Effect of Direct Bilirubin Level on Clinical Outcome and Prognoses in Severely/Critically Ill Patients With COVID-19

Incidence of major adverse kidney events after ICU admission in COVID-19 and non-COVID-19 ARDS patients

OBJECTIVES

To compare the incidence and drivers of major adverse kidney events (MAKEs) between COVID-19 and non-COVID-19 acute respiratory distress syndrome (ARDS) patients, with a focus on long-term kidney outcomes.

DESIGN

Retrospective cohort study.

SETTING

Single-centre intensive care unit in the Midlands, UK.

PARTICIPANTS

708 ARDS patients (458 COVID-19, 250 non-COVID-19).

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was MAKE at 365 days (MAKE-365), defined as new renal replacement therapy (RRT), estimated glomerular filtration rate (eGFR) <75% of baseline or all-cause mortality. Secondary analyses examined non-mortality MAKE components.

RESULTS

The incidence of MAKE-365 was significantly higher in the non-COVID-19 group compared with the COVID-19 group (66% vs 39%, p<0.001), primarily driven by increased RRT initiation, followed by mortality and eGFR decline (p=0.055). Independent predictors of MAKE-365 included lower eGFR and elevated bilirubin in both groups. Age (p<0.001) and diabetes (p=0.041) were additional predictors in the COVID-19 cohort, while lower albumin (p=0.002) was significant in the non-COVID-19 group. Excluding mortality, RRT and eGFR decline remained significant drivers of MAKE outcomes in the non-COVID-19 cohort.

CONCLUSIONS

Non-COVID-19 ARDS patients face a greater risk of MAKE-365 and adverse kidney outcomes due to higher RRT requirements and mortality rates. These findings underscore the importance of tailored interventions and long-term nephrology follow-up, particularly for patients with reduced eGFR, elevated bilirubin and comorbidities like diabetes and hypoalbuminaemia.

Changes in nonfunctional adrenal incidentaloma after COVID-19 infection and a model for predicting benign and malignant adrenal incidentaloma

Aims

To compare nonfunctional adrenal incidentalomas (NFAI) in individuals with and without a history of COVID-19 infection, while also establishing predictive models for distinguishing between benign and malignant adrenal incidentalomas (AI).

Methods

A retrospective collection of data from patients with AI who underwent surgery and were verified in our hospital between April 2022 and June 2023 was conducted. A total of 121 patients were included in the study. Demographic information, tumor characteristics, functional indicators, and complications were compared among the patients. Statistical analyses utilized the t-test for continuous variables and Pearson chi-square test or Fisher's exact test for categorical variables.

Results

Patients with COVID-19 exhibited a higher prevalence of obesity (84.2% vs. 63.3%, P=0.048) and elevated direct bilirubin (DBIL) levels (44.1% vs. 19.2%, P=0.043) compared to those without COVID-19. Moreover, patients with Malignant AI, in contrast to Benign AI, showed higher normal total protein (TP) levels (28.8% vs. 57.1%, P=0.016) and larger tumor sizes (20 vs. 32.5mm, P=0.009). Univariate analysis identified low TP (OR=0.303, 95% CI=0.111-0.825, P=0.020) and tumor size (OR=1.045, 95% CI=1.011-1.080, P=0.009) as potential risk factors for multivariate analysis. A predictive model comprising clinical risk factors (tumor size and low TP) demonstrated an AUC of 0.754 (95% CI, 0.603-0.904) with a sensitivity of 0.75 and specificity of 0.775. The calibration curve revealed a bias-corrected AUC of 0.77.

Conclusion

No discernible differences in the clinical manifestations of adrenal incidentalomas were observed between cases with and without a history of COVID-19 infection. However, AI with larger tumor diameters and lower than normal levels of total protein exhibited a more pronounced malignant potential.

Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.

U-Shaped Association between Serum Chloride Levels and In-Hospital Mortality in Patients with Congestive Heart Failure in Intensive Care Units

