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Short QT syndrome (SQTS) is an inherited cardiac ion-channel disease related to an increased risk of sudden cardiac death (SCD) in young and otherwise healthy individuals. SCD is often the first clinical presentation in patients with SQTS. However, arrhythmia risk stratification is presently unsatisfactory in asymptomatic patients. In this context, artificial intelligence-based electrocardiogram (ECG) analysis has never been applied to refine risk stratification in patients with SQTS. The purpose of this study was to analyze ECGs from SQTS patients with the aid of different AI algorithms to evaluate their ability to discriminate between subjects with and without documented life-threatening arrhythmic events. The study group included 104 SQTS patients, 37 of whom had a documented major arrhythmic event at presentation and/or during follow-up. Thirteen ECG features were measured independently by three expert cardiologists; then, the dataset was randomly divided into three subsets (training, validation, and testing). Five shallow neural networks were trained, validated, and tested to predict subject-specific class (non-event/event) using different subsets of ECG features. Additionally, several deep learning and machine learning algorithms, such as Vision Transformer, Swin Transformer, MobileNetV3, EfficientNetV2, ConvNextTiny, Capsule Networks, and logistic regression were trained, validated, and tested directly on the scanned ECG images, without any manual feature extraction. Furthermore, a shallow neural network, a 1-D transformer classifier, and a 1-D CNN were trained, validated, and tested on ECG signals extracted from the aforementioned scanned images. Classification metrics were evaluated by means of sensitivity, specificity, positive and negative predictive values, accuracy, and area under the curve. Results prove that artificial intelligence can help clinicians in better stratifying risk of arrhythmia in patients with SQTS. In particular, shallow neural networks’ processing features showed the best performance in identifying patients that will not suffer from a potentially lethal event. This could pave the way for refined ECG-based risk stratification in this group of patients, potentially helping in saving the lives of young and otherwise healthy individuals.

Brugada syndrome (BrS) is an inherited electrical cardiac disorder that is associated with a higher risk of ventricular fibrillation (VF) and sudden cardiac death (SCD) in patients without structural heart disease. The diagnosis is based on the documentation of the typical pattern in the electrocardiogram (ECG) characterized by a J-point elevation of ≥2 mm, coved-type ST-segment elevation, and negative T wave in one or more right precordial leads, called type 1 Brugada ECG. Risk stratification is particularly difficult in asymptomatic cases. Patients who have experienced documented VF are generally recommended to receive an implantable cardioverter defibrillator to lower the likelihood of sudden death due to recurrent episodes. However, for asymptomatic individuals, the most appropriate course of action remains uncertain. Accurate risk prediction is critical to avoiding premature deaths and unnecessary treatments. Due to the challenges associated with experimental research on human cardiac tissue, alternative techniques such as computational modeling and deep learning-based artificial intelligence (AI) are becoming increasingly important. This study introduces a vision transformer (ViT) model that leverages 12-lead ECG images to predict potentially fatal arrhythmic events in BrS patients. This dataset includes a total of 278 ECGs, belonging to 210 patients which have been diagnosed with Brugada syndrome, and it is split into two classes: event and no event. The event class contains 94 ECGs of patients with documented ventricular tachycardia, ventricular fibrillation, or sudden cardiac death, while the no event class is composed of 184 ECGs used as the control group. At first, the ViT is trained on a balanced dataset, achieving satisfactory results (89% accuracy, 94% specificity, 84% sensitivity, and 89% F1-score). Then, the discarded no event ECGs are attached to additional 30 event ECGs, extracted by a 24 h recording of a singular individual, composing a new test set. Finally, the use of an optimized classification threshold improves the predictions on an unbalanced set of data (74% accuracy, 95% negative predictive value, and 90% sensitivity), suggesting that the ECG signal can reveal key information for the risk stratification of patients with Brugada syndrome.

