Clinical characteristics and related risk factors of disease severity in 101 COVID-19 patients hospitalized in Wuhan, China

Modeling "Two-Hit" Severe Pneumonia in Mice: Pathological Characteristics and Mechanistic Studies

Severe pneumonia is one of the most common critical diseases in clinical practice. Existing models for severe pneumonia have limitations, leading to limited clinical translation. In this study, a two-hit severe pneumonia mouse model was established by inducing primary pneumonia through intratracheal instillation of 800 μg lipopolysaccharide (LPS), followed by intraperitoneal injection of 10 mg/kg LPS. The effectiveness of various inflammatory indicators and the lung tissue damage during the time course of this model were confirmed and evaluated. At 3 h post two-hit, the IL-6, TNF-α levels in peripheral blood and bronchoalveolar lavage fluid (BALF), and the white blood cells, neutrophils, and lymphocytes in BALF notably exhibited the most pronounced elevation. At 12 h post two-hit, the white blood cells and neutrophils in peripheral blood significantly increased, accompanied by notable alterations in splenic immune cells and worsened pulmonary histopathological damage. Transcriptomics of lung tissue, microbiota analysis of lung and gut, as well as plasma metabolomics analyses further indicated changes in transcriptional profiles, microbial composition, and metabolites due to the two-hit modeling. These results validate that the two-hit model mimics the clinical presentation of severe pneumonia and serves as a robust experimental tool for studying the pathogenesis of severe pneumonia and developing and assessing treatment strategies.

Exploring the Clinical Features, Management of Hypertension, and Predictors of Severity in Hospitalized Hypertensive COVID-19 Patients

Background Hypertension significantly contributes to the severity, prolonged hospitalization, the need for intensive care, and mortality of COVID-19 patients. However, the data is still evolving. This study investigated the predictors of severity among hypertensive COVID-19 patients. Methodology This cohort study included 333 hospitalized hypertensive COVID-19 patients at the Indus Hospital, Karachi, Pakistan, from April 2021 to October 2021. The study evaluated the clinical features, antihypertensive therapy, and predictors of severity. A multivariable binary logistic regression model was used to determine severity predictors using IBM SPSS Statistics for Windows, Version 27.0 (Released 2020; IBM Corp., Armonk, NY, USA). Results The majority of hypertensive COVID-19 patients were females (54.7%), aged <65 years (55.8%), and coexisted with diabetes mellitus (56.5%). The independent predictors of severity were male (aOR 2.65, 95% CI, 1.08-6.51; p < 0.033), fever (aOR 3.52, 95% CI, 1.24-9.92; p = 0.017), shortness of breath (aOR 4.49, 95% CI, 1.73-11.63; p = 0.002), oxygen saturation (<90%) (aOR 87.39, 95% CI, 19.15-398.75; p < 0.001), and D-dimer (>0.5 mcg/ml) (aOR 3.03, 95% CI, 1.19-7.71; p = 0.020). Conclusions Our study concluded that males with fever before admission, shortness of breath, lower oxygen saturation, and elevated D-dimer are the predictors of severity among hypertensive COVID-19 patients.

Elucidating the anti-inflammatory activity of platycodins in lung inflammation through pulmonary distribution dynamics and grey relational analysis of cytokines

ETHNOPHARMACOLOGICAL RELEVANCE

Platycodonis Radix (PR) is a traditional herbal remedy used to prevent and treat lung inflammation, and platycodins are speculated to be the major active constituents. However, concrete experimental verification for this assertion remains absent thus far.

AIM OF THE STUDY

This study aims to compare the pulmonary distribution dynamics of five platycodins and analyze their effects on cytokines. Through the grey relational analysis (GRA) between pulmonary active components and cytokines, the study ascertains platycodins as the potential effective component against lung inflammation.

MATERIALS AND METHODS

A rat lung inflammation model was created using lipopolysaccharides (LPS). Pulmonary distribution dynamics were analyzed via LC-MS/MS. Cytokine changes and distribution patterns in lung tissues were studied by multi-factor reagent kit. GRA was applied to determine correlations between pulmonary components and cytokines. Finally, the anti-inflammatory properties of platycodins were further studied using LPS-induced BEAS-2B cells in vitro.

