Biomarkers and outcomes of COVID-19 hospitalisations: systematic review and meta-analysis

How can lessons from the COVID-19 pandemic enhance antimicrobial resistance surveillance and stewardship?

COVID-19 demanded urgent and immediate global attention, during which other public health crises such as antimicrobial resistance (AMR) increased silently, undermining patient safety and the life-saving ability of several antimicrobials. In 2019, WHO declared AMR a top ten global public health threat facing humanity, with misuse and overuse of antimicrobials as the main drivers in the development of antimicrobial-resistant pathogens. AMR is steadily on the rise, especially in low-income and middle-income countries across south Asia, South America, and Africa. Extraordinary circumstances often demand an extraordinary response as did the COVID-19 pandemic, underscoring the fragility of health systems across the world and forcing governments and global agencies to think creatively. The key strategies that helped to contain the increasing SARS-CoV-2 infections included a focus on centralised governance with localised implementation, evidence-based risk communication and community engagement, use of technological methods for tracking and accountability, extensive expansion of access to diagnostics, and a global adult vaccination programme. The extensive and indiscriminate use of antimicrobials to treat patients, particularly in the early phase of the pandemic, have adversely affected AMR stewardship practices. However, there were important lessons learnt during the pandemic, which can be leveraged to strengthen surveillance and stewardship, and revitalise efforts to address the AMR crisis.

Shock index in the emergency department as a predictor for mortality in COVID-19 patients: A systematic review and meta-analysis

Background

The shock index (SI) ratio serves as a straightforward predictor to identify patients who are either at risk of or experiencing shock. COVID-19 patients with shock face increased mortality risk and reduced chances of recovery. This review aims to determine the role of SI in the emergency department (ED) to predict COVID-19 patient outcomes.

Methods

The systematic search was conducted in PubMed, ProQuest, Scopus, and ScienceDirect on June 16, 2023. We included observational studies evaluating SI in ED and COVID-19 patient outcomes. Random-effect meta-analysis was done to generate odds ratios of SI as the predictor of intensive care unit (ICU) admission and mortality. The sensitivity and specificity of SI in predicting these outcomes were also pooled, and a summary receiver operating characteristics (sROC) curve was generated.

Results

A total of eight studies involving 4557 participants were included in the pooled analysis. High SI was found to be associated with an increased risk of ICU admission (OR 5.81 [95%CI: 1.18-28.58], p = 0.03). Regarding mortality, high SI was linked to higher rates of in-hospital (OR 7.45 [95%CI: 2.44-22.74], p = 0.0004), within 30-day (OR 7.34 [95%CI: 5.27-10.21], p < 0.00001), and overall (OR 7.52 [95%CI: 3.72-15.19], p < 0.00001) mortality. The sensitivity and specificity of SI for predicting ICU admission were 76.2% [95%CI: 54.6%-89.5%] and 64.3% [95%CI: 19.6%-93.0%], respectively. In terms of overall mortality, the sensitivity and specificity were 54.0% (95%CI: 34.3%-72.6%) and 85.9% (95%CI: 75.8%-92.3%), respectively, with only subtle changes for in-hospital and within 30-day mortality. Adjustment of SI cut-off to >0.7 yielded improved sensitivity (95%CI: 78.0% [59.7%-89.4%]) and specificity (95%CI: 76.8% [41.7%-93.9%]) in predicting overall mortality.

Conclusion

SI in emergency room may be a simple and useful triage instrument for predicting ICU admission and mortality in COVID-19 patients. Future well-conducted studies are still needed to corroborate the findings of this study.

Impact of the omicron phase on a highly advanced medical facility in Japan

Background

Eight waves of the coronavirus disease 2019 (COVID-19) epidemic have been observed in Japan. This retrospective study was conducted to clarify the clinical characteristics of pediatric COVID-19 patients.

Methods

We studied 121 patients admitted to the Jichi Children's Medical Center Tochigi between April 2020 and March 2023. Incidence of pediatric COVID-19 in Tochigi Prefecture was used to examine hospitalization and severe illness rates.

Results

The mean age of the patients was 3 years and 8 months. One hundred and eleven patients (91.7%) were hospitalized after January 2022 (after the 6th wave), when the Omicron strain became endemic in Japan. Convulsions occurred in 30 patients (24.8%), all of whom were admitted after the 6th wave. Twenty-three of the 30 patients had no underlying disease. Eleven patients (9.1%) were diagnosed with acute encephalopathy. One patient died due to hemorrhagic shock and encephalopathy syndrome and two had sequelae after the 6th wave. The patient who died due to encephalopathy had hypercytokinemia. In the Tochigi Prefecture, the number of pediatric COVID-19 patients increased after the 6th wave, but the hospitalization rate declined. The rate of severe illness did not change before the end of 5th and after the 6th wave.

Conclusion

Although the rate of severe illness in patients with pediatric COVID-19 did not increase after the 6th wave, some patients had complicated critical illnesses. Systemic inflammatory reaction was considered to have been associated with the severe encephalopathy.

Effect of antiviral and immunomodulatory treatment on a cytokine profile in patients with COVID-19

Background

The severity of COVID-19 is associated with an elevated level of a variety of inflammatory mediators. Increasing evidence suggests that the Th17 response contributes to the severity of COVID-19 pneumonia, whereas Th22 response plays a regulatory role in SARS-CoV-2 infection. Two main types of available COVID-19 treatments are antivirals and immunomodulatory drugs; however, their effect on a cytokine profile is yet to be determined.

Methods

This study aim to analyse a cytokine profile in peripheral blood from patients with COVID-19 (n=44) undergoing antiviral or/and immunomodulatory treatment and healthy controls (n=20). Circulating CD4+ and CD8+ T cells and their intracellular expression of IL-17A and IL-22 were assessed by flow cytometry.

Results

Initial results showed an overexpression of IL-17F, IL-17A, CCL5/RANTES, GM-CSF, IL-4, IL-10, CXCL-10/IP-10 and IL-6 in COVID-19 patients compared to healthy controls. Treatment with remdesivir resulted in a significant decline in concentrations of IL-6, IL-10, IFN-alpha and CXCL10/IP-10. Immunomodulatory treatment contributed to a significant downregulation of IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 as well as upregulation of IL-22 and IL-1 beta. A combination of an antiviral and immunomodulatory treatment resulted in a significant decrease in IL-17F, IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 levels as well as an increase in IL-17A and IL-1 beta. We found significantly higher percentage of both CD4+ and CD8+ T cells producing IL-17A and CD4+ T cells producing IL-22 in patients with COVID-19.

Conclusion

Administration of antiviral or/and immunomodulatory treatment resulted in a significant downregulation of pro-inflammatory cytokine expression and an upregulation of T cell absolute counts in most cases, thus showing effectiveness of treatment in COVID-19. SARS-CoV-2 infection induced cytokine overexpression in hospitalized patients with COVID-19 as well as lymphopenia, particularly a decrease in CD4+ and CD8+ T cell counts. Moreover, despite the reduced counts of CD4+ and CD8+ T cells, both subsets showed overactivation and increased expression of IL-17A and IL-22, thus targeting Th17 response might alleviate inflammatory response in severe disease.

One biomarker does not fit all: tailoring anti-infective therapy through utilization of procalcitonin and other specific biomarkers

INTRODUCTION

Considering the ongoing increase in antibiotic resistance, the importance of judicious use of antibiotics through reduction of exposure is crucial. Adding procalcitonin (PCT) and other biomarkers to pathogen-specific tests may help to further improve antibiotic therapy algorithms and advance antibiotic stewardship programs to achieve these goals.

AREAS COVERED

In recent years, several trials have investigated the inclusion of biomarkers such as PCT into clinical decision-making algorithms. For adult patients, findings demonstrated improvements in the individualization of antibiotic treatment, particularly for patients with respiratory tract infections and sepsis. While most trials were performed in hospitals with central laboratories, point-of-care testing might further advance the field by providing a cost-effective and rapid diagnostic tool in upcoming years. Furthermore, novel biomarkers including CD-64, presepsin, Pancreatic stone and sTREM-1, have all shown promising results for increased accuracy of sepsis diagnosis. Availability of these markers however is currently still limited and there is insufficient evidence for their routine use in clinical care.

EXPERT OPINION

In addition to new host-response markers, combining such biomarkers with pathogen-directed diagnostics present a promising strategy to increase algorithm accuracy in differentiating between bacterial and viral infections. Recent advances in microbiologic testing using PCR or nucleic amplification tests may further improve the diagnostic yield and promote more targeted pathogen-specific antibiotic therapy.

COVID-19 and metabolic syndrome

Convergence of the two pandemics: metabolic syndrome and COVID-19 over last two years has posed unprecedented challenges to individuals as well as healthcare systems. Epidemiological data suggest a close association between metabolic syndrome and COVID-19 while variety of possible pathogenic connections have been proposed while some have been proven. Despite the evidence of high risk for adverse COVID-19 outcomes in people with metabolic syndrome, little is known about the differences in efficacy and safety among people with metabolic syndrome and without. It is important to recognize that among people with metabolic syndrome This review summarizes the current knowledge and epidemiological evidence on the association between metabolic syndrome and adverse COVID-19 outcomes, pathogenic interrelationships, management considerations for acute COVID-19 and post-COVID sequalae and sustaining care of people living with metabolic syndrome with appraisal of evidence and gaps in knowledge.

