Korean Circulation Journal

The Korean Society of Cardiology (대한심장학회)
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Bedside-Friendly Prediction for Presence of Post-Myocardial lnfarction Systolic Dysfunction Using Multimarker Panel: Integrating Salivary Diagnostics into Clinical Practice

  • Assareh, Ahmadreza (Cardiovascular Research Center, Ahvaz Jundishapur University of Medical Science) ;
  • Haybar, Habib (Cardiovascular Research Center, Ahvaz Jundishapur University of Medical Science) ;
  • Yoosefi, Hojjat (Department of Periodontal, Ahvaz Jundishapur University of Medical science) ;
  • Bozorgmanesh, Mohammadreza (Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences)
  • Published : 2013.04.30
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Abstract

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-${\alpha}$), transforming growth factor-beta (TGF-${\beta}$), 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 ${\leq}40%$). Measurements included traditional MI risk factors, plasma and salivary concentrations of troponin, IL-2, IL-6, TNF-${\alpha}$, and TGF-${\beta}$. 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 ${\rho}$ 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-${\alpha}$, and 0.65 (p<0.001) for TGF-${\beta}$. 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.

Keywords

References

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