Predictor Of COVID-19 Severity Research Articles

GDF-15 Levels and Other Laboratory Findings as Predictors of COVID-19 Severity and Mortality: A Pilot Study.

Growth differentiation factor 15 (GDF-15) is a stress-induced cytokine associated with acute and chronic inflammatory states. This prospective observational study aimed to investigate the prognostic roles of GDF-15 and routine clinical laboratory parameters in COVID-19 patients. Upon the admission of 95 adult hospitalized COVID-19 patients in Croatia, blood analysis was performed, and medical data were collected. The patients were categorized based on survival, ICU admission, and hospitalization duration. Logistic regression and ROC curve methods were employed for the statistical analysis. Logistic regression revealed two independent predictors of negative outcomes: CURB-65 score (OR = 2.55) and LDH (OR = 1.005); one predictor of ICU admission: LDH (OR = 1.004); and one predictor of prolonged hospitalization: the need for a high-flow nasal cannula (HFNC) upon admission (OR = 4.75). The ROC curve showed diagnostic indicators of negative outcomes: age, CURB-65 score, LDH, and GDF-15. The largest area under the curve (AUC = 0.767, specificity = 65.6, sensitivity = 83.9) was represented by GDF-15, with a cutoff value of 3528 pg/mL. For ICU admission, significant diagnostic indicators were LDH, CRP, and IL-6. Significant diagnostic indicators of prolonged hospitalization were CK, GGT, and oxygenation with an HFNC upon admission. This study reaffirms the significance of the commonly used laboratory parameters and clinical scores in evaluating COVID-19. Additionally, it introduces the potential for a new diagnostic approach and research concerning GDF-15 levels in this widespread disease.

Body Mass Index as a Predictor of COVID-19 Severity in ICU Patients in Saudi Arabia: A Retrospective Analysis.

Introduction The global coronavirus disease 2019 (COVID-19) pandemic has prompted research into various risk factors, including the role of body mass index (BMI) in disease severity. This study specifically examines the correlation between BMI and the severity ofCOVID-19among intensive care unit (ICU) patients in Saudi Arabia, addressing a gap in region-specific data. The study aims to assess the impact of BMI on the severity of COVID-19 in a Saudi Arabian ICU patient cohort, providing insights into how this relationship varies in different demographic contexts. Materials and methods Employing a retrospective cohort design, the study analyzed data from adult ICU patients in Saudi Arabia diagnosed with COVID-19. It focused on variables like BMI at admission, demographic information, and COVID-19 outcomes including severity, recovery, and mortality. Statistical analysis involved regression models, adjusting for age, gender, and comorbidities. Results Unlike global observations, the study found no significant correlation between BMI and COVID-19 severity in the Saudi Arabian context. This suggests that in this specific demographic, other factors may be more critical in determining the severity of the disease. Conclusion Our findings challenge the global consensus on BMI as a key factor in COVID-19 severity, highlighting the importance of regional differences in disease dynamics. They underscore the need for localized healthcare strategies and further research into diverse demographic factors affecting COVID-19. This study contributes to a broader understanding of the pandemic and encourages region-specific approaches in both clinical and public health spheres.

The Sphingolipid-Signaling Pathway as a Modulator of Infection by SARS-CoV-2.

Ceramides and other related sphingolipids, important cellular components linked to metabolic homeostasis and cardiometabolic diseases, have been found to be involved in different steps of the SARS-CoV-2 life cycle. Hence, changes in their physiological levels are identified as predictors of COVID-19 severity and prognosis, as well as potential therapeutic targets. In this review, an overview of the SARS-CoV-2 life cycle is given, followed by a description of the sphingolipid metabolism and its role in viral infection, with a particular focus on those steps required to finalize the viral life cycle. Furthermore, the use and development of pharmaceutical strategies to target sphingolipids to prevent and treat severe and long-term symptoms of infectious diseases, particularly COVID-19, are reviewed herein. Finally, research perspectives and current challenges in this research field are highlighted. Although many aspects of sphingolipid metabolism are not fully known, this review aims to highlight how the discovery and use of molecules targeting sphingolipids with reliable and selective properties may offer new therapeutic alternatives to infectious and other diseases, including COVID-19.

