Barriers and Facilitators of Suicide Risk Assessment in Emergency Departments: A Qualitative Study of Provider Perspectives

Objective To understand emergency department (ED) providers’ perspectives regarding the barriers and facilitators of suicide risk assessment and to use these perspectives to inform recommendations for best practices in ED suicide risk assessment. Methods Ninety-two ED providers from two hospital systems in a Midwestern state responded to open-ended questions via an online survey that assessed their perspectives on the barriers and facilitators to assess suicide risk as well as their preferred assessment methods. Responses were analyzed using an inductive thematic analysis approach. Results Qualitative analysis yielded six themes that impact suicide risk assessment. Time, privacy, collaboration and consultation with other professionals and integration of a standard screening protocol in routine care exemplified environmental and systemic themes. Patient engagement/participation in assessment and providers’ approach to communicating with patients and other providers also impacted the effectiveness of suicide risk assessment efforts. Conclusions The findings inform feasible suicide risk assessment practices in EDs. Appropriately utilizing a collaborative, multidisciplinary approach to assess suicide-related concerns appears to be a promising approach to ameliorate the burden placed on ED providers and facilitate optimal patient care. Recommendations for clinical care, education, quality improvement and research are offered

KREAP: An automated Galaxy platform to quantify in vitro re-epithelialization kinetics

Background: In vitro scratch assays have been widely used to study the influence of bioactive substances on the processes of cell migration and proliferation that are involved in re-epithelialization

Giant cutaneous horn in an African woman: a case report

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Where Are the Newly Diagnosed HIV Positives in Kenya? Time to Consider Geo-Spatially Guided Targeting at a Finer Scale to Reach the “First 90”

Background: The UNAIDS 90-90-90 Fast-Track targets provide a framework for assessing coverage of HIV testing services (HTS) and awareness of HIV status – the “first 90.” In Kenya, the bulk of HIV testing targets are aligned to the five highest HIV-burden counties. However, we do not know if most of the new HIV diagnoses are in these five highest-burden counties or elsewhere. Methods: We analyzed facility-level HTS data in Kenya from 1 October 2015 to 30 September 2016 to assess the spatial distribution of newly diagnosed HIV-positives. We used the Moran's Index (Moran's I) to assess global and local spatial auto-correlation of newly diagnosed HIV-positive tests and Kulldorff spatial scan statistics to detect hotspots of newly diagnosed HIV-positive tests. For aggregated data, we used Kruskal-Wallis equality-of-populations non-parametric rank test to compare absolute numbers across classes. Results: Out of 4,021 HTS sites, 3,969 (98.7%) had geocodes available. Most facilities (3,034, 76.4%), were not spatially autocorrelated for the number of newly diagnosed HIV-positives. For the rest, clustering occurred as follows; 438 (11.0%) were HH, 66 (1.7%) HL, 275 (6.9%) LH, and 156 (3.9%) LL. Of the HH sites, 301 (68.7%) were in high HIV-burden counties. Over half of 123 clusters with a significantly high number of newly diagnosed HIV-infected persons, 73(59.3%) were not in the five highest HIV-burden counties. Clusters with a high number of newly diagnosed persons had twice the number of positives per 1,000,000 tests than clusters with lower numbers (29,856 vs. 14,172). Conclusions: Although high HIV-burden counties contain clusters of sites with a high number of newly diagnosed HIV-infected persons, we detected many such clusters in low-burden counties as well. To expand HTS where most needed and reach the “first 90” targets, geospatial analyses and mapping make it easier to identify and describe localized epidemic patterns in a spatially dispersed epidemic like Kenya's, and consequently, reorient and prioritize HTS strategies.publishedVersio

Documented spatial data set containing the subdivision of the basins into groundwater systems and subsystems, the selected locations per subsystem and a description of these sites, available data and projected additional measurements and equipment

The establishment of tools for trends analysis in groundwater is essential for the prediction and evaluation of measures taken within context of the Water Framework Directive and the draft Groundwater Directive. This report describes the spatial data sets which will be used for the purpose of detection, aggregation and extrapolation of temporal trends in groundwater quality. Trend analysis methods will be applied and tested at various scales and in various hydrogeological situations. The report contains a description of the studied sub-basins in TREND 2, including information on hydrogeology, land use and pressures, available data and projected additional measurements. Major differences between the sub-basins and the data sets are described to examine consequences for the work on trend detection. One of the challenges for TREND 2 is to define criteria for the application of various statistical and deterministic trend approaches for a range of hydrogeological conditions, spatial scales and types of groundwater monitoring. An overview of these conditions, scales and monitoring types is provided in the present report.FP6 Integrated Project AquaTerra Integrated Modelling of the river-sediment-soil-groundwater system; advanced tools for the management of catchment areas and river basins in the context of global change (Project no. 505428 - GOCE

Clinical correlates of anti-SARS-CoV-2 antibody profiles in Spanish COVID-19 patients from a high incidence region

Laboratory testing for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consists of two pillars: the detection of viral RNA via rt-PCR as the diagnostic gold standard in acute cases, and the detection of antibodies against SARS-CoV-2. However, concerning the latter, questions remain about their diagnostic and prognostic value and it is not clear whether all patients develop detectable antibodies. We examined sera from 347 Spanish COVID-19 patients, collected during the peak of the epidemic outbreak in Spain, for the presence of IgA and IgG antibodies against SARS-CoV-2 and evaluated possible associations with age, sex and disease severity (as measured by duration of hospitalization, kind of respiratory support, treatment in ICU and death). The presence and to some degree the levels of anti-SARS-CoV-2 antibodies depended mainly on the amount of time between onset of symptoms and the collection of serum. A subgroup of patients did not develop antibodies at the time of sample collection. Compared to the patients that did, no differences were found. The presence and level of antibodies was not associated with age, sex, duration of hospitalization, treatment in the ICU or death. The case-fatality rate increased exponentially with older age. Neither the presence, nor the levels of anti-SARS-CoV-2 antibodies served as prognostic markers in our cohort. This is discussed as a possible consequence of the timing of the sample collection. Age is the most important risk factor for an adverse outcome in our cohort. Some patients appear not to develop antibodies within a reasonable time frame. It is unclear, however, why that is, as these patients differ in no respect examined by us from those who developed antibodies

G-CORE a core for future graph query languages

We report on a community effort between industry and academia to shape the future of graph query languages. We argue that existing graph database management systems should consider supporting a query language with two key characteristics. First, it should be composable, meaning, that graphs are the input and the output of queries. Second, the graph query language should treat paths as first-class citizens. Our result is G-CORE, a powerful graph query language design that fulfills these goals, and strikes a careful balance between path query expressivity and evaluation complexity