Predicting the presence of coronary plaques featuring high-risk characteristics using polygenic risk scores and targeted proteomics in patients with suspected coronary artery disease.

BACKGROUND: The presence of coronary plaques with high-risk characteristics is strongly associated with adverse cardiac events beyond the identification of coronary stenosis. Testing by coronary computed tomography angiography (CCTA) enables the identification of high-risk plaques (HRP). Referral for CCTA is presently based on pre-test probability estimates including clinical risk factors (CRFs); however, proteomics and/or genetic information could potentially improve patient selection for CCTA and, hence, identification of HRP. We aimed to (1) identify proteomic and genetic features associated with HRP presence and (2) investigate the effect of combining CRFs, proteomics, and genetics to predict HRP presence. METHODS: Consecutive chest pain patients (n = 1462) undergoing CCTA to diagnose obstructive coronary artery disease (CAD) were included. Coronary plaques were assessed using a semi-automatic plaque analysis tool. Measurements of 368 circulating proteins were obtained with targeted Olink panels, and DNA genotyping was performed in all patients. Imputed genetic variants were used to compute a multi-trait multi-ancestry genome-wide polygenic score (GPSMult). HRP presence was defined as plaques with two or more high-risk characteristics (low attenuation, spotty calcification, positive remodeling, and napkin ring sign). Prediction of HRP presence was performed using the glmnet algorithm with repeated fivefold cross-validation, using CRFs, proteomics, and GPSMult as input features. RESULTS: HRPs were detected in 165 (11%) patients, and 15 input features were associated with HRP presence. Prediction of HRP presence based on CRFs yielded a mean area under the receiver operating curve (AUC) ± standard error of 73.2 ± 0.1, versus 69.0 ± 0.1 for proteomics and 60.1 ± 0.1 for GPSMult. Combining CRFs with GPSMult increased prediction accuracy (AUC 74.8 ± 0.1 (P = 0.004)), while the inclusion of proteomics provided no significant improvement to either the CRF (AUC 73.2 ± 0.1, P = 1.00) or the CRF + GPSMult (AUC 74.6 ± 0.1, P = 1.00) models, respectively. CONCLUSIONS: In patients with suspected CAD, incorporating genetic data with either clinical or proteomic data improves the prediction of high-risk plaque presence. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02264717 (September 2014).

Impact of Absolute Myocardial Blood Flow Quantification on the Diagnostic Performance of PET-Based Perfusion Scans Using 82Rubidium.

BACKGROUND: Guidelines propose the inclusion of quantitative measurements from 82Rubidium positron emission tomography (RbPET) to discriminate obstructive coronary artery disease (CAD). However, the effect on diagnostic accuracy is unknown. The aim was to investigate the optimal RbPET reading algorithm for improved identification of obstructive CAD. METHODS: Prospectively enrolled patients (N=400) underwent RbPET and invasive coronary angiography with fractional flow reserve and quantitative coronary angiography. Quantitative measurements (myocardial blood flow (MBF), MBF reserve, transient ischemic dilatation) by RbPET were step-wisely added to a qualitative assessment by the summed stress score based on their diagnostic accuracy of obstructive CAD by invasive coronary angiography-fractional flow reserve. Prespecified cutoffs were summed stress score ≥4, hyperemic MBF 2.00 mL/g per min, and MBF reserve 1.80, respectively. Hemodynamically obstructive CAD was defined as >90% diameter stenosis or invasive coronary angiography-fractional flow reserve ≤0.80, and sensitivity analyses included a clinically relevant reference of anatomically severe CAD (>70% diameter stenosis by invasive coronary angiography-quantitative coronary angiography). RESULTS: Hemodynamically obstructive CAD was present in 170/400 (42.5%) patients. Stand-alone summed stress score showed a sensitivity and specificity of 57% and 93%, respectively, while hyperemic MBF showed similar sensitivity (61%, P=0.57) but lower specificity (85%, P=0.008). With increased discrimination by receiver-operating characteristic curves (0.78 versus 0.85; P<0.001), combining summed stress score, MBF and MBF reserve showed the highest sensitivity of 77% but lower specificity of 74% (P<0.001 for both comparisons). Against anatomically severe CAD, all measures independently yielded high discrimination ≥0.90 with increased sensitivity and lower specificity by additional quantification. CONCLUSIONS: The inclusion of quantitative measurements to a RbPET read increases in the identification of obstructive CAD. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03481712.

