Prophylaxis for COVID-19: a systematic review

BackgroundWhile the landscape of vaccine and treatment candidates against the novel coronavirus disease 2019 (COVID-19) has been reviewed systematically, prophylactic candidates remain unexplored.ObjectivesTo map pre- and postexposure prophylactic (PrEP and PEP) candidate for COVID-19.Data sourcesPubMed/Medline, Embase, International Committee of Medical Journal Editors and International Clinical Trials Registry Platform clinical trial registries and medRxiv.Study eligibility criteria and participantsAll studies in humans or animals and randomized controlled trials (RCTs) in humans reporting primary data on prophylactic candidates against COVID-19, excluding studies focused on key populations.InterventionsPrEP and PEP candidate for COVID-19.MethodsSystematic review and qualitative synthesis of COVID-19 PrEP and PEP studies and RCTs complemented by search of medRxiv and PubMed and Embase for studies reporting RCT outcomes since systematic review search completion.ResultsWe identified 13 studies (from 2119 database records) and 117 RCTs (from 5565 RCTs listed in the registries) that met the inclusion criteria. Non-RCT studies reported on cross-sectional studies using hydroxychloroquine (HCQ) in humans (n = 2) or reported on animal studies (n = 7), most of which used antibodies. All five completed RCTs focused on the use of HCQ as either PrEP or PEP, and these and the cross-sectional studies reported no prophylactic effect. The majority of ongoing RCTs evaluated HCQ or other existing candidates including non–severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines, anti(retro)virals or use of vitamins and supplements.ConclusionsThe key message from completed studies and RCTs seems to be that HCQ does not work. There is little evidence regarding other compounds, with all RCTs using candidates other than HCQ still ongoing. It remains to be seen if the portfolio of existing molecules being evaluated in RCTs will identify successful prophylaxis against COVID-19 or if there is a need for the development of new candidates.     

Hypotheses and facts for genetic factors related to severe COVID-19

Genome-wide association analysis allows the identification of potential candidate genes involved in the development of severe coronavirus disease 2019 (COVID-19). Hence, it seems that genetics matters here, as well. Nevertheless, the virus's nature, including its RNA structure, determines the rate of mutations leading to new viral strains with all epidemiological and clinical consequences. Given these observations, we herein comment on the current hypotheses about the possible role of the genes in association with COVID-19 severity. We discuss some of the major candidate genes that have been identified as potential genetic factors associated with the COVID-19 severity and infection susceptibility: HLA, ABO, ACE2, TLR7, ApoE, TYK2, OAS, DPP9, IFNAR2, CCR2, etc. Further study of genes and genetic variants will be of great benefit for the prevention and assessment of the individual risk and disease severity in different populations. These scientific data will serve as a basis for the development of clinically applicable diagnostic and prognostic tests for patients at high risk of COVID-19.     

Immunological and clinical efficacy of COVID-19 vaccines in immunocompromised populations: a systematic review

