The association between severe COVID-19 and low platelet count: evidence from 31 observational studies involving 7613 participants

Inflammation, Sepsis, and the Coagulation System

Sepsis has been a major health problem for centuries and it is still the leading cause of hospital deaths. Several studies in the past decades have identified numerous biochemical abnormalities in severe cases, and many of these studies provide evidence of the perturbation of the hemostatic system. This can result in complications, such as disseminated intravascular coagulation that can lead to multiorgan failure. Nevertheless, large clinical studies have demonstrated that the simple approach of inhibiting the coagulation processes by any means fails to provide significant improvement in the survival of septic patients. A cause of this failure could be the fact that in sepsis the major clinical problems result not primarily from the presence of the infective agent or enhanced coagulation but from the complex dysregulated systemic host response to pathogens. If this overt reaction is not fully deciphered, appropriate interference is highly unlikely and any improvement by conventional therapeutic interventions would be limited. Cellular activation in sepsis can be targeted by novel approaches like inhibition of the heterotypic cellular interactions of blood cells by targeting surface receptors or posttranscriptional control of the hemostatic system by noncoding ribonucleic acid (RNA) molecules. Stable RNA molecules can affect the expression of several proteins. Thus, it can be anticipated that modulation of microRNA production would result in a multitude of effects that may be beneficial in septic cases. Here, we highlight some of the recent diagnostic possibilities and potential novel routes of the dysregulated host response.

Causal Effects of COVID-19 on the Risk of Thrombosis: A Two-Sample Mendel Randomization Study

BACKGROUND

 Coronavirus disease 2019 (COVID-19) and thrombosis are linked, but the biomolecular mechanism is unclear. We aimed to investigate the causal relationship between COVID-19 and thrombotic biomarkers.

METHODS

 We used two-sample Mendelian randomization (MR) to assess the effect of COVID-19 on 20 thrombotic biomarkers. We estimated causality using inverse variance weighting with multiplicative random effect, and performed sensitivity analysis using weighted median, MR-Egger regression and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) methods. All the results were examined by false discovery rate (FDR) with the Benjamin and Hochberg method for this correction to minimize false positives. We used R language for the analysis.

RESULTS

 All COVID-19 classes showed lower levels of tissue factor pathway inhibitor (TFPI) and interleukin-1 receptor type 1 (IL-1R1). COVID-19 significantly reduced TFPI (odds ratio [OR] = 0.639, 95% confidence interval [CI]: 0.435-0.938) and IL-1R1 (OR = 0.603, 95% CI = 0.417-0.872), nearly doubling the odds. We also found that COVID-19 lowered multiple coagulation factor deficiency protein 2 and increased C-C motif chemokine 3. Hospitalized COVID-19 cases had less plasminogen activator, tissue type (tPA) and P-selectin glycoprotein ligand 1 (PSGL-1), while severe cases had higher mean platelet volume (MPV) and lower platelet count. These changes in TFPI, tPA, IL-1R1, MPV, and platelet count suggested a higher risk of thrombosis. Decreased PSGL-1 indicated a lower risk of thrombosis.

CONCLUSION

 TFPI, IL-1R, and seven other indicators provide causal clues of the pathogenesis of COVID-19 and thrombosis. This study demonstrated that COVID-19 causally influences thrombosis at the biomolecular level.

Mapping the vast landscape of multisystem complications of COVID-19: Bibliometric analysis

Background

With the rapid global spread of COVID-19, it has become evident that the virus can lead to multisystem complications, leading to a significant increase in related publications. Bibliometrics serves as a valuable tool for identifying highly cited literature and research hotspots within specific areas.

Objective

The aim of this study is to identify current research hotspots and future trends in COVID-19 complications.

Methods

The dataset was obtained from the Web of Science Core Collection, covering COVID-19 complications from December 8, 2019, to October 31, 2022. Various aspects, including publication general information, authors, journals, co-cited authors, co-cited references, research hotspots, and future trends, were subjected to analysis. Visual analysis was conducted using VOSviewer, The Online Analysis Platform of Literature Metrology, and Charticulator.

Results

There were 4597 articles in the study. The top three countries with the most published articles are the USA (n = 1350, 29.4 %), China (n = 765, 16.6 %), and Italy (n = 623, 13.6 %). USA and China have the closest collaborative relationship. The institute with the largest number of publications is Huazhong University of Science and Technology, followed by Harvard Medical School. Nevertheless, half of the top 10 institutes belong to the USA. "Rezaei, Nima" published 13 articles and ranked first, followed by "Yaghi, Shadi" with 12 articles and "Frontera, Jennifer" with 12 articles. The journal with the largest number of publications is "Journal of Clinical Medicine". The top 3 co-cited authors are "Zhou, Fei", "Guan, Wei-Jie", "Huang, Chaolin". The top 3 co-cited references addressed COVID-19's clinical features in China and noticed that COVID-19 patients had a wide range of complications. We also list four research hotspots.

Conclusions

This study conducted a bibliometric visual analysis of the literature on COVID-19 complications and summarized the current research hotspots. This study may provide valuable insights into the complications of COVID-19.

Causal relationship between physical activity and platelet traits: a Mendelian randomization study

Introduction: The purpose of this study was to discuss the causal relationship between physical activity and platelet traits. Methods: A dataset from a large-scale European physical activity and platelet traits was collected by using Mendelian randomization of the study. For the analysis, the inverse variance weighting method, weighted median and MR-Egger were used to estimate causal effects. The sensitivity analyses were also performed using Cochran's Q test, funnel plots and Leave-one-out analysis. Results: Light DIY, other exercises, strenuous sports, walking for pleasure were significantly associated with a decrease in platelet crit. But none of the heavy /light DIY was associated with increase in platelet crit. Other exercises and strenuous sports were associated with decrease in platelet count. Conclusion: Some types of physical activity have a causal relationship with platelet crit and platelet count. However, the types of physical activity we studied have not supported a causal relationship with mean platelet volume and platelet distribution width.

Ferroptosis in viral infection: a potential therapeutic target

Ferroptosis, known as a type of programmed cell death that is iron dependent, is characterized by intracellular iron accumulation, glutathione depletion, glutathione peroxidase inactivation and lipid peroxidation. More and more research in recent years has demonstrated the tight connection between viral infections and ferroptosis. This article reviews the potential role and mechanism of ferroptosis in viral infection, and these findings will help in the prevention and treatment of the virus.

