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The Internet has never been more important to our society, and understanding the behavior of the Internet is essential. The Center for Applied Internet Data Analysis (CAIDA) Telescope observes a continuous stream of packets from an unsolicited darkspace representing 1/256 of the Internet. During 2019 and 2020 over 40,000,000,000,000 unique packets were collected representing the largest ever assembled public corpus of Internet traffic. Using the combined resources of the Supercomputing Centers at UC San Diego, Lawrence Berkeley National Laboratory, and MIT, the spatial temporal structure of anonymized source-destination pairs from the CAIDA Telescope data has been analyzed with GraphBLAS hierarchical hypersparse matrices. These analyses provide unique insight on this unsolicited Internet darkspace traffic with the discovery of many previously unseen scaling relations. The data show a significant sustained increase in unsolicited traffic corresponding to the start of the COVID19 pandemic, but relatively little change in the underlying scaling relations associated with unique sources, source fan-outs, unique links, destination fan-ins, and unique destinations. This work provides a demonstration of the practical feasibility and benefit of the safe collection and analysis of significant quantities of anonymized Internet traffic.
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First responders and other forward deployed essential workers can benefit from advanced analytics. Limited network access and software security requirements prevent the usage of standard cloud based microservice analytic platforms that are typically used in industry. One solution is to precompute a wide range of analytics as files that can be used with standard preinstalled software that does not require network access or additional software and can run on a wide range of legacy hardware. In response to the COVID-19 pandemic, this approach was tested for providing geo-spatial census data to allow quick analysis of demographic data for better responding to emergencies. These data were processed using the MIT SuperCloud to create several thousand Google Earth and Microsoft Excel files representative of many advanced analytics. The fast mapping of census data using Google Earth and Microsoft Excel has the potential to give emergency responders a powerful tool to improve emergency preparedness. Our approach displays relevant census data (total population, population under 15, population over 65, median age) per census block, sorted by county, through a Microsoft Excel spreadsheet (xlsx file) and Google Earth map (kml file). The spreadsheet interface includes features that allow users to convert between different longitude and latitude coordinate units. For the Google Earth files, a variety of absolute and relative colors maps of population density have been explored to provide an intuitive and meaningful interface. Using several hundred cores on the MIT SuperCloud, new analytics can be generated in a few minutes. © 2021 IEEE.
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TOPIC: Critical Care TYPE: Fellow Case Reports INTRODUCTION: The SARS-Cov-2 (COVID-19) pandemic has had a significant impact on healthcare and the economy worldwide. In a subset of patients, COVID-19 causes a cytokine-mediated systemic hyperinflammatory response, often resulting in acute respiratory distress syndrome (ARDS) as well as multi-organ dysfunctions. Due to the hyperinflammatory response, the Seraph 100 Microbind Affinity Blood Filter has obtained Emergency Use Authorization (EUA) from the Food and Drug Administration (FDA). The Seraph 100 filter is an extracoporeal hemoperfusion device designed to remove pathogens directly from the blood via heparin-coated polyethylene beads. It is conjectured and shown in vitro to assist in the treatment of COVID-19 organ dysfunction by reducing the burden of viremia as well as circulating cytokines within the bloodstream. CASE PRESENTATION: In this case series, we present four patients admitted with severe COVID-19 who were treated with the Seraph 100 filter under the EUA. Variables assessed included the mean arterial pressure, heart rate, oxygen saturation, temperature, lactate, and pH along with vasopressor requirements before, during, and after Seraph filter use. At the time of treatment initiation with the Seraph 100 filter, all four patients met criteria for septic shock and three of the four patients had bacteremia with Staphylococcus aureus. Two of our patients (survivors) had a significant reduction in vasopressor requirement in the first few hours of treatment despite a minimal change in patients' acid-base status. The survivors also demonstrated improvements in their oxygen saturation and oxygen requirements and were ultimately discharged from the hospital. The remaining two patients (non-survivors) did not have a change in vasopressor requirement or oxygenation after one treatment with the Seraph 100 filter. One of these patient's treatments was terminated prematurely due to clinical decline and reconsideration of the patient's goals of care with family. Both of these patients passed away. DISCUSSION: We present four cases with various outcomes of critical illness related to COVID-19 treated with the novel Seraph 100 filter. Two of the four patients treated with the Seraph 100 had significant and dramatic clinical improvement upon initiation of treatment and were weaned off vasopressor support within 48 hours. Unfortunately, the other two patients showed no clinical improvement and subsequently declined resulting in death during hospitalization. The two survivors had a shorter duration of vasopressor-dependent shock prior to treatment with the Seraph 100 than the non-survivors. CONCLUSIONS: In conclusion, the Seraph 100 may improve hemodynamics in patients with COVID-19 and secondary infections. Future studies with a larger cohort will help select appropriate patients as well as determine optimal timing for initiation of therapy. REFERENCE #1: Seffer, MT, Cottam, D, Forni LG, Kielstein, JT. Heparin 2.0: A New Approach to the Infection Crisis. Blood Purification. 2021;50(1):28-34. REFERENCE #2: "ExThera Medical: MedTech Company Developing Blood Filters That Can Capture a Wide Range of Pathogens." ExThera Medical V, www.extheramedical.com/. REFERENCE #3: Ronco, C, et al. Extracorporeal Blood Purification and Organ Support in the Critically Ill Patient during COVID-19 Pandemic: Expert Review and Recommendations. Blood Purification. 2021;50:17-27. DISCLOSURES: No relevant relationships by Rohini Chatterjee, source=Web Response No relevant relationships by Mateo Houle, source=Web Response No relevant relationships by John Hunninghake, source=Web Response No relevant relationships by Arjun Kalra, source=Web Response No relevant relationships by Ian McInnis, source=Web Response No relevant relationships by Mai Nguyen, source=Web Response No relevant relationships by Nicholas Niazi, source=Web Response No relevant relationships by Melissa Rosas, source=Web Response No relevant relationships by Lauren Sattler, source=Web Response No relevant relationships by Michal Sobieszczyk, source=Web Response No relevant relationships by Brandon Walker, source=Web Response No relevant relationships by Robert Walter, source=Web Response
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Pandemic measures such as social distancing and contact tracing can be enhanced by rapidly integrating dynamic location data and demographic data. Projecting billions of longitude and latitude locations onto hundreds of thousands of highly irregular demographic census block polygons is computationally challenging in both research and deployment contexts. This paper describes two approaches labeled "simple" and "fast". The simple approach can be implemented in any scripting language (Matlab/Octave, Python, Julia, R) and is easily integrated and customized to a variety of research goals. This simple approach uses a novel combination of hierarchy, sparse bounding boxes, polygon crossing-number, vectorization, and parallel processing to achieve 100,000,000+ projections per second on 100 servers. The simple approach is compact, does not increase data storage requirements, and is applicable to any country or region. The fast approach exploits the thread, vector, and memory optimizations that are possible using a low-level language (C++) and achieves similar performance on a single server. This paper details these approaches with the goal of enabling the broader community to quickly integrate location and demographic data.
