scholarly journals Influence of symptom typicality for predicting MACE in patients without obstructive coronary artery disease: From the CONFIRM Registry (Coronary Computed Tomography Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry)

2018 ◽  
Vol 41 (5) ◽  
pp. 586-593 ◽  
Author(s):  
Ji Hyun Lee ◽  
Donghee Han ◽  
Bríain ó Hartaigh ◽  
Heidi Gransar ◽  
Yao Lu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Clinical Outcomes ◽  
Computed Tomography Angiography ◽  
Coronary Computed Tomography Angiography ◽  
Obstructive Coronary Artery Disease ◽  
Artery Disease ◽  
International Multicenter ◽  
Multicenter Registry

scholarly journals Clinical risk factors and atherosclerotic plaque extent to define risk for major events in patients without obstructive coronary artery disease: the long-term coronary computed tomography angiography CONFIRM registry

2020 ◽  
Vol 21 (5) ◽  
pp. 479-488 ◽  
Author(s):  
Alexander R van Rosendael ◽  
A Maxim Bax ◽  
Jeff M Smit ◽  
Inge J van den Hoogen ◽  
Xiaoyue Ma ◽  
...  
Keyword(s):  
Risk Factors ◽  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Computed Tomography Angiography ◽  
Prognostic Value ◽  
Coronary Computed Tomography Angiography ◽  
Obstructive Coronary Artery Disease ◽  
Artery Disease

Abstract Aims In patients without obstructive coronary artery disease (CAD), we examined the prognostic value of risk factors and atherosclerotic extent. Methods and results Patients from the long-term CONFIRM registry without prior CAD and without obstructive (≥50%) stenosis were included. Within the groups of normal coronary computed tomography angiography (CCTA) (N = 1849) and non-obstructive CAD (N = 1698), the prognostic value of traditional clinical risk factors and atherosclerotic extent (segment involvement score, SIS) was assessed with Cox models. Major adverse cardiac events (MACE) were defined as all-cause mortality, non-fatal myocardial infarction, or late revascularization. In total, 3547 patients were included (age 57.9 ± 12.1 years, 57.8% male), experiencing 460 MACE during 5.4 years of follow-up. Age, body mass index, hypertension, and diabetes were the clinical variables associated with increased MACE risk, but the magnitude of risk was higher for CCTA defined atherosclerotic extent; adjusted hazard ratio (HR) for SIS >5 was 3.4 (95% confidence interval [CI] 2.3–4.9) while HR for diabetes and hypertension were 1.7 (95% CI 1.3–2.2) and 1.4 (95% CI 1.1–1.7), respectively. Exclusion of revascularization as endpoint did not modify the results. In normal CCTA, presence of ≥1 traditional risk factors did not worsen prognosis (log-rank P = 0.248), while it did in non-obstructive CAD (log-rank P = 0.025). Adjusted for SIS, hypertension and diabetes predicted MACE risk in non-obstructive CAD, while diabetes did not increase risk in absence of CAD (P-interaction = 0.004). Conclusion Among patients without obstructive CAD, the extent of CAD provides more prognostic information for MACE than traditional cardiovascular risk factors. An interaction was observed between risk factors and CAD burden, suggesting synergistic effects of both.

scholarly journals Occult obstructive coronary artery disease is associated with prolonged cardiac troponin elevation following strenuous exercise

2019 ◽  
Vol 27 (11) ◽  
pp. 1212-1221 ◽  
Author(s):  
Øyunn Kleiven ◽  
Torbjørn Omland ◽  
Øyvind Skadberg ◽  
Tor H Melberg ◽  
Magnus F Bjørkavoll-Bergseth ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Computed Tomography Angiography ◽  
Cardiac Troponin ◽  
Coronary Computed Tomography Angiography ◽  
Obstructive Coronary Artery Disease ◽  
Strenuous Exercise ◽  
Coronary Computed Tomography ◽  
Artery Disease

Background Sudden cardiac death among middle-aged recreational athletes is predominantly due to myocardial ischaemia. This study examined whether measuring cardiac troponin I and T (cTnI and cTnT) after strenuous exercise could identify occult obstructive coronary artery disease. Design Prospective observational study. Methods Subjects were recruited from 1002 asymptomatic recreational cyclists completing a 91-km mountain bike race (North Sea Race Endurance Exercise Study). No subject had known cardiovascular disease or took cardiovascular medication. Blood samples were collected within 24 h before and 3 h and 24 h after the race. Coronary computed tomography angiography was performed in 80 participants with the highest post-exercise cTnI and in 40 reference subjects with moderately elevated cTnI values. Results Study subjects ( N = 120) were 45 (36–52) years old and 74% were male. There were similar demographics in the High-cTnI group and the Reference group. The cTn concentrations were highest at 3 h post-race: cTnI, 224 (125–304) ng/L; cTnT, 89 (55–124) ng/L. Nine subjects had obstructive coronary artery disease on coronary computed tomography angiography, eight of whom were High-cTnI responders. Two subjects had myocardial bridging, both High-cTnI responders. Troponin concentrations at 24 h post-race were higher in subjects with obstructive coronary artery disease than in the rest of the cohort ( n = 109): cTnI, 151 (72–233) ng/L vs. 24 (19–82) ng/L, p = 0.005; cTnT, 39 (25–55) ng/L vs. 20 (14–31) ng/L, p = 0.002. The areas under the receiver operating characteristic curves for predicting obstructive coronary artery disease were 0.79, p = 0.005 (cTnI) and 0.82, p = 0.002 (cTnT). Conclusion In subjects with occult obstructive coronary artery disease there was a prolonged elevation of cTn following strenuous exercise.

scholarly journals Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry

2019 ◽  
Author(s):  
Subhi J Al’Aref ◽  
Gabriel Maliakal ◽  
Gurpreet Singh ◽  
Alexander R van Rosendael ◽  
Xiaoyue Ma ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Computed Tomography Angiography ◽  
Coronary Artery Calcium ◽  
Coronary Computed Tomography Angiography ◽  
Obstructive Coronary Artery Disease ◽  
Clinical Score ◽  
Artery Disease

Abstract Aims Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and the coronary artery calcium score (CACS), to predict the presence of obstructive CAD on coronary computed tomography angiography (CCTA). Methods and results The study screened 35 281 participants enrolled in the CONFIRM registry, who underwent ≥64 detector row CCTA evaluation because of either suspected or previously established CAD. A boosted ensemble algorithm (XGBoost) was used, with data split into a training set (80%) on which 10-fold cross-validation was done and a test set (20%). Performance was assessed of the (1) ML model (using 25 clinical and demographic features), (2) ML + CACS, (3) CAD consortium clinical score, (4) CAD consortium clinical score + CACS, and (5) updated Diamond-Forrester (UDF) score. The study population comprised of 13 054 patients, of whom 2380 (18.2%) had obstructive CAD (≥50% stenosis). Machine learning with CACS produced the best performance [area under the curve (AUC) of 0.881] compared with ML alone (AUC of 0.773), CAD consortium clinical score (AUC of 0.734), and with CACS (AUC of 0.866) and UDF (AUC of 0.682), P < 0.05 for all comparisons. CACS, age, and gender were the highest ranking features. Conclusion A ML model incorporating clinical features in addition to CACS can accurately estimate the pretest likelihood of obstructive CAD on CCTA. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream management.

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