Brain motor and fear circuits regulate leukocytes during acute stress.

The nervous and immune systems are intricately linked1. Although psychological stress is known to modulate immune function, mechanistic pathways linking stress networks in the brain to peripheral leukocytes remain poorly understood2. Here we show that distinct brain regions shape leukocyte distribution and function throughout the body during acute stress in mice. Using optogenetics and chemogenetics, we demonstrate that motor circuits induce rapid neutrophil mobilization from the bone marrow to peripheral tissues through skeletal-muscle-derived neutrophil-attracting chemokines. Conversely, the paraventricular hypothalamus controls monocyte and lymphocyte egress from secondary lymphoid organs and blood to the bone marrow through direct, cell-intrinsic glucocorticoid signalling. These stress-induced, counter-directional, population-wide leukocyte shifts are associated with altered disease susceptibility. On the one hand, acute stress changes innate immunity by reprogramming neutrophils and directing their recruitment to sites of injury. On the other hand, corticotropin-releasing hormone neuron-mediated leukocyte shifts protect against the acquisition of autoimmunity, but impair immunity to SARS-CoV-2 and influenza infection. Collectively, these data show that distinct brain regions differentially and rapidly tailor the leukocyte landscape during psychological stress, therefore calibrating the ability of the immune system to respond to physical threats.

C-reactive protein and neutrophil-lymphocyte ratio as predictors of mortality in coronavirus disease 2019.

OBJECTIVE: This study investigates whether C-reactive protein, platelet-lymphocyte ratio, and neutrophil-lymphocyte ratio could be useful to predict mortality in COVID-19. METHODS: Data of 635 patients with COVID-19 followed up in Sinop Ataturk State Hospital from February to May 2020 were evaluated retrospectively. Diagnosis of COVID-19 was made according to the interim guidance of the World Health Organization. Patients were grouped into two groups based on mortality as survived and non-survived patients. Age, gender, neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, and C-reactive protein of the groups were investigated and compared. RESULTS: The mean age of the participants was 55.8±22.3 years. Among the patients, 584 survived and 51 patients died. Age was significantly different between the groups, 54.2±22.3 in the survived group and 75.6±11.1 in the dead group (p=0.000). In addition, neutrophil, C-reactive protein, and neutrophil-lymphocyte ratio values were significantly higher in the dead group (p=0.000). platelet-lymphocyte ratio was slightly higher in the dead group, but this difference was not significant (p=0.42). The area under the curve values for age, lymphocyte, platelet, C-reactive protein, and neutrophil-lymphocyte ratio are 0.797, 0.424, 0.485, 0.778, and 0.729, respectively. CONCLUSIONS: Our results showed that neutrophil-lymphocyte ratio and C-reactive protein are significantly higher in patients leading to death and could be effective biomarkers in predicting COVID-19 fatality. Furthermore, C-reactive protein could be used as an independent biomarker to predict death in patients with COVID-19, regardless of gender and age (p=0.000).

Prognostic value of neutrophil-to-lymphocyte ratio in COVID-19 compared with Influenza and respiratory syncytial virus infection.

A high neutrophil to lymphocyte ratio (NLR) is considered an unfavorable prognostic factor in various diseases, including COVID-19. The prognostic value of NLR in other respiratory viral infections, such as Influenza, has not hitherto been extensively studied. We aimed to compare the prognostic value of NLR in COVID-19, Influenza and Respiratory Syncytial Virus infection (RSV). A retrospective cohort of COVID-19, Influenza and RSV patients admitted to the Tel Aviv Medical Center from January 2010 to October 2020 was analyzed. Laboratory, demographic, and clinical parameters were collected. Two way analyses of variance (ANOVA) was used to compare the association between NLR values and poor outcomes among the three groups. ROC curve analyses for each virus was applied to test the discrimination ability of NLR. 722 COVID-19, 2213 influenza and 482 RSV patients were included. Above the age of 50, NLR at admission was significantly lower among COVID-19 patients (P < 0.001). NLR was associated with poor clinical outcome only in the COVID-19 group. ROC curve analysis was performed; the area under curve of poor outcomes for COVID-19 was 0.68, compared with 0.57 and 0.58 for Influenza and RSV respectively. In the COVID-19 group, multivariate logistic regression identified a high NLR (defined as a value above 6.82) to be a prognostic factor for poor clinical outcome, after adjusting for age, sex and Charlson comorbidity score (odds ratio of 2.9, P < 0.001). NLR at admission is lower and has more prognostic value in COVID-19 patients, when compared to Influenza and RSV.