Occurrence of SARS-CoV-2 viremia is associated with genetic variants of genes related to COVID-19 pathogenesis.

SARS-CoV-2 viral load has been related to COVID-19 severity. The main aim of this study was to evaluate the relationship between SARS-CoV-2 viremia and SNPs in genes previously studied by our group as predictors of COVID-19 severity. Retrospective observational study including 340 patients hospitalized for COVID-19 in the University Hospital La Princesa between March 2020 and December 2021, with at least one viremia determination. Positive viremia was considered when viral load was above the quantifiable threshold (20 copies/ml). A total of 38 SNPs were genotyped. To study their association with viremia a multivariate logistic regression was performed. The mean age of the studied population was 64.5 years (SD 16.6), 60.9% patients were male and 79.4% white non-Hispanic. Only 126 patients (37.1%) had at least one positive viremia. After adjustment by confounders, the presence of the minor alleles of rs2071746 (HMOX1; T/T genotype OR 9.9 p < 0.0001), rs78958998 (probably associated with SERPING1 expression; A/T genotype OR 2.3, p = 0.04 and T/T genotype OR 12.9, p < 0.0001), and rs713400 (eQTL for TMPRSS2; C/T + T/T genotype OR 1.86, p = 0.10) were associated with higher risk of viremia, whereas the minor alleles of rs11052877 (CD69; A/G genotype OR 0.5, p = 0.04 and G/G genotype OR 0.3, p = 0.01), rs2660 (OAS1; A/G genotype OR 0.6, p = 0.08), rs896 (VIPR1; T/T genotype OR 0.4, p = 0.02) and rs33980500 (TRAF3IP2; C/T + T/T genotype OR 0.3, p = 0.01) were associated with lower risk of viremia. Genetic variants in HMOX1 (rs2071746), SERPING1 (rs78958998), TMPRSS2 (rs713400), CD69 (rs11052877), TRAF3IP2 (rs33980500), OAS1 (rs2660) and VIPR1 (rs896) could explain heterogeneity in SARS-CoV-2 viremia in our population.

Predictors of COVID-19 Severity in Elderly Patients Infected by Omicron in China, 18 December 2022-5 February 2023.

To analyze the clinical characteristics and prognosis of patients hospitalized with non-severe, severe pneumonia and death in Omicron COVID-19. We collected clinical data from 118 patients with COVID-19 in China from 18 December, 2022 and 5 February, 2023. According to the outcome, the patients were divided into non-severe group, severe group and death group. Subsequently, we statistically analyzed the general condition, clinical manifestations, laboratory parameters, NLR, MLR, PLR and HALP of these groups. We also retrospectively analyzed the possible factors affecting the prognostic regression of patients with COVID-19. A total of 118 COVID-19 patients were enrolled in this study, including 64 non-severe patients, 38 severe patients and 16 death patients. Compared with the non-severe group, T lymphocytes, B lymphocytes, Th1, Th2, Th17, Treg cells, IgA, IgG, IgM in the severe and death groups decreased more significantly (P<0.05). The levels of myocardial markers, ALT, AST, BUN, Cr, D-dimer, fibrinogen, NLR, MLR and PLR in the severe and death groups were significantly higher than those in the non-severe group (P<0.05). The level of HALP was significantly lower than that of non-severe group (P<0.05). MLR is not only an independent risk factor for the transition from non-severe to severe disease, but also an independent risk factor for predicting the possibility of death in COVID-19 patients. The analysis of COVID-19 patients in China showed that severe patients were older, more likely to have related complications, lower lymphocyte count, liver and kidney function disorder, glucose and lipid metabolism disorders, myocardial injury, and abnormal coagulation function, suggesting the need for early anticoagulant therapy. In addition, NLR, MLR, PLR and HALP can be used as biomarkers to evaluate the severity and prognosis of COVID-19 patients.

