91 research outputs found

    Clinical and genetic characterization of patients with hypertrophic cardiomyopathy and right atrial enlargement

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    AIMS: Prevalence and clinical significance of right atrial enlargement (RAE) has been poorly characterized in hypertrophic cardiomyopathy. METHODS: One hundred and sixty consecutive patients with hypertrophic cardiomyopathy (35.5 ± 20 years; 64% men) were studied. They underwent clinical examination, standard ECG, M-mode, 2D and Doppler echocardiography, stress test and ECG Holter monitoring. Major adverse cardiac events were considered: cardiac death (sudden death, heart failure death); cardiac transplant; resuscitated cardiac arrest or appropriate implantable cardioverter defibrillator discharge. Genetic analysis of eight sarcomeric genes was performed using Sanger sequencing. RESULTS: RAE was observed in 22 patients (14%), associated with left atrial enlargement in all cases. Patients with RAE were likely to have restrictive mitral pattern (P < 0.001) and had higher New York Heart Association (P < 0.001), N-terminal prohormone of brain natriuretic peptide (P < 0.001), left atrial volume index (P < 0.001), lateral (P = 0.04) and septal (P = 0.002) E/e', systolic pulmonary artery pressure (P < 0.001) and lower ejection fraction (all P < 0.001). On cardiopulmonary exercise testing, peak VO2 was lower and VE/VCO2 higher in patients with RAE (P < 0.001). During a mean follow-up of 4 ± 2.1 years, 30 major adverse cardiac events in 24 patients (15%) were observed. Cox proportional hazards regression analysis identified RAE as an independent predictor of major adverse cardiac events (odds ratio = 2.6; confidence interval 1.5-4.6; P = 0.001). In patients with RAE who were genetically tested, there was a higher prevalence of sarcomeric gene mutations (68%), double mutations (16%) and troponin T mutations (21%). CONCLUSION: RAE is present in a small subset of patients with hypertrophic cardiomyopathy, and largely reflects increased pulmonary pressures because of severe diastolic and/or systolic left ventricular dysfunction. Patients with RAE had a higher prevalence of sarcomeric gene mutations, troponin T mutations and complex genotypes. In conclusion, RAE may serve as a very useful marker of disease progression and adverse outcome in patients with sarcomeric hypertrophic cardiomyopathy

    Left atrial volume during stress is associated with increased risk of arrhythmias in patients with hypertrophic cardiomyopathy

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    Introduction: In patients affected by hypertrophic cardiomyopathy (HCM), left atrial volume index (LAVi) is associated with an increased risk of tachyarrhythmias and major clinical events. To date, the clinical meaning of LAVi measured during exercise (stress LAVi [sLAVi]) has not yet been investigated in HCM. This study sought to evaluate the correlation between LAVi/sLAVi and clinical outcome (risk of arrhythmias and heart failure [HF]) in patients with HCM. Methods and Results: We enrolled a total of 51 consecutive patients with HCM (39 men; mean age: 39.41 ± 17.9 years) who underwent standard and stress echocardiography, following a common protocol. During follow-up (median follow-up was 1.82 years), the following composite endpoints were collected: ARRHYT endpoint (atrial fibrillation, paroxysmal supraventricular tachycardia, nonsustained ventricular tachycardia (VT), sustained VT, ventricular fibrillation, syncope of likely cardiogenic nature, and sudden cardiac death) and HF endpoint (worsening of functional class and left ventricular ejection fraction, hospitalization, and death for end-stage HF). Eight patients were lost at follow-up. ARRHYT endpoint occurred in 13 (30.2%) patients (8, 18.6%, supraventricular and 10, 23.2%, ventricular arrhythmias), whereas HF endpoint occurred in 5 (11.6%) patients. sLAVi (mean value of 31.16 ± 10.15 mL/m2) performed better than rLAVi as a predictor of ARRHYT endpoint (Akaike Information Criterion: 48.37 vs. 50.37, if dichotomized according to the median values). A sLAVi value of 30 mL/m2 showed a predictive accuracy of 72.1% (C-statistics of 0.7346), with a high negative predictive value (87.5%). Conclusion: These findings encourage future studies on sLAVi, as a potential predictor of arrhythmias and adverse outcome in patients with HCM

    Prevalence and clinical significance of red flags in patients with hypertrophic cardiomyopathy

