COVID-19 Disease Severity Research Articles

Antimicrobial prescribing practices and factors associated with antimicrobial prescribing in hospitalized COVID-19 patients in Oyo state: A retrospective study.

Proportion of hospitalized COVID-19 patients receiving antimicrobial drug is significantly high despite evidence of low level of actual bacterial co-infection, potentially contributing to poor health outcome and global antimicrobial resistance. A retrospective study was performed on antimicrobial agents prescribed to adult patients with confirmed COVID-19 admitted across three isolation facilities between 1 March 2020 and 30 April 2021 in Ibadan, Oyo state, Nigeria. From individual records, we evaluated patient demographics, COVID-19 risk factors, diagnostic testing, disease severity and antimicrobial utilization. The primary aim was to determine the prevalence of antimicrobial prescription as well as factors associated with antimicrobial prescribing in hospitalized patients with COVID-19 in Oyo state. In total, 271 patients were included in this study. The median age of the population was 51 years (IQR; 32-62 years). The mean duration of hospital admission was 13 days (IQR: 10-14 days). Majority of participants were symptomatic (81.5%). All participants had a COVID-19 PCR test performed and none had bacterial culture performed. All patients received antimicrobial therapy across the entire cohort. The mean DOT per LOT across cohorts was 1.2 for mild cases, 1.4 for moderate cases and 1.3 for severe cases. Factors associated with the number of antimicrobials per prescription were being single (P = 0.02), being below 60 years of age (P = 0.04), mild COVID-19 symptoms (P < 0.001) and diabetes comorbidity (P = 0.03). Given the high rate of antimicrobial prescription and absence of bacteriological culture analysis in these patients, there is risk of development and spread of antimicrobial resistant. Continuous review of antimicrobial prescription is critical in the management of hospitalized COVID-19 patients.

Association between Hematological Parameters and Severity of COVID-19 disease

Background This study aimed to determine the relationships between hematological parameters- hemoglobin, Total Leucocyte Counts (TLC), platelet counts, Absolute Neutrophil Counts (ANC), Absolute Lymphocyte Counts (ALC), Neutrophil Lymphocyte Ratio (NLR), Systemic Immune Inflammatory Index (SII), Neutrophil Monocyte Ratio (NMR), Platelet Lymphocyte Ratio (PLR) and the severity of COVID-19 disease and their use in predicting severity of COVID-19 disease. Methods and Material This was a prospective, observational, single-center study of 573 symptomatic adult inpatients of COVID 19 admitted to our tertiary care center. Statistical analysis used The above-mentioned hematological parameter levels were noted and compared between the two categories of COVID-19 disease, namely non-severe and severe COVID-19 using logistic regression methods. Their cut-off values were detected using the ROC curve. Results The median TLC, ANC, NLR, SII, NMR, PLR were notably higher in patients with severe COVID-19 than in those with non-severe COVID-19. Logistic regression analysis showed that NMR (OR=1.029, p=0.006) and ALC (OR=0.999, p=0.002) were statistically significant independent predictors of COVID-19 severity. Conclusions The hematological parameters mentioned, can be used for predicting severe COVID-19 disease at admission. ALC and NMR levels could be used as hematological markers to predict severity of COVID-19 in adult patients with their cut off values being &lt; 1105 cells/cubic millimeter and &gt; 10.434 respectively.

Clinical profile, risk factors, disease severity, and outcome for COVID-19 disease in patients with tuberculosis on treatment under the National Tuberculosis Elimination Program: a cohort of 1400 patients.

