Predictive factors for pneumonia development and progression to respiratory failure in MERS-CoV infected patients

Evaluation of various blood biomarkers associated with the outcomes of patients with COVID‑19 treated in intensive care units

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the resulting coronavirus disease 2019 (COVID-19) represented a global public health crisis and the most significant pandemic in modern times. Transmission characteristics, and the lack of effective antiviral treatment protocol and protective vaccines, pushed healthcare systems, particularly intensive care units (ICUs), to their limits and led to extreme quarantine measures to control the pandemic. It was evident from an early stage that patient stratification approaches needed to be developed to better predict disease progression. In the present study, the predictive value of clinical and blood biomarkers for the outcomes of patients with COVID-19 hospitalized in the ICU were investigated, taking age and sex into consideration. The present study analyzed blood samples from 3,050 patients with COVID-19 hospitalized in the ICU. The analysis revealed that the levels of procalcitonin, N-terminal pro-B-type natriuretic peptide, D-dimer, ferritin, liver enzymes, C-reactive protein and lactate dehydrogenase were increased and were associated with disease progression, resulting in a prolonged hospitalization period and severe COVID-19 related complications. Additionally, significant age and sex disparities among these biomarkers were documented and discussed in specific cases. On the whole, the results of the present study suggest a potential association of the demographic characteristics and blood biomarkers with prolonged hospitalization in the ICU and the mortality of patients with COVID-19.

BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data

Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge from the datasets collected from 930 COVID-19 patients hospitalized in Italy during the first wave of COVID-19 (March-June 2020). The dataset consists of twenty-five biomarkers from electronic health record and Chest X-ray (CXR) images. It is found that the system can diagnose low- or high-risk patients with an accuracy, sensitivity, and F1-score of 89.03%, 90.44%, and 89.03%, respectively. The system exhibits 6% higher accuracy than the systems that employ either CXR images or biomarker data. In addition, the system can calculate the mortality risk of high-risk patients using multivariate logistic regression-based nomogram scoring technique. Interested physicians can use the presented system to predict the early mortality risks of COVID-19 patients using the web-link: Covid-severity-grading-AI. In this case, a physician needs to input the following information: CXR image file, Lactate Dehydrogenase (LDH), Oxygen Saturation (O2%), White Blood Cells Count, C-reactive protein, and Age. This way, this study contributes to the management of COVID-19 patients by predicting early mortality risk.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00521-023-08606-w.

Assessing Biomarkers in Viral Infection

Current biomarkers to assess the risk of complications of both acute and chronic viral infection are suboptimal. Prevalent viral infections like human immunodeficiency virus (HIV), hepatitis B and C virus, herpes viruses, and, more recently, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may be associated with significant sequelae including the risk of cardiovascular disease, other end-organ diseases, and malignancies. This review considers some biomarkers which have been investigated in diagnosis and prognosis of key viral infections including inflammatory cytokines, markers of endothelial dysfunction and activation and coagulation, and the role that more conventional diagnostic markers, such as C-reactive protein and procalcitonin, can play in predicting these secondary complications, as markers of severity and to distinguish viral and bacterial infection. Although many of these are still only available in the research setting, these markers show promise for incorporation in diagnostic algorithms which may assist to predict adverse outcomes and to guide therapy.

COVID-19 Severity and Thrombo-Inflammatory Response Linked to Ethnicity

Although there is strong evidence that SARS-CoV-2 infection is associated with adverse outcomes in certain ethnic groups, the association of disease severity and risk factors such as comorbidities and biomarkers with racial disparities remains undefined. This retrospective study between March 2020 and February 2021 explores COVID-19 risk factors as predictors for patients’ disease progression through country comparison. Disease severity predictors in Germany and Japan were cardiovascular-associated comorbidities, dementia, and age. We adjusted age, sex, body mass index, and history of cardiovascular disease comorbidity in the country cohorts using a propensity score matching (PSM) technique to reduce the influence of differences in sample size and the surprisingly young, lean Japanese cohort. Analysis of the 170 PSM pairs confirmed that 65.29% of German and 85.29% of Japanese patients were in the uncomplicated phase. More German than Japanese patients were admitted in the complicated and critical phase. Ethnic differences were identified in patients without cardiovascular comorbidities. Japanese patients in the uncomplicated phase presented a suppressed inflammatory response and coagulopathy with hypocoagulation. In contrast, German patients exhibited a hyperactive inflammatory response and coagulopathy with hypercoagulation. These differences were less pronounced in patients in the complicated phase or with cardiovascular diseases. Coagulation/fibrinolysis-associated biomarkers rather than inflammatory-related biomarkers predicted disease severity in patients with cardiovascular comorbidities: platelet counts were associated with severe illness in German patients. In contrast, high D-dimer and fibrinogen levels predicted disease severity in Japanese patients. Our comparative study indicates that ethnicity influences COVID-19-associated biomarker expression linked to the inflammatory and coagulation (thrombo-inflammatory) response. Future studies will be necessary to determine whether these differences contributed to the less severe disease progression observed in Japanese COVID-19 patients compared with those in Germany.

SARS-CoV-2 in immunocompromised individuals

Immunocompromised individuals and particularly those with hematologic malignancies are at increased risk for SARS-CoV-2-associated morbidity and mortality due to immunologic deficits that limit prevention, treatment, and clearance of the virus. Understanding the natural history of viral infections in people with impaired immunity due to underlying conditions, immunosuppressive therapy, or a combination thereof has emerged as a critical area of investigation during the COVID-19 pandemic. Studies focused on these individuals have provided key insights into aspects of innate and adaptive immunity underlying both the antiviral immune response and excess inflammation in the setting of COVID-19. This review presents what is known about distinct states of immunologic vulnerability to SARS-CoV-2 and how this information can be harnessed to improve prevention and treatment strategies for immunologically high-risk populations.

Is there a relationship between epicardial adipose tissue, inflammatory markers and prognosis in COVID-19 in patients under 65 years?

Aim: This study investigated the prognostic value of epicardial adipose tissue volume (EATV) attenuation (EATA) in patients admitted to the intensive care unit for COVID-19. Materials & methods: C-reactive protein (CRP), fasting blood glucose (FBG), neutrophil and lymphocyte counts, neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-CRP ratio (LCR) were recorded. Receiver operator characteristic analysis was performed for EATV and EATA. Results: The study included 190 patients (65 deceased, 125 discharged, mean age 52.01 ± 9.6 years). The deceased group had significantly higher FBG and CRP values and significantly lower platelet count and LCR values. EATA (cut-off: -92.38 HU) and EATV (cut-off: 15.74 cm²) were significantly higher in the deceased group. EATV had a correlation with age, FBG, CRP, neutrophil, NLR and LCR, whereas EATA correlated with involvement on CT scan. Conclusion: EATV is associated with inflammatory parameters, whereas EATA is associated with CT scan involvement and can be used to predict mortality in young adult patients.

Distinct Immunological Profiles Help in the Maintenance of Salivary Secretory IgA Production in Mild Symptoms COVID-19 Patients

Background

Relevant aspects regarding the SARS-CoV-2 pathogenesis and the systemic immune response to this infection have been reported. However, the mucosal immune response of the upper airways two months after SARS-CoV-2 infection in patients with mild/moderate symptoms is still not completely described. Therefore, we investigated the immune/inflammatory responses of the mucosa of the upper airways of mild/moderate symptom COVID-19 patients two months after the SARS-CoV-2 infection in comparison to a control group composed of non-COVID-19 healthy individuals.

Methods

A cohort of 80 volunteers (age 37.2 ± 8.2), including non-COVID-19 healthy individuals (n=24) and COVID-19 patients (n=56) who presented mild/moderate symptoms during a COVID-19 outbreak in Brazil in November and December of 2020. Saliva samples were obtained two months after the COVID-19 diagnosis to assess the levels of SIgA by ELISA and the cytokines by multiplex analysis.

Results

Salivary levels of SIgA were detected in 39 volunteers into the COVID-19 group and, unexpectedly, in 14 volunteers in the control group. Based on this observation, we distributed the volunteers of the control group into without SIgA or with SIgA sub-groups, and COVID-19 group into without SIgA or with SIgA sub-groups. Individuals with SIgA showed higher levels of IL-10, IL-17A, IFN-γ, IL-12p70, IL-13, and IFN-α than those without SIgA. In intergroup analysis, the COVID-19 groups showed higher salivary levels of IL-10, IL-13, IL-17A, and IFN-α than the control group. No statistical differences were verified in the salivary levels of IL-6 and IFN-β. Lower IL-12p70/IL-10 and IFN-γ/IL-10 ratios were found in the control group without SIgA than the control group with SIgA and the COVID-19 group with SIgA.