RESULTS

The results showed that five platycodins (Platycodin D, Platycodin D3, Deapio Platycodin D, 3-O-β-D-Glucopyranosyl Platycodigenin, and Platycodigenin) featured fast absorption rate, short time to peak, and slow metabolism rate. The pulmonary distribution dynamics were significantly affected within 2 h after LPS modeling. At the same time, PR altered the relationships among different cytokines induced by LPS stimulation, particularly inflammatory cytokines IL-6 and IFN-γ. The GRA results indicated good correlation between the pulmonary distribution dynamics of the five platycodins components and the changing patterns of cytokine levels, with Platycodin D3 contributing the most. Additionally, Platycodin D3 exhibited a protective role against LPS-induced inflammation by reducing the production of pro-inflammatory mediators such as IL-1β, IL-8, and ROS, as well as increasing the expression of the anti-inflammatory mediator IL-10.

CONCLUSIONS

Platycodins are the main anti-inflammatory agents in PR and there is a good correlation with cytokines. This contributes to the anti-pneumonia effect of PR.

The laboratory parameters in predicting the severity and death of COVID-19 patients: Future pandemic readiness strategies

The range of clinical manifestations associated with the infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encompasses a broad spectrum, ranging from flu-like symptoms to the occurrence of multiple organ failure and death. The severity of the coronavirus disease 2019 (COVID-19) is categorized based on clinical presentation and is divided into three distinct levels of severity identified as non-severe, severe, and critical. Although individuals of all age groups are susceptible to SARS-CoV-2 infection, middle-aged and older adults are more frequently impacted, with the latter being more likely to develop severe illness. Various laboratory characteristics observed in hospitalized COVID-19 patients have been correlated with adverse outcomes. These include elevated levels of D-dimer, liver enzymes, lactate dehydrogenase, C-reactive protein, ferritin, prothrombin time, and troponin, as well as decreased lymphocyte and platelets counts. This review investigated the relationship between baseline clinical characteristics, initial laboratory parameters upon hospital admission, and the severity of illness and mortality rates among COVID-19 patients. Although the COVID-19 pandemic has concluded, understanding the laboratory predictors of virus severity and mortality remains crucial, and examining these predictors can have long-term effects. Such insights can help healthcare systems manage resources more effectively and deliver timely and appropriate care by identifying and targeting high-risk individuals. This knowledge can also help us better prepare for future pandemics. By examining these predictors, we can take steps to protect public health and mitigate the impact of future pandemics.

Impact of vaccination on morbidity and mortality in adults hospitalized with COVID-19 during the omicron wave in the Jazan Region, Saudi Arabia

OBJECTIVES

To evaluate the impact of coronavirus disease-19 (COVID-19) vaccination on morbidity and mortality in adults hospitalized with COVID-19 during the omicron wave in the Jazan Region, Saudi Arabia.

METHODS

A 6-month record-based historical prospective study enrolled COVID-19 adult patients admitted between January and June 2022. Individuals were classified into 3 groups according to their immunity status (immunized, partially immunized, and not immunized). Death, intensive care unit (ICU) admission, and mechanical ventilation were identified as the primary outcomes, collectively referred to as "serious outcomes". On the other hand, the length of hospital stays longer than 5 days was categorized as a secondary outcome. Multiple logistic regression analysis was used to evaluate independent factors and the relationship between the outcomes and vaccination status.

RESULTS

Among the 634 COVID-19 patients admitted to Jazan hospitals, 46.4% were fully immunized, 19.7% were partially immunized, and 33.9% were not immunized. Not being immunized was significantly associated with ICU admission (odds ratio [OR]=1.91, 95% confidence interval [CI]: [1.17-3.11]; p=0.009), mechanical ventilation (OR=2.11, 95% CI: [1.25-3.56]; p=0.005), increased length of hospital stays (OR=1.79, 95% CI: [1.24-2.59]; p=0.002), and death (OR=3.03, 95% CI: [1.85-4.98]; p<0.001).

CONCLUSION

Our study underscores the importance of a comprehensive approach for managing COVID-19 patients that includes vaccination against the disease.

