Clinical Likelihood Prediction of Hemodynamically Obstructive Coronary Artery Disease in Patients With Stable Chest Pain.

BACKGROUND: Selection for invasive angiography is recommended to be based on pretest probabilities (PTPs), and physiological measures of hemodynamical impairment by, for example, fractional flow reserve (FFR) should guide revascularization. The risk factor-weighted clinical likelihood (RF-CL) and coronary artery calcium score-weighted clinical likelihood (CACS-CL) models show superior discrimination of patients with suspected obstructive coronary artery disease (CAD), but validation against hemodynamic impairment is warranted. OBJECTIVES: The aim of this study was to validate the RF-CL and CACS-CL models against hemodynamically obstructive CAD. METHODS: Stable de novo chest pain patients (N = 4,371) underwent coronary computed tomography angiography and subsequently invasive coronary angiography with FFR measurements. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or high-grade stenosis by visual assessment (>90% diameter stenosis). For comparison, a guideline-endorsed basic PTP model was calculated based on age, sex, and symptom typicality. The RF-CL model additionally included the number of risk factors, and the CACS-CL model incorporated the coronary artery calcium score into the RF-CL. RESULTS: In total, 447 of 4,371 (10.9%) patients had hemodynamically obstructive CAD. Both the RF-CL and CACS-CL models classified more patients with a very low clinical likelihood (≤5%) of obstructive CAD compared to the basic PTP model (33.0% and 53.7% vs 12.0%; P < 0.001) with a preserved low prevalence of hemodynamically obstructive CAD (<5% for all models). Against hemodynamically obstructive CAD, calibration and discrimination of the RF-CL and CACS-CL models were superior to the basic PTP model. CONCLUSIONS: The RF-CL and CACS-CL models are well calibrated and superior to a currently recommended basic PTP model to predict hemodynamically obstructive CAD. (Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease [Dan-NICAD]; NCT02264717; Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease 2 [Dan-NICAD 2]; NCT03481712, Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease 3 [Dan-NICAD 3]; NCT04707859).

Biomarkers for identification of high-risk coronary artery plaques in patients with suspected coronary artery disease.

BACKGROUND: Patients with atherosclerotic plaques containing high-risk features have an increased likelihood of events and a worse prognosis. Whether increased levels of Troponin I (TnI) and C-reactive protein (CRP) are associated with the presence of high-risk coronary atherosclerotic plaques (HRP) is not well described. We assessed the association between 1) TnI and 2) CRP with quantified coronary plaque burden, luminal diameter stenosis, and HRP in patients with low/intermediate pre-test probability of obstructive coronary artery disease (CAD) referred for coronary computed tomography angiography (CCTA). METHODS: The CCTA from 1615 patients were analyzed using a semiautomatic software for coronary artery plaque characterization. Patients with high TnI (>6 â€‹ng/L) and high CRP (>2 â€‹mg/L) were identified. Associations of TnI and CRP with plaque burden, stenosis (≥50% luminal diameter stenosis on CCTA), and HRP were investigated. RESULTS: TnI and CRP were both positively correlated with total plaque burden (TnI rs â€‹= â€‹0.14, p â€‹< â€‹0.001; CRP rs â€‹= â€‹0.08, p â€‹< â€‹0.001). In multivariate logistic regression analyses, high TnI was associated with stenosis (OR 1.43, 95% confidence interval (CI) 1.03-1.99, p â€‹= â€‹0.034), the presence of HRP (OR 1.79, 95% CI: 1.17-2.74, p â€‹= â€‹0.008), and the subtypes of HRP; low attenuation plaque (OR 1.93, 95% CI: 1.24-3.00, p â€‹= â€‹0.003), and positive remodeling (OR 1.51, 95% CI: 1.07-2.13, p â€‹= â€‹0.018). For CRP, only stenosis and napkin ring sign correlated significantly. CONCLUSION: In patients with suspected CAD, TnI and CRP are associated with HRP features. These findings may suggest that inflammatory and particularly ischemic biomarkers might improve early risk stratification and affect patient management. GOV IDENTIFIER: NCT02264717.

Myocardial Blood Flow by Magnetic Resonance in Patients With Suspected Coronary Stenosis: Comparison to PET and Invasive Physiology.

