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Validation of ESC Pre-Test Probability Model for Obstructive CAD
Quick Takes
- The 2019-ESC-PTP model performs well and better than other models.
- Among adults with higher pre-test probability (PTP), the 2019-ESC-PTP model was superior to other models.
- Such risk stratification can assist providers and patients regarding the evaluation of symptoms suggestive of CAD.
Study Questions:
How does the 2019 European Society of Cardiology (ESC) pre-test probability (PTP) model for suspected coronary artery disease (CAD) compare to earlier models?
Methods:
2019-ESC-PTP, 2013-ESC-PTP, and CAD Consortium basic PTP scores were calculated using a cohort from the Danish population-based quality assurance database and the Western Denmark Heart Registry. All patients underwent first-time coronary computed tomography angiography (CTA) for suspected CAD between 2008–2017 at 13 hospitals. Adults with a prior diagnosis of CAD were excluded. The cohort represents 55% of the total Danish population. The reference standard was a combined endpoint of CTA and invasive coronary angiography (ICA) with obstructive CAD defined at ICA as a ≥50% diameter stenosis or fractional flow reserve ≤0.80 when performed. The 2019-ESC-PTP, 2013-ESC-PTP, and CAD Consortium basic PTP scores were calculated based on age, sex, and symptoms.
Results:
Of the 42,328 identified patients, obstructive CAD using a combined endpoint of CTA and ICA was diagnosed in 3,718 (8.8%) patients and ruled out in 38,610 (91.2%) patients. The calculated median 2019-ESC-PTP for obstructive CAD at coronary CTA was 11% (interquartile range, 6.0–19.0). The 2019-ESC-PTP and CAD Consortium basic scores classified substantially more patients into the low PTP groups (PTP <15%) than did the 2013-ESC-PTP (64% and 65% vs. 16%, p < 0.001). With the 2019-ESC-PTP model, there was a small overestimation of the prevalence of obstructive CAD in all patients regardless of the PTP. Similarly, the CAD Consortium basic model overestimated the CAD probability, most markedly in higher PTP groups. The 2013-ESC-PTP substantially overestimated the prevalence of obstructive CAD in all patients regardless of the PTP. Compared to the other models, the 2019-ESC-PTP model, area under the curve (AUC) 75.7 (74.9–76.5), had slightly higher accuracy than the 2013-ESC-PTP model, AUC 75.3 (74.5–76.1) (p < 0.05), and slightly lower accuracy than the CAD Consortium basic model, AUC 76.2 (75.4–76.9) (p < 0.01). Net reclassification indices using cut-offs 5%, 15%, and 50% with the 2019-ESC-PTP model as reference were -4.27 (-5.45 to -3.04) and 13.46 (12.3 to 14.9) for the 2013-ESC-PTP and the CAD Consortium basic models, respectively.
Conclusions:
The investigators concluded that the new 2019-ESC-PTP model is well-calibrated and superior to the previously recommended models in predicting obstructive stenosis detected by a combined endpoint of CTA and ICA.
Perspective:
The 2019-ESC-PTP model appears to perform with higher accuracy as compared to other PTP models. This was particularly true for higher PTP. Further validation in different cohorts, including non-western cohorts, is warranted.
Clinical Topics: Acute Coronary Syndromes, Invasive Cardiovascular Angiography and Intervention, Noninvasive Imaging, Prevention, Atherosclerotic Disease (CAD/PAD), Interventions and ACS, Interventions and Coronary Artery Disease, Interventions and Imaging, Angiography, Computed Tomography, Nuclear Imaging
Keywords: Acute Coronary Syndrome, Cardiology Interventions, Constriction, Pathologic, Coronary Angiography, Coronary Artery Disease, Coronary Stenosis, Diagnostic Imaging, Fractional Flow Reserve, Myocardial, Secondary Prevention, Tomography, Emission-Computed
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