Epidemiological and clinical features of SARS-CoV-2 Omicron variant infection in Quanzhou, Fujian province: a retrospective study

Epidemiological and clinical data of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (BA.2) admitted to three designated hospitals in Quanzhou City, Fujian Province, China, were collected and analyzed. Overall, 2,541 patients infected with BA.2, comprising 1,060 asymptomatic, 1,287 mild, and 194 moderate infections, were enrolled. The percentage of moderate infections was higher in patients aged ≥ 60 years than in those aged < 18 years and 18-59 years. The median hospitalization duration was 17 days. Among the 2,541 patients, 43.52% had a clear history of close contact. The vaccination rate was 87.92%, and the percentage of asymptomatic infections was higher in vaccinated than in unvaccinated patients. Moreover, patients with underlying diseases, including hypertension and diabetes mellitus, had more moderate infections than those without underlying diseases. The three most common clinical manifestations were fever, dry cough, and sore throat. The albumin-to-globulin (A/G) ratio and lymphocyte count decreased in cases with mild and moderate infections, while procalcitonin, erythrocyte sedimentation rate, interleukin-6, D-dimer, and C4 levels increased. Advanced age, non-vaccination, and underlying comorbid diseases were high-risk factors for disease progression in patients. However, dynamic monitoring of blood routine parameters, A/G ratio, and inflammatory indicators facilitated the prediction of disease progression.

Clinical and Epidemiological Characteristics of Hospitalized COVID-19 Patients in an Isolation Centre in South-West Nigeria

INTRODUCTION

The clinical presentation of coronavirus disease 2019 (COVID-19) can vary widely, and while the primary infection involves the respiratory system, other organs can also be affected. This study presents the clinical and epidemiological characteristics of hospitalized COVID-19 patients in a tertiary hospital in Ado Ekiti, South-West Nigeria.

MATERIALS AND METHODS

This is a retrospective study involving COVID-19 patients admitted to the isolation ward between August 2020 and January 2021. The data used for this study was obtained from the patient's medical record, which includes demographic characteristics, clinical presentation, baseline co-morbidities, and laboratory investigations.

RESULTS

The average age of the patients was 60.3 years, and more than two-thirds were male. The most common symptoms were fever, shortness of breath, cough, and tiredness. Comorbidities identified among the patients included diabetes mellitus, heart disease, obesity, and chronic kidney disease. The most common radiological findings were bilateral homogeneous patchy opacities and peripheral fluffy infiltrates. The overall mortality rate was 21.9%, with 13 deaths in patients with severe disease. Age and duration of admission were found to be significant predictors of death.

CONCLUSION

The results of this study provide valuable insights into the clinical presentation of COVID-19 in Nigeria and may guide future management strategies for similar infections.

Differences in the severity and mortality risk factors for patients hospitalized for COVID-19 pneumonia between the early wave and the very late stage of the pandemic

Background

Since China's dynamic zero-COVID policy is cancelled on December 7, 2022, the rapidly growing number of patients has brought a major public health challenge. This study aimed to assess whether there were differences in the severity and mortality risk factors for patients hospitalized for COVID-19 pneumonia between the early wave and the very late stage of the pandemic.

Methods

A retrospective cross-sectional study was carried out using data from 223 hospitalized patients diagnosed with COVID-19 pneumonia during the Omicron surge in Xi'an People's Hospital (Xi'an Fourth Hospital) from December 8, 2022, to January 31, 2023. Univariable and multivariable logistic regression analyses were used to identify potential risk factors associated with the severity and mortality of COVID-19 pneumonia during the first wave of the pandemic after the dynamic zero-COVID policy was retracted. Differences in the severity and mortality risk factors were assessed at different stages of the pandemic, mainly from demographic, clinical manifestation, laboratory tests and radiological findings of patients on admission.

Results

The mean age of the 223 participants was 71.2 ± 17.4. Compared with the patients in the initial stage of the pandemic, the most common manifestation among patients in this study was cough (90.6%), rather than fever (79.4%). Different from the initial stage of the pandemic, older age, chest tightness, elevated neutrophil-to-lymphocyte ratio (NLR), decreased albumin (ALB) level and ground glass opacification (GGO) in radiological finding were identified as severity risk factors, instead of mortality risk factors for COVID-19 patients in the very late stage of the pandemic. Arterial partial pressure of oxygen/fraction of inspired oxygen (PaO2/FiO2) ≤300 mmHg, cardiovascular disease and laboratory findings including elevated levels of D-dimer, α-hydroxybutyrate dehydrogenase (α-HBDH), total bilirubin (TBIL), alanine aminotransferase (ALT), urea nitrogen (BUN), creatinine (CR), fasting blood glucose (FBG) and decreased platelet count (PLT) were still associated with mortality in the very late stage of the pandemic.