BACKGROUND: Despite recent guideline recommendations, quantitative perfusion (QP) estimates of myocardial blood flow from cardiac magnetic resonance (CMR) have only been sparsely validated. Furthermore, the additional diagnostic value of utilizing QP in addition to the traditional visual expert interpretation of stress-perfusion CMR remains unknown. The aim was to investigate the correlation between myocardial blood flow measurements estimated by CMR, positron emission tomography, and invasive coronary thermodilution. The second aim is to investigate the diagnostic performance of CMR-QP to identify obstructive coronary artery disease (CAD). METHODS: Prospectively enrolled symptomatic patients with >50% diameter stenosis on computed tomography angiography underwent dual-bolus CMR and positron emission tomography with rest and adenosine-stress myocardial blood flow measurements. Subsequently, an invasive coronary angiography (ICA) with fractional flow reserve and thermodilution-based coronary flow reserve was performed. Obstructive CAD was defined as both anatomically severe (>70% diameter stenosis on quantitative coronary angiography) or hemodynamically obstructive (ICA with fractional flow reserve ≤0.80). RESULTS: About 359 patients completed all investigations. Myocardial blood flow and reserve measurements correlated weakly between estimates from CMR-QP, positron emission tomography, and ICA-coronary flow reserve (r<0.40 for all comparisons). In the diagnosis of anatomically severe CAD, the interpretation of CMR-QP by an expert reader improved the sensitivity in comparison to visual analysis alone (82% versus 88% [P=0.03]) without compromising specificity (77% versus 74% [P=0.28]). In the diagnosis of hemodynamically obstructive CAD, the accuracy was only moderate for a visual expert read and remained unchanged when additional CMR-QP measurements were interpreted. CONCLUSIONS: CMR-QP correlates weakly to myocardial blood flow measurements by other modalities but improves diagnosis of anatomically severe CAD. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03481712.

Evaluating the American Heart Association/American College of Cardiology Guideline-Recommended and Contemporary Pretest Probability Models in a Mixed Asian Cohort: The Contribution of Coronary Artery Calcium.

BACKGROUND: Most pretest probability (PTP) tools for obstructive coronary artery disease (CAD) were Western -developed. The most appropriate PTP models and the contribution of coronary artery calcium score (CACS) in Asian populations remain unknown. In a mixed Asian cohort, we compare 5 PTP models: local assessment of the heart (LAH), CAD Consortium (CAD2), risk factor-weighted clinical likelihood, the American Heart Association/American College of Cardiology and the European Society of Cardiology PTP and 3 extended versions of these models that incorporated CACS: LAH(CACS), CAD2(CACS), and the CACS-clinical likelihood. METHODS AND RESULTS: The study cohort included 771 patients referred for stable chest pain. Obstructive CAD prevalence was 27.5%. Calibration, area under the receiver-operating characteristic curves (AUC) and net reclassification index were evaluated. LAH clinical had the best calibration (χ2 5.8; P=0.12). For CACS models, LAH(CACS) showed least deviation between observed and expected cases (χ2 37.5; P<0.001). There was no difference in AUCs between the LAH clinical (AUC, 0.73 [95% CI, 0.69-0.77]), CAD2 clinical (AUC, 0.72 [95% CI, 0.68-0.76]), risk factor-weighted clinical likelihood (AUC, 0.73 [95% CI: 0.69-0.76) and European Society of Cardiology PTP (AUC, 0.71 [95% CI, 0.67-0.75]). CACS improved discrimination and reclassification of the LAH(CACS) (AUC, 0.88; net reclassification index, 0.46), CAD2(CACS) (AUC, 0.87; net reclassification index, 0.29) and CACS-CL (AUC, 0.87; net reclassification index, 0.25). CONCLUSIONS: In a mixed Asian cohort, Asian-derived LAH models had similar discriminatory performance but better calibration and risk categorization for clinically relevant PTP cutoffs. Incorporating CACS improved discrimination and reclassification. These results support the use of population-matched, CACS-inclusive PTP tools for the prediction of obstructive CAD.

DARE-ISC model for prediction of 1-year ischaemic stroke risk in the general population and atrial fibrillation patients: a Danish nationwide cohort study.