Risk factors of severe course and fatality in children hospitalized for COVID-19 – two centers cohort study.

IntroductionAfter three years of the pandemic, predictors of COVID-19 severity in children are still not completely known. This study was designed to define the high-risk group in hospitalized children.Material and methodsThe analysis covered 2338 children in two centers. Among patients with severe course three groups were identified –requiring and not requiring mechanical ventilation and those who died.ResultsThe median age of seventy children (54% female) with severe COVID-19 was 32 months. In 43 (61%) children comorbidities were present. No one was vaccinated against COVID-19. On admission, medium SpO2 was 89%. 65 (93%) patients presented with dyspnoea, and 49 (70%) with cough. 53 (76%) children required noninvasive oxygen support and 17 (24%) mechanical ventilation. 8(11%) children died. The most significant difference between mechanically ventilated children who recovered and those who died was age – 124 vs 12.8 months (p&lt;0.001). Children requiring mechanical ventilation presented higher CRP (median 33.4 vs 6.7 mg/dl), LDH, and ferritin. In children who died even higher CRP (55.9 vs 7.9 mg/dl), deep lymphopenia (0.65 vs 1.85 x 103/ul), and thrombocytopenia ( 7 vs 237 x 103/ul) were observed.ConclusionsRisk factors for a severe course of COVID-19 were – young age, lack of COVID-19 vaccination, auscultation changes and dyspnea at admission. The presence of comorbidities, high CRP, LDH, and ferritin levels were the predictors of mechanical ventilation necessity and death. Among children mechanically ventilated teenagers had a prognosis of recovery but, infants with comorbidities were at the highest risk of death.

Neutrophil functional activity indices as predictors of COVID-19 severity

Neutrophil functional activity indices as predictors of COVID-19 severity

Correlation Between Neutrophil-Lymphocyte Ratio, Platelets-Lymphocyte Ratio, and High-Resolution CT in Patients with COVID-19

Background: COVID-19 is a highly infectious disease that necessitates simple and rapid methods for recognising severe patients. Aims: To correlate between chest lesions in CT, neutrophil-lymphocyte ratio (NLR), and platelets-lymphocytes ratio in patients with COVID-19, and to detect their cut-off values as an early warning of severe COVID-19 in Egyptian patients. Subjects and Methods: A cross-sectional study included 100 adult patients with COVID-19 attending Ahmed Maher Teaching Hospital, Cairo, Egypt. Clinical, laboratory, and radiological assessments were done. They were classified according to their CT grades into three groups: seven patients with a normal chest CT, 45 non-severe cases, and 48 severe cases. Results: Dyspnoea was the most common symptom among the severe cases (79.2%) and fever among non-severe cases (71.1%), while cough (85.7%) was the most common among cases with a normal CT. The age, NLR, C-reactive protein (CRP), and D-dimer of severe cases were significantly the highest, while the absolute lymphocytes were significantly the lowest. Highly significant positive correlations were found between CT grades with D-dimer, NLR, and CRP; significant positive correlation was found with age; and significant negative correlation with CT. Using receiver operating characteristic analysis, areas under the curve of D-dimer, NLR, age, CRP, ferritin, and platelet-lymphocyte ratio were 0.760, 0.698, 0.640, 0.627, 0.614, and 0.595, respectively. The optimal cut-off value of NLR was 2.50 with 0.74 specificity, 0.61 sensitivity, and 67.5 accuracy. Conclusion: NLR is a reliable and easy-to-use predictor of COVID-19 severity. NLR (&gt;2.5) should prompt prescription of a chest CT as it could reveal essential lesions that influence further management.

COVID-19 Case Management Outcomes Amongst Diabetes and Hypertensive Patients in the United Arab Emirates: A Prospective Study.

