[The prognostication and diagnostic of acute coronary syndrome according informative parameters.]

Area of Science:

• Cardiology
• Clinical Diagnostics
• Biomarker Research

Background:

• Acute coronary syndrome (ACS) presents a significant medical challenge due to high mortality and diagnostic complexity.
• The diagnostic utility of laboratory biomarkers and mathematical models for ACS prognostication remains underexplored.
• Accurate prediction of non-ST-elevation ACS is crucial for timely intervention and improved patient outcomes.

Purpose of the Study:

• To assess the informativeness of laboratory blood biomarkers for prognostication of acute coronary syndrome without ST elevation.
• To develop and validate a predictive model for non-ST-elevation ACS using laboratory data.
• To enhance diagnostic accuracy and prognostic capabilities for ACS.

Main Methods:

• Analysis of 155 patients diagnosed with acute coronary syndrome.
• Utilized step-by-step regression analysis for prognostication.
• Measured peripheral blood levels of troponin T, creatine kinase-MB, natriuretic peptide, lactate dehydrogenase-1, and lactate dehydrogenase-2.

Main Results:

• Identified troponin T, creatine kinase-MB, and natriuretic peptide as key informative laboratory biomarkers.
• A regression model incorporating these three biomarkers demonstrated high accuracy in prognostication.
• Lactate dehydrogenase isoenzymes (LDH-1, LDH-2) were also analyzed for diagnostic relevance.

Conclusions:

• Troponin T, creatine kinase-MB, and natriuretic peptide are highly informative for predicting acute coronary syndrome without ST elevation.
• The developed regression model offers a reliable tool for accurate ACS prognostication.
• Further research can refine these biomarkers for broader clinical application in ACS management.