COVID-19 affected millions of people worldwide, and tuberculosis (TB) continues to affect millions of people each year. The combined pandemic of COVID-19 and TB had a catastrophic effect on healthcare policies and healthcare setups around the globe. The clinical profile and factors affecting the outcome of COVID-19 disease in TB patients on treatment in field conditions have not been studied in detail. The present study attempted to study the occurrence of COVID-19 among patients on TB treatment in terms of severity of COVID-19 disease and outcome of both COVID-19 and TB in patients at National Tuberculosis Elimination Program treatment centers over a period of one year during peak COVID-19 times. Out of 1400 TB patients enrolled, 65 (5%) suffered from COVID-19 disease. Of the 65 TB patients with COVID-19 disease, 37 (57%) were male and under 45 years old, 33 (51%) had a TB diagnosis after first receiving a COVID-19 diagnosis, 29 (45%) had a TB diagnosis first, and received anti-TB treatment before receiving a COVID-19 diagnosis, and only 3 patients (5%) had a COVID-19 and TB diagnosis concurrently. The majority of 59 (91%) patients had mild COVID-19 disease. The outcome of TB treatment was available in 25 patients out of these 65 COVID-19-positive patients, with 21 (84%) patients having a favorable outcome. Out of the 65 COVID-19-positive patients, 4/25 (16%) had unfavorable outcomes, with one patient (4%) failing TB treatment and two patients (8%) dying. This is the first study from India that studied the occurrence and course of COVID-19 among a large number of TB patients taking anti-TB treatment under programmatic conditions. Due to the similarity in symptoms of TB and certain viral respiratory illnesses, a protocol should be established for health care to check patients for both illnesses.

Prolactin Role in COVID-19 and Its Association with the Underlying Inflammatory Response

The COVID-19 pandemic has prompted interest in identifying reliable biomarkers to predict disease severity and guide clinical decisions. Prolactin (PRL), a hormone traditionally associated with lactation, has gained attention for its role in immune modulation. This study aimed to assess PRL as a biomarker for disease severity in COVID-19. A prospective cohort of 142 patients with moderate to severe COVID-19, defined as a WHO-CPS 5 or 6, was recruited from the University General Hospital of Patras. Baseline PRL levels were measured using an electrochemiluminescence immunoassay, and serum cytokines, including IL-1β, IL-6, IL-8, IL-10, IL-12p70, and TNF-α, were quantified through flow cytometry. Clinical outcomes, including mortality and the need for invasive mechanical ventilation (IMV), were recorded. Results indicated that PRL levels were significantly higher in female patients (12.95 ng/mL vs. 9.40 ng/mL, p &lt; 0.001) but they did not correlate with key severity indices such as CCI, SOFA score upon admission or inflammatory markers. No significant associations between baseline PRL levels, cytokine concentrations, and clinical outcomes in COVID-19 were noted. Our findings suggest that PRL may lack prognostic reliability for disease severity compared to more established predictive markers and that its role in the immune response remains uncertain.

Dynamic Changes in Lymphocyte Populations and Their Relationship with Disease Severity and Outcome in COVID-19

Studies suggest that the dynamic changes in cellular response might correlate with disease severity and outcomes in SARS-CoV-2 patients. The study aimed to investigate the dynamic changes of lymphocyte subsets in patients with COVID-19. In this regard, 53 patients with COVID-19 were prospectively included, classified as mild, moderate, and severe. The peripheral lymphocyte profiles (LyT, LyB, and NK cells), as well as CD4+/CD8+, CD3+/CD19+, CD3+/NK and CD19+/NK ratios, and their dynamic changes during hospitalization and correlation with disease severity and outcome were assessed. We found significant differences in CD3+ lymphocytes between severity groups (p &lt; 0.0001), with significantly decreased CD3+CD4+ and CD3+CD8+ in patients with severe disease (p &lt; 0.0001 and p = 0.048, respectively). Lower CD3+/CD19+ and CD3+/NK ratios among patients with severe disease (p = 0.019 and p = 0.010, respectively) were found. The dynamic changes of lymphocyte subsets showed a significant reduction in NK cells (%) and a significant increase in CD3+CD4+ and CD3+CD8+ cells in patients with moderate and severe disease. The ROC analysis on the relationship between CD3+ cells and fatal outcome yielded an AUC of 0.723 (95% CI 0.583–0.837; p = 0.007), while after addition of age and SpO2, ferritin and NLR, the AUC significantly improved to 0.927 (95%CI 0.811–0.983), p &lt; 0.001 with a sensitivity of 90.9% (95% CI 58.7–99.8%) and specificity of 85.7% (95% CI 69.7–95.2%). The absolute number of CD3+ lymphocytes might independently predict fatal outcomes in COVID-19 patients and T-lymphocyte subset evaluation in high-risk patients might be useful in estimating disease progression.

