Neutrophil-to-Lymphocyte, Lymphocyte-to-Monocyte, and Platelet-to-Lymphocyte Ratios: Prognostic Significance in COVID-19

Evaluating Personalized Add-On Ayurveda Therapy in Oxygen-Dependent Diabetic COVID-19 Patients: A 60-Day Study of Symptoms, Inflammation, and Radiological Changes

Background Effective management of both acute and post-acute sequelae of SARS-CoV-2 is essential, particularly for type 2 diabetes mellitus (T2DM) patients, who are at increased risk of severe pro-inflammatory responses and complications. Persistent symptoms and residual lung and cardiovascular damage in post-coronavirus disease (COVID-19) individuals highlight the need for comprehensive long-term treatment strategies. Conventional treatments, including Remdesivir and glucocorticoids, have limitations, suggesting that further investigation into Ayurvedic therapies could be beneficial, though controlled trials are currently limited. Objectives Evaluate the effectiveness and safety of Ayurveda with the standard of care (SOC) versus SOC in improving symptoms, moderating immune responses (interleukin-6 (IL-6), C-reactive protein (CRP), neutrophil-lymphocyte ratio (NLR), and radiological outcomes in oxygen-dependent, high-risk, non-vaccinated type 2 diabetes COVID-19 patients over 60 days, and thus addressing their heightened vulnerability to severe infections. Methods A controlled trial with 50 diabetic COVID-19 patients, aged 18-80, with an NLR of >= 4, primarily on Remdesivir, was assigned to Group 1 (Add-on Ayurveda+SOC, n=30) or Group 2 (SOC, n=20) based on their voluntary choice with follow-up on days 14, 28, and 60. Parametric outcomes in group analysis were assessed with robust regression and non-parametric outcomes with Cochran-Mantel-Haenszel, log-rank test, and chi-square tests at 95% confidence interval (CI). Results Group 1 exhibited statistically significant improvements in fever, cough, diarrhea, as well as NLR, IL-6, and CRP by 14 days, and in anosmia, loss of taste, shortness of breath, general weakness, and headache by 60 days. Though the sample size is small, notable improvements can be seen in troponin levels in Group 1 at 28 and 60 days. High-resolution computer tomography COVID-19 reporting and data system (HRCT CO-RADS) scores improved more slowly in Group 2 than in Group 1. Survival rates were 96.4% for Group 1 and 90% for Group 2. Numbers were too small for reliable comparisons at 60 days.  Conclusion The add-on Ayurveda group showed a better symptomatic response, and faster normalization in inflammatory markers, including IL-6 and NLR by 14 days, and cardiac markers by 28 days. Minimal clinical and no laboratory adverse events were observed. This study supports the need for a randomized, double-blind trial.

Monocyte-to-platelets ratio (MPR) at diagnosis is associated with inferior progression-free survival in patients with mantle cell lymphoma: a multi-center real-life survey

Mantle cell lymphoma (MCL) pathogenesis is strongly related to the role of the tumor immune microenvironment (TIME) in which MCL cells proliferate. TIME cells can produce growth signals influencing MCL cells' survival and exert an antitumoral immune response suppression. The activity of TIME cells might be mirrored by some ratios of peripheral blood cell subpopulations, such as the monocyte-to-platelet ratio (MPR). We reviewed the clinical features of 165 consecutive MCL patients newly diagnosed and not eligible for autologous stem cell transplantation (both for age or comorbidities) who accessed two Italian Centers between 2006 and 2020. MPR was calculated using data obtained from the complete blood cell count at diagnosis before any cytotoxic treatment and correlated with PFS. Univariate analysis showed that MPR ≥ 3 was associated with inferior PFS (p = 0.02). Multivariate analysis confirmed that MPR ≥ 3, LDH > 2.5 ULN, and bone marrow involvement were significant independent variables in predicting PFS. For these reasons, MPR ≥ 3 seems the most promising prognostic factor in patients with MCL, and it could be considered a variable in new predictive models.

