Efficacy and safety of baricitinib for the treatment of hospitalised adults with COVID-19: a systematic review and meta-analysis (preprint)

Several clinical trials have evaluated the efficacy and safety of baricitinib in COVID-19 patients. Recently, there have been reports on critical patients, which are different from previous research results. Studies were searched in PubMed, Embase, and Cochrane Library databases on January 31, 2023. We performed a meta-analysis to estimate the efficacy and safety of baricitinib for the treatment of hospitalised adults with COVID-19. This study is registered with INPLASY , number 202310086. A total of 3010 patients were included in our analyses. All included studies were randomized controlled trials or prospective study. There was no difference in 14-day mortality between the two groups (OR 0.23 [95% CI 0.03–1.84], I²=72%, P=0.17). In subgroup analyses we found that baricitinib did not seem to improve significantly in 24-day mortality critically ill patients (OR 0.60 [95% CI 0.35–1.02], I²=0%, P=0.06). Fortunately, baricitinib have led to faster recovery and shorter hospital stays for COVID-19 patients. There were no difference in infections and infestations, major adverse cardiovascular events, deep vein thrombosis and pulmonary embolism. Baricitinib is safe. At the same time, we can find that it reduces the mortality of COVID-19 patients, but the prognosis of the critically ill patients is not significantly improved.

Factors Influencing the Sustainability of Stroke Rehabilitation Services in Community: An Analysis Based on Kano Model

A patient's enthusiasm will affect their recovery during stroke rehabilitation training. Since rehabilitation training is a long process, patients are usually cared for at home, especially during the COVID-19 pandemic. However, professional supervision in the community is often lacking, resulting in low patient participation and initiative as well as the low sustainability of rehabilitation services. At present, many researchers are trying to optimize the process of community rehabilitation services to improve patient compliance. The majority of them, however, have failed to fully consider the psychological needs of the patients. Our aim was to find the key factors affecting patients' enthusiasm to participate in rehabilitation training. We also wanted to provide an optimal scheme for enhancing the sustainability of community rehabilitation services. Based on patient-centered research, we applied the Kano model and the customer satisfaction coefficient to the study and established a framework for improving the community rehabilitation experience. We observed that patients must first understand basic rehabilitation information and effective rehabilitation methods. Additionally, we found that some factors related to incentive and pleasure could meet the psychological needs of patients. Furthermore, as a result of this research, we applied the framework in practice and refined the design of a rehabilitation-training service system. This work may have significance for the design of sustainable community rehabilitation services. The purpose of this paper is to indicate the direction of rehabilitation services so that patients can take the initiative in rehabilitation.

LW‐CovidNet: Automatic covid‐19 lung infection detection from chest X‐ray images

Coronavirus Disease 2019 (Covid‐19) overtook the worldwide in early 2020, placing the world's health in threat. Automated lung infection detection using Chest X‐ray images has a ton of potential for enhancing the traditional covid‐19 treatment strategy. However, there are several challenges to detect infected regions from Chest X‐ray images, including significant variance in infected features similar spatial characteristics, multi‐scale variations in texture shapes and sizes of infected regions. Moreover, high parameters with transfer learning are also a constraints to deploy deep convolutional neural network(CNN) models in real time environment. A novel covid‐19 lightweight CNN(LW‐CovidNet) method is proposed to automatically detect covid‐19 infected regions from Chest X‐ray images to address these challenges. In our proposed hybrid method of integrating Standard and Depth‐wise Separable convolutions are used to aggregate the high level features and also compensate the information loss by increasing the Receptive Field of the model. The detection boundaries of disease regions representations are then enhanced via an Edge‐Attention method by applying heatmaps for accurate detection of disease regions. Extensive experiments indicate that the proposed LW‐CovidNet surpasses most cutting‐edge detection methods and also contributes to the advancement of state‐of‐the‐art performance. It is envisaged that with reliable accuracy, this method can be introduced for clinical practices in the future.

Contrastive Attention Network with Dense Field Estimation for Face Completion (preprint)

Most modern face completion approaches adopt an autoencoder or its variants to restore missing regions in face images. Encoders are often utilized to learn powerful representations that play an important role in meeting the challenges of sophisticated learning tasks. Specifically, various kinds of masks are often presented in face images in the wild, forming complex patterns, especially in this hard period of COVID-19. It's difficult for encoders to capture such powerful representations under this complex situation. To address this challenge, we propose a self-supervised Siamese inference network to improve the generalization and robustness of encoders. It can encode contextual semantics from full-resolution images and obtain more discriminative representations. To deal with geometric variations of face images, a dense correspondence field is integrated into the network. We further propose a multi-scale decoder with a novel dual attention fusion module (DAF), which can combine the restored and known regions in an adaptive manner. This multi-scale architecture is beneficial for the decoder to utilize discriminative representations learned from encoders into images. Extensive experiments clearly demonstrate that the proposed approach not only achieves more appealing results compared with state-of-the-art methods but also improves the performance of masked face recognition dramatically.

