Subclinical coronary artery disease in veteran athletes: is a new preparticipation methodology required?

2018 ◽  
pp. bjsports-2018-099840 ◽  
Author(s):  
Hélder Dores ◽  
Pedro de Araújo Gonçalves ◽  
José Monge ◽  
Rogério Costa ◽  
Luis Tátá ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Stratification ◽  
Exercise Testing ◽  
Myocardial Ischaemia ◽  
Cardiac Ct ◽  
Exercise Tests ◽  
Atherosclerotic Burden ◽  
Artery Disease

ObjectivePreparticipation evaluation of veteran athletes should focus on accurate cardiovascular (CV) risk stratification and subclinical detection of coronary artery disease (CAD), which is the main cause of sudden cardiac death in this population. We aimed to investigate the effectiveness of current preparticipation methodology used to identify veteran athletes with high coronary atherosclerotic burden.MethodsA total of 105 asymptomatic male athletes aged ≥40 years old, with low to moderate CV risk (Systematic Coronary Risk Estimation <5%) who trained ≥4 hours/week for at least 5 years, were studied. The screening protocol included clinical evaluation, ECG, transthoracic echocardiogram and exercise testing. Cardiac CT was performed to detect CAD, defined as a high atherosclerotic burden according to coronary artery calcium score and coronary CT angiography.ResultsThe majority of the athletes (n=88) engaged in endurance sports, with a median volume of exercise of 66 (44; 103) metabolic equivalent task score/hour/week. Exercise testing was abnormal in 13 (12.4%) athletes, 6 (5.7%) with electrocardiographic criteria for myocardial ischaemia and 7 (6.7%) with exercise-induced ventricular arrhythmias. A high coronary atherosclerotic burden was present in 27 (25.7%) athletes, of whom 11 (40.7%) had CV risk factors and 6 had abnormal exercise tests, including 3 who were positive for myocardial ischaemia.ConclusionsConventional methodology used in preparticipation evaluation of veteran athletes, based on clinical CV risk factors and exercise testing, was poor at identifying significant subclinical CAD. The inclusion of more objective markers, particularly data derived from cardiac CT, is promising for more accurate CV risk stratification of these athletes.

P6167Low leptin plasma levels are associated with progression of coronary atherosclerosis in patients with stable coronary artery disease from the SMARTool Study

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
C Caselli ◽  
S Rocchiccioli ◽  
A Rosendael ◽  
R Buechel ◽  
A Teresinska ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Plasma Levels ◽  
Coronary Atherosclerosis ◽  
Atherosclerotic Burden ◽  
Artery Disease ◽  
Stable Cad ◽  
Plasma Leptin

Abstract Background Leptin is an adipokine involved in energy homeostasis and has been related with established vascular risk factors. However, studies on the association of leptin plasma levels with coronary artery disease (CAD) have yielded conflicting results. Purpose Aim of the present study was to evaluate the association between leptin plasma levels and presence, severity and progression of coronary atherosclerosis in patients with suspected stable CAD. Methods In a cohort of 257 patients with symptoms of stable CAD enrolled in the SMARTool study, coronary computed tomography angiography (CTA), plasma leptin levels and clinical and bio-humoral CAD risk profile (including glucose, lipid and inflammation variables) were obtained at enrolment and after 6±1yrs of follow-up. Sixty-four patients were revascularized and the remaining 193 represent the population for the present study. CTA findings were categorised as no-minimal CAD (<30% stenosis), non-obstructive CAD (30%-50% stenosis) and obstructive CAD (≥50% stenosis in at least one major coronary vessel). A CTA risk score (based on plaque extent, severity, composition, and location) was calculated at baseline and at follow-up to assess coronary atherosclerotic burden and its progression (Δ CTA score≥5). Results CTA findings showed obstructive CAD in 11% of patients at baseline and in 15% at follow-up (p<0.0001). CTA risk score, was 8.03±7.80 at baseline and increased to 10.33±8.17 at follow-up (p<0.0001) with CAD progression in 20% of patients. Leptin plasma levels were inversely related with CTA findings both at baseline and follow-up (Figure). In a Cox model, baseline plasma leptin was an independent predictor of CAD progression, after adjustment for clinical risk factors, biomarkers, and treatment (HR 0.572, 95% CI 0.393–0.834, P=0.0037). Figure 1 Conclusion Plasma leptin is inversely associated with coronary atherosclerotic burden and disease progression in patients with stable CAD. This association is independent of known factors affecting leptin levels. These results could prompt further investigations on the pathophysiological mechanisms of this association. Acknowledgement/Funding EU H2020 research and innovation program under grant agreement No 689068

