Finding Common Ground: Communicating Across Borders to Restore the Salish Sea

Puyallup Tribe’s Chief Leschi Schools, Tulalip Tribes, and students and professors at the University of Washington are collaborating through participatory digital storytelling centered around Salish Sea restoration. The goals include intercultural education exchange across multiple disciplines leading to a balanced collaboration between communities that will inform long term policy. Students rarely learn Washington State treaty rights yet Tribes are at the forefront of Salish Sea protection. The results are the erasure of Indigenous knowledge, wisdom, and ways of knowing. Non-indigenous students are learning how to communicate with Tribes by establishing and maintaining trusting relationships in a respectful manner while also informing the public of treaty rights. Digital storytelling as an education platform creates visibility to the ongoing issues in the Salish Sea, and illuminates the Tribes’ ongoing protection of their treaty rights and sustainability efforts. Collaborative efforts between the educational institutions, Tribes, and students brings equity and diversity to environmental justice. Seven digital stories and short videos explore TransMountain Pipeline Expansion (TMX) social and ecological impacts, Puyallup resistance to a fracked gas storage facility, Coast Salish treaty rights, Tulalip-led estuary restoration and salmon recovery, means to decolonizing the UW, and Indigenous allyship principles and best practices. Diverse audiences have viewed these digital stories through online and in-person viewing events. Pre and post viewing event surveys demonstrate that digital stories have raised awareness of treaty rights, Coast Salish leadership, and means to decolonize knowledge creation in K-12 and higher education institutions. By learning tribal epistemologies, understanding tribal sovereignty, and utilizing intercultural communications there can be a better path to long term restoration. We invite you to collaborate with us as we re-engage our practices, rethink our constructs, and reimagine education with the Salish Sea community. Digital story examples include; Recovering the Salish Sea: https://storymaps.arcgis.com/stories/ce03f174417a44c5bb335ce2b749c60a Social Movements & Allyship Best Practices: https://storymaps.arcgis.com/stories/3466ffd3749a4879b591dc8e06f41ab

Measurement of red blood cell eicosapentaenoic acid (EPA) levels in a randomised trial of EPA in patients with colorectal cancer liver metastases

We investigated red blood cell (RBC) PUFA profiles, and the predictive value of RBC EPA content for tumour EPA exposure and clinical outcomes, in the EMT study, a randomised trial of EPA in patients awaiting colorectal cancer (CRC) liver metastasis surgery (Cockbain et al., 2014). There was a significant increase in RBC EPA in the EPA group (n=43; median intervention 30 days; mean absolute 1.26 [±0.14]% increase; P<0.001), but not in the placebo arm (n=45). EPA incorporation varied widely in EPA users and was not explained by treatment duration or compliance. There was little evidence of ‘contamination’ in the placebo group. The EPA level predicted tumour EPA content (r=0.36; P=0.03). Participants with post-treatment EPA ≥1.22% (n=49) had improved OS compared with EPA <1.22% (n=29; HR 0.42[95%CI 0.16–0.95]). RBC EPA content should be evaluated as a biomarker of tumour exposure and clinical outcomes in future EPA trials in CRC patients

multicentre analysis, I-MOVE-COVID-19 and ECDC networks, July to August 2021

Funding Information: This project received funding from the European Centre for Disease Prevention and Control (ECDC) under the contract ECD.11486. Funding Information: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101003673. Publisher Copyright: © 2022 European Centre for Disease Prevention and Control (ECDC). All rights reserved.Introduction: In July and August 2021, the SARS-CoV-2 Delta variant dominated in Europe. Aim: Using a multicentre test-negative study, we measured COVID-19 vaccine effectiveness (VE) against symptomatic infection. Methods: Individuals with COVID-19 or acute respiratory symptoms at primary care/community level in 10 European countries were tested for SARS-CoV-2. We measured complete primary course overall VE by vaccine brand and by time since vaccination. Results: Overall VE was 74% (95% CI: 69-79), 76% (95% CI: 71-80), 63% (95% CI: 48-75) and 63% (95% CI: 16-83) among those aged 30-44, 45-59, 60-74 and ≥ 75 years, respectively. VE among those aged 30-59 years was 78% (95% CI: 75-81), 66% (95% CI: 58-73), 91% (95% CI: 87-94) and 52% (95% CI: 40-61), for Comirnaty, Vaxzevria, Spikevax and COVID-19 Vaccine Janssen, respectively. VE among people 60 years and older was 67% (95% CI: 52-77), 65% (95% CI: 48-76) and 83% (95% CI: 64-92) for Comirnaty, Vaxzevria and Spikevax, respectively. Comirnaty VE among those aged 30-59 years was 87% (95% CI: 83-89) at 14-29 days and 65% (95% CI: 56-71%) at ≥ 90 days between vaccination and onset of symptoms. Conclusions: VE against symptomatic infection with the SARS-CoV-2 Delta variant varied among brands, ranging from 52% to 91%. While some waning of the vaccine effect may be present (sample size limited this analysis to only Comirnaty), protection was 65% at 90 days or more between vaccination and onset.publishersversionpublishe