OBJECTIVES: To develop a risk assessment model (DAnish REgister Ischaemic Stroke Classifier, DARE-ISC) for predicting 1-year primary ischaemic stroke/systemic embolism (SE) in the general population. Secondly, to validate the accuracy DARE-ISC in atrial fibrillation (AF) patients where well-established models and risk scores exist. DESIGN: Retrospective cohort study. DARE-ISC was developed using gradient boosting decision trees with information from 375 covariates including baseline information on relevant diagnoses, demographic characteristics, registered health-services, lifestyle-related covariates, hereditary stroke components, drug prescriptions and stress proxies. SETTING: Danish nationwide registries. PARTICIPANTS: All Danish individuals aged ≥18 from 2010 to 2017 (n=35 519 348 person-years). The model was trained on the 2010-2016 cohorts with validation in the 2017 cohort. PRIMARY AND SECONDARY OUTCOME MEASURES: Model optimisation and validation were performed through comparison of the area under the receiver operating characteristic curve (AUC) and average precision scores. Additionally, the relative importance of the model covariates was derived using SHAP values. RESULTS: DARE-ISC had an AUC (95% CI) of 0.874 (0.871 to 0.876) in the general population. In AF patients, DARE-ISC was superior to the GARFIELD-AF risk model and CHA2DS2-VASc score with AUC of 0.779 (95% CI 0.75 to 0.806), 0.704 (95% CI 0.674 to 0.732) and 0.681 (95% CI 0.652 to 0.709), respectively. Furthermore, in AF patients, DARE-ISC had an average threefold and fourfold higher ratio of correctly identified strokes compared with the GARFIELD-AF risk model and CHA2DS2-VASc score, as indicated by average precision scores of 0.119, 0.041 and 0.034, respectively. CONCLUSIONS: DARE-ISC had a very high stroke prediction accuracy in the general population and was superior to the GARFIELD-AF risk model and CHA2DS2-VASc score for predicting ischaemic stroke/SE in AF patients.

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).

Optimal diagnostic approach for using CT-derived quantitative flow ratio in patients with stenosis on coronary computed tomography angiography.

BACKGROUND: Coronary computed tomography angiography (CCTA)-derived quantitative flow ratio (CT-QFR) is an on-site non-invasive technique estimating invasive fractional flow reserve (FFR). This study assesses the diagnostic performance of using most distal CT-QFR versus lesion-specific CT-QFR approach for identifying hemodynamically obstructive coronary artery disease (CAD). METHODS: Prospectively enrolled de novo chest pain patients (n â€‹= â€‹445) with ≥50 â€‹% visual diameter stenosis on CCTA were referred for invasive evaluation. On-site CT-QFR was analyzed post-hoc blinded to angiographic data and obtained as both most distal (MD-QFR) and lesion-specific CT-QFR (LS-QFR). Abnormal CT-QFR was defined as ≤0.80. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or ≥70 â€‹% diameter stenosis by 3D-quantitative coronary angiography. RESULTS: In total 404/445 patients had paired CT-QFR and invasive analyses of whom 149/404 (37 â€‹%) had hemodynamically obstructive CAD. MD-QFR and LS-QFR classified 188 (47 â€‹%) and 165 (41 â€‹%) patients as abnormal, respectively. Areas under the receiver-operating characteristic curve for MD-QFR was 0.83 vs. 0.85 for LS-QFR, p â€‹= â€‹0.01. Sensitivities for MD-QFR and LS-QFR were 80 â€‹% (95%CI: 73-86) vs. 77 â€‹% (95%CI: 69-83), p â€‹= â€‹0.03, respectively, and specificities were 73 â€‹% (95%CI: 67-78) vs. 80 â€‹% (95%CI: 75-85), p â€‹< â€‹0.01, respectively. Positive predictive values for MD-QFR and LS-QFR were 63 â€‹% vs. 69 â€‹%, p â€‹< â€‹0.01, respectively, and negative predictive values for MD-QFR and LS-QFR were 86 â€‹% vs. 85 â€‹%, p â€‹= â€‹0.39, respectively). CONCLUSION: Using a lesion-specific CT-QFR approach has superior discrimination of hemodynamically obstructive CAD compared to a most distal CT-QFR approach. CT-QFR identified most cases of hemodynamically obstructive CAD while a normal CT-QFR excluded hemodynamically obstructive CAD in the majority of patients.

