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ObjectivesWe conducted a systematic literature review and meta-analysis of observational studies to investigate the association between diabetes, hypertension, body mass index (BMI) or smoking with the risk of death in patients with COVID-19 and to estimate the proportion of deaths attributable to these conditions.MethodsRelevant observational studies were identified by searches in the PubMed, Cochrane library and Embase databases through 14 November 2020. Random-effects models were used to estimate summary relative risks (SRRs) and 95% CIs. Certainty of evidence was assessed using the Cochrane methods and the Grading of Recommendations, Assessment, Development and Evaluations framework.ResultsA total of 186 studies representing 210 447 deaths among 1 304 587 patients with COVID-19 were included in this analysis. The SRR for death in patients with COVID-19 was 1.54 (95% CI 1.44 to 1.64, I2=92%, n=145, low certainty) for diabetes and 1.42 (95% CI 1.30 to 1.54, I2=90%, n=127, low certainty) for hypertension compared with patients without each of these comorbidities. Regarding obesity, the SSR was 1.45 (95% CI 1.31 to 1.61, I2=91%, n=54, high certainty) for patients with BMI ≥30 kg/m2 compared with those with BMI <30 kg/m2 and 1.12 (95% CI 1.07 to 1.17, I2=68%, n=25) per 5 kg/m2 increase in BMI. There was evidence of a J-shaped non-linear dose–response relationship between BMI and mortality from COVID-19, with the nadir of the curve at a BMI of around 22–24, and a 1.5–2-fold increase in COVID-19 mortality with extreme obesity (BMI of 40–45). The SRR was 1.28 (95% CI 1.17 to 1.40, I2=74%, n=28, low certainty) for ever, 1.29 (95% CI 1.03 to 1.62, I2=84%, n=19) for current and 1.25 (95% CI 1.11 to 1.42, I2=75%, n=14) for former smokers compared with never smokers. The absolute risk of COVID-19 death was increased by 14%, 11%, 12% and 7% for diabetes, hypertension, obesity and smoking, respectively. The proportion of deaths attributable to diabetes, hypertension, obesity and smoking was 8%, 7%, 11% and 2%, respectively.ConclusionOur findings suggest that diabetes, hypertension, obesity and smoking were associated with higher COVID-19 mortality, contributing to nearly 30% of COVID-19 deaths.Trial registration numberCRD42020218115.

In the last decade Open Science principles have been successfully advocated for and are being slowly adopted in different research communities. In response to the COVID-19 pandemic many publishers and researchers have sped up their adoption of Open Science practices, sometimes embracing them fully and sometimes partially or in a sub-optimal manner. In this article, we express concerns about the violation of some of the Open Science principles and its potential impact on the quality of research output. We provide evidence of the misuses of these principles at different stages of the scientific process. We call for a wider adoption of Open Science practices in the hope that this work will encourage a broader endorsement of Open Science principles and serve as a reminder that science should always be a rigorous process, reliable and transparent, especially in the context of a pandemic where research findings are being translated into practice even more rapidly. We provide all data and scripts at https://osf.io/renxy/ .