Complex changes in serum protein levels in COVID-19 convalescents

The COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2, has affected millions of people worldwide. Much research has been dedicated to our understanding of COVID-19 disease heterogeneity and severity, but less is known about recovery associated changes. To address this gap in knowledge, we quantified the proteome from serum samples from 29 COVID-19 convalescents and 29 age-, race-, and sex-matched healthy controls. Samples were acquired within the first months of the pandemic. Many proteins from pathways known to change during acute COVID-19 illness, such as from the complement cascade, coagulation system, inflammation and adaptive immune system, had returned to levels seen in healthy controls. In comparison, we identified 22 and 15 proteins with significantly elevated and lowered levels, respectively, amongst COVID-19 convalescents compared to healthy controls. Some of the changes were similar to those observed for the acute phase of the disease, i.e. elevated levels of proteins from hemolysis, the adaptive immune systems, and inflammation. In contrast, some alterations opposed those in the acute phase, e.g. elevated levels of CETP and APOA1 which function in lipid/cholesterol metabolism, and decreased levels of proteins from the complement cascade (e.g. C1R, C1S, and VWF), the coagulation system (e.g. THBS1 and VWF), and the regulation of the actin cytoskeleton (e.g. PFN1 and CFL1) amongst COVID-19 convalescents. We speculate that some of these shifts might originate from a transient decrease in platelet counts upon recovery from the disease. Finally, we observed race-specific changes, e.g. with respect to immunoglobulins and proteins related to cholesterol metabolism.

The development of proximity labeling technology and its applications in mammals, plants, and microorganisms

Protein‒protein, protein‒RNA, and protein‒DNA interaction networks form the basis of cellular regulation and signal transduction, making it crucial to explore these interaction networks to understand complex biological processes. Traditional methods such as affinity purification and yeast two-hybrid assays have been shown to have limitations, as they can only isolate high-affinity molecular interactions under nonphysiological conditions or in vitro. Moreover, these methods have shortcomings for organelle isolation and protein subcellular localization. To address these issues, proximity labeling techniques have been developed. This technology not only overcomes the limitations of traditional methods but also offers unique advantages in studying protein spatial characteristics and molecular interactions within living cells. Currently, this technique not only is indispensable in research on mammalian nucleoprotein interactions but also provides a reliable approach for studying nonmammalian cells, such as plants, parasites and viruses. Given these advantages, this article provides a detailed introduction to the principles of proximity labeling techniques and the development of labeling enzymes. The focus is on summarizing the recent applications of TurboID and miniTurbo in mammals, plants, and microorganisms. Video Abstract.

Crosstalk between Platelets and SARS-CoV-2: Implications in Thrombo-Inflammatory Complications in COVID-19

The SARS-CoV-2 virus, causing the devastating COVID-19 pandemic, has been reported to affect platelets and cause increased thrombotic events, hinting at the possible bidirectional interactions between platelets and the virus. In this review, we discuss the potential mechanisms underlying the increased thrombotic events as well as altered platelet count and activity in COVID-19. Inspired by existing knowledge on platelet-pathogen interactions, we propose several potential antiviral strategies that platelets might undertake to combat SARS-CoV-2, including their abilities to internalize the virus, release bioactive molecules to interfere with viral infection, and modulate the functions of immune cells. Moreover, we discuss current and potential platelet-targeted therapeutic strategies in controlling COVID-19, including antiplatelet drugs, anticoagulants, and inflammation-targeting treatments. These strategies have shown promise in clinical settings to alleviate the severity of thrombo-inflammatory complications and reduce the mortality rate among COVID-19 patients. In conclusion, an in-depth understanding of platelet-SARS-CoV-2 interactions may uncover novel mechanisms underlying severe COVID-19 complications and could provide new therapeutic avenues for managing this disease.

Preliminary Study of sCD14 and sCD163 as Predictors of Disease Severity and ICU Admission in COVID-19: Relation to Hematological Parameters, Blood Morphological Changes and Inflammatory Biomarkers

Background and Objectives

Research supports the role of monocyte/macrophage activation in COVID-19 immunopathology. This study aimed to evaluate sCD14 and sCD163 - the monocyte activation markers - and to investigate their relation to hematological parameters and blood morphology in COVID-19 infection.

Methods

This is a case-control study that included 70 COVID-19 patients. Patients were subdivided into two groups: 23 severely diseased ICU-admitted patients and another group of 47 non-ICU-admitted patients. sCD163 and sCD14 levels were determined using ELISA.

Results

sCD163 and sCD14 showed significantly higher levels in sera of patients compared to the control group, with significantly higher levels of sCD163 in ICU-admitted patients than non-ICU admitted patients. Receiver operating characteristic curve analysis demonstrated the usefulness of sCD163 with a cut-off value of 734 ng/mL as a potential marker to discriminate between ICU and non-ICU admitted COVID-19 patients (sensitivity of 81.16%; specificity of 96.67% and positive predictive value of 98% with area under the curve of 0.930). sCD163 levels showed a positive correlation with total white blood cells, absolute neutrophilic count, Neutrophil/Lymphocyte ratio, and a negative correlation with platelet count. sCD14 levels positively correlated with D-dimer values associated with a shift to the left and neutrophilic toxic granulations in blood morphology.

Conclusion

High sCD163 and sCD14 levels, hematological parameters, and blood morphology reflect monocyte activation in COVID-19 infection. sCD163 is a potential marker of disease severity. These findings support further study of therapeutics targeting macrophage activity in COVID-19 patients with high sCD163 levels.

Temporal evolution of laboratory characteristics in patients critically ill with COVID‑19 admitted to the intensive care unit (Review)

In the context of coronavirus disease 2019 (COVID-19), laboratory medicine has played a crucial role in both diagnosis and severity assessment. Although the importance of baseline laboratory findings has been extensively reported, data regarding their evolution over the clinical course are limited. The aim of the present narrative review was to provide the dynamic changes of the routine laboratory variables reported in patients with severe COVID-19 over the course of their critical illness. A search was made of the literature for articles providing data on the time-course of routine laboratory tests in patients with severe COVID-19 during their stay in the intensive care unit (ICU). White blood cell, neutrophil and lymphocyte counts, neutrophil to lymphocyte ratio, platelet counts, as well as D-dimer, fibrinogen, C-reactive protein, lactate dehydrogenase and serum albumin levels were selected as disease characteristics and routine laboratory parameters. A total of 25 research articles reporting dynamic trends in the aforementioned laboratory parameters over the clinical course of severe COVID-19 were identified. During the follow-up period provided by each study, the majority of the laboratory values remained persistently abnormal in both survivors and non-survivors. Furthermore, in the majority of studies, the temporal trends of laboratory values distinctly differentiated patients between survivors and non-survivors. In conclusion, there are distinct temporal trends in selected routine laboratory parameters between survivors and non-survivors with severe COVID-19 admitted to the ICU, indicating their importance in the prognosis of clinical outcome.

The predictive role of biochemical markers on outcomes of severe COVID-19 patients admitted to intensive care unit

Background

The pandemic of severe acute respiratory syndrome by coronavirus 2 (SARS-CoV-2) is a multi-system disease caused by a diffuse systemic process involving a complex interaction of the inflammatory, immunological and coagulative cascades. This study aims to identify the most effective biomarkers to predict poor outcome in intensive care unit (ICU) patients with severe COVID-19 disease.