Relationships Between Polymorphisms in HLA-G 3'UTR Region and COVID-19 Disease Severity.

The objective of this study is to investigate the the relationships between HLA-G gene variants and sHLA-G with susceptibility to SARS-CoV-2 infection. In this case-control study, 65 Patients with COVID-19 were and 67 healthy controls were genotyped for their main functional polymorphisms namely, the 14-bp Ins/Del (rs371194629), +3003C/T (rs1707), +3010C/G (rs1710), +3027A/C (rs17179101), +3035C/T (rs17179108), +3142C/G (rs1063320), +3187A/G (rs9380142) and +3196C/G (rs1610696) in the exon 8 of the 3' untranslated regions (3' UTRs) using sanger sequencing method. Associations were assessed for five inheritance models (codominant, dominant, recessive, over-dominant and log-additive). Moreover, the levels of plasma soluble HLA-G (sHLA-G) were explored using ELISA method. Our results revealed that the 14-bp INS/DEL polymorphism was strongly associated with COVID-19 symptoms development for almost all tested inheritance models (p < 0.001). Inversely, the (+3196C/G) polymorphism exhibited a protective effect against COVID-19. In addition, three haplotypes; UTR-1, UTR-3, and UTR-5 were found associated with COVID-19 symptoms (p < 0.05), The level of HLA-G in the serum was significantly higher in COVID-19 individuals than in healthy individuals (p < 0.001).These findings suggest that HLA-G gene polymorphisms in the regulatory 3'UTR region of the HLA-G gene may influence the host immune response to SARS-CoV-2 infection. A deeper comprehension of the functional effect of these associated polymorphisms could be useful in identifying high-risk individuals and in developing adaptive treatments for patients.

Relationship between Diet-Related Inflammation and Hospitalization Risk and Disease Severity in Patients with COVID-19

Background: Increased serum concentrations of inflammatory biomarkers in patients indicate a strong association between COVID-19 and inflammation. However, the association between diet-related inflammation and COVID-19 has been less investigated. The aim of this study is to investigate whether the inflammatory scores of the diet are associated with the severity of COVID-19 disease and the probability of hospitalization of patients. Methods: The authors conducted a cross-sectional study involving 141 patients with COVID-19. The empirical dietary inflammatory pattern (EDIP) and dietary inflammation scores (DIS) were calculated based on a 147-item semi-quantitative food frequency questionnaire. The association between serum levels of inflammatory biomarkers and diet-related inflammation was also investigated. Results: 74 inpatients and 87 outpatients participated in this study. Higher DIS scores were significantly associated with an increased risk of COVID-related hospitalization (Tertile3 vs. tertile1: OR = 3·62; 95 % CI 1·43 to 9·14, P=0·008 after fully adjustment). This association with EDIP was also observed, but it was not significant. Conclusion: The data from this provide evidence that a pro-inflammatory diet was associated with higher risk of hospitalization due to high severity of COVID-19.

The HLA-B -21 M/T dimorphism associates with disease severity in COVID-19.

Host genetics shape immune responses and influence severity of infectious diseases. The HLA-B -21 M/T dimorphism tunes the functionality of natural killer (NK) cells expressing the inhibitory receptor NKG2A. NKG2A+ NK cells have been reported to recognize SARS-CoV-2-infected cells, but it remains unclear whether the HLA-B -21 M/T dimorphism associates with COVID-19 severity. Here, we investigated the influence of the HLA-B -21 M/T dimorphism in a cohort of 230 unvaccinated patients hospitalized with COVID-19 and requiring respiratory support. We found that HLA-B -21 M/M genotypes were more prevalent in patients with moderate compared to severe COVID-19 (6.0% vs. 0.9%). Comparison of age- and sex-matched sub-groups revealed that patients with M/M genotypes required mechanical respiratory support less frequently (OR = 0.13, 95% CI = 0.01-0.76, P = 0.013). Furthermore, patients with M/M genotypes showed a coordinately shifted signature of clinical laboratory parameters, coinciding with elevated serum levels of the anti-viral cytokine IFN-γ. These findings demonstrate that HLA-B variants associate with COVID-19 severity and suggest that the robust functionality of NKG2A+ NK cells in patients carrying the M/M genotype may contribute to protection from severe disease.

