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Coronary artery disease (CAD) is one of the major causes of mortality and morbidity worldwide, with a high socioeconomic impact. Currently, various guidelines and recommendations have been published about chronic coronary syndromes (CCS). According to the recent European Society of Cardiology guidelines on chronic coronary syndrome, a multimodal imaging approach is strongly recommended in the evaluation of patients with suspected CAD. Today, in the current practice, non-invasive imaging methods can assess coronary anatomy through coronary computed tomography angiography (CCTA) and/or inducible myocardial ischemia through functional stress testing (stress echocardiography, cardiac magnetic resonance imaging, single photon emission computed tomography—SPECT, or positron emission tomography—PET). However, recent trials (ISCHEMIA and REVIVED) have cast doubt on the previous conception of the management of patients with CCS, and nowadays it is essential to understand the limitations and strengths of each imaging method and, specifically, when to choose a functional approach focused on the ischemia versus a coronary anatomy-based one. Finally, the concept of a pathophysiology-driven treatment of these patients emerged as an important goal of multimodal imaging, integrating ‘anatomical’ and ‘functional’ information. The present review aims to provide an overview of non-invasive imaging modalities for the comprehensive management of CCS patients.

Coronary artery disease is still a major cause of death and morbidity worldwide. In the setting of chronic coronary disease, demonstration of inducible ischemia is mandatory to address treatment. Consequently, scientific and technological efforts were made in response to the request for non-invasive diagnostic tools with better sensitivity and specificity. To date, clinicians have at their disposal a wide range of stress-imaging techniques. Among others, stress cardiac magnetic resonance (S-CMR) and computed tomography perfusion (CTP) techniques both demonstrated their diagnostic efficacy and prognostic value in clinical trials when compared to other non-invasive ischemia-assessing techniques and invasive fractional flow reserve measurement techniques. Standardized protocols for both S-CMR and CTP usually imply the administration of vasodilator agents to induce hyperemia and contrast agents to depict perfusion defects. However, both methods have their own limitations, meaning that optimizing their performance still requires a patient-tailored approach. This review focuses on the characteristics, drawbacks, and future perspectives of these two techniques.

Background Early-life respiratory tract infections might affect chronic obstructive respiratory diseases, but conclusive studies from general populations are lacking. Our objective was to examine if children with early-life respiratory tract infections had increased risks of lower lung function and asthma at school age.Methods We used individual participant data of 150 090 children primarily from the EU Child Cohort Network to examine the associations of upper and lower respiratory tract infections from age 6 months to 5 years with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, forced expiratory flow at 75% of FVC (FEF75%) and asthma at a median (range) age of 7 (4–15) years.Results Children with early-life lower, not upper, respiratory tract infections had a lower school-age FEV1, FEV1/FVC and FEF75% (z-score range: −0.09 (95% CI −0.14– −0.04) to −0.30 (95% CI −0.36– −0.24)). Children with early-life lower respiratory tract infections had a higher increased risk of school-age asthma than those with upper respiratory tract infections (OR range: 2.10 (95% CI 1.98–2.22) to 6.30 (95% CI 5.64–7.04) and 1.25 (95% CI 1.18–1.32) to 1.55 (95% CI 1.47–1.65), respectively). Adjustment for preceding respiratory tract infections slightly decreased the strength of the effects. Observed associations were similar for those with and without early-life wheezing as a proxy for early-life asthma.Conclusions Our findings suggest that early-life respiratory tract infections affect development of chronic obstructive respiratory diseases in later life, with the strongest effects for lower respiratory tract infections.