Objectives Anatomical substrate and mechanical trigger co-act in arrhythmia’s onset in patients with bileaflet mitral valve prolapse (bMVP). Feature tracking (FT) may improve risk stratification provided by cardiac magnetic resonance (CMR). The aim was to investigate differences in CMR and FT parameters in bMVP patients with and without complex arrhythmias (cVA and no-cVA). Methods In this retrospective study, 52 patients with bMVP underwent 1.5 T CMR and were classified either as no-cVA ( n = 32; 12 males; 49.6 ± 17.4 years) or cVA ( n = 20; 3 males; 44.7 ± 11.2 years), the latter group including 6 patients (1 male; 45.7 ± 12.7 years) with sustained ventricular tachycardia or ventricular fibrillation (SVT-FV). Twenty-four healthy volunteers (11 males, 36.2 ± 12.5 years) served as control. Curling, prolapse distance, mitral annulus disjunction (MAD), and late gadolinium enhancement (LGE) were recorded and CMR-FT analysis performed. Statistical analysis included non-parametric tests and binary logistic regression. Results LGE and MAD distance were associated with cVA with an odds ratio (OR) of 8.51 for LGE (95% CI 1.76, 41.28; p = 0.008) and of 1.25 for MAD (95% CI 1.02, 1.54; p = 0.03). GLS 2D (− 11.65 ± 6.58 vs − 16.55 ± 5.09 1/s; p = 0.04), PSSR longitudinal 2D (0.04 ± 1.62 1/s vs − 1.06 ± 0.35 1/s; p = 0.0001), and PSSR radial 3D (3.95 ± 1.97 1/s vs 2.64 ± 1.03 1/s; p = 0.0001) were different for SVT-VF versus the others. PDSR circumferential 2D (1.10 ± 0.54 vs. 0.84 ± 0.34 1/s; p = 0.04) and 3D (0.94 ± 0.42 vs. 0.69 ± 0.17 1/s; p = 0.04) differed between patients with and without papillary muscle LGE. Conclusions CMR-FT allowed identifying subtle myocardial deformation abnormalities in bMVP patients at risk of SVT-VF. LGE and MAD distance were associated with cVA. Key Points • CMR-FT allows identifying several subtle myocardial deformation abnormalities in bMVP patients, especially those involving the papillary muscle. • CMR-FT allows identifying subtle myocardial deformation abnormalities in bMVP patients at risk of SVT and VF. • In patients with bMVP, the stronger predictor of cVA is LGE (OR = 8.51; 95% CI 1.76, 41.28; p = 0.008), followed by MAD distance (OR = 1.25; 95% CI 1.02, 1.54; p = 0.03).

Current guidelines on the management of pericardial diseases suggest to identify high-risk features associated with an increased risk of non-idiopathic aetiology and complications. The aim of this study is to evaluate a “pericarditis score” to assess potential complicated pericarditis in order to facilitate initial clinical triage. Consecutive patients with pericarditis were included in a prospective cohort study from January 2017 to December 2018. Complicated pericarditis was defined as pericarditis with a non-idiopathic aetiology, and/or complications, and/or requiring hospitalization. A clinical and echocardiographic follow-up were performed at 1, 3, 6 months and then every 6 months. The study population was randomized in derivation and validation cohorts. In the derivation cohort, female gender (HR 2.57, p = 0.016), fever > 38 °C (HR 2.86, p = 0.005), previous lack of colchicine use (HR 3.16, p = 0.006), previous use of corticosteroids (HR 3.01, p = 0.009), and echocardiographic signs of constriction (HR 2.26, p = 0.018) were selected by a stepwise procedure in a Cox regression model and constituted the score showing a C-statistics of 0.81. In the validation group, the score was significantly associated with the risk of complicated pericarditis (HR 1.438 per 10-points increase, 95% CI 1.208–1.711, p < 0.001) and showed an increase in event rate with increasing score (low risk ≤ 20 points: complicated pericarditis in 4/19 patients, incidence 21%, p = 0.003, high risk > 40 points: complicated pericarditis in 18/24 patients, incidence 75%, p = 0.006). In this study, we developed and tested a simple score to efficiently identify at presentation patients at high risk of developing complicated pericarditis.

