). Secondary outcomes were mortality, HF and angina/MI. During a follow-up of 26.1months (IQR 6.6-64.5), 391 subjects experienced the primary end-point. Patients with DM orhypovitD had similar rate of the composite end-point. Patients with only hypovitD or DM did notdiffer regarding components of composite end-point (angina p = 0.97, HF p = 0.29, mortality p = 0.62).DM and VitD deficiency had similarly adjusted risks for primary end-point (HR 1.3, 95%CI 1.05-1.61; HR 1.3, 95% CI 1.04-1.64). The adjusted HR for primary composite end-point for patients withhypovitD and DM was 1.69 (95%CI 1.25-2.29, p = 0.001) in comparison to patients with neitherhypoD nor DM. In conclusion, DM and hypovitD, individually and synergistically, are associatedwith a worse outcome after MI.

Background: Cardiac magnetic resonance (CMR) is widely used to assess tissue and functional abnormalities in arrhythmogenic right ventricular cardiomyopathy (ARVC). Recently, a ARVC risk score was proposed to predict the 5-year risk of malignant ventricular arrhythmias in patients with ARVC. However, CMR features such as fibrosis, fat infiltration, and left ventricular (LV) involvement were not considered., Objectives: The authors sought to evaluate the prognostic role of CMR phenotype in patients with definite ARVC and to evaluate the effectiveness of the novel 5-year ARVC risk score to predict cardiac events in different CMR presentations., Methods: A total of 140 patients with definite ARVC were enrolled (mean age 42 ± 17 years, 97 males) in this multicenter prospective registry. As per study design, CMR was performed in all the patients at enrollment. The novel 5-year ARVC risk score was retrospectively calculated using the patient's characteristics at the time of enrollment. During a median follow-up of 5 years (2 to 8 years), the combined endpoint of sudden cardiac death, appropriate implantable cardioverter-defibrillator intervention, and aborted cardiac arrest was considered., Results: CMR was completely negative in 14 patients (10%), isolated right ventricular (RV) involvement was found in 58 (41%), biventricular in 52 (37%), and LV dominant in 16 (12%). During the follow-up, 48 patients (34%) had major events, but none occurred in patients with negative CMR. At Kaplan-Meier analysis, patients with LV involvement (LV dominant and biventricular) had a worse prognosis than those with lone RV (p < 0.0001). At multivariate analysis, the LV involvement, a LV-dominant phenotype, and the 5-year ARVC risk score were independent predictors of major events. The estimated 5-year risk was able to predict the observed risk in patients with lone RV but underestimated the risk in those with LV involvement., Conclusions: Different CMR presentations of ARVC are associated with different prognoses. The 5-year ARVC risk score is valid for the estimation of risk in patients with lone-RV presentation but underestimated the risk when LV is involved., (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

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.

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.