Conclusion

Monitoring continuously differences in the severity and mortality risk factors for COVID-19 patients between different stages of the pandemic could provide evidence for exploring uncharted territory in the coming post-pandemic era.

The clinical and immunological characteristics of COVID-19 patients with delayed SARS-CoV-2 virus clearance

BACKGROUND

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a great threat to human health. Some severe COVID-19 patients still carried detectable levels of SARS-CoV-2 even after prolonged intensive care unit treatment. However, the immunological features of these COVID-19 patients with delayed virus clearance (CDVC) are still unclear.

METHODS

We retrospectively reviewed the clinical and immunological data of 13 CDVC cases, who were admitted into one hospital in Wuhan from February to April 2020. These data were also compared to those of perished (n = 9) and recovered (n = 52) cases. The expression of the exhaustion marker PD-1 on circulating T cells of these patients was measured by flow cytometry.

RESULTS

High levels of serum interleukin-6 (IL-6), IL-1β, IL-8, as well as other inflammatory mediators, were seen in CDVC cases. Severe lymphopenia was observed in CDVC patients with the counts of total lymphocytes (0.9 × 109 /L), CD4+ T cells (0.35 × 109 /L), and CD8+ T cells (0.28 × 109 /L) below their corresponding lower limits of normal range. Similar to the perished group, CDVC cases have higher percentages of CD25+ Foxp3+ regulatory T cells (Treg) in circulation. Moreover, enhanced expression of the exhaustion marker PD-1 on CCR7- CD45RA+ effector, CCR7+ CD45RA- central memory, and CCR7- CD45RA- effector memory CD4+ and CD8+ T cells were also observed in CDVC cases.

CONCLUSION

CDVC patients still have SARS-CoV-2 and these cases manifest with severe clinical symptoms due to persistent inflammation. Augmentation of the frequency of circulating Treg, severe lymphopenia, and functional exhaustion of T cells might lead to inefficient clearance of SARS-CoV-2. Therefore, enhancing lymphocyte counts and reversing T-cell exhaustion might be key methods to boost immune responses and eliminate SARS-CoV-2 in CDVC patients.

Immunosuppressive dead cell as lung-targeting vehicle and cytokine absorption material for cytokine storm attenuation of pneumonia

Effectively controlling cytokine storm is important to reduce the mortality of severe pneumonia. In this work a bio-functional dead cell was engineered by one-time quick shock of live immune cells in liquid nitrogen, and the obtained immunosuppressive dead cell could server as both lung-targeting vehicle and cytokine absorption material. After loading the anti-inflammatory drugs of dexamethasone (DEX) and baicalin (BAI), the drug-loaded dead cell (DEX&BAI/Dead cell) could first passively target to the lung after intravenous administration and quickly release the drugs under high shearing stress of pulmonary capillaries, realizing drug enrichment in the lung. Then, the immunosuppressive dead cell acted as the camouflage of normal immune cells with various cytokine receptors exposing on their surface, to "capture" the cytokines and further reduce the state of inflammation. With above formulation design, a synergic anti-inflammatory effect between drugs and carrier could be achieved. In a lipopolysaccharide-induced pneumonia mice model, this system could calm down the cytokine storm with high efficacy and elongate the survival of mice.