Exercise electrocardiography for pre-test assessment of the likelihood of coronary artery disease.

OBJECTIVES: To develop a tool including exercise electrocardiography (ExECG) for patient-specific clinical likelihood estimation of patients with suspected obstructive coronary artery disease (CAD). METHODS: An ExECG-weighted clinical likelihood (ExECG-CL) model was developed in a training cohort of patients with suspected obstructive CAD undergoing ExECG. Next, the ExECG-CL model was applied in a CAD validation cohort undergoing ExECG and clinically driven invasive coronary angiography and a prognosis validation cohort and compared with the risk factor-weighted clinical likelihood (RF-CL) model for obstructive CAD discrimination and prognostication, respectively.In the CAD validation cohort, obstructive CAD was defined as >50% diameter stenosis on invasive coronary angiography. For prognosis, the endpoint was non-fatal myocardial infarction and death. RESULTS: The training cohort consisted of 1214 patients (mean age 57 years, 57% males). In the CAD (N=408; mean age 55 years, 53% males) and prognosis validation (N=3283; mean age 57 years, 57% males) cohorts, 11.8% patients had obstructive CAD and 4.4% met the endpoint. In the CAD validation cohort, discrimination of obstructive CAD was similar between the ExECG-CL and RF-CL models: area under the receiver-operating characteristic curves 83.1% (95% CIs 77.5% to 88.7%) versus 80.7% (95% CI 74.6% to 86.8%), p=0.14. In the ExECG-CL model, more patients had very low (≤5%) clinical likelihood of obstructive CAD compared with the RF-CL (42.2% vs 36.0%, p<0.01) where obstructive CAD prevalence and event risk remained low. CONCLUSIONS: ExECG incorporated into a clinical likelihood model improves reclassification of patients to a very low clinical likelihood group with very low prevalence of obstructive CAD and favourable prognosis.

External validation of novel clinical likelihood models to predict obstructive coronary artery disease and prognosis.

OBJECTIVES: The risk factor-weighted and coronary artery calcium score-weighted clinical likelihood (RF-CL and CACS-CL, respectively) models improve discrimination of patients with suspected obstructive coronary artery disease (CAD). However, external validation is warranted.Compared to the 2019 European Society of Cardiology pretest probability (ESC-PTP) model, the aims were (1) to validate the RF-CL and CACS-CL models for identification of obstructive CAD and revascularisation, and (2) to investigate prognosis by CL thresholds. METHODS: Stable de novo chest pain patients (n=1585) undergoing coronary CT angiography (CTA) were investigated. Obstructive CAD was defined as >70% diameter stenosis in a major epicardial vessel on CTA. Decision of revascularisation within 120 days was based on onsite judgement. The endpoint was non-fatal myocardial infarction or cardiovascular death. The ESC-PTP was calculated based on age, sex and symptom typicality, the RF-CL additionally included number of risk factors, and the CACS-CL incorporated CACS to the RF-CL. RESULTS: Obstructive CAD was present in 386/1585 (24.4%) patients, and 91/1585 (5.7%) patients underwent revascularisation. Both the RF-CL and CACS-CL classified more patients to very-low CL (<5%) of obstructive CAD compared with the ESC-PTP model (41.4% and 52.2% vs 19.2%, p<0.001). In very-low CL patients, obstructive CAD and revascularisation prevalences (≤6% and <1%) remained similar combined with low event risk during 5.0 years follow-up. CONCLUSION: In an external validation cohort, the novel RF-CL and CACS-CL models improve categorisation to a very-low CL group with preserved prevalences of obstructive CAD, revascularisation and favourable prognosis.

Combining Polygenic and Proteomic Risk Scores With Clinical Risk Factors to Improve Performance for Diagnosing Absence of Coronary Artery Disease in Patients With de novo Chest Pain.

