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We describe the association between job roles and coronavirus disease 2019 (COVID-19) among healthcare personnel. A wide range of hazard ratios were observed across job roles. Medical assistants had higher hazard ratios than nurses, while attending physicians, food service workers, laboratory technicians, pharmacists, residents and fellows, and temporary workers had lower hazard ratios.
We describe COVID-19 cases among nonphysician healthcare personnel (HCP) by work location. The proportion of HCP with coronavirus disease 2019 (COVID-19) was highest in the emergency department and lowest among those working remotely. COVID-19 and non–COVID-19 units had similar proportions of HCP with COVID-19 (13%). Cases decreased across all work locations following COVID-19 vaccination.
Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities.
We combined two novel approaches. First, normative modeling to map deviations from the typical age-related pattern at the level of the individual of (i) activity during emotion matching and (ii) of anatomical images derived from DBD cases (n = 77) and controls (n = 52) aged 8–18 years from the EU-funded Aggressotype and MATRICS consortia. Second, linked independent component analysis to integrate subject-specific deviations from both modalities.
While cases exhibited on average a higher activity than would be expected for their age during face processing in regions such as the amygdala when compared to controls these positive deviations were widespread at the individual level. A multimodal integration of all functional and anatomical deviations explained 23% of the variance in the clinical DBD phenotype. Most notably, the top marker, encompassing the default mode network (DMN) and subcortical regions such as the amygdala and the striatum, was related to aggression across the whole sample.
Overall increased age-related deviations in the amygdala in DBD suggest a maturational delay, which has to be further validated in future studies. Further, the integration of individual deviation patterns from multiple imaging modalities allowed to dissect some of the heterogeneity of DBD and identified the DMN, the striatum and the amygdala as neural signatures that were associated with aggression.
We analyzed blood-culture practices to characterize the utilization of the Infectious Diseases Society of America (IDSA) recommendations related to catheter-related bloodstream infection (CRBSI) blood cultures. Most patients with a central line had only peripheral blood cultures. Increasing the utilization of CRBSI guidelines may improve clinical care, but may also affect other quality metrics.
Adverse drug reactions (ADRs) are associated with increased morbidity, mortality, and resource utilization. Drug interactions (DDIs) are among the most common causes of ADRs, and estimates have cited that up to 22% of patients take interacting medications. DDIs are often due to the propensity for agents to induce or inhibit enzymes responsible for the metabolism of concomitantly administered drugs. However, this phenomenon is further complicated by genetic variants of such enzymes. The aim of this study is to quantify and describe potential drug-drug, drug-gene, and drug-drug-gene interactions in a community-based patient population.
A regional pharmacy with retail outlets in Arkansas provided deidentified prescription data from March 2020 for 4761 individuals. Drug-drug and drug-drug-gene interactions were assessed utilizing the logic incorporated into GenMedPro, a commercially available digital gene-drug interaction software program that incorporates variants of 9 pharmacokinetic (PK) and 2 pharmacodynamic (PD) genes to evaluate DDIs and drug-gene interactions. The data were first assessed for composite drug-drug interaction risk, and each individual was stratified to a risk category using the logic incorporated in GenMedPro. To calculate the frequency of potential drug-gene interactions, genotypes were imputed and allocated to the cohort according to each gene’s frequency in the general population. Potential genotypes were randomly allocated to the population 100 times in a Monte Carlo simulation. Potential drug-drug, gene-drug, or gene-drug-drug interaction risk was characterized as minor, moderate, or major.
Based on prescription data only, the probability of a DDI of any impact (mild, moderate, or major) was 26% [95% CI: 0.248-0.272] in the population. This probability increased to 49.6% [95% CI: 0.484-0.507] when simulated genetic polymorphisms were additionally assessed. When assessing only major impact interactions, there was a 7.8% [95% CI: 0.070-0.085] probability of drug-drug interactions and 10.1% [95% CI: 0.095-0.108] probability with the addition of genetic contributions. The probability of drug-drug-gene interactions of any impact was correlated with the number of prescribed medications, with an approximate probability of 77%, 85%, and 94% in patients prescribed 5, 6, or 7+ medications, respectively. When stratified by specific drug class, antidepressants (19.5%), antiemetics (21.4%), analgesics (16%), antipsychotics (15.6%), and antiparasitics (49.7%) had the highest probability of major drug-drug-gene interaction.