BackgroundAvailable data show that COVID-19 vaccines may be less effective in immunocompromised populations, who are at increased risk of severe COVID-19.ObjectivesWe conducted a systematic review of literature to assess immunogenicity, efficacy and effectiveness of COVID-19 vaccines in immunocompromised populations.Data sourcesWe searched Medline and Embase databases.Study eligibility criteria, patients, interventionsWe included studies of COVID-19 vaccines after complete vaccination in immunocompromised patients until 31 August 2021. Studies with <10 patients, safety data only and case series of breakthrough infections were excluded.MethodsRisk of bias was assessed via the tool developed by the National Institutes of Health on interventional and observational studies. Immunogenicity was assessed through non-response rate defined as no anti-SARS-CoV-2 spike protein antibodies, efficacy and effectiveness by the relative reduction in risk of SARS-CoV-2 infection or COVID-19. We collected factors associated with the risk of non-response. We presented collected data by immunosuppression type.ResultsWe screened 5917 results, included 162 studies. There were 157 on immunogenicity in 25 209 participants, including 7835 cancer or haematological malignancy patients (31.1%), 6302 patients on dialysis (25.0%), 5974 solid organ transplant recipients (23.7%) and 4680 immune-mediated disease patients (18.6%). Proportion of non-responders seemed higher among solid organ transplant recipients (range 18–100%) and patients with haematological malignancy (range 14–61%), and lower in patients with cancer (range 2–36%) and patients on dialysis (range 2–30%). Risk factors for non-response included older age, use of corticosteroids, immunosuppressive or anti-CD20 agent. Ten studies evaluated immunogenicity of an additional dose. Five studies evaluated vaccine efficacy or effectiveness: three on SARS-CoV-2 infection (range 71–81%), one on COVID-19-related hospitalization (62.9%), one had a too small sample size.ConclusionsThis systematic review highlights the risk of low immunogenicity of COVID-19 vaccines in immunocompromised populations, especially solid organ transplant recipients and patients with haematological malignancy. Despite lack of vaccine effectiveness data, enhanced vaccine regimens may be necessary.     

New-onset diabetes in COVID-19 and clinical outcomes: A systematic review and meta-analysis

BACKGROUNDDiabetes mellitus (DM) is associated with adverse clinical outcomes and high mortality in patients with coronavirus disease 2019 (COVID-19). The relationship between diabetes and COVID-19 is known to be bidirectional.AIMTo analyze the rate of new-onset diabetes in COVID-19 patients and compare the clinical outcomes of new-onset diabetes, pre-existing diabetes, hyperglycemic, and non-diabetes among COVID-19 patients.METHODSWe used the Meta-analysis of Observational Studies in Epidemiology statement for the present meta-analysis. Online databases were searched for all peer-reviewed articles published until November 6, 2020. Articles were screened using Covidence and data extracted. Further analysis was done using comprehensive meta-analysis. Among the 128 studies detected after thorough database searching, seven were included in the quantitative analysis. The proportion was reported with 95% confidence interval (CI) and heterogeneity was assessed using I².RESULTSAnalysis showed that 19.70% (CI: 10.93-32.91) of COVID-19 patients had associated DM, and 25.23% (CI: 19.07-32.58) had associated hyperglycemia. The overall mortality rate was 15.36% (CI: 12.57-18.68) of all COVID-19 cases, irrespective of their DM status. The mortality rate was 9.26% among non-diabetic patients, 10.59% among patients with COVID-19 associated hyperglycemia, 16.03% among known DM patients, and 24.96% among COVID-19 associated DM patients. The overall occurrence of adverse events was 20.52% (CI: 14.21-28.70) among COVID-19 patients in the included studies, 15.29% among non-diabetic patients, 20.41% among patients with COVID-19 associated hyperglycemia, 20.69% among known DM patients, and 45.85% among new-onset DM. Meta-regression showed an increasing rate of mortality among new hyperglycemic patients, known diabetics, and new-onset DM patients in comparison to those without diabetes.CONCLUSIONA significantly higher rate of new onset DM and hyperglycemia was observed. Higher mortality rates and adverse events were seen in patients with new-onset DM and hyperglycemia than in the non-diabetic population.     