Conclusion

We were able to present, for the first time, that associations between distinct immunological profiles can help the mucosal immunity to maintain the salivary levels of SIgA in COVID-19 patients two months after the SARS-CoV-2 infection.

Prognostic Value of C-Reactive Protein and Platelet Lymphocyte Ratio in Coronavirus Disease 19

The coronavirus (SARS-CoV-2) that causes Coronavirus disease 19 (COVID-19) has recently emerged as a cause of severe infection in a considerable percentage of infected persons. Predicting the risk factors for severe disease can greatly help manage critical cases and save lives. This study aimed to assess the prognostic value of the platelet-lymphocyte ratio (PLR) and C-reactive protein (CRP) in patients with COVID-19. This cross-sectional study enrolled 160 confirmed cases with COVID-19 by real-time polymerase chain reaction. Demographic data (age, gender, smoking status, body mass index (BMI)) and comorbidity were collected through direct interviews. Laboratory investigations, including total leukocyte count, absolute neutrophil, lymphocyte, platelet count, serum level of C-reactive protein, and hemoglobin, were obtained from the patient's records. The platelets-lymphocyte ratio was calculated by dividing absolute platelet count by absolute lymphocyte count. According to their outcome, patients were categorized into two groups: those discharged well and those who required intensive care unit (ICU) admission. Out of 160 included patients, 32 (20%) needed ICU admission due to the deterioration of their status. Age (64.28±13.08 years versus 57.43±13.15 years), hypertension (40.63% versus 20.31%) absolute neutrophil count (median = 12.9×103/ml, range 3.83-22.8×103/ml versus median=6×103/ml, range 2.17-22.8×103/ml) and PLR ((median= 257.27, range= 62.72-1072 versus median= 191.54, range= 17.85-919.12) were significantly higher in patients required ICU admission than those discharged well, and associated significantly with the severity of the disease. Advanced age, hypertension, neutrophilia, and PLR at admission are predictors of severity and need for ICU admission in patients with COVID-19. PLR is an inexpensive, easy-to-be-calculated parameter that can be used routinely to predict the severity of COVID-19. Keywords. COVID-19, intensive care unit, platelet-lymphocyte ratio

Predictors of mortality in patients less than 50 years old with coronavirus disease 2019: a multicenter experience in Istanbul

OBJECTIVE

The objectives of this study were to identify predictors of mortality in young adult patients with coronavirus disease 2019 and to assess the link between blood type and mortality in those patients.

METHODS

This multicenter retrospective study, which was conducted in seven training and research hospitals in Istanbul, involved young adults who aged ≥18 and <50 years and hospitalized with coronavirus disease 2019.

RESULTS

Among 1,120 patients, confusion at admission (p<0.001) and oxygen saturation (p<0.001) were significantly predictive factors of mortality. Blood type O was significantly associated with mortality compared to those discharged from the hospital (p<0.001). Among co-morbidities, the most reliable predictive factors were cerebral vascular disease (p<0.001) and chronic renal failure (p=0.010). Among laboratory parameters, high C-reactive protein (p<0.001) and low albumin (p<0.001) levels were predictors of mortality in young adult patients with coronavirus disease 2019.

CONCLUSIONS

SpO2 at admission was the best predictor of mortality in young adult patients with coronavirus disease 2019. The mortality rate was increased by cerebral vascular disease and chronic renal failure. Also, high C-reactive protein and low albumin levels were predictive factors of mortality. Moreover, blood type O was associated with a higher mortality rate than the other types.

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Pandemic: Are Africa's Prevalence and Mortality Rates Relatively Low?

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the cause of coronavirus disease 19 (COVID-19), has been rapidly spreading since December 2019, and within a few months, it turned out to be a global pandemic. The disease affects primarily the lungs, but its pathogenesis spreads to other organs as well. However, its mortality rates vary, and in the majority of infected people, there are no serious consequences. Many factors including advanced age, preexisting health conditions, and genetic predispositions are believed to exacerbate outcomes of COVID-19. The virus contains several structural proteins including the spike (S) protein with subunits for binding, fusion, and internalization into host cells following interaction with host cell receptors and proteases (ACE2 and TMPRSS2, respectively) to cause the subsequent pathology. Although the pandemic has spread into all countries, most of Africa is thought of as having relatively less prevalence and mortality. Several hypotheses have been forwarded as reasons for this and include warmer weather conditions, vaccination with BCG (i.e., trained immunity), and previous malaria infection. From genetics or metabolic points of view, it has been proposed that most African populations could be protected to some degree because they lack some genetic susceptibility risk factors or have low-level expression of allelic variants, such as ACE2 and TMPRSS2 that are thought to be involved in increased infection risk or disease severity. The frequency of occurrence of α-1 antitrypsin (an inhibitor of a tissue-degrading protease, thereby protecting target host tissues including the lung) deficiency is also reported to be low in most African populations. More recently, infections in Africa appear to be on the rise. In general, there are few studies on the epidemiology and pathogenesis of the disease in African contexts, and the overall costs and human life losses due to the pandemic in Africa will be determined by all factors and conditions interacting in complex ways.

Pharmaco-immunomodulatory interventions for averting cytokine storm-linked disease severity in SARS-CoV-2 infection

The year 2020 is characterised by the COVID-19 pandemic that has quelled more than half a million lives in recent months. We are still coping with the negative repercussions of COVID-19 pandemic in 2021, in which the 2nd wave in India resulted in a high fatality rate. Regardless of emergency vaccine approvals and subsequent meteoric global vaccination drives in some countries, hospitalisations for COVID-19 will continue to occur due to the propensity of mutation in SARS-CoV-2 virus. The immune response plays a vital role in the control and resolution of infectious diseases. However, an impaired immune response is responsible for the severity of the respiratory distress in many diseases. The severe COVID-19 infection persuaded cytokine storm that has been linked with acute respiratory distress syndrome (ARDS), culminates into vital organ failures and eventual death. Thus, safe and effective therapeutics to treat hospitalised patients remains a significant unmet clinical need. In that state, any clue of possible treatments, which save patients life, can be treasured for this time point. Many cohorts and clinical trial studies demonstrated that timely administration of immunomodulatory drugs on severe COVID-19 patients may mitigate the disease severity, hospital stay and mortality. This article addresses the severity and risk factors of hypercytokinemia in COVID-19 patients, with special emphasis on prospective immunomodulatory therapies.

Development and Validation of a Nomogram to Assist Monitoring Nosocomial SARS-CoV-2 Infection of Hospitalized Patients

Purpose

SARS-CoV-2 is extremely infectious, and the incidence of nosocomial infection is conceivably high. We aimed to develop and validate a nomogram to assist monitoring nosocomial SARS-CoV-2 infection in hospitalized patients.

Patients and Methods

There were 437 COVID-19 hospitalized cases and 420 negative inpatients enrolled from two hospitals in Hubei province, China. We compared the demographic and clinical characteristics of participants between the two groups. Then, LASSO regression and logistic regression were applied to build a nomogram for SARS-CoV-2 infection prediction in the development cohort. Our nomogram was assessed by area under the curve (AUC), calibration curve, decision curve (DCA) and clinical impact curve analysis (CICA).

Results

After LASSO regression filtration, eleven laboratory indicators were correlated with SARS-CoV-2 infection. Then, we integrated these features and constructed a nomogram, which showed a high AUC 0.863 (95% CI: 0.834–0.892) in the development cohort with a sensitivity of 80.41% and specificity of 77.38% and 0.813 (95% CI: 0.760–0.866) in validation cohort with a sensitivity of 82.98% and specificity of 70.43%. The calibration plot displayed that the predicted outcomes were in good concordance with the actual observations. DCA and CICA further showed a larger clinical net benefit.

Conclusion

We constructed and validated a nomogram that integrated eleven laboratory indexes to assist monitoring of nosocomial SARS-CoV-2 infection in hospitalized patients. Our nomogram is remarkably informative for clinical practice, which will be helpful for preventing SARS-CoV-2 further transmission in hospital and avoiding nosocomial infection.