scholarly journals Carotid intima-media thickness as a marker for assessing the severity of coronary artery disease on coronary angiography

2018 ◽  
Vol 6 (4) ◽  
pp. 1283 ◽  
Author(s):  
Asif S. Wani ◽  
Zafirah . ◽  
Samia Rashid ◽  
Hanief M. Tantray
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
At Risk ◽  
Coronary Artery ◽  
Coronary Angiography ◽  
Intima Media Thickness ◽  
Carotid Intima Media Thickness ◽  
Atherosclerotic Burden ◽  
Simple Tool ◽  
Artery Disease

Background: Coronary artery disease (CAD), the leading cause of death worldwide, has a huge area of primary prevention where patients at risk can be identified for more intensive, evidence-based medical interventions to reduce cardiovascular events. Whereas coronary angiography has stood the test of time to assess atherosclerotic burden, it is still unavailable to a huge population at risk of CAD. This study was devised in search of a cheap and simple tool to assess atherosclerotic burden. We aimed to investigate the relationship between Carotid Intima Media Thickness (CIMT) and Coronary Artery Disease (CAD) in patients evaluated by coronary angiography for suspected CAD and whether CIMT could predict the extension of CAD.Methods: This study was a cross-sectional study conducted from March 2013 to September 2015 in Department of Medicine, SMHS Hospital, J and K, India. A total of 100 patients admitted to for undergoing coronary angiography indicated for suspected coronary artery disease were enrolled. the risk factors evaluated in this study included age, body mass index, sex, dyslipidemia, hypertension, diabetes mellitus and smoking. CAD was assessed and classified by coronary angiography and CIMT was assessed by carotid doppler.Results: There was a positive relationship between CIMT and CAD. Risk factors like Age, smoking, BMI, cholesterol, hypertension, and diabetes had significant positive effect on CIMT; whereas gender, VLDL, triglycerides, HDL and LDL were statistically insignificant in affecting CIMT.Conclusions: CIMT is a cheap and simple tool to predict the extent of CAD.

Vasospasm induced myocardial ischaemia secondary to sumatriptan use

2020 ◽  
Vol 13 (8) ◽  
pp. e235387 ◽  
Author(s):  
Kenneth Okonkwo ◽  
Utkarsh Ojha
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Coronary Arteries ◽  
Myocardial Ischaemia ◽  
Myocardial Infarctions ◽  
Acute Migraine ◽  
Artery Disease ◽  
Cluster Headaches ◽  
Prior Risk

Certain medications have been implicated in causing acute myocardial infarctions (AMI). Sumatriptan, a medication usually prescribed for acute migraine and cluster headaches has been documented as potentially causing coronary vasospasm, thereby leading to MI. This is usually seen in patients with strong risk factors for coronary artery disease (CAD) or in those with established CAD. Most cases thus far have been reported in patients using the subcutaneous preparation of sumatriptan. Here, we present a case of a patient without prior risk factors for CAD and angiographically unremarkable coronary arteries who presented with evidence of an AMI after oral sumatriptan use for migraines.

scholarly journals Prediction of obstructive coronary artery disease after Rb-82 PET myocardial perfusion imaging and coronary artery calcium scoring using machine learning