Point-of-care pancreatic stone protein measurement in critically ill COVID-19 patients

INTRODUCTION

Pancreatic stone protein (PSP) is a novel biomarker that is reported to be increased in pneumonia and acute conditions. The primary aim of this study was to prospectively study plasma levels of PSP in a COVID-19 intensive care unit (ICU) population to determine how well PSP performed as a marker of mortality in comparison to other plasma biomarkers, such as C reactive protein (CRP) and procalcitonin (PCT).

METHODS

We collected clinical data and blood samples from COVID-19 ICU patients at the time of admission (T0), 72 h later (T1), five days later (T2), and finally, seven days later. The PSP plasma level was measured with a point-of-care system; PCT and CRP levels were measured simultaneously with laboratory tests. The inclusion criteria were being a critical COVID-19 ICU patient requiring ventilatory mechanical assistance.

RESULTS

We enrolled 21 patients and evaluated 80 blood samples; we found an increase in PSP plasma levels according to mixed model analysis over time (p < 0.001), with higher levels found in the nonsurvivor population (p < 0.001). Plasma PSP levels achieved a statistically significant result in terms of the AUROC, with a value higher than 0.7 at T0, T1, T2, and T3. The overall AUROC of PSP was 0.8271 (CI (0.73-0.93), p < 0.001). These results were not observed for CRP and PCT.

CONCLUSION

These first results suggest the potential advantages of monitoring PSP plasma levels through point-of-care technology, which could be useful in the absence of a specific COVID-19 biomarker. Additional data are needed to confirm these results.

Biomarkers of immunothrombosis and polymorphisms of IL2, IL6, and IL10 genes as predictors of the severity of COVID-19 in a Kazakh population

OBJECTIVES

To study the role of biological markers of immunothrombosis and polymorphisms of cytokine genes IL2, IL6, IL10 and their influence on the severity of COVID-19 in a Kazakh population.

METHODS

A total of 301 patients of Kazakh nationality with a confirmed diagnosis of COVID-19 participated in the retrospective study, including 142 patients with severe and 159 with a mild course. Single nucleotide polymorphisms IL2R rs1801274, IL6 rs2069840, and IL10 rs1800872 were genotyped by real-time PCR. Activated partial thromboplastin time, normalized ratio, prothrombin index, prothrombin time, fibrinogen prothrombin time, fibrinogen, D-dimer, and C-reactive protein analysis were also conducted.

RESULTS

The average age of patients with severe COVID-19 is higher than of patients with mild COVID-19 (p = 0.03). The findings showed that fibrinogen, D-dimer, and C-reactive protein were significantly greater in the group of patients with severe COVID-19 (p = 0.0001). A very strong correlation between the severity of COVID-19 with the D-dimer and C-reactive protein (p = 0.9) (p = 0.02) was found.

CONCLUSION

The results of our study confirm that D-dimer, fibrinogen, and CRP are biomarkers of inflammation and hypercoagulation that serve as predictors of immunothrombosis affecting the severity of COVID-19. D-dimer is also associated with IL10 rs1800872 gene polymorphism in the Kazakh population with severe COVID-19.

Post-acute (long) COVID-19 quality of life: validation of the German version of (PAC19QoL) instrument

Purpose

The aim of our study was to validate a German translation of the post-acute (long) COVID-19 quality of life (PAC-19QoL) instrument among German patients with long COVID-19 syndrome.

Patients and methods

The PAC-19QoL instrument was translated into the German language and administrated to patients with long COVID-19 syndrome. Cronbach's alpha coefficient was used to analyze the internal consistency of the instrument. Construction validity was evaluated by using Pearson's correlation coefficient and Spearman's rank correlation. Scores of patients and controls were compared using the Mann-Whitney U-test.

Results

A total of 45 asymptomatic and 41 symptomatic participants were included. In total, 41 patients with long COVID-19 syndrome completed the PAC-19QoL and EQ-5D-5L questionnaires. PAC-19QoL domain scores were significantly different between symptomatic and asymptomatic participants. All items achieved a Cronbach's alpha >0.7. There was a significant correlation between all domains on the test (p < 0.001), with the highest correlation between total (r = 0.994) and domain 1 (r = 0.991). Spearman's rank correlation analysis confirmed that the instrument items correlated with the objective PAC-19QoL examination findings.

Conclusion

The German version of the instrument is valid and reliable and can be a suitable tool for research and daily clinical practice among patients with long COVID-19 syndrome.

Proteomic analysis of circulating immune cells identifies cellular phenotypes associated with COVID-19 severity

Certain serum proteins, including C-reactive protein (CRP) and D-dimer, have prognostic value in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nonetheless, these factors are non-specific, providing limited mechanistic insight into the peripheral blood mononuclear cell (PBMC) populations that drive the pathogenesis of severe COVID-19. To identify cellular phenotypes associated with disease, we performed a comprehensive, unbiased analysis of total and plasma-membrane PBMC proteomes from 40 unvaccinated individuals with SARS-CoV-2, spanning the whole disease spectrum. Combined with RNA sequencing (RNA-seq) and flow cytometry from the same donors, we define a comprehensive multi-omic profile for each severity level, revealing that immune-cell dysregulation progresses with increasing disease. The cell-surface proteins CEACAMs1, 6, and 8, CD177, CD63, and CD89 are strongly associated with severe COVID-19, corresponding to the emergence of atypical CD3+CD4+CEACAM1/6/8+CD177+CD63+CD89+ and CD16+CEACAM1/6/8+ mononuclear cells. Utilization of these markers may facilitate real-time patient assessment by flow cytometry and identify immune populations that could be targeted to ameliorate immunopathology.

Immunohematologic Biomarkers in COVID-19: Insights into Pathogenesis, Prognosis, and Prevention

Coronavirus disease 2019 (COVID-19) has had profound effects on the health of individuals and on healthcare systems worldwide. While healthcare workers on the frontlines have fought to quell multiple waves of infection, the efforts of the larger research community have changed the arch of this pandemic as well. This review will focus on biomarker discovery and other efforts to identify features that predict outcomes, and in so doing, identify possible effector and passenger mechanisms of adverse outcomes. Identifying measurable soluble factors, cell-types, and clinical parameters that predict a patient's disease course will have a legacy for the study of immunologic responses, especially stimuli, which induce an overactive, yet ineffectual immune system. As prognostic biomarkers were identified, some have served to represent pathways of therapeutic interest in clinical trials. The pandemic conditions have created urgency for accelerated target identification and validation. Collectively, these COVID-19 studies of biomarkers, disease outcomes, and therapeutic efficacy have revealed that immunologic systems and responses to stimuli are more heterogeneous than previously assumed. Understanding the genetic and acquired features that mediate divergent immunologic outcomes in response to this global exposure is ongoing and will ultimately improve our preparedness for future pandemics, as well as impact preventive approaches to other immunologic diseases.

Phase 2, randomized, double-blind, placebo-controlled multi-center trial of the clinical and biological effects of anti-CD14 treatment in hospitalized patients with COVID-19 pneumonia

BACKGROUND

Severe COVID-19 is associated with innate immunopathology, and CD14, a proximal activator of innate immunity, has been suggested as a potential therapeutic target.

METHODS

We conducted the COVID-19 anti-CD14 Treatment Trial (CaTT), a Phase II randomized, double-blind, placebo-controlled trial at 5 US-sites between April 12, 2021 and November 30, 2021 (NCT04391309). Hospitalized adults with COVID-19 requiring supplemental oxygen (<30 LPM) were randomized 1:1 to receive 4 daily doses of intravenous IC14, an anti-CD14 monoclonal antibody, or placebo. All participants received remdesivir. The primary outcome was time-to-resolution of illness, defined as improvement on the 8-point NIH-Ordinal COVID-19 Scale to category ≤3. Secondary endpoints were safety and exploratory endpoints were pro-inflammatory and antiviral mediators in serum on days 0-5 & 7. The trial was stopped after 40 patients were randomized and treated due to slow enrollment.

FINDINGS

40 participants were randomized and treated with IC14 (n = 20) or placebo (n = 20). The median time-to-recovery was 6 days (95% CI, 5-11) in the IC14 group vs. 5 days (95% CI, 4-10) in the Placebo group (recovery rate ratio: 0.77 (95% CI, 0.40, 1.48) (log-rank p = 0.435). The number of adverse events was similar in each group, and no IC14-attributable secondary infections occurred. In repeated-measures mixed-effects analyses, IC14 treatment increased serum sCD14 concentrations, an expected pharmacodynamic effect. Pre-planned, exploratory analyses suggested that IC14 treatment decreased the trajectories of circulating MIP-1β and TNF-α.

INTERPRETATION

IC14 treatment did not improve time-to-resolution of illness in hypoxemic patients with COVID-19 in this small trial. Results of exploratory analyses suggested IC14 had biologic effects that warrant future clinical investigation.

FUNDING

National Institute of Allergy and Infectious Diseases.

The Relationship Between Decreased CD-8 T-Cells and Mortality in Patients with COVID-19 Pneumonia in the Intensive Care Unit, A Retrospective Study

Objective

CD-8 T-cells are responsible for the clearance of virally infected cells. In patients with Coronavirus disease-2019 (COVID-19) pneumonia, there are quantitative reductions and functional impairments in T-cells. Low CD-8 T-cell levels cause worse clinical situations. In this study, the relationship between decreased CD-8 T-cells and mortality in patients with COVID-19 pneumonia in the intensive care unit (ICU) was investigated.