The Role of Sequentially Monitored Laboratory Values and Inflammatory Biomarkers in Assessing the Severity of COVID-19

With the onset of the pandemic in 2020, COVID-19 pneumonia has become a common cause for hospitalization and is associated with high mortality rates. Inflammatory biomarkers play a crucial role in understanding and monitoring the progression of various diseases, including COVID-19. The objective of this study was to assess the significance of sequentially monitored standard laboratory tests, including complete blood cell count, D-dimer, fibrinogen, ferritin, albumin, C-reactive protein (CRP), as well as newly calculated inflammatory biomarkers in predicting the severity and prognosis of COVID-19 pneumonia. This single-center retrospective study included 194 patients hospitalized due to COVID-19 pneumonia. Patients were grouped based on the severity of their clinical symptoms, with 134 categorized as severe disease and 60 as mild-moderate disease. The patients' demographic data and laboratory values at hospital admission and on the third day of hospitalization were comparatively evaluated. In the severe illness group, there were more complaints about shortness of breath and a significant drop in the SPO2 value was observed at the time of application (p =0.005 and p<0.001, respectively). The overall mortality rate in all patients was 9% (18/194), and all deaths occurred within the severe disease group. All laboratory parameters, with the exception of platelet count and ferritin levels, were significantly associated and correlated with the severity of the disease during the hospitalization period. Among the biomarkers, there was no significant difference in neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) on the first day, a significant increase was observed on the third day of hospitalization in the severe disease group (p=0.050 vs. 0.003 and p=0.073 vs. 0.020, respectively). No significant difference was observed only in the PNR (platelet/neutrophil ratio) value among the inflammatory biomarkers (p=0.090 vs. p=0.354). In conclusion, the SPO2 level of COVID-19 patients at admission and the subsequent laboratory parameters examined show a significant relationship with the severity of the disease. In addition, simple inflammation biomarkers derived from laboratory values have shown a very significant relationship and correlation in the diagnosis and follow-up of the disease. In both admission and follow-up evaluation, a more significant association was observed with CRP-related biomarkers such as CRP/albumin ratio and CRP/lymphocyte ratio rather than NLR and PLR, which are widely used in the literature, in showing the severity of COVID-19. In patients with pneumonia, the laboratory assessment made on the third day of hospitalization reflects the severity of the disease more clearly than on the first day.

Leveraging machine learning to distinguish between bacterial and viral induced pharyngitis using hematological markers: a retrospective cohort study

Accurate differentiation between bacterial and viral-induced pharyngitis is recognized as essential for personalized treatment and judicious antibiotic use. From a cohort of 693 patients with pharyngitis, data from 197 individuals clearly diagnosed with bacterial or viral infections were meticulously analyzed in this study. By integrating detailed hematological insights with several machine learning algorithms, including Random Forest, Neural Networks, Decision Trees, Support Vector Machine, Naive Bayes, and Lasso Regression, for potential biomarkers were identified, with an emphasis being placed on the diagnostic significance of the Monocyte-to-Lymphocyte Ratio. Distinct inflammatory signatures associated with bacterial infections were spotlighted in this study. An innovation introduced in this research was the adaptation of the high-accuracy Lasso Regression model for the TI-84 calculator, with an AUC (95% CI) of 0.94 (0.925-0.955) being achieved. Using this adaptation, pivotal laboratory parameters can be input on-the-spot and infection probabilities can be computed subsequently. This methodology embodies an improvement in diagnostics, facilitating more effective distinction between bacterial and viral infections while fostering judicious antibiotic use.

Systemic Inflammation Response Index as a Predictor of Stroke Risk in Elderly Patients with Hypertension: A Cohort Study

Objective

This study aimed to evaluate the relationship between the systemic inflammation response index (SIRI) and the risk of stroke and its subtypes in elderly patients with hypertension and to explore its predictive accuracy and any potential effect modifiers.

Methods

The study included 4749 participants with no history of stroke at baseline. Cox regression was used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CIs). Interaction tests and subgroup analyses were conducted. The predictive performance of various inflammatory indicators for stroke was compared using the area under the curve (AUC), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

Results

During a median follow-up period of 3.2 years, 640 strokes were recorded, of which 526 were ischemic and the remainder hemorrhagic. After adjustment for confounders, compared to the reference group, the HRs (95% CI) of stroke were 1.28 (95% CI, 1.01-1.64) and 1.46 (95% CI, 1.14-1.88) for participants in the second and third tertiles, respectively. We observed interactions between SIRI and homocysteine levels (< 15 vs. ≥ 15 μmol/L) (p for interaction = 0.014) on ischemic stroke risk. Furthermore, the AUC, NRI, and IDI analyses demonstrated that SIRI exhibited better predictive value for stroke risk when compared to other indicators. Similar results were observed for both ischemic and hemorrhagic strokes.

