Comparing the Modified History, Electrocardiogram, Age, Risk Factors, and Troponin Score and Coronary Artery Disease...

Area of Science:

• Cardiology
• Medical Diagnostics
• Risk Stratification

Background:

• Accurate prediction of obstructive coronary artery disease (CAD) is crucial for managing patients with acute chest pain.
• Existing risk assessment tools, such as the History, Electrocardiogram, Age, Risk factors, and Troponin (HEART) score, require validation against newer models.

Purpose of the Study:

• To compare the predictive performance of the HEART score and the clinical coronary artery disease consortium (CADC) model.
• To evaluate their ability to identify obstructive CAD and predict 30-day major adverse cardiovascular events (MACE).

Main Methods:

• A study of 1981 patients with no known CAD presenting with acute chest pain and negative initial troponin/ECG.
• Classification of chest pain (typical, atypical, nonanginal) for the HEART score's history component.
• Comparison of C-statistics for predicting obstructive CAD and 30-day MACE using both models.

Main Results:

• The CADC model demonstrated a higher C-statistic for predicting obstructive CAD (0.792 vs. 0.747, P=0.0005).
• Both models showed similar performance in predicting 30-day MACE (C-statistics 0.850 for CADC vs. 0.820 for HEART, P=0.11).
• Both models effectively identified low-risk patients, with <1% 30-day MACE observed in patients predicted as low-risk by either score.

Conclusions:

• The CADC model is superior to the HEART score in predicting obstructive CAD.
• Both the HEART score and CADC model are effective in safely stratifying low-risk patients, minimizing 30-day MACE.
• These findings support the use of the CADC model for enhanced diagnostic accuracy in suspected CAD.