2021 ◽  
Vol 22 (Supplement_3) ◽  
Author(s):  
RJ Metselaar ◽  
JA Van Dalen ◽  
BN Vendel ◽  
M Mouden ◽  
CH Slump ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Stratification ◽  
Coronary Artery Calcium ◽  
Positive Family History ◽  
Unseen Data ◽  
Artery Disease ◽  
Rubidium 82

Abstract Funding Acknowledgements Type of funding sources: None. Background Accurate risk stratification in patients with suspected stable coronary artery disease (CAD) is essential for choosing an appropriate treatment strategy but remains challenging in clinical practice. Purpose Our aim was to develop and validate a risk model to predict the presence of obstructive CAD after Rubidium-82 PET and a coronary artery calcium score (CACS) scan using a machine learning (ML) algorithm. Methods We retrospectively included 1007 patients without prior cardiovascular history and  a low-intermediate pre-test likelihood, referred for rest and regadenoson-induced stress Rubidium-82 PET combined with a CACS scan. Multiple features were included in the ML model; PET derived features such as summed difference score and flow values, CACS, cardiovascular risk factors (cigarette smoking, hypertension, hypercholesterolemia, diabetes, positive family history of CAD), medication; age; gender; body mass index; creatinine serum values; and visual PET interpretation. An XGBoost ML algorithm was developed using a subset of 805 patients to predict obstructive CAD by using 5-fold cross validation in combination with a grid search. Obstructive CAD during follow-up was defined as a significant stenosis during invasive coronary angiography, a percutaneous coronary intervention or a coronary artery bypass graft procedure. The ML algorithm was validated with unseen data of the remaining 202 patients. Results Application of the XGBoost algorithm resulted in an area under the curve (AUC) of 0.93 using the training data (n = 805) and an AUC of 0.89 using the unseen data (n = 202) in predicting obstructive CAD. The strongest predictors were the CAC-scores and quantitative PET derived features. The classical risk factors and medication hardly provided an added value in the prediction of obstructive CAD. Conclusion The developed ML algorithm is able to provide individualized risk stratification by predicting the probability of obstructive CAD.  Although validation with a larger dataset could result in a more well defined performance range, this model already shows potential to be implemented in the diagnostic workflow.

Risk stratification for sudden cardiac death in the general population

ESC CardioMed ◽  
2018 ◽  
pp. 2305-2308
Author(s):  
Efstathios K. Iliodromitis ◽  
Dimitrios Farmakis
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Heart Disease ◽  
Coronary Artery ◽  
Sudden Cardiac Death ◽  
General Population ◽  
Risk Stratification ◽  
Cardiac Death ◽  
Increased Risk ◽  
Artery Disease

There are three main groups in the general population as far as sudden cardiac death (SCD) is concerned: individuals without a known history or predisposing factors for heart disease; individuals with known risk factors for heart disease or SCD; and patients with diagnosed ischaemic, structural, or electrical cardiac conditions, acquired or genetic, that are associated with an increased risk for SCD. Although SCD literature focuses mainly on patients with known heart disease, approximately 50% of SCD cases occur in individuals belonging to the first two groups. The annual incidence of SCD in the general population ranges between 0.6 and greater than 1.4 per 1000 individuals. SCD occurs more commonly in men than in women and with an incidence that increases with age due to the increase in coronary artery disease. The commonest aetiologies for SCD in the general population are coronary artery disease and cardiomyopathy, accounting for 80% and 10–15% of cases, respectively. A number of factors have been related to an increased risk for SCD in the general population including genetic predisposition, risk factors for atherosclerosis, strenuous physical activity and sports, electrocardiographic abnormalities, elevated levels of biomarkers, and abnormalities in imaging and other diagnostic techniques. However, large-scale prospective studies that confirm the feasibility, clinical efficacy, and cost-effectiveness of using these factors for broad mass screening for SCD are generally lacking and therefore risk stratification for SCD in the general population remains challenging.

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