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Comparison of two biomarker only algorithms for...
Journal article

Comparison of two biomarker only algorithms for early risk stratification in patients with suspected acute coronary syndrome

Abstract

BACKGROUND: We developed a biomarker algorithm encompassing the clinical chemistry score (CCS; which includes the combination of a random glucose concentration, an estimated glomerular filtration rate and high-sensitivity cardiac troponin; hs-cTn) with the Ortho Clinical Diagnostics hs-cTnI assay (CCS-serial) and compared it to the cutoffs derived from Ortho Clinical Diagnostics 0/1 h (h) algorithm for 7-day myocardial infarction (MI) or cardiovascular (CV)-death. METHODS: The study cohort was an emergency department (ED) population (n = 906) with symptoms suggestive of acute coronary syndrome (ACS) who had two Ortho hs-cTnI results approximately 3 h apart. Diagnostic parameters (sensitivity/specificity/negative predictive value; NPV/positive predictive value; PPV) were derived for the CCS-serial and the 0/1 h algorithm for 7-day MI/CV-death. A safety analysis was performed for patients in the rule-out arms of the algorithms for 30-day MI/death. RESULTS: The CCS-serial algorithm yielded 100% sensitivity/NPV (32% low-risk) and 95.7% specificity/65% PPV (11% high-risk). The 0/1 h algorithm-cutoffs yielded sensitivity/NPV/specificity/PPV of 97.8%/99.4%/91.3%/50%, which classified 38% of patients as low-risk and 16% of patients as high-risk. Four patients (1.2%) in the 0/1 h algorithm-cutoff rule-out arm had a 30-day MI/death outcome as compared to zero patients in the CCS-serial rule-out arm (p = 0.06). CONCLUSION: Both the CCS-serial and 0/1 h algorithm cutoffs yield high NPVs with a similar proportion of patients identified as low-risk. These data may be useful for sites who are unable to collect samples at 0/1 h in the emergency department.

Authors

Kavsak PA; Mondoux SE; Ma J; Sherbino J; Hill SA; Clayton N; Mehta SR; Griffith LE; McQueen M; Devereaux PJ

Journal

International Journal of Cardiology, Vol. 319, , pp. 140–143

Publisher

Elsevier

Publication Date

November 15, 2020

DOI

10.1016/j.ijcard.2020.06.066

ISSN

0167-5273

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