Methods

In this multicenter retrospective study, 277 patients were analyzed. Demographic data, ICU admission scores, blood gas levels, laboratory samples, and outcomes were recorded. Statistical Package for the Social Sciences version 28 was used for statistical analysis.

Results

Two hundred forty of 277 patients were included in the study. The mortality rate was 43.3%. In non-survivors, median values of age, Charlson comorbidity index, Acute Physiology and Chronic Health Evaluation II (APACHE-II), procalcitonin, leukocyte count, neutrophil count, neutrophil-lymphocyte count ratio, and duration of invasive mechanical ventilation were significantly higher, whereas median values of PaO₂-FiO₂ ratio, lymphocyte count, CD-4, and CD-8 T-cells were significantly lower than those in survivors. In the multivariate Cox regression model, the risk of mortality increased 1.04-fold (1.02-1.06) and 1.05-fold (1.01-10.8) by every one unit increase in age and APACHE-II, respectively, whereas it decreased 0.71-fold (0.58-0.87) by every hundred increase in CD-8 T-cells P < 0.001, P=0.007 and P=0.001 respectively.

Conclusion

According to our findings, age, APACHE-II, and CD-8 T-cell levels seem to be independent risk factors for mortality in patients with COVID-19 pneumonia in the ICU.

Comparison of C-reactive protein with distinct hyperinflammatory biomarkers in association with COVID-19 severity, mortality and SARS-CoV-2 variants

C-reactive protein (CRP) has been one of the most investigated inflammatory-biomarkers during the ongoing COVID-19 pandemics caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The severe outcome among patients with SARS-CoV-2 infection is closely related to the cytokine storm and the hyperinflammation responsible for the acute respiratory distress syndrome and multiple organ failure. It still remains a challenge to determine which of the hyperinflammatory biomarkers and cytokines are the best predictors for disease severity and mortality in COVID-19 patients. Therefore, we evaluated and compared the outcome prediction efficiencies between CRP, the recently reported inflammatory modulators (suPAR, sTREM-1, HGF), and the classical biomarkers (MCP-1, IL-1β, IL-6, NLR, PLR, ESR, ferritin, fibrinogen, and LDH) in patients confirmed with SARS-CoV-2 infection at hospital admission. Notably, patients with severe disease had higher serum levels of CRP, suPAR, sTREM-1, HGF and classical biomarkers compared to the mild and moderate cases. Our data also identified CRP, among all investigated analytes, to best discriminate between severe and non-severe forms of disease, while LDH, sTREM-1 and HGF proved to be excellent mortality predictors in COVID-19 patients. Importantly, suPAR emerged as a key molecule in characterizing the Delta variant infections.

Distinct Clinical Presentations and Outcomes of Hospitalized Adults with the SARS-CoV-2 Infection Occurring during the Omicron Variant Surge

The COVID-19 Omicron variant has imposed a tremendous burden on healthcare services. We characterized the types of the Omicron variant-associated hospitalizations and their associations with clinical outcomes. Consecutive adults hospitalized with COVID-19 during the Omicron variant surge period of 1-14 January 2022, were classified into one of three groups based on their clinical presentations on admission: Group 1-primary COVID-19; Group 2-extrapulmonary manifestations of COVID-19; and Group 3-incidental COVID-19. Of the 500 patients who were hospitalized, 51.4% fell into Group 1, 16.4% into Group 2, and 32.2% into Group 3. The patients in Groups 1 and 2 were older, with higher proportions of comorbidities than patients in Group 3. The Group 1 patients had the highest mortality rate (15.6%), followed by Group 2 (8.5%), and Group 3 (0.6%), with adjusted odds ratios (OR) of 22.65 (95% confidence interval [CI], 2.75-239.46; p = 0.004) and 10.95 (95% CI, 1.02-117.28; p = 0.048), respectively, compared to Group 3. Those in Group 1 showed a greater utilization of intensive care services (15.9%), followed by Group 2 (10.9%), and Group 3 (2.5%), with adjusted ORs of 7.95 (95% CI, 2.52-25.08; p < 0.001) and 5.07 (95% CI, 1.34-19.15; p = 0.017), respectively, compared to Group 3. The patients in Groups 1 and 2 had longer hospitalization stays than the patients in Group 3 (p < 0.001 and p = 0.002, respectively). Older age (≥65 years) was an independent factor associated with longer hospital stays (OR = 1.72, 95% CI, 1.07-2.77). These findings can help hospitals prioritize patient care and service planning for future SARS-CoV-2 variants.

MR-proADM as Prognostic Factor of Outcome in COVID-19 Patients

BACKGROUND

Serum mid-regional proadrenomedullin (MR-proADM) has emerged as a marker of organ failure (mainly lungs and kidneys) and poor prognosis in patients admitted to intensive care (IC); some reports also suggest it and other markers, such as Krebs von den Lungen-6 (KL-6) and interleukin-6 (IL-6), as a prognostic biomarker of COVID-19. The aim of the study was to evaluate the performance MR-proADM in hospitalized COVID-19 patients for predicting in-hospital mortality and need for non-invasive or invasive respiratory support.

METHODS

We enrolled 74 patients hospitalized in the COVID Unit of Siena Hospital from March to May 2020, for whom serum samples were available on admission for assay of MR-proADM, KL-6 and IL-6. Demographic data, comorbidities, medical history and clinical laboratory data on days 1-3 of admission and Simplified Acute Physiology Score and Simplified Organ Failure Assessment scores calculated at day 1 were collected retrospectively, as well as mortality and IC admission data.

RESULTS

12 patients died in hospital (16%) and 14 patients were admitted to IC (19%). Serum concentrations of MR-proADM on admission and on day 1 were higher among non-survivors than among survivors (p = 0.015 and p = 0.045, respectively), while those on day 3 were not significantly different. Patients needing respiratory support had higher MR-proADM concentrations on admission than the others (p = 0.046), and those requiring invasive mechanical ventilation had higher MR-proADM on day 1 (p = 0.017). Serum concentrations of KL-6 and IL-6 were significantly higher in non-survivors (p = 0.03 and p = 0.004, respectively). ROC curve analysis showed that serum MR-proADM on day 1 had the best accuracy in predicting death and/or IC admission (AUC = 0.9583, p = 0.0006); the combination of all three biomarkers further improved the accuracy of prediction of death or IC admission (AUC = 0.9793; p = 0.00004).

CONCLUSIONS

Our data sustain the potential of serum MR-proADM as a reliable prognostic biomarker of hospitalized COVID-19 patients and confirms the utility of the three markers in the management and risk stratification of hospitalized patients. The markers are collected mini-invasively and are quick to analyze and cost-effective.

Rotational Thromboelastometry (ROTEM®) in Relation to Inflammatory Biomarkers and Clinical Outcome in COVID-19 Patients

Background: The pathogenesis of hypercoagulability in COVID-19 patients is complex and not fully understood. Rotational thromboelastometry (ROTEM^®) is a viscoelastic method that allows the definition of a patient's hemostatic profile. This study aimed to assess the relationship between ROTEM^® parameters, the profile of inflammatory cytokines, and clinical outcomes in COVID-19 patients. Methods: A total of 63 participants (n = 29 symptomatic non-ICU COVID-19 patients, and n = 34 healthy controls) were prospectively included in the study. We assessed the relationship between the parameters of three ROTEM^® tests (NATEM^®, EXTEM^®, and FIBTEM^®) and levels of CRP, interleukin-8, interleukin-1β, interleukin-6, interleukin-10, tumor necrosis factor, interleukin 12p70, and clinical outcomes. Results: ROTEM^® indicated hypercoagulability in COVID-19 patients in all the tests performed. The levels of all inflammatory cytokines were significantly higher in COVID-19 patients. NATEM more frequently detected hypercoagulability in COVID-19 patients compared to EXTEM. The strongest correlations with inflammatory biomarkers and CT severity score were with FIBTEM parameters. The elevated maximum clot elasticity (MCE) in FIBTEM was the strongest predictor of poor outcomes. Conclusions: Increased FIBTEM MCE may be associated with greater severity of COVID-19. Non-activated ROTEM (NATEM test) seems to be more valuable for detecting hypercoagulability in COVID-19 patients compared to the tissue factor activated test (EXTEM).

A novel scale based on biomarkers associated with COVID-19 severity can predict the need for hospitalization and intensive care, as well as enhanced probabilities for mortality

Prognostic scales may help to optimize the use of hospital resources, which may be of prime interest in the context of a fast spreading pandemics. Nonetheless, such tools are underdeveloped in the context of COVID-19. In the present article we asked whether accurate prognostic scales could be developed to optimize the use of hospital resources. We retrospectively studied 467 files of hospitalized patients after COVID-19. The odds ratios for 16 different biomarkers were calculated, those that were significantly associated were screened by a Pearson's correlation, and such index was used to establish the mathematical function for each marker. The scales to predict the need for hospitalization, intensive-care requirement and mortality had enhanced sensitivities (0.91 CI 0.87-0.94; 0.96 CI 0.94-0.98; 0.96 CI 0.94-0.98; all with p < 0.0001) and specificities (0.74 CI 0.62-0.83; 0.92 CI 0.87-0.96 and 0.91 CI 0.86-0.94; all with p < 0.0001). Interestingly, when a different population was assayed, these parameters did not change considerably. These results show a novel approach to establish the mathematical function of a marker in the development of highly sensitive prognostic tools, which in this case, may aid in the optimization of hospital resources. An online version of the three algorithms can be found at: http://benepachuca.no-ip.org/covid/index.php.