Background Early appropriate antibiotic therapy reduces morbidity and mortality of severe pneumonia. However, the emergence of bacterial resistance requires the earliest use of antibiotics with the narrowest possible spectrum. The Unyvero Hospitalized Pneumonia (HPN, Curetis) test is a multiplex PCR (M-PCR) system detecting 21 bacteria and 19 resistance genes on respiratory samples within 5 h. We assessed the performance and the potential impact of the M-PCR on the antibiotic therapy of ICU patients. Methods In this prospective study, we performed a M-PCR on bronchoalveolar lavage (BAL) or plugged telescoping catheter (PTC) samples of patients with ventilated HAP or VAP with Gram-negative bacilli or clustered Gram-positive cocci. This study was conducted in 3 ICUs in a French academic hospital: the medical and infectious diseases ICU, the surgical ICU, and the cardio-surgical ICU. A multidisciplinary expert panel simulated the antibiotic changes they would have made if the M-PCR results had been available. Results We analyzed 95 clinical samples of ventilated HAP or VAP (72 BAL and 23 PTC) from 85 patients (62 males, median age 64 years). The median turnaround time of the M-PCR was 4.6 h (IQR 4.4–5). A total of 90/112 bacteria were detected by the M-PCR system with a global sensitivity of 80% (95% CI, 73–88%) and specificity of 99% (95% CI 99–100). The sensitivity was better for Gram-negative bacteria (90%) than for Gram-positive cocci (62%) ( p  = 0.005). Moreover, 5/8 extended-spectrum beta-lactamases (CTX-M gene) and 4/4 carbapenemases genes (3 NDM, one oxa-48) were detected. The M-PCR could have led to the earlier initiation of an effective antibiotic in 20/95 patients (21%) and to early de-escalation in 37 patients (39%) but could also have led to one (1%) inadequate antimicrobial therapy. Among 17 empiric antibiotic treatments with carbapenems, 10 could have been de-escalated in the following hours according to the M-PCR results. The M-PCR also led to 2 unexpected diagnosis of severe legionellosis confirmed by culture methods. Conclusions Our results suggest that the use of a M-PCR system for respiratory samples of patients with VAP and ventilated HAP could improve empirical antimicrobial therapy and reduce the use of broad-spectrum antibiotics.

The COVID-19 pandemic poses a historical challenge to society. The profusion of data requires machine learning to improve and accelerate COVID-19 diagnosis, prognosis and treatment. However, a global and open approach is necessary to avoid pitfalls in these applications.

Controversy remains regarding the transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To review current evidence on air contamination with SARS-CoV-2 in hospital settings and the factors associated with contamination, including viral load and particle size. The MEDLINE, Embase, and Web of Science databases were systematically queried for original English-language articles detailing SARS-CoV-2 air contamination in hospital settings between January 1 and October 27, 2020. This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The positivity rate of SARS-CoV-2 viral RNA and culture were described and compared according to the setting, clinical context, air ventilation system, and distance from patients. The SARS-CoV-2 RNA concentrations in copies per meter cubed of air were pooled, and their distribution was described by hospital areas. Particle sizes and SARS-CoV-2 RNA concentrations in copies or median tissue culture infectious dose (TCID50) per meter cubed were analyzed after categorization as less than 1 μm, from 1 to 4 μm, and greater than 4 μm. Among 2284 records identified, 24 cross-sectional observational studies were included in the review. Overall, 82 of 471 air samples (17.4%) from close patient environments were positive for SARS-CoV-2 RNA, with a significantly higher positivity rate in intensive care unit settings (intensive care unit, 27 of 107 [25.2%] vs non-intensive care unit, 39 of 364 [10.7%]; P < .001). There was no difference according to the distance from patients (≤1 m, 3 of 118 [2.5%] vs >1-5 m, 13 of 236 [5.5%]; P = .22). The positivity rate was 5 of 21 air samples (23.8%) in toilets, 20 of 242 (8.3%) in clinical areas, 15 of 122 (12.3%) in staff areas, and 14 of 42 (33.3%) in public areas. A total of 81 viral cultures were performed across 5 studies, and 7 (8.6%) from 2 studies were positive, all from close patient environments. The median (interquartile range) SARS-CoV-2 RNA concentrations varied from 1.0 × 103 copies/m3 (0.4 × 103 to 3.1 × 103 copies/m3) in clinical areas to 9.7 × 103 copies/m3 (5.1 × 103 to 14.3 × 103 copies/m3) in the air of toilets or bathrooms. Protective equipment removal and patient rooms had high concentrations per titer of SARS-CoV-2 (varying from 0.9 × 103 to 40 × 103 copies/m3 and 3.8 × 103 to 7.2 × 103 TCID50/m3), with aerosol size distributions that showed peaks in the region of particle size less than 1 μm; staff offices had peaks in the region of particle size greater than 4 μm. In this systematic review, the air close to and distant from patients with coronavirus disease 2019 was frequently contaminated with SARS-CoV-2 RNA; however, few of these samples contained viable viruses. High viral loads found in toilets and bathrooms, staff areas, and public hallways suggest that these areas should be carefully considered.

