Notes

Oesophageal cancers remedy habits, timeliness associated with care and results in the Loddon Mallee region involving Victoria: A new retrospective cohort research.
COVID-19 may predispose to both venous and arterial thromboembolism event (TEE). Reports on the prevalence and prognosis of thrombotic complications are still emerging.

To describe the rate of TEE complications and its influence in the prognosis of hospitalized patients with COVID-19 after a cross-sectional study.

We evaluated the prevalence of TEE and its relationship with in-hospital death among hospitalized patients with COVID-19 who were admitted between 1st March to 20th April 2020 in a multicentric network of sixteen Hospitals in Spain. TEE was defined by the occurrence of venous thromboembolism (VTE), acute ischemic stroke (AIS), systemic arterial embolism or myocardial infarction (MI).

We studied 1737 patients with proven COVID-19 infection of whom 276 died (15.9%). TEE were presented in 64 (3.7%) patients 49 (76.6%) patients had a VTE, 8 (12.5%) patients had MI, 6 (9.4%%) patients had AIS, and one (1.5%) patient a thrombosis of portal vein. TEE patients exhibited a diffuse profile older, high levels of D-dimer protein and a tendency of lower levels of prothrombin. The multivariate regression models, confirmed the association between in-hospital death and age (odds ratio [OR] 1.12 [95% CI 1.10-1.14], p<0.001), diabetes (OR 1.49 [95% CI 1.04-2.13], p = 0.029), chronic obstructive pulmonary disease (OR 1.61 [95% CI 1.03-2.53], p = 0.039), ICU care (OR 9.39 [95% CI 5.69-15.51], p<0.001), and TTE (OR 2.24 [95% CI 1.17-4.29], p = 0.015).

Special attention is needed among hospitalized COVID-19 patients with TTE and other comorbidities as they have an increased risk of in-hospital death.
Special attention is needed among hospitalized COVID-19 patients with TTE and other comorbidities as they have an increased risk of in-hospital death.In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.Estimation of disease prevalence at sub-city neighborhood scale allows early and targeted interventions that can help save lives and reduce public health burdens. However, the cost-prohibitive nature of highly localized data collection and sparsity of representative signals, has made it challenging to identify neighborhood scale prevalence of disease. To overcome this challenge, we utilize alternative data sources, which are both less sparse and representative of localized disease prevalence using query data from a large commercial search engine, we identify the prevalence of respiratory illness in the United States, localized to census tract geographic granularity. Focusing on asthma and Chronic Obstructive Pulmonary Disease (COPD), we construct a set of features based on searches for symptoms, medications, and disease-related information, and use these to identify illness rates in more than 23 thousand tracts in 500 cities across the United States. Out of sample model estimates from search data alone correlate with ground truth illness rate estimates from the CDC at 0.69 to 0.76, with simple additions to these models raising those correlations to as high as 0.84. We then show that in practice search query data can be added to other relevant data such as census or land cover data to boost results, with models that incorporate all data sources correlating with ground truth data at 0.91 for asthma and 0.88 for COPD.Across several decades there has been an unprecedented increase in immigration enforcement including detention and deportation. Immigration detention profoundly impacts those experiencing detention and their family members. An emerging area of research has found that immigrants experience a number of challenges which constrain and limit their decisions, choices, and options for security and integration in the United States due to social, political and structural determinants. These determinants lead to greater structural vulnerabilities among immigrants. The purpose of the current study was to illuminate the perceived vulnerabilities of detained noncitizen immigrants as they are raised and described while attending case hearings at the Bloomington, Minnesota immigration court. Through conducting a thematic analysis of notes derived from third party immigration court observers, three areas of perceived vulnerability were identified. These perceived vulnerabilities include 1) migration and motivations to migrate, 2) structural vulnerabilities (e.g., discrimination, financial insecurity, social ties and family support, stable or fixed residence, English language proficiency, health and mental health) in the US, and 3) challenges in navigating immigration detention. These findings demonstrate that noncitizen immigrants who are undergoing immigration detention are experiencing multiple intersecting vulnerabilities which profoundly impact their lives. Collaborative efforts across sectors are needed to work towards comprehensive immigration reforms including both short-term and long-term solutions to address pressing issues for noncitizens undergoing immigration detention.In sub-Saharan Africa growing season precipitation is affected by climate change. Due to this, in Cameroon, it is uncertain how some crops are vulnerable to growing season precipitation. Here, an assessment of the vulnerability of maize, millet, and rice to growing season precipitation is carried out at a national scale and validated at four sub-national scales/sites. The data collected were historical yield, precipitation, and adaptive capacity data for the period 1961-2019 for the national scale analysis and 1991-2016 for the sub-national scale analysis. The crop yield data were collected for maize, millet, and rice from FAOSTAT and the global yield gap atlas to assess the sensitivity both nationally and sub-nationally. Historical data on mean crop growing season and mean annul precipitation were collected from a collaborative database of UNDP/Oxford University and the climate portal of the World Bank to assess the exposure both nationally and sub-nationally. Bcl 2 inhibitor To assess adaptive capacity, literacy, and poverty rate proxies for both the national and regional scales were collected from KNOEMA and the African Development Bank.
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