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1.
Int J Clin Pract ; : e14900, 2021 Sep 21.
Article in English | MEDLINE | ID: covidwho-1429761

ABSTRACT

AIM: This meta-analysis aimed to explore potential risk factors for severe Covid-19. METHODS: We systemically and comprehensively retrieved the eligible study evaluating clinical differences between severe vs non-severe Covid-19. Main effect sizes were demographic characteristics, comorbidities, signs and symptoms, laboratory findings as well as radiological features of chest CT. RESULTS: A total of 2566 Covid-19 people (771 in the severe group and 1795 in the non-severe group) from 14 studies were eligible for this meta-analysis. It was demonstrated that older age and males were more likely to have severe Covid-19. Patients with underlying comorbidities, such as hypertension, diabetes, heart disease and COPD were significantly more susceptible to severe Covid-19. Patients with dyspnoea were more likely to be severely ill. Depressed total lymphocytes were observed in this article. Meanwhile, although reticulation (30.8%), intrathoracic lymph node enlargement (20.5%) and pleural effusions (30.8%) were relatively infrequent, meta-analysis revealed that patients with these presentations in chest CT were associated with increased risk of severe Covid-19. CONCLUSIONS: There are significant differences in clinical characteristics between the severe and non-severe Covid-19 patients. Many factors are related to the severity of the disease, which can help clinicians to differentiate severe patients from non-severe patients.

2.
Front Immunol ; 11: 607583, 2020.
Article in English | MEDLINE | ID: covidwho-1084623

ABSTRACT

The ongoing pandemic coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is rapidly spreading and has resulted in grievous morbidity and mortality worldwide. Despite the high infectiousness of SARS-CoV-2, the majority of infected individuals are asymptomatic or have mild symptoms and could eventually recover as a result of their balanced immune function. On the contrary, immuno-compromised patients are prone to progress into severe or critical types underpinned by the entanglement of an overexuberant proinflammatory response and injured immune function. Therefore, well-coordinated innate and adaptive immune systems are pivotal to viral eradication and tissue repair. An in-depth understanding of the immunological processes underlying COVID-19 could facilitate rapidly identifying and choosing optimal immunotherapy for patients with severe SARS-CoV-2 infection. In this review, based on current immunological evidence, we describe potential immune mechanisms and discuss promising immunotherapies for COVID-19, including IL-6R blockades, convalescent plasma, intravenous gamma globulin, thymosin alpha1, corticosteroids, and type-I interferon, and recent advances in the development of COVID-19 vaccines.


Subject(s)
COVID-19/drug therapy , COVID-19/immunology , Immunotherapy/methods , Humans , SARS-CoV-2
3.
BMJ Glob Health ; 5(11)2020 11.
Article in English | MEDLINE | ID: covidwho-917789

ABSTRACT

BACKGROUND: Respiratory viruses (RVs) is a common cause of illness in people of all ages, at present, different types of sampling methods are available for respiratory viral diagnosis. However, the diversity of available sampling methods and the limited direct comparisons in randomised controlled trials (RCTs) make decision-making difficult. We did a network meta-analysis, which accounted for both direct and indirect comparisons, to determine the detection rate of different sampling methods for RVs. METHODS: Relevant articles were retrieved comprehensively by searching the online databases of PubMed, Embase and Cochrane published before 25 March 2020. With the help of R V.3.6.3 software and 'GeMTC V.0.8.2' package, network meta-analysis was performed within a Bayesian framework. Node-splitting method and I 2 test combined leverage graphs and Gelman-Rubin-Brooks plots were conducted to evaluate the model's accuracy. The rank probabilities in direct and cumulative rank plots were also incorporated to rank the corresponding sampling methods for overall and specific virus. RESULTS: 16 sampling methods with 54 438 samples from 57 literatures were ultimately involved in this study. The model indicated good consistency and convergence but high heterogeneity, hence, random-effect analysis was applied. The top three sampling methods for RVs were nasopharyngeal wash (NPW), mid-turbinate swab (MTS) and nasopharyngeal swab (NPS). Despite certain differences, the results of virus-specific subanalysis were basically consistent with RVs: MTS, NPW and NPS for influenza; MTS, NPS and NPW for influenza-a and b; saliva, NPW and NPS for rhinovirus and parainfluenza; NPW, MTS and nasopharyngeal aspirate for respiratory syncytial virus; saliva, NPW and MTS for adenovirus and sputum; MTS and NPS for coronavirus. CONCLUSION: This network meta-analysis provides supporting evidences that NPW, MTS and NPS have higher diagnostic value regarding RVs infection, moreover, particular preferred methods should be considered in terms of specific virus pandemic. Of course, subsequent RCTs with larger samples are required to validate our findings.


