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Abstract Background In the early COVID-19 pandemic concerns about the correct choice of analgesics in patients with COVID-19 were raised. Little data was available on potential usefulness or harmfulness of prescription free analgesics, such as paracetamol. This international multicentre study addresses that lack of evidence regarding the usefulness or potential harm of paracetamol intake prior to ICU admission in a setting of COVID-19 disease within a large, prospectively enrolled cohort of critically ill and frail intensive care unit (ICU) patients. Methods This prospective international observation study (The COVIP study) recruited ICU patients ≥ 70 years admitted with COVID-19. Data on Sequential Organ Failure Assessment (SOFA) score, prior paracetamol intake within 10 days before admission, ICU therapy, limitations of care and survival during the ICU stay, at 30 days, and 3 months. Paracetamol intake was analysed for associations with ICU-, 30-day- and 3-month-mortality using Kaplan Meier analysis. Furthermore, sensitivity analyses were used to stratify 30-day-mortality in subgroups for patient-specific characteristics using logistic regression. Results 44% of the 2,646 patients with data recorded regarding paracetamol intake within 10 days prior to ICU admission took paracetamol. There was no difference in age between patients with and without paracetamol intake. Patients taking paracetamol suffered from more co-morbidities, namely diabetes mellitus (43% versus 34%, p < 0.001), arterial hypertension (70% versus 65%, p = 0.006) and had a higher score on Clinical Frailty Scale (CFS; IQR 2–5 versus IQR 2–4, p < 0.001). Patients under prior paracetamol treatment were less often subjected to intubation and vasopressor use, compared to patients without paracetamol intake (65 versus 71%, p < 0.001; 63 versus 69%, p = 0.007). Paracetamol intake was not associated with ICU-, 30-day- and 3-month-mortality, remaining true after multivariate adjusted analysis. Conclusion Paracetamol intake prior to ICU admission was not associated with short-term and 3-month mortality in old, critically ill intensive care patients suffering from COVID-19. Trial registration. This prospective international multicentre study was registered on ClinicalTrials.gov with the identifier “NCT04321265” on March 25, 2020.

Objectives: Disease transmission models are used in impact assessment and economic evaluations of infectious disease prevention and treatment strategies, prominently so in the COVID-19 response. These models rarely consider dimensions of equity relating to the differential health burden between individuals and groups. We describe concepts and approaches which are useful when considering equity in the priority setting process, and outline the technical choices concerning model structure, outputs, and data requirements needed to use transmission models in analyses of health equity. Methods: We reviewed the literature on equity concepts and approaches to their application in economic evaluation and undertook a technical consultation on how equity can be incorporated in priority setting for infectious disease control. The technical consultation brought together health economists with an interest in equity-informative economic evaluation, ethicists specialising in public health, mathematical modellers from various disease backgrounds, and representatives of global health funding and technical assistance organisations, to formulate key areas of consensus and recommendations. Results: We provide a series of recommendations for applying the Reference Case for Economic Evaluation in Global Health to infectious disease interventions, comprising guidance on 1) the specification of equity concepts; 2) choice of evaluation framework; 3) model structure; and 4) data needs. We present available conceptual and analytical choices, for example how correlation between different equity- and disease-relevant strata should be considered dependent on available data, and outline how assumptions and data limitations can be reported transparently by noting key factors for consideration. Conclusions: Current developments in economic evaluations in global health provide a wide range of methodologies to incorporate equity into economic evaluations. Those employing infectious disease models need to use these frameworks more in priority setting to accurately represent health inequities. We provide guidance on the technical approaches to support this goal and ultimately, to achieve more equitable health policies.

Abstract Background The sublingual microcirculation presumably exhibits disease-specific changes in function and morphology. Algorithm-based quantification of functional microcirculatory hemodynamic variables in handheld vital microscopy (HVM) has recently allowed identification of hemodynamic alterations in the microcirculation associated with COVID-19. In the present study we hypothesized that supervised deep machine learning could be used to identify previously unknown microcirculatory alterations, and combination with algorithmically quantified functional variables increases the model’s performance to differentiate critically ill COVID-19 patients from healthy volunteers. Methods Four international, multi-central cohorts of critically ill COVID-19 patients and healthy volunteers (n = 59/n = 40) were used for neuronal network training and internal validation, alongside quantification of functional microcirculatory hemodynamic variables. Independent verification of the models was performed in a second cohort (n = 25/n = 33). Results Six thousand ninety-two image sequences in 157 individuals were included. Bootstrapped internal validation yielded AUROC(CI) for detection of COVID-19 status of 0.75 (0.69–0.79), 0.74 (0.69–0.79) and 0.84 (0.80–0.89) for the algorithm-based, deep learning-based and combined models. Individual model performance in external validation was 0.73 (0.71–0.76) and 0.61 (0.58–0.63). Combined neuronal network and algorithm-based identification yielded the highest externally validated AUROC of 0.75 (0.73–0.78) (P < 0.0001 versus internal validation and individual models). Conclusions We successfully trained a deep learning-based model to differentiate critically ill COVID-19 patients from heathy volunteers in sublingual HVM image sequences. Internally validated, deep learning was superior to the algorithmic approach. However, combining the deep learning method with an algorithm-based approach to quantify the functional state of the microcirculation markedly increased the sensitivity and specificity as compared to either approach alone, and enabled successful external validation of the identification of the presence of microcirculatory alterations associated with COVID-19 status.

