Diagnostic performance of clinical likelihood models of obstructive coronary artery disease to predict myocardial perfusion defects.

AIMS: Clinical likelihood (CL) models are designed based on a reference of coronary stenosis in patients with suspected obstructive coronary artery disease (CAD). However, a reference standard of a myocardial perfusion defects (MPD) could be more appropriate.We aimed to investigate the ability of the 2019 European Society of Cardiology pre-test probability (ESC-PTP), the risk factor-weighted (RF-CL) and coronary artery calcium score-weighted (CACS-CL) models to diagnose MPDs. METHODS AND RESULTS: Symptomatic stable de novo chest pain patients (n = 3374) underwent coronary computed tomography angiography (CTA) and subsequent myocardial perfusion imaging by single photon emission tomography (SPECT), positron emission tomography (PET) or cardiac magnetic resonance (CMR). For all modalities, MPD was defined as coronary CTA with suspected stenosis and stress-perfusion abnormality in ≥2 segments. The ESC-PTP was calculated based on age, sex and symptom typicality, and the RF-CL and CACS-CL additionally included a number of risk factors and CACS.In total, 219/3374 (6.5%) patients had a MPD. Both the RF-CL and CACS-CL classified substantially more patients to low CL (<5%) of obstructive CAD compared to the ESC-PTP (32.5% and 54.1% vs. 12.0%, p < 0.001) with preserved low prevalences of MPD (<2% for all models). Compared to the ESC-PTP (AUC 0.74 (0.71-0.78), the discrimination of having a MPD was higher for the CACS-CL (AUC 0.88 (0.86-0.91), p < 0.001) while similar for the RF-CL model (AUC 0.73 (0.70-0.76), p = 0.32). CONCLUSIONS: Compared to basic CL models, the RF-CL and CACS-CL models improve down-classification of patients to a very low-risk group with low prevalence of MPD