Methods

A single-centre retrospective observational study enrolled 69 deceased and 20 recovered patients treated in the ICU of the General Hospital Gradiska in the period from March 1, 2021. until April 1, 2022. We evaluated the leukocytes (WBC), lymphocytes (LYM), neutrophils (NEU), platelets (PLT), haemoglobin, neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). In addition, we evaluated the IL-6, ferritin, CRP, D-dimer, magnesium, bilirubin and lactate dehydrogenase.

Clinical characteristics and outcomes of COVID-19 patients with varying renal functions statuses during the Omicron pandemic in Shanghai

OBJECTIVE

This study aims to provide an academic summary of the clinical characteristics, outcomes and risk factors associated with prolonged hospital stays among the patients with varying renal function statuses during the Omicron pandemic in Shanghai.

METHODS

Clinical data was collected from COVID-19 patients admitted to Shanghai Jiaotong University School of Medicine Ruijin Hospital Northern District. Based on their baseline eGFR, the patients were divided into three groups: Group A (eGFR > = 90ml/min/1.73m2, n = 384), Group B (15ml/min/1.73m2 < = eGFR < 90ml/min/1.73m2, n = 220), and Group C (Hemodialysis-dependent patient, n = 92). Clinical characteristics and laboratory data were compared among the three groups. The cumulative hazards of ICU admission were compared using the Kaplan-Meier method. Univariate and multivariate linear regression analyses were conducted to identify the factors influencing the duration of positive nucleic acid test.

RESULTS

Between March 25, 2022, and May 31, 2022, a total of 696 COVID-19 patients were included in the study. Among the dialysis patients, 92% (85) of dialysis patients had not received any COVID-19 vaccination, and 14.1%(13) of hemodialysis (HD) patients eventually progressed to severe or critical cases. A total of 13 (2.15%) patients were admitted to the ICU, with 8 (61.5%) were HD patients. The duration of nucleic acid positivity showed a negative correlation with eGFR (B: -0.048, 95%CI: -0.059~-0.037, P = 0.000), platelet counts (B: -0.011, 95%CI: -0.017~-0.005, P = 0.001) or lymphocyte counts (B: -0.658, 95%CI: -1.229~-0.086, P = 0.024).

CONCLUSIONS

The majority of Omicron patients have a favorable prognosis, while HD patients experience relatively poorer outcomes and higher rates of ICU admission. Decreased eGFR and low lymphocyte/platelet counts are the important risk factors associated with prolonged Omicron infection.

Inflammatory Response and Activation of Coagulation after COVID-19 Infection

SARS-CoV-2 (COVID-19) infection is responsible for causing a disease with a wide spectrum of clinical presentations. Predisposition to thromboembolic disease due to excessive inflammation is also attributed to the disease. The objective of this study was to characterize the clinical and laboratory aspects of hospitalized patients, in addition to studying the pattern of serum cytokines, and associate them with the occurrence of thromboembolic events.

METHODOLOGY

A retrospective cohort study with 97 COVID-19 patients hospitalized from April to August 2020 in the Triângulo Mineiro macro-region was carried out. A review of medical records was conducted to evaluate the clinical and laboratory aspects and the frequency of thrombosis, as well as the measurement of cytokines, in the groups that presented or did not present a thrombotic event.

RESULTS

There were seven confirmed cases of thrombotic occurrence in the cohort. A reduction in the time of prothrombin activity was observed in the group with thrombosis. Further, 27.8% of all patients had thrombocytopenia. In the group that had thrombotic events, the levels of IL1b, IL-10, and IL2 were higher (p < 0.05).

CONCLUSIONS

In the studied sample, there was an increase in the inflammatory response in patients with thrombotic events, confirmed by the increase in cytokines. Furthermore, in this cohort, a link was observed between the IL-10 percentage and an increased chance of a thrombotic event.

Platelet‑related parameters as potential biomarkers for the prognosis of sepsis

Early diagnosis and accurate prognosis are key for reducing the fatality rate and medical expenses associated with sepsis. Platelets are involved in the delayed tissue injury that occurs during sepsis. Therefore, the aim of the present study was to investigate the usefulness of platelets and associated parameters as prognostic markers of sepsis. The present study collected patient samples based on The Third International Consensus Definitions for Sepsis and Septic Shock criteria. Platelet-associated parameters were detected by flow cytometry and their correlation with clinical scores and prognoses was analyzed. Considering the association between endothelial cells and platelet activation, levels of plasma tumor necrosis factor-like weak inducer of apoptosis (TWEAK) and angiopoietin-2 (Ang-2) were analyzed by ELISA. The results showed significant differences in platelet P-selectin expression and phosphatidylserine exposure, mitochondrial membrane potential (Mmp)-Index values and plasma levels of TWEAK and Ang-2 between patients and healthy controls (P<0.05). Except for P-selectin and TWEAK levels, all parameters were correlated with clinical scores (acute physiology and chronic health evaluation II and sequential/sepsis-related organ failure assessment). Additionally, platelet Mmp-Index between admission and the end of therapy was only different in non-survivors (P<0.001) and platelet phosphatidylserine exposure was significantly lower in survivors (P=0.006). Therefore, of the parameters tested, the dynamic monitoring of phosphatidylserine exposure, platelet Mmp-Index values and plasma Ang-2 levels had the most potential for the assessment of disease severity and clinical outcomes.

Parameters to Predict the Outcome of Severe and Critical COVID-19 Patients when Admitted to the Hospital

Manifestations of COVID-19 are diverse and range from asymptomatic to severe, critical illness and death. Cases requiring hospital care (in severe and critical illnesses) are associated with comorbidities and hyperactivation of the immune system. Therefore, in this exploratory observational study, we analyzed which parameters are associated with mortality. We evaluated: demographic characteristics (age, sex and comorbidities), laboratory data (albumin, leukocytes, lymphocytes, platelets, ferritin), days of hospital stay, interleukins (IL-2, IL-6, IL-7, IL-10, IL-17) and sP-selectin in 40 Mexican patients admitted to medical emergencies with a confirmed diagnosis of COVID-19, a complete clinical record, and who signed the informed consent. Twenty severe (they required intermediate care with non-invasive ventilation) and twenty critically ill patients (they required mechanical ventilation) were classified, and these were subsequently compared with healthy and recovered subjects. A significant difference was found between the hospitalized groups in the parameters of age, ferritin, days of hospital stay and death with p values = 0.0145, p = 0.0441, p = 0.0001 and p = 0.0001, respectively. In the determination of cytokines and P-selectin, a significant difference was found between the following groups: recovered patients and healthy volunteers compared with hospitalized patients in severe and critical condition. Importantly, IL-7 remained elevated one year later in recovered patients. Taken together, these values determined at the time of hospital admission could be useful to monitor patients closely and evaluate in-hospital progress, hospital discharge, and out-of-hospital progress.

