Validation of European Society of Cardiology pre-test probabilities for obstructive coronary artery disease in suspected stable angina

Validation of the European Society of Cardiology pretest probability models for obstructive coronary artery disease in high-risk population

BACKGROUND

The pre-test probability (PTP) model for obstructive coronary artery disease (CAD) was updated in 2019 by the European Society of Cardiology (ESC). To our knowledge, this model was never externally validated in population with high incidence of CAD. The aim of this study is to validate the new PTP ESC model in our population which has a high CAD incidence and to compare it with previous PTP ESC model from 2013.

METHODS

We retrospectively analysed 1294 symptomatic patients with suspected CAD referred to our centre between 2015 and 2019. In all patients, the PTP score was calculated based on age, gender and symptoms according to the ESC model from 2013 (2013-ESC-PTP) and 2019 (2019-ESC-PTP). All patients underwent invasive coronary angiography (ICA).

RESULTS

Of the 1294 patients, obstructive CAD was diagnosed in 533 patients (41.2%). The 2019-ESC-PTP model categorised significantly more patients into the low probability group (PTP < 15%) than the 2013-ESC-PTP model (39.8% vs. 5.6%, P< 0.001). Obstructive CAD prevalence was underestimated using 2019-ESC-PTP at all PTP levels (calibration intercept 1.15, calibration slope 0.96). The 2013-ESC-PTP overestimated obstructive CAD prevalence (calibration intercept -0.24, calibration slope 0.73). The discrimination measured with an area under the curve was similar for both models, indicating moderate accuracy of the models.

CONCLUSIONS

In high-risk Serbian population, both the 2013 and 2019 ESC-PTP models had moderate accuracy in diagnosing CAD, with the 2019-ESC-PTP underestimating the prevalence of CAD, while the 2013-ESC-PTP overestimating it. Further studies are warranted to establish PTP models for high-risk countries.

Use of coronary artery calcium score and coronary CT angiography to guide cardiovascular prevention and treatment

Currently, cardiovascular risk stratification to guide preventive therapy relies on clinical scores based on cardiovascular risk factors. However, the discriminative power of these scores is relatively modest. The use of coronary artery calcium score (CACS) and coronary CT angiography (CCTA) has surfaced as methods for enhancing the estimation of risk and potentially providing insights for personalized treatment in individual patients. CACS improves overall cardiovascular risk prediction and may be used to improve the yield of statin therapy in primary prevention, and possibly identify patients with a favorable risk/benefit relationship for antiplatelet therapies. CCTA holds promise to guide anti-atherosclerotic therapies and to monitor individual response to these treatments by assessing individual plaque features, quantifying total plaque volume and composition, and assessing peri-coronary adipose tissue. In this review, we aim to summarize current evidence regarding the use of CACS and CCTA for guiding lipid-lowering and antiplatelet therapy and discuss the possibility of using plaque burden and plaque phenotyping to monitor response to anti-atherosclerotic therapies.

Clinical Value of Using Heart Rate Variability Biofeedback Before Elective CT Coronary Angiography to Reduce Heart Rate and the Need for Beta-Blockers

The value of biofeedback before elective coronary computed tomography angiography (CCTA) to reduce patients' heart rates (HR) was investigated in the current work. Sixty patients who received CCTA to exclude coronary artery disease were included in our study and separated into two groups: with biofeedback (W-BF) and without biofeedback (WO-BF). The W-BF group used a biofeedback device for 15 min before CCTA. HR was determined in each patient at four measurement time points (MTP): during the pre-examination interview (MTP1), positioning on the CT patient table before CCTA (MTP2), during CCTA image acquisition (MTP3), and after completing CCTA (MTP4). If necessary, beta-blockers were administered in both groups after MTP2 until a HR of less than 65 bpm was achieved. Two board-certified radiologists subsequently assessed the image quality and analyzed the findings. Overall, the need for beta-blockers was significantly lower in patients in the W-BF group than the WO-BF group (p = 0.032). In patients with a HR of 81-90, beta-blockers were not required in four of six cases in the W-BF group, whereas in the WO-BF group all patients needed beta-blockers (p = 0.03). The amount of HR reduction between MTP1 and MTP2 was significantly higher in the W-BF compared to the WO-BF group (p = 0.028). There was no significant difference between the W-BF and WO-BF groups regarding image quality (p = 0.179). By using biofeedback prior to elective CCTA, beta-blocker use could be decreased without compromising CT image quality and analysis, especially in patients with an initial HR of 81-90 bpm.