Circulating inflammatory cytokines predict severity disease in hospitalized COVID-19 patients: a prospective multicenter study of the European DRAGON consortium

BackgroundCOVID-19 has put a huge strain on the healthcare systems worldwide, requiring unprecedented intensive care resources. There is still an unmet clinical need for easily available biomarkers capable of predicting the risk for severe disease. The main goal of this prospective multicenter study was to identify biomarkers that could predict ICU admission and in-hospital mortality. MethodsWe prospectively recruited COVID-19 PCR positive patients in two hospitals, in Belgium and Italy. Blood samples were collected at hospital admission and 20 potential biomarkers were measured with the Luminex technology. Logistic regression models were performed to identify the biomarkers that, alone or together, were associated with patient disease severity. ResultsOur study demonstrates that elevated levels of circulating inflammatory cytokines were associated with disease severity in COVID-19 hospitalized patients. CXCL10, IL-4, IL-6 and MCP-1 values were predictive of ICU admission. Elevated levels of IL-6 and MCP-1 were also associated with in hospital death in COVID-19 hospitalized patients. ConclusionAltogether, elevated and correlated inflammatory cytokines in the blood of COVID-19 patients at hospital admission are predictive of disease severity and suggest a dysregulated inflammation induced by SARS-CoV-2 infection.

Ethnic disparities in clinical severity of COVID-19 as predictor of long COVID

Abstract Background Recent studies from Europe have shown a higher incidence of long COVID among ethnic minorities compared to the majority population. Little is known of these disparities, but they might be related to factors such as COVID-19 disease severity, barriers in access to health and individual factors such as working and living conditions. This study will elucidate possible predictors of long COVID related to COVID-19 disease severity in an ethnic diverse hospitalised cohort. Methods A retrospective cohort study of 1648 patients admitted with COVID-19 at three hospitals in Copenhagen, Denmark, between 1st February 2020 and 31st May 2022. Clinical data was extracted from health care records, and subsequently linked to data from Statistics Denmark on long COVID diagnosis (ICD-10 “DB948A”) as well as migration status. Results 1361 patients were discharged alive and of those, 113 (8,3%) patients got a long COVID diagnosis. Preliminary analyses show no excess risk of getting a long COVID diagnosis as a migrant compared to patients of Danish origin (RR = 1,20, p = 0,35). Some ethnic disparities are seen in disease severity among all patients discharged alive. Patients with migrant background were admitted to the hospital later (6,8 vs 5,6 days, p &amp;lt; 0,0001), and at a greater risk of needing high flow oxygen administration upon admission (RR = 1,46, p = 0,0012) compared to patients of Danish origin. Furthermore, a higher degree of systemic inflammation is seen among migrants with regards to lactate dehydrogenase (LDH) compared to patients of Danish origin (349,7 vs 317,2 U/L, p = 0,0014). No significant differences in c-reactive protein (CRP) levels (92,8 vs 85,9 mg/L, p = 0,11). Conclusions Preliminary analyses indicates possible ethnic disparities in COVID-19 disease severity among patients discharged alive possibly playing a role as predictors of long COVID. Low health literacy or language barriers might partly explain this. Further analyses are needed. Key messages • In preliminary analyses of 1381 patients previously admitted with COVID-19, we find no excess risk of a long COVID diagnosis (DB 948B) among patients with migrant background. • Preliminary analyses show some ethnic disparities in COVID-19 disease severity that might act as possible predictors of long COVID.