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Background: Cardiac injury has been identified as an independent risk factor of mortality in COVID-19, but early recognition of severe COVID-19 illness remains challenging. Several lab parameters have been proposed to help guide clinical decisions. This study aimed to evaluate the association between troponin (TN), N-terminal pro-brain naturietic peptide (BNP), and sodium and adverse clinical outcomes in COVID-19.Methods: This retrospective single-center cohort included consecutive COVID-19 patients admitted to the George Washington University Hospital between March 2020 and May 2020. Patient demographics, cardiovascular comorbidities, and laboratory values were examined. Elevated TN and BNP were defined as >0.02 ng/mL and >150 ng/L, respectively. Primary outcomes included ICU admission and mortality. The presence of underlying cardiovascular disease (CVD) was analyzed to evaluate for relative effect on clinical outcomes. Chi-square and multinomial regression models were utilized to evaluate the association between biomarkers and clinical outcomes.Results: 290 patients were identified with a median age of 62 and the majority were male (52.4%), Black (71.3%), and had CVD risk factors (72.1%). ICU admission occurred in 88 (30.3%) while death occurred in 74 (25.5%) individuals. Patients with both an elevated TN and CVD were more likely to experience ICU admission or death (OR=2.55, p=0.017) while patients with both elevated TN and elevated BNP had markedly increased odds of ICU admission or death (OR=7.53, p<0.001). Among patients with CVD, hypernatremia (Na>145) was associated with over an eight-fold increased odds of ICU admission or death (OR=8.57, p<0.001). An isolated elevated BNP with CVD did not increase the risk of primary events.Conclusion: Among COVID-19 patients with underlying CVD, the presence of an elevated TN or hypernatremia was associated with significantly increased odds of ICU admission or death. Elevated BNP with CVD did not increase risk of events. Identifying these factors on presentation may prove helpful for early triage of high-risk patients.
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Background: Severe acute respiratory syndrome coronavirus 2 (COVID-19) is linked to adverse cardiovascular outcomes in hospitalized patients but predicting the clinical course remains challenging. The purpose of this study was to examine the association between two biomarkers, troponin-I (TN) and interleukin-6 (IL-6), and cardiovascular morbidity and mortality in patients hospitalized with COVID-19. Methods: This is a retrospective single-center study of patients hospitalized with COVID-19 from March 2020 to May 2020. Elevated TN and IL-6 were defined as >0.02 ng/ml and >65.9 ng/mL respectively. The primary outcome was mortality with secondary outcomes including intensive care unit (ICU) admission and adverse cardiovascular outcomes (heart failure (HF), arrhythmia, myocardial infarction (MI), and pericarditis). Chi-squared tests and student t-tests were used for statistical analyses to examine the relationship between the presence of positive biomarkers and outcomes;p<0.05 significant. Results: In total, 150 patients were identified with the majority being African American (70%), males (55%) and an average age of 63.7 years. Patients with elevated TN had significantly increased mortality rates (36.1% vs. 19.2%, OR 2.4, p=0.021), incidence of arrhythmias (15.3% vs. 1.3%, OR 13.9, p=0.002), incidence of HF (13.9% vs. 1.3%, OR 12.4, p=0.003), and incidence of MI (13.9% vs. 1.3%, OR 12.4, p=0.003). Patients with elevated IL-6 had significantly higher mortality rates (42.7% vs. 12.0%, OR 5.5, p=<0.001), ICU admissions (50.7% vs. 18.7%, OR 4.5, p=<0.0001), incidence of arrhythmias (13.3% vs. 2.7%, OR 5.6, p=0.016), incidence of HF (12.0% vs. 2.7%, OR 5.0, p=0.028), and incidence of MI (13.3% vs. 1.3%, OR 11.4, p= 0.0048). Conclusion: Myocardial injury evidenced by elevated TN and elevated IL-6 are predictive of severe COVID-19 infections and cardiovascular complications, irrespective of race as seen in this cohort. Early detection at hospital admission and perhaps subsequent monitoring of TN and IL-6 could be beneficial in triage and to identify potential early escalation of care.