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    Introduction: We sought to determine prevalence and predictive accuracy of clinical markers (red flags, RF), known to be associated with specific systemic disease in a consecutive cohort of patients with hypertrophic cardiomyopathy (HCM). / Methods: We studied 129 consecutive patients (23.7 ± 20.9 years, range 0–74 years; male/female 68%/32%). Pre-specified RF were categorized into five domains: family history; signs/symptoms; electrocardiography; imaging; and laboratory. Sensitivity (Se), specificity (Sp), negative predictive value (NPV), positive predictive value (PPV), and predictive accuracy of RF were analyzed in the genotyped population. / Results: In the overall cohort of 129 patients, 169 RF were identified in 62 patients (48%). Prevalence of RF was higher in infants (78%) and in adults >55 years old (58%). Following targeted genetic and clinical evaluation, 94 patients (74%) had a definite diagnosis (sarcomeric HCM or specific causes of HCM). We observed 14 RF in 13 patients (21%) with sarcomeric gene disease, 129 RF in 34 patients (97%) with other specific causes of HCM, and 26 RF in 15 patients (45%) with idiopathic HCM (p  55yo. Se, Sp, PPV, NPV and PA of RF were 97%, 70%, 55%, 98% and 77%, respectively. Single and clinical combination of RF (clusters) had an high specificity, NPV and predictive accuracy for the specific etiologies (syndromes/metabolic/infiltrative disorders associated with HCM). / Conclusions: An extensive diagnostic work up, focused on analysis of specific diagnostic RF in patients with unexplained LVH facilitates a clinical diagnosis in 74% of patients with HCM

    The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

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    The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning

    Using Project-Based-Learning in a mobile application development course-An experience report

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    In this paper, we report the experience gained in a Mobile Application Development course. We involved students in Computer Science at the University of Salerno, who in teams had to conduct a project. The goal of this project was to design and develop applications (or simply app) for Android-based devices. The adopted teaching approach was based on Project-Based-Learning and enhanced collaboration and competition. Collaboration took place among members of the same team (intra-team), while competition among different teams of students (extra-team). To allow intra-team collaboration, students used GitHub as Computer-Supported-Collaborative-Learning tool. It provided support for implicit and explicit communication among members in each team and for distributed revision control and management of software artifacts (e.g., source code and requirements models). Developed apps underwent a final public competition prized by IT managers of national and international software companies. This is how we implemented extra-team competition. IT managers expressed a positive judgment on both studentsŚł competition and developed apps. Also, students provided very good feedback on used teaching approach and support GitHub provided

    On the Use of Requirements Measures to Predict Software Project and Product Measures in the Context of Android Mobile Apps: a Preliminary Study

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    In this paper, we study the value of software project and product measures in the context of Android mobile apps. In particular, we focus on the effort to develop mobile apps and the number of graphical components in these apps. Estimation models are based on information from requirements specification documents (e.g., Number of actors, number of use cases, and number of classes). We have used a dataset containing information on 23 Android apps and employed a stepwise linear regression to build estimation models. The predictions have been compared with those obtained considering models built on software measures (e.g., Number of classes, number of files, and number of line of code). The results suggest that the measures from the artifacts produced in requirements engineering process are not worse predictors than those measures from source code. That is, requirements measures can effectively employed to estimate software project and product measures of a mobile app and estimations can be done early in the software development process

    Mobile App Development and Management: Results from a Qualitative Investigation

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    We conducted a qualitative study to investigate the main aspects related to the development and management of applications (or apps) for smart and mobile devices. Is investigation is composed of two main steps and its context is the so ware industry. In the rst step, we interviewed so ware managers with experience in the context of app development and management. Is part of our study can be intended as explorative because we used its outcomes to plan and execute the second step of our study, namely a survey with so ware professionals. From this survey, we obtained a number of ndings that we can summarize as follows: (i) app development is mostly done by junior developers, (ii) agile methodologies and cross-platform development frameworks are largely adopted even if there are no approaches and frameworks considered the best, (iii) support for testing is considered inadequate, (iv) fragmentation of so ware and hardware is perceived an important concern, and (v) app development is considered di erent from the development of web/desktop applications. Based on our ndings, we highlight areas that require more a ention from the research and the industry

    Risk Stratification of Sudden Cardiac Death in Patients with Heart Failure: An update

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    Heart failure (HF) is a complex clinical syndrome in which structural/functional myocardial abnormalities result in symptoms and signs of hypoperfusion and/or pulmonary or systemic congestion at rest or during exercise. More than 80% of deaths in patients with HF recognize a cardiovascular cause, with most being either sudden cardiac death (SCD) or death caused by progressive pump failure. Risk stratification of SCD in patients with HF and preserved (HFpEF) or reduced ejection fraction (HFrEF) represents a clinical challenge. This review will give an update of current strategies for SCD risk stratification in both HFrEF and HFpEF.Heart failure (HF) is a complex clinical syndrome in which structural/functional myocardial abnormalities result in symptoms and signs of hypoperfusion and/or pulmonary or systemic congestion at rest or during exercise. More than 80% of deaths in patients with HF recognize a cardiovascular cause, with most being either sudden cardiac death (SCD) or death caused by progressive pump failure. Risk stratification of SCD in patients with HF and preserved (HFpEF) or reduced ejection fraction (HFrEF) represents a clinical challenge. This review will give an update of current strategies for SCD risk stratification in both HFrEF and HFpEF
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