The global pandemic of the novel Coronavirus infection 2019 (COVID-19) challenged the care of comorbid patients. The risk imposed by COVID-19 on diabetes patients is multisystemic, exponential, and involves glucose dysregulation. The increased burden for diabetes patients infected with COVID-19 is substantial in countries with a high prevalence of diabetics, such as the United Arab Emirates (UAE). This study aims to explore the prevalence of diabetes, clinical characteristic, and outcomes of patients admitted for COVID-19 treatment with or without a concurrent preadmission diagnosis of diabetes. A prospective study was performed on 1199 adults admitted with confirmed COVID-19 from December 2020 to April 2021 to a single hospital in the UAE. The study compared the demographics, clinical characteristics, and outcomes in COVID-19-infected patients with diabetes to patients without diabetes. The study endpoints include the development of new-onset diabetes, admission to ICU, trends in the blood glucose levels, and death. A total of 1199 patients (390 with diabetes) were included in the study. A diabetes prevalence was detected among 9.8% of the study population. Among the diabetes group, 10.8% were morbidly obese, 65.4% had associated hypertension, and 18.9% had coronary artery disease. Diabetes patients showed higher rates of ICU admission (11.1% vs. 7.1%), NIV requirement (9.6% vs. 6.4%), and intubation (5.45% vs. 2%) compared to the non-diabetes group. Advanced age was a predictor of a worsening COVID-19 course, while diabetes (p < 0.050) and hypertension (p < 0.025) were significant predictors of death from COVID-19. Nearly three-fourths (284 (73.4%)) of the diabetic patients developed worsened hyperglycemia as compared to one-fifth (171 (20.9%)) of the nondiabetic patients. New-onset diabetes was detected in 9.8% of COVID-19 patients. COVID-19 severity is higher in the presence of diabetes and is associated with worsening hyperglycemia and poor clinical outcomes. Preexisting hypertension is a predictor of COVID-19 severity and death.

Direct Detection of Glycated Human Serum Albumin and Hyperglycosylated IgG3 in Serum, by MALDI-ToF Mass Spectrometry, as a Predictor of COVID-19 Severity.

The prefusion spike protein of SARS-CoV-2 binds advanced glycation end product (AGE)-glycated human serum albumin (HSA) and a higher mass (hyperglycosylated/glycated) immunoglobulin (Ig) G3, as determined by matrix assisted laser desorption mass spectrometry (MALDI-ToF). We set out to investigate if the total blood plasma of patients who had recovered from acute respiratory distress syndrome (ARDS) as a result of COVID-19, contained more glycated HSA and higher mass (glycosylated/glycated) IgG3 than those with only clinically mild or asymptomatic infections. A direct serum dilution, and disulphide bond reduction, method was developed and applied to plasma samples from SARS-CoV-2 seronegative (n = 30) and seropositive (n = 31) healthcare workers (HCWs) and 38 convalescent plasma samples from patients who had been admitted with acute respiratory distress (ARDS) associated with COVID-19. Patients recovering from COVID-19 ARDS had significantly higher mass AGE-glycated HSA and higher mass IgG3 levels. This would indicate that increased levels and/or ratios of hyper-glycosylation (probably terminal sialic acid) IgG3 and AGE glycated HSA may be predisposition markers for the development of COVID-19 ARDS as a result of SARS-CoV2 infection. Furthermore, rapid direct analysis of serum/plasma samples by MALDI-ToF for such humoral immune correlates of COVID-19 presents a feasible screening technology for the most at risk; regardless of age or known health conditions.

