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Clinical question What is the role of drug interventions in the treatment and prevention of covid-19? Recommendations The first version on this living guidance focuses on corticosteroids. It contains a strong recommendation for systemic corticosteroids in patients with severe and critical covid-19, and a weak or conditional recommendation against systemic corticosteroids in patients with non-severe covid-19. Corticosteroids are inexpensive and are on the World Health Organisation list of essential medicines. How this guideline was created This guideline reflects an innovative collaboration between the WHO and the MAGIC Evidence Ecosystem Foundation, driven by an urgent need for global collaboration to provide trustworthy and living covid-19 guidance. A standing international panel of content experts, patients, clinicians, and methodologists, free from relevant conflicts of interest, produce recommendations for clinical practice. The panel follows standards, methods, processes, and platforms for trustworthy guideline development using the GRADE approach. We apply an individual patient perspective while considering contextual factors (that is, resources, feasibility, acceptability, equity) for countries and healthcare systems. The evidence A living systematic review and network meta-analysis, supported by a prospective meta-analysis, with data from eight randomised trials (7184 participants) found that systemic corticosteroids probably reduce 28 day mortality in patients with critical covid-19 (moderate certainty evidence;87 fewer deaths per 1000 patients (95% confidence interval 124 fewer to 41 fewer)), and also in those with severe disease (moderate certainty evidence;67 fewer deaths per 1000 patients (100 fewer to 27 fewer)). In contrast, systemic corticosteroids may increase the risk of death in patients without severe covid-19 (low certainty evidence;absolute effect estimate 39 more per 1000 patients, (12 fewer to 107 more)). Systemic corticosteroids probably reduce the need for invasive mechanical ventilation, and harms are likely to be minor (indirect evidence). Understanding the recommendations The panel made a strong recommendation for use of corticosteroids in severe and critical covid-19 because there is a lower risk of death among people treated with systemic corticosteroids (moderate certainty evidence), and they believe that all or almost all fully informed patients with severe and critical covid-19 would choose this treatment. In contrast, the panel concluded that patients with non-severe covid-19 would decline this treatment because they would be unlikely to benefit and may be harmed. Moreover, taking both a public health and a patient perspective, the panel warned that indiscriminate use of any therapy for covid-19 would potentially rapidly deplete global resources and deprive patients who may benefit from it most as potentially lifesaving therapy. Updates This is a living guideline. Work is under way to evaluate other interventions. New recommendations will be published as updates to this guideline. Readers note This is version 1 of the living guideline, published on 4 September (BMJ 2020;370:m3379) version 1. Updates will be labelled as version 2, 3 etc. When citing this article, please cite the version number. Submitted August 28 Accepted August 31Copyright © Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to.
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Background: Psychiatric impact of COVID-19 is still explored and previous data suggest potential long-term risks of anxiety, depression and PTSD related to COVID-19 1,2,3. We aimed to explore the predictive value of risk factors during hospitalization for COVID-19 for anxiety, depression and PTSD and at three months because they could differ over these two time points. Methods: We performed a screening of mental suffering in hospitalized patients for COVID-19, as well as specialized care and three months longitudinal follow-up. We evaluated the prevalence of anxiety, depression and PTSD in survivors who benefited from early detection and treatment, during hospitalization for COVID-19 (T0) and three months after (T1) and assessed possible risk factors in adults surviving COVID-19 between the 30th March and the 1st of July 2020. Univariate and multivariate regressive linear model have been built to assess the factors associated with the post-traumatic stress disorder scale 5 (PCL5) and Hospital Anxiety and Depression Scale (HADS) at T0, and T1. For the univariate model of HADS and post-traumatic stress disorder scale 5 (PCL5) at T1, we also included HADS and PCL5 at T0. We used STATA 15 for the statistical analyses. Results: A total of 364 patients were hospitalized between the 30th of March and 1st of July 2020 and of these, 109 patients were screened at T0 and 61 of these were reassessed at T1. During hospitalization, we found 44.9% pathological score on PDEQ, 14.6% with a score of PCL5 > 31 and three months after hospitalization, 10.6% of PCL5 score >31. Finally, PDEQ score at T0 was positively correlated to PCL5 score at T1 (β=0.26, p=0.01) and that was confirmed in multivariate analysis (β=0.04, p=0.02 for the log of PCL5 per point on the PDEQ). Female gender was associated with higher HADS-Depression score during hospitalization in both univariate and multivariate regression models (β=0.58 for the log of HADS-D, p=0.019, data not shown, available upon request). Age ≥ 65 years old was associated with lower HADS-Depression at T0 (p=0.027) only in the univariate analysis. Psychiatric follow-up recorded at 1 month following hospitalization was associated with higher HADS-Anxiety score at T1 (β=0.52, p=0.028) only in the multivariate analysis. In univariate analysis, PDEQ, HADS-Anxiety, HADS-Depression and PCL5 scores during hospitalization were correlated with PCL5 score at T1. Patients requiring an ICU stay, compared to those who did not, had significantly higher PDEQ score during hospitalization (24.1 versus 15.6, p = 0.0014), but a lower HADS-A score three months after hospitalization (5.3 vs 2.3, p=0.01) and a lower HADS-D score at T0 (5.4 vs 2.6, p=0.01). In the multivariate analysis using the log of the outcomes, ICU stay was associated with a lower PCL5 at T1 (β=-1.24, p=0.012), a lower HADS-A at T1 (β=-0.77, p=0.019), and lower HADS-D at T0 (β=-1.03, p=0.004), and T1 (β-1.06, p=0.023). Conclusion: Screening of psychiatric symptoms during hospitalization for COVID-19 should be systematic, especially peritraumatic dissociation to offer an early treatment and prevent PTSD, which seemed frequent for hospitalized patients for COVID-19 at three months. No conflict of interest
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OBJECTIVES: To validate the diagnostic accuracy of a Euroimmun SARS-CoV-2 IgG and IgA immunoassay for COVID-19. METHODS: In this unmatched (1:2) case-control validation study, we used sera of 181 laboratory-confirmed SARS-CoV-2 cases and 326 controls collected before SARS-CoV-2 emergence. Diagnostic accuracy of the immunoassay was assessed against a whole spike protein-based recombinant immunofluorescence assay (rIFA) by receiver operating characteristic (ROC) analyses. Discrepant cases between ELISA and rIFA were further tested by pseudo-neutralization assay. RESULTS: COVID-19 patients were more likely to be male and older than controls, and 50.3% were hospitalized. ROC curve analyses indicated that IgG and IgA had high diagnostic accuracies with AUCs of 0.990 (95% Confidence Interval [95%CI]: 0.983-0.996) and 0.978 (95%CI: 0.967-0.989), respectively. IgG assays outperformed IgA assays (p=0.01). Taking an assessed 15% inter-assay imprecision into account, an optimized IgG ratio cut-off > 2.5 displayed a 100% specificity (95%CI: 99-100) and a 100% positive predictive value (95%CI: 96-100). A 0.8 cut-off displayed a 94% sensitivity (95%CI: 88-97) and a 97% negative predictive value (95%CI: 95-99). Substituting the upper threshold for the manufacturer's, improved assay performance, leaving 8.9% of IgG ratios indeterminate between 0.8-2.5. CONCLUSIONS: The Euroimmun assay displays a nearly optimal diagnostic accuracy using IgG against SARS-CoV-2 in patient samples, with no obvious gains from IgA serology. The optimized cut-offs are fit for rule-in and rule-out purposes, allowing determination of whether individuals in our study population have been exposed to SARS-CoV-2 or not. IgG serology should however not be considered as a surrogate of protection at this stage.