Graphene Oxide versus Carbon Nanofibers in Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Films: Degradation in Simulated Intestinal Environments

Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is a microbial biodegradable polymer with a broad range of promising industrial applications. The effect of incorporation of low amounts (1% w/w) of carbon nanomaterials (CBNs) such as 1D carbon nanofibers (CNFs) or 2D graphene oxide (GO) nanosheets into the PHBV polymer matrix affects its degradation properties, as it is reported here for the first time. The study was performed in simulated gut conditions using two different media: an acidic aqueous medium (pH 6) and Gifu anaerobic medium. The results of this study showed that the incorporation of low amounts of filamentous 1D hydrophobic CNFs significantly increased the degradability of the hydrophobic PHBV after 3 months in simulated intestinal conditions as confirmed by weight loss (~20.5% w/w in acidic medium) and electron microscopy. We can attribute these results to the fact that the long hydrophobic carbon nanochannels created in the PHBV matrix with the incorporation of the CNFs allowed the degradation medium to penetrate at ultrafast diffusion speed increasing the area exposed to degradation. However, the hydrogen bonds formed between the 2D hydrophilic GO nanosheets and the hydrophobic PHBV polymer chains produced a homogeneous composite structure that exhibits lower degradation (weight loss of ~4.5% w/w after three months in acidic aqueous medium). Moreover, the water molecules present in both degradation media can be linked to the hydroxyl (-OH) and carboxyl (-COOH) groups present on the basal planes and at the edges of the GO nanosheets, reducing their degradation potential.

A Predictive Nomogram for Predicting Improved Clinical Outcome Probability in Patients with COVID-19 in Zhejiang Province, China

The aim of this research was to develop a quantitative method for clinicians to predict the probability of improved prognosis in patients with coronavirus disease 2019 (COVID-19). Data on 104 patients admitted to hospital with laboratory-confirmed COVID-19 infection from 10 January 2020 to 26 February 2020 were collected. Clinical information and laboratory findings were collected and compared between the outcomes of improved patients and non-improved patients. The least absolute shrinkage and selection operator (LASSO) logistics regression model and two-way stepwise strategy in the multivariate logistics regression model were used to select prognostic factors for predicting clinical outcomes in COVID-19 patients. The concordance index (C-index) was used to assess the discrimination of the model, and internal validation was performed through bootstrap resampling. A novel predictive nomogram was constructed by incorporating these features. Of the 104 patients included in the study (median age 55 years), 75 (72.1%) had improved short-term outcomes, while 29 (27.9%) showed no signs of improvement. There were numerous differences in clinical characteristics and laboratory findings between patients with improved outcomes and patients without improved outcomes. After a multi-step screening process, prognostic factors were selected and incorporated into the nomogram construction, including immunoglobulin A (IgA), C-reactive protein (CRP), creatine kinase (CK), acute physiology and chronic health evaluation II (APACHE II), and interaction between CK and APACHE II. The C-index of our model was 0.962 (95% confidence interval (CI), 0.931-0.993) and still reached a high value of 0.948 through bootstrapping validation. A predictive nomogram we further established showed close performance compared with the ideal model on the calibration plot and was clinically practical according to the decision curve and clinical impact curve. The nomogram we constructed is useful for clinicians to predict improved clinical outcome probability for each COVID-19 patient, which may facilitate personalized counselling and treatment.

SARS, MERS and CoVID-19: An overview and comparison of clinical, laboratory and radiological features

In the 21st century, we have seen a total of three outbreaks by members of the coronavirus family. Although the first two outbreaks did not result in a pandemic, the third and the latest outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) culminated in a pandemic. This pandemic has been extremely significant on a social and international level. As these viruses belong to the same family, they are closely related. Despite their numerous similarities, they have slight distinctions that render them distinct from one another. The Severe Acute Respiratory Distress Syndrome and Middle East Respiratory Syndrome (MERS) cases were reported to have a very high case fatality rate of 9.5 and 34.4% respectively. In contrast, the CoVID-19 has a case fatality rate of 2.13%. Also, there are no clear medical countermeasures for these coronaviruses yet. We can cross information gaps, including cultural weapons for fighting and controlling the spread of MERS-CoV and SARS-CoV-2, and plan efficient and comprehensive defensive lines against coronaviruses that might arise or reemerge in the future by gaining a deeper understanding of these coronaviruses and the illnesses caused by them. The review thoroughly summarises the state-of-the-art information and compares the biochemical properties of these deadly coronaviruses with the clinical characteristics, laboratory features and radiological manifestations of illnesses induced by them, with an emphasis on comparing and contrasting their similarities and differences.

A full-term pregnant woman with secondary Evans syndrome caused by severe coronavirus disease 2019: a case report

BACKGROUND

In this report, we describe a very challenging case of a patient with secondary Evans syndrome caused by severe coronavirus disease 2019 infection in a pregnant full-term woman.

CASE PRESENTATION

A 29-year-old full-term pregnant Indonesian woman presented with gross hematuria, dry cough, fever, dyspnea, nausea, anosmia, and fatigue 5 days after confirmation of coronavirus disease 2019 infection. Laboratory examinations showed very severe thrombocytopenia, increased indirect bilirubin, and a positive direct Coombs' test. From peripheral blood, there was an increased number of spherocytes, which indicated an autoimmune hemolytic process. Antinuclear antibody and anti-double-stranded DNA test results were negative, and her virology serological markers are also negative for human immunodeficiency virus, cytomegalovirus, and hepatitis B and C. Despite aggressive treatment with platelet transfusion, high-dose steroid, and thrombopoietin receptor agonists, the platelet count did not recover, and a speculative cesarean delivery had to be done with a very low platelet count.

The coexistence of low albumin levels and obesity worsens clinical outcomes among subjects admitted for sars-cov-2 infection

Background and aims

The clinical spectrum of the SARS-CoV-2 infection is very broad, ranging from asymptomatic infection to severe pneumonia. However, the majority of fatalities related to COVID-19 have involved old, frail and patients with comorbidities, such as obesity, groups that also have high rates of a poor nutritional status. To assess the impact on clinical outcomes of the coexistence of any degree of obesity and low albumin levels on admission among patients with COVID-19.

Methods

This is a sub-analysis of a former study where 75 patients admitted due to COVID-19 were evaluated cross-sectionally. In this analysis, patients were divided in two groups, according to the presence of obesity and albumin levels on admission lower than 3.5 g/dl.

Results

11 out 75 patients evaluated (14.7%) had obesity and albumin levels lower than 3.5 g/dl. Patients with obesity and hypoalbuminemia were older than patients without these two conditions (65.3 ± 7.7 vs 54.2 ± 17 years; p = 0.01). CRP (141.4 ± 47.9 vs 70.1 ± 60.6 mg/l; p = 0.002), D-dimer (2677.3 ± 2358.3 vs 521.7 ± 480.3 ng/ml; p = 0.001), fibrinogen (765.9 ± 123.9 vs 613.5 ± 158gr/L; p = 0.007) ferritin levels (903.1 ± 493 vs 531.4 ± 418.9 mcg/l; p = 0.01) and procalcitonin (3.5 ± 0.6 vs 1.1 ± 0.7 ng/ml; p = 0.009) were significantly higher in the group with obesity and hypoalbuminemia. Among patients with low albumin and obesity, length of hospital was higher (21.9 ± 18.7 vs 10.5 ± 9.5 days; p = 0.004) and the proportion of subjects admitted to ICU was greater (81.8% vs 11.5%; p < 0.0001). However, mortality rates were comparable between the two groups (3.8% vs 0%; p = 0.5).

Conclusions

The combination of obesity and hypoalbuminemia may worsen the prognosis of patients with a SARS-CoV-2 infection. Therefore, prompt identification and amelioration of nutritional status could be beneficial.

The journey of SARS-CoV-2 in human hosts: a review of immune responses, immunosuppression, and their consequences

Coronavirus disease 2019 (COVID-19) is a highly infectious viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Laboratory findings from a significant number of patients with COVID-19 indicate the occurrence of leukocytopenia, specifically lymphocytopenia. Moreover, infected patients can experience contrasting outcomes depending on lymphocytopenia status. Patients with resolved lymphocytopenia are more likely to recover, whereas critically ill patients with signs of unresolved lymphocytopenia develop severe complications, sometimes culminating in death. Why immunodepression manifests in patients with COVID-19 remains unclear. Therefore, the evaluation of clinical symptoms and laboratory findings from infected patients is critical for understanding the disease course and its consequences. In this review, we take a logical approach to unravel the reasons for immunodepression in patients with COVID-19. Following the footprints of the virus within host tissues, from entry to exit, we extrapolate the mechanisms underlying the phenomenon of immunodepression.