Common mitochondrial haplogroups as modifiers of the onset-age for critical COVID-19

As a key regulator of innate immunity, mitochondrial function is essential to maintain antiviral activities. Common mitochondrial DNA variants (haplogroups) have been associated with different physiological capacities and the nrisk of developing several diseases. Haplogroup H was associated with increased survival among sepsis patients, and lower risk of progression toward AIDS in HIV infected and lower manifestation of severe manifestation of herpex virus disease. We studied 316 Spanish with critical COVID-19, and found that the 7028C (haplogroup H) was protective among patients with early-onset disease (≤65 vs > 65 years, p = 0.01), while the ancestral 16223T was a risk factor for early-onset critical COVID-19 (OR = 3.36, 95 %CI = 1.49–7.54). Our work suggested that common mitochondrial variants may serve as predictors of COVID-19 severity. Additional studies to confirm this effect from other populations are of special interest.

Zinc Deficiency as Predictor of COVID-19 Severity: A Systematic Review

Introduction: Despite the fact that zinc deficiency is asymptomatic, its incidence is rising over the world, with no visible clinical manifestation. Mineral and vitamin supplementation to prevent the inflammatory response is a major concern during the COVID-19 pandemic. Zinc may play a role in the development of a stronger immunological response. Nonetheless, there is insufficient information to investigate the benefits of zinc on its own. The impact of zinc deficiency on the severity of COVID-19 infection will be discussed in this systematic study.&#x0D; Material and Methods: We used the search phrases "COVID-19" or "SARS-CoV-2" and "Zinc Deficiency" to look for publications published between 2020 and April 2021 in scholar google, PubMed, SCOPUS, and Proquest. All of the information was examined qualitatively.&#x0D; Results: There are three papers that discuss the benefits of zinc and indicate that zinc deficiency has a key influence in the severity of COVID-19. According to one study, there is no link between zinc deficiency and COVID-19 severity.&#x0D; Conclusions: COVID-19 infection is linked to low zinc levels in the blood. It may become a risk factor for COVID-19 severity or a contributing factor that goes unnoticed in regular practice. Zinc supplementation or zinc baseline serum may play a role in determining potential daily supplementation and treatment for patients at risk of zinc insufficiency in the COVID-19 group in RCT and better design studies.

Managing ANCA-associated vasculitis during COVID-19 pandemic: a single-center cross-sectional study.

The objective of the study is to report the outcomes of COVID-19 in ANCA-associated vasculitis (AAV) patients. This was a registry-based observational study conducted at a tertiary care center in north India. AAV patients with at least one follow-up visit between March 2020 and September 2021 were included. Demographic features, clinical manifestations, disease activity, and treatment details of underlying AAV were noted in all patients. Details of COVID-19 infection including severity, treatment, and outcomes were noted. Predictors of COVID-19 severity were determined using univariate analysis. A total of 33 (18.3%) out of 180 AAV patients contracted COVID-19 infection. Moderate COVID-19 infection was seen in 33.3% and severe or critical infection was seen in 36.3% of patients. Seventeen patients (51.5%) required supplemental oxygen therapy. Nine patients had active disease at the time of COVID-19 infection and three of them died due to COVID-19 infection. The risk of COVID-19 infection and its severity did not differ between patients receiving different immunosuppressants including rituximab induction. Hypothyroidism (p = 0.046) and ocular (p = 0.038) involvement due to AAV predicted the development of moderate to severe/critical COVID-19. Three (9.1%) patients died from COVID-19 and the rate of AAV flare after COVID-19 was similar to that in non-COVID-19 patients (15.3/100 person-year vs. 15.6/100 person-year, p = 0.95). Majority of the patients with AAV had moderate to severe or critical COVID-19 infection. The rate of death due to COVID-19 in AAV is higher than in general population. Use of standard remission induction regimens did not lead to increased risk of COVID-19 infection in our AAV cohort.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00296-022-05177-2.