Comparison of two diagnostic strategies for patients with stable chest pain suggestive of chronic coronary syndrome: rationale and design of the double-blind, pragmatic, randomized and controlled OPERATE Trial

BACKGROUND

To achieve potential financial savings and avoid exposing the patients to unnecessary risk, an optimal diagnostic strategy to identify low risk individual who may derive minimal benefit from further cardiac imaging testing (CIT) is important for patients with stable chest pain (SCP) suggestive of chronic coronary syndrome (CCS). Although several diagnostic strategies have been recommended by the most recent guidelines, few randomized controlled trials (RCTs) have prospectively investigated the actual effect of applying these strategies in clinical practice.

METHODS

OPERATE (OPtimal Evaluation of stable chest pain to Reduce unnecessAry utilization of cardiac imaging TEsting) trial is an investigator-initiated, multicenter, coronary computed tomography angiography (CCTA)-based, 2-arm parallel-group, double-blind, pragmatic and confirmative RCT planning to include 800 subjects with SCP suggestive of CCS. After enrollment, all subjects will be randomized to two arms (2016 U.K. National Institute of Health and Care Excellence guideline-determined and 2019 European Society of Cardiology guideline-determined diagnostic strategy) on a 1:1 basis. According to each strategy, CCTA should be referred and deferred for a subject in high and low risk group, respectively. The primary (effectiveness) endpoint is CCTA without obstructive coronary artery disease. Safety of each strategy will be mainly assessed by 1-year major adverse cardiovascular event rates.

DISCUSSION

The OPERATE trial will provide comparative effectiveness and safety evidences for two different diagnostic strategies for patients with SCP suggestive of CCS, with the intension of improving the diagnostic yield of CCTA at no expense of safety.

CLINICAL TRIAL REGISTRATION

ClinicalTrial.org Identifier NCT05640752.

Computed tomographic angiography in coronary artery disease

Coronary computed tomographic angiography (CCTA) is becoming the first-line investigation for establishing the presence of coronary artery disease and, with fractional flow reserve (FFRCT), its haemodynamic significance. In patients without significant epicardial obstruction, its role is either to rule out atherosclerosis or to detect subclinical plaque that should be monitored for plaque progression/regression following prevention therapy and provide risk classification. Ischaemic non-obstructive coronary arteries are also expected to be assessed by non-invasive imaging, including CCTA. In patients with significant epicardial obstruction, CCTA can assist in planning revascularisation by determining the disease complexity, vessel size, lesion length and tissue composition of the atherosclerotic plaque, as well as the best fluoroscopic viewing angle; it may also help in selecting adjunctive percutaneous devices (e.g., rotational atherectomy) and in determining the best landing zone for stents or bypass grafts.

Comparison of risk assessment strategies incorporating coronary artery calcium score with estimation of pretest probability to defer cardiovascular testing in patients with stable chest pain

BACKGROUND

The risk assessment of patients with stable chest pain (SCP) to defer further cardiovascular testing is crucial, but the most appropriate risk assessment strategy remains unknown. We aimed to compare current strategies to identify low risk SCP patients.

METHODS

5289 symptomatic patients who had undergone coronary artery calcium score (CACS) and coronary computed tomographic angiography scan were identified and followed. Pretest probability (PTP) of obstructive coronary artery disease (CAD) for every patient was estimated according to European Society of Cardiology (ESC)-PTP model and CACS-weighted clinical likelihood (CACS-CL) model, respectively. Based on the 2019 ESC guideline-determined risk assessment strategy (ESC strategy) and CACS-CL model-based risk assessment strategy (CACS-CL strategy), all patients were divided into low and high risk group, respectively. Area under receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) was used.

RESULTS

CACS-CL model provided more robust estimation of PTP than ESC-PTP model did, with a larger AUC (0.838 versus 0.735, p < 0.0001), positive IDI (9%, p < 0.0001) and less discrepancy between observed and predicted probabilities. As a result, compared to ESC strategy which only applied CACS-CL model to patients with borderline ESC-PTP, CACS-CL strategy incorporating CACS with estimation of PTP to entire SCP patients indicated a positive NRI (19%, p < 0.0001) and a stronger association to major adverse cardiovascular events, with hazard ratios: 3.97 (95% confidence intervals: 2.75-5.72) versus 5.11 (95% confidence intervals: 3.40-7.69).