Serum magnesium in patients with severe acute respiratory syndrome coronavirus 2 from Wuhan, China.

The aim of the study was to evaluate the significance of hypomagnesemia in patients with coronavirus disease 2019 (COVID-19) and clarify its possible pathogenesis. A retrospective cohort study was conducted by reviewing 83 patients hospitalized in Guanggu district, Wuhan Third Hospital, China. Clinical histories, laboratory findings and outcome data were collected. Eighteen patients had hypomagnesemia during hospitalization. Fourteen patients were in the critical group and six died. In the critical group, serum magnesium (0.72 ± 0.15 mmol/L) was much lower than that in the moderate and severe groups. At the same time, we also found that several indicators are correlated with the level of magnesium. The level of magnesium was positively associated with the lymphocyte count (r = 0.203, P = 0.004) and platelet count (r = 0.217, P = 0.002) but negatively related to the levels of CRP (r = -0.277, P = 0.000), LDH (r = -0.185, P = 0.011) and α-hydroxybutyrate dehydrogenase (r = -0.198, P = 0.008) in the critical group. Hypomagnesemia might increase symptoms and may be associated with mortality in COVID-19 by affecting enzyme activity and activating the inflammatory response. Thus, magnesium might play a key role in the pathogenesis of COVID-19.

Clinical features and death risk factors in COVID-19 patients with cancer: a retrospective study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has spread around the world. This retrospective study aims to analyze the clinical features of COVID-19 patients with cancer and identify death outcome related risk factors. METHODS: From February 10th to April 15th, 2020, 103 COVID-19 patients with cancer were enrolled. Difference analyses were performed between severe and non-severe patients. A propensity score matching (PSM) analysis was performed, including 103 COVID-19 patients with cancer and 206 matched non-cancer COVID-19 patients. Next, we identified death related risk factors and developed a nomogram for predicting the probability. RESULTS: In 103 COVID-19 patients with cancer, the main cancer categories were breast cancer, lung cancer and bladder cancer. Compared to non-severe patients, severe patients had a higher median age, and a higher proportion of smokers, diabetes, heart disease and dyspnea. In addition, most of the laboratory results between two groups were significantly different. PSM analysis found that the proportion of dyspnea was much higher in COVID-19 patients with cancer. The severity incidence in two groups were similar, while a much higher mortality was found in COVID-19 patients with cancer compared to that in COVID-19 patients without cancer (11.7% vs. 4.4%, P = 0.028). Furthermore, we found that neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) were related to death outcome. And a nomogram based on the factors was developed. CONCLUSION: In COVID-19 patients with cancer, the clinical features and laboratory results between severe group and non-severe group were significantly different. NLR and CRP were the risk factors that could predict death outcome.

Immunometabolic signatures predict risk of progression to sepsis in COVID-19.

Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986-0.995), with sensitivity of 0.978 (0.963-0.992) and specificity of 0.920 (0.890-0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952-0.977), with sensitivity of 0.993(0.984-1.000) and specificity of 0.851 (0.815-0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800-0.858), with sensitivity of 0.738 (0.695-0.781) and specificity of 0.781 (0.735-0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788-0.874), with sensitivity of 0.765 (0.697-0.832) and specificity of 0.817 (0.770-0.865).

Serological SARS-CoV-2 antibody response, potential predictive markers and safety of BNT162b2 mRNA COVID-19 vaccine in haematological and oncological patients.