In a community-based population of outpatients, the probability of drug-drug interaction risk increases when genetic polymorphisms are attributed to the population. These data suggest that pharmacogenetic testing may be useful in predicting drug interactions, drug-gene interactions, and severity of interactions when proactively evaluating patient medication profiles.
To determine the incidence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare personnel (HCP) and to assess occupational risks for SARS-CoV-2 infection.
Prospective cohort of healthcare personnel (HCP) followed for 6 months from May through December 2020.
Large academic healthcare system including 4 hospitals and affiliated clinics in Atlanta, Georgia.
HCP, including those with and without direct patient-care activities, working during the coronavirus disease 2019 (COVID-19) pandemic.
Incident SARS-CoV-2 infections were determined through serologic testing for SARS-CoV-2 IgG at enrollment, at 3 months, and at 6 months. HCP completed monthly surveys regarding occupational activities. Multivariable logistic regression was used to identify occupational factors that increased the risk of SARS-CoV-2 infection.
Of the 304 evaluable HCP that were seronegative at enrollment, 26 (9%) seroconverted for SARS-CoV-2 IgG by 6 months. Overall, 219 participants (73%) self-identified as White race, 119 (40%) were nurses, and 121 (40%) worked on inpatient medical-surgical floors. In a multivariable analysis, HCP who identified as Black race were more likely to seroconvert than HCP who identified as White (odds ratio, 4.5; 95% confidence interval, 1.3–14.2). Increased risk for SARS-CoV-2 infection was not identified for any occupational activity, including spending >50% of a typical shift at a patient’s bedside, working in a COVID-19 unit, or performing or being present for aerosol-generating procedures (AGPs).
In our study cohort of HCP working in an academic healthcare system, <10% had evidence of SARS-CoV-2 infection over 6 months. No specific occupational activities were identified as increasing risk for SARS-CoV-2 infection.
We described the epidemiology of bat intrusions into a hospital and subsequent management of exposures during 2018–2020. Most intrusions occurred in older buildings during the summer and fall months. Hospitals need bat intrusion surveillance systems and protocols for bat handling, exposure management, and intrusion mitigation.
We opened this volume with sobering stories of the dire global challenges before us. Indeed, one would not be hard pressed to find stories of the urgency of our various environmental and social crises. While we wrote this book, the COVID-19 pandemic raged, towns in the Arctic reached unprecedented temperatures, countless hectares of forests fell while fossil fuels continued to be violently extracted from the earth, and Black, Indigenous and people of colour continued to be exploited and oppressed. Yet, despite all this, or rather because of it, we wish to begin our conclusion with hope and determination. Drawing on Solnit (2016), we believe that there is a spaciousness in the uncertainties posed by the challenges before us in that they offer new possibilities for being, thinking and acting – for renewal and purposeful redirection in our trajectory – and it is through a reawakened awareness of our rich and dynamic relationships to place that we can find a better way forward.
Climate change adaptation demands a deeper appreciation of plural senses of place and how these pluralities can create synergies as well as frictions in adaptation practice. In this chapter we aim to explore one highly overlooked dimension of this global challenge – the plural temporalities embedded within senses of place. Here we explore the dimensions of time in place-focused adaptation efforts by drawing on a series of case studies that utilise scenario-based futures methods. These methods have rapidly become critical tools in tackling the exigencies of the climate crisis but too often they presume a singular temporal mode and marginalise other temporalities and senses of place. This chapter concludes by offering new ways to reconceptualise plural senses of place and time in both theory and practice.