Hyperglycemia is a frequent condition in patients with acute coronary syndromes (ACS). Hyperglycemia during ACS is caused by an inflammatory and adrenergic response to ischemic stress, when catecholamines are released and glycogenolysis induced. Although the involved pathophysiological mechanisms have not yet been fully elucidated, it is believed that hyperglycemia is associated with an increase in free fat acids (which induce cardiac arrhythmias), insulin resistance, chemical inactivation of nitric oxide and the production of oxygen reactive species (with consequent microvascular and endothelial dysfunction), a prothrombotic state, and vascular inflammation. It is also related to myocardial metabolic disorders, leading to thrombosis, extension of the damaged area, reduced collateral circulation, and ischemic preconditioning. In the last few years, several observational studies demonstrated that hyperglycemia in ACS is a powerful predictor of survival, increasing the risk of immediate and long-term complications in patients both with and without previously known diabetes mellitus. Glucose management strategies in ACS may improve outcomes in patients with hyperglycemia, perhaps by reducing inflammatory and clotting mediators, by improving endothelial function and fibrinolysis and by reducing infarct size. Recent clinical trials of insulin in ACS have resulted in varying levels of benefit, but the clinical benefit of an aggressive treatment with insulin is yet unproved.

No abstract

In 2019, the Innovative Medicines Initiative (IMI) funded the ConcePTION project-Building an ecosystem for better monitoring and communicating safety of medicines use in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generation-with the vision that there is a societal obligation to rapidly reduce uncertainty about the safety of medication use in pregnancy and breastfeeding. The present paper introduces the set of concepts used to describe the European data sources involved in the ConcePTION project and illustrates the ConcePTION Common Data Model (CDM), which serves as the keystone of the federated ConcePTION network. Based on data availability and content analysis of 21 European data sources, the ConcePTION CDM has been structured with six tables designed to capture data from routine healthcare, three tables for data from public health surveillance activities, three curated tables for derived data on population (e.g., observation time and motherchild linkage), plus four metadata tables. By its first anniversary, the ConcePTION CDM has enabled 13 data sources to run common scripts to contribute to major European projects, demonstrating its capacity to facilitate effective and transparent deployment of distributed analytics, and its potential to address questions about utilization, effectiveness, and safety of medicines in special populations, including during pregnancy and breastfeeding, and, more broadly, in the general population.

No abstract

No abstract