Catholic University of the Sacred Heart

About: Catholic University of the Sacred Heart is a education organization based out in Milan, Lombardia, Italy. It is known for research contribution in the topics: Population & Health care. The organization has 13592 authors who have published 31048 publications receiving 853961 citations.

The COVID-19 Pandemic and Physical Activity

Abstract: The SARS-CoV-2-caused COVID-19 pandemic has resulted in a devastating threat to human society in terms of health, economy, and lifestyle. Although the virus usually first invades and infects the lung and respiratory track tissue, in extreme cases, almost all major organs in the body are now known to be negatively impacted often leading to severe systemic failure in some people. Unfortunately, there is currently no effective treatment for this disease. Pre-existing pathological conditions or comorbidities such as age are a major reason for premature death and increased morbidity and mortality. The immobilization due to hospitalization and bed rest and the physical inactivity due to sustained quarantine and social distancing can downregulate the ability of organs systems to resist to viral infection and increase the risk of damage to the immune, respiratory, cardiovascular, musculoskeletal systems and the brain. The cellular mechanisms and danger of this “second wave” effect of COVID-19 to the human body, along with the effects of aging, proper nutrition, and regular physical activity, are reviewed in this article.

International standardization of diagnostic criteria for vasospastic angina

Abstract: The Coronary Vasomotion Disorders International Study Group (COVADIS) was established to develop international standards for the diagnostic criteria of coronary vasomotor disorders. The first symposium held on the 4-5 September 2013 addressed the criteria for vasospastic angina, which included the following (i) nitrate-responsive angina, (ii) transient ischaemic electrocardiogram changes, and (iii) documented coronary artery spasm. Adoption of these diagnostic criteria will improve the clinical diagnosis of this condition and facilitate research in this field.

Predicting outcomes in radiation oncology--multifactorial decision support systems

Abstract: With the emergence of individualized medicine and the increasing amount and complexity of available medical data, a growing need exists for the development of clinical decision-support systems based on prediction models of treatment outcome. In radiation oncology, these models combine both predictive and prognostic data factors from clinical, imaging, molecular and other sources to achieve the highest accuracy to predict tumour response and follow-up event rates. In this Review, we provide an overview of the factors that are correlated with outcome-including survival, recurrence patterns and toxicity-in radiation oncology and discuss the methodology behind the development of prediction models, which is a multistage process. Even after initial development and clinical introduction, a truly useful predictive model will be continuously re-evaluated on different patient datasets from different regions to ensure its population-specific strength. In the future, validated decision-support systems will be fully integrated in the clinic, with data and knowledge being shared in a standardized, instant and global manner.