Calcium Scoring Improves Clinical Management in Patients With Low Clinical Likelihood of Coronary Artery Disease.

BACKGROUND: Coronary artery calcium scoring (CACS) improves management of chest pain patients. However, it is unknown whether the benefit of CACS is dependent on the clinical likelihood (CL). OBJECTIVES: This study aims to investigate for which patients CACS has the greatest benefit when added to a CL model. METHODS: Based on data from a clinical database, the CL of obstructive coronary artery disease (CAD) was calculated for 39,837 patients referred for cardiac imaging due to symptoms suggestive of obstructive CAD. Patients were categorized according to the risk factor-weighted (RF-CL) model (very low, ≤5%; low, >5 to ≤15%; moderate >15 to ≤50%; high, >50%). CL was then recalculated incorporating the CACS result (CACS-CL). Reclassification rates and the number needed to test with CACS to reclassify patients were calculated and validated in 3 independent cohorts (n = 9,635). RESULTS: In total, 15,358 (39%) patients were down- or upclassified after including CACS. Reclassification rates were 8%, 75%, 53%, and 30% in the very low, low, moderate, and high RF-CL categories, respectively. Reclassification to very low CACS-CL occurred in 48% of reclassified patients. The number needed to test to reclassify 1 patient from low RF-CL to very low CACS-CL was 2.1 with consistency across age, sex, and cohorts. CACS-CL correlated better to obstructive CAD prevalence than RF-CL. CONCLUSIONS: Added to an RF-CL model for obstructive CAD, CACS identifies more patients unlikely to benefit from further testing. The number needed to test with CACS to reclassify patients depends on the pretest RF-CL and is lowest in patients with low (>5% to ≤15%) likelihood of CAD.

Contact with general practice in patients with suspected chronic coronary syndrome before and after CT angiography compared with the general population.

BACKGROUND: Most patients undergoing coronary computed tomography angiography (CCTA) to diagnose coronary artery disease (CAD) are referred from general practitioners (GP). The burden in contacts to GP in relation to investigation on suspected CAD is unknown. METHODS: All patients undergoing CCTA in Western Denmark from 2014-2022 were included. CCTA stenosis was defined as diameter stenosis of ≥ 50%. Patients with and without stenosis were matched, in each group, 1:5 to a reference population based on birth-year, gender and municipality using data from national registries. All GP visits were registered in up to five years preceding and one year after the CTA and stratified by gender and age. Charlson comorbidity index (CCI) were calculated in all groups. RESULTS: Of the 62 512 patients included, 12 886 had a stenosis while 49 626 did not. Patients in both groups had a substantially higher GP visit frequency compared to reference populations. In the year of coronary CTA median GP contacts in patients with stenosis was 11 [6-17] vs. 6 [2-11] in the reference population (P < 0.001), in patients without stenosis 10 [6-17] vs. 5 [2-11] (P < 0.001). These findings were consistent across age and gender. CCI was higher among both patients with and without stenosis compared to reference groups. CONCLUSION: In patients undergoing CCTA to diagnose CAD, a substantially increased frequency of contacts to GP was observed in the five-year period prior to examination compared to the reference populations regardless of the CCTA findings. Obtaining the CCTA result did not seem to substantially affect the GP visit frequency.

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.

Bone Mineral Density Derived from Cardiac CT Scans: Using Contrast Enhanced Scans for Opportunistic Screening.

