In order to bring you the best possible user experience, this site uses Javascript. If you are seeing this message, it is likely that the Javascript option in your browser is disabled. For optimal viewing of this site, please ensure that Javascript is enabled for your browser.

The free consultation period for this content is over.

It is now only available year-round to ESC Professional Members, Fellows of the ESC, and Young combined Members

Direct comparison of the safety and efficacy of two rule-out strategies for acute myocardial infarction:2h-algorithm versus combination of 1h-algorithm and undetectable levels at presentation

Session Poster session 5

Speaker Maria Rubini Gimenez

Event : ESC Congress 2015

  • Topic : coronary artery disease, acute coronary syndromes, acute cardiac care
  • Sub-topic : Acute Cardiac Care
  • Session type : Poster Session

Authors : M Rubini Gimenez (Basel,CH), R Twerenbold (Basel,CH), K Wildi (Bad Krozingen,DE), C Puelacher (Bad Krozingen,DE), S Osswald (Bad Krozingen,DE), C Mueller (Bad Krozingen,DE)

Authors:
M. Rubini Gimenez1 , R. Twerenbold1 , K. Wildi2 , C. Puelacher2 , S. Osswald2 , C. Mueller2 , 1University Hospital Basel, Department of Cardiology - Basel - Switzerland , 2Heart Centre Bad Krozingen, Dept. of Cardiology - Bad Krozingen - Germany ,

Citation:
European Heart Journal ( 2015 ) 36 ( Abstract Supplement ), 758-759

Purpose: Addressing the increasingly recognized, yet unmet clinical need for rapid rule-out of acute myocardial infarction (AMI), several novel strategies have been developed. Due to the lack of direct comparisons in the same dataset, selection of the best strategy for clinical practice is challenging. We therefore aimed to directly compare the safety and efficacy of two previously defined strategies: LOD (Undetectable levels of high-sensitivity cardiac troponin (hs-cTn) T at presentation) in combination with hs-cTnT 1h-algorithm versus hs-cTnT 2h-algorithm.

Methods: In a prospective international multicentre diagnostic study enrolling 1697 patients presenting with suspected AMI to the emergency department, the final diagnosis of AMI was adjudicated by two independent cardiologists using all available clinical information including serial hs-cTnT concentrations. Safety was quantified as the negative predictive value (NPV) for AMI in the rule-out zone of the respective rule-out strategies. Efficacy was quantified as the percentage of the overall cohort assigned to the rule-out zone by the respective strategy. The 2h-algoritm was defined as 0h and 2h values <14ng/l and Δ0–2h<4ng/l; The combination LOD and 1h algorithm was defined as LOD <5ng/L or 0h<12ng/l and Δ0–1h<3ng/l. As both strategies should only be applied once ST-elevation MI (STEMI) has been excluded by the initial ECG, STEMI patients were excluded from the analysis.

Results: Acute myocardial infarction was the final diagnosis in 16% of patients. The safety was very high and comparable with both algorithms (2h algorithm: NPV 100%, 95% CI 99.7–100% versus LOD+1h-Algorithm: NPV 99.9%, 95% CI 99.5–100%, p=ns).

Regarding efficacy, 2h-algorithm allowed rule-out in 64% of patients versus 60% with 1h-algorithm +LOD (p=0.018).

Conclusion: Both investigated rule-out strategies allow a safe rule-out of AMI. The 2h-algorithm has a slightly higher efficacy; however the combination of LOD+1h-algorithm has the obvious advantage of allowing rule-out already after 1h.

Get your access to resources

Join now
  • 1ESC Professional Members – access all ESC Congress resources 
  • 2ESC Association Members (Ivory, Silver, Gold) – access your Association’s resources
  • 3Under 40 or in training - with a Combined Membership, access all resources
Join now

Our sponsors

ESC 365 is supported by Bayer, Boehringer Ingelheim and Lilly Alliance, Bristol-Myers Squibb and Pfizer Alliance, Novartis Pharma AG and Vifor Pharma in the form of educational grants. The sponsors were not involved in the development of this platform and had no influence on its content.

logo esc

Our mission: To reduce the burden of cardiovascular disease

Who we are