From the Journals

Algorithm boosts MACE prediction in patients with chest pain

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Algorithms to guide chest pain management

In patients presenting at the emergency department with chest pain, it’s important not only to diagnose acute myocardial infarction, but also to predict short-term risk of cardiac events to help guide management. This thoughtful and comprehensive analysis is the largest study assessing the added value of clinical and ECG assessment to the prognostication by high-sensitivity cardiac troponin algorithms in patients evaluated for chest pain. It reinforces the accuracy of hs-cTn at presentation and after 1 hour (ESC hs-cTn 0/1 h) algorithms to predict AMI and 30-day AMI-related events.

It is important to note that if unstable angina had been included as a major adverse cardiac event, the study would have found that the extended algorithm performs better than the hs-cTn 0/1 h algorithm in the prediction of this endpoint.

Germán Cediel, MD, is from Hospital Universitari Germans Trias i Pujol in Spain, Alfredo Bardají, MD, is from the Joan XXIII University Hospital in Spain, and José A. Barrabés, MD, is from Vall d’Hebron University Hospital and Research Institute, Universitat Autònoma de Barcelona. The comments are adapted from an editorial (J Am Coll Cardiol. 2019 Aug 20. doi: 10.1016/j.jacc.2019.05.065). The authors declared support from Instituto de Salud Carlos III, Spain, cofinanced by the European Regional Development Fund, and declared consultancies and educational activities with the pharmaceutical sector.


 

FROM JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY

Adding electrocardiogram findings and clinical assessment to high-sensitivity cardiac troponin measurements in patients presenting with chest pain could improve predictions of their risk of 30-day major adverse cardiac events, particularly unstable angina, research suggests.

Investigators reported outcomes of a prospective study involving 3,123 patients with suspected acute myocardial infarction. The findings are in the Journal of the American College of Cardiology.

The aim of the researchers was to validate an extended algorithm that combined the European Society of Cardiology’s high-sensitivity cardiac troponin measurement at presentation and after 1 hour (ESC hs-cTn 0/1 h algorithm) with clinical assessment and ECG findings to aid prediction of major adverse cardiac events (MACE) within 30 days.

The clinical assessment involved the treating ED physician’s use of a visual analog scale to assess the patient’s pretest probability for an acute coronary syndrome (ACS), with a score above 70% qualifying as high likelihood.

The researchers found that the ESC hs-cTn 0/1 h algorithm alone triaged significantly more patients toward rule-out for MACE than did the extended algorithm (60% vs. 45%, P less than .001). This resulted in 487 patients being reclassified toward “observe” by the extended algorithm, and among this group the 30-day MACE rate was 1.1%.

However, the 30-day MACE rates were similar in the two groups – 0.6% among those ruled out by the ESC hs-cTn 0/1 h algorithm alone and 0.4% in those ruled out by the extended algorithm – resulting in a similar negative predictive value.

“These estimates will help clinicians to appropriately manage patients triaged toward rule-out according to the ESC hs-cTnT 0/1 h algorithm, in whom either the [visual analog scale] for ACS or the ECG still suggests the presence of an ACS,” wrote Thomas Nestelberger, MD, of the Cardiovascular Research Institute Basel (Switzerland) at the University of Basel, and coinvestigators.

The ESC hs-cTn 0/1 h algorithm also ruled in fewer patients than did the extended algorithm (16% vs. 26%, P less than .001), giving it a higher positive predictive value.

When the researchers added unstable angina to the major adverse cardiac event outcome, they found the ESC hs-cTn 0/1 h algorithm had a lower negative predictive value and a higher negative likelihood ratio compared with the extended algorithm for patients ruled out, but a higher positive predictive value and positive likelihood ratio for patients ruled in.

“Our findings corroborate and extend previous research regarding the development and validation of algorithms for the safe and effective rule-out and rule-in of MACE in patients with symptoms suggestive of AMI,” the authors wrote.

This study was supported by the Swiss National Science Foundation, the Swiss Heart Foundation, the European Union, the Cardiovascular Research Foundation Basel, the University Hospital Basel, Abbott, Beckman Coulter, Biomerieux, BRAHMS, Roche, Nanosphere, Siemens, Ortho Diagnostics, and Singulex. Several authors reported grants and support from the pharmaceutical sector.

SOURCE: Nestelberger T et al. J Am Coll Cardiol. 2019 Aug 20. doi: 10.1016/j.jacc.2019.06.025.

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