ABSTRACT
Both types of aortic dissection (AD), Stanford type A and type B, can result in complications such as acute kidney injury (AKI) and aortic rupture. Renal complications in AD arise from compromised renal perfusion affecting the renal arteries. Understanding the intricate connection between AD and AKI is crucial for navigating the complexities of tailored treatment and formulating specific management plans. Concerning machine learning models, in patients with type A aortic dissection, factors such as decreased platelet count on admission, increased D-dimer level, longer cardiopulmonary bypass duration, elevated white blood cell levels, the need for blood transfusion, longer aortic clamp time, extended surgery duration, advanced age, and an elevated body mass index were positively associated with the development of AKI. For the risk of AKI after type B aortic dissection, elevated Nt-pro brain natriuretic peptide, prolonged activated partial thromboplastin time, elevated admission systolic blood pressure, and a higher contrast agent requirement during operative repair were found to predict the risk. Male gender was associated with a higher risk of AKI, and nonwhite race was linked to a higher risk of AKI, a greater likelihood of requiring more urgent procedures, and lower levels of insurance coverage. The treatment of AKI following AD requires a multifaceted approach. Identifying and addressing the underlying cause, such as low blood pressure, renal artery involvement, or medication-induced injury, is crucial for effective management and preventing further kidney damage. Maintaining proper fluid balance is essential for improving renal perfusion, but careful monitoring is necessary to avoid complications. The evolving landscape of research, particularly in biomarkers and AI programs, reveals a promising role in predicting the risk for and managing AKI post-AD.
ABSTRACT
The 2019 American College of Cardiology and American Heart Association guidelines regarding low-dose aspirin in the primary prevention of atherosclerotic cardiovascular disease (ASCVD) indicate an increased risk of bleeding without a net benefit. The coronary artery calcium (CAC) score could be used to guide aspirin therapy in high-risk patients without an increased risk of bleeding. With this systematic review, we aimed to analyze studies that have investigated the role of CAC in primary prevention with aspirin. A total of 4 relevant studies were identified and the primary outcomes of interest were bleeding events and major adverse cardiac events. The outcomes of interest were stratified into 3 groups based on CAC scoring: 0, 1 to 99, and ≥100. A study concluded from 2,191 patients that with a low bleeding risk, CAC ≥100, and ASCVD risk ≥5% aspirin confers a net benefit, whereas patients with a high bleeding risk would experience a net harm, irrespective of ASCVD risk or CAC. All other studies demonstrated net benefit in patients with CAC ≥100 with a clear benefit. CAC scores correspond to calcified plaque in coronary vessels and are associated with graded increase in adverse cardiovascular events. Our review has found that in the absence of a significant bleeding risk, increased ASCVD risk and CAC score corelate with increased benefit from aspirin. A study demonstrated a decrease in the odds of myocardial infarction from 3 to 0.56 in patients on aspirin. The major drawback of aspirin for primary prevention is the bleeding complication. At present, there is no widely validated tool to predict the bleeding risk with aspirin, which creates difficulties in accurately delineating risk. Barring some discrepancy between studies, evidence shows a net harm for the use of aspirin in low ASCVD risk (<5%), irrespective of CAC score.