In infectious disease epidemiology, the instantaneous reproduction number R t is a time-varying parameter defined as the average number of secondary infections generated by an infected individual at time t. It is therefore a crucial epidemiological statistic that assists public health decision makers in the management of an epidemic. We present a new Bayesian tool (EpiLPS) for robust estimation of the time-varying reproduction number. The proposed methodology smooths the epidemic curve and allows to obtain (approximate) point estimates and credible intervals of R t by employing the renewal equation, using Bayesian P-splines coupled with Laplace approximations of the conditional posterior of the spline vector. Two alternative approaches for inference are presented: (1) an approach based on a maximum a posteriori argument for the model hyperparameters, delivering estimates of R t in only a few seconds; and (2) an approach based on a Markov chain Monte Carlo (MCMC) scheme with underlying Langevin dynamics for efficient sampling of the posterior target distribution. Case counts per unit of time are assumed to follow a negative binomial distribution to account for potential overdispersion in the data that would not be captured by a classic Poisson model. Furthermore, after smoothing the epidemic curve, a “plug-in’’ estimate of the reproduction number can be obtained from the renewal equation yielding a closed form expression of R t as a function of the spline parameters. The approach is extremely fast and free of arbitrary smoothing assumptions. EpiLPS is applied on data of SARS-CoV-1 in Hong-Kong (2003), influenza A H1N1 (2009) in the USA and on the SARS-CoV-2 pandemic (2020-2021) for Belgium, Portugal, Denmark and France.

Background and purposeTwitter presence in academia has been linked to greater research impact which influences career progression. The purpose of this study was to analyse Twitter activity of the radiotherapy community around ESTRO congresses with a focus on gender-related and geographic trends.Materials and methodsTweets, re-tweets and replies, here designated as interactions, around the ESTRO congresses held in 2012–2021 were collected. Twitter activity was analysed temporally and, for the period 2016–2021, the geographical span of the ESTRO Twitter network was studied. Tweets and Twitter users collated during the 10 years analysed were ranked based on number of ‘likes’, ‘re-tweets’ and followers, considered as indicators of leadership/influence. Gender representation was assessed for the top-end percentiles.ResultsTwitter activity around ESTRO congresses was multiplied by 60 in 6 years growing from 150 interactions in 2012 to a peak of 9097 in 2018. In 2020, during the SARS-CoV-2 pandemic, activity dropped by 60 % to reach 2945 interactions and recovered to half the pre-pandemic level in 2021. Europe, North America and Oceania were strongly connected and remained the main contributors. While overall, 58 % of accounts were owned by men, this proportion increased towards top liked/re-tweeted tweets and most-followed profiles to reach up to 84 % in the top-percentiles.ConclusionDuring the SARS-CoV-2 pandemic, Twitter activity around ESTRO congresses substantially decreased. Men were over-represented on the platform and in most popular tweets and influential accounts. Given the increasing importance of social media presence in academia the gender-based biases observed may help in understanding the gender gap in career progression.

Global concern about problematic usage of the internet (PUI), and its public health and societal costs, continues to grow, sharpened in focus under the privations of the COVID-19 pandemic. This narrative review reports the expert opinions of members of the largest international network of researchers on PUI in the framework of the European Cooperation in Science and Technology (COST) Action (CA 16207), on the scientific progress made and the critical knowledge gaps remaining to be filled as the term of the Action reaches its conclusion. A key advance has been achieving consensus on the clinical definition of various forms of PUI. Based on the overarching public health principles of protecting individuals and the public from harm and promoting the highest attainable standard of health, the World Health Organisation has introduced several new structured diagnoses into the ICD-11, including gambling disorder, gaming disorder, compulsive sexual behaviour disorder, and other unspecified or specified disorders due to addictive behaviours, alongside naming online activity as a diagnostic specifier. These definitions provide for the first time a sound platform for developing systematic networked research into various forms of PUI at global scale. Progress has also been made in areas such as refining and simplifying some of the available assessment instruments, clarifying the underpinning brain-based and social determinants, and building more empirically based etiological models, as a basis for therapeutic intervention, alongside public engagement initiatives. However, important gaps in our knowledge remain to be tackled. Principal among these include a better understanding of the course and evolution of the PUI-related problems, across different age groups, genders and other specific vulnerable groups, reliable methods for early identification of individuals at risk (before PUI becomes disordered), efficacious preventative and therapeutic interventions and ethical health and social policy changes that adequately safeguard human digital rights. The paper concludes with recommendations for achievable research goals, based on longitudinal analysis of a large multinational cohort co-designed with public stakeholders. Comprehensive Psychiatry, 118 ISSN:0010-440X ISSN:1532-8384