A Potential Novel COVID-19 Vaccine With RBD-HR1/HR2 Hexamer Structure (preprint)

The COVID-19 pandemic and the continued spreading of the SARS-CoV-2 variants have brought a grave public health consequence and severely devastated the global economy with recessions. Vaccination is considered as one of the most promising and efficient methods to end the COVID-19 pandemic and mitigate the disease conditions if infected. Although a few vaccines have been developed with an unprecedented speed, scientists around the world are continuing pursuing the best possible vaccines with innovations. Comparing to the expensive mRNA vaccines and attenuated/inactivated SARS-CoV-2 vaccines, recombinant protein vaccines have certain advantages, including their safety (non-virus components), potential stronger immunogenicity, broader protection, ease of scaling-up production, reduced cost, etc. In this study, we reported a novel COVID-19 vaccine generated with RBD-HR1/HR2 hexamer that was creatively fused with the RBD domain and heptad repeat 1 (HR1) or heptad repeat 2 (HR2) to form a dumbbell-shaped hexamer to target the spike S1 subunit. The novel hexamer COVID-19 vaccine induced high titers of neutralizing antibody in mouse studies (>100,000), and further experiments also showed that the vaccine also induced an alternative antibody to the HR1 region, which probably alleviated the drop of immunogenicity from the frequent mutations of SARS-CoV-2.

Spatial Differentiation and Elements Influencing Urban Resilience in the Middle Reaches of the Yangtze River under the COVID-19 Pandemic

Since the outbreak of COVID-19 in Wuhan City, Hubei Province, in December 2019, the middle reaches of the Yangtze River became the key areas of the spread of the pandemic and association, and also as the urban economic recovery process after the pandemic eased, it provided an excellent opportunity to research urban resilience. From the viewpoint of urban social-ecological system resilience in public health emergencies, this study comprehensively applies the spatial econometrics, geodetector model, and other methods to investigate the urban resilience level, spatial differentiation, and dominant elements in the middle reaches of the Yangtze River under the impact of the pandemic. This study would aid in providing a scientific basis for sustainable spatial planning and governance. The results demonstrated that the urban resilience in the middle reaches of the Yangtze River had notable spatial agglomeration features, eight elements including tertiary industry proportion possessed a robust explanatory power to the spatial differentiation of urban resilience, and the explanatory power was markedly enhanced after the interaction between influential elements of economic and ecological subsystems. Thus, to upgrade the system cycle mechanism and augment the endogenous power for urban development, we need to focus more on the flow of innovative elements in central cities, the optimization of ecological and safe spatial patterns in Hunan and Hubei Provinces, and the innovation of sustainable supply chain in the entire region. [ABSTRACT FROM AUTHOR] Copyright of Discrete Dynamics in Nature & Society is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Human Blastocyst is Susceptible to SARS-CoV-2 Infection based on Protein Level Examination of Key Entry Factors in Human Oocytes and Early Embryos (preprint)

Objective ACE2, TMPRSS2 and NRP1 are key factors for SARS-CoV-2 infection. Here, we used immunofluorescence to examine the expression patterns of ACE2, TMPRSS2 and NRP1 in human oocytes and different stages of preimplantation embryos to investigated the susceptibility to be infected by SARS-CoV-2.Methods We collected human GV oocytes and different stages of early embryos donated by patients and then performed immunofluorescence followed by confocal microscopy for signals of ACE2, TMPRSS2 and NRP1 proteins in these oocytes and embryos.Results We found that ACE2 was abundant in both inner cell mass and trophectoderm at blastocyst stage, while TMPRSS2 was mainly enriched in trophectoderm. Both of the two factors had faint signal in cleavage embryos and oocytes. In contrast, NRP1 was barely detectable in oocytes or any stage of early embryos. Conclusion Taken together, we propose that human blastocysts, instead of human oocytes and other stages of early embryos, are susceptible to be infected by SARS-CoV-2. Therefore, specific attention should be paid to manipulation of human blastocysts in assisted reproductive technology.