Conclusion

Elevated SIRI levels were significantly associated with the risk of stroke and its subtypes in elderly patients with hypertension, suggesting its potential as a promising indicator for stroke risk in this population. However, larger prospective studies are needed to confirm these findings.

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

Abnormal immunological indicators associated with disease severity and mortality in patients with COVID-19 have been reported in several observational studies. However, there are marked heterogeneities in patient characteristics and research methodologies in these studies. We aimed to provide an updated synthesis of the association between immune-related indicators and COVID-19 prognosis. We conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune-related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes. A total of 145 studies were included in the current meta-analysis, with 26 immunological, 11 hematological, 5 inflammatory, 4 coagulation, and 10 biochemical variables reported. Of them, levels of cytokines, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, IgG, and CD4+ T/CD8+ T cell ratio, WBC, neutrophil, platelet, ESR, CRP, ferritin, SAA, D-dimer, FIB, and LDH were significantly increased in severely ill patients or non-survivors. Moreover, non-severely ill patients or survivors presented significantly higher counts of lymphocytes, monocytes, lymphocyte/monocyte ratio, eosinophils, CD3+ T,CD4+T and CD8+T cells, B cells, and NK cells. The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19 containing IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells, and their subtype CD4+ and CD8+ T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with poor prognosis. Therefore, parameters of immune response dysfunction combined with inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict severe patients and those non-survivors.

Evaluation of Lymphocyte-to-Monocyte Ratio and Mean Platelet Volume-to-Platelet Ratio in Rhegmatogenous Retinal Detachment

Purpose

To assess the predictive value of inflammatory blood biomarkers in rhegmatogenous retinal detachment (RRD) patients and its correlation with proliferative retinopathy (PVR) grade.

Methods

82 RRD patients and 1 : 1 age- and gender-randomly matched cataract patients as the control group were included. The clinical features and laboratory parameters of all participants were collected and recorded, and the comprehensive index of inflammatory blood and its correlation with PVR were calculated.

Results

Monocytes and monocyte-to-high-density lipoprotein ratio (MHR) were significantly lower (P=0.005, P=0.044), while mean platelet volume (MPV), lymphocyte-to-monocyte ratio (LMR), and MPV-to-platelet ratio (MPR) were significantly higher in RRD patients as compared with the control group (P=0.013, P=0.019, P=0.037). LMR and MPR might be the predictors of RRD. The receiver operating characteristics analysis showed that the values of MPV, LMR, and MPR in RRD patients were 0.612, 0.606, and 0.594, respectively. PVR grade was not associated with inflammatory blood biomarkers.

Conclusion

The increase in MPV, LMR, and MPR were associated with increased odds of RRD. LMR and MPR may be useful as inexpensive and effortless biomarkers for assessing the occurrence of RRD.

Neutrophil-to-Lymphocyte Ratio and Cut-off Values as Predictor of Severity and Mortality in COVID-19 Patients in Millennium COVID-19 Care Center, Addis Ababa, Ethiopia

Background

Early identification of patients at high risk of poor clinical outcomes is the key to success in saving the lives of patients with coronavirus disease 2019 (COVID-19). Neutrophil to Lymphocyte Ratio (NLR) is an easily available and cheap surrogate inflammatory marker, its baseline NLR role in African COVID-19 patients remains to be investigated. The objective of the study aimed to evaluate the role of NLR as a predictor of severity and mortality of COVID-19 patients admitted at the Millennium COVID 19 care center in Addis Ababa, Ethiopia.

Methods

A cross-sectional study was conducted on patients with COVID-19 admitted to the Millennium COVID-19 care center from August 1 to October 30, 2021. Receiver Operating Characteristic curve analysis was used to calculate the area under the curve to assess the predictive capacity of NLR on mortality and severity. Multivariable logistic regression analysis was done to identify the association between independent variables and disease outcomes with an Adjusted Odds Ratio (AOR), P-value, and 95% CI for AOR were used for testing significance.

Results

The NLR of 9.47 was identified as the optimal cut-off value for predicting mortality with a sensitivity of 88.7% and a specificity of 95.4% (Area Under the Curve (AUC):0.95, 95% CI 0.92-98; P<0.001) and the NLR of 5.86 was an effective threshold value in predicting the severity of disease with a sensitivity of 92.2% and a specificity of 75% (AUC:0.85, 95% CI 0.800-0.905; P<0.001). In multivariable logistic regression analysis, after adjusting for confounding factors, NLR of more than 9.47 and 5.86 was significantly associated with all-cause of in-hospital mortality (AOR=4.73, 95% CI, 1.19-33.68; P<0.02), and severity of disease (AOR=12.98, 95% CI 3.85-43.80; P=0.001), respectively.

