Cargando…

Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?

Chest pain accounts for approximately 6% of Emergency Department (ED) attendances and is the most common reason for emergency hospital admission. For many years, our approach to diagnosis has required patients to stay in hospital for at least 6–12 h to undergo serial biomarker testing. As less than...

Descripción completa

Detalles Bibliográficos
Autor principal: Body, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6107971/
https://www.ncbi.nlm.nih.gov/pubmed/30191187
http://dx.doi.org/10.1016/j.tjem.2018.05.005
_version_ 1783350063915859968
author Body, Richard
author_facet Body, Richard
author_sort Body, Richard
collection PubMed
description Chest pain accounts for approximately 6% of Emergency Department (ED) attendances and is the most common reason for emergency hospital admission. For many years, our approach to diagnosis has required patients to stay in hospital for at least 6–12 h to undergo serial biomarker testing. As less than one fifth of the patients undergoing investigation actually has an acute coronary syndrome (ACS), there is tremendous potential to reduce unnecessary hospital admissions. Recent advances in diagnostic technology have improved the efficiency of care pathways. Decision aids such as the Thrombolysis in Myocardial Infarction (TIMI) risk score and the History, Electrocardiogram, Age, Risk factors and Troponin (HEART) score enable rapid ‘rule out’ of ACS within hours of patients arriving in the ED. With high sensitivity cardiac troponin (hs-cTn) assays, approximately one third of patients can have ACS ‘ruled out’ with a single blood test, and up to two thirds could have an acute myocardial infarction ‘ruled out’ with a second sample taken after as little as 1 h. Building on those recent advances, this paper presents an overview of the principles behind the development of the Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid. This clinical prediction model could be used to ‘rule out’ and ‘rule in’ ACS following a single blood test and to calculate the probability of ACS for every patient. The future potential of this approach is then addressed, including practical applications of artificial intelligence, shared decision making, near-patient testing and personalized medicine.
format Online
Article
Text
id pubmed-6107971
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-61079712018-09-06 Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes? Body, Richard Turk J Emerg Med Review Article Chest pain accounts for approximately 6% of Emergency Department (ED) attendances and is the most common reason for emergency hospital admission. For many years, our approach to diagnosis has required patients to stay in hospital for at least 6–12 h to undergo serial biomarker testing. As less than one fifth of the patients undergoing investigation actually has an acute coronary syndrome (ACS), there is tremendous potential to reduce unnecessary hospital admissions. Recent advances in diagnostic technology have improved the efficiency of care pathways. Decision aids such as the Thrombolysis in Myocardial Infarction (TIMI) risk score and the History, Electrocardiogram, Age, Risk factors and Troponin (HEART) score enable rapid ‘rule out’ of ACS within hours of patients arriving in the ED. With high sensitivity cardiac troponin (hs-cTn) assays, approximately one third of patients can have ACS ‘ruled out’ with a single blood test, and up to two thirds could have an acute myocardial infarction ‘ruled out’ with a second sample taken after as little as 1 h. Building on those recent advances, this paper presents an overview of the principles behind the development of the Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid. This clinical prediction model could be used to ‘rule out’ and ‘rule in’ ACS following a single blood test and to calculate the probability of ACS for every patient. The future potential of this approach is then addressed, including practical applications of artificial intelligence, shared decision making, near-patient testing and personalized medicine. Elsevier 2018-07-13 /pmc/articles/PMC6107971/ /pubmed/30191187 http://dx.doi.org/10.1016/j.tjem.2018.05.005 Text en © 2018 The Emergency Medicine Association of Turkey. Production and hosting by Elsevier B.V. on behalf of the Owner. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Article
Body, Richard
Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?
title Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?
title_full Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?
title_fullStr Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?
title_full_unstemmed Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?
title_short Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?
title_sort acute coronary syndromes diagnosis, version 2.0: tomorrow's approach to diagnosing acute coronary syndromes?
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6107971/
https://www.ncbi.nlm.nih.gov/pubmed/30191187
http://dx.doi.org/10.1016/j.tjem.2018.05.005
work_keys_str_mv AT bodyrichard acutecoronarysyndromesdiagnosisversion20tomorrowsapproachtodiagnosingacutecoronarysyndromes