Interleukin-6 inhibitors reduce mortality in coronavirus disease-2019: An individual patient data meta-analysis from randomized controlled trials

Age-related immune response disparities between adults and children with severe COVID-19: a case-control study in China

Background

Elucidation of immune response differences is critical for uncovering underlying mechanisms and developing potential intervention measures among adults and children with COVID-19.

Methods

In this retrospective study, we analyzed serum biochemical markers and cytokine profiles among adults and children with COVID-19 in the First People's Hospital of Chenzhou in Hunan, China from 1 December 2022 to 13 February 2023. A case-control study was conducted using propensity score matching (PSM) to mitigate possible confounding factors.

Results

The significant differences observed included lymphocyte exhaustion, an increased neutrophil-to-lymphocyte (NEU/LYM) ratio, high levels of C-reactive protein (CRP), and a cytokine storm, characterized by high levels of Th1 proinflammatory cytokines, including interleukin 1β (IL-1β), IL-6, IL-8, interferon type I (IFN-γ), and tumor necrosis factor (TNF-α) in the lung among severe adult COVID-19 patients. Additionally, systemic immune responses were observed in children with COVID-19.

Conclusion

Significant differences in immune responses between adults and children with COVID-19 highlight the different mechanisms and potential intervention measures of COVID-19.

Impact of metabolic dysfunction-associated steatotic liver disease on COVID-19 hospitalizations: A propensity-matched analysis of the United States

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD), formally known as nonalcoholic fatty liver disease, is the most common chronic liver disease in the United States. Patients with MASLD have been reported to be at a higher risk of developing severe coronavirus disease 2019 (COVID-19) and death. However, most studies are single-center studies, and nationwide data in the United States is lacking.

AIM

To study the influence of MASLD on COVID-19 hospitalizations during the initial phase of the pandemic.

METHODS

We retrospectively analyzed the 2020 National Inpatient Sample (NIS) database to identify primary COVID-19 hospitalizations based on an underlying diagnosis of MASLD. A matched comparison cohort of COVID-19 hospitalizations without MASLD was identified from NIS after 1: N propensity score matching based on gender, race, and comorbidities, including hypertension, heart failure, diabetes, and cirrhosis. The primary outcomes included inpatient mortality, length of stay, and hospitalization costs. Secondary outcomes included the prevalence of systemic complications.

RESULTS

A total of 2210 hospitalizations with MASLD were matched to 2210 hospitalizations without MASLD, with a good comorbidity balance. Overall, there was a higher prevalence of severe disease with more intensive care unit admissions (9.5% vs 7.2%, P = 0.007), mechanical ventilation (7.2% vs 5.7%, P = 0.03), and septic shock (5.2% vs 2.7%, P <0.001) in the MASLD cohort than in the non-MASLD cohort. However, there was no difference in mortality (8.6% vs 10%, P = 0.49), length of stay (5 d vs 5 d, P = 0.25), and hospitalization costs (42081.5 $ vs 38614$, P = 0.15) between the MASLD and non-MASLD cohorts.

CONCLUSION

The presence of MAFLD with or without liver cirrhosis was not associated with increased mortality in COVID-19 hospitalizations; however, there was an increased incidence of severe COVID-19 infection. This data (2020) predates the availability of COVID-19 vaccines, and many MASLD patients have since been vaccinated. It will be interesting to see if these trends are present in the subsequent years of the pandemic.

Placebo effects on all-cause mortality of patients with COVID-19 in randomized controlled trials of interleukin 6 antagonists: A systematic review and network meta-analysis

AIM

Many randomized controlled trials (RCTs) have investigated the use of interleukin 6 antagonists for the treatment of coronavirus disease 2019 (COVID-19), yielding inconsistent results. This network meta-analysis (NMA) aimed to identify the source of these inconsistent results by reassessing whether participants treated with standard of care (SoC) plus placebo have different all-cause mortality from those treated with SoC alone and to reevaluate the efficacy of interleukin 6 antagonists in the treatment of COVID-19.

METHODS

We conducted a systematic search for relevant RCTs from the inception of electronic databases through 1 September 2022. The primary outcome was all-cause mortality. The secondary outcomes were the incidences of major medical events, secondary infections, all-cause discontinuation, and serious adverse events.

