Background Takotsubo syndrome is usually triggered by a stressful event. The type of trigger seems to influence the outcome and should therefore be considered separately. Methods and Results Patients included in the GEIST (German‐Italian‐Spanish Takotsubo) registry were categorized according to physical trigger (PT), emotional trigger (ET), and no trigger (NT) of Takotsubo syndrome. Clinical characteristics as well as outcome predictors were analyzed. Overall, 2482 patients were included. ET was detected in 910 patients (36.7%), PT in 885 patients (34.4%), and NT was observed in 717 patients (28.9%). Compared with patients with PT or NT, patients with ET were younger, less frequently men, and had a lower prevalence of comorbidities. Adverse in‐hospital events (NT: 18.8% versus PT: 27.1% versus ET: 12.1%, P <0.001) and long‐term mortality rates (NT: 14.4% versus PT: 21.6% versus ET: 8.5%, P <0.001) were significantly lower in patients with ET. Increasing age ( P <0.001), male sex ( P =0.007), diabetes ( P <0.001), malignancy ( P =0.002), and a neurological disorder ( P <0.001) were associated with a higher risk of long‐term mortality, while chest pain ( P =0.035) and treatment with angiotensin‐converting enzyme inhibitor/angiotensin receptor blocker ( P =0.027) were confirmed as independent predictors for a lower risk of long‐term mortality. Conclusions Patients with ET have better clinical conditions and a lower mortality rate. Increasing age, male sex, malignancy, a neurological disorder, chest pain, angiotensin‐converting enzyme inhibitor/angiotensin receptor blocker, and diabetes were confirmed as predictors of long‐term mortality.

Background: Brugada syndrome (BrS) is an inherited primary channelopathy syndrome associated to sudden cardiac death. Overall, variants have been identified in eighteen genes encoding for ion channel subunits and seven genes for regulatory proteins. Recently, a missense variant in DLG1 has been found within a BrS phenotype-positive patient. DLG1 encodes for synapse associated protein 97 (SAP97), a protein characterized by the presence of multiple domains for protein–protein interactions including PDZ domains. In cardiomyocytes, SAP97 interacts with Nav1.5, a PDZ binding motif of SCN5A and others potassium channel subunits. Aim of the Study: To characterize the phenotype of an Italian family with BrS syndrome carrying a DLG1 variant. Methods: Clinical and genetic investigations were performed. Genetic testing was performed with whole-exome sequencing (WES) using the Illumina platform. According to the standard protocol, a variant found by WES was confirmed in all members of the family by bi-directional capillary Sanger resequencing. The effect of the variant was investigated by using in silico prediction of pathogenicity. Results: The index case was a 74-year-old man with spontaneous type 1 BrS ECG pattern that experienced syncope and underwent ICD implantation. WES of the index case, performed assuming a dominant mode of inheritance, identified a heterozygous variant, c.1556G>A (p.R519H), in the exon 15 of the DLG1 gene. In the pedigree investigation, 6 out of 12 family members had the variant. Carriers of the gene variant all had BrS ECG type 1 drug induced and showed heterogeneous cardiac phenotypes with two patients experiencing syncope during exercise and fever, respectively. The amino acid residue #519 lies near a PDZ domain and in silico analysis suggested a causal role for the variant. Modelling of the resulting protein structure predicted that the variant disrupts an H-bond and a likelihood of being pathogenic. As a consequence, it is likely that a conformational change affects protein functionality and the modulating role on ion channels. Conclusions: A DLG1 gene variant identified was associated with BrS. The variant could modify the formation of multichannel protein complexes, affecting ion channels to specific compartments in cardiomyocytes.