BACKGROUND: Patients with de novo chest pain, referred for evaluation of possible coronary artery disease (CAD), frequently have an absence of CAD resulting in millions of tests not having any clinical impact. The objective of this study was to investigate whether polygenic risk scores and targeted proteomics improve the prediction of absence of CAD in patients with suspected CAD, when added to the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) minimal risk score (PMRS). METHODS: Genotyping and targeted plasma proteomics (N=368 proteins) were performed in 1440 patients with symptoms suspected to be caused by CAD undergoing coronary computed tomography angiography. Based on individual genotypes, a polygenic risk score for CAD (PRSCAD) was calculated. The prediction was performed using combinations of PRSCAD, proteins, and PMRS as features in models using stability selection and machine learning. RESULTS: Prediction of absence of CAD yielded an area under the curve of PRSCAD-model, 0.64±0.03; proteomic-model, 0.58±0.03; and PMRS model, 0.76±0.02. No significant correlation was found between the genetic and proteomic risk scores (Pearson correlation coefficient, -0.04; P=0.13). Optimal predictive ability was achieved by the full model (PRSCAD+protein+PMRS) yielding an area under the curve of 0.80±0.02 for absence of CAD, significantly better than the PMRS model alone (P<0.001). For reclassification purpose, the full model enabled down-classification of 49% (324 of 661) of the 5% to 15% pretest probability patients and 18% (113 of 611) of >15% pretest probability patients. CONCLUSIONS: For patients with chest pain and low-intermediate CAD risk, incorporating targeted proteomics and polygenic risk scores into the risk assessment substantially improved the ability to predict the absence of CAD. Genetics and proteomics seem to add complementary information to the clinical risk factors and improve risk stratification in this large patient group. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02264717.

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. However, a reference standard for myocardial perfusion defects (MPDs) 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) model, and coronary artery calcium score-weighted (CACS-CL) model to diagnose MPDs. METHODS AND RESULTS: Symptomatic stable de novo chest pain patients (n = 3374) underwent coronary computed tomography angiography and subsequent myocardial perfusion imaging by single-photon emission computed tomography, positron emission tomography, or cardiac magnetic resonance. For all modalities, MPD was defined as coronary computed tomography angiography 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 an MPD. Both the RF-CL and the CACS-CL classified substantially more patients to low CL (<5%) of obstructive coronary artery disease compared with 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 with the ESC-PTP [area under the receiver-operating characteristic curve (AUC) 0.74 (0.71-0.78)], the discrimination of having an MPD was higher for the CACS-CL model [AUC 0.88 (0.86-0.91), P < 0.001], while it was similar for the RF-CL model [AUC 0.73 (0.70-0.76), P = 0.32]. CONCLUSION: Compared with basic CL models, the RF-CL and CACS-CL models improve down classification of patients to a very low-risk group with a low prevalence of MPD.

Coronary Artery Stenosis Evaluation by Angiography-Derived FFR: Validation by Positron Emission Tomography and Invasive Thermodilution.

BACKGROUND: Fractional flow reserve (FFR) derived from invasive coronary angiography (QFR) is promising for evaluation of intermediate coronary artery stenosis. OBJECTIVES: The authors aimed to compare the diagnostic performance of QFR and the guideline-recommended invasive FFR using 82Rubidium positron emission tomography (82Rb-PET) myocardial perfusion imaging as reference standard. METHODS: This is a prospective, observational study of symptomatic patients with suspected obstructive coronary artery disease on coronary computed tomography angiography (≥50% diameter stenosis in ≥1 vessel). All patients were referred to 82Rb-PET and invasive coronary angiography with FFR and QFR assessment of all intermediate (30%-90% diameter stenosis) stenoses. Main analyses included a comparison of the ability of QFR and FFR to identify reduced myocardial blood flow (<2 mL/g/min) during vasodilation and/or relative perfusion abnormalities (summed stress score ≥4 in ≥2 adjacent segments). RESULTS: A total of 250 patients (320 vessels) with indication for invasive physiological assessment were included. The continuous relationship of 82Rb-PET stress myocardial blood flow per 0.10 increase in FFR was +0.14 mL/g/min (95% CI: 0.07-0.21 mL/g/min) and +0.08 mL/g/min (95% CI: 0.02-0.14 mL/g/min) per 0.10 QFR increase. Using 82Rb-PET as reference, QFR and FFR had similar diagnostic performance on both a per-patient level (accuracy: 73%; 95% CI: 67%-79%; vs accuracy: 71%; 95% CI: 64%-78%) and per-vessel level (accuracy: 70%; 95% CI: 64%-75%; vs accuracy: 68%; 95% CI: 62%-73%). The per-vessel feasibility was 84% (95% CI: 80%-88%) for QFR and 88% (95% CI: 85%-92%) for FFR by intention-to-diagnose analysis. CONCLUSIONS: With 82Rb-PET as reference modality, the wire-free QFR solution showed similar diagnostic accuracy as invasive FFR in evaluation of intermediate coronary stenosis. (DAN-NICAD - Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease; NCT02264717).