RESULTS

The results of NMA of 33 RCTs showed that patients with COVID-19 treated with SoC plus placebo had lower odds of all-cause mortality than those who received SoC alone (OR, 0.75 [95% confidence interval, 0.58-0.97]). This finding remained consistent after excluding studies with no incident deaths. In addition, when we consider the impact of the widely promoted COVID-19 vaccination and newly developed antiviral treatment strategy, the results from the analysis of the RCT published in 2021 and 2022 remained similar.

CONCLUSION

These findings suggest the potential influence of placebo effects on the treatment outcomes of COVID-19 in RCTs. When evaluating the efficacy of treatment strategies for COVID-19, it is crucial to consider the use of placebo in the design of clinical trials.

Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses

BACKGROUND

Individual participant data meta-analyses (IPD-MAs), which involve harmonising and analysing participant-level data from related studies, provide several advantages over aggregate data meta-analyses, which pool study-level findings. IPD-MAs are especially important for building and evaluating diagnostic and prognostic models, making them an important tool for informing the research and public health responses to COVID-19.

METHODS

We conducted a rapid systematic review of protocols and publications from planned, ongoing, or completed COVID-19-related IPD-MAs to identify areas of overlap and maximise data request and harmonisation efforts. We searched four databases using a combination of text and MeSH terms. Two independent reviewers determined eligibility at the title-abstract and full-text stages. Data were extracted by one reviewer into a pretested data extraction form and subsequently reviewed by a second reviewer. Data were analysed using a narrative synthesis approach. A formal risk of bias assessment was not conducted.

RESULTS

We identified 31 COVID-19-related IPD-MAs, including five living IPD-MAs and ten IPD-MAs that limited their inference to published data (e.g., case reports). We found overlap in study designs, populations, exposures, and outcomes of interest. For example, 26 IPD-MAs included RCTs; 17 IPD-MAs were limited to hospitalised patients. Sixteen IPD-MAs focused on evaluating medical treatments, including six IPD-MAs for antivirals, four on antibodies, and two that evaluated convalescent plasma.

CONCLUSIONS

Collaboration across related IPD-MAs can leverage limited resources and expertise by expediting the creation of cross-study participant-level data datasets, which can, in turn, fast-track evidence synthesis for the improved diagnosis and treatment of COVID-19.

TRIAL REGISTRATION

10.17605/OSF.IO/93GF2.

COVID-19 and the Genetics of Inflammation

OBJECTIVE

Interindividual variability in the clinical progression of COVID-19 may be explained by host genetics. Emerging literature supports a potential inherited predisposition to severe forms of COVID-19. Demographic and inflammatory characteristics of COVID-19 suggest that acquired hematologic mutations leading to clonal hematopoiesis (CH) may further increase vulnerability to adverse sequelae. This review summarizes the available literature examining genetic predispositions to severe COVID-19 and describes how these findings could eventually be used to improve its clinical management.

DATA SOURCES

A PubMed literature search was performed.

STUDY SELECTION

Studies examining the significance of inherited genetic variation or acquired CH mutations in severe COVID-19 were selected for inclusion.

DATA EXTRACTION

Relevant genetic association data and aspects of study design were qualitatively assessed and narratively synthesized.

DATA SYNTHESIS

Genetic variants affecting inflammatory responses may increase susceptibility to severe COVID-19. Genome-wide association studies and candidate gene approaches have identified a list of inherited mutations, which likely alter cytokine and interferon secretion, and lung-specific mechanisms of immunity in COVID-19. The potential role of CH in COVID-19 is more uncertain at present; however, the available evidence suggests that the various types of acquired mutations and their differential influence on immune cell function must be carefully considered.

CONCLUSIONS

The current literature supports the hypothesis that host genetic factors affect vulnerability to severe COVID-19. Further research is required to confirm the full scope of relevant variants and the causal mechanisms underlying these associations. Clinical approaches, which consider the genetic basis of interindividual variability in COVID-19 and potentially other causes of critical illness, could optimize hospital resource allocation, predict responsiveness to treatment, identify more efficacious drug targets, and ultimately improve outcomes.

COVID-19 and MAFLD/NAFLD: An updated review

The COVID-19 pandemic is ongoing and places a substantial burden on healthcare systems worldwide. As we further shed light on different disease characteristics, we identify more and more groups of people at higher risk of poor COVID-19 outcomes. Metabolic-associated fatty liver disease (MAFLD) (previously non-alcoholic fatty liver disease or NAFLD) is a common metabolic disorder characterized by fat accumulation and liver fibrosis. Given its close correlation with metabolic syndrome, an established risk factor for severe COVID-19, it is necessary to investigate its interplay with the novel coronavirus. In this study, we review the available data on COVID-19 prognosis, treatment and prevention options in patients with MAFLD, and the effect that the disease and the pandemic have on MAFLD care. Furthermore, we point out the gaps in the current literature to accentuate the work that needs to be done to improve MAFLD care during the pandemic and beyond.