Aims Risk stratification in patients with advanced chronic heart failure (HF) is an unmet need. Circulating microRNA (miRNA) levels have been proposed as diagnostic and prognostic biomarkers in several diseases including HF. The aims of the present study were to characterize HF‐specific miRNA expression profiles and to identify miRNAs with prognostic value in HF patients. Methods and results We performed a global miRNome analysis using next‐generation sequencing in the plasma of 30 advanced chronic HF patients and of matched healthy controls. A small subset of miRNAs was validated by real‐time PCR (P < 0.0008). Pearson's correlation analysis was computed between miRNA expression levels and common HF markers. Multivariate prediction models were exploited to evaluate miRNA profiles' prognostic role. Thirty‐two miRNAs were found to be dysregulated between the two groups. Six miRNAs (miR‐210‐3p, miR‐22‐5p, miR‐22‐3p, miR‐21‐3p, miR‐339‐3p, and miR‐125a‐5p) significantly correlated with HF biomarkers, among which N‐terminal prohormone of brain natriuretic peptide. Inside the cohort of advanced HF population, we identified three miRNAs (miR‐125a‐5p, miR‐10b‐5p, and miR‐9‐5p) altered in HF patients experiencing the primary endpoint of cardiac death, heart transplantation, or mechanical circulatory support implantation when compared with those without clinical events. The three miRNAs added substantial prognostic power to Barcelona Bio‐HF score, a multiparametric and validated risk stratification tool for HF (from area under the curve = 0.72 to area under the curve = 0.82). Conclusions This discovery study has characterized, for the first time, the advanced chronic HF‐specific miRNA expression pattern. We identified a few miRNAs able to improve the prognostic stratification of HF patients based on common clinical and laboratory values. Further studies are needed to validate our results in larger populations.

Patients with drug-induced type 1 Brugada electrocardiograms (BrECGs) are considered to have good prognosis. Spontaneous type 1 is, instead, considered a risk factor; however, it is probably underestimated because of the BrECG fluctuations. The aim of this study was to analyze, in a large population of patients with Br, the real prevalence of type 1 BrECG using 12-lead 24-hour Holter monitoring (12L-Holter) and its correlation with the time of the day. We recorded 303 12L-Holter in 251 patients. Seventy-five (30%) patients exhibited spontaneous type 1 BrECG at 12-lead ECG (group 1) and 176 (70%) had only drug-induced type 1 (group 2). Type 1 BrECG was defined as “persistent” (>85% of the recording), “intermittent” (<85%), or “absent.” In group 1, 12% showed persistent type 1 at 12L-Holter, 57% intermittent type 1%, and 31% never had type 1; in group 2, none had persistent type 1, 20% had intermittent type 1%, and 80% never showed type 1. To evaluate the circadian fluctuations of BrECG, 4 periods in the day were considered. Type 1 BrECG was more frequent between 12-noon and 6 p.m. (52%, p <0.001). In conclusion, in patients with drug-induced type 1, spontaneous type 1 BrECG can be detected more frequently with 12L-Holter than with conventional follow-up with periodic ECGs and this has important implications in the risk stratification. 12L-Holter recording might avoid 20% of the pharmacological challenges with sodium channel blockers, which are not without risks, and should thus be considered as the first screening test, particularly in children or in presence of borderline diagnostic basal ECG.

Cardiac laminopathies encompass a wide range of diseases caused by defects in nuclear envelope proteins, including cardiomyopathy, atrial and ventricular arrhythmias and conduction system abnormalities. Two genes, namely LMNA and EMD, are typically associated with these disorders and are part of the routine genetic panel performed in affected patients. Yet, there are other markedly fewer known proteins, the nesprins, encoded by SYNE genes, that play a pivotal role in connecting the nuclear envelope to cytoskeletal elements. So far, SYNE gene variants have been described in association with neurodegenerative diseases; their potential association with cardiac disorders, albeit anecdotally reported, is still largely unexplored. This review focuses on the role of nesprins in cardiomyocytes and explores the potential clinical implications of SYNE variants by presenting five unrelated patients with distinct cardiac manifestations and reviewing the literature. Emerging research suggests that SYNE-related cardiomyopathies involve disrupted nuclear–cytoskeletal coupling, leading to impaired cardiac function. Understanding these mechanisms is critical for furthering insights into the broader implications of nuclear envelope proteins in cardiac health and for potentially developing targeted therapeutic strategies. Additionally, our data support the inclusion of SYNE genes in the cardiac genetic panel for cardiomyopathies and cardiac conduction disorders.