CONCLUSION

The additional use of CACS for all SCP patients in CACS-CL strategy improved the risk assessment of SCP patients to identify individuals at low risk.

Assessment of the Efficiency of Non-Invasive Diagnostic Imaging Modalities for Detecting Myocardial Ischemia in Patients Suspected of Having Stable Angina

This study aimed to assess and compare the efficiency of non-invasive imaging modalities in detecting myocardial ischemia in patients with suspected stable angina as easy-to-understand indices. Our study included 1000 patients with chest pain and possible stable myocardial ischemia. The modalities to be assessed were cardiac magnetic resonance imaging (CMRI), single-photon emission computed tomography, positron emission computed tomography (PET), stress echocardiography, and fractional flow reserve derived from coronary computed tomography angiography (FFRCT). As a simulation study, we assumed that all five imaging modalities were performed on these patients, and a decision tree analysis was conducted. From the results, the following efficiencies were assessed and compared: (1) number of true positive (TP), false positive (FP), false negative (FN), and true negative (TN) test results; (2) positive predictive value (PPV); (3) negative predictive value (NPV); (4) post-test probability; (5) diagnostic accuracy (DA); and (6) number needed to diagnose (NND). In the basic settings (pre-test probability: 30%), PET generated the highest TP (267) and NPV (95%, 95% confidence interval (CI): 93-96%). In contrast, CMRI produced the highest TN (616), PPV (76%, 95% CI: 71-80%), and DA (88%, 95% CI: 86-90%) and the lowest NND (1.33, 95% CI: 1.24-1.47). Although FFRCT generated the highest TP (267) and lowest FN (33), it generated the highest FP (168). In terms of detecting myocardial ischemia, compared with the other modalities, PET and CMRI were more efficient. The results of our study might be helpful for both patients and medical professionals associated with their examination.

Coronary Calcium Scoring Improves Risk Prediction in Patients With Suspected Obstructive Coronary Artery Disease

BACKGROUND

In patients with suspected obstructive coronary artery disease (CAD), the risk factor-weighted clinical likelihood (RF-CL) model and the coronary artery calcium score-weighted clinical likelihood (CACS-CL) model improves the identification of obstructive CAD compared with basic pretest probability (PTP) models.

OBJECTIVES

The aim of this study was to assess the prognostic value of the new models.

METHODS

The incidences of myocardial infarction and death were stratified according to categories by the RF-CL and CACS-CL and compared with categories by the PTP model. We used cohorts from a Danish register (n = 41,177) and a North American randomized study (n = 3,952). All patients were symptomatic and were referred for diagnostic testing because of clinical indications.

RESULTS

Despite substantial down-reclassification of patients to a likelihood ≤5% of CAD with either the RF-CL (45%) or CACS-CL (60%) models compared with the PTP (18%), the annualized event rates of myocardial infarction and death were low using all 3 models; RF-CL 0.51% (95% CI: 0.46-0.56), CACS-CL 0.48% (95% CI: 0.44-0.56), and PTP 0.37% (95% CI: 0.31-0.44), respectively. Overall, comparison of the predictive power of the 3 models using Harrell's C-statistics demonstrated superiority of the RF-CL (0.64 [95% CI: 0.63-0.65]) and CACS-CL (0.69 [95% CI: 0.67-0.70]) compared with the PTP model (0.61 [95% CI: 0.60-0.62]).

CONCLUSIONS

The simple clinical likelihood models that include classical risk factors or risk factors combined with CACS provide improved risk stratification for myocardial infarction and death compared with the standard PTP model. Hence, the optimized RF-CL and CACS-CL models identify 2.5 and 3.3 times more patients, respectively, who may not benefit from further diagnostic testing.

Improved pre-test likelihood estimation of coronary artery disease using phonocardiography

Aims

Current early risk stratification of coronary artery disease (CAD) consists of pre-test probability scoring such as the 2019 ESC guidelines on chronic coronary syndromes (ESC2019), which has low specificity and thus rule-out capacity. A newer clinical risk factor model (risk factor-weighted clinical likelihood, RF-CL) showed significantly improved rule-out capacity over the ESC2019 model. The aim of the current study was to investigate if the addition of acoustic features to the RF-CL model could improve the rule-out potential of the best performing clinical risk factor models.