The Impact of SARS-CoV-2 Infection on Blood Coagulation and Fibrinolytic Pathways: A Review of Prothrombotic Changes Caused by COVID-19

The cardinal pathology of coronavirus disease 2019 (COVID-19) is a primary infection of pulmonary tract cells by severe acute respiratory syndrome coronavirus 2, provoking a local inflammatory response, often accompanied by cytokine storm and acute respiratory distress syndrome, especially in patients with severe disease. Systemic propagation of the disease may associate with thrombotic events, including deep vein thrombosis, pulmonary embolism, and thrombotic microangiopathy, which are important causes of morbidity and mortality in patients with COVID-19. This narrative review describes current knowledge of the pathophysiological mechanisms of COVID-19-associated coagulopathy, with focus on prothrombotic changes in hemostatic mediators, including plasma levels of clotting factors, natural anticoagulants, components of fibrinolytic system, and platelets. It will also highlight the central role of endothelial cells in COVID-19-associated coagulopathy. This narrative review discusses also potential therapeutic strategies for managing thrombotic complications. Awareness by medical experts of contributors to the pathogenesis of thrombotic events in COVID-19 is imperative to develop therapeutics not limited to regular anticoagulants. Instituting cooperation among medical personnel and researchers may lessen this novel virus' impact now, and in the event of recurrence.

Hypoalbuminemia - An Indicator of the Severity and Prognosis of COVID-19 Patients: A Multicentre Retrospective Analysis

BACKGROUND

Hypoalbuminemia has been reported in COVID-19 patients. Exploring the influencing factors and possible adverse consequences of albumin reduction may provide some guidance for the treatment of COVID-19 patients.

METHODS

In this multicentre retrospective study, we collected information including demographics, comorbidities, clinical symptoms, complications, laboratory tests, treatment, and outcomes of patients diagnosed with COVID-19 from three hospitals in Wuhan, China. We compared the indexes between patients with hypoalbuminemia and normal albumin. Regression model was used to evaluate various influencing factors of patients with hypoalbuminemia and their relationship with clinical outcomes. We also compared the changes of particular laboratory indexes in patients with hypoalbuminemia before and after enteral nutrition therapy.

RESULTS

A total of 482 patients were enrolled in the study. About 53.7% patients developed hypoalbuminemia during admission. Patients with hypoalbuminemia were older, had a higher proportion of combined diabetes mellitus, fever, dyspnea, and natriuresis, and had a relatively poorer prognosis than patients with normal albumin. Patients with hypoalbuminemia had higher levels of CRP, leukocytes, ALT, AST, total bilirubin, ALP, GGT, LDH, creatine kinase, D-dimer, globulin, and lower levels of lymphocytes and eosinophils. Severe, older, anorexia, elevated CRP, and decreased lymphocytes were the independent predictors for decreased albumin in COVID-19 patients. In addition, decreased albumin is correlated with adverse outcomes. Nutritional support therapy to correct serum albumin may improve patient outcomes.

CONCLUSION

COVID-19 patients with hypoalbuminemia tend to have more severe clinical manifestations and more abnormal biochemical tests, which may result in poorer clinical outcomes. Nutritional support therapy may improve the clinical outcome of these patients.

Clinical Symptoms and Types of Samples Are Critical Factors for the Molecular Diagnosis of Symptomatic COVID-19 Patients: A Systematic Literature Review

BACKGROUND

Currently, a novel coronavirus found in 2019 known as SARS-CoV-2 is the etiological agent of the COVID-19 pandemic. Various parameters including clinical manifestations and molecular evaluation can affect the accuracy of diagnosis. This review aims to discuss the various clinical symptoms and molecular evaluation results in COVID-19 patients, to point out the importance of onset symptoms, type, and timing of the sampling, besides the methods that are used for detection of SARS-CoV-2.

METHODS

A systematic literature review of current articles in the Web of Science, PubMed, Scopus, and EMBASE was conducted according to the PRISMA guideline.

RESULTS

Of the 12946 patients evaluated in this investigation, 7643 were confirmed to be COVID-19 positive by molecular techniques, particularly the RT-PCR/qPCR combined technique (qRT-PCR). In most of the studies, all of the enrolled cases had 100% positive results for molecular evaluation. Among the COVID-19 patients who were identified as such by positive PCR results, most of them showed fever or cough as the primary clinical signs. Less common symptoms observed in clinically confirmed cases were hemoptysis, bloody sputum, mental disorders, and nasal congestion. The most common clinical samples for PCR-confirmed COVID-19 patients were obtained from throat, oropharyngeal, and nasopharyngeal swabs, while tears and conjunctival secretions seem to be the least common clinical samples for COVID-19 diagnosis among studies. Also, different conserved SARS-CoV-2 gene sequences could be targeted for qRT-PCR detection. The suggested molecular assay being used by most laboratories for the detection of SARS-CoV-2 is qRT-PCR.

CONCLUSION

There is a worldwide concern on the COVID-19 pandemic and a lack of well-managed global control. Hence, it is crucial to update the molecular diagnostics protocols for handling the situation. This is possible by understanding the available advances in assays for the detection of the SARS-CoV-2 infection. Good sampling procedure and using samples with enough viral loads, also considering the onset symptoms, may reduce the qRT-PCR false-negative results in symptomatic COVID-19 patients. Selection of the most efficient primer-probe for target genes and samples containing enough viral loads to search for the existence of SARS-CoV-2 helps detecting the virus on time using qRT-PCR.

Mortality Prediction Utilizing Blood Biomarkers to Predict the Severity of COVID-19 Using Machine Learning Technique

Healthcare researchers have been working on mortality prediction for COVID-19 patients with differing levels of severity. A rapid and reliable clinical evaluation of disease intensity will assist in the allocation and prioritization of mortality mitigation resources. The novelty of the work proposed in this paper is an early prediction model of high mortality risk for both COVID-19 and non-COVID-19 patients, which provides state-of-the-art performance, in an external validation cohort from a different population. Retrospective research was performed on two separate hospital datasets from two different countries for model development and validation. In the first dataset, COVID-19 and non-COVID-19 patients were admitted to the emergency department in Boston (24 March 2020 to 30 April 2020), and in the second dataset, 375 COVID-19 patients were admitted to Tongji Hospital in China (10 January 2020 to 18 February 2020). The key parameters to predict the risk of mortality for COVID-19 and non-COVID-19 patients were identified and a nomogram-based scoring technique was developed using the top-ranked five parameters. Age, Lymphocyte count, D-dimer, CRP, and Creatinine (ALDCC), information acquired at hospital admission, were identified by the logistic regression model as the primary predictors of hospital death. For the development cohort, and internal and external validation cohorts, the area under the curves (AUCs) were 0.987, 0.999, and 0.992, respectively. All the patients are categorized into three groups using ALDCC score and death probability: Low (probability < 5%), Moderate (5% < probability < 50%), and High (probability > 50%) risk groups. The prognostic model, nomogram, and ALDCC score will be able to assist in the early identification of both COVID-19 and non-COVID-19 patients with high mortality risk, helping physicians to improve patient management.

SARS-CoV-2 infection in the immunodeficient host: necessary and dispensable immune pathways

Since its outbreak in late December 2019 in Wuhan, coronavirus disease 2019 pandemic has posed a therapeutic challenge for the world population, with a plenty of clinical pictures and a broad spectrum of severity of the manifestations. In spite of initial speculations on a direct role of primary or acquired immune deficiency in determining a worse disease outcome, recent studies have provided evidence that specific immune defects may either serve as an experimentum naturae entailing this risk or may not be relevant enough to impact the host defense against the virus. Taken together, these observations may help unveil pathogenetic mechanisms of the infection and suggest new therapeutic strategies. Thus, in this review, we summarize current knowledge regarding the mechanisms of immune response against severe acute respiratory syndrome coronavirus 2 infection and clinical manifestations with a special focus on children and patients presenting with congenital or acquired immune deficiency.

