Mental health of staff working in intensive care during COVID-19

BACKGROUND: Staff working in intensive care units (ICUs) have faced significant challenges during the COVID-19 pandemic which have the potential to adversely affect their mental health. AIMS: To identify the rates of probable mental health disorder in staff working in ICUs in nine English hospitals during June and July 2020. METHODS: An anonymized brief web-based survey comprising standardized questionnaires examining depression, anxiety symptoms, symptoms of post-traumatic stress disorder (PTSD), well-being and alcohol use was administered to staff. RESULTS: Seven hundred and nine participants completed the surveys comprising 291 (41%) doctors, 344 (49%) nurses and 74 (10%) other healthcare staff. Over half (59%) reported good well-being; however, 45% met the threshold for probable clinical significance on at least one of the following measures: severe depression (6%), PTSD (40%), severe anxiety (11%) or problem drinking (7%). Thirteen per cent of respondents reported frequent thoughts of being better off dead, or of hurting themselves in the past 2 weeks. Within the sample used in this study, we found that doctors reported better mental health than nurses across a range of measures. CONCLUSIONS: We found substantial rates of probable mental health disorders, and thoughts of self-harm, amongst ICU staff; these difficulties were especially prevalent in nurses. Whilst further work is needed to better understand the real level of clinical need amongst ICU staff, these results indicate the need for a national strategy to protect the mental health, and decrease the risk of functional impairment, of ICU staff whilst they carry out their essential work during COVID-19

A Phase transition in acoustic propagation in 2D random liquid media

Acoustic wave propagation in liquid media containing many parallel air-filled cylinders is considered. A self-consistent method is used to compute rigorously the propagation, incorporating all orders of multiple scattering. It is shown that under proper conditions, multiple scattering leads to a peculiar phase transition in acoustic propagation. When the phase transition occurs, a collective behavior of the cylinders appears and the acoustic waves are confined in a region of space in the neighborhood of the transmission source. A novel phase diagram is used to describe such phase transition. Originally submitted on April 6, 99.Comment: 5 pages, 5 color figure

Neural Networks for Information Retrieval

Machine learning plays a role in many aspects of modern IR systems, and deep learning is applied in all of them. The fast pace of modern-day research has given rise to many different approaches for many different IR problems. The amount of information available can be overwhelming both for junior students and for experienced researchers looking for new research topics and directions. Additionally, it is interesting to see what key insights into IR problems the new technologies are able to give us. The aim of this full-day tutorial is to give a clear overview of current tried-and-trusted neural methods in IR and how they benefit IR research. It covers key architectures, as well as the most promising future directions.Comment: Overview of full-day tutorial at SIGIR 201

Research fatigue in COVID-19 pandemic and post-disaster research: Causes, consequences and recommendations

Purpose: Research fatigue occurs when an individual or population of interest tires of engaging with research, consequently avoiding further participation. This paper considers research fatigue in the context of the current COVID-19 pandemic, to identify contributory factors and possible solutions for future post-disaster research. Methodology: We draw on examples from the literature and our own observations from the recruitment and data collection phases of qualitative and quantitative studies, to provide an overview of possible research fatigue in the current COVID-19 pandemic, with implications for future post disaster research. Findings: People affected by disasters sometimes receive multiple requests for study participation by separate teams who may not necessarily be coordinating their work. Not keeping participants informed of the research process or outcomes can lead to disillusionment. Being overburdened with too many research requests and failing to see any subsequent changes following participation may cause individuals to experience research fatigue. Originality: Guidelines for researchers wishing to reduce the occurrence of research fatigue include ensuring greater transparency within research; sharing of results; and using oversight or gatekeeper bodies to aid coordination. Failure to restrict the number of times that people are asked to participate in studies risks poor participation rates. This can subsequently affect the quality of information with which to inform policy-makers and protect the health of the public during the COVID-19 pandemic or other public health disasters/emergencies

Epidemiology of Mycobacterium abscessus in England: an observational study

BACKGROUND: Mycobacterium abscessus has emerged as a significant clinical concern following reports that it is readily transmissible in health-care settings between patients with cystic fibrosis. We linked routinely collected whole-genome sequencing and health-care usage data with the aim of investigating the extent to which such transmission explains acquisition in patients with and without cystic fibrosis in England. METHODS: In this retrospective observational study, we analysed consecutive M abscessus whole-genome sequencing data from England (beginning of February, 2015, to Nov 14, 2019) to identify genomically similar isolates. Linkage to a national health-care usage database was used to investigate possible contacts between patients. Multivariable regression analysis was done to investigate factors associated with acquisition of a genomically clustered strain (genomic distance <25 single nucleotide polymorphisms [SNPs]). FINDINGS: 2297 isolates from 906 patients underwent whole-genome sequencing as part of the routine Public Health England diagnostic service. Of 14 genomic clusters containing isolates from ten or more patients, all but one contained patients with cystic fibrosis and patients without cystic fibrosis. Patients with cystic fibrosis were equally likely to have clustered isolates (258 [60%] of 431 patients) as those without cystic fibrosis (322 [63%] of 513 patients; p=0·38). High-density phylogenetic clusters were randomly distributed over a wide geographical area. Most isolates with a closest genetic neighbour consistent with potential transmission had no identifiable relevant epidemiological contacts. Having a clustered isolate was independently associated with increasing age (adjusted odds ratio 1·14 per 10 years, 95% CI 1·04–1·26), but not time spent as an hospital inpatient or outpatient. We identified two sibling pairs with cystic fibrosis with genetically highly divergent isolates and one pair with closely related isolates, and 25 uninfected presumed household contacts with cystic fibrosis. INTERPRETATION: Previously identified widely disseminated dominant clones of M abscessus are not restricted to patients with cystic fibrosis and occur in other chronic respiratory diseases. Although our analysis showed a small number of cases where person-to-person transmission could not be excluded, it did not support this being a major mechanism for M abscessus dissemination at a national level in England. Overall, these data should reassure patients and clinicians that the risk of acquisition from other patients in health-care settings is relatively low and motivate future research efforts to focus on identifying routes of acquisition outside of the cystic fibrosis health-care-associated niche. FUNDING: The National Institute for Health Research, Health Data Research UK, The Wellcome Trust, The Medical Research Council, and Public Health England

Direct parametric reconstruction with joint motion estimation/correction for dynamic brain PET data

Direct reconstruction of parametric images from raw photon counts has been shown to improve the quantitative analysis of dynamic positron emission tomography (PET) data. However it suffers from subject motion which is inevitable during the typical acquisition time of 1-2 hours. In this work we propose a framework to jointly estimate subject head motion and reconstruct the motion-corrected parametric images directly from raw PET data, so that the effects of distorted tissue-to-voxel mapping due to subject motion can be reduced in reconstructing the parametric images with motion-compensated attenuation correction and spatially aligned temporal PET data. The proposed approach is formulated within the maximum likelihood framework, and efficient solutions are derived for estimating subject motion and kinetic parameters from raw PET photon count data. Results from evaluations on simulated [11C]raclopride data using the Zubal brain phantom and real clinical [18F]florbetapir data of a patient with Alzheimer’s disease show that the proposed joint direct parametric reconstruction motion correction approach can improve the accuracy of quantifying dynamic PET data with large subject motion