Faculty Bibliography

PURPOSE OF REVIEW/OBJECTIVE:Although rare, the development of mechanical complications following an acute myocardial infarction is associated with a high morbidity and mortality. Here, we review the clinical features, diagnostic strategy, and treatment options for each of the mechanical complications, with a focus on the role of echocardiography. RECENT FINDINGS/RESULTS:The growth of percutaneous structural interventions worldwide has given rise to new non-surgical options for management of mechanical complications. As such, select patients may benefit from a novel use of these established treatment methods. A thorough understanding of the two-dimensional, three-dimensional, color Doppler, and spectral Doppler findings for each mechanical complication is essential in recognizing major causes of hemodynamic decompensation after an acute myocardial infarction. Thereafter, echocardiography can aid in the selection and maintenance of mechanical circulatory support and potentially facilitate the use of a percutaneous intervention.

IMPORTANCE/UNASSIGNED:Current data identifying COVID-19 risk factors lack standardized outcomes and insufficiently control for confounders. OBJECTIVE/UNASSIGNED:To identify risk factors associated with COVID-19, severe COVID-19, and SARS-CoV-2 infection. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This secondary cross-protocol analysis included 4 multicenter, international, randomized, blinded, placebo-controlled, COVID-19 vaccine efficacy trials with harmonized protocols established by the COVID-19 Prevention Network. Individual-level data from participants randomized to receive placebo within each trial were combined and analyzed. Enrollment began July 2020 and the last data cutoff was in July 2021. Participants included adults in stable health, at risk for SARS-CoV-2, and assigned to the placebo group within each vaccine trial. Data were analyzed from April 2022 to February 2023. EXPOSURES/UNASSIGNED:Comorbid conditions, demographic factors, and SARS-CoV-2 exposure risk at the time of enrollment. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Coprimary outcomes were COVID-19 and severe COVID-19. Multivariate Cox proportional regression models estimated adjusted hazard ratios (aHRs) and 95% CIs for baseline covariates, accounting for trial, region, and calendar time. Secondary outcomes included severe COVID-19 among people with COVID-19, subclinical SARS-CoV-2 infection, and SARS-CoV-2 infection. RESULTS/UNASSIGNED:A total of 57 692 participants (median [range] age, 51 [18-95] years; 11 720 participants [20.3%] aged ≥65 years; 31 058 participants [53.8%] assigned male at birth) were included. The analysis population included 3270 American Indian or Alaska Native participants (5.7%), 7849 Black or African American participants (13.6%), 17 678 Hispanic or Latino participants (30.6%), and 40 745 White participants (70.6%). Annualized incidence was 13.9% (95% CI, 13.3%-14.4%) for COVID-19 and 2.0% (95% CI, 1.8%-2.2%) for severe COVID-19. Factors associated with increased rates of COVID-19 included workplace exposure (high vs low: aHR, 1.35 [95% CI, 1.16-1.58]; medium vs low: aHR, 1.41 [95% CI, 1.21-1.65]; P < .001) and living condition risk (very high vs low risk: aHR, 1.41 [95% CI, 1.21-1.66]; medium vs low risk: aHR, 1.19 [95% CI, 1.08-1.32]; P < .001). Factors associated with decreased rates of COVID-19 included previous SARS-CoV-2 infection (aHR, 0.13 [95% CI, 0.09-0.19]; P < .001), age 65 years or older (aHR vs age <65 years, 0.57 [95% CI, 0.50-0.64]; P < .001) and Black or African American race (aHR vs White race, 0.78 [95% CI, 0.67-0.91]; P = .002). Factors associated with increased rates of severe COVID-19 included race (American Indian or Alaska Native vs White: aHR, 2.61 [95% CI, 1.85-3.69]; multiracial vs White: aHR, 2.19 [95% CI, 1.50-3.20]; P < .001), diabetes (aHR, 1.54 [95% CI, 1.14-2.08]; P = .005) and at least 2 comorbidities (aHR vs none, 1.39 [95% CI, 1.09-1.76]; P = .008). In analyses restricted to participants who contracted COVID-19, increased severe COVID-19 rates were associated with age 65 years or older (aHR vs <65 years, 1.75 [95% CI, 1.32-2.31]; P < .001), race (American Indian or Alaska Native vs White: aHR, 1.98 [95% CI, 1.38-2.83]; Black or African American vs White: aHR, 1.49 [95% CI, 1.03-2.14]; multiracial: aHR, 1.81 [95% CI, 1.21-2.69]; overall P = .001), body mass index (aHR per 1-unit increase, 1.03 [95% CI, 1.01-1.04]; P = .001), and diabetes (aHR, 1.85 [95% CI, 1.37-2.49]; P < .001). Previous SARS-CoV-2 infection was associated with decreased severe COVID-19 rates (aHR, 0.04 [95% CI, 0.01-0.14]; P < .001). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this secondary cross-protocol analysis of 4 randomized clinical trials, exposure and demographic factors had the strongest associations with outcomes; results could inform mitigation strategies for SARS-CoV-2 and viruses with comparable epidemiological characteristics.

RATIONALE:The BMPs (bone morphogenetic proteins) are essential morphogens in angiogenesis and vascular development. Disruption of BMP signaling can trigger cardiovascular diseases, such as arteriovenous malformations. OBJECTIVE:A computational model predicted that BMP4 and BMP9 and their inhibitors MGP (matrix gamma-carboxyglutamic acid [Gla] protein) and CV2 (crossveinless-2) would form a regulatory system consisting of negative feedback loops with time delays and that BMP9 would trigger oscillatory expression of the 2 inhibitors. The goal was to investigate this regulatory system in endothelial differentiation and vascular growth. METHODS AND RESULTS:Oscillations in the expression of MGP and CV2 were detected in endothelial cells in vitro, using quantitative real-time polymerase chain reaction and immunoblotting. These organized temporally downstream BMP-related activities, including expression of stalk-cell markers and cell proliferation, consistent with an integral role of BMP9 in vessel maturation. In vivo, the inhibitors were located in distinct zones in relation to the front of the expanding retinal network, as determined by immunofluorescence. Time-dependent changes of the CV2 location in the retina and the existence of an endothelial population with signs of oscillatory MGP expression in developing vasculature supported the in vitro findings. Loss of MGP or its BMP4-binding capacity disrupted the retinal vasculature, resulting in poorly formed networks, especially in the venous drainage areas, and arteriovenous malformations as determined by increased cell coverage and functional testing. CONCLUSIONS:Our results suggest a previously unknown mechanism of temporal orchestration of BMP4 and BMP9 activities that utilize the tandem actions of the extracellular antagonists MGP and CV2. Disruption of this mechanism may contribute to vascular malformations and disease.