Aromatase, testosterone, TMPRSS2: determinants of COVID-19 severity

BackgroundMale sex has been identified as a risk factor for worse COVID-19 outcomes. This sex difference has been mostly attributed to the complex role of sex hormones. Cell surface entry of SARS-CoV-2 is mediated by the transmembrane protease serine 2 (TMPRSS2) which is under transcriptional regulation by androgens. P450 aromatase enzyme converts androgens to estrogens. This study measured concentrations of aromatase enzyme, testosterone, estradiol, and TMPRSS-2 in plasma of hospitalized COVID-19 patients to elucidate the dynamics of sex-linked disparity in COVID-19 and correlate them with disease severity and mortality.MethodsIn this prospective cohort study, a total of 265 patients (41% women), age 18 years and older, who had a positive COVID-19 PCR test and were hospitalized for COVID-19 at Memorial Hermann Hospital in Houston, (between May 2020 and May 2021) were enrolled in the study if met inclusion criteria. Plasma concentrations of Testosterone, aromatase, TMPRSS-2, and estradiol were measured by ELISA. COVID-19 patients were dichotomized based on disease severity into moderate-severe (n = 146) or critical (n = 119). Mann Whitney U and logistic regression were used to correlate the analytes with disease severity and mortality.ResultsTMPRSS2 (2.5 ± 0.31 vs. 1.73 ± 0.21 ng/mL, p < 0.01) and testosterone (1.2 ± 0.1 vs. 0.44 ± 0.12 ng/mL, p < 0.01) were significantly higher in men as compared to women with COVID-19 after adjusting for age in a multivariate model. There was no sex difference seen in the level of estradiol and aromatase in COVID-19 patients. TMPRSS2 and aromatase were higher, while testosterone was lower in patients with increased COVID-19 severity. They were independently associated with COVID-19 severity, after adjusting for several baseline risk factors in a multivariate logistic regression model. In terms of mortality, TMPRRS2 and aromatase levels were significantly higher in non-survivors.ConclusionsOur study demonstrates that testosterone, aromatase, and TMPRSS2 are markers of COVID-19 severity. Estradiol levels do not change with disease severity in COVID-19. In terms of mortality prediction, higher aromatase and TMPRSS-2 levels can be used to predict mortality from COVID-19 in hospitalized patients.Plain English SummaryCOVID-19 has caused over a million deaths in the U.S., with men often getting sicker than women. Testosterone, a male hormone, helps control a protein called TMPRSS-2, which allows the COVID-19 virus to spread more easily in the body. A protein called aromatase converts the male hormone testosterone into the female hormone estrogen. It is thought that female hormone estrogen helps protect women from getting seriously ill from COVID-19. To understand the role of these hormones in COVID-19 and sex differences, we measured levels of testosterone, estrogen, aromatase (which turns testosterone into estrogen), and TMPRSS-2 in hospitalized COVID-19 patients. We also checked how this level might reflect the severity of the disease. We found that critically ill COVID-19 patients (the ones in ICU) had higher levels of TMPRSS-2 and aromatase, and lower testosterone levels. When we used these hormone levels to predict death in hospitalized COVID-19 patients, higher levels of TMPRSS-2 and aromatase were linked to a lower chance of survival.

Enhancing COVID-19 disease severity classification through advanced transfer learning techniques and optimal weight initialization schemes

ObjectiveMedical imaging plays a central role in medicine today by supporting diagnosis and treatment. For small medical image datasets, training from scratch is a time-consuming process and transfer learning emerges as a solution. In these cases, ImageNet weights are usually used as initial weights, after which fine-tuning is performed. We propose a methodology for COVID-19 severity classification (mild, moderate, severe, critical) in chest X-ray images based on transfer learning using DenseNet121 architecture as a base model. MethodsThe novelty of the approach mainly lies in the investigation of three different weight initialization schemes (i) ImageNet (ii) CheXNeXt (iii) DeepCOVID-XR, which are similar in a graded manner in terms of image nature, with ImageNet being the least similar, CheXNeXt similar as they were trained on different lung diseases not including COVID-19 and DeepCOVID-XR the most similar as they were obtained by training specifically on COVID-19 X-ray images. ResultsThe results show that the worst results are achieved using ImageNet as initial weights (average AUC = 0.700), followed by the better results with DeepCOVID-XR (average AUC = 0.774) while CheXNeXt performed significantly better (average AUC = 0.917). The results of weaker performing classification models were improved when the severe and critical classes were merged, to account for the similarity between these classes in the dataset (average AUC for initialization schemes were ImageNet AUC = 0.867, CheXNeXt AUC = 0.900 and DeepCOVID-XR AUC = 0.794). ConclusionThis leads to a conclusion that, in the medical domain, where image datasets are usually small and highly imbalanced, if initial weights are chosen to be in nature similar to the new dataset, achieved results are better. However, there is no need to start from weights obtained during training on the same disease, as this may cause overfitting. There are significant discrepancies between ImageNet and medical imaging datasets and the results from this paper could help in guiding future implementations of transfer learning in medical applications.

