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The inherited and acquired long QT is a risk marker for potential serious cardiac arrhythmias and sudden cardiac death. Smartwatches are becoming more popular and are increasingly used for monitoring human health. The present study aimed to assess the feasibility and reliability of evaluating the QT interval in lead I, lead II, and V2 lead using a commercially available Apple Watch. One hundred nineteen patients admitted to our Cardiology Division were studied. I, II, and V2 leads were obtained after recording a standard 12-lead ECG. Lead I was recorded with the smartwatch on the left wrist and the right index finger on the crown. Lead II was obtained with the smartwatch on the left lower abdomen and the right index finger on the crown. The V2 lead was recorded with the smartwatch in the fourth intercostal space left parasternal with the right index finger on the crown. There was agreement among the QT intervals of I, II, and V2 leads and the QT mean using the smartwatch and the standard ECG with Spearman’s correlations of 0.886; 0.881; 0.793; and 0.914 (p < 0.001), respectively. The reliability of the QTc measurements between standard and smartwatch ECG was also demonstrated with a Bland–Altman analysis using different formulas. These data show that a smartwatch can feasibly and reliably assess QT interval. These results could have an important clinical impact when frequent QT interval monitoring is required.

Background: About half of patients with ST-segment Elevation Myocardial Infarction (STEMI) have multivessel coronary artery disease (MVD). Our aim was to provide a quantitative comparison of single-stage complete revascularization during the index revascularization versus deferred staged complete revascularization in STEMI patients with MVD. Methods: All studies evaluating patients with STEMI and MVD were included. The primary endpoint was a composite of all-cause death, myocardial infarction and repeat revascularization. Secondary endpoints were cardiovascular death, acute kidney injury and trial defined major bleeding. Results: Eight studies and 2256 patients with STEMI and MVD were included. No difference was evident in the rate of the primary composite endpoint among the study group (Risk Ratio 0.95; 95% CI 0.71–1.27, p = 0.74), while meta-regression showed a significant interaction with drug eluting stent (DES) use (Coefficient –0.005; 95% CI –0.01 to –0.001; p = 0.007). Higher rates of cardiovascular (CV) death were found in the immediate complete revascularization group (5.0% vs 2.6%; Risk Ratio 0.39; 95% CI 0.25–0.62; p < 0.01). Conclusions: Our analysis documented similar clinical outcomes with either single-stage immediate complete revascularization and delayed staged complete revascularization. Secondary analyses suggest that an increase in cardiovascular death might be expected with single-stage percutaneous coronary intervention (PCI). While new randomized trials on the topic are ongoing, revascularization can be personalized and guided by the acute clinical setting, patients’-related factors and workflow logistics.

Coronavirus disease 2019 (COVID-19) is a highly contagious disease that appeared in China in December 2019 and spread rapidly around the world. Several patients with severe COVID-19 infection can develop a coagulopathy according to the ISTH criteria for disseminated intravascular coagulopathy (DIC) with fulminant activation of coagulation, resulting in widespread microvascular thrombosis and consumption of coagulation factors. We conducted a meta-analysis in order to explore differences in coagulopathy indices in patients with severe and non-severe COVID-19. An electronic search was performed within PubMed, Google Scholar and Scopus electronic databases between December 2019 (first confirmed Covid-19 case) up to April 6th, 2020. The primary endpoint was the difference of D-dimer values between Non-Severe vs Severe disease and Survivors vs Non-Survivors. Furthermore, results on additional coagulation parameters (platelet count, prothrombin time, activated partial thromboplastin time) were also analyzed. The primary analysis showed that mean d-dimer was significantly lower in COVID-19 patients with non-severe disease than in those with severe (SMD − 2.15 [− 2.73 to − 1.56], I 2 98%, P < 0.0001). Similarly, we found a lower mean d-dimer in Survivors compared to Non-Survivors (SMD − 2.91 [− 3.87 to − 1.96], I 2 98%, P < 0.0001). Additional analysis of platelet count showed higher levels of mean PLT in Non-Severe patients than those observed in the Severe group (SMD 0.77 [0.32 to 1.22], I 2 96%, P < 0.001). Of note, a similar result was observed even when Survivors were compared to Non-Survivors (SMD 1.84 [1.16 to 2.53], I 2 97%, P < 0.0001). Interestingly, shorter mean PT was found in both Non-Severe (SMD − 1.34 [− 2.06 to − 0.62], I 2 98%, P < 0.0002) and Survivors groups (SMD − 1.61 [− 2.69 to − 0.54], I 2 98%, P < 0.003) compared to Severe and Non-Survivor patients. In conclusion, the results of the present meta-analysis demonstrate that Severe COVID-19 infection is associated with higher D-dimer values, lower platelet count and prolonged PT. This data suggests a possible role of disseminated intravascular coagulation in the pathogenesis of COVID-19 disease complications.