Second-Line Myocardial Perfusion Imaging to Detect Obstructive Stenosis: Head-to-Head Comparison of CMR and PET.

BACKGROUND: Guidelines recommend verification of myocardial ischemia by selective second-line myocardial perfusion imaging (MPI) following a coronary computed tomography angiography (CTA) with suspected obstructive coronary artery disease (CAD). Head-to-head data on the diagnostic performance of different MPI modalities in this setting are sparse. OBJECTIVES: The authors sought to compare, head-to-head, the diagnostic performance of selective MPI by 3.0-T cardiac magnetic resonance (CMR) and 82rubidium positron emission tomography (RbPET) in patients with suspected obstructive stenosis at coronary CTA using invasive coronary angiography (ICA) with fractional flow reserve (FFR) as reference. METHODS: Consecutive patients (n = 1,732, mean age: 59.1 ± 9.5 years, 57.2% men) referred for coronary CTA with symptoms suggestive of obstructive CAD were included. Patients with suspected stenosis were referred for both CMR and RbPET and subsequently ICA. Obstructive CAD was defined as FFR ≤0.80 or >90% diameter stenosis by visual assessment. RESULTS: In total, 445 patients had suspected stenosis on coronary CTA. Of these, 372 patients completed both CMR, RbPET and subsequent ICA with FFR. Hemodynamically obstructive CAD was identified in 164 of 372 (44.1%) patients. Sensitivities for CMR and RbPET were 59% (95% CI: 51%-67%) and 64% (95% CI: 56%-71%); P = 0.21, respectively, and specificities 84% (95% CI: 78%-89%) and 89% (95% CI: 84%-93%]); P = 0.08, respectively. Overall accuracy was higher for RbPET compared with CMR (73% vs 78%; P = 0.03). CONCLUSIONS: In patients with suspected obstructive stenosis at coronary CTA, CMR, and RbPET show similar and moderate sensitivities but high specificities compared with ICA with FFR. This patient group represents a diagnostic challenge with frequent mismatch between advanced MPI tests and invasive measurements. (Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease 2 [Dan-NICAD 2]; NCT03481712).

Likelihood reclassification by an acoustic-based score in suspected coronary artery disease.

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.

Validation and update of the minimal risk tool in patients suspected of chronic coronary syndrome.

Risk stratification in patients with suspected coronary artery disease (CAD) is important. Recently, the minimal-risk-tool (MRT) was developed to identify individuals with low CAD risk despite symptoms in order to avoid unnecessary testing. We aimed to validate and update the MRT-model in a contemporary cohort. The Dan-NICAD trial cohort, consisting of 1675 consecutive patients referred for coronary computed tomography angiography (CTA), was used to calculate the MRT-score based on the published fitted variable coefficients from the PROMISE and SCOT-HEART trials. Minimal risk was defined as zero calcium score, no coronary atherosclerosis at coronary CTA, and no cardiovascular events in the follow-up period. We tested an updated MRT-model by pooling the fitted variable coefficients from all three trials. A total of 1544 patients fulfilling the inclusion criteria were followed for 3.1 [2.7-3.4] years. In 710 (46%) patients, the criteria for minimal risk were fulfilled. Despite substantial coefficient variation, the MRTs based on the PROMISE, the SCOT-HEART and the updated MRT variables showed similar moderate to high discriminative performance for minimal risk estimation. Although all three models tended to underestimate minimal risk, the updated MRT had the best performance. Using a 75% minimal risk cut-off, the updated MRT showed a sensitivity of 11.6% (95% CI 9.3-14.2%) and specificity of 99.3% (95% CI 98.6-99.8%). An updated MRT model based on three large studies increased calibration compared to the existing MRT models, whereas discrimination was similar despite substantial coefficient variation. The updated MRT might supplement currently recommended pre-test probability models.