Investigation of Long-Term CD4+ T Cell Receptor Repertoire Changes Following SARS-CoV-2 Infection in Patients with Different Severities of Disease.

The difference in the immune response to severe acute respiratory syndrome coro-navirus 2 (SARS-CoV-2) in patients with mild versus severe disease remains poorly understood. Recent scientific advances have recognised the vital role of both B cells and T cells; however, many questions remain unanswered, particularly for T cell responses. T cells are essential for helping the generation of SARS-CoV-2 antibody responses but have also been recognised in their own right as a major factor influencing COVID-19 disease outcomes. The examination of T cell receptor (TCR) family differences over a 12-month period in patients with varying COVID-19 disease severity is crucial for understanding T cell responses to SARS-CoV-2. We applied a machine learning approach to analyse TCR vb family responses in COVID-19 patients (n = 151) across multiple timepoints and disease severities alongside SARS-CoV-2 infection-naïve (healthy control) individ-uals (n = 62). Blood samples from hospital in-patients with moderate, severe, or critical disease could be classified with an accuracy of 94%. Furthermore, we identified significant variances in TCR vb family specificities between disease and control subgroups. Our findings suggest advantageous and disadvantageous TCR repertoire patterns in relation to disease severity. Following validation in larger cohorts, our methodology may be useful in detecting protective immunity and the assessment of long-term outcomes, particularly as we begin to unravel the immunological mechanisms leading to post-COVID complications.

The Relationship between Plasminogen Activator Inhibitors and the Severity of COVID-19

The fibrinolysis process is assisted by plasminogen activators and inhibitors by converting plasminogen into plasmin, which later will promote the fibrinolysis process. Incomplete fibrinolysis increases the risk of thrombosis in patients with COVID-19. Plasminogen Activator Inhibitor (PAI-1) plays an important role as acute phase reactants to be used as a marker to assess the prognosis and mortality of COVID-19 patients. This study aimed to elaborate on whether fibrinolysis shutdown occurs in COVID-19 patients using PAI-1 as a marker of fibrinolysis. This was a cross-sectional analytical study from November 2022 to May 2023. This research consisted of a total of 39 patients with COVID-19, hospitalized at Haji Adam Malik General Hospital, Medan. PAI-test in COVID-19 patients was carried out with the ELISA method using Chemwell Analyzer. The severity of COVID-19 measured by clinical examination was divided into moderate, severe, and critical. The association between the two variables was subjected to a comparative test followed by a correlation test to explore the association between the two variables with an independent T-test. In this study, the median PAI-1 level was 1.77 ng/mL (0.71–11.49 ng/mL). The highest PAI-1 levels were observed in the critical severity group, followed by the severe and moderate group of 8.54 ng/mL (5.76–10.84), 2.45 ng/mL (0.71–11.49), and 1.29 ng/mL (0.73–3.77), respectively. There was a significant relationship between PAI-1 levels and the severity of COVID-19 patients (p=0.003). PAI-1 cut-off value of 1.89 ng/mL may predict the degree of COVID-19 severity with sensitivity of 88.9%, specificity of 90.5%, and accuracy of 89.7%. This study classified the severity of COVID-19 into two categories, which are moderate (n=21) and severe-critical (n=18) to obtain the AUC value of PAI-1. PAI-1 can be used to predict the severity of COVID-19 disease with a moderate level (AUC &gt;70–80%). This phenomenon can be secondary to enhanced platelet aggregation, inflammation micro thrombosis, and impaired fibrinolysis. Fibrinolysis disorders lead to a fibrin buildup and increased levels of PAI-1 in the circulation.