Characteristics, outcomes, and risk factors for in-hospital mortality of COVID-19 patients: A retrospective study in Thailand

Introduction

Data on the characteristics and outcomes of patients hospitalized for Coronavirus Disease 2019 (COVID-19) in Thailand are limited.

Objective

To determine characteristics and outcomes and identify risk factors for hospital mortality for hospitalized patients with COVID-19.

Methods

We retrospectively reviewed the medical records of patients who had COVID-19 infection and were admitted to the cohort ward or ICUs at Siriraj Hospital between January 2020 and December 2021.

Results

Of the 2,430 patients included in this study, 229 (9.4%) died; the mean age was 54 years, 40% were men, 81% had at least one comorbidity, and 13% required intensive care unit (ICU). Favipiravir (86%) was the main antiviral treatment. Corticosteroids and rescue anti-inflammatory therapy were used in 74 and 6%, respectively. Admission to the ICU was the only factor associated with reduced mortality [odds ratio (OR) 0.01, 95% confidence interval (CI) 0.01-0.05, P < 0.001], whereas older age (OR 14.3, 95%CI 5.76-35.54, P < 0.001), high flow nasal cannula (HFNC; OR 9.2, 95% CI 3.9-21.6, P < 0.001), mechanical ventilation (OR 269.39, 95%CI 3.6-2173.63, P < 0.001), septic shock (OR 7.79, 95%CI, 2.01-30.18, P = 0.003), and hydrocortisone treatment (OR 27.01, 95%CI 5.29-138.31, P < 0.001) were factors associated with in-hospital mortality.

Conclusion

The overall mortality of hospitalized patients with COVID-19 was 9%. The only factor associated with reduced mortality was admission to the ICU. Therefore, appropriate selection of patients for admission to the ICU, strategies to limit disease progression and prevent intubation, and early detection and prompt treatment of nosocomial infection can improve survival in these patients.

Hematologic Abnormalities After COVID-19 Infection: A Case of Coombs-Negative Hemolytic Anemia and Thrombocytopenia

The occurrence of hemolytic anemia in patients with active SARS-CoV-2 infection has been documented in medical literature. While relatively uncommon, there have been instances where this condition presents as a Coombs-negative hemolytic anemia. In this research study, we report a distinctive case of Coombs-negative hemolytic anemia and thrombocytopenia in a patient with a known history of COVID-19 infection. The patient demonstrated a favorable response to treatment involving the administration of steroids and intravenous immunoglobulin (IVIG) therapy. This case adds to the existing body of evidence regarding the hematological manifestations of SARS-CoV-2 infection, highlighting the importance of considering and managing hematological complications in patients with COVID-19.

A Nomogram for Predicting Delayed Viral Shedding in Non-Severe SARS-CoV-2 Omicron Infection

Purpose

The Omicron variant of SARS-CoV-2 has emerged as a significant global concern, characterized by its rapid transmission and resistance to existing treatments and vaccines. However, the specific hematological and biochemical factors that may impact the clearance of Omicron variant infection remain unclear. The present study aimed to identify easily accessible laboratory markers that are associated with prolonged virus shedding in non-severe patients with COVID-19 caused by the Omicron variant.

Patients and Methods

A retrospective cohort study was conducted on 882 non-severe COVID-19 patients who were diagnosed with the Omicron variant in Shanghai between March and June 2022. The least absolute shrinkage and selection operator regression model was used for feature selection and dimensional reduction, and multivariate logistic regression analysis was performed to construct a nomogram for predicting the risk of prolonged SARS-CoV-2 RNA positivity lasting for more than 7 days. The receiver operating characteristic (ROC) curve and calibration curves were used to assess predictive discrimination and accuracy, with bootstrap validation.

Results

Patients were randomly divided into derivation (70%, n = 618) and validation (30%, n = 264) cohorts. Optimal independent markers for prolonged viral shedding time (VST) over 7 days were identified as Age, C-reactive protein (CRP), platelet count, leukocyte count, lymphocyte count, and eosinophil count. These factors were subsequently incorporated into the nomogram utilizing bootstrap validation. The area under the curve (AUC) in the derivation (0.761) and validation (0.756) cohorts indicated good discriminative ability. The calibration curve showed good agreement between the nomogram-predicted and actual patients with VST over 7 days.

Conclusion

Our study confirmed six factors associated with delayed VST in non-severe SARS-CoV-2 Omicron infection and constructed a Nomogram which may assist non-severely affected patients to better estimate the appropriate length of self-isolation and optimize their self-management strategies.

Coagulation Profile of COVID-19 Patients

Coronavirus disease is a viral infection that can affect multiple systems and be expressed with many-or no-symptoms. The viral infection begins when the virus binds to the host's receptor and from that point on, it is transmitted to the rest of the body, where it causes inflammatory reactions. Among other tissues and systems, SARS-CoV-2 impacts the coagulation system, where it triggers the immunothrombotic response. Its effects are rather intense and can lead to many complications. COVID-19-associated coagulopathy is frequently observed in hospitalized patients, especially ICU patients, and can be proven detrimental. It is usually accompanied by other complications, such as sepsis-induced coagulopathy, disseminated intravascular coagulation and venous thromboembolism. Since all these conditions lead to poor prognosis for severely ill patients, thromboprophylaxis and coagulopathy prognosis are just as important as the therapeutic handling of these patients. Since the beginning of the pandemic, many biomarkers have been considered useful when trying to assess the thrombotic risk of hospitalized patients or evaluate the severity of their situation. At the same time, many drugs have already been tested-while others are still being trialed-in order to find the optimal therapy for each urgent situation.

Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application

Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine learning (ML) sensors for the prompt diagnosis of COVID-19 are an important option for IoT application in healthcare and ambient assisted living (AAL). Determining a COVID-19 infected status with various diagnostic tests and imaging results is costly and time-consuming. This study provides a fast, reliable and cost-effective alternative tool for the diagnosis of COVID-19 based on the routine blood values (RBVs) measured at admission. The dataset of the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 test results and 51 routine blood values. In this study, 13 popular classifier machine learning models and the LogNNet neural network model were exanimated. The most successful classifier model in terms of time and accuracy in the detection of the disease was the histogram-based gradient boosting (HGB) (accuracy: 100%, time: 6.39 sec). The HGB classifier identified the 11 most important features (LDL, cholesterol, HDL-C, MCHC, triglyceride, amylase, UA, LDH, CK-MB, ALP and MCH) to detect the disease with 100% accuracy. In addition, the importance of single, double and triple combinations of these features in the diagnosis of the disease was discussed. We propose to use these 11 features and their binary combinations as important biomarkers for ML sensors in the diagnosis of the disease, supporting edge computing on Arduino and cloud IoT service.

