Bedside-Friendly Prediction for Presence of Post-Myocardial lnfarction Systolic Dysfunction Using Multimarker Panel: Integrating Salivary Diagnostics into Clinical Practice

BACKGROUND AND OBJECTIVES We investigated if a combination of plasma or salivary interleukin-2 (IL-2), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), transforming growth factor-beta (TGF-β), and troponin can improve estimation of the pretest probability of the left ventricular systolic dysfunction (LVSD). SUBJECTS AND METHODS Eighty patients with newly-diagnosed myocardial infarction (MI) were echocardiographically examined for LVSD (ejection fraction ≤40%). Measurements included traditional MI risk factors, plasma and salivary concentrations of troponin, IL-2, IL-6, TNF-α, and TGF-β. With the LVSD as the outcome variable, we developed logistic regression models, starting with a basic model incorporating traditional risk factors and consecutively adding salivary and plasma biomarkers. Models were compared using several criteria, including (but not limited to) C statistic (discrimination) and net reclassification improvement index (NRI). RESULTS APART FROM TROPONIN, PLASMA, AND SALIVARY VALUES OF THE BIOMARKERS WERE CORRELATED: spearman's ρ was 0.19 (p=0.088) for troponin, 0.36 (p=0.001) for IL-2, 0.74 (p<0.001) for IL-6, 0.61 (p<0.001) for TNF-α, and 0.65 (p<0.001) for TGF-β. The predictive performances of the basic model for estimating the pretest probability of the presence of LVSD considerably improved when cytokines were added (salivary added: C-statistic from 0.77 to 0.82 and NRI 77%; plasma added: C-statistic to 0.80 and NRI 134%). CONCLUSION Multiple biomarkers added diagnostic value to the standard risk factors for predicting the presence of post-MI LVSD.