Body Mass Index as an independent predictor for Mortality and Severe Disease among Patients with COVID-19

Objective: Worldwide studies reported variable death rates and severe disease among patients with COVID-19. The different rate of obesity across countries is one of the main predictors that may explain the diverse rate of COVID outcomes. This study explored the association between body mass index (BMI) and other predictors of COVID-19 severity and mortality. Methods: We retrospectively reviewed cases with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. We used univariate and multivariate logistic regression to understand the relationship between patients' characteristics and severe COVID-19 and mortality. Results: 297 cases (83%) of 354 COVID-19 cases reviewed were symptomatic. 66 (18.6%) were hospitalized, (5.3%) were admitted to the intensive care unit (ICU), and 2.8% (10/354) died. The risk factors associated with mortality were old age (OR 95% CI 1.08[1.0-1.15]; p&lt;0.03) and high BMI (OR 95% CI 9.29[1.92-44.98]; p&lt;0.006). High BMI was also significantly associated with critical disease (OR 95% CI 5.19[2.18-12.38]; P&lt;0.001) Conclusion: High BMI was the leading independent risk factor associated with symptomatic COVID-19, severe COVID-19, and COVID-19-related mortality. Medical interventions to prevent and treat obesity are urgently needed to reduce covid-19 related mortality.

Correction: Transmembrane protease serine 2 (TMPRSS2) rs75603675, comorbidity and sex are the primary predictors of Covid-19 severity.

We identified an error in the abstract of the article: TPMRSS2 rs75603675 OR is incorrectly indicated. It should read (OR = 2.140) instead of (OR = 0.586). We apologize for this error. However, since the main text is correct, it has no impact on the results displayed in the study.

Mean Platelet Volume as a Predictor of COVID-19 Severity: A Prospective Cohort Study in the Highlands of Peru.

Introduction: Although 80% of symptomatic individuals with COVID-19 develop mild forms, it is the severe (15%) and critical (5%) forms that have the greatest impact in the hospital setting. Recognizing markers that can predict severe forms is essential, especially in high-altitude populations. Methods: We conducted a prospective cohort study at 3200 masl (meters above sea level) in a city in Peru to determine if MPV (mean platelet volume) level is a predictor of COVID-19 severity. Patients with mild/moderate disease were enrolled and followed for 21 days or until the development of severe disease (primary outcome). A bivariate analysis was used to identify variables associated with severe disease. A ROC analysis determined the best MPV (mean platelet count) cut-off to predict COVID-19 severity, and then, a multiple regression analysis was performed. Results: 64 patients were enrolled. The median age was 48.5 years (IQT 39–64.5) and the proportion of women was 51.6%, the most frequent symptoms were chest pain (73%), fever (71%), and dyspnea (67%). The median time to develop a severe form from the onset of symptoms was 11 days (IQT 10.5–13). The most common radiographic phase on CT scan (computed tomography) was progressive (60.38%). We observed that an MPV of more than 10.15 fL in the first week of disease predicted severity regardless of age and sex at high altitudes. Conclusions: MPV in the first week of the disease may predict severity in patients diagnosed with COVID-19 at high altitudes; however, we need prospective studies with a larger population and at a different altitude, levels to confirm these findings.

Predictors of COVID-19 severity and hospitalization: A survey-based study from Jordan

ObjectivesTo explore the possible predictors of severe illness and hospitalization due to COVID-19 among Jordanians. MethodThe study was cross-sectional, survey-based and was conducted from March to July of 2021. Individuals who had recovered from COVID-19 (n = 2148) were recruited in the study. Participants were categorized according to the severity of COVID-19 infection and hospitalization. The study sample was stratified according to age, gender, body mass index (BMI), comorbidities, family income, smoking status, and ABO blood groups. Risk factors were investigated using the Chi-square test and multivariate logistic regression analyses. ResultsSevere illness and hospitalization were associated with older age, males, individuals with comorbidities, higher BMI, and lower-income. No significant differences were found in the incidence of severe illness or hospitalization frequency between the ABO groups or between smokers and non-smokers. Multivariate logistic regression analyses predicted male gender, being older than 40, having a BMI of over 30, having 3 or more comorbidities, and low family income as risk factors for severe COVID-19 outcomes. ConclusionAge was the strongest predictor for severe COVID-19 outcome, followed by having 3 or more comorbidities and to a lesser extent male gender and obesity. These results could help target at-risk groups with infection prevention measures including prioritizing primary COVID-19 vaccines, as well as booster doses.

