Emerging clinical evidence suggests that thrombosis in the microvasculature of patients with Coronavirus disease 2019 (COVID-19) plays an essential role in dictating the disease progression. Because of the infectious nature of SARS-CoV-2, patients’ fresh blood samples are limited to access for in vitro experimental investigations. Herein, we employ a novel multiscale and multiphysics computational framework to perform predictive modeling of the pathological thrombus formation in the microvasculature using data from patients with COVID-19. This framework seamlessly integrates the key components in the process of blood clotting, including hemodynamics, transport of coagulation factors and coagulation kinetics, blood cell mechanics and adhesive dynamics, and thus allows us to quantify the contributions of many prothrombotic factors reported in the literature, such as stasis, the derangement in blood coagulation factor levels and activities, inflammatory responses of endothelial cells and leukocytes to the microthrombus formation in COVID-19. Our simulation results show that among the coagulation factors considered, antithrombin and factor V play more prominent roles in promoting thrombosis. Our simulations also suggest that recruitment of WBCs to the endothelial cells exacerbates thrombogenesis and contributes to the blockage of the blood flow. Additionally, we show that the recent identification of flowing blood cell clusters could be a result of detachment of WBCs from thrombogenic sites, which may serve as a nidus for new clot formation. These findings point to potential targets that should be further evaluated, and prioritized in the anti-thrombotic treatment of patients with COVID-19. Altogether, our computational framework provides a powerful tool for quantitative understanding of the mechanism of pathological thrombus formation and offers insights into new therapeutic approaches for treating COVID-19 associated thrombosis.

In the United States, from 1999 to 2019, opioid overdose, either regularly prescribed or illegally acquired, was the cause of death for nearly 500,000 people. In addition to this pronounced mortality burden that has increased gradually over time, opioid overdose has significant morbidity with severe risks and side effects. As a result, opioid misuse is a cause for concern and is considered an epidemic. This article examines the trends and consequences of the opioid epidemic presented in recent international literature, reflecting on the causes of this phenomenon and the possible strategies to address it. The detailed analysis of 33 international articles highlights numerous impacts in the social, public health, economic, and political spheres. The prescription opioid epidemic is an almost exclusively North American problem. This phenomenon should be carefully evaluated from a healthcare systems perspective, for consequential risks and harms of aggressive opioid prescription practices for pain management. Appropriate policies are required to manage opioid use and prevent abuse efficiently. Examples of proper policies vary, such as the use of validated questionnaires for the early identification of patients at risk of addiction, the effective use of regional and national prescription monitoring programs, and the proper dissemination and translation of knowledge to highlight the risks of prescription opioid abuse.

OBJECTIVES Risk scores for left ventricular assist device (LVAD) therapy are known to predict morbidity and adverse events in addition to mortality. This study evaluates the capacity of popular LVAD risk scores to predict cardiopulmonary exercise parameters. METHODS Adult patients undergoing continuous flow LVAD implantation were prospectively followed. Five risk scores were calculated before implantation: Model for End-stage Liver Disease (MELD), MELD excluding international normalized ratio (MELD-XI), MELD including sodium (MELD-Na), HeartMate2 Risk Score (HMRS) and Destination Therapy Risk Score (DTRS). Cardiopulmonary exercise tests (CPETs) were performed before and after implantation; peak oxygen consumption (vO2max), the lowest ventilation to carbon dioxide output ratio (vE/vCO2) and exercise time were measured. RESULTS Ninety-two patients were implanted during the study period; of these, 30 patients completed preimplantation and postimplantation CPETs (CPET cohort). The mean preimplantation and postimplantation CPET dates were 29 ± 10 days before and 109 ± 5 days following implantation. CPET parameters significantly improved after implantation (P < 0.05). In multivariate analysis, MELD, MELD-XI, MELD-Na and HMRS independently predicted both preimplantation and postimplantation vE/vCO2, while MELD-Na and HMRS were also independent predictors of preimplantation and postimplantation vO2max, respectively. CONCLUSIONS Four preimplantation LVAD risk scores (HMRS, MELD, MELD-Na and MELD-XI) independently predict important cardiopulmonary exercise parameters such as vE/vCO2 and vO2 max in LVAD therapy. Out of these 4 risk scores, MELD-Na and HMRS appear to be the best predictors of preimplantation and postimplantation CPET parameters, respectively.

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This nationwide analysis shows that patients undergoing surgery with perioperative COVID-19 had higher risks of 30-day mortality & morbidity, especially thromboembolic events, compared to matched patients undergoing surgeries of similar urgency & complexity.