Cope with the COVID-19 Pandemic: Dynamic Bed Allocation and Patient Subsidization in a Public Healthcare System (preprint)

In many countries and territories, public hospitals play a major role in coping with the COVID-19 pandemic. For public hospital managers, on the one hand, they must best utilize their hospital beds to serve the COVID-19 patients immediately. On the other hand, they need to consider the need of bed resources from non-COVID-19 patients, including emergency and elective patients. In this work, we consider two control mechanisms for public hospital managers to maximize the overall utility of patients. One is the dynamic allocation of bed resources according to the evolution process of the COVID-19 pandemic. The other is the usage of a subsidy scheme to move elective patients from the public to private hospitals. We develop a dynamic programming model to study the allocation of isolation and ordinary beds and the effect of the subsidy policy in serving three types of patients, COVID-19, emergency, and elective-care. We first show that the dynamic allocation between isolation and ordinary beds can provide a better utilization of bed resources, by cutting down at least 33.5\% of the total cost compared with the static policy (i.e., keeping a fixed number of isolation beds) when facing a medium pandemic alert. Our results further show that subsidizing elective patients and referring them to private hospitals is an efficient way to ease the overcrowded situation in public hospitals. Our results demonstrate that, by dynamically conducting bed allocation and subsidy scheme in different phases of the COVID-19 pandemic, patient overall utility can be greatly improved.

Establishing emergency medical system of classified treatment to alleviate the overload medical needs after the community outbreak of corona virus disease 2019 in Wuhan City / 中华传染病杂志

Wuhan is the city with the most serious outbreak of corona virus disease 2019 (COVID-19) in China. The outbreak of community has exhausted the current medical resources. With integrating local and support medical resources from other province, Wuhan City has rapidly rebuilt a new emergency medical system of classified treatment, and effectively responded to the overload medical demand after the outbreak in the community.

Early-stage predictive markers of critically ill COVID-19 cases (preprint)

Background: Severe cytokine storm syndrome (CSS) is considered as the cause of death among critically ill COVID-19 cases. Early identification of the high-risk severe cases is crucial to lower the fatality and healthcare costs.Methods: In this study, we retrospectively analyzed the first and second-week serum levels of IL-6, IL-8, and IL-10 of 50 COVID-19 cases. We calculated the ratios of IL-6/IL-10 and IL-8/IL-10 at 3rd, 6th, 9th, and 12th days of hospitalization. Results: We collected 50 COVID-19 cases (male 54%, mean age 51.2, range 18 - 86), including 39 mild cases (78%), 7 severe/recovered cases (14%), and 4 died cases (8%).The ratios of IL 6/IL-10 and IL-8/IL-10 among mild cases were below 27 (the highest, 26.9) along the 4 testing points of two week hospitalization, while we found that the IL-6/IL-10 and IL-8/IL-10 ratios were as high as 187.51 and 225.3 respectively in the death group on 3rd day with the highest IL-6/IL-10 ratio of 297.28 on the 6th day of hospitalization. Conclusions: Our preliminary results suggest that the ratios of IL-6/IL-10 and IL-8/IL-10 at the early stage (the first two weeks) of COVID-19 could be a predictive marker for the disease prognosis, of which the cut-off lines were suggested below 50 for a mild and recoverable severe cases.

The Effects of Steroids in Severe Hospitalized Patients with COVID-19: A Retrospective Cohort Study (preprint)

The efficacy of corticosteroids in the treatment of patients with severe COVID-19 remains unknown. We evaluated the impact of corticosteroids on clinical improvement among severe COVID-19 patients. In this retrospective, two-centered, cohort study, we enrolled 101 patients with severe COVID-19: with 39 patients in the steroid group and 63 patients in the non-steroid group. The primary endpoint was Time to Clinical Improvement (TTCI) by up to 28 days after the treatment. Secondary endpoints included the rate of CAT scan improvement, the percentage of negative SARS-Cov-2 RT-PCR tests by Day 28, and the time to discharge. We found that patients in the steroid group did not have significant differences of TTCI from patients in the non-steroid group by 28 days after the treatment (median, 19 days vs. 20 days; hazard ratio, 1.07; p=0.797). The CAT scan improvement rate was not statistically different between the two groups by Day 28 (87.2% vs. 79.0%, p=0.170). The negative test of SARS-CoV2 RT-PCR by Day 28 was 68.4% in the steroid group, 87.1% in the non-steroid group (p= 0.060). Time to discharge was significantly longer in the steroid group than the non-steroid group (35 days vs 21 days, p=0.005). Our findings indicated the short-term corticosteroid at a low to moderate dose did not improve the clinical outcomes for patients with severe COVID-19. Further randomized clinical trials are needed to confirm the findings.