Anemia as a risk factor for disease progression in patients admitted for COVID-19: data from a large, multicenter cohort study

In respiratory infections, anemia is both a consequence of acute inflammation and a predictor of poor clinical outcomes. There are few studies investigating the role of anemia in COVID-19, suggesting a potential role in predicting disease severity. In this study, we aimed to assess the association between the presence of anemia at admission and incidence of severe disease and death in patients hospitalized for COVID-19. Data from all adult patients admitted for COVID-19 in University Hospital "P. Giaccone" Palermo, and University Hospital of Bari, Italy, were retrospectively collected from 1st of September 2020 to 31 August 2022. The association between anemia (defined as Hb < 13 g/dl and < 12 g/dl in males and females, respectively), in-hospital mortality and severe COVID-19 was tested using a Cox's regression analysis. Severe COVID-19 forms were defined as admission to intensive or sub-intensive care unit or a qSOFAscore ≥ 2 or CURB65scores ≥ 3. p values were calculated using the Student's t test for continuous variables and the Mantel-Haenszel Chi-square test for categorical ones. The association between anemia and the mortality was made using a Cox's regression analysis, adjusted, in two models, for the potential confounders and using a propensity score. Among the 1562 patients included in the analysis, prevalence of anemia was 45.1% (95% CI 43-48%). Patients with anemia were significantly older (p < 0.0001), reported more co-morbidities, and presented higher baseline levels of procalcitonin, CRP, ferritin and IL-6. Overall, the crude incidence of mortality was about four times higher in patients with anemia compared to those without. After adjusting for 17 potential confounders, the presence of anemia significantly increased the risk of death (HR = 2.68; 95% CI: 1.59-4.52) and of risk of severe COVID-19 (OR = 2.31; 95% CI: 1.65-3.24). The propensity score analysis substantially confirmed these analyses. Our study provides evidence that, in patients hospitalized for COVID-19, anemia is both associated with a more pronounced baseline pro-inflammatory profile and higher incidence of in-hospital mortality and severe disease.

Stress levels, psychological symptoms, and C-reactive protein levels in COVID-19: A cross-sectional study

BACKGROUND

Although many studies have pointed out a possible relationship between COVID-19 and the presence of psychiatric disorders, the majority of the studies have significant limitations. This study investigates the influence of COVID-19 infection on mental health.

METHODS

This cross-sectional study included an age- and sex-matched sample of adult individuals positive (cases) or negative (controls) for COVID-19. We evaluated the presence of psychiatric conditions and C-reactive protein (CRP).

RESULTS

Findings showed greater severity of depressive symptoms, higher levels of stress, and greater CRP in cases. The severity of depressive and insomnia symptoms, as well as the CRP were more remarkable in individuals with moderate/severe COVID-19. We found a positive correlation between stress and severity of anxiety, depression, and insomnia in individuals with or without COVID-19. There was a positive correlation between CRP levels and severity of depressive symptoms in cases and controls, and a positive correlation between CRP levels and the severity of anxiety symptoms and stress levels only in individuals with COVID-19. Individuals with COVID-19 and depression had greater CRP than those with COVID-19 without current major depressive disorder.

LIMITATIONS

We cannot infer causality because this is a cross-sectional study, and the majority of COVID-19 sample was asymptomatic or had mild symptoms, which may limit the generalizability of our findings for moderate/severe cases.

CONCLUSIONS

Individuals with COVID-19 showed greater severity of psychological symptoms, which may impact on the development of psychiatric disorders in the future. CPR seem to be a promising biomarker for earlier detection of post-COVID depression.

The Relationship Between Laboratory Findings and Mortality in COVID-19 Patients Requiring Intensive Care

INTRODUCTION

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shows a wide clinical manifestation from asymptomatic infection to life-threatening respiratory failure. This study aimed to determine the relationship between the survival and demographic data, comorbidity status, and laboratory parameters of coronavirus disease 2019 (COVID-19) patients requiring intensive care.

MATERIAL AND METHODS

We retrospectively analyzed 236 patients requiring intensive care whose diagnosis was confirmed by the SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test. The patients were divided into two groups in terms of survival. Demographic data; procalcitonin and C-reactive protein (CRP) levels; leukocyte, lymphocyte, and neutrophil counts in hemogram and neutrophil-to-lymphocyte ratio (NLR) levels; and lower respiratory and blood cultures were examined, and the relationships between these parameters and survival were evaluated with hypothesis testing.

RESULTS

 In the study, 156 (66.1%) males and 80 (33.9%) females, a total of 236 patients, were included. Sixty-seven (28.3%) surviving patients were determined as Group 1, and 169 (71.7%) deceased patients were determined as Group 2. A statistically significant difference was found between the groups in terms of mean age (p<0.001) and gender distribution (p=0.011). In laboratory parameters, a significant difference was observed between the groups in lymphocyte count (p=0.001), NLR (p<0.001), and procalcitonin levels (p<0.001). Although leukocyte (p=0.075), neutrophil (p=0.031), and CRP (p=0.112) levels were higher in Group 2, there was no statistical difference. Mortality was found to be higher in patients with comorbidity (p=0.012) or co-infection (p=0.002).

CONCLUSION

High levels of neutrophil count, NLR, and procalcitonin; low lymphocyte count; the presence of comorbidity; and secondary bacterial infection were found to be associated with mortality in COVID-19 patients in the intensive care unit.

Ovarian Cancer Biomarkers in the COVID-19 Era

Ovarian Cancer (OC) diagnosis is entrusted to CA125 and HE4. Since the latter has been found increased in COVID-19 patients, in this study, we aimed to evaluate the influence of SARS-CoV-2 infection on OC biomarkers. HE4 values above the cut-off were observed in 65% of OC patients and in 48% of SARS-CoV-2-positive patients (not oncologic patients), whereas CA125 values above the cut-off were observed in 71% of OC patients and in 11% of SARS-CoV-2 patients. Hence, by dividing the HE4 levels into quartiles, we can state that altered levels of HE4 in COVID-19 patients were mostly detectable in quartile I (151-300 pmol/L), while altered levels in OC patients were mostly clustered in quartile III (>600, pmol/L). In light of these observations, in order to better discriminate women with ovarian cancer versus those with COVID-19, we established a possible HE4 cut-off of 328 pmol/L by means of a ROC curve. These results demonstrate that the reliability of HE4 as a biomarker in ovarian cancer remains unchanged, despite COVID-19 interference; moreover, it is important for a proper diagnosis that whether the patient has a recent history of SARS-CoV-2 infection is determined.

Association of Monocyte Distribution Width with the Need for Respiratory Support in Hospitalized COVID-19 Patients

Background

The monocyte distribution width (MDW), a novel inflammatory biomarker reflecting morphological changes in response to inflammation, has been shown to be useful in identifying COVID-19 infection or predicting death. However, data on the association with predicting the need for respiratory support are still limited. The aim of this study was to determine the association of MDW with the need for respiratory support in patients with SARS-CoV-2 infection.

Patients and methods

This is a single-center retrospective cohort study. Consecutive hospitalized COVID-19 adult patients who presented at the outpatient department (OPD) or emergency department (ED) between May and August 2021 were enrolled. Respiratory support was defined as any one of the following: conventional oxygen therapy, high-flow oxygen nasal cannula, noninvasive, or invasive mechanical ventilation. The performance of MDW was measured using the area under the receiver operating characteristic (AuROC) curve.

Results

Of the 250 enrolled patients, 122 (48.8%) patients received respiratory support. The mean MDW was significantly higher in the respiratory support group: 27.2 ± 4.6 vs 23.6 ± 4.1 (p < 0.001). The MDW ≥ 25 had the best AuROC characteristics of 0.70 (95% CI: 0.65-0.76).

Conclusions

The MDW is a potential biomarker that may aid in identifying individuals at risk of requiring oxygen support in COVID-19 and can be easily implemented in clinical practice.

How to cite this article

Daorattanachai K, Hirunrut C, Pirompanich P, Weschawalit S, Srivilaithon W. Association of Monocyte Distribution Width with the Need for Respiratory Support in Hospitalized COVID-19 Patients. Indian J Crit Care Med 2023;27(5):352-357.

Multiplex sensing of IL-10 and CRP towards predicting critical illness in COVID-19 infections

Here we present a sensitive method for the detection and quantification of two (IL -10 and CRP) immuno-responsive biomarkers in various biofluids. The significance of these immune response biomarkers lies in them displaying elevated levels in critically ill COVID -19 patients. The developed electrochemical sensor contains a gold film electrode with ZnO nanoparticles deposited on its surface to increase the surface area of the working electrode while integrating antibody-antigen interactions into the detection system. This multiplex biosensor has a wide linear range from 0.01 μg/mL to 100 μg/mL and 0.1 pg/mL to 1000 pg/mL for CRP and IL10, respectively. The cross-reactivity of this multiplex sensor platform was evaluated between these two proteins and was <20%. Recovery studies were performed by spiking known concentrations in serum and urine samples. The recovery was calculated and ranged from 80% to 100%, confirming clinical applicability. This electrochemical sensing platform can aid in the early screening of COVID -19 patients to monitor for the development of more serious and potentially lethal symptoms.