Haemato-oncological patients are at risk in case of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Currently, vaccination is the best-evaluated preventive strategy. In the present study, we aimed to assess serological response, predictive markers, and safety of BNT162b2 in haemato-oncological patients. A total of 259 haemato-oncological patients were vaccinated with two 30 µg doses of BNT162b2 administered 21 days apart. Serological response was assessed by ELECSYS® Anti-SARS-CoV-2-S immunoassay before vaccination, and at 3 and 7 weeks after the first dose (T1, T2). Safety assessment was performed. At T2 spike protein receptor binding domain (S/RBD) antibodies were detected in 71·4% of haematological and in 94·5% of oncological patients (P < 0·001). Haematological patients receiving systemic treatment had a 14·2-fold increased risk of non-responding (95% confidence interval 3·2-63·3, P = 0·001). Subgroups of patients with lymphoma or chronic lymphocytic leukaemia were at highest risk of serological non-response. Low immunoglobulin G (IgG) level, lymphocyte- and natural killer (NK)-cell counts were significantly associated with poor serological response (P < 0·05). Vaccination was well tolerated with only 2·7% of patients reporting severe side-effects. Patients with side-effects developed a higher S/RBD-antibody titre compared to patients without side-effects (P = 0·038). Haematological patients under treatment were at highest risk of serological non-response. Low lymphocytes, NK cells and IgG levels were found to be associated with serological non-response. Serological response in oncological patients was encouraging. The use of BNT162b2 is safe in haemato-oncological patients.

Higher admission activated partial thromboplastin time, neutrophil-lymphocyte ratio, serum sodium, and anticoagulant use predict in-hospital COVID-19 mortality in people with Diabetes: Findings from Two University Hospitals in the U.K.

AIMS: To create and compare survival models from admission laboratory indices in people hospitalized with coronavirus disease 2019 (COVID-19) with and without diabetes. METHODS: Retrospective observational study of patients with COVID-19 with or without diabetes admitted to Sheffield Teaching Hospitals from 29 February to 01 May 2020. Predictive variables for in-hospital mortality from COVID-19 were explored using Cox proportional hazard models. RESULTS: Out of 505 patients, 156 (30.8%) had diabetes mellitus (DM) of which 143 (91.7%) had type 2 diabetes. There were significantly higher in-hospital COVID-19 deaths in those with DM [DM COVID-19 deaths 54 (34.6%) vs. non-DM COVID-19 deaths 88 (25.2%): P < 0.05]. Activated partial thromboplastin time (APPT) > 24 s without anticoagulants (HR 6.38, 95% CI: 1.07-37.87: P = 0.04), APTT > 24 s with anticoagulants (HR 24.01, 95% CI: 3.63-159.01: P < 0.001), neutrophil-lymphocyte ratio > 8 (HR 6.18, 95% CI: 2.36-16.16: P < 0.001), and sodium > 136 mmol/L (HR 3.27, 95% CI: 1.12-9.56: P = 0.03) at admission, were only associated with in-hospital COVID-19 mortality for those with diabetes. CONCLUSIONS: At admission, elevated APTT with or without anticoagulants, neutrophil-lymphocyte ratio and serum sodium are unique factors that predict in-hospital COVID-19 mortality in patients with diabetes compared to those without. This novel finding may lead to research into haematological and biochemical mechanisms to understand why those with diabetes are more susceptible to poor outcomes when infected with Covid-19, and contribute to identification of those most at risk when admitted to hospital.

The Systematic Effect of Mesenchymal Stem Cell Therapy in Critical COVID-19 Patients: A Prospective Double Controlled Trial.