Cluster Analysis of Biochemical Markers as Predictor of COVID-19 Severity

Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus. The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patients into two groups(severe cases and non-severe cases groups). Ferritin, lactate dehydrogenase LDH, D-dimer and CRP were markedly increased in COVID-19 patients in the first group (severe cases). Our findings imply that early measured levels of (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) are linked to a decreased probability of COVID-19 severity. Elevated levels of this biomarker may predict COVID severity development.

Long noncoding RNA HULC is an independent predictor of COVID-19 severity and mortality in relation to microRNA-9 and IL-6

&lt;abstract&gt; &lt;p&gt;LncRNA HULC regulates inflammation in vascular endothelial cells resulting in their dysfunction. Endothelial dysfunction contributes to severe COVID-19. lncRNA HULC targets miRNA-9 that play roles in the pathogenesis and progression of COVID-19 through the acute inflammatory response mediated by IL-6. This study aimed to evaluate the role of lncRNA HULC, miRNA-9, and IL-6 in estimating the severity and predicting the prognosis of COVID-19. There were 38 non-severe, 38 severe COVID-19 patients, and 38 healthy controls enrolled in this study. Expression of lncRNA HULC and miRNA-9 was performed using RT-qPCR. ELISA was utilized to measure serum IL-6. Expression of lncRNA HULC and IL-6 level were increased in severe patients compared to non-severe patients and controls (p &amp;lt; 0.001). MiRNA-9 showed the lowest expression levels in the severe patients in comparison with non-severe patients and controls (p &amp;lt; 0.001) lncRNA HULC was negatively correlated with miRNA-9 (p &amp;lt; 0.001, r = −0.582) and positively correlated with IL-6 (p &amp;lt; 0.001, r = 0.567). Furthermore, miRNA-9 showed a negative correlation with IL-6 (p &amp;lt; 0.001, r = −0.0466). For severity prediction, lncRNA HULC expression had an adjusted OR of 52.5 (95% CI: 1.43−192.2, p = 0.031). The lncRNA HULC had an adjusted mortality hazard ratio of 1.9 (95% CI: 1.02−3.56, p = 0.043) after the adjustment of IL-6. So, in COVID-19 patients, the lncRNA HULC had a positive correlation with IL-6 and a negative correlation with miRNA-9. The COVID-19 severity and mortality appear to be predicted independently by the lncRNA HULC.&lt;/p&gt; &lt;/abstract&gt;

Role of immune mediators in predicting hospitalization of SARS-CoV-2 positive patients.

BackgroundSeveral immune mediators (IM) including cytokines, chemokines, and their receptors have been suggested to play a role in COVID-19 pathophysiology and severity.AimTo determine if early IM profiles are predictive of clinical outcome and which of the IMs tested possess the most clinical utility.MethodsA custom bead-based multiplex assay was used to measure IM concentrations in a cohort of SARS-CoV-2 PCR positive patients (n = 326) with varying disease severities as determined by hospitalization status, length of hospital stay, and survival. Patient groups were compared, and clinical utility was assessed. Correlation plots were constructed to determine if significant relationships exist between the IMs in the setting of COVID-19.ResultsIn PCR positive SARS-CoV-2 patients, IL-6 was the best predictor of the need for hospitalization and length of stay. Additionally, MCP-1 and sIL-2Rα were moderate predictors of the need for hospitalization. Hospitalized PCR positive SARS-CoV-2 patients displayed a notable correlation between sIL-2Rα and IL-18 (Spearman’s ρ = 0.48, P=<0.0001).ConclusionsIM profiles between non-hospitalized and hospitalized patients were distinct. IL-6 was the best predictor of COVID-19 severity among all the IMs tested.