Using tabu search to configure support vector regression for effort estimation

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

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

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

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

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

Evidence for a relationship between Leishmania load and clinical manifestations.

Visceral leishmaniasis (VL) is a life-threatening disease of medical, social and economic importance in endemic areas. Dogs are the main reservoir of Leishmaniainfantum. In this study, the authors investigated a group of 56 natural infected dogs to establish the relationship between parasite load and various clinical forms of leishmaniasis. The sick dogs were monitored at the beginning from clinical and physiological point of view. Leishmania load was measured by real-time PCR assay on whole blood samples and lymph node aspirates, collected at the time of diagnosis. Our results indicate that a higher quantity of Leishmania DNA was found in the lymph nodes of dogs characterized by maximum clinical score. This interesting finding indicates the presence of a positive relationship between Leishmania load and clinical manifestations in dogs showing a severe clinical form of leishmaniasis

Leishmania DNA quantification by real-time PCR in naturally infected dogs treated with miltefosine.

A new drug that has just become available in India for treatment of human visceral leishmaniasis (VL) is miltefosine, an alkyphospholipid that was originally developed as an oral antineoplastic agent. Miltefosine is not only directly toxic for Leishmania parasite, but it also enhances both T cell and macrophage activation and production of microbicidal reactive nitrogen and oxygen intermediates. It is highly effective in the treatment of Leishmania infection in mice and human beings. However, adverse effects in dogs treated with miltefosine have been reported, but there are no data on the efficacy of this drug for the treatment of canine visceral leishmaniasis (CVL). The aim of this study was to use a real-time PCR assay to monitor the Leishmania load in the blood samples and lymph node aspirates of 18 naturally infected dogs before and after treatment with miltefosine (2 mg/kg for 30 days). The results of our study showed that the therapy with miltefosine shows a drastic and progressive reduction of parasite load in lymph node aspirates, but does not suppress the parasite in lymph nodes. In all dogs the real-time PCR assay demonstrated an irregular presence of parasites in blood. Therefore, blood does not seem a suitable substrate for the purpose of quantifying Leishmania DNA

Applying support vector regression for web effort estimation using a cross-company dataset

Support Vector Regression (SVR) is a new generation of Machine Learning algorithms, suitable for predictive data modeling problems. The objective of this paper is to investigate the effectiveness of SVR for Web effort estimation, in particular when dealing with a cross-company dataset. To gain a deeper insight on the method, we carried out an empirical study using four kernels for SVR, namely linear, polynomial, Gaussian, and sigmoid. Moreover, we used two variables' preprocessing strategies (normalization and logarithmic), and two different dependent variables (effort and inverse effort). As a result, SVR was applied using six different configurations for each kernel. As for the dataset, we employed the Tukutuku database, which is widely adopted in Web effort estimation studies. A hold-out approach was adopted to evaluate the prediction accuracy for all the configurations, using two training sets, each containing data on 130 projects randomly selected, and two test sets, each containing the remaining 65 projects. As benchmark, SVR-based predictions were also compared to predictions obtained using Manual StepWise Regression, Case-Based Reasoning, and Bayesian Networks. Our results suggest that SVR performed well, since on the first hold-out, the linear kernel with a logarithmic transformation of variables provided significantly superior prediction accuracy than all the other techniques, while for the second hold-out, the Gaussian kernel achieved significantly superior predictions than all other techniques, except for Manual StepWise Regression