Remdesivir for the treatment of COVID-19: a systematic review and meta-analysis

BackgroundThe benefits of remdesivir in the treatment of hospitalized patients with COVID-19 remain debated with the National Institutes of Health and the World Health Organization providing contradictory recommendations for and against use.ObjectivesTo evaluate the role of remdesivir for hospitalized inpatients as a function of oxygen requirements.Data sourcesBeginning with our prior systematic review, we searched MEDLINE using PubMed from 15 January 2021 through 5 May 2022.Study eligibility criteriaRandomised controlled trials; all languages.ParticipantsAll hospitalized adults with COVID-19.InterventionsRemdesivir, in comparison to either placebo, or standard of care.Assessment of risk of biasWe used the ROB-2 criteria.Methods of data synthesisThe primary outcome was mortality, stratified by oxygen use (none, supplemental oxygen without mechanical ventilation, and mechanical ventilation). We conducted a frequentist random effects meta-analysis on the risk ratio scale and, to contextualize the probabilistic benefits, we also performed a Bayesian random effects meta-analysis on the risk difference scale. A ≥1% absolute risk reduction was considered clinically important.ResultsWe identified eight randomized trials, totaling 10 751 participants. The risk ratio for mortality comparing remdesivir vs. control was 0.77 (95% CI, 0.5–1.19) in the patients who did not require supplemental oxygen; 0.89 (95% CI, 0.79–0.99) for nonventilated patients requiring oxygen; and 1.08 (95% CI, 0.88–1.31) in the setting of mechanical ventilation. Using neutral priors, the probabilities that remdesivir reduces mortality were 76.8%, 93.8%, and 14.7%, respectively. The probability that remdesivir reduced mortality by ≥ 1% was 77.4% for nonventilated patients requiring oxygen.ConclusionsBased on this meta-analysis, there is a high probability that remdesivir reduces mortality for nonventilated patients with COVID-19 requiring supplemental oxygen therapy. Treatment guidelines should be re-evaluated.     

Big data driven COVID-19 pandemic crisis management: potential approach for global health

IntroductionInformation has the power to protect against unexpected events and control any crisis such as the COVID-19 pandemic. Since COVID-19 has already rapidly spread all over the world, only technology-driven data management can provide accurate information to manage the crisis. This study aims to explore the potential of big data technologies for controlling COVID-19 transmission and managing it effectively.MethodsA systematic review guided by PRISMA guidelines has been performed to obtain the key elements.ResultsThis study identified the thirty-two most relevant documents for qualitative analysis. This study also reveals 10 possible sources and 8 key applications of big data for analyzing the virus infection trend, transmission pattern, virus association, and differences of genetic modifications. It also explores several limitations of big data usage including unethical use, privacy, and exploitative use of data.ConclusionsThe findings of the study will provide new insight and help policymakers and administrators to develop data-driven initiatives to tackle and manage the COVID-19 crisis.     

Current systematic reviews and meta-analyses of COVID-19

BACKGROUNDCoronavirus disease 2019 (COVID-19) has left a significant impact on the world''s health, economic and political systems; as of November 20, 2020, more than 57 million people have been infected worldwide, with over 1.3 million deaths. While the global spotlight is currently focused on combating this pandemic through means ranging from finding a treatment among existing therapeutic agents to inventing a vaccine that can aid in halting the further loss of life.AIMTo collect all systematic reviews and meta-analyses published related to COVID-19 to better identify available evidence, highlight gaps in knowledge, and elucidate further meta-analyses and umbrella reviews that are yet to be performed.METHODSWe explored studies based on systematic reviews and meta-analyses with the key-terms, including severe acute respiratory syndrome (SARS), SARS virus, coronavirus disease, COVID-19, and SARS coronavirus-2. The included studies were extracted from Embase, Medline, and Cochrane databases. The publication timeframe of included studies ranged between January 01, 2020, to October 30, 2020. Studies that were published in languages other than English were not considered for this systematic review. The finalized full-text articles are freely accessible in the public domain.RESULTSSearching Embase, Medline, and Cochrane databases resulted in 1906, 669, and 19 results, respectively, that comprised 2594 studies. 515 duplicates were subsequently removed, leaving 2079 studies. The inclusion criteria were systematic reviews or meta-analyses. 860 results were excluded for being a review article, scope review, rapid review, panel review, or guideline that produced a total of 1219 studies. After screening articles were categorized, the included articles were put into main groups of clinical presentation, epidemiology, screening and diagnosis, severity assessment, special populations, and treatment. Subsequently, there was a second subclassification into the following groups: gastrointestinal, cardiovascular, neurological, stroke, thrombosis, anosmia and dysgeusia, ocular manifestations, nephrology, cutaneous manifestations, D-dimer, lymphocyte, anticoagulation, antivirals, convalescent plasma, immunosuppressants, corticosteroids, hydroxychloroquine, renin-angiotensin-aldosterone system, technology, diabetes mellitus, obesity, pregnancy, children, mental health_, smoking, cancer, and transplant.CONCLUSIONAmong the included articles, it is clear that further research is needed regarding treatment options and vaccines. With more studies, data will be less heterogeneous, and statistical analysis can be better applied to provide more robust clinical evidence. This study was not designed to give recommendations regarding the management of COVID-19.     

