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Updated: Oct 21, 2025

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

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Diagnostic prediction model in subjects with low-risk unstable angina pectoris/non-ST segment Elevation Myocardial

I Dakota1, M Munawar, R Pranata

  • 1Department of Cardiology and Vascular Medicine, National Cardiovascular Center Harapan Kita, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia. iwandakota@gmail.com.

European Review for Medical and Pharmacological Sciences
|September 6, 2021
PubMed

Insights

This study developed a prediction model using non-invasive tests and risk factors to detect coronary artery disease (CAD) severity in low-risk unstable angina pectoris/Non-ST Segment Elevation Myocardial Infarction (UAP/NSTEMI) patients. The model, including nitric oxide (NO), carotid intima-media thickness (CIMT), smoking history, and age-gender, shows diagnostic validity.

Area of Science:

  • Cardiology and Cardiovascular Disease Research
  • Diagnostic Model Development
  • Non-invasive Cardiovascular Assessment

Background:

  • Coronary artery disease (CAD) diagnosis in low-risk patients with unstable angina pectoris (UAP)/Non-ST Segment Elevation Myocardial Infarction (NSTEMI) often requires invasive procedures.
  • Developing accurate non-invasive prediction models can improve patient management and reduce healthcare costs.
  • Identifying key non-invasive markers and cardiovascular risk factors is crucial for early CAD detection.

Purpose of the Study:

  • To construct and validate a prediction model for CAD presence and severity.
  • The model is based on non-invasive examinations and cardiovascular risk factors.
  • The target population is patients presenting with low-risk UAP/NSTEMI.

Main Methods:

  • A cross-sectional study involving 104 patients (60 men, 44 women; mean age 52.3 years).
  • Two prediction models were developed using non-invasive data: Model 1 (NO, CIMT, smoking history, Age-Gender) and Model 2 (CIMT, smoking history, Age-Gender).
  • Model performance was evaluated against coronary angiography, the gold standard, using AUC, sensitivity, and specificity.

Main Results:

  • The main model (NO, CIMT, smoking history, Age-Gender) achieved an AUC of 74.5% (95% CI: 64.9-84.1), sensitivity of 72.7%, and specificity of 65.0%.
  • The alternative model (CIMT, smoking history, Age-Gender) showed an AUC of 69.0% (95% CI: 58.9-79.1), sensitivity of 65.9%, and specificity of 56.7%.
  • Both models demonstrated similar diagnostic prediction performance (p = 0.70).

Conclusions:

  • Nitric oxide (NO), carotid intima-media thickness (CIMT), smoking history, and age-gender are valuable diagnostic predictors for CAD in low-risk UAP/NSTEMI patients.
  • The developed non-invasive model offers a promising tool for assessing CAD presence and severity.
  • These findings support the use of non-invasive markers in the initial evaluation of suspected CAD.
Abstract

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