The aim of this clinical trial was to control the cytokine storm by administering mesenchymal stem cells (MSCs) to critically-ill COVID-19 patients, to evaluate the healing effect, and to systematically investigate how the treatment works. Patients with moderate and critical COVID-19 clinical manifestations were separated as Group 1 (moderate cases, n = 10, treated conventionally), Group 2 (critical cases, n = 10, treated conventionally), and Group 3 (critical cases, n = 10, treated conventionally plus MSCs transplantation therapy of three consecutive doses on treatment days 0, 3, and 6, (as 3 × 106 cells/kg, intravenously). The treatment mechanism of action was investigated with evaluation markers of the cytokine storm, via biochemical parameters, levels of proinflammatory and anti-inflammatory cytokines, analyses of tissue regeneration via the levels of growth factors, apoptosis markers, chemokines, matrix metalloproteinases, and granzyme-B, and by the assessment of the immunomodulatory effects via total oxidant/antioxidant status markers and the levels of lymphocyte subsets. In the assessment of the overall mortality rates of all the cases, six patients in Group-2 and three patients in Group-3 died, and there was no loss in Group-1. Proinflammatory cytokines IFNγ, IL-6, IL-17A, IL-2, IL-12, anti-inflammatory cytokines IL-10, IL-13, IL-1ra, and growth factors TGF-ß, VEGF, KGF, and NGF levels were found to be significant in Group-3. When Group-2 and Group-3 were compared, serum ferritin, fibrinogen and CRP levels in Group-3 had significantly decreased. CD45 +, CD3 +, CD4 +, CD8 +, CD19 +, HLA-DR +, and CD16 + / CD56 + levels were evaluated. In the statistical comparison of the groups, significance was only determined in respect of neutrophils. The results demonstrated the positive systematic and cellular effects of MSCs application on critically ill COVID-19 patients in a versatile way. This effect plays an important role in curing and reducing mortality in critically ill patients.

Inflammatory biomarkers in pregnant women with COVID-19: a retrospective cohort study.

Coronavirus disease 2019 (COVID-19) is a pandemic viral disease affecting also obstetric patients and uncertainties exist about the prognostic role of inflammatory biomarkers and hemocytometry values in patients with this infection. To clarify that, we have assessed the values of several inflammatory biomarkers and hemocytometry variables in a cohort of obstetric patients hospitalized with COVID-19 and we have correlated the values at admission with the need of oxygen supplementation during the hospitalization. Overall, among 62 (27.3%) pregnant women and 165 (72.7%) postpartum women, 21 (9.2%) patients received oxygen supplementation and 2 (0.9%) required admission to intensive care unit but none died. During hospitalization leukocytes (p < 0.001), neutrophils (p < 0.001), neutrophils to lymphocytes ratio (p < 0.001) and C reactive protein (p < 0.001) decreased significantly, whereas lymphocytes (p < 0.001), platelets (p < 0.001) and ferritin (p = 0.001) increased. Lymphocyte values at admission were correlated with oxygen need, with a 26% higher risk of oxygen supplementation for each 1000 cells decreases. Overall, in obstetric patients hospitalized with COVID-19, C reactive protein is the inflammatory biomarker that better mirrors the course of the disease whereas D-dimer or ferritin are not reliable predictors of poor outcome. Care to the need of oxygen supplementation should be reserved to patients with reduced lymphocyte values at admission.

Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL).

The objective of the study was to develop and validate a prediction model that identifies COVID-19 patients at risk of requiring oxygen support based on five parameters: C-reactive protein (CRP), hypertension, age, and neutrophil and lymphocyte counts (CHANeL). This retrospective cohort study included 221 consecutive COVID-19 patients and the patients were randomly assigned randomly to a training set and a test set in a ratio of 1:1. Logistic regression, logistic LASSO regression, Random Forest, Support Vector Machine, and XGBoost analyses were performed based on age, hypertension status, serial CRP, and neutrophil and lymphocyte counts during the first 3 days of hospitalization. The ability of the model to predict oxygen requirement during hospitalization was tested. During hospitalization, 45 (41.8%) patients in the training set (n = 110) and 41 (36.9%) in the test set (n = 111) required supplementary oxygen support. The logistic LASSO regression model exhibited the highest AUC for the test set, with a sensitivity of 0.927 and a specificity of 0.814. An online risk calculator for oxygen requirement using CHANeL predictors was developed. "CHANeL" prediction models based on serial CRP, neutrophil, and lymphocyte counts during the first 3 days of hospitalization, along with age and hypertension status, provide a reliable estimate of the risk of supplement oxygen requirement among patients hospitalized with COVID-19.