Tools and factors predictive of the severity of COVID-19

The outbreak of the novel coronavirus infection caused worldwide confusion. The problem with this infection is that it causes severe illness in some patients, resulting in a high rate of death if appropriate treatment is not given. If patients with severe illness that requires treatment are appropriately identified, treatment can be focused on these patients. However, in the early days of the COVID-19 outbreak, the inability to predict and diagnose the disease led to hospitals being overwhelmed. Therefore, various methods for the diagnosis of severe disease were developed early on, and various methods are still being investigated to predict high-risk patients. The currently available prediction methods are divided into those that predict the onset of severe disease and those used to determine the severity of the disease. Specifically, the main methods include genetic factors, serum humoral factors, laboratory tests, and diagnostic imaging. Since each of these factors has different features, using them in combination is likely to be advantageous.

Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients: Results from a Cohort Observational Study

Purpose: COVID-19 presents complex pathophysiology, and evidence collected points towards an intricate interaction between viral-dependent and individual immunological mechanisms. Identifying phenotypes through clinical and biological markers may provide a better understanding of the subjacent mechanisms and an early patient-tailored characterization of illness severity. Methods: A multicenter prospective cohort study was performed in 5 hospitals in Portugal and Brazil for one year between 2020-2021. All adult patients with an Intensive Care Unit admission with SARS-CoV-2 pneumonia were eligible. COVID-19 was diagnosed using clinical and radiologic criteria with a SARS-CoV-2 positive RT-PCR test. A two-step hierarchical cluster analysis was made using several class-defining variables. Results: 814 patients were included. The cluster analysis revealed a three-class model, allowing for the definition of three distinct COVID-19 phenotypes: 407 patients in phenotype A, 244 patients in phenotype B, and 163 patients in phenotype C. Patients included in phenotype A were significantly older, with higher baseline inflammatory biomarkers profile, and a significantly higher requirement of organ support and mortality rate. Phenotypes B and C demonstrated some overlapping clinical characteristics but different outcomes. Phenotype C patients presented a lower mortality rate, with consistently lower C-reactive protein, but higher procalcitonin and interleukin-6 serum levels, describing an immunological profile significantly different from phenotype B. Conclusions: Severe COVID-19 patients exhibit three different clinical phenotypes with distinct profiles and outcomes. Their identification could have an impact on patients' care, justifying different therapy responses and inconsistencies identified across different randomized control trial results.

A Retrospective Assessment of Sputum Samples and Antimicrobial Resistance in COVID-19 Patients

Data on bacterial or fungal pathogens and their impact on the mortality rates of Western Romanian COVID-19 patients are scarce. As a result, the purpose of this research was to determine the prevalence of bacterial and fungal co- and superinfections in Western Romanian adults with COVID-19, hospitalized in in-ward settings during the second half of the pandemic, and its distribution according to sociodemographic and clinical conditions. The unicentric retrospective observational study was conducted on 407 eligible patients. Expectorate sputum was selected as the sampling technique followed by routine microbiological investigations. A total of 31.5% of samples tested positive for Pseudomonas aeruginosa, followed by 26.2% having co-infections with Klebsiella pneumoniae among patients admitted with COVID-19. The third most common Pathogenic bacteria identified in the sputum samples was Escherichia coli, followed by Acinetobacter baumannii in 9.3% of samples. Commensal human pathogens caused respiratory infections in 67 patients, the most prevalent being Streptococcus penumoniae, followed by methicillin-sensitive and methicillin-resistant Staphylococcus aureus. A total of 53.4% of sputum samples tested positive for Candida spp., followed by 41.1% of samples with Aspergillus spp. growth. The three groups with positive microbial growth on sputum cultures had an equally proportional distribution of patients admitted to the ICU, with an average of 30%, compared with only 17.3% among hospitalized COVID-19 patients with negative sputum cultures (p = 0.003). More than 80% of all positive samples showed multidrug resistance. The high prevalence of bacterial and fungal co-infections and superinfections in COVID-19 patients mandates for strict and effective antimicrobial stewardship and infection control policies.

Variant-Related Differences in Laboratory Biomarkers among Patients Affected with Alpha, Delta and Omicron: A Retrospective Whole Viral Genome Sequencing and Hospital-Setting Cohort Study

During the COVID-19 pandemic, different SARS-CoV-2 variants of concern (VOC) with specific characteristics have emerged and spread worldwide. At the same time, clinicians routinely evaluate the results of certain blood tests upon patient admission as well as during hospitalization to assess disease severity and the overall patient status. In the present study, we searched for significant cell blood count and biomarker differences among patients affected with the Alpha, Delta and Omicron VOCs at admission. Data from 330 patients were retrieved regarding age, gender, VOC, cell blood count results (WBC, Neut%, Lymph%, Ig%, PLT), common biomarkers (D-dimers, urea, creatinine, SGOT, SGPT, CRP, IL-6, suPAR), ICU admission and death. Statistical analyses were performed using ANOVA, the Kruskal-Wallis test, two-way ANOVA, Chi-square, T-test, the Mann-Whitney test and logistic regression was performed where appropriate using SPSS v.28 and STATA 14. Age and VOC were significantly associated with hospitalization, whereas significant differences among VOC groups were found for WBC, PLT, Neut%, IL-6, creatinine, CRP, D-dimers and suPAR. Our analyses showed that throughout the current pandemic, not only the SARS-CoV-2 VOCs but also the laboratory parameters that are used to evaluate the patient's status at admission are subject to changes.

Modified SCOPE (mSCOPE) Score as a Tool to Predict Mortality in COVID-19 Critically Ill Patients

Introduction: Efficient clinical scores predicting the outcome of severe COVID-19 pneumonia may play a pivotal role in patients’ management. The aim of this study was to assess the modified Severe COvid Prediction Estimate score (mSCOPE) index as a predictor of mortality in patients admitted to the ICU due to severe COVID-19 pneumonia. Materials and methods: In this retrospective observational study, 268 critically ill COVID-19 patients were included. Demographic and laboratory characteristics, comorbidities, disease severity, and outcome were retrieved from the electronical medical files. The mSCOPE was also calculated. Results: An amount of 70 (26.1%) of patients died in the ICU. These patients had higher mSCOPE score compared to patients who survived (p < 0.001). mSCOPE correlated to disease severity (p < 0.001) and to the number and severity of comorbidities (p < 0.001). Furthermore, mSCOPE significantly correlated with days on mechanical ventilation (p < 0.001) and days of ICU stay (p = 0.003). mSCOPE was found to be an independent predictor of mortality (HR:1.219, 95% CI: 1.010–1.471, p = 0.039), with a value ≥ 6 predicting poor outcome with a sensitivity (95%CI) 88.6%, specificity 29.7%, a positive predictive value of 31.5%, and a negative predictive value of 87.7%. Conclusion: mSCOPE score could be proved useful in patients’ risk stratification, guiding clinical interventions in patients with severe COVID-19.

Insights from a Rapidly Implemented COVID-19 Biobank Using Electronic Consent and Informatics Tools

Biobanking during the COVID-19 pandemic presented unique challenges regarding patient enrollment, sample collection, and experimental analysis. This report details the ways in which we rapidly overcame those challenges to create a robust database of clinical information and patient samples while maintaining clinician and researcher safety. We developed a pipeline using REDCap (Research Electronic Data Capture) to coordinate electronic informed consent, sample collection, immunological assay execution, and data analysis for biobanking samples from patients with COVID-19. We then integrated immunological assay data with clinical data extracted from the electronic health record to link study parameters with clinical readouts. Of the 193 inpatients who participated in this study, 138 consented electronically and 56 provided paper consent. We collected and banked blood samples to measure circulating cytokines and chemokines, peripheral immune cell composition and activation status, anti-COVID-19 antibodies, and germline gene polymorphisms. In addition, we collected DNA and RNA from nasopharyngeal swabs to assess viral titer and microbiome composition by 16S sequencing. The rapid spread and contagious nature of COVID-19 required special considerations and innovative solutions to biobank samples quickly while protecting researchers and clinicians. Overall, this workflow and computational pipeline allowed for comprehensive immune profiling of 193 inpatients infected with COVID-19, as well as 89 outpatients, 157 patients receiving curbside COVID-19 testing, and 86 healthy controls. We describe a novel electronic framework for biobanking and analyzing patient samples during COVID-19, and present insights and strategies that can be applied more broadly to other biobank studies.

Prognostic models in COVID-19 infection that predict severity: a systematic review

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

Histology and cytokine levels in hepatic injury accompanying a case of non-severe COVID-19

The pathogenesis of liver dysfunction that complicates coronavirus disease 2019 (COVID-19) remains unclear, especially in mild to moderate severity cases. In this case, a novel coronavirus infection was detected by polymerase chain reaction (PCR) in a 76-year-old woman hospitalized after presenting with fever. No other abnormal physical findings were observed, and oxygen administration was not required. Chest computed tomography (CT) showed a ground-glass-like and an infiltrative shadow in the right lung, and moderate COVID-19 was diagnosed. Initially, the fever resolved, and PCR turned negative; however, the fever reappeared on hospitalization day 14, and CT showed pneumonia exacerbation accompanied by new onset of fatty liver. Biochemical testing revealed marked liver dysfunction, accompanied by elevated serum interleukin (IL)-6, IL-10, and tumor necrosis factor-α levels. Physical findings and all laboratory parameters improved after conservative treatment, and she was discharged on day 22. A liver biopsy performed 44 days post-discharge showed T-cell-dominant inflammatory cell infiltration, mainly in the portal region. Some hepatocytes showed fatty degeneration.We report a case of moderate COVID-19 in which histological hepatitis persisted after a substantial period had passed since the initial infection had cleared and associated transaminase elevations had resolved, with a comparison of serum cytokine dynamics.

