ESC pre-test probability estimates for obstructive coronary artery disease: can they be used in Brazil?

Fernanda Erthal1,2, Ronaldo Lima2,3, Filipe Penna2

  • 1Department of Medicine (Cardiology), Universidade Federal Fluminense, Rua Marques de Parana 303, 24033-900 Niteroi, Brazil.

Insights

The European Society of Cardiology (ESC) model better estimates pre-test probability (PTP) for coronary artery disease (CAD) in Brazil compared to the Diamond-Forrester (DF) model. This finding is crucial for accurate CAD diagnosis in the Brazilian population.

Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Public Health

Background:

  • Coronary artery disease (CAD) is a major global cause of death.
  • Accurate pre-test probability (PTP) estimation is vital for diagnosing CAD.
  • Traditional scoring systems like Diamond-Forrester (DF) and European Society of Cardiology (ESC) are used for PTP, but their population-specific applicability may vary.

Purpose of the Study:

  • To compare the performance of the DF and ESC PTP scoring systems.
  • To evaluate these models within the Brazilian population context.
  • To assess PTP estimation accuracy using coronary computed tomography angiography (CCTA) as a reference standard.

Main Methods:

  • Calculated PTP for obstructive CAD using DF and ESC scores in 409 symptomatic patients without known CAD.
  • Patients underwent CCTA between 2019 and 2022.
  • Compared predicted PTP from both models against actual CAD prevalence.

Main Results:

  • The DF model tended to overestimate CAD prevalence across various age and symptom groups.
  • The ESC model demonstrated better alignment with the actual prevalence of CAD.
  • CCTA served as the reference standard for validating PTP predictions.

Conclusions:

  • The ESC PTP model is more suitable for PTP determination in the Brazilian population.
  • The DF model's overestimation highlights potential limitations in this demographic.
  • Accurate PTP estimation using validated models like ESC is essential for appropriate CAD management.
Abstract

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