Background Sodium glucose cotransporter type 2 inhibitors (SGLT2i), also called gliflozins, are playing an emerging role for the treatment of heart failure with reduced left ventricle ejection fraction (HFrEF). However, the direct effects of SGLT2i on left and right ventricular remodeling and function have not been completely clarified. We therefore aimed to assess clinical response to gliflozins focusing on echocardiographic evaluation and identify any predictive factors with a machine learning approach. Methods Based on Random Forest, a robust and consolidated machine learning approach, we carried out a single subject analysis to evaluate to which extent patients treated with gliflozins can effectively be distinguished from patients undergoing non-gliflozins treatments. Besides, we carried out an eXplainability analysis using Shapley values to outline the clinical parameters which mostly took advantage by gliflozins. Finally, machine learning experiments were designed to highlight the presence of specific clinical patterns undermining the gliflozins effectiveness. Results 5-fold cross-validation analyses showed that gliflozin treatment was identified with a 0.70 ± 0.03% accuracy; the most important parameters supporting such accuracy were Right Ventricle S’ Velocity (RV S’), Left Ventricle End Systolic Diameter (LVESD) and E/e’ ratio. Low Tricuspid Annular Plane Systolic Excursion (TAPSE) values along with high LVESD and End Diastolic Volume (EDV) values are likely to impair the gliflozin effectiveness. Conclusions Treatment with gliflozins resulted in an improvement of several echocardiographic parameters related to biventricular function and left ventricle remodeling. Several clinical parameters, as simple echocardiographic parameters, may accurately predict the cardiovascular response to gliflozins treatment.

Background According to 4th Universal Definition of Myocardial Infarction (MI), it is possible to differentiate clinically type 2 MI (T2MI) from type 1 MI (T1MI) and acute myocardial injury (AMI). However, in many cases this differentiation may be difficult. To date there are poor data that allow to distinguish AMI, T2MI and T1MI from the changes and the absolute or relative values of biomarkers of myocardial necrosis. We sought to compare T2MI vs T1MI and vs AMI in terms of cardiac biomarkers changes. Methods we consecutively enrolled 90 patients (30 with T1MI, 30 with T2MI and 30 with AMI). excluding patients with ST-segment elevation myocardial infarction. The ratio of the peak to the upper limit of normal (RULN) were calculated for both CK-MB and cardiac troponin T (cTnT). Moreover, the ratio of peak cTnT to peak CK-MB was also calculated. Results the ratio peak/RULN for cTnI and CK-MB were significantly higher for T1MI in comparison with T2MI (cTnI 100.8 vs 67.1, p &lt; 0.001; CK-MB 2.1 vs 0.66, p 0.003) while there were not significant differences between T2MI and AMI (T2MI 67.1 vs AMI 47.3., p 0.159; T2MI 0.66 vs AMI 0.39, p 0.052). Interstingly, there was a higher rise of cTnT than CK-MB in type 2 compared with type 1 myocardial infarction, so that the ratio of peak cTnT to peak CK-MB was significantly higher for T1MI in comparison with T2MI (T1MI 196.2 vs AMI 20.5, p 0.008). Conclusions Both cTnT and CK-MB peaks were higher in T1MI than in T2MI. Furthermore, cTnT rises out of proportion to CK-MB in T2MI. These changes may contribute to a better differentiation between T2MI and T1MI.

Background Takotsubo Syndrome (TTS) is a clinical condition characterized by an acute transient heart failure with reversible ventricular motion abnormalities. Obesity is related with an increased oxidative stress, which is one of the postulated mechanism of TTS. Aim of the study To investigate the association between Body Mass Index (BMI) and in-hospital and long-term follow-up events among patients with TTS. Methods 178 consecutive patients with TTS at admission were enrolled in a multicenter international registry. According to BMI, patients were divided into two groups: normal-weight (BMI 18.5-25 Kg/m2, N=70) and over-weight (BMI ≥ 25 Kg/m2, N=78). Medical history, clinical data, echocardiographic parameters and in-hospital and long-term follow-up events of all patients were evaluated. Results Mean body mass index was 26±5 Kg/m2. There were no significant differences between over- and normal- weight patients in terms of sex, age and cardiovascular risk factors (diabetes, dyslipidaemia, smoking habit) except for arterial hypertension (85% vs 67%, p=0.01). When evaluating non cardiovascular comorbidities, overweight patients had a higher prevalence of chronic pulmonary diseases (38% vs 20% p=0.018). During hospitalization no differences in terms of admission LVEF and hospital length of stay were found; however, overweight patients had higher rates of in-hospital complications (51 vs 27%, p=0.004). At follow-up, overweight patients had higher rate of MACE (44% vs 27%, p=0.03), one-year (32% vs 15%, p=0.02) and long-term mortality (37% vs 24%, log rank p=0.01), but no differences in terms of rehospitalizations and TTS recurrence. Conclusion Overweight in TTS is associated with higher rates of in-hospital events and long-term mortality and MACE.