Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Monte Carlo simulations of the magnetic behaviour of iron oxide nanoparticle ensembles : taking size dispersion, particle anisotropy, and dipolar interactions into account

In this work, the magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) submitted to an external magnetic field are studied using a Metropolis algorithm. The influence on the M(B) curves of the size distribution of the nanoparticles, of uniaxial anisotropy, and of dipolar interaction between the cores are examined, as well as the influence of drying the samples under a zero or non-zero magnetic field. It is shown that the anisotropy impacts the shape of the magnetization curves, which then deviate from a pure Langevin behaviour, whereas the dipolar interaction has no influence on the curves at 300 K for small particles (with a radius of $$3\,\hbox {nm}$$). The fitting of the magnetization curves of particles with magnetic anisotropy to a Langevin model (including a size distribution of the particles) can then lead to erroneous values of the distribution parameters. The simulation results are qualitatively compared to experimental results obtained for iron oxide nanoparticles (with a $$3.21\, \hbox {nm}$$ median radius)

Improvement of the Off-Resonance Saturation, an MRI sequence for positive contrast with SPM particles: Theoretical and experimental study

The SuperParaMagnetic particles (SPM particles) are used as contrast agents in MRI and produce negative contrast with conventional T2 or T2(∗)-weighted sequences. Unfortunately, the SPM particle detection on images acquired with such sequences is sometimes difficult because negative contrast can be created by artifacts such as air bubbles or calcification. To overcome this problem, new sequences as Off-Resonance Saturation (ORS) were developed to produce positive contrast with SPM particles. This work explores a new way to optimize the contrast generated by the ORS sequence by increasing the number of saturation pulses applied before the imaging sequence. This modified sequence is studied with numerical simulations and experiments on agarose gel phantoms. A theoretical model able to predict the contrast for different values of the sequence parameters is also developed. The results show that the contrast increases with the saturation pulses number with an optimal value of three saturation pulses in order to avoid artifacts and limit the Specific Absorption Rate (SAR) effect. The dependence of the contrast on the SPM particle concentration and sequence parameters is comparable to what was observed for the ORS sequence

Bottom-up study of the MRI positive contrast created by the Off-Resonance Saturation sequence

Superparamagnetic iron oxide nanoparticles (SPM particles) are used in MRI to highlight regions such as tumors through negative contrast. Unfortunately, sources as air bubbles or tissues interfaces also lead to negative contrast, which complicates the image interpretation. New MRI sequences creating positive contrast in the particle surrounding, such as the Off-Resonance Saturation sequence (ORS), have thus been developed. However, a theoretical study of the ORS sequence is still lacking, which hampers the optimization of this sequence. For this reason, this work provides a self-consistent analytical expression able to predict the dependence of the contrast on the sequence parameters and the SPM particles properties. This expression was validated by numerical simulations and experiments on agarose gel phantoms on a 11.7 T scanner system. It provides a fundamental understanding of the mechanisms leading to positive contrast, which could allow the improvement of the sequence for future in vivo applications. The influence of the SPM particle relaxivities, the SPM particle concentration, the echo time and the saturation pulse parameters on the contrast were investigated. The best contrast was achieved with SPM particles possessing the smallest transverse relaxivity, an optimal particle concentration and for low echo times

Theoretical and experimental study of ON-Resonance Saturation, an MRI sequence for positive contrast with superparamagnetic nanoparticles

Superparamagnetic iron oxide nanoparticles (SPM particles) are widely used in MRI as negative contrast agents. Their detection is sometimes difficult because negative contrast can be caused by different artifacts. To overcome this problem, MRI protocols achieving positive contrast specific to SPM particles were developed such as the ON-Resonance Saturation (ONRS) sequence. The aim of the present work is to achieve a bottom-up study of the ONRS sequence by an understanding of the physical mechanisms leading to positive contrast. A complete theoretical modeling, a novel numerical simulation approach and experiments on agarose gel phantoms on a 11.7 T MRI system were carried out for this purpose. The influence of the particle properties and concentration - as well as the effect of the sequence parameters on the contrast - were investigated. It was observed that theory and experiments were in strong agreement. The tools developed in this work allowed to predict the parameters leading to the maximum contrast. For example, particles presenting a low transverse relaxivity can provide an interesting positive contrast after optimization of their concentration in the sample