Internal Medicine Resident McGill University Montréal, Nova Scotia, Canada
Background: Myocardial infarction (MI) occurs when cardiac cells lack sufficient oxygen, leading to intracellular changes and eventual necrosis and death. However, differentiating type 1 myocardial infarction (T1MI) from type 2 myocardial infarction (T2MI) can be challenging based on clinical variables alone. We aimed to explore the utility of novel and traditional biomarkers to discriminate between T1MI and T2MI, and provide additional prognostic information.
METHODS AND RESULTS: A systematic review of observational studies and randomized controlled trials that examined the discriminatory or prognostic roles of either traditional cardiac biomarkers or non-traditional biomarkers was undertaken. Data sources included PubMed, SCOPUS, Web of Science, Embase, and ClinicalTrials.gov and were last searched on November 15, 2024. All study types evaluating the ability of biomarkers to help discriminate between T1MI and T2MI and the prognostic utility of these identified biomarkers are reported.
28 studies with 15,892 individuals with T2MI were included. Of 12 studies that examined traditional cardiac biomarkers (troponin, creatinine kinase, and b-type natriuretic peptide), the ability to discriminate between T1MI and T2MI ranged from an area under the curve (AUC) of 0.61-0.71. Patients with T2MI exhibited significantly lower baseline values, peaks, and relative changes across all traditional cardiac biomarkers, however, with only fair discrimination. Studies that added traditional cardiac biomarkers to clinical variables (n = 4) demonstrated a diagnostic accuracy AUC of 0.71-0.82. The prognostic value of these biomarkers was infrequently assessed (n=4) and inconsistently demonstrated a correlation with subsequent cardiovascular events. Studies including non-traditional biomarkers (n=12) demonstrated that various markers of inflammation (CRP, procalcitonin), hemodynamic stress (MR-proANP, myosin-binding protein-C), and endothelial dysfunction (CT-proET1) generally demonstrate fair diagnostic accuracy. However, when combined in a multi biomarker model (with or without clinical variables), can achieve excellent discriminatory ability (AUC 0.82-0.92). CRP was consistently elevated in T2MI, and the CRP/troponin ratio had high specificity (90%) in discriminating between T2MI over T1MI. Among studies exploring non-traditional biomarkers, prognostic utility was infrequently assessed.
Conclusion: Integrating novel biomarkers, metabolomic profiles and proteomic profiles in clinical assessments may aid in the diagnosis and prognostication of T2MI. Identifying these novel biomarkers is crucial for improving diagnostic accuracy and guiding treatment strategies to optimize patient outcomes with T2MI.