Right-left digit ratios, a novel form of asymmetry: Patterns of instability in children and relationships to platelet counts and hospitalization in adults with COVID-19

High right minus left (R-L) asymmetry of digit ratios has been reported to be linked to hospitalization for COVID-19. Here we examined the developmental patterns of this novel form of asymmetry in children and further explored their relationships to platelet counts and hospitalization for COVID-19 in adult patients. We considered ratios calculated from four digits (2D, 3D, 4D, 5D) in: (i) a sample of healthy participants aged 2 years to 18 years (n = 680, 340 males) and (ii) 96 adult patients (42 males) hospitalized for COVID-19 and 100 controls (53 males). The protocol for (ii) included a questionnaire and laboratory test results. In sample (i) of the six unsigned digit ratio asymmetries, those which included 5D had the highest mean asymmetry with the greatest between-individual variation and they were unstable over the age range of 2 years to 18 years. In sample (ii) patients showed higher asymmetries than controls in four ratios (2D:4D, 2D:5D, 3D:5D, 4D:5D) and a sum of asymmetries of the two independent ratios (2D:4D+3D:5D) correlated positively with platelet counts and hospitalization. Conclusion: Means and SDs of digit ratio asymmetry that include the 5th digit are high and age-unstable. Digit ratio asymmetry, particularly 5th digit ratio asymmetry and a composite measure of 2D:4D + 3D:5D asymmetry, may be positively linked to high platelet counts in COVID-19 patients and to an elevated risk of hospitalization.

Effect of stimulated platelets in COVID-19 thrombosis: Role of alpha7 nicotinic acetylcholine receptor

Since early 2020, SARS-CoV-2-induced infection resulted in global pandemics with high morbidity, especially in the adult population. COVID-19 is a highly prothrombotic condition associated with subsequent multiorgan failure and lethal outcomes. The exact mechanism of the prothrombotic state is not well understood and might be multifactorial. Nevertheless, platelets are attributed to play a crucial role in COVID-19-associated thrombosis. To date, platelets' role was defined primarily in thrombosis and homeostasis. Currently, more focus has been set on their part in inflammation and immunity. Moreover, their ability to release various soluble factors under activation as well as internalize and degrade specific pathogens has been highly addressed in viral research. This review article will discuss platelet role in COVID-19-associated thrombosis and their role in the cholinergic anti-inflammatory pathway. Multiple studies confirmed that platelets display a hyperactivated phenotype in COVID-19 patients. Critically ill patients demonstrate increased platelet activation markers such as P-selectin, PF4, or serotonin. In addition, platelets contain acetylcholine and express α7 nicotinic acetylcholine receptors (α7nAchR). Thus, acetylcholine can be released under activation, and α7nAchR can be stimulated in an autocrine manner and support platelet function. α7 receptor is one of the most important mediators of the anti-inflammatory properties as it is associated with humoral and intrinsic immunity and was demonstrated to contribute to better outcomes in COVID-19 patients when under stimulation. Hematopoietic α7nAchR deficiency increases platelet activation and, in experimental studies, α7nAchR stimulation can diminish the pro-inflammatory state and modulate platelet reactiveness via increased levels of NO. NO has been described to inhibit platelet adhesion, activation, and aggregation. In addition, acetylcholine has been demonstrated to decrease platelet aggregation possibly by blocking the e p-38 pathway. SARS-CoV-2 proteins have been found to be similar to neurotoxins which can bind to nAChR and prevent the action of acetylcholine. Concluding, the platelet role in COVID-19 thrombotic events could be explained by their active function in the cholinergic anti-inflammatory pathway.

Hemostatic system and COVID-19 crosstalk: A review of the available evidence

Since the discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its resultant coronavirus disease 2019 (COVID-19) pandemic, respiratory manifestations have been the mainstay of clinical diagnosis, laboratory evaluations, and radiological investigations. As time passed, other pathological aspects of SARS-CoV-2 have been revealed. Various hemostatic abnormalities have been reported since the rise of the pandemic, which was sometimes superficial, transient, or fatal. Mild thrombocytopenia, thrombocytosis, venous, arterial thromboembolism, and disseminated intravascular coagulation are among the many hemostatic events associated with COVID-19. Venous thromboembolism necessitating therapeutic doses of anticoagulants is more frequently seen in severe cases of COVID-19, especially in patients admitted to intensive care units. Hemorrhagic complications rarely arise in COVID-19 patients either due to a hemostatic imbalance resulting from severe disease or as a complication of over anticoagulation. Although the pathogenesis of coagulation disturbance in SARS-CoV-2 infection is not yet understood, professional societies recommend prophylactic antithrombotic therapy in severe cases, especially in the presence of abnormal coagulation indices. The review article discusses the various available evidence on coagulation disorders, management strategies, outcomes, and prognosis associated with COVID-19 coagulopathy, which raises awareness about the importance of anticoagulation therapy for COVID-19 patients to guard against possible thromboembolic events.

Prognosing the risk of COVID-19 death through a machine learning-based routine blood panel: A retrospective study in Brazil

Background:

Despite an extensive network of primary care availability, Brazil has suffered profoundly during the COVID-19 pandemic, experiencing the greatest sanitary collapse in its history. Thus, it is important to understand phenotype risk factors for SARS-CoV-2 infection severity in the Brazilian population in order to provide novel insights into the pathogenesis of the disease.

Objective:

This study proposes to predict the risk of COVID-19 death through machine learning, using blood biomarkers data from patients admitted to two large hospitals in Brazil.

Methods:

We retrospectively collected blood biomarkers data in a 24-h time window from 6,979 patients with COVID-19 confirmed by positive RT-PCR admitted to two large hospitals in Brazil, of whom 291 (4.2%) died and 6,688 (95.8%) were discharged. We then developed a large-scale exploration of risk models to predict the probability of COVID-19 severity, finally choosing the best performing model regarding the average AUROC. To improve generalizability, for each model five different testing scenarios were conducted, including two external validations.

Results:

We developed a machine learning-based panel composed of parameters extracted from the complete blood count (lymphocytes, MCV, platelets and RDW), in addition to C-Reactive Protein, which yielded an average AUROC of 0.91 ± 0.01 to predict death by COVID-19 confirmed by positive RT-PCR within a 24-h window.

Conclusion:

Our study suggests that routine laboratory variables could be useful to identify COVID-19 patients under higher risk of death using machine learning. Further studies are needed for validating the model in other populations and contexts, since the natural history of SARS-CoV-2 infection and its consequences on the hematopoietic system and other organs is still quite recent.

Inflammatory and thrombotic parameters associated with the COVID-19 course in Poland (SARSTer study)

Purpose

The aim of the study was to assess the coagulation and inflammatory markers connected with severe course of COVID-19 and no clinical improvement.

Material and methods

The study population included 2590 adult patients, diagnosed with COVID-19, selected from the SARSTer national database - an ongoing project led by the Polish Association of Epidemiologists and Infectiologists and supported by the Medical Research Agency. Clinical and laboratory parameters, such as C-reactive protein (CRP), white blood cells (WBCs), neutrophil and lymphocyte count, procalcitonin, ferritin, interleukin-6 (IL-6), D-dimer concentration and platelet (PLT) count were analyzed before and after treatment (remdesivir, tocilizumab, dexamethasone, anticoagulants).

