Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-26T11:58:12.726Z Has data issue: false hasContentIssue false

PD41 Use Of High-Sensitivity Cardiac Troponin Assays In Real-Practice Within Emergency Departments

Published online by Cambridge University Press:  03 January 2019

Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Introduction:

Acute myocardial infarction (AMI) is one of the leading causes of death and disability worldwide. The European Society of Cardiology Guidelines have established a new definition of myocardial infarction and have strengthened the central role of cardiac troponins in cardiology diagnostics for rule-in and rule-out of non ST-elevation myocardial infarction (NSTEMI). High-sensitivity cardiac troponin I assays (hsTnI) should increase diagnostic sensitivity, and a shorter interval for ruling-in and ruling-out AMI. This analysis aims to provide an overview of the clinical, economic, organizational and ethical impact of the use of hsTnI in clinical practice of Emergency Departments (ED) in Italy.

Methods:

HsTnl for rule-in and rule-out of AMI in the ED is being evaluated using the EUnetHTA Core Model® framework for health technology assessment. The hsTnI HTA assessment will be completed with real-world evidence derived from a multicenter observational study which has been designed to be conducted in 12 Italian EDs, enrolling 6000 patients with chest pain of suspected cardiac origin, aiming to provide data from the Italian context on clinical, organizational and economic aspects of the use of the test in the ED. Endpoints of the study include: time lapses related to diagnosis, admission, treatment and discharge of patients; number of tests performed; and number of patients diagnosed with AMI.

Results:

Initial results from a literature review confirm the usefulness of the hsTnI assay in diagnosing AMI. Generated real-world data will be collected, analyzed and integrated to existing evidence to assess the utility of the test in real contexts, providing details relevant for organizational aspects of the use of the test in the ED.

Conclusions:

The use of hsTnl could improve diagnosis of AMI by allowing a faster ruling-in or ruling-out, and reducing inappropriate hospitalizations. Furthermore, this technology could represent an opportunity to reduce overall costs for the healthcare system.

Type
Poster Display Presentations
Copyright
Copyright © Cambridge University Press 2018