Comparison of Blood Counts and Markers of Inflammation and Coagulation in Patients With and Without COVID-19 Presenting to the Emergency Department in Seattle, WA.

OBJECTIVES: We compared complete blood count (CBC) with differential and markers of inflammation and coagulation in patients with and without coronavirus disease 2019 (COVID-19) presenting to emergency departments in Seattle, WA. METHODS: We reviewed laboratory values for 1 week following each COVID-19 test for adult patients who received a standard severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcription polymerase chain reaction (RT-PCR) test before April 13, 2020. Results were compared by COVID-19 status and clinical course. RESULTS: In total 1,027 patients met inclusion criteria. Patients with COVID-19 (n = 155) had lower leukocytes (P < .0001), lymphocytes (P < .0001), platelets (P < .0001), and higher hemoglobin (P = .0140) than those without, but absolute differences were small. Serum albumin was lower in patients with COVID-19 (P < .0001) and serum albumin, neutrophil to lymphocyte ratio (NLR), and red cell distribution width (RDW) were each associated with disease severity. NLR did not differ between patients with COVID-19 and those without (P = .8012). CONCLUSIONS: Patients with COVID-19 had modestly lower leukocyte, lymphocyte, and platelet counts and higher hemoglobin values than patients without COVID-19. The NLR, serum albumin, and RDW varied with disease severity, regardless of COVID-19 status.

Th17 Cells in Viral Infections-Friend or Foe?

Th17 cells are recognized as indispensable in inducing protective immunity against bacteria and fungi, as they promote the integrity of mucosal epithelial barriers. It is believed that Th17 cells also play a central role in the induction of autoimmune diseases. Recent advances have evaluated Th17 effector functions during viral infections, including their critical role in the production and induction of pro-inflammatory cytokines and in the recruitment and activation of other immune cells. Thus, Th17 is involved in the induction both of pathogenicity and immunoprotective mechanisms seen in the host's immune response against viruses. However, certain Th17 cells can also modulate immune responses, since they can secrete immunosuppressive factors, such as IL-10; these cells are called non-pathogenic Th17 cells. Here, we present a brief review of Th17 cells and highlight their involvement in some virus infections. We cover these notions by highlighting the role of Th17 cells in regulating the protective and pathogenic immune response in the context of viral infections. In addition, we will be describing myocarditis and multiple sclerosis as examples of immune diseases triggered by viral infections, in which we will discuss further the roles of Th17 cells in the induction of tissue damage.

Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as mortality predictor of advanced stage non-small cell lung cancer (NSCLC) with COVID-19 in Indonesia.

OBJECTIVE: This study aimed to compare the mortality rate between advanced-stage non-small cell lung cancer patients (NSCLC) with and without COVID-19. This study also explores the possible laboratory characteristics used for prognostication in patients with NSCLC and COVID-19. Additionally, this study evaluated potential differences in laboratory values between the case and control groups. PATIENTS AND METHODS: This is a single-center retrospective cohort study conducted in Dharmais National Cancer Hospital, Indonesia, enrolling patients with NSCLC undergoing chemotherapy or targeted therapy between May 2020 and January 2021. All patients with NSCLC and COVID-19 in these periods were enrolled into the case group. The control group was age-matched NSCLC patients without COVID-19 that was derived from the NSCLC cohort through randomization. RESULTS: There were 342 patients with NSCLC between May 2020 and January 2021. Twenty-seven (7.9%) of the patients were infected by COVID-19. To facilitate comparison, thirty-five age-matched controls with NSCLC were selected from the cohort. The mortality rate in patients with COVID-19 was 46.2%. Eleven patients (40.7%) had severe COVID-19, of which none survived. NLR >8.35 has a sensitivity of 83.3%, specificity of 92.9%, LR+ of 12, and LR- of 0.18. The AUC was 0.946 (95% CI 0.867-1.000), p<0.001. PLR >29.14 has a sensitivity of 75.0%, specificity of 71.4%, LR+ 2.62, LR- 0.35, and AUC 0.851 (95% CI 0.706-0.996), p=0.002. Both NLR and PLR were associated with shorter time-to-mortality in the unadjusted and adjusted model CONCLUSIONS: NLR and PLR are independent predictors of mortality in COVID-19 patients with NSCLC.

