Outcomes of Patients with Opioid-Related Diagnoses in Acute Coronary Syndrome: a National Inpatient Sample-Based Analysis.

BACKGROUND: Acute coronary syndrome (ACS) and opioid use are both major causes of morbidity and mortality globally. Although epidemiological studies point to increased risk of ACS in opioid users, in-hospital management and outcomes are unknown for this population when presenting with ACS. We sought to determine whether there are differences for in-hospital outcomes and management of ACS for those with and without opioid-related diagnoses (ORD). METHODS AND RESULTS: From the National Inpatient Sample database, we extracted patients hospitalized between 2012 and 2016 for ACS. The primary independent variable was ORD by International Classification of Diseases, 9th and 10th Revision, codes. The primary outcome was in-hospital mortality; secondary outcomes were cardiac arrest, receipt of angiogram, and percutaneous coronary intervention (PCI). Statistical comparisons were performed using χ2 test and Student's t test. Multivariable logistic regression was performed to determine the independent association between ORD and outcomes of interest. Among the estimated 5.8 million admissions for ACS, the proportion of patients with ORD increased over the study period (p for trend < 0.01). Compared to patients without ORD presenting with ACS, patients with ORD were younger with fewer cardiovascular risk factors. Yet, in-hospital mortality was higher in patients with ORD presenting with ACS (AOR 1.36, 95% CI 1.26-1.48). Patients with ORD were more likely to experience in-hospital cardiac arrest (AOR 1.42, 95% CI 1.23-1.63) and less likely to undergo angiogram (AOR 0.42, 95% CI 0.38-0.45) or PCI (AOR 0.30, 95% CI 0.28-0.32). CONCLUSION: Despite evidence of increased risk of mortality and cardiac arrest, patients with ORD admitted for ACS are less likely to receive ACS management.

2019 clinical trials in lipid lowering.

PURPOSE OF REVIEW: Lipid-lowering therapies play a major role in reducing atherosclerotic cardiovascular disease (ASCVD). This article reviews the most recent lipid-lowering therapy trials, many of which provide a unique opportunity to further reduce low-density lipoprotein cholesterol (LDL-C) levels and ASCVD risk on top of statin therapy, and in doing so further decrease the number of future major adverse cardiovascular events. RECENT FINDINGS: Although statin therapy has been the mainstay of treatment for lowering LDL-C levels for many years, many individuals require additional or alternative options for further reducing their risk. Trials on previously studied therapies, such as PCSK9 inhibitors, and new therapies, including inclisiran, bempedoic acid and icosapent ethyl demonstrate significant potential for further lowering of LDL-C levels and risk for events on top of maximally tolerated statin therapy with favourable side effect profiles. SUMMARY: As therapies for ASCVD prevention continue to emerge, clinicians will need to identify the appropriate treatment for individuals based on their estimated risk and risk-enhancing factors. When statin therapy is either not sufficient or patients do not tolerate adequate statin therapy, relying on newer therapies, such as PCSK9-inhibitors, inclisiran, bempedoic acid and icosapent ethyl, will be critical to maximize risk factor profiles to reduce adverse outcomes.

Harnessing mHealth technologies to increase physical activity and prevent cardiovascular disease.

Research into prevention of cardiovascular disease has increasingly focused on mobile health (mHealth) technologies and their efficacy in helping individuals adhere to heart-healthy recommendations, including daily physical activity levels. By including the use of mHealth technologies in the discussion of physical activity recommendations, clinicians empower patients to play an active daily role in modifying their cardiovascular risk-factor profile. In this review, we critically evaluate the mHealth and physical activity literature to determine how these tools may lower cardiovascular risk while providing real-time tracking, feedback, and motivation on physical activity levels. We analyze the various domains-including user knowledge, social support, behavioral change theory, and self-motivation-that potentially influence the effectiveness of smartphone applications to impact individual physical activity levels. In doing so, we hope to provide a thorough overview of the mHealth landscape, in addition to highlighting many of the administrative, reimbursement, and patient-privacy challenges of using these technologies in patient care. Finally, we propose a behavioral change model and checklist for clinicians to assist patients in utilizing mHealth technology to best achieve meaningful changes in daily physical activity levels.