Association of COVID-19 with acute and post-acute risk of multiple different complications and mortality in patients infected with omicron variant stratified by initial disease severity: a cohort study in Hong Kong

BackgroundFew studies have attempted to use clinical and laboratory parameters to stratify COVID-19 patients with severe versus non-severe initial disease and evaluate age-specific differences in developing multiple different COVID-19-associated disease outcomes.MethodsA retrospective cohort included patients from the electronic health database of Hong Kong Hospital Authority between 1 January 2022 and 15 August 2022 until 15 November 2022. The cohort was divided into three cohorts by age (≤ 40, 41–64, and ≥ 65 years old). Each age cohort was stratified into four groups: (1) COVID-19 critically exposed group (ICU admission, mechanical ventilation support, CRP > 80 mg/L, or D-dimer > 2 g/mL), (2) severely exposed group (CRP 30–80 mg/L, D-dimer 0.5–2 g/mL, or CT value < 20), (3) mildly–moderately exposed group (COVID-19 positive-tested but not fulfilling the criteria for the aforementioned critically and severely exposed groups), and (4) unexposed group (without COVID-19). The characteristics between groups were adjusted with propensity score-based marginal mean weighting through stratification. Cox regression was conducted to determine the association of COVID-19 disease severity with disease outcomes and mortality in the acute and post-acute phase (< 30 and ≥ 30 days from COVID-19 infection) in each age group.ResultsA total of 286,114, 320,304 and 194,227 patients with mild–moderate COVID-19 infection; 18,419, 23,678 and 31,505 patients with severe COVID-19 infection; 1,168, 2,261 and 10,178 patients with critical COVID-19 infection, and 1,143,510, 1,369,365 and 1,012,177 uninfected people were identified in aged ≤ 40, 40–64, and ≥ 65 groups, respectively. Compared to the unexposed group, a general trend tending towards an increase in risks of multiple different disease outcomes as COVID-19 disease severity increases, with advancing age, was identified in both the acute and post-acute phases. Notably, the mildly–moderately exposed group were associated with either insignificant risks (aged ≤ 40) or the lowest risks (aged > 40) for the disease outcomes in the acute phase of infection (e.g., mortality risk HR (aged ≤ 40): 1.0 (95%CI: 0.5,2.0), HR (aged 41–64): 2.1 (95%CI: 1.8, 2.6), HR (aged > 65): 4.8 (95%CI: 4.6, 5.1)); while in the post-acute phase, these risks were largely insignificant in those aged < 65, remaining significant only in the elderly (age ≥ 65) (e.g., mortality risk HR (aged ≤ 40): 0.8 (95%CI: (0.5, 1.0)), HR (aged 41–64): 1.1 (95%CI: 1.0,1.2), HR (aged > 65): 1.5 (95%CI: 1.5,1.6)). Fully vaccinated patients were associated with lower risks of disease outcomes than those receiving less than two doses of vaccination.ConclusionsThe risk of multiple different disease outcomes in both acute and post-acute phases increased significantly with the increasing severity of acute COVID-19 illness, specifically among the elderly. Moreover, future studies could improve by risk-stratifying patients based on universally accepted thresholds for clinical parameters, particularly biomarkers, using biological evidence from immunological studies.

COVID-19 Disease Incidence and Severity in Previously Infected Unvaccinated Compared with Previously Uninfected Vaccinated Persons.

Using the VA COVID-19 National Database, we created matched pairs of previously uninfected vaccinated (≥2 doses of an mRNA vaccine) and previously infected unvaccinated individuals. The incidence rate (per 1000 person-days) of breakthrough infection among vaccinated individuals (0.30, 95% CI 0.29-0.32) was similar to reinfection rate among unvaccinated individuals (0.31, 95% CI 0.30-0.32; p=0.5). The incidence rate of hospitalization/death was higher after reinfection (7.31, 95% CI 6.66-8.03) compared with rate after breakthrough infection (4.69, 95% CI 4.06-5.42; P<0.0001). Conclusion: The incidence of hospitalization/death is significantly higher after reinfection among unvaccinated individuals compared with breakthrough infection after vaccination.