An Emergency Use Authorization was issued in the United States and in Europe for a monoclonal antibody monotherapy to prevent severe COVID-19 in high-risk patients. This study aimed to assess the risk of emergence of mutations following treatment with a single monoclonal antibody. Bamlanivimab was administered at a single dose of 700 mg in a one-hour IV injection in a referral center for the management of COVID-19 in France. Patients were closely monitored clinically and virologically with nasopharyngeal RT-PCR and viral whole genome sequencing. Six patients were treated for a nosocomial SARS-CoV-2 infection, all males, with a median age of 65 years and multiple comorbidities. All patients were infected with a B.1.1.7 variant, which was the most frequent variant in France at the time, and no patients had E484 mutations at baseline. Bamlanivimab was infused in the six patients within 4 days of the COVID-19 diagnosis. Four patients had a favorable outcome, one died of complications unrelated to COVID-19 or bamlanivimab, and one kidney transplant patient treated with belatacept died from severe COVID-19 more than 40 days after bamlanivimab administration. Virologically, four patients cleared nasopharyngeal viral shedding within one month after infusion, while two presented prolonged viral excretion for more than 40 days. The emergence of E484K mutants was observed in five out of six patients, and the last patient presented a Q496R mutation potentially associated with resistance. CONCLUSIONS: These results show a high risk of emergence of resistance mutants in COVID-19 patients treated with monoclonal antibody monotherapy.

Background Healthcare services across the world have been deeply impacted by the COVID-19 pandemic. In primary care, community pharmacists have had an important role in the frontline healthcare response to the pandemic. Objectives This study aimed to explore the experiences, contributions and perceived challenges of community pharmacists regarding the provision of healthcare services during the COVID-19 pandemic. Methods Semi-structured qualitative interviews were conducted with community pharmacists in France. Participants were recruited through a professional organization of pharmacists combined with a snowballing technique. Interviews were transcribed and then analyzed using thematic analysis. Results A total of 16 community pharmacists participated in the interviews. Study participants described providing a range of novel services in response to the pandemic on top of continuing their usual services. All participants described providing preventative services to reduce and mitigate the spread of SARS-CoV-2, such as education on hygiene and social distancing, delivery of face masks and hand sanitizer and adjusting pharmacy premises. Most respondents also described being involved in SARS-CoV-2 detection through screening and performing antigen testing in pharmacies. Participants reported being actively involved in COVID-19 vaccination by educating the general public about vaccines, facilitating their distribution to general practitioners as well as administering vaccines. Over half the respondents described rapidly changing guidelines and service users’ anxiety as challenges to the provision of healthcare services during the pandemic. Conclusions This study suggests that community pharmacists have significantly contributed to the response to the COVID-19 pandemic by ensuring continuity of pharmaceutical services and providing novel screening, testing and vaccination services. Their roles and responsibilities during the COVID-19 health crisis indicate that they can play an important role in the management of emerging infectious diseases.

