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Introduction: Ischaemic heart disease is the single most common cause of death worldwide. Traditionally, distinguishing patients with cardiac ischaemia from patients with less alarming disease, in prehospital triage of chest pain, is challenging for both general practitioners and ambulance paramedics. Less than 20% of patients with chest pain, transferred to the emergency department (ED), have an acute coronary syndrome (ACS) and the transportation and analysis at the ED of non-ACS patients result in substantial healthcare costs and a great patient burden.

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Coronary artery calcium (CAC) score is a neglected biomarker that can be derived from non-cardiac chest computed tomography scan and represents a surrogate for atherosclerosis. We created a simulation model using different CAC score values in the MESA coronary artery risk score in a population derived from the Fourier Trial. CAC score could modulate the sample sizes of cardiovascular trials in primary and secondary prevention and offer new primary prevention treatments to high-risk subjects with reasonable numbers needed to treat comparable to secondary prevention trials.

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Coronary artery disease (CAD) remains a leading global cause of morbidity and mortality, underscoring the need for effective cardiovascular risk stratification and preventive strategies. Coronary artery calcium (CAC) scoring, traditionally performed using electrocardiogram (ECG)-gated cardiac computed tomography (CT) scans, has been widely validated as a robust tool for assessing cardiovascular risk. However, its application has been largely limited to high-risk populations due to the costs, technical requirements, and limited accessibility of cardiac CT scans.

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A nomogram to distinguish noncardiac chest pain based on cardiopulmonary exercise testing in cardiology clinic.

BMC Med Inform Decis Mak

December 2024

Department of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Background: Psychological disorders, such as anxiety and depression, are considered to be one of the causes of noncardiac chest pain (NCCP). And these patients can be challenging to differentiate from coronary artery disease (CAD), leading to a considerable number of patients still undergoing angiography. We aim to develop a practical prediction model and nomogram using cardiopulmonary exercise testing (CPET), to help identify these patients.

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