The Nexus Between Telomere Length and Lymphocyte Count in Seniors Hospitalized With COVID-19

Profound T-cell lymphopenia is the hallmark of severe coronavirus disease 2019 (COVID-19). T-cell proliferation is telomere length (TL) dependent and telomeres shorten with age. Older COVID-19 patients, we hypothesize, are, therefore, at a higher risk of having TL-dependent lymphopenia. We measured TL by the novel Telomere Shortest Length Assay (TeSLA), and by Southern blotting (SB) of the terminal restriction fragments in peripheral blood mononuclear cells of 17 COVID-19 and 21 non-COVID-19 patients, aged 87 ± 8 (mean ± SD) and 87 ± 9 years, respectively. TeSLA tallies and measures single telomeres, including short telomeres undetected by SB. Such telomeres are relevant to TL-mediated biological processes, including cell viability and senescence. TeSLA yields 2 key metrics: the proportions of telomeres with different lengths (expressed in %) and their mean (TeSLA mTL), (expressed in kb). Lymphocyte count (109/L) was 0.91 ± 0.42 in COVID-19 patients and 1.50 ± 0.50 in non-COVID-19 patients (p < .001). In COVID-19 patients, but not in non-COVID-19 patients, lymphocyte count was inversely correlated with the proportion of telomeres shorter than 2 kb (p = .005) and positively correlated with TeSLA mTL (p = .03). Lymphocyte count was not significantly correlated with SB mTL in either COVID-19 or non-COVID-19 patients. We propose that compromised TL-dependent T-cell proliferative response, driven by short telomere in the TL distribution, contributes to COVID-19 lymphopenia among old adults. We infer that infection with SARS-CoV-2 uncovers the limits of the TL reserves of older persons. Clinical Trials Registration Number: NCT04325646.

The prognostic value of myocardial injury in COVID-19 patients and associated characteristics

Background

Since December 2019, coronavirus disease 2019 (COVID‐19) has emerged as an international pandemic. COVID‐19 patients with myocardial injury might need special attention. However, an understanding on this aspect remains unclear. This study aimed to illustrate clinical characteristics and the prognostic value of myocardial injury to COVID‐19 patients.

Methods

This retrospective, single‐center study finally included 304 hospitalized COVID‐19 cases confirmed by real‐time reverse‐transcriptase polymerase chain reaction from January 11 to March 25, 2020. Myocardial injury was determined by serum high‐sensitivity troponin I (Hs‐TnI). The primary endpoint was COVID‐19‐associated mortality.

Results

Of 304 COVID‐19 patients (median age, 65 years; 52.6% males), 88 patients (27.3%) died (61 patients with myocardial injury, 27 patients without myocardial injury on admission). COVID‐19 patients with myocardial injury had more comorbidities (hypertension, chronic obstructive pulmonary disease, cardiovascular disease, and cerebrovascular disease); lower lymphocyte counts, higher C‐reactive protein (CRP; median, 84.9 vs. 28.5 mg/L; p < .001), procalcitonin levels (median, 0.29 vs. 0.06 ng/ml; p < .001), inflammatory and immune response markers; more frequent need for noninvasive ventilation, invasive mechanical ventilation; and was associated with higher mortality incidence (hazard ratio [HR] = 7.02; 95% confidence interval [CI], 4.45–11.08; p < .001) than those without myocardial injury. Myocardial injury (HR = 4.55; 95% CI, 2.49–8.31; p < .001), senior age, CRP levels, and novel coronavirus pneumonia types on admission were independent predictors to mortality in COVID‐19 patients.

Conclusions

COVID‐19 patients with myocardial injury on admission is associated with more severe clinical presentation and biomarkers. Myocardial injury and higher Hs‐TnI are both strongest independent predictors to COVID‐19‐related mortality after adjusting confounding factors.

Nursing Care for People with Chronic Diseases and Pulmonary Infection by Coronavirus: An Integrative Review

Objective: To identify the implications, for Nursing, of pulmonary infections by coronavirus in people with chronic non-communicable diseases and to propose actions for care. Materials and method: A literature review, with a search for primary studies in the Biblioteca Regional Virtual de Saúde, Cumulative Index to Nursing and Allied Health Literature, National Library of Medicine and Scopus databases, from March 15th to March 30th, 2020, in Portuguese, English, and Spanish, with a quantitative and qualitative approach, in adults with chronic non-communicable diseases with respiratory infection by viruses of the coronavirus family, from 2010 to 2020. Results: A total of 11 articles were analyzed, which made it possible to identify guidelines for Nursing actions at the community and hospital levels and in critical care; among the care actions proposed for people with chronic diseases are education in health, encouragement to control the disease, immunization and lifestyle change, monitoring of suspected and confirmed cases, and use of masks in public environments. Conclusions: The study highlights the role of Nursing at all health care levels and the possibilities for learning and improving care actions through the use of evidence obtained from previous experiences.

The COVID-19 pandemic: an increased risk of rheumatoid arthritis

COVID-19 is a respiratory infection similar to viral pneumonia and is caused by SARS-CoV-2. Chloroquine and hydroxychloroquine make up the major part of the treatment regimen for the management of COVID-19 infections, which are also commonly used in treatment of patients with malaria as well as autoimmune diseases like rheumatoid arthritis (RA). In this review, we analyzed the scientific evidences pertaining to any possible association of SARS-CoV-2 infection with RA. We thus believe that people predisposed to RA carry a higher infection risk than the general population both due to the iatrogenic effects of the RA related drug therapy. Thus COVID-19 pandemic may bring a higher risk of health emergency in complex diseases such as RA.

Phytochemicals as Potential Therapeutics for SARS-CoV-2-Induced Cardiovascular Complications: Thrombosis and Platelet Perspective

After gaining entry through ACE2 aided by TMPRSS2, the SARS-CoV-2 causes serious complications of the cardiovascular system leading to myocarditis and other myocardial injuries apart from causing lung, kidney and brain dysfunctions. Here in this review, we are going to divulge the cellular and immunological mechanisms behind the cardiovascular, thrombotic and platelet impairments that are caused in COVID-19. In addition, we also propose the significance of various anti-platelet and anti-thrombotic phytochemicals in the treatment of COVID-19. The virus induces many immune-modulatory cytokines and chemokines which help in the intravascular coagulation and create a pro-thrombotic environment along with pulmonary embolism and thrombocytopenia. Different types of innate and adaptive immune cells and their granular contents regulate the pathophysiology of SARS-CoV-2 induced endothelial and platelet dysfunctions which correlate the involvement of platelets with myocardial injury and intravascular thrombi directly or indirectly. Hence, by exploiting the natural bioactive compounds from medicinal plants and inhibiting the platelet mediated thrombus formation can be beneficial for the treatment of SARS-CoV-2 infection.

An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning

COVID-19 pandemic has created an extreme pressure on the global healthcare services. Fast, reliable, and early clinical assessment of the severity of the disease can help in allocating and prioritizing resources to reduce mortality. In order to study the important blood biomarkers for predicting disease mortality, a retrospective study was conducted on a dataset made public by Yan et al. in [1] of 375 COVID-19 positive patients admitted to Tongji Hospital (China) from January 10 to February 18, 2020. Demographic and clinical characteristics and patient outcomes were investigated using machine learning tools to identify key biomarkers to predict the mortality of individual patient. A nomogram was developed for predicting the mortality risk among COVID-19 patients. Lactate dehydrogenase, neutrophils (%), lymphocyte (%), high-sensitivity C-reactive protein, and age (LNLCA)-acquired at hospital admission-were identified as key predictors of death by multi-tree XGBoost model. The area under curve (AUC) of the nomogram for the derivation and validation cohort were 0.961 and 0.991, respectively. An integrated score (LNLCA) was calculated with the corresponding death probability. COVID-19 patients were divided into three subgroups: low-, moderate-, and high-risk groups using LNLCA cutoff values of 10.4 and 12.65 with the death probability less than 5%, 5-50%, and above 50%, respectively. The prognostic model, nomogram, and LNLCA score can help in early detection of high mortality risk of COVID-19 patients, which will help doctors to improve the management of patient stratification.

Predicting Risk Score for Mechanical Ventilation in Hospitalized Adult Patients Suffering from COVID-19

Background

COVID-19 has become a pandemic since December 2019, causing millions of deaths worldwide. It has a wide spectrum of severity, ranging from mild infection to severe illness requiring mechanical ventilation. In the middle of a pandemic, when medical resources (including mechanical ventilators) are scarce, there should be a scoring system to provide the clinicians with the information needed for clinical decision-making and resource allocation.

Objectives

This study aimed to develop a scoring system based on the data obtained on admission, to predict the need for mechanical ventilation in COVID-19 patients.

Methods

This study included COVID-19 patients admitted to Sina Hospital, Tehran University of Medical Sciences from February 20 to May 29, 2020. Patients' data on admission were retrospectively recruited from Sina Hospital COVID-19 Registry (SHCo-19R). Multivariable logistic regression and receiver operating characteristic (ROC) curve analysis were performed to identify the predictive factors for mechanical ventilation.

