Cost-effectiveness and diagnostic accuracy of focused cardiac ultrasound in the pre-participation screening of athletes: the SPORT-FoCUS study.

Aims: The role of pre-participation screening (PPS) modalities in preventing sudden cardiac death (SCD) in athletes is debated due to a high false-positive rate. Focused cardiac ultrasound (FoCUS) has shown higher sensitivity and specificity, but its cost-effectiveness remains uncertain. This study aimed to determine the diagnostic performance and cost-effectiveness of FoCUS use in PPS.

Description, Organization, and Individual Postgraduate Perspectives of One Italian School of Anesthesia and Intensive Care.

Introduction: The study aims to describe the organization of one accredited school of Anesthesia and Intensive Care of University of Modena and Reggio Emilia, Italy. The analysis of the post-graduation period aims to measure the time-to-first job, the perceived challenges, what postgraduate residents choose as first employ, and the overall satisfaction rating of a cohort of residents completing their training until 2017 with the usual and standard training program.

Methods: We collected organization and administrative records of the five-year program of the A-IC School of 4 cohorts of residents who joined from 2009 to 2012 and we performed a survey.

How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic.

The COVID-19 pandemic has worked as a catalyst, pushing governments, private companies, and healthcare facilities to design, develop, and adopt innovative solutions to control it, as is often the case when people are driven by necessity. After 18 months since the first case, it is time to think about the pros and cons of such technologies, including artificial intelligence-which is probably the most complex and misunderstood by non-specialists-in order to get the most out of them, and to suggest future improvements and proper adoption. The aim of this narrative review was to select the relevant papers that directly address the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2: environmental measures; acquisition and sharing of knowledge in the general population and among clinicians; development and management of drugs and vaccines; remote psychological support of patients; remote monitoring, diagnosis, and follow-up; and maximization and rationalization of human and material resources in the hospital environment.

Prediction of 28-day mortality in critically ill patients with COVID-19: Development and internal validation of a clinical prediction model.

Background: COVID-19 pandemic has rapidly required a high demand of hospitalization and an increased number of intensive care units (ICUs) admission. Therefore, it became mandatory to develop prognostic models to evaluate critical COVID-19 patients.

Materials And Methods: We retrospectively evaluate a cohort of consecutive COVID-19 critically ill patients admitted to ICU with a confirmed diagnosis of SARS-CoV-2 pneumonia.

A Machine Learning Approach for Mortality Prediction in COVID-19 Pneumonia: Development and Evaluation of the Piacenza Score.

Background: Several models have been developed to predict mortality in patients with COVID-19 pneumonia, but only a few have demonstrated enough discriminatory capacity. Machine learning algorithms represent a novel approach for the data-driven prediction of clinical outcomes with advantages over statistical modeling.

Objective: We aimed to develop a machine learning-based score-the Piacenza score-for 30-day mortality prediction in patients with COVID-19 pneumonia.

Scattering in Terms of Bohmian Conditional Wave Functions for Scenarios with Non-Commuting Energy and Momentum Operators.

Without access to the full quantum state, modeling quantum transport in mesoscopic systems requires dealing with a limited number of degrees of freedom. In this work, we analyze the possibility of modeling the perturbation induced by non-simulated degrees of freedom on the simulated ones as a transition between single-particle pure states. First, we show that Bohmian conditional wave functions (BCWFs) allow for a rigorous discussion of the dynamics of electrons inside open quantum systems in terms of single-particle time-dependent pure states, either under Markovian or non-Markovian conditions.

[Late occurrence of pulmonary embolsim in SARS-CoV-2 pneumonia: a case series].

Several studies suggested that the acute phase of SARS-CoV-2 infection may be associated with a hypercoagulable state and increased risk for venous thromboembolism but the incidence of thrombotic complications in the late phase of the disease is currently unknown. The present article describes three cases of patients with SARS-CoV-2 pneumonia and late occurrence of pulmonary embolism. Case 1: a 57-year-old man diagnosed with pulmonary embolism and type B aortic dissection after 12 days from SARS-CoV-2 pneumonia.

Education in anesthesia: three years of online logbook implementation in an Italian school.

Background: The progress of physicians through residency training in anesthesiology can be monitored using an online logbook. The aim of this investigation was to establish how residents record clinical activities in their computerized web-based logbooks during their first years of anesthesiology training.

Methods: For this retrospective observational trial, the ESSE 3(©) digital registry of the University of Modena and Reggio Emilia, Italy was used to record all anesthesia-related activities performed by three consecutive year-groups of residents (Groups A, B and C) between 2009 and 2012.

[Thromboembolic risk in atrial fibrillation: new clinical perspectives].

Prevention of embolic complications is one of the major goals of therapeutic strategy for atrial fibrillation. The embolic risk is related to the presence and nature of underlying heart disease; furthermore cerebrovascular accidents associated with atrial fibrillation occur in a higher percentage in the elderly, representing 6.7% of the total number of cerebrovascular accidents in the 50-to-59-year-old population and 36% in the 80-to-89-year-old population.