The role of phosphodiesterase 9A inhibitors in heart failure.

INTRODUCTION: There are currently limited effective treatments available to improve lusitropy in patients suffering from heart failure with preserved ejection fraction. The role of PDE9A in diastolic dysfunction has been well-studied over recent years, with a special focus on its association with myocardial hypertrophy. Recent insights into PDE9A inhibition have brought to light the potential for reversal of cardiac remodeling, with multiple studies showing promising results in preclinical data. AREAS COVERED: This expert opinion provides an overview of the role of PDE9A in diastolic heart dysfunction along with the efficacy of PDE9A inhibitors in laboratory models of heart failure with preserved ejection fraction. EXPERT OPINION: The available data on PDE9A inhibition in preclinical studies suggest that there is potential for reversal of diastolic dysfunction and myocardial hypertrophy, however, conflicting data suggests that further studies are required before progressing to clinical trials.

Harnessing the Power of AI: A Comprehensive Review of Left Ventricular Ejection Fraction Assessment With Echocardiography.

The quantification of left ventricular ejection fraction (LVEF) has important clinical utility in the assessment of cardiac function and is vital for the diagnosis of cardiovascular diseases. A transthoracic echocardiogram serves as the most commonly used tool for LVEF assessment for several reasons, including, its noninvasive nature, great safety profile, real-time image processing ability, portability, and cost-effectiveness. However, transthoracic echocardiogram is highly dependent on the clinical skill of the sonographer and interpreting physician. Moreover, even amongst well-trained clinicians, significant interobserver variability exists in the quantification of LVEF. In search of possible solutions, the usage of artificial intelligence (AI) has been increasingly tested in the clinical setting. While AI-derived ejection fraction is in the preliminary stages of development, it has shown promise in its ability to rapidly quantify LVEF, decrease variability, increase accuracy, and utilize higher-order processing capabilities. This review will delineate the latest advancements of AI in evaluating LVEF through echocardiography and explore the challenges and future trajectory of this emerging domain.

Lipoprotein(a): A Review of Risk Factors, Measurements, and Novel Treatment Modalities.

The study of lipoprotein(a) [Lp(a)] has long been a source of interest as a possible independent risk factor for atherosclerotic cardiovascular disease (ASCVD). The results of large sample observational studies, genome-wide association studies, and Mendelian randomization studies have been strong indicators supporting the link between ASCVD and Lp(a) despite early studies, with less sensitive assays, failing to show a connection. The recommendations for the indications and frequency of testing Lp(a) levels vary between US, Canadian, and European organizations due to the uncertain role of Lp(a) in ASCVD. The innovation of recent therapies, such as antisense oligonucleotides and small interfering RNA, designed to specifically target and reduce Lp(a) levels by targeting mRNA translation have once more thrust LP(a) into the spotlight of inquiry. These emerging modalities serve the dual purpose of definitively elucidating the connection between elevated Lp(a) levels and atherosclerotic cardiovascular risk, as well as the possibility of providing clinicians with the tools necessary to manage elevated Lp(a) levels in vulnerable populations. This review seeks to examine the mechanisms of atherogenicity of Lp(a) and explore the most current pharmacologic therapies currently in development.