PURPOSE: Osteoporosis is under-diagnosed and often co-exists with other diseases. Very low bone mineral density (BMD) indicates risk of osteoporosis and opportunistic screening for low BMD in CT-scans has been suggested. In a non-contrast enhanced thoracic CT scan, the scan-field-of-view includes vertebrae enabling BMD estimation. However, many CT scans are obtained by administration of contrast material. If the impact of contrast enhancement on BMD measurements could be quantified, considerably more patients are eligible for screening. METHODS: This study investigated the impact of intravenous contrast on thoracic BMD measurements in cardiac CT scans pre- and post-contrast, including different contrast trigger levels of 130 and 180 Hounsfield units (HU). BMD was measured using quantitative CT with asynchronous calibration. RESULTS: In 195 participants undergoing cardiac CT (mean age 57±9 years, 37 % females) contrast increased mean thoracic BMD from 116±33 mg/cm3 (non-enhanced CT) to 130±38 mg/cm3 (contrast-enhanced CT) (p<0.001). Using clinical cut-off values for very low (<80 mg/cm3) and low BMD (<120 mg/cm3) showed that 24 % (47/195 participants) were misclassified when BMD was measured on contrast-enhanced CT-scans. Of the misclassified patients, 6 % (12/195 participants) were categorized as having low BMD despite having very low BMD on the non-enhanced images. Contrast-CT using a higher contrast trigger level showed a significant increase in BMD compared to the lower trigger level (119±32 vs. 135±40 mg/cm3, p<0.01). CONCLUSION: For patients undergoing cardiac CT, using contrast-enhanced images to assess BMD entails substantial overestimation. Contrast protocol trigger levels also affect BMD measurements. Adjusting for these factors is needed before contrast-enhanced images can be used clinically. MINI ABSTRACT: Osteoporosis is under-diagnosed. Contrast-enhanced CT made to examine other diseases might be utilized simultaneously for bone mineral density (BMD) screening. These scans, however, likely entails overestimation of BMD due to the effect of contrast. Adjusting for this effect is needed before contrast-enhanced images can be implemented clinically for BMD screening.

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 Proposed American Heart Association Algorithm for Cardiovascular Screening Before Kidney Transplantation.

BACKGROUND: Screening for cardiovascular disease is currently recommended before kidney transplantation. The present study aimed to validate the proposed algorithm by the American Heart Association (AHA-2022) considering cardiovascular findings and outcomes in kidney transplant candidates, and to compare AHA-2022 with the previous recommendation (AHA-2012). METHODS AND RESULTS: We applied the 2 screening algorithms to an observational cohort of kidney transplant candidates (n=529) who were already extensively screened for coronary heart disease by referral to cardiac computed tomography between 2014 and 2019. The cohort was divided into 3 groups as per the AHA-2022 algorithm, or into 2 groups as per AHA-2012. Outcomes were degree of coronary heart disease, revascularization rate following screening, major adverse cardiovascular events, and all-cause death. Using the AHA-2022 algorithm, 69 (13%) patients were recommended for cardiology referral, 315 (60%) for cardiac screening, and 145 (27%) no further screening. More patients were recommended cardiology referral or screening compared with the AHA-2012 (73% versus 53%; P<0.0001). Patients recommended cardiology referral or cardiac screening had a higher risk of major adverse cardiovascular events (hazard ratio [HR], 5.5 [95% CI, 2.8-10.8]; and HR, 2.1 [95% CI, 1.2-3.9]) and all-cause death (HR, 12.0 [95% [CI, 4.6-31.4]; and HR, 5.3 [95% CI, 2.1-13.3]) compared with patients recommended no further screening, and were more often revascularized following initial screening (20% versus 7% versus 0.7%; P<0.001). CONCLUSIONS: The AHA-2022 algorithm allocates more patients for cardiac referral and screening compared with AHA-2012. Furthermore, the AHA-2022 algorithm effectively discriminates between kidney transplant candidates at high, intermediate, and low risk with respect to major adverse cardiovascular events and all-cause death.

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.

Radiomics analysis enhances the diagnostic performance of CMR stress perfusion: a proof-of-concept study using the Dan-NICAD dataset.