Serum chloride level has clinical significance in the prognosis of heart failure. Little is known regarding the association between serum chloride levels and in-hospital mortality in patients with heart failure.This retrospective study used clinical data obtained from the Medical Information Mart for Intensive Care Database. The study cohort comprised patients who were categorized on the basis of their serum chloride levels, and the primary endpoint was in-hospital mortality. To assess the impact of serum chloride levels at the time of intensive care unit admission on in-hospital mortality, we used various statistical approaches, including multivariable logistic regression models, a generalized additive model, and a two-piecewise linear regression model. In addition, subgroup analysis was conducted to examine the robustness of the main findings.This study comprised 15,983 participants. When compared with the reference group (Q5), the groups with the highest (Q7) and lowest (Q1) blood chloride levels exhibited increased in-hospital mortality, with fully adjusted odds ratios (ORs) of 1.36 [95% confidence interval (CI): 1.08-1.71] and 1.25 (95% CI: 1-1.56), respectively. A U-shaped relationship was observed between blood chloride levels and in-hospital mortality, with the lowest risk observed at a threshold of 105.017 mmol/L. The effect sizes and corresponding CIs below and above the threshold were 0.969 (95% CI: 0.957-0.982) and 1.039 (95% CI: 1.002-1.076), respectively. Stratified analyses demonstrated the robustness of this correlation.The relationship between serum chloride levels and in-hospital mortality in patients with heart failure was U-shaped, with an inflection point of 105.017 mmol/L.

Elevated Levels of Cytotoxicity, Cytokines, and Anti-SARS-CoV-2 Antibodies in Mild Cases of COVID-19

Current evidence shows higher production of cytokines and antibodies against severe acute respiratory coronavirus 2 (SARS-CoV-2) in severe and critical cases of Coronavirus Disease 2019 (COVID-19) in comparison with patients with moderate or mild disease. A recent hypothesis proposes an important role of genotoxicity and cytotoxicity in the induction of the cytokine storm observed in some patients at later stages of the disease. Interestingly, in this study, we report significantly higher levels of interleukin (IL)-1β, IL-6, MCP-1, and IL-4 cytokines in mild COVID-19 patients versus severe cases, as well as a high frequency of karyorrhexis (median [Me] = 364 vs. 20 cells) and karyolysis (Me = 266 vs. 52 cells) in the mucosal epithelial cells of both groups of patients compared with uninfected individuals. Although we observed higher levels of anti-SARS-CoV-2 IgM and IgG antibodies in COVID-19 patients, IgM antibodies were significantly higher only in mild cases, for the N and the S viral antigens. High levels of IgG antibodies were observed in both mild and severe cases. Our results showed elevated concentrations of proinflammatory and anti-inflammatory cytokines in mild cases, which may reflect an active innate immune response and could be related to the higher IgM and IgG antibody levels found in those patients. In addition, we found that SARS-CoV-2 infection induces cytotoxic damage in the oral mucosa, highlighting the importance of studying the genotoxic and cytotoxic events induced by infection and its role in the pathophysiology of COVID-19.

Impact of ABO Blood Group, Hematological, and Biochemical Abnormalities on Incidence of Patients Infected with COVID-19

This study aimed to investigate the relationship between blood types and COVID-19 susceptibility and explore changes in blood variables, as well as their relationship with the occurrence of COVID-19. SARS-CoV-2 is a pandemic that has affected people's health and the global financial system. Since the initial confirmed case of COVID-19, people have been influenced worldwide with varying manifestations. Moreover, researchers have illustrated a link between ABO blood types and COVID-19 susceptibility and incidence. Research has also shown that ABO blood groups might play a role in estimating COVID-19 susceptibility and death. Our analysis revealed that blood type O might probably reduce vulnerability to the SARS-CoV-2 illness. On the contrary, people with blood type A are at a higher risk of SARS-CoV-2 infection. This study also evaluated liver biomarkers among COVID-19 patients, revealing significant abnormalities in the levels of alanine amino transferees, aspartate amino transferees, gamma-glutamyl transferees, and total bilirubin.

Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis

Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman's correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. IMPORTANCE Previous reports on the associations between COVID-19 and gut microbiome have been constrained by taxonomic-level analysis and overlook the interaction between microbes. By applying a genome-resolved, reference-free, guild-based metagenomic analysis, we demonstrated that the relationship between gut microbiota and COVID-19 is genome-specific instead of taxon-specific or even species-specific. Moreover, the COVID-19-associated genomes were not independent but formed two competing guilds, with Guild 1 potentially beneficial and Guild 2 potentially more detrimental to the host based on comparative genomic analysis. The dominance of Guild 2 over Guild 1 at time of admission was associated with hospitalized COVID-19 patients at high risk for more severe outcomes. Moreover, the guild-level microbiome signature is not only correlated with the symptom severity of COVID-19 patients, but also differentiates COVID-19 patients from pneumonia controls and healthy subjects across different studies. Here, we showed the possibility of using genome-resolved and guild-level microbiome signatures to identify hospitalized COVID-19 patients with a high risk of more severe outcomes at the time of admission.