Results

Significant differences between patients with mild and severe course of the disease were observed in all examined parameters before treatment (p ​< ​0.05). After treatment only ferritin concentration did not differ significantly. In patients with pulmonary embolism, CRP concentration, neutrophil count, D-dimer and IL-6 concentration were significantly higher than in patients without embolism (p ​< ​0.05). The significant differences between the groups with and without fatal outcome were observed within all analyzed parameters. Significant differences in all examined parameters before treatment were observed between patients with and without clinical improvement (p ​< ​0.05).

Multivariate logistic regression showed that no clinical improvement was associated with: IL-6>100 ​pg/ml (OR-2.14), D-dimer concentration over 1000 ​ng/ml (OR-1.62) and PLT count below 150,000/μl (OR-1.57).

Conclusions

Severe course of the disease is associated with lower PLT and lymphocyte count, higher D-dimer, CRP, neutrophil count and IL-6 concentration. The best predictors of no clinical improvement in COVID-19 are: IL-6>100 ​pg/ml, D-dimer>1000 ​ng/ml and PLT<150,000/μl.

Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network

Since February 2020, the world has been engaged in an intense struggle with the COVID-19 disease, and health systems have come under tragic pressure as the disease turned into a pandemic. The aim of this study is to obtain the most effective routine blood values (RBV) in the diagnosis and prognosis of COVID-19 using a backward feature elimination algorithm for the LogNNet reservoir neural network. The first dataset in the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 tests. The LogNNet-model achieved the accuracy rate of 99.5% in the diagnosis of the disease with 46 features and the accuracy of 99.17% with only mean corpuscular hemoglobin concentration, mean corpuscular hemoglobin, and activated partial prothrombin time. The second dataset consists of a total of 3899 patients with a diagnosis of COVID-19 who were treated in hospital, of which 203 were severe patients and 3696 were mild patients. The model reached the accuracy rate of 94.4% in determining the prognosis of the disease with 48 features and the accuracy of 82.7% with only erythrocyte sedimentation rate, neutrophil count, and C reactive protein features. Our method will reduce the negative pressures on the health sector and help doctors to understand the pathogenesis of COVID-19 using the key features. The method is promising to create mobile health monitoring systems in the Internet of Things.

COVID-19 and platelet traits: A bidirectional Mendelian randomization study

This study aimed to evaluate the host genetic liability of coronavirus disease 2019 (covid‐19) with platelet traits using the Mendelian randomization (MR) approach. We conducted a bidirectional two‐sample MR using summary statistics from the largest genome‐wide association study of three variables, covid‐19 severity (severe acute respiratory syndrome coronavirus 2 [SARS‐CoV‐2] infection, covid‐19 hospitalization, and severe covid‐19, N = ~1 059 456–1 557 411) and four platelet traits (mean platelet volume [MPV], plateletcrit, platelet distribution width, and platelet count; N = 408 112). Inverse‐variance weighted (IVW), median weighted, MR‐Egger, and contamination mixture methods were used to estimate the causal association. Null and inconsistent associations in the IVW and sensitivity analyses were observed for SARS‐CoV‐2 infection and covid‐19 hospitalization with platelet traits. For severe covid‐19, significant associations with MPV and platelet count were observed in the IVW and sensitivity analyses, with the beta_IVW of 0.01 (95% confidence interval [CI]: 0.005–0.016, p = 3.51 × 10⁻⁴) and −0.009 (95% CI: −0.015 to −0.002, p = 0.008) per doubling in odds of severe covid‐19, respectively. Conversely, null associations were observed for platelet traits with covid‐19 traits. In conclusion, host genetic liability to severe covid‐19 was causally associated with increased MPV and reduced platelet count, which may provide insights into evaluating hypercoagulability and thromboembolic events in covid‐19 patients.

Pathophysiology of COVID-19: Critical Role of Hemostasis

The COVID-19 pandemic, caused by SARS-CoV-2, had its first cases identified in late 2019 and was considered a clinical pandemic in March 2020. In March 2022, more than 500 million people were infected and 6,2 million died as a result of this disease, increasingly associated with changes in human hemostasis, such as hypercoagulation. Numerous factors contribute to the hypercoagulable state, and endothelial dysfunction is the main one, since the activation of these cells can strongly activate platelets and the coagulation system. In addition, there is a dysregulation of the renin-angiotensin system due to the SARS-CoV-2 takeover of the angiotensin converting enzyme 2, resulting in a strong immune response that could further damage the endothelium. Thrombus formation in the pulmonary microvasculature structure in patients with COVID-19 is an important factor to determine the severity of the clinical picture and the outcome of this disease. This review describes the hemostatic changes that occur in SARS-CoV-2 infection, to further improve our understanding of pathogenic mechanisms and the interaction between endothelium dysfunction, kallikrein-kinins, renin angiotensin, and the Coagulation/fibrinolysis systems as underlying COVID-19 effectors. This knowledge is crucial for the development of new effective therapeutic approaches, attenuating the severity of SARS-CoV-2’s infection and to reduce the deaths.

Association of platelet count with mortality in patients with infectious diseases in intensive care unit: a multicenter retrospective cohort study

Platelets play important roles in thrombosis, hemostasis, inflammation, and infection. We aimed to evaluate the association between platelet count and its variation trend and prognosis of patient with infectious diseases in intensive care units (ICUs). This retrospective cohort study extracted 4,251 critically ill adult patients with infectious diseases from the eICU Collaborative Research Database, whose platelet counts were measured daily during the first 7 days after admission. In the survivors, platelet counts decreased in the first days after admission, reached a nadir on day 3, and then returned and continued to rise above the admission value. In non-survivors, the platelet counts decreased after admission, without a subsequent upturn. We defined three subgroups according to the nadir platelet counts within 7 days: ≤50, 50-130, and ≥130 × 10⁹/L, corresponding to high, intermediate, and low ICU mortality. A decreased platelet count was associated with increased ICU mortality (intermediate vs. low: 1.676 [1.285-2.187]; high vs. low: 3.632 [2.611-5.052]). In conclusion, during the first 7 days, platelet counts decreased after ICU admission, while increased subsequently in the survivors but not in the non-survivors. ICU mortality risk increased as nadir platelet count decreased below 130 × 10⁹/L, and further boosted when it reached below 50 × 10⁹/L.

What is the impact and efficacy of routine immunological, biochemical and hematological biomarkers as predictors of COVID-19 mortality?