Successive Waves of the COVID-19 Pandemic Had an Increasing Impact on Chronic Cardiovascular Patients in a Western Region of Romania

Three years since the COVID-19 pandemic started, there is still little information about patients with chronic medical conditions, such as cardiovascular diseases (CVDs), who become infected with SARS-CoV-2. A retrospective analysis was performed to evaluate the impact of the COVID-19 pandemic on patients with cardiovascular comorbidities hospitalized with positive RT-PCR results for SARS-CoV-2 during the highest peaks of the first three pandemic waves: April 2020, October 2020, and November 2021. The primary outcome was in-hospital mortality; the secondary outcomes were length of hospitalization and required mechanical ventilation to assess the disease severity. Data were extracted from the hospital electronic database system: 680 eligible cases were identified out of 2919 patients. Mortality was the highest in wave 3 (31.9%) compared to the previous waves (13.6% and 25.8%). Hospitalization was also significantly longer in wave 3 (11.58 ± 5.34 vs. 8.94 ± 4.74 and 10.19 ± 5.06; p < 0.001), and so was the need for mechanical ventilation (21.7% vs. 8.2% and 9%; p < 0.001). Older age and male gender were confirmed as highly significant predictors of unfavorable outcomes. Ischemic heart disease worsened the odds of patients' survival irrespective of the three pandemic waves (Breslow-Day test, p = 0.387), with a marginally significant Mantel-Haenszel common estimate for risk: OR = 1.604, 95% (0.996; 2.586). The significantly worse outcomes in wave 3 could have been influenced by a combination of factors: the low percentage of vaccinations in Romanian population, the more virulent delta strain, and pandemic attrition in the care provided to these patients with chronic CVDs.

The COVID-19 vaccination decision-making preferences of elderly people: a discrete choice experiment

COVID-19 is a continuing threat to global public health security. For elderly people, timely and effective vaccination reduces infection rates in this group and safeguards their health. This paper adopted an offline Discrete Choice Experiment (DCE) to research the preference for COVID-19 vaccination amongst Chinese adults aged 50 years and above. Through multinomial logistic regression analysis, our DCE leverages five attributes-the risk of adverse reactions, protective duration, injection doses, injection period, and effectiveness-each of which is split into three to four levels. The risk of adverse reaction and the protective duration were demonstrated to be determinants of vaccination preference. Moreover, it was found that socio demographic factors like region, self-health assessment and the number of vaccinated household members can strengthen or weaken the effects of vaccine attributes. In conclusion, the preferences of the elderly population should be considered when developing COVID-19 vaccination programs for this population in China. Accordingly, the results may provide useful information for policymakers to develop tailored, effectively vaccination strategies.

The persistence of SARS-CoV-2 neutralizing antibodies after COVID-19: A one-year observation. Is a SARS-CoV-2 vaccination booster dose necessary?

Introduction

The aim of this study was to investigate the persistence of SARS-CoV-2 neutralizing antibodies (NAbs) one year after contracting COVID-19.

Material and methods

The study included 38 patients - 34 men and 4 women - suffering from COVID-19 between March 15 and May 26, 2020. The median age in the group was 31 years, ranging from 22 to 67 years. The levels of neutralizing antibodies were measured at three time-points - baseline, 6 months, and 12 months. The primary endpoint was a post-infection positive result for NAbs (> 15 AU/ml; Liaison SARS-CoV-2 S1/S2 IgG quantitative test) 12 months after infection.

Results

The median level of NAbs after 12 months was 26.5 AU/ml. At the end of observation (12 months), 21 of the 38 patients had a NAb level of >15 AU/ml (positive). The median antibody half-life was 5.8 months.

Conclusions

A high percentage of the patients maintained positive levels of antibodies 6 and 12 months after COVID-19 infection. The dynamics of the antibody level decline suggests the need for booster vaccination at least once a year.

Sex differences in D-dimer and critical illness in patients with COVID-19: A systematic review and meta-analysis

Background

Observed sex differences in COVID-19 outcomes suggest that men are more likely to experience critical illness and mortality. Thrombosis is common in severe COVID-19, and D-dimer is a significant marker for COVID-19 severity and mortality. It is unclear whether D-dimer levels differ between men and women, and the effect of D-dimer levels on disease outcomes remains under investigation.

Objectives

We aimed to evaluate the sex difference in the D-dimer level among hospitalized patients with COVID-19 and the effect of sex and D-dimer level on disease outcomes.

Methods

We meta-analyzed articles reporting D-dimer levels in men and women hospitalized for COVID-19, until October 2021, using random effects. Primary outcomes were mortality, critical illness, and thrombotic complications.