Severity predictors of COVID-19 in SARS-CoV-2 variant, delta and omicron period; single center study

Background

The outcomes of coronavirus disease 2019 (COVID-19) treatment have improved due to vaccination and the establishment of better treatment regimens. However, the emergence of variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, and the corresponding changes in the characteristics of the disease present new challenges in patient management. This study aimed to analyze predictors of COVID-19 severity caused by the delta and omicron variants of SARS-CoV-2.

Methods

We retrospectively analyzed the data of patients who were admitted for COVID-19 at Yokohama City University Hospital from August 2021 to March 2022.

Results

A total of 141 patients were included in this study. Of these, 91 had moderate COVID-19, whereas 50 had severe COVID-19. There were significant differences in sex, vaccination status, dyspnea, sore throat symptoms, and body mass index (BMI) (p <0.0001, p <0.001, p <0.001, p = 0.02, p< 0.0001, respectively) between the moderate and severe COVID-19 groups. Regarding comorbidities, smoking habit and renal dysfunction were significantly different between the two groups (p = 0.007 and p = 0.01, respectively). Regarding laboratory data, only LDH level on the first day of hospitalization was significantly different between the two groups (p<0.001). Multiple logistic regression analysis revealed that time from the onset of COVID-19 to hospitalization, BMI, smoking habit, and LDH level were significantly different between the two groups (p<0.03, p = 0.039, p = 0.008, p<0.001, respectively). The cut-off value for the time from onset of COVID-19 to hospitalization was four days (sensitivity, 0.73; specificity, 0.70).

Conclusions

Time from the onset of COVID-19 to hospitalization is the most important factor in the prevention of the aggravation of COVID-19 caused by the delta and omicron SARS-CoV-2 variants. Appropriate medical management within four days after the onset of COVID-19 is essential for preventing the progression of COVID-19, especially in patients with smoking habits.

Network Pharmacology and Bioinformatics Analysis Identifies Potential Therapeutic Targets of Paxlovid Against LUAD/COVID-19

Background

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a pandemic in many countries around the world. The virus is highly contagious and has a high fatality rate. Lung adenocarcinoma (LUAD) patients may have higher susceptibility and mortality to COVID-19. While Paxlovid is the first oral drug approved by the U.S. Food and Drug Administration (FDA) for COVID-19, its specific drug mechanism for lung cancer patients infected with COVID-19 remains to be further studied.

Methods

COVID-19 related genes were obtained from NCBI, GeneCards, and KEGG, and then the transcriptome data for LUAD was downloaded from TCGA. The drug targets of Paxlovid were revealed through BATMAN-TCM, DrugBank, SwissTargetPrediction, and TargetNet. The genes related to susceptibility to COVID-19 in LUAD patients were obtained through differential analysis. The interaction of LUAD/COVID-19 related genes was evaluated and displayed by STRING, and a COX risk regression model was established to screen and evaluate the correlation between genes and clinical characteristics. The Venn diagram was drawn to select the candidate targets of Paxlovid against LUAD/COVID-19, and the functional analysis of the target genes was performed using KEGG and GO enrichment analysis. Finally, Cytoscape was used to screen and visualize the Hub Gene, and Autodock was used for molecular docking between the drug and the target.

Result

Bioinformatics analysis was performed by combining COVID-19-related genes with the gene expression and clinical data of LUAD, including analysis of prognosis-related genes, survival rate, and hub genes screened out by the prognosis model. The key targets of Paxlovid against LUAD/COVID-19 were obtained through network pharmacology, the most important targets include IL6, IL12B, LBP. Furthermore, pathway analysis showed that Paxlovid modulates the IL-17 signaling pathway, the cytokine-cytokine receptor interaction, during LUAD/COVID-19 treatment.

Conclusions

Based on bioinformatics and network pharmacology, the prognostic signature of LUAD/COVID-19 patients was screened. And identified the potential therapeutic targets and molecular pathways of Paxlovid Paxlovid in the treatment of LUAD/COVID. As promising features, prognostic signatures and therapeutic targets shed light on improving the personalized management of patients with LUAD.