Validation of the European Society of Cardiology pre-test probability model for obstructive coronary artery disease.

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.

One-step anatomic and function testing by cardiac CT versus second-line functional testing in symptomatic patients with coronary artery stenosis: head-to-head comparison of CT-derived fractional flow reserve and myocardial perfusion imaging.

BACKGROUND: CT-QFR is a novel coronary computed tomography angiography (CTA)-based method for on-site evaluation of patients with suspected obstructive coronary artery disease (CAD). AIMS: We aimed to compare the diagnostic performance of CT-QFR with myocardial perfusion scintigraphy (MPS) and cardiovascular magnetic resonance (CMR) as second-line tests in patients with suspected obstructive CAD after coronary CTA. METHODS: A paired analysis of CT-QFR and MPS or CMR, with an invasive FFR-based classification as reference standard was carried out. Symptomatic patients with >50% diameter stenosis on coronary CTA were randomised to MPS or CMR and referred for invasive coronary angiography. RESULTS: The rate of coronary CTA not feasible for CT-QFR analysis was 17%. Paired patient-level data were available for 118 patients in the MPS group and 113 in the CMR group. Patient-level diagnostic accuracy was better for CT-QFR than for both MPS (82.2% [95% CI: 75.2-89.2] vs 70.3% [95% CI: 62.0-78.7], p=0.029) and CMR (77.0% [95% CI: 69.1-84.9] vs 65.5% [95% CI: 56.6-74.4], p=0.047). Following a positive coronary CTA and with the intention to diagnose, CT-QFR, CMR and MPS were equally suitable as rule-in and rule-out modalities. CONCLUSIONS: The diagnostic performance of CT-QFR as a second-line test was at least similar to MPS and CMR for the evaluation of obstructive CAD in symptomatic patients presenting with ≥50% diameter stenosis on coronary CTA.

Association between circulating proprotein convertase subtilisin/kexin type 9 levels and prognosis in patients with severe chronic kidney disease.

BACKGROUND: Chronic kidney disease is a risk factor for premature development of coronary atherosclerosis and mortality. A high level of proprotein convertase subtilisin/kexin type 9 (PCSK9) is a recently recognized cardiovascular risk factor and has become the target of effective inhibitory treatment. In 167 kidney transplantation candidates, we aimed to: (i) compare levels of PCSK9 with those of healthy controls, (ii) examine the association between levels of PCSK9 and low-density lipoprotein cholesterol (LDL-c) and the degree of coronary artery disease (CAD) and (iii) evaluate if levels of PCSK9 predict major adverse cardiac events (MACE) and mortality. METHODS: Kidney transplant candidates (n = 167) underwent coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) before transplantation. MACE and mortality data were extracted from the Western Denmark Heart Registry, a review of patient records and patient interviews. A group of 79 healthy subjects were used as controls. RESULTS: Mean PCSK9 levels did not differ between healthy controls and kidney transplant candidates. In patients not receiving lipid-lowering therapy, PCSK9 correlated positively with LDL-c (rho = 0.24, P < 0.05). Mean PCSK9 was similar in patients with and without obstructive CAD at both CCTA and ICA. In a multiple regression analysis, PCSK9 was associated with neither LDL-c (ß=-6.45, P = 0.44) nor coronary artery calcium score (ß=2.17, P = 0.84). During a follow-up of 3.7 years, PCSK9 levels were not associated with either MACE or mortality. CONCLUSIONS: The ability of PCSK9 levels to predict cardiovascular disease and prognosis does not seem to apply to a cohort of kidney transplant candidates.