Objectives: To assess the feasibility of extracting radiomics signal intensity based features from the myocardium using cardiovascular magnetic resonance (CMR) imaging stress perfusion sequences. Furthermore, to compare the diagnostic performance of radiomics models against standard-of-care qualitative visual assessment of stress perfusion images, with the ground truth stenosis label being defined by invasive Fractional Flow Reserve (FFR) and quantitative coronary angiography. Methods: We used the Dan-NICAD 1 dataset, a multi-centre study with coronary computed tomography angiography, 1,5 T CMR stress perfusion, and invasive FFR available for a subset of 148 patients with suspected coronary artery disease. Image segmentation was performed by two independent readers. We used the Pyradiomics platform to extract radiomics first-order (n = 14) and texture (n = 75) features from the LV myocardium (basal, mid, apical) in rest and stress perfusion images. Results: Overall, 92 patients (mean age 62 years, 56 men) were included in the study, 39 with positive FFR. We double-cross validated the model and, in each inner fold, we trained and validated a per territory model. The conventional analysis results reported sensitivity of 41% and specificity of 84%. Our final radiomics model demonstrated an improvement on these results with an average sensitivity of 53% and specificity of 86%. Conclusion: In this proof-of-concept study from the Dan-NICAD dataset, we demonstrate the feasibility of radiomics analysis applied to CMR perfusion images with a suggestion of superior diagnostic performance of radiomics models over conventional visual analysis of perfusion images in picking up perfusion defects defined by invasive coronary angiography.

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.

The Diagnostic Yield and Clinical Impact of Systematic Screening of Kidney Transplant Candidates by Cardiac Computed Tomography: A Cohort Study.

BACKGROUND: Although cardiovascular screening of kidney transplant candidates is recommended, the optimal approach is debated. Previous studies show that noninvasive imaging provides prognostic information, but systematic screening may have less recognized effects, such as additional investigations, incidental findings, procedural complications, and delay of transplantation. To address this, we characterized the diagnostic yield and clinical implications of systematic screening for cardiovascular disease using cardiac computed tomography (CT) in potential kidney transplant candidates. METHODS: This was a single-center, observational cohort study including all potential kidney transplant candidates >40 years of age or with diabetes or on dialysis treatment for >5 years, systematically referred to cardiac computed tomography (CT; non-contrast CT and coronary CT angiography) between 2014 and 2019 before evaluation for kidney transplantation at Aarhus University Hospital. Patient records were examined for data on baseline characteristics, additional investigations and complications, plasma creatinine, dialysis initiation, time until wait-listing, and incidental findings. RESULTS: Of 473 patients who underwent cardiac CT, additional cardiac investigations were performed in 156 (33%), and 32 (7%) were revascularized. Twenty-two patients had significant incidental nonvascular findings on cardiac CT. No patient was rejected for transplantation based on cardiac CT. In patients not yet on dialysis, the slope in the estimated glomerular filtration rate decline did not change significantly after coronary CT angiography. CONCLUSION: Screening by cardiac CT led to additional cardiac investigations in one-third of patients; only a few patients were revascularized, with unknown benefits in asymptomatic patients. Cardiac CT was safe in this population; however, the clinical consequences of the screening were limited.

Danish study of Non-Invasive Testing in Coronary Artery Disease 3 (Dan-NICAD 3): study design of a controlled study on optimal diagnostic strategy.

INTRODUCTION: Current guideline recommend functional imaging for myocardial ischaemia if coronary CT angiography (CTA) has shown coronary artery disease (CAD) of uncertain functional significance. However, diagnostic accuracy of selective myocardial perfusion imaging after coronary CTA is currently unclear. The Danish study of Non-Invasive testing in Coronary Artery Disease 3 trial is designed to evaluate head to head the diagnostic accuracy of myocardial perfusion imaging with positron emission tomography (PET) using the tracers 82Rubidium (82Rb-PET) compared with oxygen-15 labelled water PET (15O-water-PET) in patients with symptoms of obstructive CAD and a coronary CT scan with suspected obstructive CAD. METHODS AND ANALYSIS: This prospective, multicentre, cross-sectional study will include approximately 1000 symptomatic patients without previous CAD. Patients are included after referral to coronary CTA. All patients undergo a structured interview and blood is sampled for genetic and proteomic analysis and a coronary CTA. Patients with possible obstructive CAD at coronary CTA are examined with both 82Rb-PET, 15O-water-PET and invasive coronary angiography with three-vessel fractional flow reserve and thermodilution measurements of coronary flow reserve. After enrolment, patients are followed with Seattle Angina Questionnaires and follow-up PET scans in patients with an initially abnormal PET scan and for cardiovascular events in 10 years. ETHICS AND DISSEMINATION: Ethical approval was obtained from Danish regional committee on health research ethics. Written informed consent will be provided by all study participants. Results of this study will be disseminated via articles in international peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT04707859.