Impact of using the 2024 ESC guideline-recommended method to estimate the likelihood of obstructive coronary disease - a cardiac CT study
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Rita Barbosa Sousa1, Maria Rita Lima1, Pedro M Lopes1
1Department of Cardiology, Hospital Santa Cruz, Unidade Local de Saúde de Lisboa Ocidental, Carnaxide, Lisbon, Portugal.
Introduction:
The 2024 ESC guidelines on chronic coronary syndromes integrated cardiovascular risk factors to estimate the pre-test probability (PTP) of obstructive coronary artery disease (CAD). Additionally, coronary artery calcium score (CACS) was proposed to reclassify patients with low PTP. We aimed to assess the impact of these new recommendations.
Methods:
Single-center cross-sectional study including 1595 patients undergoing coronary computed tomography angiography (CCTA) for suspected CAD. Obstructive CAD was defined as ≥50% stenosis on CCTA, with reclassification based on downstream invasive or non-invasive test results when available. Discrimination, calibration, and reclassification were evaluated.
Results:
Obstructive CAD prevalence was 14.0% (n = 223). Compared to the 2019 ESC-PTP, 2024 ESC-PTP showed improved discrimination [C-statistics of 0.76 (95%CI: 0.74-0.78) vs 0.74 (95%CI: 0.72-0.77), p = 0.042]. Regarding calibration, the 2019 ESC-PTP overestimated the likelihood of CAD (intercept -0.23, 95%CI: -0.38 to -0.09), while the 2024 ESC-PTP underestimated it (intercept 0.26, 95%CI: 0.11 to 0.41). The 2024 ESC-PTP reclassified 47.3% (n = 755) of patients, with 97.2% (n = 734) moving to a lower PTP category. Using CACS in patients with low PTP by the 2024 ESC-PTP (n = 617) would reclassify 41.3% (n = 255) to very low PTP. Of these, 1.6% (n = 4) had obstructive CAD.
Conclusions:
The 2024 ESC-PTP model, calibrated to obstructive CAD defined by invasive coronary angiography, demonstrates slightly improved discrimination, but appears to underestimate the likelihood of CAD when evaluated against CCTA-defined disease. These guideline recommendations could obviate further testing in approximately half of the population, at the cost of 2% missed diagnoses.
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