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Background: The objective of the STREAM Trial was to evaluate the effect of simulation training on process times in acute stroke care.
Methods: The multicenter prospective interventional STREAM Trial was conducted between 10/2017 and 04/2019 at seven tertiary care neurocenters in Germany with a pre- and post-interventional observation phase. We recorded patient characteristics, acute stroke care process times, stroke team composition and simulation experience for consecutive direct-to-center patients receiving intravenous thrombolysis (IVT) and/or endovascular therapy (EVT). The intervention consisted of a composite intervention centered around stroke-specific in situ simulation training. Primary outcome measure was the ‘door-to-needle’ time (DTN) for IVT. Secondary outcome measures included process times of EVT and measures taken to streamline the pre-existing treatment algorithm.
Results: The effect of the STREAM intervention on the process times of all acute stroke operations was neutral. However, secondary analyses showed a DTN reduction of 5 min from 38 min pre-intervention (interquartile range [IQR] 25–43 min) to 33 min (IQR 23–39 min, p = 0.03) post-intervention achieved by simulation-experienced stroke teams. Concerning EVT, we found significantly shorter door-to-groin times in patients who were treated by teams with simulation experience as compared to simulation-naive teams in the post-interventional phase (−21 min, simulation-naive: 95 min, IQR 69–111 vs. simulation-experienced: 74 min, IQR 51–92, p = 0.04).
Conclusion: An intervention combining workflow refinement and simulation-based stroke team training has the potential to improve process times in acute stroke care.
An ever-increasing demand for novel antimicrobials to treat life-threatening infections caused by the global spread of multidrug-resistant bacterial pathogens stands in stark contrast to the current level of investment in their development, particularly in the fields of natural-product-derived and synthetic small molecules. New agents displaying innovative chemistry and modes of action are desperately needed worldwide to tackle the public health menace posed by antimicrobial resistance. Here, our consortium presents a strategic blueprint to substantially improve our ability to discover and develop new antibiotics. We propose both short-term and long-term solutions to overcome the most urgent limitations in the various sectors of research and funding, aiming to bridge the gap between academic, industrial and political stakeholders, and to unite interdisciplinary expertise in order to efficiently fuel the translational pipeline for the benefit of future generations.
The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.