Methods and results

Four studies with heart sound recordings from 2222 patients were pooled and distributed into two data sets: training and test. From a feature bank of 40 acoustic features, a forward-selection technique was used to select three features that were added to the RF-CL model. Using a cutoff of 5% predicted risk of CAD, the developed acoustic-weighted clinical likelihood (A-CL) model showed significantly (P < 0.05) higher specificity of 48.6% than the RF-CL model (specificity of 41.5%) and ESC 2019 model (specificity of 6.9%) while having the same sensitivity of 84.9% as the RF-CL model. Area under the curve of the receiver operating characteristic for the three models was 72.5% for ESC2019, 76.7% for RF-CL, and 79.5% for A-CL.

Conclusion

The proposed A-CL model offers significantly improved rule-out capacity over the ESC2019 model and showed better overall performance than the RF-CL model. The addition of acoustic features to the RF-CL model was shown to significantly improve early risk stratification of symptomatic patients suspected of having stable CAD.

Machine learning models of clinically relevant biomarkers for the prediction of stable obstructive coronary artery disease

Background

In patients with suspected obstructive coronary artery disease (CAD), evaluation using a pre-test probability model is the key element for diagnosis; however, its accuracy is controversial. This study aimed to develop machine learning (ML) models using clinically relevant biomarkers to predict the presence of stable obstructive CAD and to compare ML models with an established pre-test probability of CAD models.

Methods

Eight machine learning models for prediction of obstructive CAD were trained on a cohort of 1,312 patients [randomly split into the training (80%) and internal validation sets (20%)]. Twelve clinical and blood biomarker features assessed on admission were used to inform the models. We compared the best-performing ML model and established the pre-test probability of CAD (updated Diamond-Forrester and CAD consortium) models.

Results

The CatBoost algorithm model showed the best performance (area under the receiver operating characteristics, AUROC, 0.796, and 95% confidence interval, CI, 0.740-0.853; Matthews correlation coefficient, MCC, 0.448) compared to the seven other algorithms. The CatBoost algorithm model improved risk prediction compared with the CAD consortium clinical model (AUROC 0.727; 95% CI 0.664-0.789; MCC 0.313). The accuracy of the ML model was 74.6%. Age, sex, hypertension, high-sensitivity cardiac troponin T, hemoglobin A1c, triglyceride, and high-density lipoprotein cholesterol levels contributed most to obstructive CAD prediction.

Conclusion

The ML models using clinically relevant biomarkers provided high accuracy for stable obstructive CAD prediction. In real-world practice, employing such an approach could improve discrimination of patients with suspected obstructive CAD and help select appropriate non-invasive testing for ischemia.

Assessment of Pre-test and Clinical Probability in the Diagnosis of Chronic Coronary Syndrome — What's New?

In the 2019 European Society of Cardiology (ESC) guidelines, the diagnostic algorithm for chronic coronary syndrome (CCS) was significantly changed, a significant revision of the pretest probability assessment scale (PTP) was made, an assessment of the clinical probability of obstructive coronary artery disease was proposed, the recommendations on the use of diagnostic tests in various groups of patients were updated. Such a radical change in approaches to the diagnosis of CCS raised many questions that had to be answered by further studies conducted in the past two years. The review provides data on the validation of the new PTP scale and the proposed assessment of the clinical probability of obstructive coronary artery disease, taking into account risk factors and with the additional inclusion of information on the calcium index of coronary arteries. The proposals of experts on new algorithms for the choice of non-invasive / invasive examination of this category of patients were also considered. Overall, the new PTV rating scale (ECS 2019) has been validated and validated in retrospective analyzes of cohort studies. The scale for assessing the clinical likelihood of obstructive coronary artery disease makes it possible to classify 3.8-5 times more patients as a low probability of coronary artery disease compared to the assessment of PTP alone. Assessment of the post-test probability of coronary artery disease does not allow to confirm the presence of obstructive lesion and was not used. The experts proposed new modifications of the diagnostic algorithm (with a detailed assessment of the clinical probability, as well as without taking it into account), which require verification in further studies. Therefore, it is advisable to conduct prospective studies to confirm the possibility of reducing the total number of non-invasive and invasive studies in patients with suspected coronary heart disease, as well as the safety of such a decrease in diagnostic procedures.

