Lp(a): A Toolkit for Health Care Professionals

16 z Is it reasonable to recommend universal testing of Lp(a) in everyone, regardless of family history or health status, to encourage healthy habits and inform clinical decision-making? z Will earlier testing and effective interventions help to improve outcomes? z What will be the benefit of medical interventions that target Lp(a) lowering, and how will such therapies change outcomes of people at risk and those currently affected by ASCVD? z Will Lp(a)-lowering therapy be effective in people with low LDL-C, in light of new promising LDL-C– lowering therapies beyond statins, ezetimibe and PCSK9 inhibitors? z What role will Lipoprotein apheresis continue to play in reduction of LDL and Lp(a) in people with FH and anginal symptoms? z What part will artificial intelligence and machine learning play in risk assessment that will expedite patient diagnosis and treatment? AI has the potential to address disparities in medical resources and expedite patient diagnosis and treatment. 4 It may also improve cardiovascular disease risk prediction and facilitate personalized medicine. 16 What Does the Future Hold? Much is now known about Lp(a) and its role in ASCVD and aortic valve disease. But more evidence is needed to inform future recommendations for clinical practice. For Lp(a) to be accepted as a risk factor for intervention, a randomized clinical trial of specific Lp(a) lowering in those at risk is required. Until we have the results of such a trial, several important unanswered questions remain: What part will artificial intelligence and machine learning play in risk assessment that will expedite patient diagnosis and treatment?