Danish study of Non-Invasive testing in Coronary Artery Disease 2 (Dan-NICAD 2): Study design for a controlled study of diagnostic accuracy.

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), 82rubidium positron emission tomography (82Rb-PET), and CT-derived fractional flow reserve (FFRCT) 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 82Rb-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 82Rb-PET, FFRCT, 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.

Prognostic Value of Risk Factors, Calcium Score, Coronary CTA, Myocardial Perfusion Imaging, and Invasive Coronary Angiography in Kidney Transplantation Candidates.

OBJECTIVES: This study sought to perform a prospective head-to-head comparison of the predictive value of clinical risk factors and a variety of cardiac imaging modalities including coronary artery calcium score (CACS), coronary computed tomography angiography (CTA), single-photon emission computed tomography (SPECT), and invasive coronary angiography (ICA) on major adverse cardiac events (MACE) and all-cause mortality in kidney transplantation candidates. BACKGROUND: Current guidelines recommend screening for coronary artery disease in kidney transplantation candidates. Furthermore, noninvasive stress imaging is recommended in current guidelines, despite its low diagnostic accuracy and uncertain prognostic value. METHODS: The study prospectively evaluated 154 patients referred for kidney transplantation. All patients underwent CACS, coronary CTA, SPECT, and ICA testing. The clinical endpoints were extracted from patients' interviews, patients' records, and registries. RESULTS: The mean follow-up time was 3.7 years. In total, 27 (17.5%) patients experienced MACE, and 31 (20.1%) patients died during follow-up. In a time-to-event analysis, both risk factors and CACS significantly predicted death, but only CACS predicted MACE. Combining risk factors with CACS identified a very-low-risk cohort with a MACE event rate of 2.1%, and a 1.0% mortality rate per year. Of the diagnostic modalities, coronary CTA and ICA significantly predicted MACE, but only coronary CTA predicted death. In contrast, SPECT predicted neither MACE nor death. CONCLUSIONS: Compared with traditional risk factors and other cardiac imaging modalities, CACS and coronary CTA seem superior for risk stratification in kidney transplant candidates. Applying a combination of risk factors and CACS and subsequently coronary CTA seems to be the most appropriate strategy. (Angiographic CT of Renal Transplantation Candidate Study [ACToR]; NCT01344434).

Diagnostic performance of an acoustic-based system for coronary artery disease risk stratification.

OBJECTIVE: Diagnosing coronary artery disease (CAD) continues to require substantial healthcare resources. Acoustic analysis of transcutaneous heart sounds of cardiac movement and intracoronary turbulence due to obstructive coronary disease could potentially change this. The aim of this study was thus to test the diagnostic accuracy of a new portable acoustic device for detection of CAD. METHODS: We included 1675 patients consecutively with low to intermediate likelihood of CAD who had been referred for cardiac CT angiography. If significant obstruction was suspected in any coronary segment, patients were referred to invasive angiography and fractional flow reserve (FFR) assessment. Heart sound analysis was performed in all patients. A predefined acoustic CAD-score algorithm was evaluated; subsequently, we developed and validated an updated CAD-score algorithm that included both acoustic features and clinical risk factors. Low risk is indicated by a CAD-score value ≤20. RESULTS: Haemodynamically significant CAD assessed from FFR was present in 145 (10.0%) patients. In the entire cohort, the predefined CAD-score had a sensitivity of 63% and a specificity of 44%. In total, 50% had an updated CAD-score value ≤20. At this cut-off, sensitivity was 81% (95% CI 73% to 87%), specificity 53% (95% CI 50% to 56%), positive predictive value 16% (95% CI 13% to 18%) and negative predictive value 96% (95% CI 95% to 98%) for diagnosing haemodynamically significant CAD. CONCLUSION: Sound-based detection of CAD enables risk stratification superior to clinical risk scores. With a negative predictive value of 96%, this new acoustic rule-out system could potentially supplement clinical assessment to guide decisions on the need for further diagnostic investigation. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov identifier NCT02264717; Results.