Multi-Marker Approach with the Use of Biochip Cardiac Array Technology for Early Diagnosis in Patients with Acute

Marcin Sawicki1, Grazyna Sypniewska1, Magdalena Krintus1

  • 1Department of Laboratory Medicine, University of Nicolaus Copernicus , Bydgoszcz, Poland.

EJIFCC
|September 30, 2016
PubMed

Insights

Early detection of acute coronary syndrome (ACS) is improved using a multi-marker strategy. Heart-fatty acid binding protein (H-FABP) shows high early efficacy, enhancing diagnosis alongside sensitive troponin assays.

Area of Science:

  • Cardiology
  • Biomarker Discovery
  • Diagnostic Technologies

Background:

  • Acute coronary syndrome (ACS) diagnosis is challenging, requiring rapid risk stratification.
  • CK-MB mass and troponins have prolonged release patterns, complicating early chest pain origin identification.
  • A multi-marker approach may improve differential diagnosis of ACS.

Purpose of the Study:

  • To evaluate the efficacy of a multi-marker strategy using biochip array technology for early ACS identification.
  • To compare the diagnostic performance of various cardiac biomarkers shortly after symptom onset.

Main Methods:

  • 42 patients with suspected ACS were studied.
  • Serum biomarkers were measured on admission (≤6 hours) and 6 hours later.
  • Cardiac troponin I (cTnI) was measured by a routine assay; six cardiac markers, including heart-fatty acid binding protein (H-FABP), were assessed via biochip array.

Main Results:

  • H-FABP showed high early efficacy (90.5%) in ACS detection, outperforming myoglobin and CK-MB mass.
  • H-FABP sensitivity reached 100% for non-ST-elevation myocardial infarction (NSTEMI)/ST-elevation myocardial infarction (STEMI).
  • Diagnostic efficacy of troponin, myoglobin, and CK-MB mass improved significantly within 12 hours, but not for unstable angina (UA) early on.

Conclusions:

  • A multi-marker strategy incorporating H-FABP and sensitive troponin enhances early ACS diagnosis and decision-making.
  • Biochip cardiac array technology offers a powerful tool for clinical ACS detection.
  • Early risk stratification for UA remains a challenge with the current panel.
Abstract

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