It remains important to investigate the changing and impact of routine blood values (RBVs) in order to predict mortality and follow an appropriate treatment in COVID-19 patients. In the study, the importance of RBVs in the mortality of patients with COVID-19 was investigated. The changes in the biochemical, hematological, and immunological parameters of patients who recovered (n = 4364) and died (n = 233) from COVID-19 over time and their relationship with the mortality of the disease were evaluated retrospectively. Odds ratios of the parameters affecting one-month mortality were calculated by running multiple-logistic-regression analysis. The cut off values and diagnostic efficiencies of the parameters that posed a risk for mortality were obtained via receiver operating curve analysis. It was determined that the C-reactive protein (CRP), D-dimer, procalcitonin, erythrocyte-sedimentation-rate (ESR), troponin values were at abnormal levels until death occurred in the patients who died. In addition, the procalcitonin levels were consistently high in patients who died. The patients who died generally had a sustained increase in their leukocyte and neutrophil levels and biochemical variables, and an ongoing decrease in lymphopenia and eosinopenia levels. Although significant changes were observed in liver function tests, cardiac troponin, hemogram values, kidney function tests and parameters related to inflammation in deceased patients, high ESR, international-normalized-ratio (INR), prothrombin-time (PT), CRP, D-dimer, ferritin and red-cell-distribution width (RDW) values, respectively, were the most effective predictive mortality risk biomarkers of COVID-19. In addition, neutrophilia, leukocytosis, thrombocytopenia, erythrocytopenia were other risk predictors of mortality. Indicators was found in this study can be successfully used to predict mortality from COVID-19.

Insight into prognostics, diagnostics, and management strategies for SARS CoV-2

The foremost challenge in countering infectious diseases is the shortage of effective therapeutics. The emergence of coronavirus disease (COVID-19) outbreak has posed a great menace to the public health system globally, prompting unprecedented endeavors to contain the virus. Many countries have organized research programs for therapeutics and management development. However, the longstanding process has forced authorities to implement widespread infrastructures for detailed prognostic and diagnostics study of severe acute respiratory syndrome (SARS CoV-2). This review discussed nearly all the globally developed diagnostic methodologies reported for SARS CoV-2 detection. We have highlighted in detail the approaches for evaluating COVID-19 biomarkers along with the most employed nucleic acid- and protein-based detection methodologies and the causes of their severe downfall and rejection. As the variable variants of SARS CoV-2 came into the picture, we captured the breadth of newly integrated digital sensing prototypes comprised of plasmonic and field-effect transistor-based sensors along with commercially available food and drug administration (FDA) approved detection kits. However, more efforts are required to exploit the available resources to manufacture cheap and robust diagnostic methodologies. Likewise, the visualization and characterization tools along with the current challenges associated with waste-water surveillance, food security, contact tracing, and their role during this intense period of the pandemic have also been discussed. We expect that the integrated data will be supportive and aid in the evaluation of sensing technologies not only in current but also future pandemics.

Pathological effects of SARS-CoV-2 on hematological and immunological cells: Alterations in count, morphology, and function

The novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent of COVID-19 outbreak, spread rapidly and infected more than 140 million people with more than three million victims worldwide. The SARS-CoV-2 causes destructive changes in the immunological and hematological system of the host. These alterations appear to play a critical role in disease pathology and the emerging of clinical manifestations. In this review, we aimed to discuss the effect of COVID-19 on the count, function and morphology of immune and blood cells and the role of these changes in the pathophysiology of the disease. Knowledge of these changes may help with better management and treatment of COVID-19 patients.

Prevention and management of thrombosis in hospitalised patients with COVID-19 pneumonia

A proportion of people infected with SARS-CoV-2 develop moderate or severe COVID-19, with an increased risk of thromboembolic complications. The inflammatory response to SARS-CoV-2 infection can cause an acute-phase response and endothelial dysfunction, which contribute to COVID-19-associated coagulopathy, the clinical and laboratory features of which differ in some respects from those of classic disseminated intravascular coagulation. Understanding of the pathophysiology of thrombosis in COVID-19 is needed to develop approaches to management and prevention, with implications for short-term and long-term health outcomes. Evidence is emerging to support treatment decisions in patients with COVID-19, but many questions remain about the optimum approach to management. In this Viewpoint, we provide a summary of the pathophysiology of thrombosis and associated laboratory and clinical findings, and highlight key considerations in the management of coagulopathy in hospitalised patients with severe COVID-19, including coagulation assessment, identification of thromboembolic complications, and use of antithrombotic prophylaxis and therapeutic anticoagulation. We await the results of trials that are underway to establish the safety and benefits of prolonged thromboprophylaxis after hospital discharge.

A Model Predicting Mortality of Hospitalized Covid-19 Patients Four Days After Admission: Development, Internal and Temporal-External Validation

Objective

To develop and validate a prognostic model for in-hospital mortality after four days based on age, fever at admission and five haematological parameters routinely measured in hospitalized Covid-19 patients during the first four days after admission.

Methods

Haematological parameters measured during the first 4 days after admission were subjected to a linear mixed model to obtain patient-specific intercepts and slopes for each parameter. A prediction model was built using logistic regression with variable selection and shrinkage factor estimation supported by bootstrapping. Model development was based on 481 survivors and 97 non-survivors, hospitalized before the occurrence of mutations. Internal validation was done by 10-fold cross-validation. The model was temporally-externally validated in 299 survivors and 42 non-survivors hospitalized when the Alpha variant (B.1.1.7) was prevalent.

Results

The final model included age, fever on admission as well as the slope or intercept of lactate dehydrogenase, platelet count, C-reactive protein, and creatinine. Tenfold cross validation resulted in a mean area under the receiver operating characteristic curve (AUROC) of 0.92, a mean calibration slope of 1.0023 and a Brier score of 0.076. At temporal-external validation, application of the previously developed model showed an AUROC of 0.88, a calibration slope of 0.95 and a Brier score of 0.073. Regarding the relative importance of the variables, the (apparent) variation in mortality explained by the six variables deduced from the haematological parameters measured during the first four days is higher (explained variation 0.295) than that of age (0.210).

Conclusions

The presented model requires only variables routinely acquired in hospitals, which allows immediate and wide-spread use as a decision support for earlier discharge of low-risk patients to reduce the burden on the health care system.

Clinical Trial Registration

Austrian Coronavirus Adaptive Clinical Trial (ACOVACT); ClinicalTrials.gov, identifier NCT04351724.

Impact of Dementia on Mortality Due to Coronavirus Disease 2019: Propensity-Score-Matching Study

BACKGROUND AND PURPOSE

Patients with dementia are particularly vulnerable to coronavirus disease 2019 (COVID-19) because they tend to be older and often have concomitant diseases. Previous studies have investigated the impact of dementia on COVID-19 outcomes, but the evidence is not robust for Asian populations. We aimed to determine the relationship between dementia and COVID-19 outcomes using data from a large-scale nationwide public database.

METHODS

Data on patients with COVID-19 who were released from quarantine between January 1, 2020 and April 30, 2020, published by the Korea Disease Control and Prevention Agency, were divided into two groups based on the dementia status. Propensity-score matching was used to adjust for multiple confounders between the dementia and no-dementia groups. Binary, ordinal logistic regression and multivariate Cox proportional-hazards models were used to compare mortality, quarantine duration, and clinical deterioration according to the dementia status in the two groups.