Results

A total of 681 patients were included in the study; 74 patients (10.9%) needed mechanical ventilation during hospitalization, while 607 (89.1%) did not. Multivariate logistic analysis revealed that age (OR,1.049; 95% CI:1.008-1.091), history of diabetes mellitus (OR,3.216; 95% CI:1.134-9.120), respiratory rate (OR,1.051; 95% CI:1.005-1.100), oxygen saturation (OR,0.928; 95% CI:0.872-0.989), CRP (OR,1.013; 95% CI:1.001-1.024) and bicarbonate level (OR,0.886; 95% CI:0.790-0.995) were risk factors for mechanical ventilation during hospitalization.

Conclusions

A risk score has been developed based on the available data within the first hours of hospital admission to predict the need for mechanical ventilation. This risk score should be further validated to determine its applicability in other populations.

CAPRL Scoring System for Prediction of 30-day Mortality in 949 Patients with Coronavirus Disease 2019 in Wuhan, China: A Retrospective, Observational Study

Background

Coronavirus disease 2019 (COVID-19) is a serious and even lethal respiratory illness. The mortality of critically ill patients with COVID-19, especially short term mortality, is considerable. It is crucial and urgent to develop risk models that can predict the mortality risks of patients with COVID-19 at an early stage, which is helpful to guide clinicians in making appropriate decisions and optimizing the allocation of hospital resoureces.

Methods

In this retrospective observational study, we enrolled 949 adult patients with laboratory-confirmed COVID-19 admitted to Tongji Hospital in Wuhan between January 28 and February 12, 2020. Demographic, clinical and laboratory data were collected and analyzed. A multivariable Cox proportional hazard regression analysis was performed to calculate hazard ratios and 95% confidence interval for assessing the risk factors for 30-day mortality.

Results

The 30-day mortality was 11.8% (112 of 949 patients). Forty-nine point nine percent (474) patients had one or more comorbidities, with hypertension being the most common (359 [37.8%] patients), followed by diabetes (169 [17.8%] patients) and coronary heart disease (89 [9.4%] patients). Age above 50 years, respiratory rate above 30 beats per minute, white blood cell count of more than10 × 109/L, neutrophil count of more than 7 × 109/L, lymphocyte count of less than 0.8 × 109/L, platelet count of less than 100 × 109/L, lactate dehydrogenase of more than 400 U/L and high-sensitivity C-reactive protein of more than 50 mg/L were independent risk factors associated with 30-day mortality in patients with COVID-19. A predictive CAPRL score was proposed integrating independent risk factors. The 30-day mortality were 0% (0 of 156), 1.8% (8 of 434), 12.9% (26 of 201), 43.0% (55 of 128), and 76.7% (23 of 30) for patients with 0, 1, 2, 3, ≥4 points, respectively.

Conclusions

We designed an easy-to-use clinically predictive tool for assessing 30-day mortality risk of COVID-19. It can accurately stratify hospitalized patients with COVID-19 into relevant risk categories and could provide guidance to make further clinical decisions.

Combined clinical and imaging features better predict the critical outcomes of patients with SARS-COV-2

The purpose of this study was to investigate the predictive value of combined clinical and imaging features, compared with the clinical or radiological risk factors only. Moreover, the expected results aimed to improve the identification of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) patients who may have critical outcomes.This retrospective study included laboratory-confirmed SARS-COV-2 cases between January 18, 2020, and February 16, 2020. The patients were divided into 2 groups with noncritical illness and critical illness regarding severity status within the hospitalization. Univariable and multivariable logistic regression models were used to explore the risk factors associated with clinical and radiological outcomes in patients with SARS-COV-2. The ROC curves were performed to compare the prediction performance of different factors.A total of 180 adult patients in this study included 20 critical patients and 160 noncritical patients. In univariate logistic regression analysis, 15 risk factors were significantly associated with critical outcomes. Of importance, C-reactive protein (1.051, 95% confidence interval 1.024-1.078), D-dimer (1.911, 95% CI, 1.050-3.478), and CT score (1.29, 95% CI, 1.053-1.529) on admission were independent risk factors in multivariate analysis. The combined model achieved a better performance in disease severity prediction (P = .05).CRP, D-dimer, and CT score on admission were independent risk factors for critical illness in adults with SARS-COV-2. The combined clinical and radiological model achieved better predictive performance than clinical or radiological factors alone.

Association between thrombocytopenia and 180-day prognosis of COVID-19 patients in intensive care units: A two-center observational study

BACKGROUND

Thrombocytopenia has been proved to be associated with hospital mortality in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. However, the detailed association of thrombocytopenia with subsequent progression of organ functions and long-term prognosis in critically ill COVID-19 patients remains to be explored.

METHODS

Medical records of 167 confirmed cases of critically ill COVID-19 from February 16 to March 21, 2020 were collected in this two-center retrospective study. 180-day's outcome and clinical organ development in patients with thrombocytopenia and non-thrombocytopenia were analyzed.

FINDINGS

Among all 167 patients, the median age was 66 years and 67.07% were male. Significant differences were noticed in laboratory findings including white blood cells, blood urea, total bilirubin, lactate dehydrogenase and SOFA score between groups of thrombocytopenia and non-thrombocytopenia. Older age, lower platelet count and longer activated partial thromboplastin time at admission were determined to be risk factors of 28-day mortality, and all three, together with higher white blood cells were risk factors of 180-day mortality. Subsequent changes of six-point ordinal scale score, oxygenation index, and SOFA score in patients with thrombocytopenia showed marked worsening trends compared with patients without thrombocytopenia. Patients with thrombocytopenia had significantly higher mortality not only in 28 days, but also in 90 days and 180 days. The time-course curves in non-survival group showed a downtrend of platelet count and oxygenation index, while the curve of six-point ordinal scale kept an uptrend. Kaplan-Meier analysis indicated that patients with thrombocytopenia had much lower probability of survival (p<0.01).

INTERPRETATION

The thrombocytopenia was associated with the deterioration of respiratory function. Baseline platelet count was associated with subsequent and long-term mortality in critically ill COVID-19 patients.

Perspectives on Targeting IL-6 as a Potential Therapeutic Strategy for COVID-19

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has been a major threat to global public health. In Indonesia, the cases have rapidly increased, and the case fatality rate remains high. With COVID-19, most of the deaths have been caused by acute respiratory distress syndrome and dysregulation of the immune response. A lung biopsy from a patient with COVID-19 showed inflammatory cellular infiltration with diffuse alveolar damage. Massive pulmonary destruction has also been reported as a result of highly increased levels of proinflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), IL-1β, interferon-γ (IFN-γ), induced protein 10 (IP-10), and monocyte chemoattractant protein-1 (MCP-1). IL-6 is an inflammatory cytokine produced by various cell types, including immune cells and nonleukocytes, such as endothelial cells, fibroblasts, epithelial cells, type II pneumocytes, and certain tumor cells. Several studies have shown that IL-6 contributes to the severity and mortality of COVID-19. In this review, we would like to explore the immune response in COVID-19 and the role of IL-6 in the immunopathogenesis of COVID-19.

Upregulation of the Renin-Angiotensin System Pathways and SARS-CoV-2 Infection: The Rationale for the Administration of Zinc-Chelating Agents in COVID-19 Patients

The article describes the rationale for the administration of zinc-chelating agents in COVID-19 patients. In a previous work I have highlighted that the binding of the SARS-CoV spike proteins to the zinc-metalloprotease ACE2 has been shown to induce ACE2 shedding by activating the zinc-metalloprotease ADAM17, which ultimately leads to systemic upregulation of ACE2 activity. Moreover, based on experimental models, it was also shown the detrimental effect of the excessive systemic activity of ACE2 through its downstream pathways, which leads to "clinical" manifestations resembling COVID-19. In this regard, strong upregulation of circulating ACE2 activity was recently reported in COVID-19 patients, thus supporting the previous hypothesis that COVID-19 may derive from upregulation of ACE2 activity. Based on this, a reasonable hypothesis of using inhibitors that curb the upregulation of both ACE2 and ADAM17 zinc-metalloprotease activities and consequent positive feedback-loops (initially triggered by SARS-CoV-2 and subsequently sustained independently on viral trigger) is proposed as therapy for COVID-19. In particular, zinc-chelating agents such as citrate and ethylenediaminetetraacetic acid (EDTA) alone or in combination are expected to act in protecting from COVID-19 at different levels thanks to their both anticoagulant properties and inhibitory activity on zinc-metalloproteases. Several arguments are presented in support of this hypothesis and based on the current knowledge of both beneficial/harmful effects and cost/effectiveness, the use of chelating agents in the prevention and therapy of COVID-19 is proposed. In this regard, clinical trials (currently absent) employing citrate/EDTA in COVID-19 are urgently needed in order to shed more light on the efficacy of zinc chelators against SARS-CoV-2 infection in vivo.