Comparison of Risk Assessment Strategies for Patients with Diabetes Mellitus and Stable Chest Pain: A Coronary Computed Tomography Angiography Study

BACKGROUND

To compare two risk assessment strategies to identify individuals likely to benefit from further imaging testing in patients with diabetes mellitus (DM) and stable chest pain (SCP) suspected of obstructive coronary artery disease (CAD).

METHODS

602 DM patients referred to coronary computed tomography angiography (CCTA) for SCP were included. They were divided into high- and low-risk groups according to the 2016 National Institute of Health and Care Excellence guideline-determined strategy (NICE strategy) which focused on symptom evaluation and 2019 European Society of Cardiology guideline-determined strategy (ESC strategy) which was based on pretest probability (PTP) sequentially determined by the ESC-PTP estimator and risk factor-weighted clinical likelihood (RF-CL) model, respectively. The associations of clinical outcomes with risk groups and net reclassification improvement (NRI) were evaluated.

RESULTS

The NICE and ESC strategy classified 44% and 39% patients into the low-risk group, respectively. Compared to the NICE strategy, the ESC strategy indicated stronger associations between risk groups and events (hazard ratios: 4.24 versus 1.91), intensive clinical management, and a positive NRI (27.71%, p < 0.0001). The application of the RF-CL model ameliorated the underestimation of risk in patients with borderline ESC-PTP, which principally account for the improvement of the ESC strategy.

CONCLUSION

Compared to the NICE strategy, the ESC strategy seemed to be associated with greater efficiency in identifying high risk individuals in patients with DM and SCP.

The impact and challenges of implementing CTCA according to the 2019 ESC guidelines on chronic coronary syndromes: a survey and projection of CTCA services in the Netherlands

Background

The 2019 ESC-guidelines on chronic coronary syndromes (ESC-CCS) recommend computed tomographic coronary angiography (CTCA) or non-invasive functional imaging instead of exercise ECG as initial test to diagnose obstructive coronary artery disease. Since impact and challenges of these guidelines are unknown, we studied the current utilisation of CTCA-services, status of CTCA-protocols and modeled the expected impact of these guidelines in the Netherlands.

Methods and results

A survey on current practice and CTCA utilisation was disseminated to every Dutch hospital organisation providing outpatient cardiology care and modeled the required CTCA capacity for implementation of the ESC guideline, based on these national figures and expert consensus. Survey response rate was 100% (68/68 hospital organisations). In 2019, 63 hospital organisations provided CTCA-services (93%), CTCA was performed on 99 CTCA-capable CT-scanners, and 37,283 CTCA-examinations were performed. Between the hospital organisations, we found substantial variation considering CTCA indications, CTCA equipment and acquisition and reporting standards. To fully implement the new ESC guideline, our model suggests that 70,000 additional CTCA-examinations would have to be performed in the Netherlands.

Conclusions

Despite high national CTCA-services coverage in the Netherlands, a substantial increase in CTCA capacity is expected to be able to implement the 2019 ESC-CCS recommendations on the use of CTCA. Furthermore, the results of this survey highlight the importance to address variations in image acquisition and to standardise the interpretation and reporting of CTCA, as well as to establish interdisciplinary collaboration and organisational alignment.

Use of Coronary CT Angiography to Predict Obstructive Lesions in Patients with Chest Pain without Enzyme and ST-Segment Elevation

It is challenging to rule out acute coronary syndrome among chest pain patients without both ST-segment elevation in electrocardiography and troponin elevation at emergency departments (ED). The purpose of this study was to develop a prediction model for rapidly determining the occurrence of significant stenosis in coronary computed tomography angiography (CCTA). Retrospective observational cohort study was conducted with 904 patients who had presented with chest pain without troponin elevation and ST-segment changes and underwent CCTA between January 2017 and December 2018. The primary endpoint was the presence of significant stenosis on CCTA, defined as narrowing above 70% diameter. The logistic regression model was used for development a new predictive model. One hundred and thirty-four patients (14.8%) were shown severe stenosis. The independent associated factors for significant stenosis were age ≥65 years, male, diabetes, history of acute coronary syndrome, and typical chest pain. Based these results, we developed a new prediction model. The area under the curve was 0.782 (95% confidence interval 0.742-0.822). Moreover, score of ≥5 was chosen as cut-off values with 86.6% sensitivity and 56.4% specificity. In conclusion, among chest pain patients without ST changes and troponin elevation, the new score will be helpful to identify potential candidate for CCTA such as patients with significant stenosis.