Suboptimal use of antimicrobials is a driver of antimicrobial resistance in West Africa. Clinical decision support systems (CDSSs) can facilitate access to updated and reliable recommendations. This study aimed to assess contextual factors that could facilitate the implementation of a CDSS for antimicrobial prescribing in West Africa and Central Africa and to identify tailored implementation strategies. This qualitative study was conducted through 21 semistructured individual interviews via videoconference with health care professionals between September and December 2020. Participants were recruited using purposive sampling in a transnational capacity-building network for hospital preparedness in West Africa. The interview guide included multiple constructs derived from the Consolidated Framework for Implementation Research. Interviews were transcribed, and data were analyzed using thematic analysis. The panel of participants included health practitioners (12/21, 57%), health actors trained in engineering (2/21, 10%), project managers (3/21, 14%), antimicrobial resistance research experts (2/21, 10%), a clinical microbiologist (1/21, 5%), and an anthropologist (1/21, 5%). Contextual factors influencing the implementation of eHealth tools existed at the individual, health care system, and national levels. At the individual level, the main challenge was to design a user-centered CDSS adapted to the prescriber's clinical routine and structural constraints. Most of the participants stated that the CDSS should not only target physicians in academic hospitals who can use their network to disseminate the tool but also general practitioners, primary care nurses, midwives, and other health care workers who are the main prescribers of antimicrobials in rural areas of West Africa. The heterogeneity in antimicrobial prescribing training among prescribers was a significant challenge to the use of a common CDSS. At the country level, weak pharmaceutical regulations, the lack of official guidelines for antimicrobial prescribing, limited access to clinical microbiology laboratories, self-medication, and disparity in health care coverage lead to inappropriate antimicrobial use and could limit the implementation and diffusion of CDSS for antimicrobial prescribing. Participants emphasized the importance of building a solid eHealth ecosystem in their countries by establishing academic partnerships, developing physician networks, and involving diverse stakeholders to address challenges. Additional implementation strategies included conducting a local needs assessment, identifying early adopters, promoting network weaving, using implementation advisers, and creating a learning collaborative. Participants noted that a CDSS for antimicrobial prescribing could be a powerful tool for the development and dissemination of official guidelines for infectious diseases in West Africa. These results suggest that a CDSS for antimicrobial prescribing adapted for nonspecialized prescribers could have a role in improving clinical decisions. They also confirm the relevance of adopting a cross-disciplinary approach with participants from different backgrounds to assess contextual factors, including social, political, and economic determinants.

We investigated whether baseline levels of biomarkers related to endotheliopathy, thromboinflammation, and fibrosis were associated with clinical outcomes in hospitalized COVID-19 patients. We analyzed the associations between baseline levels of 21 biomarkers and time to hospital discharge and change in NEWS-2 score in patients from DisCoVeRy trial. We fitted multivariate models adjusted for baseline ISARIC 4C score, disease severity, D-dimer values, and treatment regimen. Between March 22 and June 29, 2020, 603 participants were randomized; 454 had a sample collected at baseline and analyzed. The backward selection of multivariate models showed that higher baseline levels of soluble suppressor of tumorigenicity 2 (sST2) and nucleosomes were statistically associated with a lower chance of hospital discharge before day 29 (sST2: aHR 0.24, 95% CI [0.15–0.38], p  < 10 −9 ; nucleosomes: aHR 0.62, 95% CI [0.48–0.81], p  < 10 −3 ). Likewise, higher levels of baseline sST2 were statistically associated with lower changes in the NEWS-2 score between baseline and day 15 (adjusted beta 4.47, 95% CI [2.65–6.28], p  < 10 −5 ). Moreover, we evaluated sST2 involvement in a confirmation cohort (SARCODO study, 103 patients) and found that elevated baseline sST2 levels were significantly associated with lower rates of hospital discharge before day 29 and a higher model performance (AUC at day 29 of 92%) compared to models without sST2. sST2 emerged as an independent predictor of clinical outcomes in two large cohort of hospitalized COVID-19 patients, warranting further investigation to elucidate its role in disease progression and potential as a therapeutic target.

Background All prevention efforts currently being implemented for COVID-19 are aimed at reducing the burden on strained health systems and human resources. There has been little research conducted to understand how SARS-CoV-2 has affected health care systems and professionals in terms of their work. Finding effective ways to share the knowledge and insight between countries, including lessons learned, is paramount to the international containment and management of the COVID-19 pandemic. The aim of this project is to compare the pandemic response to COVID-19 in Brazil, Canada, China, France, Japan, and Mali. This comparison will be used to identify strengths and weaknesses in the response, including challenges for health professionals and health systems. Methods We will use a multiple case study approach with multiple levels of nested analysis. We have chosen these countries as they represent different continents and different stages of the pandemic. We will focus on several major hospitals and two public health interventions (contact tracing and testing). It will employ a multidisciplinary research approach that will use qualitative data through observations, document analysis, and interviews, as well as quantitative data based on disease surveillance data and other publicly available data. Given that the methodological approaches of the project will be largely qualitative, the ethical risks are minimal. For the quantitative component, the data being used will be made publicly available. Discussion We will deliver lessons learned based on a rigorous process and on strong evidence to enable operational-level insight for national and international stakeholders.