T-Helper Cell Subset Response Is a Determining Factor in COVID-19 Progression

The immune response type organized against viral infection is determinant in the prognosis of some infections. This work has aimed to study Th polarization in acute COVID-19 and its possible association with the outcome through an observational prospective study. Fifty-eight COVID-19 patients were recruited in the Medicine Department of the hospital “12 de Octubre,” 55 patients remaining after losses to follow-up. Four groups were established according to maximum degree of disease progression. T-helper cell percentages and phenotypes, analyzed by flow cytometer, and serum cytokines levels, analyzed by Luminex, were evaluated when the microbiological diagnosis (acute phase) of the disease was obtained. Our study found a significant reduction of %Th1 and %Th17 cells with higher activated %Th2 cells in the COVID-19 patients compared with reference population. A higher percent of senescent Th2 cells was found in the patients who died than in those who survived. Senescent Th2 cell percentage was an independent risk factor for death (OR: 13.88) accompanied by the numbers of total lymphocytes (OR: 0.15) with an AUC of 0.879. COVID-19 patients showed a profile of pro-inflammatory serum cytokines compared to controls, with higher levels of IL-2, IL-6, IL-15, and IP-10. IL-10 and IL-13 were also elevated in patients compared to controls. Patients who did not survive presented significantly higher levels of IL-15 than those who recovered. No significant differences were observed according to disease progression groups. The study has shown that increased levels of IL-15 and a high Th2 response are associated with a fatal outcome of the disease.

Influenza infection, SARS, MERS and COVID-19: Cytokine storm - The common denominator and the lessons to be learned

The outbreak of COVID-19 reminds us that the emerging and reemerging respiratory virus infections pose a continuing threat to human life. Cytokine storm syndromes of viral origin seem to have a common pathogenesis of the imbalanced immune response with the exaggerated inflammatory reaction combined with the reduction and functional exhaustion of T cells. Immunomodulatory therapy is gaining interest in COVID-19, but this strategy has received less attention in other respiratory viral infections than it deserved. In this review we suggest that based on the similarities of the immune dysfunction in the severe cases of different respiratory viral infections, some lessons from the immunomodulatory therapy of COVID-19 (particularly regarding the choice of an immunomodulatory drug, the selection of patients and optimal time window for this kind of therapy) could be applied for some cases of severe influenza infection and probably for some future outbreaks of novel severe respiratory viral infections.

Identification of risk factors for in-hospital death of COVID - 19 pneumonia -- lessions from the early outbreak

Background

To examine the clinical characteristics and identify independent risk factors for in-hospital mortality of 2019 novel coronavirus (COVID-19) pneumonia.

Methods

A total of 156 patients diagnosed with COVID-19 pneumonia at the Central Hospital of Wuhan from January 29, 2020, to March 20, 2020, and 20 healthy individuals were enrolled in this single-centered retrospective study. The epidemiological parameters, clinical presentations, underlying diseases, laboratory test results, and disease outcomes were collected and analyzed.

Results

The median age of all enrolled patients was 66 years. At least one underlying disease was identified in 101 COVID-19 patients, with hypertension being the most common one, followed by cardiovascular disease and diabetes. The most common symptoms identified upon admission were fever, cough, dyspnea, and fatigue. Compared to survival cases, patients who died during hospitalization had higher plasma levels of D-dimer, creatinine, creatine kinase, lactate dehydrogenase, lactate, and lower percentage of lymphocytes (LYM [%]), platelet count and albumin levels. Most enrolled patients received antibiotics and anti-viral treatment. In addition, 60 patients received corticosteroids, and 51 received intravenous immunoglobulin infusion. Forty-four patients received noninvasive ventilation and 19 received invasive ventilation. Respiratory failure was the most frequently observed complication (106 [67.9%]), followed by sepsis (103 [66.0%]), acute respiratory distress syndrome (ARDS) (67 [42.9%]), and septic shock (50 [32.1%]).

Multivariable regression suggested that advanced age (OR [odds ratio] = 1.098, 95% CI [confidence interval]: 1.006–1.199, P = 0.037), shorter duration from onset to admission (OR = 0.853, 95% CI: 0.750–0.969, P = 0.015) and elevated lactate level upon admission (OR = 2.689, 95% CI: 1.044–6.926, P = 0.040) were independent risk factors for in-hospital mortality for COVID-19 infection. Meanwhile, increased LYM (%) at admission (OR = 0.787, 95% CI: 0.686–0.903, P = 0.001) indicated a better prognosis.

Conclusions

In this study, we discovered that age, duration from onset to admission, LYM (%), and lactate level upon admission were independent factors that affecting the in-hospital mortality rate.

Peripheral Inflammatory Cytokines and Lymphocyte Subset Features of Deceased COVID-19 Patients

OBJECTIVE

To compare the difference of inflammatory cytokines and lymphocyte subsets between deceased patients and survivors with COVID-19.

METHODS

This retrospective study included 254 confirmed patients from 10 January to 11 March, 2020, at Tongji Hospital of Wuhan, China. Laboratory and immunologic features were collected and analyzed, and the main outcomes focused on inflammatory cytokines and lymphocyte subsets.

RESULTS

A trend of markedly higher levels of inflammatory cytokines as well as lower lymphocyte subset levels in deceased patients was observed compared with survivors. ROC curve analyses indicated that inflammatory cytokines and the decrease levels of T cell, Th (helper T cells) cell, Ts (suppressor T cells) cell, B cell, and NK cell along with Th/Ts ratio increase could be used to predict the death of COVID-19. Multivariate analyses showed that higher levels of IL-6, IL-8, and IL-10 remained significantly correlated with shorter survival time and that the amount of Ts cells was negatively associated with the possibility of death in COVID-19 patients. In conclusion, SARS-CoV-2 would cause lymphopenia and result in decreased lymphocyte subset cells, particularly in Ts cell counts, which further induces hyperinflammatory response and cytokine storm. IL-6, IL-8, IL-10, and Ts cell might be independent predictors for the poor outcome of COVID-19.

Respiratory failure among patients with COVID-19 in Jiangsu province, China: a multicentre retrospective cohort study

This study was a retrospective multicentre cohort study of patients with coronavirus disease 2019 (COVID-19) diagnosed at 24 hospitals in Jiangsu province, China as of 15 March 2020. The primary outcome was the occurrence of acute respiratory failure during hospital stay. Of 625 patients, 56 (9%) had respiratory failure. Some selected demographic, epidemiologic, clinical and laboratory features as well as radiologic features at admission and treatment during hospitalisation were significantly different in patients with and without respiratory failure. The multivariate logistic analysis indicated that age (in years) (odds ratio [OR], 1.07; 95% confidence interval [CI]: 1.03–1.10; P = 0.0002), respiratory rate (breaths/minute) (OR, 1.23; 95% CI: 1.08–1.40; P = 0.0020), lymphocyte count (10⁹/l) (OR, 0.18; 95% CI: 0.05–0.69; P = 0.0157) and pulmonary opacity score (per 5%) (OR, 1.38; 95% CI: 1.19–1.61; P < 0.0001) at admission were associated with the occurrence of respiratory failure. Older age, increased respiratory rate, decreased lymphocyte count and greater pulmonary opacity score at admission were independent risk factors of respiratory failure in patients with COVID-19. Patients having these risk factors need to be intensively managed during hospitalisation.

Dynamic changes in lymphocyte subsets and parallel cytokine levels in patients with severe and critical COVID-19

Background

The lack of knowledge regarding the pathogenesis and host immune response during SARS-CoV-2 infection has limited the development of effective treatments. Thus, we longitudinally investigated the dynamic changes in peripheral blood lymphocyte subsets and parallel changes in cytokine levels in COVID-19 patients with different disease severities to further address disease pathogenesis.

Methods

A total of 67 patients (10 moderate, 38 severe and 19 critical cases) with COVID-19 admitted to a tertiary care hospital in Wuhan from February 8th to April 6th, 2020 were retrospectively studied. Dynamic data of lymphocyte subsets and inflammatory cytokines were collected.