Circulating levels of microRNA (miR)-133a are increased in patients with coronary atherosclerotic disease (CAD). Whether the cardiac release of this miR provides any prognostic information in patients with CAD is currently unknown. We aimed to investigate if changes in concentration of miR-133a trough the coronary circulation may be associated with patients' cardiovascular outcome. We enrolled 111 patients (82 with stable CAD and 29 with acute coronary syndromes [ACS]) who underwent coronary angiography. Circulating levels of miR-133a were measured across the transcoronary circulation. Major adverse cardiac events (MACE: death, nonfatal myocardial infarction, and need for revascularization) were recorded through a median follow-up of 32 months. An increased transcoronary concentration gradient of miR133a showed a significant association with overall rate of MACE at follow-up in patients with both stable CAD and ACS (p = 0.011 and p = 0.002, respectively). At the single end point-analysis, increased transcoronary concentration gradients of miR133a were significantly associated with increased rate of death in patients with ACS (p = 0.017) and with increased incidence of new revascularization because of in-stent restenosis in patients with stable CAD (p = 0.026). Kaplan-Meier curves showed a significantly worse event-free survival in patients with greater transcoronary gradients of miR133a (p = 0.026 in stable CAD group and p = 0.007 for ACS group). Nevertheless, these findings lost their significance after adjustment for common cardiovascular risk factor and high-sensitivity troponin-T. In conclusions, the release of miR133a, as measured by its transcoronary concentration gradient, is associated with a higher incidence of MACE in patients with CAD, but it does not add significant prognostic information compared with traditional prognostic biomarkers, therefore limiting its potential usefulness in the clinical practice. Nevertheless, the differential modulation of miR-133a release in the coronary circulation may reflect pathophysiological mechanism involved in CAD progression and complications and suggest a novel potential role for this miR in the development of in-stent restenosis.

Background The overall risk of long-term adverse events of a transient episode of new-onset atrial fibrillation (AF) in patients with acute coronary syndrome (ACS) remains uncertain. This meta-analysis aimed to assess the prognostic impact of transient new-onset AF complicating ACS. Methods and results Cohort studies examining the risk of adverse events in patients with transient new-onset AF compared to those in sinus rhythm after ACS were identified through a comprehensive search of MEDLINE, Scopus, Cochrane, and Google Scholar Library. Studies reporting the incidence of ischaemic stroke events, recurrent AF, or all-cause mortality at the longest follow-up were included. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CI) were synthesized using inverse variance-weighted random-effects meta-analysis. In the seven observational studies included, comprising 151 735 patients, 6 597 (4.3%) experienced transient new-onset AF, which was associated with an increased risk of ischaemic stroke, recurrent AF, or all-cause mortality (HR: 2.24, 95% CI: 1.75–2.85; P < 0.0001; I2 = 30.76%; seven studies). The results remained consistent across each individual endpoint, including ischaemic stroke (HR 2.38, 95% CI: 1.64–3.44; P < 0.01; I2 = 50.2%; five studies), recurrent AF (HR 4.68, 95% CI: 2.07–10.59; P = 0.0002; I2 = 50.2%; four studies), and all-cause mortality (HR 1.36, 95% CI: 1.08–1.71; P = 0.0089; I2 = 53.25%; four studies). Meta-regression analyses revealed a significant increase in these adverse events associated with ST-elevation myocardial infarction (P = 0.001), while there was a tendency for their decrease associated with oral anticoagulant prescription at discharge (P = 0.07). Conclusions The occurrence of transient new-onset AF is associated with an elevated long-term risk of stroke, recurrent AF, and all-cause mortality in patients with ACS. Consequently, these data urge randomized clinical trials to assess the best antithrombotic regimen while potentially helping the current treatment decision-making process for these patients.