Comparison of Different Investigation Strategies to Defer Cardiac Testing in Patients With Stable Chest Pain

OBJECTIVES

This study aimed to compare the current 5 investigation strategies to defer cardiac testing in patients with stable chest pain.

BACKGROUND

For the clinical management of stable chest pain, the identification of patients unlikely to benefit from further cardiac testing is important, but the most appropriate investigation strategy is unknown.

METHODS

A total of 4,207 patients referred to coronary computed tomography angiography for stable chest pain were classified into low- and high-risk groups according to the 2016 National Institute of Health and Care Excellence (NICE) guideline-determined strategy; PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) minimal risk tool-based strategy; 2019 European Society of Cardiology (ESC) guideline-determined strategy; and coronary artery calcium score (CACS), either in isolation (the CACS strategy) or as part of a weighted clinical likelihood model-based strategy (the CACS-CL strategy). The associations of obstructive coronary artery disease on coronary computed tomography angiography, major adverse cardiovascular events, and subsequent clinical management with risk groups according to different strategies were evaluated and compared.

RESULTS

The NICE, PROMISE, ESC, CACS, and CACS-CL strategies classified a proportion (22.63%, 29.21%, 41.84%, 46.76%, and 51.41%, respectively) of patients into low-risk groups. Compared with the NICE, PROMISE, ESC, and CACS strategies, the CACS-CL strategy had a stronger association between risk groups and obstructive coronary artery disease (odd ratios: 16.00 vs 2.93, 5.53, 7.94, and 10.39, respectively), major adverse cardiovascular events (HRs: 6.83 vs 1.90, 2.94, 4.23, and 5.13, respectively) and intensive subsequent clinical management as well as better metrics of diagnostic accuracy and positive net reclassification improvement.

CONCLUSIONS

Among contemporary strategies used to identify patients with stable chest pain at low risk, the use of CACS, especially when combined with clinical risk features, showed the strongest potential to effectively defer cardiac testing.

Troponin-Guided Coronary Computed Tomographic Angiography After Exclusion of Myocardial Infarction

BACKGROUND

Patients with suspected acute coronary syndrome in whom myocardial infarction has been excluded are at risk of future adverse cardiac events.

OBJECTIVES

This study evaluated the usefulness of high-sensitivity cardiac troponin I (hs-cTnI) to select patients for further investigation after myocardial infarction has been excluded.

METHODS

This is a prospective cohort study of patients presenting to the emergency department with suspected acute coronary syndrome and hs-cTnI concentrations below the sex-specific 99th percentile. Patients were recruited in a 2:1 fashion, stratified by peak hs-cTnI concentration above and below the risk stratification threshold of 5 ng/L. All patients underwent coronary computed tomography angiography (CCTA) after hospital discharge.

RESULTS

Overall, 250 patients were recruited (61.4 ± 12.2 years 31% women) in whom 62.4% (156 of 250 patients) had coronary artery disease (CAD). Patients with intermediate hs-cTnI concentrations (between 5 ng/L and the sex-specific 99th percentile) were more likely to have CAD than those with hs-cTnI concentrations <5 ng/L (71.9% [120 of 167 patients] vs 43.4% [36 of 83 patients]; odds ratio: 3.33; 95% CI: 1.92-5.78). Conversely, there was no association between anginal symptoms and CAD (63.2% [67 of 106 patients] vs 61.8% [89 of 144 patients]; odds ratio: 0.92; 95% CI: 0.48-1.76). Most patients with CAD did not have a previous diagnosis (53.2%; 83 of 156 patients) and were not on antiplatelet and statin therapies (63.5%; 99 of 156 patients) before they underwent CCTA.

CONCLUSIONS

In patients who had myocardial infarction excluded, CAD was 3× more likely in those with intermediate hs-cTnI concentrations compared with low hs-cTnI concentrations. In such patients, CCTA could help to identify those with occult CAD and to target preventative treatments, thereby improving clinical outcomes.