Results

In total, 11,682 patients from 10 studies were analyzed (N = 5606 men (55.7%), N = 5176 women (44.3%)). Men had significantly higher odds of experiencing mortality (odds ratios (OR) = 1.41, 95% CI: [1.25, 1.59], P ≤ .001, I² = 0%) and critical illness (OR = 1.76, 95% CI: [1.43, 2.18], P ≤ .001, I² = 61%). The mean D-dimer level was not significantly different between men and women (MD = 0.08, 95% CI: [-0.23, 0.40], P = .61, I² = 52%). In the subgroup analysis, men had significantly higher odds of experiencing critical illness compared with women in both the "higher" (P = .006) and "lower" (P = .001) D-dimer subgroups.

Conclusion

Men have significantly increased odds of experiencing poor COVID-19 outcomes compared with women. No sex difference was found in the D-dimer level between men and women with COVID-19. The diversity in D-dimer reporting impacts data interpretation and requires further attention.

A comparison of machine learning algorithms in predicting COVID-19 prognostics

ML algorithms are used to develop prognostic and diagnostic models and so to support clinical decision-making. This study uses eight supervised ML algorithms to predict the need for intensive care, intubation, and mortality risk for COVID-19 patients. The study uses two datasets: (1) patient demographics and clinical data (n = 11,712), and (2) patient demographics, clinical data, and blood test results (n = 602) for developing the prediction models, understanding the most significant features, and comparing the performances of eight different ML algorithms. Experimental findings showed that all prognostic prediction models reported an AUROC value of over 0.92, in which extra tree and CatBoost classifiers were often outperformed (AUROC over 0.94). The findings revealed that the features of C-reactive protein, the ratio of lymphocytes, lactic acid, and serum calcium have a substantial impact on COVID-19 prognostic predictions. This study provides evidence of the value of tree-based supervised ML algorithms for predicting prognosis in health care.

Cellular stress modulates severity of the inflammatory response in lungs via cell surface BiP

Inflammation is a central pathogenic feature of the acute respiratory distress syndrome (ARDS) in COVID-19. Previous pathologies such as diabetes, autoimmune or cardiovascular diseases become risk factors for the severe hyperinflammatory syndrome. A common feature among these risk factors is the subclinical presence of cellular stress, a finding that has gained attention after the discovery that BiP (GRP78), a master regulator of stress, participates in the SARS-CoV-2 recognition. Here, we show that BiP serum levels are higher in COVID-19 patients who present certain risk factors. Moreover, early during the infection, BiP levels predict severe pneumonia, supporting the use of BiP as a prognosis biomarker. Using a mouse model of pulmonary inflammation, we observed increased levels of cell surface BiP (cs-BiP) in leukocytes during inflammation. This corresponds with a higher number of neutrophiles, which show naturally high levels of cs-BiP, whereas alveolar macrophages show a higher than usual exposure of BiP in their cell surface. The modulation of cellular stress with the use of a clinically approved drug, 4-PBA, resulted in the amelioration of the lung hyperinflammatory response, supporting the anti-stress therapy as a valid therapeutic strategy for patients developing ARDS. Finally, we identified stress-modulated proteins that shed light into the mechanism underlying the cellular stress-inflammation network in lungs.

Using laboratory parameters as predictors for the severity and mortality of COVID-19 in hospitalized patients

Objective

The aim of this study was to explore association of initial laboratory parameters of hospitalized patients with COVID-19, with the severity and death incident.

Methods

In this retrospective study, patients were classified based on mortality outcome (survivor and non-survivor) and disease severity (non-severe, severe, and critical). The initial laboratory data (within the first two days of hospital admission) were compared between these categories.

Results

Of 362 COVID-19 patients hospitalized between January-2021 and May-2021, 39.0% were non-severe, 32.2% severe, and 28.7% critical. 77.3% were lived and 22.7% died in hospital. Non-survivors were significantly older than survivors. There was a statistically significant association between exceeding the cut-points of laboratory parameters and the severity of the disease or even death. These laboratory parameters included D-dimer, C-reactive protein, prothrombin time, ferritin, white blood cells, neutrophil count, aspartate aminotransferase, creatinine, blood urea nitrogen, lymphocyte count, and albumin. Also, exceeding the cut-points of these parameters showed high odds of death. The highest odds ratio was reported for albumin <3.5 g/dL (OR=14.318 [4.784-42.851], p<0.001).