Severe COVID-19 Pneumonia in a Three-Year-Old with Congenital Iron and B12 Deficiency Anemia of Unknown Etiology: A Case Report

Since COVID-19 first emerged in Wuhan, China, and was declared a global pandemic by the WHO, researchers have been meticulously studying the disease and its complications. Studies of severe COVID-19 disease among pediatric populations are scarce, leading to difficulty in establishing a comprehensive management approach. Case presentation: This report outlines a case of a long-standing combined iron and vitamin B12 deficiency anemia in a three-year-old treated at the Children's Clinical University Hospital due to severe COVID-19 disease. The patient's clinical condition coincided with the derangement of biomarkers described in the literature, including lymphopenia, increased neutrophil/lymphocyte ratio (NLR), decreased lymphocyte/C-reactive protein ratio (LCR), as well as elevated inflammatory markers such as CRP and D-dimers. The patient developed severe bilateral pneumonia requiring invasive ventilation, high-flow oxygen, immunosuppressive therapy with dexamethasone and tocilizumab, and supplementation of anemia deficits with blood transfusion and vitamin B12 administration. Conclusions: Our findings are consistent with the most important biomarkers reported in the literature indicative of severe disease progression. Additionally, poorly controlled anemia may be suggested as a potentially important risk factor for severe COVID-19 disease among children. However, additional quantitative research is required to establish the nature and severity of the risk.

Sequelae of long COVID, known and unknown: A review of updated information

Over three years have passed since the COVID-19 pandemic started. The dangerousness and impact of COVID-19 should definitely not be ignored or underestimated. Other than the symptoms of acute infection, the long-term symptoms associated with SARS-CoV-2 infection, which are referred to here as "sequelae of long COVID (LC)", are also a conspicuous global public health concern. Although such sequelae were well-documented, the understanding of and insights regarding LC-related sequelae remain inadequate due to the limitations of previous studies (the follow-up, methodological flaws, heterogeneity among studies, etc.). Notably, robust evidence regarding diagnosis and treatment of certain LC sequelae remain insufficient and has been a stumbling block to better management of these patients. This awkward situation motivated us to conduct this review. Here, we comprehensively reviewed the updated information, particularly focusing on clinical issues. We attempt to provide the latest information regarding LC-related sequelae by systematically reviewing the involvement of main organ systems. We also propose paths for future exploration based on available knowledge and the authors' clinical experience. We believe that these take-home messages will be helpful to gain insights into LC and ultimately benefit clinical practice in treating LC-related sequelae.

An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems

BACKGROUND

We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalization and compared it with the existing risk scores.

METHODS

This is a retrospective study of adults hospitalized with COVID-19 from March 2020 to February 2021. Patients, each with 92 variables, and one composite outcome underwent feature selection process to identify the most predictive variables. Selected variables were modeled to build four ML algorithms (artificial neural network, support vector machine, gradient boosting machine, and Logistic regression) and an ensemble model to generate a CORE-COVID-19 model to predict the composite outcome and compared with existing risk prediction scores. The net benefit for clinical use of each model was assessed by decision curve analysis.

RESULTS

Of 1796 patients, 278 (15%) patients reached primary outcome. Six most predictive features were identified. Four ML algorithms achieved comparable discrimination (P > 0.827) with c-statistics ranged 0.849-0.856, calibration slopes 0.911-1.173, and Hosmer-Lemeshow P > 0.141 in validation dataset. These 6-variable fitted CORE-COVID-19 model revealed a c-statistic of 0.880, which was significantly (P < 0.04) higher than ISARIC-4C (0.751), CURB-65 (0.735), qSOFA (0.676), and MEWS (0.674) for outcome prediction. The net benefit of the CORE-COVID-19 model was greater than that of the existing risk scores.

CONCLUSION

The CORE-COVID-19 model accurately assigned 88% of patients who potentially progressed to 30-day composite events and revealed improved performance over existing risk scores, indicating its potential utility in clinical practice.

Inflammation Related to Association of Low Uric Acid and Progression to Severe Disease in Patients Hospitalized for Non-Severe Coronavirus Disease 2019

Uric acid has antioxidant properties. To examine whether a low uric acid level is associated with severe coronavirus disease 2019 (COVID-19) progression via inflammation, alveolar damage, and/or coagulation abnormality, a retrospective observational study of 488 patients with non-severe COVID-19 and serum uric acid level ≤7 mg/dL at admission was conducted. Serum C-reactive protein (CRP), serum Krebs von den Lungen 6 (KL-6), and plasma D-dimer levels were also measured as markers of inflammation, alveolar damage, and coagulation abnormality, respectively. Median values for uric acid, CRP, KL-6, and D-dimer at admission were 4.4 mg/dL, 3.33 mg/dL, 252.0 U/mL, and 0.8 µg/mL, respectively. Among the total cohort, 95 (19.5%) progressed to severe COVID-19 with a median (interquartile range) time of 7 (4–14) days. Multivariable Cox proportional hazards regression analysis showed that low uric acid level was associated with a higher rate of severe COVID-19 progression. However, uric acid level was inversely associated with CRP level, and the association between the level of uric acid and severe COVID-19 progression was significantly different with and without CRP level inclusion. In contrast, no such association was found for KL-6 or D-dimer level. Low uric acid may contribute to severe COVID-19 progression via increased inflammation in subjects without hyperuricemia.

Relevance of TMPRSS2, CD163/CD206, and CD33 in clinical severity stratification of COVID-19

Background

Approximately 13.8% and 6.1% of coronavirus disease 2019 (COVID-19) patients require hospitalization and sometimes intensive care unit (ICU) admission, respectively. There is no biomarker to predict which of these patients will develop an aggressive stage that we could improve their quality of life and healthcare management. Our main goal is to include new markers for the classification of COVID-19 patients.

Methods

Two tubes of peripheral blood were collected from a total of 66 (n = 34 mild and n = 32 severe) samples (mean age 52 years). Cytometry analysis was performed using a 15-parameter panel included in the Maxpar® Human Monocyte/Macrophage Phenotyping Panel Kit. Cytometry by time-of-flight mass spectrometry (CyTOF) panel was performed in combination with genetic analysis using TaqMan® probes for ACE2 (rs2285666), MX1 (rs469390), and TMPRSS2 (rs2070788) variants. GemStone™ and OMIQ software were used for cytometry analysis.

Results

The frequency of CD163+/CD206- population of transitional monocytes (T-Mo) was decreased in the mild group compared to that of the severe one, while T-Mo CD163-/CD206- were increased in the mild group compared to that of the severe one. In addition, we also found differences in CD11b expression in CD14dim monocytes in the severe group, with decreased levels in the female group (p = 0.0412). When comparing mild and severe disease, we also found that CD45- [p = 0.014; odds ratio (OR) = 0.286, 95% CI 0.104–0.787] and CD14dim/CD33+ (p = 0.014; OR = 0.286, 95% CI 0.104–0.787) monocytes were the best options as biomarkers to discriminate between these patient groups. CD33 was also indicated as a good biomarker for patient stratification by the analysis of GemStone™ software. Among genetic markers, we found that G carriers of TMPRSS2 (rs2070788) have an increased risk (p = 0.02; OR = 3.37, 95% CI 1.18–9.60) of severe COVID-19 compared to those with A/A genotype. This strength is further increased when combined with CD45-, T-Mo CD163+/CD206-, and C14dim/CD33+.

Conclusions

Here, we report the interesting role of TMPRSS2, CD45-, CD163/CD206, and CD33 in COVID-19 aggressiveness. This strength is reinforced for aggressiveness biomarkers when TMPRSS2 and CD45-, TMPRSS2 and CD163/CD206, and TMPRSS2 and CD14dim/CD33+ are combined.

The effect of therapeutic plasma exchange therapy on veno-venous ECMO weaning success in severe COVID-19 ARDS patients

INTRODUCTION

Primarily, this study aimed to investigate the effect of TPE (therapeutic plasma exchange) treatment on successful ECMO weaning in severe COVID-19 ARDS patients treated with V-V ECMO.

METHODS

The study was applied retrospectively on patients over the age of 18 who were hospitalized in the ICU between January 1, 2020 and March 1, 2022.

RESULTS

The study was performed on 33 patients, 36.3% (n: 12) of whom received TPE treatment. The rate of successful ECMO weaning was statistically higher in the TPE treatment group (without TPE: 14.3% [n: 3], with TPE: 50% [n: 6], p = 0.044). The 1-month mortality was also statistically lower in the TPE treatment group (p = 0.044). In the logistic analysis, It was found that the risk of unsuccessful ECMO weaning increased 6 times in those who did not receive TPE treatment (OR; 6.0, 95% CI; 1.134-31.735, p = 0.035).