This study aims to describe prevalence and clinical significance of latent Brugada syndrome (BrS) in a young population with atrial fibrillation (AF). Between September 2015 and November 2017, among 111 AF patients below 45 years of age, those without pre-existing pathologies and/or known risk factors were selected for the study. Based on baseline 12-lead-24-h Holter electrocardiogram (ECG), previous class 1C antiarrhythmic drug therapy, or ajmaline testing, patients were stratified as latent type 1 BrS or not. Within the 78 enrolled patients, 13 (16.7%; group 1) revealed a type 1 BrS ECG pattern, while 65 (83.3%; group 2) did not. Mean age was 37 ± 8 vs. 35 ± 7 ( = 0.42), and males were 7 (54%) vs. 54 (83%) ( = 0.02) in the two groups, respectively. Family history of BrS was significantly more common within group 1 patients (2, 15% vs. 0; = 0.03), and 4 (31%) patients experienced syncope in group 1 vs. 5 (8%) in group 2 ( = 0.02). After a mean follow-up of 42 ± 18 months from the index AF event, more than 80% of the patients, in both study groups, were in sinus rhythm. In young patients with AF without pre-existing pathologies and/or known risk factors, latent BrS should be suspected. Syncope and a family history of BrS emerge as easily identifiable factors related to BrS. Long-term sinus rhythm maintenance appears satisfactory, either in the presence or not of BrS.

ObjectiveFrequent flares of pericardial inflammation in recurrent or incessant pericarditis with corticosteroid dependence and colchicine resistance may represent a risk factor for constrictive pericarditis (CP). This study was aimed at the identification of CP in these patients, evaluating the efficacy and safety of anakinra, a third-line treatment based on interleukin-1 inhibition, to treat CP and prevent the need for pericardiectomy.MethodsConsecutive patients with recurrent or incessant pericarditis with corticosteroid dependence and colchicine resistance were included in a prospective cohort study from 2015 to 2018. Enrolled patients received anakinra 100 mg once daily subcutaneously. The primary end point was the occurrence of CP. A clinical and echocardiographic follow-up was performed at 1, 3, 6 months and then every 6 months.ResultsThirty-nine patients (mean age 42 years, 67% females) were assessed, with a baseline recurrence rate of 2.76 flares/patient-year and a median disease duration of 12 months (IQR 9–20). During follow-up, CP was diagnosed in 8/39 (20%) patients. After anakinra dose of 100 mg/day, 5 patients (63%) had a complete resolution of pericardial constriction within a median of 1.2 months (IQR 1–4). In other three patients (37%), CP became chronic, requiring pericardiectomy within a median of 2.8 months (IQR 2–5). CP occurred in 11 patients (28%) with incessant course, which was associated with an increased risk of CP over time (HR for CP 30.6, 95% CI 3.69 to 253.09).ConclusionsIn patients with recurrent or incessant pericarditis, anakinra may have a role in CP reversal. The risk of CP is associated with incessant rather than recurrent course.

ObjectiveAim of this paper is to evaluate the outcomes of ‘idiopathic’ chronic large pericardial effusions without initial evidence of pericarditis.MethodsAll consecutive cases of idiopathic chronic large pericardial effusions evaluated from 2000 to 2015 in three Italian tertiary referral centres for pericardial diseases were enrolled in a prospective cohort study. The term ‘idiopathic’ was applied to cases that performed a complete diagnostic evaluation to exclude a specific aetiology. A clinical and echocardiographic follow-up was performed every 3–6 months.Results100 patients were included (mean age 61.3±14.6 years, 54 females, 44 patients were asymptomatic according to clinical evaluation) with a mean follow-up of 50 months. The baseline median size of the effusion (evaluated as the largest end-diastolic echo-free space) was 25 mm (IQR 8) and decreased to a mean value of 7 mm (IQR 19; p<0.0001) with complete regression in 39 patients at the end of follow-up. There were no new aetiological diagnoses. Adverse events were respectively: cardiac tamponade in 8 patients (8.0%), pericardiocentesis in 30 patients (30.0%), pericardial window in 12 cases (12.0%) and pericardiectomy in 3 patients (3.0%). Recurrence-free survival and complications-free survival was better in patients treated without interventions (log rank p=0.0038).ConclusionsThe evolution of ‘idiopathic’ chronic large pericardial effusions is usually benign with reduction of the size of the effusion in the majority of cases, and regression in about 40% of cases. The risk of cardiac tamponade is 2.2%/year and recurrence/complications survival was better in patients treated conservatively without interventions.