Conclusion

NLR greater than 9.47 and 5.86 effectively predict mortality and severity of the disease, respectively. It provides an objective input for early decision-making in inpatient management especially in resources limited area.

Platelet Indices and Platelet to Lymphocyte Ratio (PLR) as Markers for Predicting COVID-19 Infection Severity

Background Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (or coronavirus disease 2019; COVID-19) has caused a large number of infections across the globe. Numerous markers are being used to predict the severity of infection. This study was undertaken to assess the utility of platelet count, mean platelet volume (MPV), platelet distribution width (PDW), and platelet lymphocyte ratio (PLR) as markers of severity and mortality among patients with COVID-19 infection. Methodology This is a retrospective study conducted in a tertiary care center in India from April 2021 to June 2021. Patients admitted with COVID-19 infection were included in the study. Based on the severity, patients were categorized into the mild and severe (moderate severity included) groups. Platelet count, MPV, PDW, and PLR done at admission were studied and correlated with the disease severity and mortality. Statistics The independent t-test was used to compare the variables. The receiver operating characteristic (ROC) curve was done to identify the cut-off value. Statistical analysis was performed using SPSS 18 software (SPSS Inc. Released 2009. PASW Statistics for Windows, Version 18.0. Chicago: SPSS Inc). Results One hundred patients admitted with COVID-19 infection were studied. 51 patients had a mild and 49 had a severe infection. The mean PLR was 141.40 among patients with mild illness and 252.6 with severe infection (P<0.001). The mean PLR among survivors was 104.4 (SD-23.56) and among nonsurvivors was 302.78 (SD-34.5) (P<0.001). There was no statistically significant difference between the two groups with respect to platelet count, MPV, and PDW. Conclusion PLR was found to be a reliable marker of severity and mortality among patients with COVID-19 illness.

The Role of Neutrophil-to-Lymphocyte Ratio in Risk Stratification and Prognostication of COVID-19: A Systematic Review and Meta-Analysis

Several studies have proposed that the neutrophil−lymphocyte ratio (NLR) is one of the various biomarkers that can be useful in assessing COVID-19 disease-related outcomes. Our systematic review analyzes the relationship between on-admission NLR values and COVID-19 severity and mortality. Six different severity criteria were used. A search of the literature in various databases was conducted from 1 January 2020 to 1 May 2021. We calculated the pooled standardized mean difference (SMD) for the collected NLR values. A meta-regression analysis was performed, looking at the length of hospitalization and other probable confounders, such as age, gender, and comorbidities. A total of sixty-four studies were considered, which included a total of 15,683 patients. The meta-analysis showed an SMD of 3.12 (95% CI: 2.64−3.59) in NLR values between severe and non-severe patients. A difference of 3.93 (95% CI: 2.35−5.50) was found between survivors and non-survivors of the disease. Upon summary receiver operating characteristics analysis, NLR showed 80.2% (95% CI: 74.0−85.2%) sensitivity and 75.8% (95% CI: 71.3−79.9%) specificity for the prediction of severity and 78.8% (95% CI: 73.5−83.2%) sensitivity and 73.0% (95% CI: 68.4−77.1%) specificity for mortality, and was not influenced by age, gender, or co-morbid conditions. Conclusion: On admission, NLR predicts both severity and mortality in COVID-19 patients, and an NLR > 6.5 is associated with significantly greater the odds of mortality.

Value of hematological parameters for predicting patients with severe coronavirus disease 2019: a real-world cohort from Morocco

Objective

Coronavirus disease 2019 (COVID-19) is a viral disease caused by severe acute respiratory syndrome coronavirus 2. The clinical manifestations and the evolution of patients with COVID-19 are variable. In addition to respiratory involvement, COVID-19 leads to systemic involvement and can affect the hematopoietic system. This study aimed to evaluate the prognostic value of hematological and hemocytometric parameters in predicting the severity of patients with COVID-19.

Methods

We performed a retrospective study at Mohammed VI university Hospital from 1 March to 11 November 2020. We collected demographic characteristics and hematological findings of incident COVID-19 cases.