CONCLUSION

TPE treatment may increase the success rate of V-V ECMO weaning in severe COVID-19 ARDS patients treated with V-V ECMO.

Effect of ferritin, INR, and D-dimer immunological parameters levels as predictors of COVID-19 mortality: A strong prediction with the decision trees

Background and objective

A hyperinflammatory environment is thought to be the distinctive characteristic of COVID-19 infection and an important mediator of morbidity. This study aimed to determine the effect of other immunological parameter levels, especially ferritin, as a predictor of COVID-19 mortality via decision-trees analysis.

Material and method

This is a retrospective study evaluating a total of 2568 patients who died (n = 232) and recovered (n = 2336) from COVID-19 in August and December 2021. Immunological laboratory data were compared between two groups that died and recovered from patients with COVID-19. In addition, decision trees from machine learning models were used to evaluate the performance of immunological parameters in the mortality of the COVID-19 disease.

Results

Non-surviving from COVID-19 had 1.75 times higher ferritin, 10.7 times higher CRP, 2.4 times higher D-dimer, 1.14 times higher international-normalized-ratio (INR), 1.1 times higher Fibrinogen, 22.9 times higher procalcitonin, 3.35 times higher troponin, 2.77 mm/h times higher erythrocyte-sedimentation-rate (ESR), 1.13sec times longer prothrombin time (PT) when compared surviving patients. In addition, our interpretable decision tree, which was constructed with only the cut-off values of ferritin, INR, and D-dimer, correctly predicted 99.7% of surviving patients and 92.7% of non-surviving patients.

Conclusions

This study perfectly predicted the mortality of COVID-19 with our interpretable decision tree constructed with INR and D-dimer, especially ferritin. For this reason, we think that it may be important to include ferritin, INR, and D-dimer parameters and their cut-off values in the scoring systems to be planned for COVID-19 mortality.

Complicated appendicitis, acute pancreatitis, pleural effusion, and sinus bradycardia in a COVID-19 patient

This study shows that complicated appendicitis and acute pancreatitis could occur during a COVID-19 infection, since the same gastrointestinal manifestations are notable in all aforementioned diseases. Sinus bradycardia is a side effect of remdesivir. Both COVID-19 infection and remdesivir therapy can elevate liver transaminases.

Detection of COVID-19-related biomarkers by electrochemical biosensors and potential for diagnosis, prognosis, and prediction of the course of the disease in the context of personalized medicine

As a more efficient and effective way to address disease diagnosis and intervention, cutting-edge technologies, devices, therapeutic approaches, and practices have emerged within the personalized medicine concept depending on the particular patient's biology and the molecular basis of the disease. Personalized medicine is expected to play a pivotal role in assessing disease risk or predicting response to treatment, understanding a person's health status, and, therefore, health care decision-making. This work discusses electrochemical biosensors for monitoring multiparametric biomarkers at different molecular levels and their potential to elucidate the health status of an individual in a personalized manner. In particular, and as an illustration, we discuss several aspects of the infection produced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a current health care concern worldwide. This includes SARS-CoV-2 structure, mechanism of infection, biomarkers, and electrochemical biosensors most commonly explored for diagnostics, prognostics, and potentially assessing the risk of complications in patients in the context of personalized medicine. Finally, some concluding remarks and perspectives hint at the use of electrochemical biosensors in the frame of other cutting-edge converging/emerging technologies toward the inauguration of a new paradigm of personalized medicine.

Hyperglycemia in COVID-19 infection without diabetes mellitus: Association with inflammatory markers

BACKGROUND

New onset hyperglycemia is common in patients with severe coronavirus disease 2019 (COVID-19) infection. Cytokine storm due to COVID-19 infection is an essential etiology for new-onset hyperglycemia, but factors like direct severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced pancreatic β-cell failure have also been postulated to play a role.

AIM

We plan to investigate further the mechanisms underlying SARS-CoV-2 infection-induced hyperglycemia, particularly the rationale of the cytokine-induced hyperglycemia hypothesis, by evaluating the association between inflammatory markers and new onset hyperglycemia in non-diabetic patients with COVID-19 infection.

METHODS

We conducted a retrospective case-control study on adults without diabetes mellitus hospitalized for COVID-19 infection. The serum levels of glucose and inflammatory markers at presentation before initiation of corticosteroid were collected. Hyperglycemia was defined as glucose levels ≥ 140 mg/dL. C-Reactive protein (CRP) ≥ 100 mg/L, ferritin ≥ 530 ng/mL, lactate dehydrogenase (LDH) ≥ 590 U/L, and D-dimer ≥ 0.5 mg/L were considered elevated. We used the χ² test for categorical variables and the Mann-Whitney U test for continuous variables and calculated the logistic regression for hyperglycemia.

RESULTS

Of the 520 patients screened, 248 met the inclusion criteria. Baseline demographics were equally distributed between patients with hyperglycemia and those who were normoglycemic. Serum inflammatory markers in patients with or without new-onset hyperglycemia were elevated as follows: CRP (58.1% vs 65.6%, P = 0.29), ferritin (48.4% vs 34.9%, P = 0.14), D-dimer (37.1% vs 37.1%, P = 0.76) and LDH (19.4% vs 11.8%, P = 0.02). Logistic regression analysis showed LDH odds ratio (OR) = 1.623 (P = 0.256). We observed significantly higher mortality (24.2% vs 9.1%, P = 0.001; OR = 2.528, P = 0.024) and length of stay (8.89 vs 6.69, P = 0.026) in patients with hyperglycemia.

CONCLUSION

Our study showed no association between CRP, ferritin, LDH, D-dimer levels, and new-onset hyperglycemia in non-diabetic patients with COVID-19 infection. It also shows an increased mortality risk and length of stay in patients with hyperglycemia. With new-onset hyperglycemia being closely associated with poor prognostic indices, it becomes pivotal to understand the underlying pathophysiological mechanisms behind the SARS-CoV-2 infection-induced hyperglycemia. We conclude that the stress hyperglycemia hypothesis is not the only mechanism of SARS-CoV-2 infection-induced hyperglycemia but rather a multicausal pathogenesis leading to hyperglycemia that requires further research and understanding. This would help us improve not only the clinical outcomes of COVID-19 disease and inpatient hyperglycemia management but also understand the long-term effects of SARS-CoV-2 infection and further management.

Efficacy of blood urea nitrogen-to-albumin ratio for predicting prognostic outcomes of inpatients with COVID-19: A meta-analysis

BACKGROUND

The associations between blood urea nitrogen (BUN)/albumin ratio and poor prognosis in patients with diagnosis of coronavirus disease 2019 (COVID-19) remain to be clarified.

METHODS

A search based on 4 electronic databases (i.e., EMBASE, Google scholar, MEDLINE, and Cochrane Library) was performed on June 23, 2022. The association of BUN/Albumin ratio with poor prognostic outcomes, defined as patients with mortality/severe illnesses, were analyzed.

RESULTS

Results from analysis of 7 cohort studies (3600 individuals with COVID-19) published between 2020 and 2022 showed a higher BUN/Albumin ratio in the poor-prognosis group (Mean difference:  = 2.838, 95% confidence interval: 2.015-3.66, P < .001, I2 = 92.5%) than the good-prognosis group. Additional investigation into the connection between BUN/Albumin ratio as a binary variable (i.e., high or low) and the risk of poor outcome also supported an association between a higher BUN/Albumin ratio and a poor prognostic risk (odd ratio = 3.009, 95% confidence interval: 1.565-5.783, P = .001, I2 = 93.7%, 5 studies). Merged analysis of poor prognosis produced a sensitivity of 0.76, specificity of 0.72, and area under curve of 0.81.

CONCLUSION

This meta-analysis demonstrated a positive correlation between BUN/albumin ratio and poor outcome in patients with COVID-19. Additional large-scale prospective studies are needed to verify our findings.

Characteristics, Mortality, and Clinical Outcomes of Hospitalized Patients with COVID-19 and Diabetes: A Reference Single-Center Cohort Study from Poland

Background

Diabetes is a risk factor for a severe course of COVID-19. We evaluated the characteristics and risk factors associated with undesirable outcomes in diabetic patients (DPs) hospitalized due to COVID-19.

Materials and Methods

The data analysis of patients admitted between March 6, 2020, and May 31, 2021, to the University Hospital in Krakow (Poland), a reference center for COVID-19, was performed. The data were gathered from their medical records.

Results

A total number of 5191 patients were included, of which 2348 (45.2%) were women. The patients were at the median age of 64 (IQR: 51-74) years, and 1364 (26.3%) were DPs. DPs, compared to nondiabetics, were older (median age: 70 years, IQR: 62-77 vs. 62, IQR: 47-72, and p < 0.001) and had a similar gender distribution. The DP group had a higher mortality rate (26.2% vs. 15.7%, p < 0.001) and longer hospital stays (median: 15 days, IQR: 10-24 vs. 13, IQR: 9-20, and p < 0.001). DPs were admitted to the ICU more frequently (15.7% vs. 11.0%, p < 0.001) and required mechanical ventilation more often (15.5% vs. 11.3%, p < 0.001). In a multivariate logistic regression, factors associated with a higher risk of death were age >65 years, glycaemia >10 mmol/L, CRP and D-dimer level, prehospital insulin and loop diuretic use, presence of heart failure, and chronic kidney disease. Factors contributing to lower mortality were in-hospital use of statin, thiazide diuretic, and calcium channel blocker.