Vaccine effectiveness against symptomatic SARS-CoV-2 infection in adults aged 65 years and older in primary care: I-MOVE-COVID-19 project, Europe, December 2020 to May 2021

I-MOVE-COVID-19 primary care study team (in addition to authors above): Nick Andrews, Jamie Lopez Bernal, Heather Whitaker, Caroline Guerrisi, Titouan Launay, Shirley Masse, Sylvie van der Werf, Vincent Enouf, John Cuddihy, Adele McKenna, Michael Joyce, Cillian de Gascun, Joanne Moran, Ana Miqueleiz, Ana Navascués, Camino Trobajo-Sanmartín, Carmen Ezpeleta, Paula López Moreno, Javier Gorricho, Eva Ardanaz, Fernando Baigorria, Aurelio Barricarte, Enrique de la Cruz, Nerea Egüés, Manuel García Cenoz, Marcela Guevara, Conchi Moreno-Iribas, Carmen Sayón, Verónica Gomez, Baltazar Nunes, Rita Roquete, Adriana Silva, Aryse Melo, Inês Costa, Nuno Verdasca, Patrícia Conde, Diogo FP Marques, Anna Molesworth, Leanne Quinn, Miranda Leyton, Selin Campbell, Janine Thoulass, Jim McMenamin, Ana Martínez Mateo, Luca Basile, Daniel Castrillejo, Carmen Quiñones Rubio, Concepción Delgado-Sanz, Jesús Oliva.The I-MOVE-COVID-19 network collates epidemiological and clinical information on patients with coronavirus disease (COVID-19), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virological characterisation in 11 European countries [1]. One component of I-MOVE-COVID-19 is the multicentre vaccine effectiveness (VE) study at primary care/outpatient level in nine European study sites in eight countries. We measured overall and product-specific COVID-19 VE against symptomatic SARS-CoV-2 infection among those aged 65 years and older. We also measured VE by time since vaccination.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101003673.info:eu-repo/semantics/publishedVersio

LEARN: A multi-centre, cross-sectional evaluation of Urology teaching in UK medical schools

OBJECTIVE: To evaluate the status of UK undergraduate urology teaching against the British Association of Urological Surgeons (BAUS) Undergraduate Syllabus for Urology. Secondary objectives included evaluating the type and quantity of teaching provided, the reported performance rate of General Medical Council (GMC)-mandated urological procedures, and the proportion of undergraduates considering urology as a career. MATERIALS AND METHODS: LEARN was a national multicentre cross-sectional study. Year 2 to Year 5 medical students and FY1 doctors were invited to complete a survey between 3rd October and 20th December 2020, retrospectively assessing the urology teaching received to date. Results are reported according to the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). RESULTS: 7,063/8,346 (84.6%) responses from all 39 UK medical schools were included; 1,127/7,063 (16.0%) were from Foundation Year (FY) 1 doctors, who reported that the most frequently taught topics in undergraduate training were on urinary tract infection (96.5%), acute kidney injury (95.9%) and haematuria (94.4%). The most infrequently taught topics were male urinary incontinence (59.4%), male infertility (52.4%) and erectile dysfunction (43.8%). Male and female catheterisation on patients as undergraduates was performed by 92.1% and 73.0% of FY1 doctors respectively, and 16.9% had considered a career in urology. Theory based teaching was mainly prevalent in the early years of medical school, with clinical skills teaching, and clinical placements in the later years of medical school. 20.1% of FY1 doctors reported no undergraduate clinical attachment in urology. CONCLUSION: LEARN is the largest ever evaluation of undergraduate urology teaching. In the UK, teaching seemed satisfactory as evaluated by the BAUS undergraduate syllabus. However, many students report having no clinical attachments in Urology and some newly qualified doctors report never having inserted a catheter, which is a GMC mandated requirement. We recommend a greater emphasis on undergraduate clinical exposure to urology and stricter adherence to GMC mandated procedures

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality.

peer reviewedDespite advances in COVID-19 management, identifying patients evolving toward death remains challenging. To identify early predictors of mortality within 60 days of symptom onset (DSO), we performed immunovirological assessments on plasma from 279 individuals. On samples collected at DSO11 in a discovery cohort, high severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA), low receptor binding domain–specific immunoglobulin G and antibody-dependent cellular cytotoxicity, and elevated cytokines and tissue injury markers were strongly associated with mortality, including in patients on mechanical ventilation. A three-variable model of vRNA, with predefined adjustment by age and sex, robustly identified patients with fatal outcome (adjusted hazard ratio for log-transformed vRNA = 3.5). This model remained robust in independent validation and confirmation cohorts. Since plasma vRNA’s predictive accuracy was maintained at earlier time points, its quantitation can help us understand disease heterogeneity and identify patients who may benefit from new therapies

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707