Conclusion

The cut-points of the laboratory parameters could effectively be used as predictors to assess the severity and risk of death to improve the management of COVID-19 patients.

Elevated Levels of Pleiotropic Interleukin-6 (IL-6) and Interleukin-10 (IL-10) are Critically Involved With the Severity and Mortality of COVID-19: An Updated Longitudinal Meta-Analysis and Systematic Review on 147 Studies

Objectives

Disruption in the natural immune reaction due to SARS-CoV-2 infection can initiate a potent cytokine storm among COVID-19 patients. An elevated level of IL-6 and IL-10 during a hyperinflammatory state plays a vital role in increasing the risk of severity and mortality. In this study, we aimed to evaluate the potential of circulating IL-6 and IL-10 levels as biomarkers for detecting the severity and mortality of COVID-19.

Methods

This study was conducted according to the Cochrane Handbook and PRISMA guidelines. Authorized databases were searched to extract suitable studies using specific search terms. RevMan 5.4 was applied for performing the meta-analysis. Mean differences in IL-6 and IL-10 levels were calculated among COVID-19 patients via a random-effects model. NOS scoring, publication bias and sensitivity analyses were checked to ensure study quality.

Results

A total of 147 studies were selected, with 31 909 COVID-19 patients under investigation. In the severity analysis, the mean concentration of IL-6 was significantly higher in the severe COVID-19 cases than in the non-severe cases (MD: 19.98; P < .001; 95% CI: 17.56, 22.40). Similar result was observed for IL-10 mean concentration in severe COVID-19 cases (MD: 1.35; P < .001; 95% CI: 0.90, 1.80). In terms of mortality analysis, circulating IL-6 showed sharp elevation in the deceased patients (MD: 42.11; P < .001; 95% CI: 36.86, 47.36). IL-10 mean concentration was higher in the dead patients than in the survived patients (MD: 4.79; P < .001; 95% CI: 2.83, 6.75). Publication bias was not found except for comparing IL-6 levels with disease severity. Sensitivity analysis also reported no significant deviation from the pooled outcomes.

Conclusions

Elevated levels of circulating IL-6 and IL-10 signifies worsening of COVID-19. To monitor the progression of SARS-CoV-2 infection, IL-6 and IL-10 should be considered as potential biomarkers for severity and mortality detection in COVID-19.

Systematic review registration

INPLASY registration number: INPLASY202240046.

T-Cell Subsets and Interleukin-10 Levels Are Predictors of Severity and Mortality in COVID-19: A Systematic Review and Meta-Analysis

Background

Many COVID-19 patients reveal a marked decrease in their lymphocyte counts, a condition that translates clinically into immunodepression and is common among these patients. Outcomes for infected patients vary depending on their lymphocytopenia status, especially their T-cell counts. Patients are more likely to recover when lymphocytopenia is resolved. When lymphocytopenia persists, severe complications can develop and often lead to death. Similarly, IL-10 concentration is elevated in severe COVID-19 cases and may be associated with the depression observed in T-cell counts. Accordingly, this systematic review and meta-analysis aims to analyze T-cell subsets and IL-10 levels among COVID-19 patients. Understanding the underlying mechanisms of the immunodepression observed in COVID-19, and its consequences, may enable early identification of disease severity and reduction of overall morbidity and mortality.

Methods

A systematic search was conducted covering PubMed MEDLINE, Scopus, Web of Science, and EBSCO databases for journal articles published from December 1, 2019 to March 14, 2021. In addition, we reviewed bibliographies of relevant reviews and the medRxiv preprint server for eligible studies. Our search covered published studies reporting laboratory parameters for T-cell subsets (CD4/CD8) and IL-10 among confirmed COVID-19 patients. Six authors carried out the process of data screening, extraction, and quality assessment independently. The DerSimonian-Laird random-effect model was performed for this meta-analysis, and the standardized mean difference (SMD) and 95% confidence interval (CI) were calculated for each parameter.

Results

A total of 52 studies from 11 countries across 3 continents were included in this study. Compared with mild and survivor COVID-19 cases, severe and non-survivor cases had lower counts of CD4/CD8 T-cells and higher levels of IL-10.