Conclusion

In this large COVID-19 cohort, DPs constituted more than a quarter of hospitalized patients. The risk of death and other outcomes compared to nondiabetics was higher in this group. We identified a number of clinical, laboratory, and therapeutic variables associated with the risk of hospital death in DPs.

Association between serum ferritin level and decreased diffusion capacity 3 months after the onset of COVID-19 pneumonia

BACKGROUND

Coronavirus disease 2019 (COVID-19) pneumonia can have prolonged sequelae and lead to respiratory dysfunction, mainly because of impaired diffusion capacity for carbon monoxide (DLCO). The clinical factors associated with DLCO impairment, including blood biochemistry test parameters, remain unclear.

METHODS

Patients with COVID-19 pneumonia who underwent inpatient treatment between April 2020 and August 2021 were included in this study. A pulmonary function test was performed 3 months after onset, and the sequelae symptoms were investigated. Clinical factors, including blood test parameters and abnormal chest shadows on computed tomography, of COVID-19 pneumonia associated with DLCO impairment were investigated.

RESULTS

In total, 54 recovered patients participated in this study. Twenty-six patients (48%) and 12 patients (22%) had sequelae symptoms 2 and 3 months after, respectively. The main sequelae symptoms at 3 months were dyspnea and general malaise. Pulmonary function tests showed that 13 patients (24%) had both DLCO <80% predicted value (pred) and DLCO/alveolar volume (VA) <80% pred, and appeared to have DLCO impairment not attributable to an abnormal lung volume. Clinical factors associated with impaired DLCO were investigated in multivariable regression analysis. Ferritin level of >686.5 ng/mL (odds ratio: 11.08, 95% confidence interval [CI]: 1.84-66.59; p = 0.009) was most strongly associated with DLCO impairment.

CONCLUSIONS

Decreased DLCO was the most common respiratory function impairment, and ferritin level was a significantly associated clinical factor. Serum ferritin level could be used as a predictor of DLCO impairment in cases of COVID-19 pneumonia.

Comparing serum ferritin levels during COVID-19 infection and recovery period in pediatric patients with transfusion-dependent thalassemia, a single-center study

Background

Ferritin has been recognized as a predictor of severity among Coronavirus-19 disease (COVID-19) patients. Studies have shown higher levels of ferritin in patients with COVID-19 than in healthy children. Patients with transfusion-dependent thalassemia (TDT) basically have high ferritin level due to iron overload. It is uncertain whether serum ferritin level in these patients is associated with COVID-19 infection.

Objective

To evaluate ferritin levels in TDT with COVID-19 before, during, and after the course of infection.

Methods

This retrospective study enrolled all TDT children with COVID-19 infection that were hospitalized in Ulin General Hospital Banjarmasin during the COVID-19 pandemic (March 2020 to June 2022). Data were collected from medical records.

Results

There were 14 patients included in this study, 5 patients had mild symptoms and 9 patients were asymptomatic. The mean of hemoglobin level upon admission was 8.1 ± 3 g/dL and serum ferritin level were 5148.5 ± 2651.8 ng/mL. The average serum ferritin level during COVID-19 infection was 2373.2 ng/mL higher than before infection and then decreased by 952.4 ng/mL after infection. We found no association of increasing serum ferritin with patients' symptoms (p = 0.27). The severity of anemia also was not correlated with the presentation of COVID-19 infection (p = 0.902).

Conclusion

Serum ferritin levels in TDT children may not reflect disease severity or predict poor outcomes during COVID-19 infection. However, the presence of other co-morbid conditions/confounders warrants cautious interpretation.

Outcome prediction in hospitalized COVID-19 patients: Comparison of the performance of five severity scores

Background

The aim of our study was to externally validate the predictive capability of five developed coronavirus disease 2019 (COVID-19)-specific prognostic tools, including the COVID-19 Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), Shang COVID severity score, COVID-intubation risk score-neutrophil/lymphocyte ratio (IRS-NLR), inflammation-based score, and ventilation in COVID estimator (VICE) score.

Methods

The medical records of all patients hospitalized for a laboratory-confirmed COVID-19 diagnosis between May 2021 and June 2021 were retrospectively analyzed. Data were extracted within the first 24 h of admission, and five different scores were calculated. The primary and secondary outcomes were 30-day mortality and mechanical ventilation, respectively.

Results

A total of 285 patients were enrolled in our cohort. Sixty-five patients (22.8%) were intubated with ventilator support, and the 30-day mortality rate was 8.8%. The Shang COVID severity score had the highest numerical area under the receiver operator characteristic (AUC-ROC) (AUC 0.836) curve to predict 30-day mortality, followed by the SEIMC score (AUC 0.807) and VICE score (AUC 0.804). For intubation, both the VICE and COVID-IRS-NLR scores had the highest AUC (AUC 0.82) compared to the inflammation-based score (AUC 0.69). The 30-day mortality increased steadily according to higher Shang COVID severity scores and SEIMC scores. The intubation rate exceeded 50% in the patients stratified by higher VICE scores and COVID-IRS-NLR score quintiles.

Conclusion

The discriminative performances of the SEIMC score and Shang COVID severity score are good for predicting the 30-day mortality of hospitalized COVID-19 patients. The COVID-IRS-NLR and VICE showed good performance for predicting invasive mechanical ventilation (IMV).

FEATURES OF COAGULOPATHY AND SYSTEMIC INFLAMMATION IN PATIENTS AFTER COVID-19 INFECTION

OBJECTIVE

The aim: To determine the peculiarities of laboratory data concerning blood coagulation and systemic inflammation in COVID-19 patients in three months after discharge and recovery. The state of coagulation, anticoagulation, and fibrinolytic systems, as well as their prognostic value having been well studied in hospitalized COVID-19 patients, their state three months after hospitalization, are not yet well understood.

PATIENTS AND METHODS

Materials and methods: Methods of randomization, anthropometry, ECG, standard clinical blood testing, immunoenzymometry, immunoanalysis, and primary statistical analysis were used in the study. Anthropometric measurements of patients (n=20), blood samples, blood serum samples, urine samples, and statistical data were the materials of the study.

RESULTS

Results: Indices of coagulation and systemic inflammation in studied patients after COVID-19 were obtained (PTT, s ; PATPT, s; Fibrinogen, g/L; Platelets ×109 /L; PCT, ng/mL; DD, μg/L; СRP, mg/L; IL -6, pg/mL; IL -10, pg/mL; Cortisol (nM/L); CIC (IU/mL); Ig A (g/L).

CONCLUSION

Conclusions: Summing up the results obtained, it is possible to assert micro- and macro-vascular thromboses to be common in COVID-19 cases; they are associated with poor prognosis for diseased patients and are not completely investigated; the role of thromboses in COVID-19 course and complications are to be studied as well as the strategies of fibrinolytic therapies for such condition are to be justified. The presence of specific rheological and serological changes in patients even three months after surviving COVID-19 needs further study to understand the necessity of anti-thrombolytic drug uptake for a relatively long time.

Cardiovascular Complications in Coronavirus Disease 2019-Pathogenesis and Management

The coronavirus disease 2019 (COVID-19) pandemic has caused a devastating impact on morbidity and mortality around the world. Severe acute respiratory syndrome-coronavirus-2 has a characteristic tropism for the cardiovascular system by entering the host cells and binding to angiotensin-converting enzyme 2 receptors, which are expressed in different cells, particularly endothelial cells. This endothelial injury is linked by a direct intracellular viral invasion leading to inflammation, microthrombosis, and angiogenesis. COVID-19 has been associated with acute myocarditis, cardiac arrhythmias, new onset or worsening heart failure, ischemic heart disease, stroke, and thromboembolic disease. This review summarizes key relevant literature regarding the epidemiology, diagnosis, treatment, and preventive measures related to cardiovascular complications in the setting of COVID-19.

Sustained Cytotoxic Response of Peripheral Blood Mononuclear Cells from Unvaccinated Individuals Admitted to the ICU Due to Critical COVID-19 Is Essential to Avoid a Fatal Outcome

The main objective of this study was to determine the influence of the cytotoxic activity of peripheral blood mononuclear cells (PBMCs) on the outcome of unvaccinated individuals with critical COVID-19 admitted to the ICU. Blood samples from 23 individuals were collected upon admission and then every 2 weeks for 13 weeks until death (Exitus group) (n = 13) or discharge (Survival group) (n = 10). We did not find significant differences between groups in sociodemographic, clinical, or biochemical data that may influence the fatal outcome. However, direct cellular cytotoxicity of PBMCs from individuals of the Exitus group against pseudotyped SARS-CoV-2-infected Vero E6 cells was significantly reduced upon admission (-2.69-fold; p = 0.0234) and after 4 weeks at the ICU (-5.58-fold; p = 0.0290), in comparison with individuals who survived, and it did not improve during hospitalization. In vitro treatment with IL-15 of these cells did not restore an effective cytotoxicity at any time point until the fatal outcome, and an increased expression of immune exhaustion markers was observed in NKT, CD4+, and CD8+ T cells. However, IL-15 treatment of PBMCs from individuals of the Survival group significantly increased cytotoxicity at Week 4 (6.18-fold; p = 0.0303). Consequently, immunomodulatory treatments that may overcome immune exhaustion and induce sustained, efficient cytotoxic activity could be essential for survival during hospitalization due to critical COVID-19.