Chest CT abnormalities in COVID-19: a systematic review

Computed tomography (CT) of the chest is one of the main diagnositic tools for coronavirus disease 2019 (COVID-19) infection. To document the chest CT findings in patients with confirmed COVID-19 and their association with the clinical severity, we searched related literatures through PubMed, MEDLINE, Embase, Web of Science (inception to May 4, 2020) and reviewed reference lists of previous systematic reviews. A total of 31 case reports (3768 patients) on CT findings of COVID-19 were included. The most common comorbid conditions were hypertension (18.4%) and diabetes mellitus (8.3%). The most common symptom was fever (78.7%), followed by cough (60.2%). It took an average of 5.6 days from symptom onset to admission. The most common chest CT finding was vascular enlargement (84.8%), followed by ground-glass opacity (GGO) (60.1%), air-bronchogram (47.8%), and consolidation (41.4%). Most lung lesions were located in the lung periphery (72.2%) and involved bilateral lung (76%). Most patients showed normal range of laboratory findings such as white blood cell count (96.4%) and lymphocyte (87.2%). Compared to previous published meta-analyses, our study is the first to summarize the different radiologic characteristics of chest CT in a total of 3768 COVID-19 patients by compiling case series studies. A comprehensive diagnostic approach should be adopted for patients with known COVID-19, suspected cases, and for exposed individuals.     

Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19

The role of clinical laboratory data in the differential diagnosis of the severe forms of COVID-19 has not been definitely established. The aim of this study was to look for the warning index in severe COVID-19 patients. We investigated 43 adult patients with COVID-19. The patients were classified into mild group (28 patients) and severe group (15 patients). A comparison of the hematological parameters between the mild and severe groups showed significant differences in interleukin-6 (IL-6), d -dimer (d -D), glucose, thrombin time, fibrinogen, and C-reactive protein (P < .05). The optimal threshold and area under the receiver operator characteristic curve (ROC) of IL-6 were 24.3 and 0.795 µg/L, respectively, while those of d -D were 0.28 and 0.750 µg/L, respectively. The area under the ROC curve of IL-6 combined with d -D was 0.840. The specificity of predicting the severity of COVID-19 during IL-6 and d -D tandem testing was up to 93.3%, while the sensitivity of IL-6 and d -D by parallel test in the severe COVID-19 was 96.4%. IL-6 and d -D were closely related to the occurrence of severe COVID-19 in the adult patients, and their combined detection had the highest specificity and sensitivity for early prediction of the severity of COVID-19 patients, which has important clinical value.     

