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Significant advances have been made in artificial intelligence technology in recent years. Many health care applications have been investigated to assist clinicians and the technology is close to being integrated into routine clinical practice. The high prevalence of cardiac disease in Australia places overwhelming demands on the existing health care system, challenging its capacity to provide quality patient care. Artificial intelligence has emerged as a promising solution. This discussion paper provides an Australian perspective on the current state of artificial intelligence in cardiology, including the benefits and challenges of implementation. This paper highlights some current artificial intelligence applications in cardiology, while also detailing challenges such as data privacy, ethical considerations, and integration within existing health infrastructures. Overall, this paper aims to provide insights into the potential benefits of artificial intelligence in cardiology, while also acknowledging the barriers that need to be addressed to ensure safe and effective implementation into an Australian health system. [ABSTRACT FROM AUTHOR]

Computed tomography coronary angiography (CTCA) is a non-invasive diagnostic modality that provides a comprehensive anatomical assessment of the coronary arteries and coronary atherosclerosis, including plaque burden, composition and morphology. The past decade has witnessed an increase in the role of CTCA for evaluating patients with both stable and acute chest pain, and recent international guidelines have provided increasing support for a first line CTCA diagnostic strategy in select patients. CTCA offers some advantages over current functional tests in the detection of obstructive and non-obstructive coronary artery disease, as well as for ruling out obstructive coronary artery disease. Recent randomised trials have also shown that CTCA improves prognostication and guides the use of guideline-directed preventive therapies, leading to improved clinical outcomes. CTCA technology advances such as fractional flow reserve, plaque quantification and perivascular fat inflammation potentially allow for more personalised risk assessment and targeted therapies. Further studies evaluating demand, supply, and cost-effectiveness of CTCA for evaluating chest pain are required in Australia. This discussion paper revisits the evidence supporting the use of CTCA, provides an overview of its implications and limitations, and considers its potential role for chest pain evaluation pathways in Australia. [ABSTRACT FROM AUTHOR]

Introduction: Lipoprotein(a) [Lp(a)] and diabetes are independently associated with premature coronary artery disease (pCAD). However, there is an inverse relationship between Lp(a) concentration and type 2 diabetes (T2D) risk. We examine whether Lp(a) distribution in patients with pCAD differs between those with or without T2D, and whether elevated Lp(a) is associated with pCAD in patients with T2D.Methods: Lp(a) concentration was measured in consecutive acute coronary syndrome (ACS) patients in two coronary care units (study one: ACS with or without diabetes, study two: ACS and diabetes). Elevated Lp(a) mass concentration was defined as ≥0.5 g/L and pCAD where CAD was diagnosed age <60 years. The association between elevated Lp(a) and pCAD was assessed using logistic regression.Results: Of 449 patients, 233 (51.9%) had pCAD and 278 (61.9%) had T2D. In patients with pCAD, those with T2D had a significantly lower median Lp(a) concentration (0.13 g/L versus 0.27 g/L, p=0.004). In patients with T2D, elevated Lp(a) was significantly associated with pCAD (OR 2.419, 95% CI 1.513-3.867, p<0.001). After adjusting for gender, smoking, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides, elevated Lp(a) remained significantly associated with pCAD (OR 2.895, 95% CI 1.427-5.876, p=0.003) in patients with T2D.Conclusions: In coronary care patients with pCAD, patients with T2D had lower Lp(a) concentrations than those without T2D. Despite this, elevated Lp(a) remained predictive of pCAD in patients with T2D. Measurement of Lp(a) should be considered in younger adults with T2D to identify who may benefit from earlier preventative therapies to reduce pCAD burden. [ABSTRACT FROM AUTHOR]