Documento escrito por un elevado número de autores/as, solo se referencia el/la que aparece en primer lugar y los/as autores/as pertenecientes a la UC3M. The 2022 Roadmap is the next update in the series of Plasma Roadmaps published by Journal of Physics D with the intent to identify important outstanding challenges in the field of low-temperature plasma (LTP) physics and technology. The format of the Roadmap is the same as the previous Roadmaps representing the visions of 41 leading experts representing 21 countries and five continents in the various sub-fields of LTP science and technology. In recognition of the evolution in the field, several new topics have been introduced or given more prominence. These new topics and emphasis highlight increased interests in plasma-enabled additive manufacturing, soft materials, electrification of chemical conversions, plasma propulsion, extreme plasma regimes, plasmas in hypersonics and data-driven plasma science. Cristina Canal acknowledges PID2019-103892RB-I00/AEI/10.13039/501100011033 Project (AEI) and the Generalitat de Catalunya for the ICREA Academia Award and SGR2017-1165. The research by Annemie Bogaerts was funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC Synergy Grant 810182 SCOPE). Eduardo Ahedo was funded by Spain's Agencia Estatal de Investigación, under Grant No. PID2019-108034RB-I00 (ESPEOS Project).

It has been shown that the COVID-19 pandemic affected some agricultural systems more than others, and even within geographic regions, not all farms were affected to the same extent. To build resilience of agricultural systems to future shocks, it is key to understand which farms were affected and why. In this study, we examined farmers' perceived robustness to COVID-19, a key resilience capacity. We conducted standardized farmer interviews (n = 257) in 15 case study areas across Europe, covering a large range of socio-ecological contexts and farm types. Interviews targeted perceived livelihood impacts of the COVID-19 pandemic on productivity, sales, price, labor availability, and supply chains in 2020, as well as farm(er) characteristics and farm management. Our study corroborates earlier evidence that most farms were not or only slightly affected by the first wave(s) of the pandemic in 2020, and that impacts varied widely by study region. However, a significant minority of farmers across Europe reported that the pandemic was "the worst crisis in a lifetime" (3%) or "the worst crisis in a decade" (7%). Statistical analysis showed that more specialized and intensive farms were more likely to have perceived negative impacts. From a societal perspective, this suggests that highly specialized, intensive farms face higher vulnerability to shocks that affect regional to global supply chains. Supporting farmers in the diversification of their production systems while decreasing dependence on service suppliers and supply chain actors may increase their robustness to future disruptions. Agronomy for Sustainable Development, 42 (5) ISSN:1773-0155 ISSN:1774-0746 ISSN:0249-5627

Immune modulation is a key therapeutic approach for allergic diseases, asthma and autoimmunity. It can be achieved in an antigen-specific manner via allergen immunotherapy (AIT) or in an endotype-driven approach using biologicals that target the major pathways of the type 2 (T2) immune response: immunoglobulin (Ig)E, interleukin (IL)-5 and IL-4/IL-13 or non-type 2 response: anti-cytokine antibodies and B-cell depletion via anti-CD20. Coronavirus disease 2019 (COVID-19) vaccination provides an excellent opportunity to tackle the global pandemics and is currently being applied in an accelerated rhythm worldwide. The vaccine exerts its effects through immune modulation, induces and amplifies the response against the severe acute respiratory syndrome coronavirus (SARS-CoV-2). Thus, as there may be a discernible interference between these treatment modalities, recommendations on how they should be applied in sequence are expected. The European Academy of Allergy and Clinical Immunology (EAACI) assembled an expert panel under its Research and Outreach Committee (ROC). This expert panel evaluated the evidence and have formulated recommendations on the administration of COVID-19 vaccine in patients with allergic diseases and asthma receiving AIT or biologicals. The panel also formulated recommendations for COVID-19 vaccine in association with biologicals targeting the type 1 or type 3 immune response. In formulating recommendations, the panel evaluated the mechanisms of COVID-19 infection, of COVID-19 vaccine, of AIT and of biologicals and considered the data published for other anti-infectious vaccines administered concurrently with AIT or biologicals.

The COVID-19 pandemic represents one of the biggest challenges of the 21st century. In addition to the general effect on society and health-care systems, patients with systemic sclerosis and their physicians face specific challenges related to the chronic nature of their disease, the involvement of multiple organs, and the use of immunosuppressive treatments. Data from registries and single centre cohorts indicate that the risk of contracting SARS-CoV-2 does not seem to increase substantially in people with systemic sclerosis; conversely, severe COVID-19 outcomes are seen more frequently in these patients than in the general population. Vaccination against SARS-CoV-2 is therefore highly recommended for patients with systemic sclerosis; however, no specific recommendations are available regarding the different vaccine platforms. Both patients and physicians should be aware that the effectiveness of vaccines might be reduced in patients taking immunosuppressive therapy, because antibody responses might be blunted, specifically in patients treated with rituximab and mycophenolate mofetil.