Finding disease genes: a fast and flexible approach for analyzing high-throughput data

Linkage disequilibrium (LD) is the non-random distribution of alleles across the genome, and it can create serious problems for modern linkage studies. In particular, computational feasibility is often obtained at the expense of power, precision, and/or accuracy. In our new approach, we combine linkage results over multiple marker subsets to provide fast, efficient, and robust analyses, without compromising power, precision, or accuracy. Allele frequencies and LD in the densely spaced markers are used to construct subsamples that are highly informative for linkage. We have tested our approach extensively, and implemented it in the software package EAGLET (Efficient Analysis of Genetic Linkage: Estimation and Testing). Relative to several commonly used methods we show that EAGLET has increased power to detect disease genes across a range of trait models, LD patterns, and family structures using both simulated and real data. In particular, when the underlying LD pattern is derived from real data, we find that EAGLET outperforms several commonly used linkage methods. In-depth analysis of family data, simulated with linkage and under the real-data derived LD pattern, showed that EAGLET had 78.1% power to detect a dominant disease with incomplete penetrance, whereas the method that uses one marker per cM had 69.7% power, and the cluster-based approach implemented in MERLIN had 76.7% power. In this same setting, EAGLET was three times faster than MERLIN, and it narrowed the MERLIN-based confidence interval for trait location by 29%. Overall, EAGLET gives researchers a fast, accurate, and powerful new tool for analyzing high-throughput linkage data, and large extended families are easily accommodated.     

LabSystem Gen, a tool for structuring and analyzing genetic data in histocompatibility laboratories

Analysis of HLA data involves queries on web portals, whose search parameters are data stored in laboratories' databases. In order to automate these queries, one approach is to structure laboratory data into a database and to develop bioinformatic tools to perform the data mapping. In this context, we developed the LabSystem Gen tool that allows users to create a Laboratory Information System, without programming. Additionally we implemented a framework that provides bioinformatic tools, transparent access to public HLA (human leukocyte antigen) information resources. We demonstrated the LabSystemGen system by implementing BMDdb, which is a LIMS that manages data of recipients and donors of organ transplant.     

Effectiveness of favipiravir in COVID-19: a live systematic review

We performed a systematic review and meta-analysis for the effectiveness of Favipiravir on the fatality and the requirement of mechanical ventilation for the treatment of moderate to severe COVID-19 patients. We searched available literature and reported it by using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Until June 1, 2021, we searched PubMed, bioRxiv, medRxiv, ClinicalTrials.gov, Cochrane Central Register of Controlled Trials (CENTRAL), and Google Scholar by using the keywords “Favipiravir” and terms synonymous with COVID-19. Studies for Favipiravir treatment compared to standard of care among moderate and severe COVID-19 patients were included. Risk of bias assessment was performed using Revised Cochrane risk of bias tool for randomized trials (RoB 2) and ROBINS-I assessment tool for non-randomized studies. We defined the outcome measures as fatality and requirement for mechanical ventilation. A total of 2702 studies were identified and 12 clinical trials with 1636 patients were analyzed. Nine out of 12 studies were randomized controlled trials. Among the randomized studies, one study has low risk of bias, six studies have moderate risk of bias, and 2 studies have high risk of bias. Observational studies were identified as having moderate risk of bias and non-randomized study was found to have serious risk of bias. Our meta-analysis did not reveal any significant difference between the intervention and the comparator on fatality rate (OR 1.11, 95% CI 0.64–1.94) and mechanical ventilation requirement (OR 0.50, 95% CI 0.13–1.95). There is no significant difference in fatality rate and mechanical ventilation requirement between Favipiravir treatment and the standard of care in moderate and severe COVID-19 patients.

     

Exploring the ethics of genetic prioritisation for COVID-19 vaccines

There is evidence to suggest that host genomic factors may account for disease response variability in COVID-19 infection. In this paper, we consider if and how host genomics should influence decisions about vaccine allocation. Three potential host genetic factors are explored: vulnerability to infection, resistance to infection, and increased infectivity. We argue for the prioritisation of the genetically vulnerable in vaccination schemes, and evaluate the potential for ethical de-prioritisation of individuals with genetic markers for resistance. Lastly, we discuss ethical prioritisation of individuals with genetic markers for increased infectivity (those more likely to spread COVID-19).Subject terms: Health policy, Ethics     