Results

On admission, compared with moderate cases, severe and critical cases showed significantly decreased levels of total lymphocytes, T lymphocytes, CD4⁺ T cells, CD8⁺ T cells, B cells and NK cells. IL-6 and IL-10 were significantly higher in the critical group. During the following hospitalization period, most of the lymphocyte subsets in the critical group began to recover to levels comparable to those in the severe group from the fourth week after illness onset, except for NK cells, which recovered after the sixth week. A sustained decrease in the lymphocyte subsets and an increase in IL-6 and IL-10 were observed in the nonsurvivors until death. There was a strong negative correlation between IL-6 and IL-10 and total lymphocytes, T lymphocytes, CD4⁺ T cells, CD8⁺ T cells and NK cells.

Conclusions

A sustained decrease in lymphocyte subsets, especially CD4⁺ T cells and NK cells, interacting with proinflammatory cytokine storms was associated with severe disease and poor prognosis in COVID-19.

Clinical Characteristics and Diagnostic Challenges of COVID-19: An Update From the Global Perspective

Clinical characteristics are essential for the correct diagnosis of diseases. The current review aimed to summarize the global clinical characteristics of the COVID-19 patients systematically and identify their diagnostic challenges to help the medical practitioners properly diagnose and for better management of COVID-19 patients. We conducted a systematic search in PubMed, Web of Science, Scopus, Science Direct, and Google Scholar databases for original articles containing clinical information of COVID-19 published up to 7th May 2020. Two researchers independently searched the databases to extract eligible articles. A total of 34 studies from 8 different countries with 10889 case-patients were included for clinical characteristics. The most common clinical symptoms were cough 59.6, fever 46.9, fatigue 27.8, and dyspnea 20.23%. The prominent laboratory findings were lymphocytopenia 55.9, elevated levels of CRP 61.9, aspartate aminotransferase 53.3, LDH 40.8, ESR 72.99, serum ferritin 63, IL-6 52, and prothrombin time 35.47%, and decreased levels of platelets 17.26, eosinophils 59.0, hemoglobin 29, and albumin 38.4%. CT scan of the chest showed an abnormality in 93.50% cases with bilateral lungs 71.1%, ground-glass opacity 48%, lesion in lungs 78.3%, and enlargement of lymph node 50.7%. Common comorbidities were hypertension, diabetes, obesity, and cardiovascular diseases. The estimated median incubation period was 5.36 days, and the overall case fatality rate was 16.9% (Global case fatality outside China was 22.24%: USA 21.24%, Italy 25.61%, and others 0%; whereas the case fatality inside the Hubei Province of China was found to be 11.71%). Global features on the clinical characteristics of COVID-19 obtained from laboratory tests and CT scan results will provide useful information to the physicians to diagnose the disease and for better management of the patients as well as to address the diagnostic challenges to control the infection.

Low arterial oxygen partial pressure induces pulmonary thrombocytopenia in patients and a mouse model

BACKGROUND

Recent basic studies demonstrate that the lung is a primary organ of platelet biogenesis. However, whether the pathophysiological state of the lung affect the platelets is little known. We aim to investigate the incidence of thrombocytopenia in patients with pulmonary infection (PIN) and risk factors associated with pulmonary thrombocytopenia.

METHODS

In total, 11,941 patients with pulmonary infection (PIN) were enrolled, and patients with other three infectious diseases were collected as controls. The incidence of thrombocytopenia was compared, and the risk factors associated with thrombocytopenia in PIN patients were investigated by multivariate analysis. To explore the mechanism of thrombocytopenia, hypoxic model was constructed. Blood platelet counts from the angular vein (PLTs), left ventricle (PLT_post) and right ventricle (PLT_pre) were determined. Megakaryocytes identified by anti-CD41 antibody were detected through flow cytometry and immunofluorescence.

RESULTS

The incidence of thrombocytopenia in PIN was higher than that in other three infectious diseases (9.8% vs. 6.4% ~ 5.0%, P < 0.001). Low arterial oxygen partial pressure (PaO₂) was an important risk factor for thrombocytopenia (OR = 0.88; P < 0.001). In a hypoxic mouse model, PLTs decreased (518.38 ± 127.92 vs 840.75 ± 77.30, P < 0.05), which showed that low PaO₂ induced thrombocytopenia. The difference between the PLT_post and PLT_pre (∆PLT_post-pre), representing the production of platelets in the lungs, was significantly attenuated in hypoxic mice when compared with normoxic mice (F = 25.47, P < 0.05). Additionally, proportions of CD41-positive megakaryocytes in the lungs, marrow, spleen all decreased in hypoxic mice.

CONCLUSION

There is a high incidence for thrombocytopenia in PIN patients. Low PaO₂-induced thrombocytopenia is associated with impaired generation of platelet in the lungs.

Ongoing outbreak of human adenovirus-associated acute respiratory illness in the Republic of Korea military, 2013 to 2018

BACKGROUND/AIMS

Human adenovirus type 55 (HAdV-55), an emerging epidemic strain, has caused several large outbreaks in the Korean military since 2014, and HAdV-associated acute respiratory illness (HAdV-ARI) has been continuously reported thereafter.

METHODS

To evaluate the epidemiologic characteristics of HAdV-ARI in the Korean military, we analyzed respiratory virus polymerase chain reaction (RV-PCR) results, pneumonia surveillance results, and severe HAdV cases from all 14 Korean military hospitals from January 2013 to May 2018 and compared these data with nationwide RV surveillance data for the civilian population.

RESULTS

A total of 14,630 RV-PCRs was performed at military hospitals. HAdV (45.4%) was the most frequently detected RV, followed by human rhinovirus (12.3%) and influenza virus (6.3%). The percentage of the military positive for HAdV was significantly greater than the percentage of civilians positive for HAdV throughout the study period, with a large outbreak occurring during the winter to spring of 2014 to 2015. The outbreak continued until the end of the study, and non-seasonal detections increased over time. The reported number of pneumonia patients also increased during the outbreak. Case fatality rate was 0.075% overall but 15.6% in patients with respiratory failure. The proportion of severe patients did not change significantly during the study period.

CONCLUSION

A large HAdV outbreak is currently ongoing in the Korean military, with a trend away from seasonality, and HAdV-55 is likely the predominant strain. Persistent efforts to control the outbreak, HAdV type-specific surveillance, and vaccine development are required.

Epidemiology, virology, and history of Covid-19 infection

In this chapter, we will discuss the infection history and epidemiology, the viral structure of COVID 19 or SARS-CoV-2, mode of transmission, virulence, and pathogenesis of disease, and we also discuss how it was started and its relation to other coronaviruses. Then we will mention the relation to pregnancy, how it can affect pregnant female, sequelae on pregnancy course and labor, and effect on fetus and neonates.

Prognostic value of inflammatory biomarkers for predicting the extent of lung involvement and final clinical outcome in patients with COVID-19

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Development and Validation of an Early Scoring System for Prediction of Disease Severity in COVID-19 Using Complete Blood Count Parameters

The coronavirus disease 2019 (COVID-19) after outbreaking in Wuhan increasingly spread throughout the world. Fast, reliable, and easily accessible clinical assessment of the severity of the disease can help in allocating and prioritizing resources to reduce mortality. The objective of the study was to develop and validate an early scoring tool to stratify the risk of death using readily available complete blood count (CBC) biomarkers. A retrospective study was conducted on twenty-three CBC blood biomarkers for predicting disease mortality for 375 COVID-19 patients admitted to Tongji Hospital, China from January 10 to February 18, 2020. Machine learning based key biomarkers among the CBC parameters as the mortality predictors were identified. A multivariate logistic regression-based nomogram and a scoring system was developed to categorize the patients in three risk groups (low, moderate, and high) for predicting the mortality risk among COVID-19 patients. Lymphocyte count, neutrophils count, age, white blood cell count, monocytes (%), platelet count, red blood cell distribution width parameters collected at hospital admission were selected as important biomarkers for death prediction using random forest feature selection technique. A CBC score was devised for calculating the death probability of the patients and was used to categorize the patients into three sub-risk groups: low (<=5%), moderate (>5% and <=50%), and high (>50%), respectively. The area under the curve (AUC) of the model for the development and internal validation cohort were 0.961 and 0.88, respectively. The proposed model was further validated with an external cohort of 103 patients of Dhaka Medical College, Bangladesh, which exhibits in an AUC of 0.963. The proposed CBC parameter-based prognostic model and the associated web-application, can help the medical doctors to improve the management by early prediction of mortality risk of the COVID-19 patients in the low-resource countries.