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Objective: Validation studies of the 2019 European Society of Cardiology pretest probability model (ESC-PTP) for coronary artery disease (CAD) report that 35%-40% of patients have low pretest probability (ESC-PTP 5% to <15%). Acoustic detection of coronary stenoses could potentially improve clinical likelihood stratification. Aims were to (1) investigate the diagnostic performance of an acoustic-based CAD score and (2) study the reclassification potential of a dual likelihood strategy by the ESC-PTP and a CAD score., Methods: Consecutive patients (n=1683) with stable angina symptoms referred for coronary CT angiography (CTA) underwent heart sound analyses by an acoustic CAD-score device. All patients with ≥50% luminal stenosis in any coronary segment at coronary CTA were referred to investigation with invasive coronary angiography (ICA) with fractional flow reserve (FFR).A predefined CAD-score cut-off ≤20 was used to rule out obstructive CAD., Results: In total, 439 patients (26%) had ≥50% luminal stenosis on coronary CTA. The subsequent ICA with FFR showed obstructive CAD in 199 patients (11.8%). Using the ≤20 CAD-score cut-off for obstructive CAD rule-out, sensitivity was 85.4% (95% CI 79.7 to 90.0), specificity 40.4% (95% CI 37.9 to 42.9), positive predictive value 16.1% (95% CI 13.9 to 18.5) and negative predictive value 95.4% (95% CI 93.4 to 96.9) in all patients. Applying the cut-off in ESC-PTP 5% to <15% patients, 316 patients (48%) were down-classified to very-low likelihood. The obstructive CAD prevalence was 3.5% in this group., Conclusion: In a large contemporary cohort of patients with low CAD likelihood, the additional use of an acoustic rule-out device showed a clear potential to downgrade likelihood and could supplement current strategies for likelihood assessment to avoid unnecessary testing., Trial Registration Number: NCT03481712., Competing Interests: Competing interests: SW acknowledges support from the Novo Nordisk Foundation Clinical Emerging Investigator grant (NNF21OC0066981). MB discloses advisory board participation for Novo Nordisk, AstraZeneca, Pfizer, Boeringer Ingelheim, Bayer, Sanofi, Novartis, Amgen, CLS-Behring and Acarix. The remaining authors have nothing to declare., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background Substantial differences exist between different guideline-recommended pretest probability (PTP) models for the detection of obstructive coronary artery disease (CAD). This study was performed to study the performance of the 2021 American Heart Association/American College of Cardiology (AHA/ACC) guideline-recommended PTP (AHA/ACC-PTP) model in assessing the likelihood of obstructive CAD compared with previously proposed models. Methods and Results Symptomatic patients (N=50 561) referred for coronary computed tomography angiography were included. The reference standard was invasive coronary angiography with optional fractional flow reserve measurements. The AHA/ACC-PTP values based on sex and age were calculated and compared with the 2019 European Society of Cardiology guideline PTP values based on sex, age, and symptoms as well as the risk factor-weighted clinical likelihood values based on sex, age, symptoms, and risk factors. The AHA/ACC-PTP maximum values overestimated by a factor of 2.6 the actual prevalence of CAD. Compared with the AHA/ACC-PTP model (area under the receiver-operating curve, 71.5 [95% CI, 70.7-72.2]), inclusion of typicality of symptoms in the European Society of Cardiology guideline PTP improved discrimination of CAD (area under the receiver-operating curve, 75.5 [95% CI, 74.7-76.3]). Inclusion of both symptoms and risk factors in the risk factor-weighted clinical likelihood model further improved discrimination (area under the receiver-operating curve, 77.7 [95% CI, 77.0-78.5]). The proportion of patients classified as very low PTP was lower using the AHA/ACC-PTP (5%) compared with the European Society of Cardiology guideline PTP (19%) and the risk factor-weighted clinical likelihood (49%) models. Conclusions The new AHA/ACC-PTP model overestimates the prevalence of obstructive CAD substantially if type of symptoms and risk factors are not taken into account. Inclusion of both symptoms and risk factors improves model performance and identifies more patients with very low likelihood of CAD in whom further testing can be deferred.

Aims: Estimation of pre-test probability (PTP) of disease in patients with suspected coronary artery disease (CAD) is a common challenge. Due to decreasing prevalence of obstructive CAD in patients referred for diagnostic testing, the European Society of Cardiology suggested a new PTP (2019-ESC-PTP) model. The aim of this study was to validate that model., Methods and Results: Symptomatic patients referred for coronary computed tomography angiography (CTA) due to suspected CAD in a geographical uptake area of 3.3 million inhabitants were included. 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. Of the 42 328 identified patients, coronary stenosis was detected in 8.8% using the combined endpoint. 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). Using the combined endpoint as reference, calibration of the 2019-ESC-PTP model was superior to the 2013-ESC-PTP and CAD Consortium basic score., Conclusion: 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., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2020. For permissions, please email: journals.permissions@oup.com.)

Background: Coronary computed tomography angiography (CTA) is the preferred primary diagnostic modality when examining patients with low to intermediate pre-test probability of coronary artery disease (CAD). Only 20-30% of these have potentially obstructive CAD. Because of the relatively poor positive predictive value of coronary CTA, unnecessary invasive coronary angiographies (ICAs) are conducted with the costs and risks associated with the procedure. Hence, an optimized diagnostic CAD algorithm may reduce the numbers of ICAs not followed by revascularization. The Dan-NICAD 2 study has 3 equivalent main aims: (1) To examine the diagnostic precision of a sound-based diagnostic algorithm, The CADScor®System (Acarix A/S, Denmark), in patients with a low to intermediate pre-test risk of CAD referred to a primary examination by coronary CTA. We hypothesize that the CADScor®System provides better stratification prior to coronary CTA than clinical risk stratification scores alone. (2) To compare the diagnostic accuracy of 3T cardiac magnetic resonance imaging (3T CMRI), 82 rubidium positron emission tomography ( 82 Rb-PET), and CT-derived fractional flow reserve (FFR CT ) in patients where obstructive CAD cannot be ruled out by coronary CTA using ICA fractional flow reserve (FFR) as reference standard. (3) To compare the diagnostic performance of quantitative flow ratio (QFR) and ICA-FFR in patients with low to intermediate pre-test probability of CAD using 82 Rb-PET as reference standard., Methods: Dan-NICAD 2 is a prospective, multicenter, cross-sectional study including approximately 2,000 patients with low to intermediate pre-test probability of CAD and without previous history of CAD. Patients are referred to coronary CTA because of symptoms suggestive of CAD, as evaluated by a cardiologist. Patient interviews, sound recordings, and blood samples are obtained in connection with the coronary CTA. If coronary CTA does not rule out obstructive CAD, patients will be examined by 3T CMRI 82 Rb-PET, FFR CT , ICA, and FFR. Reference standard is ICA-FFR. Obstructive CAD is defined as an FFR ≤0.80 or as high-grade stenosis (>90% diameter stenosis) by visual assessment. Diagnostic performance will be evaluated as sensitivity, specificity, predictive values, likelihood ratios, calibration, and discrimination. Enrolment started January 2018 and is expected to be completed by June 2020. Patients are followed for 10 years after inclusion., Discussion: The results of the Dan-NICAD 2 study are expected to contribute to the improvement of diagnostic strategies for patients suspected of CAD in 3 different steps: risk stratification prior to coronary CTA, diagnostic strategy after coronary CTA, and invasive wireless QFR analysis as an alternative to ICA-FFR., (Copyright © 2019 Elsevier Inc. All rights reserved.)