An evolving approach to the laboratory assessment of COVID-19

As the 2019 novel coronavirus disease (COVID-19) outbreak has evolved in each country, the approach to the laboratory assessment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has had to evolve as well. This review addresses the evolving approach to the laboratory assessment of COVID-19 and discusses how algorithms for testing have been driven, in part, by the demand for testing overwhelming the capacity to accomplish such testing. This review focused on testing in the USA, as this testing is evolving, whereas in China and other countries such as South Korea testing is widely available and includes both molecular testing for SARS-CoV-2 as well as serological testing using both enzyme-linked immunosorbent assay methodology and lateral flow immunoassay methodology. Although commercial testing systems are becoming available, there will likely be insufficient numbers of such tests due to high demand. Serological testing will be the next testing issue as the COVID-19 begins to subside. This will allow immunity testing as well as will allow the parameters of the COVID-19 outbreak to be defined.     

Adverse reactions to COVID-19 vaccines: A practical approach

COVID-19-related mortality in high-risk individuals is substantial and current treatment options are limited. There is convincing evidence that the COVID-19 vaccines reduce the severity of infection and prevent deaths. Three COVID-19 vaccines are approved in the United Kingdom with many more in development. There are limited data on the triggers and mechanisms of anaphylaxis to these vaccines. We review the potential allergenic compounds in the COVID-19 vaccines and describe an innovative allergy support model for the vaccination hubs that allows most patients with severe allergy be immunized. Finally, we propose a practical algorithm for the investigations of anaphylaxis to these vaccines.     

An empirical survey on biobanking of human genetic material and data in six EU countries

Biobanks correspond to different situations: research and technological development, medical diagnosis or therapeutic activities. Their status is not clearly defined. We aimed to investigate human biobanking in Europe, particularly in relation to organisational, economic and ethical issues in various national contexts. Data from a survey in six EU countries (France, Germany, the Netherlands, Portugal, Spain and the UK) were collected as part of a European Research Project examining human and non-human biobanking (EUROGENBANK, coordinated by Professor JC Galloux). A total of 147 institutions concerned with biobanking of human samples and data were investigated by questionnaires and interviews. Most institutions surveyed belong to the public or private non-profit-making sectors, which have a key role in biobanking. This activity is increasing in all countries because few samples are discarded and genetic research is proliferating. Collections vary in size, many being small and only a few very large. Their purpose is often research, or research and healthcare, mostly in the context of disease studies. A specific budget is very rarely allocated to biobanking and costs are not often evaluated. Samples are usually provided free of charge and gifts and exchanges are the common rule. Good practice guidelines are generally followed and quality controls are performed but quality procedures are not always clearly explained. Associated data are usually computerised (identified or identifiable samples). Biobankers generally favour centralisation of data rather than of samples. Legal and ethical harmonisation within Europe is considered likely to facilitate international collaboration. We propose a series of recommendations and suggestions arising from the EUROGENBANK project.     

The interplay of post-acute COVID-19 syndrome and aging: a biological,clinical and public health approach

The post-acute COVID-19 syndrome (PACS) is characterized by the persistence of fluctuating symptoms over three months from the onset of the possible or confirmed COVID-19 acute phase. Current data suggests that at least 10% of people with previously documented infection may develop PACS, and up to 50–80% of prevalence is reported among survivors after hospital discharge. This viewpoint will discuss various aspects of PACS, particularly in older adults, with a specific hypothesis to describe PACS as the expression of a modified aging trajectory induced by SARS CoV-2. This hypothesis will be argued from biological, clinical and public health view, addressing three main questions: (i) does SARS-CoV-2-induced alterations in aging trajectories play a role in PACS?; (ii) do people with PACS face immuno-metabolic derangements that lead to increased susceptibility to age-related diseases?; (iii) is it possible to restore the healthy aging trajectory followed by the individual before pre-COVID?. A particular focus will be given to the well-being of people with PACS that could be assessed by the intrinsic capacity model and support the definition of the healthy aging trajectory.