Community preventive behaviour and perception on the severity of COVID-19 disease in Indonesia, 2021-2022: Structural equation modelling

Community preventive behaviour and perception on the severity of COVID-19 disease in Indonesia, 2021-2022: Structural equation modelling

Hemophagocytosis of the Hilar Pulmonary Lymph Nodes Is a More Sensitive Indicator of the Severity of COVID-19 Disease than Bone Marrow Hemophagocytosis.

In systemic hyper-inflammation, as in severe COVID-19 disease, there are pronounced disorders of the hematological and lymphatic systems with prognostically relevant hemophagocytosis of the bone marrow. The current work aimed to address the importance of hemophagocytosis in the lymph nodes of patients with severe COVID-19 disease. From 28 patients who died of severe COVID-19 infection, samples of the vertebral bone marrow and lymph nodes from the cervical, hilar, para-aortic, mesenteric and inguinal locations were morphologically and immunohistologically (CD163, CD68, CD61, CD71, CD3, CD20, CD138) examined for the possible presence of hemophagocytosis. In the single-center study at the University Hospital Jena, a total of 191 hemophagocytes were found in the bone marrow and a total of 780 hemophagocytes in the lymph nodes in a standardized area of 21,924 mm2 per tissue sample. With 370 hemophagocytes, hilar lymph nodes were most frequently affected (370/780; 47.44%; 95%-CI: [43.94, 50.95]), followed by cervical lymph nodes (206/780; 26.41%; 95%-CI: [23.41, 29.59]), para-aortic lymph nodes (125/780; 16.03%; 95%-CI: [13.58, 18.73]) and inguinal/mesenteric lymph nodes (79/780; 10.13%; 95%-CI: [8.155, 12.4]). Based on the standard area (21,924 mm2), the difference in the number of hemophagocytes in the bone marrow and in the hilar lymph nodes was statistically significant (p < 0.05), while this did not apply to the lymph nodes from the other locations. In fatal COVID-19 disease, hemophagocytosis is particularly found in the hilar lymph nodes and is therefore a better indicator of the severity of the disease than hemophagocytosis in the bone marrow. The findings provide some evidence for the concept of compartmentalized human host responses to life-threatening infections.

Combination of the chemokine receptor type 2 (CCR2) antagonist DMX-200 and candesartan for COVID-19: a randomised controlled trial

ObjectiveTo determine whether a chemokine receptor type 2 antagonist, DMX-200 (repagermanium), in combination with an angiotensin receptor blocker, candesartan, improves clinical outcomes in people with COVID-19.DesignProspective, multicentre, double-blind, placebo-controlled trial.SettingTen...

Correlation Of BCG Vaccination And COVID-19 Disease Through Measurement Of Immunological Markers IFN-Γ And Anti-BCG Igg In Different Age Groups Running Title: Correlation Between BCG Vaccination And COVID-19 Disease

Introduction Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China in December 2019 and then became a pandemic. BCG vaccination has conferred non-specific (targeted-off) protective effects against unrelated pathogens including respiratory viral infections that have been hypothesized to it could reduce the severity of COVID-19 disease. Objective: Assess whether BCG vaccination has a role in the prevention of COVID-19. Methods: A cross-sectional study including 111 healthy people was carried out from October 2021 to December 2022. Specific anti-BGC-IgG and IFN-γ levels were estimated in blood samples after stimulation with BCG vaccine for 2 days. All participants were examined for BCG scar status and COVID-19 confirmation. Results: There was no significant difference in anti-BCG IgG levels or IFN-γ levels (p&gt;0.05) in relation to COVID-19 infection. There was no statistically significant association between BCG scar diameter and COVID-19 infection (p&gt;0.05). Furthermore, there was no statistically significant association between the BCG scar diameter and COVID-19 severity (p&gt;0.05). There was no significant difference in anti-BCG IgG levels (p&gt;0.05) in relation to COVID-19 severity. Likewise, there was no significant difference in between IFN γ levels and COVID-19 severity (p&gt;0.05). Conclusion: There was no correlation between BCG vaccination and infection or severity of COVID-19.