Subject(s)
Respiratory Tract Infections/virology , Specimen Handling/methods , Bayes Theorem , Humans , Network Meta-Analysis
5.
Brain Behav Immun ; 88: 50-58, 2020 08.
Article in English | MEDLINE | ID: covidwho-549071

ABSTRACT

Sleep is known to play an important role in immune function. However, the effects of sleep quality during hospitalization for COVID-19 remain unclear. This retrospective, single-center cohort study was conducted to investigate the effects of sleep quality on recovery from lymphopenia and clinical outcomes in hospitalized patients with laboratory-confirmed COVID-19 admitted to the West District of Wuhan Union Hospital between January 25 and March 15, 2020. The Richards-Campbell sleep questionnaire (RCSQ) and Pittsburgh Sleep Quality Index (PSQI) were used to assess sleep quality. The epidemiological, demographic, clinical, laboratory, treatment, and outcome data were collected from electronic medical records and compared between the good-sleep group and poor-sleep group. In all, 135 patients (60 in good-sleep group and 75 in poor-sleep group) were included in this study. There were no significant between-group differences regarding demographic and baseline characteristics, as well as laboratory parameters upon admission and in-hospital treatment. Compared with patients in the good-sleep group, patients in the poor-sleep group had lower absolute lymphocyte count (ALC) (day 14: median, 1.10 vs 1.32, P = 0.0055; day 21: median, 1.18 vs 1.48, P = 0.0034) and its reduced recovery rate (day 14: median, 56.91 vs 69.40, P = 0.0255; day 21: median, 61.40 vs 111.47, P = 0.0003), as well as increased neutrophil-to-lymphocyte ratio (NLR; day 14: median, 3.17 vs 2.44, P = 0.0284; day 21: median, 2.73 vs 2.23, P = 0.0092) and its associated deterioration rate (day 14: median, -39.65 vs -61.09, P = 0.0155; day 21: median, -51.40% vs -75.43, P = 0.0003). Nine [12.0%] patients in the poor-sleep group required ICU care (P = 0.0151); meanwhile, none of the patients in good-sleep group required ICU care. Patients in the poor-sleep group had increased duration of hospital stay (33.0 [23.0-47.0] days vs 25.0 [20.5-36.5] days, P = 0.0116) compared to those in the good-sleep group. An increased incidence of hospital-acquired infection (seven [9.3%] vs one [1.7%]) was observed in the poor-sleep group compared to the good-sleep group; however, this difference was not significant (P = 0.1316). In conclusion, poor sleep quality during hospitalization in COVID-19 patients with lymphopenia is associated with a slow recovery from lymphopenia and an increased need for ICU care.


Subject(s)
Coronavirus Infections/blood , Lymphopenia/blood , Pneumonia, Viral/blood , Sleep Initiation and Maintenance Disorders/physiopathology , Sleep , Aged , Betacoronavirus , COVID-19 , Convalescence , Coronavirus Infections/complications , Coronavirus Infections/physiopathology , Coronavirus Infections/therapy , Female , Health Facility Environment , Hospitalization , Humans , Intensive Care Units/statistics & numerical data , Length of Stay , Lymphopenia/complications , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/physiopathology , Pneumonia, Viral/therapy , Retrospective Studies , SARS-CoV-2 , Sleep Initiation and Maintenance Disorders/complications , Time Factors
6.
Brain Behav Immun ; 87: 59-73, 2020 07.
Article in English | MEDLINE | ID: covidwho-102174

ABSTRACT

As of April 15, 2020, the ongoing coronavirus disease 2019 (COVID-2019) pandemic has swept through 213 countries and infected more than 1,870,000 individuals, posing an unprecedented threat to international health and the economy. There is currently no specific treatment available for patients with COVID-19 infection. The lessons learned from past management of respiratory viral infections have provided insights into treating COVID-19. Numerous potential therapies, including supportive intervention, immunomodulatory agents, antiviral therapy, and convalescent plasma transfusion, have been tentatively applied in clinical settings. A number of these therapies have provided substantially curative benefits in treating patients with COVID-19 infection. Furthermore, intensive research and clinical trials are underway to assess the efficacy of existing drugs and identify potential therapeutic targets to develop new drugs for treating COVID-19. Herein, we summarize the current potential therapeutic approaches for diseases related to COVID-19 infection and introduce their mechanisms of action, safety, and effectiveness.


Subject(s)
Coronavirus Infections/therapy , Pneumonia, Viral/therapy , Adrenal Cortex Hormones/therapeutic use , Angiotensin-Converting Enzyme 2 , Anti-Inflammatory Agents, Non-Steroidal/therapeutic use , Antibodies, Monoclonal, Humanized/therapeutic use , Anticoagulants/therapeutic use , Antimalarials/therapeutic use , Antiviral Agents/therapeutic use , Betacoronavirus , Bevacizumab/therapeutic use , COVID-19 , COVID-19 Vaccines , Chloroquine/therapeutic use , Coronavirus Infections/drug therapy , Coronavirus Infections/prevention & control , Humans , Hydroxychloroquine/therapeutic use , Immunization, Passive , Immunoglobulins, Intravenous/therapeutic use , Immunologic Factors/therapeutic use , Interferons/therapeutic use , Janus Kinase Inhibitors/therapeutic use , Killer Cells, Natural , Medicine, Chinese Traditional , Mesenchymal Stem Cell Transplantation , Nitric Oxide/therapeutic use , Pandemics , Peptidyl-Dipeptidase A , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Trace Elements/therapeutic use , Viral Vaccines/therapeutic use , Vitamins/therapeutic use , Zinc/therapeutic use
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