Abstract Aims Although alirocumab and evolocumab have both been associated with improved outcomes in patients with dyslipidaemia or established atherosclerotic cardiovascular disease, data on their respective performances are scarce. This study aimed at providing an indirect comparison of the efficacy and safety of alirocumab vs. evolocumab. Methods and results We conducted a systematic review and network meta-analysis of randomized trials comparing alirocumab or evolocumab to placebo with consistent background lipid-lowering therapy up to November 2018. We estimated the relative risk (RR) and the 95% confidence intervals (CIs) using fixed-effect model in a frequentist pairwise and network meta-analytic approach. A total of 30 trials, enrolling 59 026 patients were included. Eligibility criteria varied significantly across trials evaluating alirocumab and evolocumab. Compared with evolocumab, alirocumab was associated with a significant reduction in all-cause death (RR 0.80, 95% CI 0.66–0.97) but not in cardiovascular death (RR 0.83, 95% CI 0.65–1.05). This study did not find any significant differences in myocardial infarction (RR 1.15, 95% CI 0.99–1.34), stroke (RR 0.96, 95% CI 0.71–1.28), or coronary revascularization (RR 1.13, 95% CI 0.99–1.29) between the two agents. Alirocumab was associated with a 27% increased risk of injection site reaction compared to evolocumab; however, no significant differences were found in terms of treatment discontinuations, systemic allergic reaction, neurocognitive events, ophthalmologic events, or new-onset of or worsening of pre-existing diabetes. Conclusion Alirocumab and evolocumab share a similar safety profile except for injection site reaction. No significant differences were observed across the efficacy endpoints, except for all-cause death, which may be related to the heterogeneity of the studied populations treated with the two drugs.

The rising incidence of myocardial infarction (MI) in individuals under 50 years of age underscores an urgent need for innovative rehabilitation strategies that extend beyond hospital care, empowering young patients to reclaim active lives through sustained physical activity and remote monitoring. Wearable health technologies hold transformative potential here, as studies demonstrate their ability to boost exercise capacity daily steps while reducing rehospitalizations in post-MI recovery. This study thus assesses the clinical value of wearable devices in remotely tracking motor activity among young adults during early MI rehabilitation. Using the SiDLY Care Pro wristband, continuous non-invasive measurements of heart rate, oxygen saturation, and physical activity were collected from 62 of 80 post-MI patients (<50 years) over seven days, alongside validated questionnaires (IPAQ, SF-36, DASS-21). Time-series clustering and principal component analysis characterized heart rate dynamics and activity patterns. Most participants showed sedentary behavior (2000–4000 steps/day), though self-reported health and psychological well-being were satisfactory. The device provided reliable, clinically meaningful data, particularly when linked to clinician feedback. Participants expressed an interest in using such technologies, especially if supported through reimbursement and professional guidance. Despite limitations—short monitoring timelines, small heterogeneous samples, and accuracy constraints—the findings suggest that wearable systems can enhance remote monitoring, patient engagement, and early intervention in post-MI care. Broader studies and supportive policies are recommended. Overall, integrating wearable technologies with professional oversight and patient participation may substantially improve recovery and outcomes for young MI survivors.

