Multiple immune function impairments in diabetic patients and their effects on COVID-19

Reliable Hallmarks and Biomarkers of Senescent Lymphocytes

The phenomenon of accumulation of senescent adaptive immunity cells in the elderly is attracting attention due to the increasing risk of global epidemics and aging of the global population. Elderly people are predisposed to various infectious and age-related diseases and are at higher risk of vaccination failure. The accumulation of senescent cells increases age-related background inflammation, "Inflammaging", causing lymphocyte exhaustion and cardiovascular, neurodegenerative, autoimmune and cancer diseases. Here, we present a comprehensive contemporary review of the mechanisms and phenotype of senescence in the adaptive immune system. Although modern research has not yet identified specific markers of aging lymphocytes, several sets of markers facilitate the separation of the aging population based on normal memory and exhausted cells for further genetic and functional analysis. The reasons for the higher predisposition of CD8+ T-lymphocytes to senescence compared to the CD4+ population are also discussed. We point out approaches for senescent-lymphocyte-targeting markers using small molecules (senolytics), antibodies and immunization against senescent cells. The suppression of immune senescence is the most relevant area of research aimed at developing anti-aging and anti-cancer therapy for prolonging the lifespan of the global population.

What’s old is new again: Insights into diabetic foot microbiome

Diabetes is a chronic disease that is considered one of the most stubborn global health problems that continues to defy the efforts of scientists and physicians. The prevalence of diabetes in the global population continues to grow to alarming levels year after year, causing an increase in the incidence of diabetes complications and health care costs all over the world. One major complication of diabetes is the high susceptibility to infections especially in the lower limbs due to the immunocompromised state of diabetic patients, which is considered a definitive factor in all cases. Diabetic foot infections continue to be one of the most common infections in diabetic patients that are associated with a high risk of serious complications such as bone infection, limb amputations, and life-threatening systemic infections. In this review, we discussed the circumstances associated with the high risk of infection in diabetic patients as well as some of the most commonly isolated pathogens from diabetic foot infections and the related virulence behavior. In addition, we shed light on the different treatment strategies that aim at eradicating the infection.

Effect of viral storm in patients admitted to intensive care units with severe COVID-19 in Spain: a multicentre, prospective, cohort study

BACKGROUND

The contribution of the virus to the pathogenesis of severe COVID-19 is still unclear. We aimed to evaluate associations between viral RNA load in plasma and host response, complications, and deaths in critically ill patients with COVID-19.

METHODS

We did a prospective cohort study across 23 hospitals in Spain. We included patients aged 18 years or older with laboratory-confirmed SARS-CoV-2 infection who were admitted to an intensive care unit between March 16, 2020, and Feb 27, 2021. RNA of the SARS-CoV-2 nucleocapsid region 1 (N1) was quantified in plasma samples collected from patients in the first 48 h following admission, using digital PCR. Patients were grouped on the basis of N1 quantity: VIR-N1-Zero (<1 N1 copies per mL), VIR-N1-Low (1-2747 N1 copies per mL), and VIR-N1-Storm (>2747 N1 copies per mL). The primary outcome was all-cause death within 90 days after admission. We evaluated odds ratios (ORs) for the primary outcome between groups using a logistic regression analysis.

FINDINGS

1068 patients met the inclusion criteria, of whom 117 had insufficient plasma samples and 115 had key information missing. 836 patients were included in the analysis, of whom 403 (48%) were in the VIR-N1-Low group, 283 (34%) were in the VIR-N1-Storm group, and 150 (18%) were in the VIR-N1-Zero group. Overall, patients in the VIR-N1-Storm group had the most severe disease: 266 (94%) of 283 patients received invasive mechanical ventilation (IMV), 116 (41%) developed acute kidney injury, 180 (65%) had secondary infections, and 148 (52%) died within 90 days. Patients in the VIR-N1-Zero group had the least severe disease: 81 (54%) of 150 received IMV, 34 (23%) developed acute kidney injury, 47 (32%) had secondary infections, and 26 (17%) died within 90 days (OR for death 0·30, 95% CI 0·16-0·55; p<0·0001, compared with the VIR-N1-Storm group). 106 (26%) of 403 patients in the VIR-N1-Low group died within 90 days (OR for death 0·39, 95% CI 0·26-0·57; p<0·0001, compared with the VIR-N1-Storm group).

INTERPRETATION

The presence of a so-called viral storm is associated with increased all-cause death in patients admitted to the intensive care unit with severe COVID-19. Preventing this viral storm could help to reduce poor outcomes. Viral storm could be an enrichment marker for treatment with antivirals or purification devices to remove viral components from the blood.

FUNDING

Instituto de Salud Carlos III, Canadian Institutes of Health Research, Li Ka-Shing Foundation, Research Nova Scotia, and European Society of Clinical Microbiology and Infectious Diseases.

TRANSLATION

For the Spanish translation of the abstract see Supplementary Materials section.

Survival analysis of patients with COVID-19 admitted at six hospitals in Uganda in 2021: a cohort study

Background

Assessing factors associated with mortality among COVID-19 patients could guide in developing context relevant interventions to mitigate the risk. The study aimed to describe mortality and associated factors among COVID-19 patients admitted at six health facilities in Uganda.

Methods

We reviewed medical records of patients admitted with COVID-19 between January 1st 2021 and December 31st 2021 in six hospitals in Uganda. Using Stata version 17.0, Kaplan Meier and Cox regression analyses were performed to describe the time to death and estimate associations between various exposures and time to death. Finally, accelerated failure time (AFT) models with a lognormal distribution were used to estimate corresponding survival time ratios.

Results

Out of the 1040 study participants, 234 (22.5%: 95%CI 12.9 to 36.2%) died. The mortality rate was 30.7 deaths per 1000 person days, 95% CI (26.9 to 35.0). The median survival time was 33 days, IQR (9–82). Factors associated with time to COVID-19 death included; age ≥ 60 years [adjusted hazard ratio (aHR) = 2.4, 95% CI: [1.7, 3.4]], having malaria test at admission [aHR = 2.0, 95% CI:[1.0, 3.9]], a COVID-19 severity score of severe/critical [aHR = 6.7, 95% CI:[1.5, 29.1]] and admission to a public hospital [aHR = 0.4, 95% CI:[0.3, 0.6]]. The survival time of patients aged 60 years or more is estimated to be 63% shorter than that of patients aged less than 60 years [adjusted time ratio (aTR) 0.37, 95% CI 0.24, 0.56]. The survival time of patients admitted in public hospitals was 2.5 times that of patients admitted in private hospitals [aTR 2.5 to 95%CI 1.6, 3.9]. Finally, patients with a severe or critical COVID-19 severity score had 87% shorter survival time than those with a mild score [aTR 0.13, 95% CI 0.03, 0.56].

Conclusion

In-hospital mortality among COVID-19 patients was high. Factors associated with shorter survival; age ≥ 60 years, a COVID-19 severity score of severe or critical, and having malaria at admission. We therefore recommend close monitoring of COVID-19 patients that are elderly and also screening for malaria in COVID-19 admitted patients.