An algorithm for rule-in and rule-out of acute myocardial infarction using a novel troponin I assay
2017 (English)In: Heart, ISSN 1355-6037, E-ISSN 1468-201X, Vol. 103, no 2, 125-131 p.Article in journal (Refereed) Published
Objective To derive and validate a hybrid algorithm for rule-out and rule-in of acute myocardial infarction based on measurements at presentation and after 2 hours with a novel cardiac troponin I (cTnI) assay. Methods The algorithm was derived and validated in two cohorts (605 and 592 patients) from multicentre studies enrolling chest pain patients presenting to the emergency department (ED) with onset of last episode within 12 hours. The index diagnosis and cardiovascular events up to 30 days were adjudicated by independent reviewers. Results In the validation cohort, 32.6% of the patients were ruled out on ED presentation, 6.1% were ruled in and 61.3% remained undetermined. A further 22% could be ruled out and 9.8% ruled in, after 2 hours. In total, 54.6% of the patients were ruled out with a negative predictive value (NPV) of 99.4% (95% CI 97.8% to 99.9%) and a sensitivity of 97.7% (95% CI 91.9% to 99.7%); 15.8% were ruled in with a positive predictive value (PPV) of 74.5% (95% CI 64.8% to 82.2%) and a specificity of 95.2% (95% CI 93.0% to 96.9%); and 29.6% remained undetermined after 2 hours. No patient in the rule-out group died during the 30-day follow-up in the two cohorts. Conclusions This novel two-step algorithm based on cTnI measurements enabled just over a third of the patients with acute chest pain to be ruled in or ruled out already at presentation and an additional third after 2 hours. This strategy maximises the speed of rule-out and rule-in while maintaining a high NPV and PPV, respectively.
Place, publisher, year, edition, pages
2017. Vol. 103, no 2, 125-131 p.
Cardiac and Cardiovascular Systems
IdentifiersURN: urn:nbn:se:uu:diva-316032DOI: 10.1136/heartjnl-2016-309951ISI: 000392214500010PubMedID: 27486143OAI: oai:DiVA.org:uu-316032DiVA: diva2:1076906
FunderEU, FP7, Seventh Framework ProgrammeAstraZeneca