Coronary Computed Tomographic Angiography for Complete Assessment of Coronary Artery Disease: JACC State-of-the-Art Review

Coronary computed tomography angiography (CTA) has shown great technological improvements over the last 2 decades. High accuracy of CTA in detecting significant coronary stenosis has promoted CTA as a substitute for conventional invasive coronary angiography in patients with suspected coronary artery disease. In patients with coronary stenosis, CTA-derived physiological assessment is surrogate for intracoronary pressure and velocity wires, and renders possible decision-making about revascularization solely based on computed tomography. Computed tomography coronary anatomy with functionality assessment could potentially become a first line in diagnosis. Noninvasive imaging assessment of plaque burden and morphology is becoming a valuable substitute for intravascular imaging. Recently, wall shear stress and perivascular inflammation have been introduced. These assessments could support risk management for both primary and secondary cardiovascular prevention. Anatomy, functionality, and plaque composition by CTA tend to replace invasive assessment. Complete CTA assessment could provide a 1-stop-shop for diagnosis, risk management, and decision-making on treatment.

Discrimination capability of pretest probability of stable coronary artery disease: a systematic review and meta-analysis suggesting how to improve validation procedures

OBJECTIVE

Externally validated pretest probability models for risk stratification of subjects with chest pain and suspected stable coronary artery disease (CAD), determined through invasive coronary angiography or coronary CT angiography, are analysed to characterise the best validation procedures in terms of discriminatory ability, predictive variables and method completeness.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Global Health (Ovid), Healthstar (Ovid) and MEDLINE (Ovid) searched on 22 April 2020.

ELIGIBILITY CRITERIA

We included studies validating pretest models for the first-line assessment of patients with chest pain and suspected stable CAD. Reasons for exclusion: acute coronary syndrome, unstable chest pain, a history of myocardial infarction or previous revascularisation; models referring to diagnostic procedures different from the usual practices of the first-line assessment; univariable models; lack of quantitative discrimination capability.

METHODS

Eligibility screening and review were performed independently by all the authors. Disagreements were resolved by consensus among all the authors. The quality assessment of studies conforms to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A random effects meta-analysis of area under the receiver operating characteristic curve (AUC) values for each validated model was performed.

RESULTS

27 studies were included for a total of 15 models. Besides age, sex and symptom typicality, other risk factors are smoking, hypertension, diabetes mellitus and dyslipidaemia. Only one model considers genetic profile. AUC values range from 0.51 to 0.81. Significant heterogeneity (p<0.003) was found in all but two cases (p>0.12). Values of I² >90% for most analyses and not significant meta-regression results undermined relevant interpretations. A detailed discussion of individual results was then carried out.

CONCLUSIONS

We recommend a clearer statement of endpoints, their consistent measurement both in the derivation and validation phases, more comprehensive validation analyses and the enhancement of threshold validations to assess the effects of pretest models on clinical management.

PROSPERO REGISTRATION NUMBER

CRD42019139388.

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.

Coronary stenoses in patients suspected to have obstructive coronary artery disease: the exemption rather than the rule!

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ESC 2019 guidelines on chronic coronary syndromes: could calcium scoring improve detection of coronary artery disease in patients with low risk score. Findings from a retrospective cohort of patients in a district general hospital

BACKGROUND

The European Society of Cardiology (ESC) published an updated stable chest pain guideline in 2019, recommending the use of an updated pre-test probability (PTP) risk score (RS) to assess the likelihood of coronary artery disease (CAD). We sought to compare the 2019 and 2013 PTPRS in a contemporary cohort of patients.

METHODS

612 patients who were investigated with computed tomography coronary angiography (CTCA) for stable chest pain were included in a retrospective analysis.

RESULTS

There were 255 patients with 2019 PTPRS 15-50% with a 9% yield of severe CAD on CTCA, compared with 402 patients and a 4% yield using the 2013 PTPRS (p = 0.01). 355 patients had a 2019 PTPRS of <15%, with 3% found to have severe CAD, compared with 67 patients and none with severe CAD using the 2013 PTPRS (p = 0.14). 336 of patients with 2019 PTPRS of <15% had a calcium score as part of the CTCA. 223 of these had a zero calcium score and only one had severe CAD. In comparison, 113 patients had a positive calcium score, and 10 (9%) had severe CAD (p < 0.001).

DISCUSSION

The ESC 2019 PTPRS classifies more patients as at lower risk of CAD and hence reduces the risk overestimation associated with the 2013 PTPRS. However, in patients with a 2019 PTPRS of <15%, who would not be investigated, the use of the calcium score detected the majority of patients with significant CAD, who may benefit from secondary prevention and an associated mortality benefit as per the SCOT-Heart trial.

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.