Lymphocyte-monocyte-neutrophil index: a predictor of severity of coronavirus disease 2019 patients produced by sparse principal component analysis.

BACKGROUND: It is important to recognize the coronavirus disease 2019 (COVID-19) patients in severe conditions from moderate ones, thus more effective predictors should be developed. METHODS: Clinical indicators of COVID-19 patients from two independent cohorts (Training data: Hefei Cohort, 82 patients; Validation data: Nanchang Cohort, 169 patients) were retrospected. Sparse principal component analysis (SPCA) using Hefei Cohort was performed and prediction models were deduced. Prediction results were evaluated by receiver operator characteristic curve and decision curve analysis (DCA) in above two cohorts. RESULTS: SPCA using Hefei Cohort revealed that the first 13 principal components (PCs) account for 80.8% of the total variance of original data. The PC1 and PC12 were significantly associated with disease severity with odds ratio of 4.049 and 3.318, respectively. They were used to construct prediction model, named Model-A. In disease severity prediction, Model-A gave the best prediction efficiency with area under curve (AUC) of 0.867 and 0.835 in Hefei and Nanchang Cohort, respectively. Model-A's simplified version, named as LMN index, gave comparable prediction efficiency as classical clinical markers with AUC of 0.837 and 0.800 in training and validation cohort, respectively. According to DCA, Model-A gave slightly better performance than others and LMN index showed similar performance as albumin or neutrophil-to-lymphocyte ratio. CONCLUSIONS: Prediction models produced by SPCA showed robust disease severity prediction efficiency for COVID-19 patients and have the potential for clinical application.

Clinical characteristics and laboratory features of COVID-19 in high altitude areas: A retrospective cohort study.

Coronavirus disease 2019 (COVID-19) is highly contagious and has affected the whole world. We seek to investigate the clinical and laboratory characteristics of COVID-19 patients in the high altitude areas of Sichuan, China. In this retrospective cohort study, a total of 67 patients with laboratory-confirmed SARS-CoV-2 infections in Sichuan's Ngawa Tibetan and Qiang Autonomous Prefecture were included from February 1, 2020, to March 2, 2020. Their clinical characteristics, as well as radiological and laboratory features, were extracted. Four (6.0%) patients were categorized as severe cases; 39 (58.2%) were non-severe cases, and 24 (35.8%) were asymptomatic cases. A total of 46 (68.7%) patients were associated with cluster infection events in this study. The most common symptoms were cough, sputum production, dyspnea, fatigue or myalgia, and headache. Seven (10.4%) patients showed leucopenia, and 20 (29.9%) patients showed lymphopenia. Lymphocyte counts and neutrophil-to-lymphocyte ratios (NPR) were different between the three groups. In total, 14 (20.9%) patients had thrombocytopenia, and prothrombin times (PT) and fibrinogen levels differed between groups. We also found significant differences in sodium, chloride and calcium levels between the three groups. Antiviral therapy did not lead to obvious adverse events or shortened durations from initial positive to subsequent negative nuclei acid tests. Advanced age, hypertension, high neutrophil count, the neutrophil-to-lymphocyte ratio, fibrinogen and lactate dehydrogenase levels were identified as independent risk factors for symptomatic cases of COVID-19. In conclusion, the symptoms of patients in high altitude areas were mild, and about one third were asymptomatic. We also identified several independent risk factors for symptomatic cases of COVID-19.