Background: Sleep disturbance has been associated with poor prognosis in patients with acute coronary syndrome (ACS). This study examined the course of sleep disturbance and associated factors in patients with ACS who were followed for one year. Methods: Study participants were 180 patients (mean age 59.6 years, 81.7% men) with ACS admitted to a tertiary hospital to undergo acute coronary intervention. Sleep disturbance was interviewer-assessed at admission (n = 180), at 3 months (n = 146), and at 12 months (n = 101) using the Jenkins Sleep Scale (JSS)-4, with a total of 414 assessments over one year. Random linear mixed regression models were used to evaluate the relationship between sociodemographic factors, cardiac diseases severity, perceived distress during ACS, comorbidities, medication, health behaviors, and sleep disturbance over time. Results: At admission, 3 months, and 12 months, 56.7%, 49.3%, and 49.5% of patients, respectively, scored above the mean value for sleep disturbance in the general population (JSS-4 score ≥5). There was a significant decrease in continuous JSS-4 scores over time [estimate (SE) = -0.211 (0.074), p = 0.005]. Female sex [0.526 (0.206), p = 0.012], greater fear of dying [0.074 (0.026), p = 0.004], helplessness during ACS [0.062 (0.029), p = 0.034], and a history of depression [0.422 (0.171), p = 0.015] were independently associated with higher JSS-4 scores over time. Conclusion: Despite a decrease from admission to 3 months, sleep disturbance is prevalent in the first year after ACS. Female sex, depression history, and distress during ACS identify patients at increased risk of developing persistent sleep disturbance and may inform interventions to prevent sleep disturbance.

In this paper we propose a continuous time model for modeling the dynamics of a commodity price. In particular, we focus on the term structure of future prices under the assumption that the underlying asset price follows an exponential CARMA(p, q) model where the driving noise is a Time Changed Brownian motion. The use of CARMA models well suits a market where if a shock occurs its effect does not vanish gradually but it may induce a more complex dynamics for the asset. The obtained formula is strictly connected to the cumulant generating function of the subordinator process in the Time Changed Brownian Motion.

In this paper we study the numerical stability of the closed form solution of the classical portfolio optimization problem. Such explicit solution relies upon a technical symmetric square matrix A, whose dimension is 2 independently from the number of assets considered in the portfolio. We observe that the computation of A involves the problem's possible sources of instability, which are essentially related to the estimation and the inversion of the covariance matrix and to the relative scaling of the problem constraints equations, namely the budget and the portfolio expected return constraints respectively. We propose a theoretical approach to minimize the condition number of A by rescaling both its rows and columns with an optimal constant. Using this result, we substitute the original ill-posed optimization problem with an equivalent well-posed formulation of it. Finally, through a simple empirical example, we illustrate the validity of the proposed approach showing considerable improvements in the stability of the closed form solution.

A large number of studies has demonstrated that abnormalities of coronary microcirculation may be responsible for both acute and chronic cardiac ischemic syndromes. In clinical practice the microvascular origin of myocardial ischemia and angina is usually considered in patients who are found to have normal or near-normal coronary arteries at angiography. In this article, we review the diagnostic approach to patients with suspected coronary microvascular dysfunction as a cause of ischemic syndromes and also suggest a classification of chronic and acute microvascular coronary ischemic syndrome, including myocardial infarction with normal coronary arteries.

This proposal puts forth a methodology that can be used to derive optimal asset allocations for general forms of Loss Aversion, explicitly accounting for the real risks associated with large-scale investments. The portfolio problem is solved by a stochastic algorithm based on Particle Swarm Optimization, which permits the inclusion of transaction costs and other constraints faced by investors and fund managers. An empirical study compares the proposed approach to traditional strategies in terms of portfolio composition, downside protection in adverse market conditions and global performance.

Car accident causes are relevant both for insurance companies as well as for policy makers. The former are interested into the dynamics of the accidents in order to evaluate responsibilities, the latter to foster good driving behavior for the sake of social benefit, too. By using a large set of medical and police reports, and by exploiting Natural Language Processing techniques we aim at grasping latent information useful to classify them according to the relevance of their content.

Starting from the Markowitz’s formula for a portfolio we compute the solutions for three structures of dependencies and use acyclic directed graphs (DAGs) to represent the structures. Same levels of returns and volatilities are adopted for all assets in order to focus just on the role of correlations. We start with two structures of dependencies among three assets. We then compute the optimal solution for a four assets portfolio whose DAG is the superposition of the previous patterns.