Results

A total of 245 patients were included in our study. We found that the rate of lymphopenia was significantly reduced in patients who were severely affected by COVID-19. Additionally, the rate of neutrophilia, the neutrophil side fluorescence light signal, monocyte fluorescent intensity, monocyte size, the neutrophil-to-lymphocyte ratio, the platelet-to-lymphocyte ratio, and the lymphocyte-to-monocyte ratio were significantly elevated in patients who were severely affected by COVID-19.

Conclusions

These results are consistent with the literature regarding the predictive value of these markers. A prospective validation in a large population with a longer follow-up is required.

A Pilot Study on COVID-19 Positive Subjects: An Excerpt of Post-Infection-Pro-Diabetic Disposition & Related Consequences in Correlation to Hepato-Pancreatic Bio-Markers, Pro-Inflammatory Cytokines and Other Risk Factors

COVID-19, a global pandemic that led to increased morbidity and mortality worldwide since its outcome at the end of the year 2019. A newly discovered variant of severe acute respiratory distress syndrome coronavirus-2 (SARS-CoV-2) was the arbitrator for spreading the syndrome by droplet transmission causing multi-organ failure in many occasions. A post-infection-pro-diabetic disposition was found evident in this study with the persistence of hepato-pancreatic aberrations in respect of reference range of tissue specific bio-markers in hospital admitted COVID-19 cases. The results of this study show that hyperglycemia is a risk factor in precipitating disease oriented complications to the patients with COVID-19 disease. A post-infection follow- up on glycemic-index and related complexities is a vital need to the COVID-19 infected convalescent subjects. Implementation of guidelines on social measure and awareness of anti-viral interventions may be the only way to prevent COVID-19 transmission.

Utility of Monocyte Expression of HLA-DR versus T Lymphocyte Frequency in the Assessment of COVID-19 Outcome

Background

Dysregulated immunity is a hallmark of SARS-CoV-2 infection. Immune suppression is indicated by low monocyte expression of human leukocyte antigen D-related (mHLA-DR). T cells are important antiviral cells. We aimed to assess the role of mHLA-DR and T lymphocyte frequency in predicting COVID-19 severity.

Patients and Methods

This cross-sectional study enrolled 97 SARS-CoV-2 positive patients, including mild to moderate (n = 49) and severe cases admitted to intensive care unit (ICU) (n = 48). These ICU cases were further subdivided into survivors (n = 35) and non-survivors (n = 13).

Results

Severe cases had a significant decrease in the mHLA-DR mean fluorescence intensity (MFI) and T lymphocyte percentage compared to mild to moderate cases (P<0.001). Non-survivors had a lower T lymphocyte percentage (P=0.004) than survivors. The mHLA-DR MFI and T lymphocyte percentage correlated with oxygen saturation (r=0.632, P<0.001) and (r=0.669, P<0.001), respectively. According to the ROC curves, mHLA-DR MFI, at a cutoff of 143 and an AUC of 0.9, is a reliable biomarker for distinguishing severe COVID-19 cases, with 89.6% sensitivity and 81.6% specificity, while T lymphocyte frequency had 81.3% sensitivity and 81.6% specificity at a cutoff of 54.4% and an AUC of 0.9. The T lymphocyte percentage as a predictor of ICU survival at a cutoff of 38.995% exhibited 100% sensitivity and 57.1% specificity. According to multivariate regression analysis, reduced mHLA-DR MFI and T lymphocyte percentage are independent predictors of COVID-19 severity (OR = 0.976, 95% CI: 0.955–0.997, P = 0.025) and (OR = 0.849, 95% CI: 0.741–0.972, P = 0.018), respectively.

Conclusion

Reduced mHLA-DR expression and T-lymphocyte percentage are independent predictors of COVID-19 severity. Oxygen saturation percentage is correlated with mHLA-DR MFI and T lymphocyte frequency. The T lymphocyte frequency is a proposed predictor of COVID-19 survival in ICU admitted patients.

Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia

The highly heterogeneous symptomatology and unpredictable progress of COVID-19 triggered unprecedented intensive biomedical research and a number of clinical research projects. Although the pathophysiology of the disease is being progressively clarified, its complexity remains vast. Moreover, some extremely infrequent cases of thrombotic thrombocytopenia following vaccination against SARS-CoV-2 infection have been observed. The present study aimed to map the signaling pathways of thrombocytopenia implicated in COVID-19, as well as in vaccine-induced thrombotic thrombocytopenia (VITT). The biomedical literature database, MEDLINE/PubMed, was thoroughly searched using artificial intelligence techniques for the semantic relations among the top 50 similar words (>0.9) implicated in COVID-19-mediated human infection or VITT. Additionally, STRING, a database of primary and predicted associations among genes and proteins (collected from diverse resources, such as documented pathway knowledge, high-throughput experimental studies, cross-species extrapolated information, automated text mining results, computationally predicted interactions, etc.), was employed, with the confidence threshold set at 0.7. In addition, two interactomes were constructed: i) A network including 119 and 56 nodes relevant to COVID-19 and thrombocytopenia, respectively; and ii) a second network containing 60 nodes relevant to VITT. Although thrombocytopenia is a dominant morbidity in both entities, three nodes were observed that corresponded to genes (AURKA, CD46 and CD19) expressed only in VITT, whilst ADAM10, CDC20, SHC1 and STXBP2 are silenced in VITT, but are commonly expressed in both COVID-19 and thrombocytopenia. The calculated average node degree was immense (11.9 in COVID-19 and 6.43 in VITT), illustrating the complexity of COVID-19 and VITT pathologies and confirming the importance of cytokines, as well as of pathways activated following hypoxic events. In addition, PYCARD, NLP3 and P2RX7 are key potential therapeutic targets for all three morbid entities, meriting further research. This interactome was based on wild-type genes, revealing the predisposition of the body to hypoxia-induced thrombosis, leading to the acute COVID-19 phenotype, the 'long-COVID syndrome', and/or VITT. Thus, common nodes appear to be key players in illness prevention, progression and treatment.

Spine artery dissection as another puzzle of Covid-19 (Clinical case)

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Comprehensive Analysis of the Systemic Transcriptomic Alternations and Inflammatory Response during the Occurrence and Progress of COVID-19

The pandemic of the coronavirus disease 2019 (COVID-19) has posed huge threats to healthcare systems and the global economy. However, the host response towards COVID-19 on the molecular and cellular levels still lacks full understanding and effective therapies are in urgent need. Here, we integrate three datasets, GSE152641, GSE161777, and GSE157103. Compared to healthy people, 314 differentially expressed genes were identified, which were mostly involved in neutrophil degranulation and cell division. The protein-protein network was established and two significant subsets were filtered by MCODE: ssGSEA and CIBERSORT, which comprehensively revealed the alternation of immune cell abundance. Weighted gene coexpression network analysis (WGCNA) as well as GO and KEGG analyses unveiled the role of neutrophils and T cells during the progress of the disease. Based on the hospital-free days after 45 days of follow-up and statistical methods such as nonnegative matrix factorization (NMF), submap, and linear correlation analysis, 31 genes were regarded as the signature of the peripheral blood of COVID-19. Various immune cells were identified to be related to the prognosis of the patients. Drugs were predicted for the genes in the signature by DGIdb. Overall, our study comprehensively revealed the relationship between the inflammatory response and the disease course, which provided strategies for the treatment of COVID-19.

The inflammatory markers of multisystem inflammatory syndrome in children (MIS-C) and adolescents associated with COVID-19: A meta-analysis

To conduct a systematic review and meta-analysis to characterize inflammatory markers in comparisons of multisystem inflammatory syndrome in children (MIS-C) versus severe/non-severe COVID-19, severe MIS-C versus non-severe MIS-C, and among age groups of MIS-C. Nine databases were searched for studies on inflammatory markers of MIS-C. After quality checks, data were pooled using a fixed or random effects model. Inflammatory markers included white blood cell count (WBC) or leukocytes, absolute lymphocyte count (ALC), absolute neutrophil count (ANC), platelet count (PLT), C-reactive protein (CRP), procalcitonin (PCT), ferritin, D-dimer, lactate dehydrogenase (LDH), fibrinogen, and erythrocyte sedimentation rate (ESR) for comparisons by severity and age. Twenty-one studies with 1735 participants yielded 787 MIS-C patients. Compared to non-severe COVID-19 patients, MIS-C patients had lower ALC and higher ANC, CRP, and D-dimer levels. Compared to severe COVID-19 patients, MIS-C patients had lower LDH and PLT counts and higher ESR levels. Severe MIS-C patients had higher levels of WBC, ANC, CRP, D-dimer, and ferritin than non-severe MIS-C patients. For MIS-C, younger children (0-5 years) had lower CRP and ferritin levels than middle-aged/older children/adolescents. Measurement of inflammatory markers might assist clinicians in accurate evaluation and diagnosis of MIS-C and the associated disorders.