Distinguishing between COVID-19 and influenza during the early stages by measurement of peripheral blood parameters.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 infection. This study aims to examine the changes in peripheral blood parameters during the early stages of COVID-19 and influenza. We analyzed the peripheral blood parameters of 169 COVID-19 patients and 131 influenza patients during the early-onset stage. Results from the patients with COVID-19 were compared with those from healthy controls and influenza patients. In addition, results from patients with common and severe COVID-19 were further compared. There were significant differences between COVID-19 and influenza patients in terms of age, white blood cell count, platelet count, percentage of neutrophils, percentage of lymphocytes, percentage of monocytes, percentage of eosinophils, percentage of basophils, neutrophil, count and monocyte count. Two parameters (monocyte count and percentage of basophils) were combined to clarify the diagnostic efficacy of COVID-19 and influenza and the area under the curve was found to be 0.772. Comparison of peripheral blood parameters from common COVID-19, severe COVID-19, and influenza patients revealed many differences during the early disease stages. The diagnostic formula developed by this study will be of benefit for physicians in the differentiation of COVID-19 and influenza.

Bronchoalveolar lavage fluid characteristics and outcomes of invasively mechanically ventilated patients with COVID-19 pneumonia in Genoa, Italy.

BACKGROUND: The primary objective of the study is to describe the cellular characteristics of bronchoalveolar lavage fluid (BALF) of COVID-19 patients requiring invasive mechanical ventilation; the secondary outcome is to describe BALF findings between survivors vs non-survivors. MATERIALS AND METHODS: Patients positive for SARS-CoV-2 RT PCR, admitted to ICU between March and April 2020 were enrolled. At ICU admission, BALF were analyzed by flow cytometry. Univariate, multivariate and Spearman correlation analyses were performed. RESULTS: Sixty-four patients were enrolled, median age of 64 years (IQR 58-69). The majority cells in the BALF were neutrophils (70%, IQR 37.5-90.5) and macrophages (27%, IQR 7-49) while a minority were lymphocytes, 1%, TCD3+ 92% (IQR 82-95). The ICU mortality was 32.8%. Non-survivors had a significantly older age (p = 0.033) and peripheral lymphocytes (p = 0.012) were lower compared to the survivors. At multivariate analysis the percentage of macrophages in the BALF correlated with poor outcome (OR 1.336, CI95% 1.014-1.759, p = 0.039). CONCLUSIONS: In critically ill patients, BALF cellularity is mainly composed of neutrophils and macrophages. The macrophages percentage in the BALF at ICU admittance correlated with higher ICU mortality. The lack of lymphocytes in BALF could partly explain a reduced anti-viral response.

Pattern of inflammatory immune response determines the clinical course and outcome of COVID-19: unbiased clustering analysis.

The objective of the study was to identify distinct patterns in inflammatory immune responses of COVID-19 patients and to investigate their association with clinical course and outcome. Data from hospitalized COVID-19 patients were retrieved from electronic medical record. Supervised k-means clustering of serial C-reactive protein levels (CRP), absolute neutrophil counts (ANC), and absolute lymphocyte counts (ALC) was used to assign immune responses to one of three groups. Then, relationships between patterns of inflammatory responses and clinical course and outcome of COVID-19 were assessed in a discovery and validation cohort. Unbiased clustering analysis grouped 105 patients of a discovery cohort into three distinct clusters. Cluster 1 (hyper-inflammatory immune response) was characterized by high CRP levels, high ANC, and low ALC, whereas Cluster 3 (hypo-inflammatory immune response) was associated with low CRP levels and normal ANC and ALC. Cluster 2 showed an intermediate pattern. All patients in Cluster 1 required oxygen support whilst 61% patients in Cluster 2 and no patient in Cluster 3 required supplementary oxygen. Two (13.3%) patients in Cluster 1 died, whereas no patient in Clusters 2 and 3 died. The results were confirmed in an independent validation cohort of 116 patients. We identified three different patterns of inflammatory immune response to COVID-19. Hyper-inflammatory immune responses with elevated CRP, neutrophilia, and lymphopenia are associated with a severe disease and a worse outcome. Therefore, targeting the hyper-inflammatory response might improve the clinical outcome of COVID-19.