Conclusion

Our findings reveal that the level of CD4/CD8 T-cells and IL-10 are reliable predictors of severity and mortality in COVID-19 patients. The study protocol is registered with the International Prospective Register of Systematic Reviews (PROSPERO); registration number CRD42020218918.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020218918, identifier: CRD42020218918.

SARS-CoV-2 genetic variations associated with COVID-19 pathogenicity

In this study, we performed genome-wide association analyses on SARS-CoV-2 genomes to identify genetic mutations associated with pre-symptomatic/asymptomatic COVID-19 cases. Various potential covariates and confounding factors of COVID-19 severity, including patient age, gender and country, as well as virus phylogenetic relatedness were adjusted for. In total, 3021 full-length genomes of SARS-CoV-2 generated from original clinical samples and whose patient status could be determined conclusively as either ‘pre-symptomatic/asymptomatic’ or ‘symptomatic’ were retrieved from the GISAID database. We found that the mutation 11 083G>T, located in the coding region of non-structural protein 6, is significantly associated with asymptomatic COVID-19. Patient age is positively correlated with symptomatic infection, while gender is not significantly correlated with the development of the disease. We also found that the effects of the mutation, patient age and gender do not vary significantly among countries, although each country appears to have varying baseline chances of COVID-19 symptom development.

COVID-19: The Impact on Cardiovascular System

SARS-CoV-2 has been circulating in population worldwide for the past year and a half, and thus a vast amount of scientific literature has been produced in order to study the biology of the virus and the pathophysiology of COVID-19, as well as to determine the best way to prevent infection, treat the patients and eliminate the virus. SARS-CoV-2 binding to the ACE2 receptor is the key initiator of COVID-19. The ability of SARS-CoV-2 to infect various types of cells requires special attention to be given to the cardiovascular system, as it is commonly affected. Thorough diagnostics and patient monitoring are beneficial in reducing the risk of cardiovascular morbidity and to ensure the most favorable outcomes for the infected patients, even after they are cured of the acute disease. The multidisciplinary nature of the fight against the COVID-19 pandemic requires careful consideration from the attending clinicians, in order to provide fast and reliable treatment to their patients in accordance with evidence-based medicine principles. In this narrative review, we reviewed the available literature on cardiovascular implications of COVID-19; both the acute and the chronic.

Initial presenting symptoms, comorbidities and severity of COVID-19 patients during the second wave of epidemic in Myanmar

Background

Coronavirus disease 2019 (COVID-19) caused by a highly contagious virus called severe acute respiratory syndrome coronavirus 2 emerged in China at the end of 2019 and became a major threat to health around the world. The health experts are still learning more about the detailed knowledge of the natural course and the severity of COVID-19. The study aimed to assess the prevalence and association of severity of disease with demographic characteristics, initial presenting symptoms, and comorbidities among COVID-19 patients in treatment centers, Myanmar.

Methods

A cross-sectional study was conducted at Hmawbi and Indine treatment centers, Yangon Region, Myanmar, from November to December 2020. Data were collected by using standardized case report forms and then, a total of 222 confirmed COVID-19 inpatients were included in this study. The odds ratio with a 95% confidence interval (CI) was used as a measure of association and the independent associated factors for severity of disease were investigated using logistic regression analysis.

Results

In total, 81.5% were symptomatic patients and of these, the most common presenting symptoms were fever 54.1%, loss of smell 50.3%, and cough 30.9%. Among 37.8% of COVID-19 patients with comorbidities, the most common comorbidities were hypertension 58.3%, diabetes mellitus 29.8%, and heart diseases 26.2%, respectively. As a severity, 20.7% of patients had signs of severe pneumonia. The associated factors of severe pneumonia were aged 60 years and older [Adjusted odds ratio (AOR) = 2.88, 95% CI 1.14–7.29], overweight or obesity (AOR: 3.87, 95%CI 1.80–8.33), and current smoking (AOR: 6.74, 95% CI 2.72–16.75).

Conclusions

In this study, one-fifth of the patients developed severe pneumonia. The COVID-19 patients who were aged 60 years and older, overweight or obesity, and current smokers should be monitored carefully during the course of treatment to reduce the disease severity.