The ongoing pandemic of Novel Coronavirus Disease 2019 (COVID-19) infection has created a global emergency. Despite the infection causes a mild illness to most people, some patients are severely affected, demanding an urgent need to better understand how to risk-stratify infected subjects. This is a meta-analysis of observational studies evaluating cardiovascular (CV) complications in hospitalized COVID-19 patients and the impact of cardiovascular risk factors (RF) or comorbidities on mortality. Data sources: PubMed, Scopus, and ISI from 1 December 2019 through 11 June 2020; references of eligible studies; scientific session abstracts; cardiology web sites. We selected studies reporting clinical outcomes of hospitalized patients with COVID-19. The main outcome was death. Secondary outcomes were cardiovascular symptoms and cardiovascular events developed during the COVID-19-related hospitalization. Extracted data were recorded in excel worksheets and analysed using statistical software (MedCalc, OpenMetanalyst, R). We used the proportion with 95% CI as the summary measure. A Freeman-Tukey transformation was used to calculate the weighted summary proportion under the random-effects model. Heterogeneity was assessed by using the Cochran Q test and I2 values. Among 77317 hospitalized patients from 21 studies, 12.86% had cardiovascular comorbidities or RF. Cardiovascular complications were registered in 14.09% of cases during hospitalization. At meta-regression analysis, pre-existing cardiovascular comorbidities or RF were significantly associated to cardiovascular complications in COVID-19 patients (p = 0.019). Pre-existing cardiovascular comorbidities or RF (p<0.001), older age (p<0.001), and the development of cardiovascular complications during the hospitalization (p = 0.038) had a significant interaction with death. Cardiovascular complications are frequent among COVID-19 patients, and might contribute to adverse clinical events and mortality, together with pre-existing cardiovascular comorbidities and RF. Clinicians worldwide should be aware of this association, to identifying patients at higher risk.

Artificial intelligence (AI) is transforming cardiac electrophysiology across the entire care pathway, from arrhythmia detection on 12-lead electrocardiograms (ECGs) and wearables to the guidance of catheter ablation procedures, through to outcome prediction and therapeutic personalization. End-to-end deep learning (DL) models have achieved cardiologist-level performance in rhythm classification and prognostic estimation on standard ECGs, with a reported arrhythmia classification accuracy of ≥95% and an atrial fibrillation detection sensitivity/specificity of ≥96%. The application of AI to wearable devices enables population-scale screening and digital triage pathways. In the electrophysiology (EP) laboratory, AI standardizes the interpretation of intracardiac electrograms (EGMs) and supports target selection, and machine learning (ML)-guided strategies have improved ablation outcomes. In patients with cardiac implantable electronic devices (CIEDs), remote monitoring feeds multiparametric models capable of anticipating heart-failure decompensation and arrhythmic risk. This review outlines the principal modeling paradigms of supervised learning (regression models, support vector machines, neural networks, and random forests) and unsupervised learning (clustering, dimensionality reduction, association rule learning) and examines emerging technologies in electrophysiology (digital twins, physics-informed neural networks, DL for imaging, graph neural networks, and on-device AI). However, major challenges remain for clinical translation, including an external validation rate below 30% and workflow integration below 20%, which represent core obstacles to real-world adoption. A joint clinical engineering roadmap is essential to translate prototypes into reliable, bedside tools.

Accurate anatomical assessment is essential for pre-procedural planning in structural heart disease. Advanced 3D imaging could offer improved visualization for more accurate reconstruction. We assessed the performance of a novel immersive 3D virtual reality (VEA) for the pre-procedural planning of transcatheter aortic valve implantation (TAVI) candidates. Measurement of cardiac-gated contrast-enhanced computed tomography (CT) scans was performed with the novel VEA and established tools: 3Mensio and Horos. 50 consecutive patients were included. Annular and LVOT measurements obtained with VEA were strongly correlated with those derived from standard CT analysis. The intraclass correlation coefficient (ICC) confirmed excellent consistency for annular measurements (ICC = 0.93), while the concordance correlation coefficient indicated very good overall agreement (CCC = 0.83, 95% CI 0.73-0.90). Similarly, LVOT measurements obtained with VEA showed strong correlation with CT values, with good consistency (ICC = 0.90) and good overall agreement (CCC = 0.77, 95% CI 0.64-0.86). VEA-based planning improved prosthesis size selection accuracy, achieving higher concordance with implanted valves and a significant net reclassification gain over conventional CT. Given the increasing use of advanced 3D cardiac imaging technologies, understanding their diagnostic accuracy to guide pre-procedural planning of TAVI is paramount. In our study, VEA provided reliable assessment of aortic root anatomy for TAVI planning. This novel 3D software provides accurate, patient-specific reconstructions of the aortic root and surrounding structures that may optimize valve sizing, improve procedural safety and enhance procedural outcomes. This provides a rationale for future studies to assess the procedural benefit derived from a three-dimensional assessment of the aortic valve geometry.