RESULTS

Males and older individuals (age ≥60 years) constituted 41.5% and 32.9%, respectively, of the 5,299 patients. The prevalence of dementia was 4.2%, and 4.5% of the participants died during hospitalization. In multivariate analysis, dementia was significantly associated with increased mortality (odds ratio [OR]=2.80, 95% confidence interval [CI]=1.60-4.60), longer duration of quarantine (hazard ratio=1.69, 95% CI=1.16-2.45), and larger shift to a worse clinical severity (common OR=1.74, 95% CI=1.18-2.61).

CONCLUSIONS

After adjusting for important clinical predictors, dementia was associated with increased in-hospital mortality, duration of quarantine, and clinical deterioration during hospitalization in COVID-19 patients.

Prothrombotic Phenotype in COVID-19: Focus on Platelets

COVID-19 infection is associated with a broad spectrum of presentations, but alveolar capillary microthrombi have been described as a common finding in COVID-19 patients, appearing as a consequence of a severe endothelial injury with endothelial cell membrane disruption. These observations clearly point to the identification of a COVID-19-associated coagulopathy, which may contribute to thrombosis, multi-organ damage, and cause of severity and fatality. One significant finding that emerges in prothrombotic abnormalities observed in COVID-19 patients is that the coagulation alterations are mainly mediated by the activation of platelets and intrinsically related to viral-mediated endothelial inflammation. Beyond the well-known role in hemostasis, the ability of platelets to also release various potent cytokines and chemokines has elevated these small cells from simple cell fragments to crucial modulators in the blood, including their inflammatory functions, that have a large influence on the immune response during infectious disease. Indeed, platelets are involved in the pathogenesis of acute lung injury also by promoting NET formation and affecting vascular permeability. Specifically, the deposition by activated platelets of the chemokine platelet factor 4 at sites of inflammation promotes adhesion of neutrophils on endothelial cells and thrombogenesis, and it seems deeply involved in the phenomenon of vaccine-induced thrombocytopenia and thrombosis. Importantly, the hyperactivated platelet phenotype along with evidence of cytokine storm, high levels of P-selectin, D-dimer, and, on the other hand, decreased levels of fibrinogen, von Willebrand factor, and thrombocytopenia may be considered suitable biomarkers that distinguish the late stage of COVID-19 progression in critically ill patients.

Fundamentals in Covid-19-Associated Thrombosis: Molecular and Cellular Aspects

The novel coronavirus disease (COVID-19) is associated with a high incidence of coagulopathy and venous thromboembolism that may contribute to the worsening of the clinical outcome in affected patients. Marked increased D-dimer levels are the most common laboratory finding and have been repeatedly reported in critically ill COVID-19 patients. The infection caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is followed by a massive release of pro-inflammatory cytokines, which mediate the activation of endothelial cells, platelets, monocytes, and neutrophils in the vasculature. In this context, COVID-19-associated thrombosis is a complex process that seems to engage vascular cells along with soluble plasma factors, including the coagulation cascade, and complement system that contribute to the establishment of the prothrombotic state. In this review, we summarize the main findings concerning the cellular mechanisms proposed for the establishment of COVID-19-associated thrombosis.

Prognostic Nutritional Index and CRP, age, platelet count, albumin level score in predicting mortality and intensive care unit admission for COVID-19

Aim: In our study, we investigated the efficiency of the prognostic nutritional index (PNI) score and the CRP, age, platelet count, albumin level (CAPA) score predicting mortality and intensive care unit (ICU) admission in COVID-19 disease. Materials & methods: PNI and CAPA score of patients confirmed with COVID-19 calculated by using the complete blood count and biochemical parameters at admission to the hospital, in predicting the COVID-19-associated mortality and ICU admission were analyzed. Results: PNI and CAPA scores in predicting mortality were detected as AUC: 0.67 (p < 0.001), AUC: 0.71 (p < 0.001), respectively. For predicting ICU admission AUC was 0.66 (p < 0.001), AUC was 0.77 (p < 0.001), respectively. Conclusion: PNI and CAPA scores are effective scores in COVID-19, with CAPA score being better in predicting mortality and ICU admission.

Platelets contribute to disease severity in COVID-19

OBJECTIVE

Heightened inflammation, dysregulated immunity, and thrombotic events are characteristic of hospitalized COVID-19 patients. Given that platelets are key regulators of thrombosis, inflammation, and immunity they represent prime candidates as mediators of COVID-19-associated pathogenesis. The objective of this study was to understand the contribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the platelet phenotype via phenotypic (activation, aggregation) and transcriptomic characterization.

APPROACH AND RESULTS

In a cohort of 3915 hospitalized COVID-19 patients, we analyzed blood platelet indices collected at hospital admission. Following adjustment for demographics, clinical risk factors, medication, and biomarkers of inflammation and thrombosis, we find platelet count, size, and immaturity are associated with increased critical illness and all-cause mortality. Bone marrow, lung tissue, and blood from COVID-19 patients revealed the presence of SARS-CoV-2 virions in megakaryocytes and platelets. Characterization of COVID-19 platelets found them to be hyperreactive (increased aggregation, and expression of P-selectin and CD40) and to have a distinct transcriptomic profile characteristic of prothrombotic large and immature platelets. In vitro mechanistic studies highlight that the interaction of SARS-CoV-2 with megakaryocytes alters the platelet transcriptome, and its effects are distinct from the coronavirus responsible for the common cold (CoV-OC43).

CONCLUSIONS

Platelet count, size, and maturity associate with increased critical illness and all-cause mortality among hospitalized COVID-19 patients. Profiling tissues and blood from COVID-19 patients revealed that SARS-CoV-2 virions enter megakaryocytes and platelets and associate with alterations to the platelet transcriptome and activation profile.

A rare case of intracerebral hemorrhage complicating heparin-induced thrombocytopenia in a COVID-19 patient

Introduction

Heparin-induced thrombocytopenia is a rare complication of heparin therapy associated with thrombocytopenia and mainly thrombotic complications.

Case report

we herein describe a case of a woman hospitalized for management of a severe case of COVID-19 treated with low molecular weight heparin, who developed heparin-induced thrombocytopenia complicated by intracerebral hemorrhage with no thrombotic complications.

Conclusion

Discontinuation of heparin was effective without the use of other non-heparin anticoagulants, platelet transfusion or plasmapheresis.

•

HIT is a rare complication of LMWH, it is associated with thrombocytopenia and mainly thrombotic complications.

•

In this paper we will report a rare complication of HIT : ICH in a 63 years old woman admitted for covid 19-infection.

•

Discontinuation of heparin was effective without the use of other non-heparin anticoagulants, platelet transfusion or plasmapheresis.

Drug delivery systems as immunomodulators for therapy of infectious disease: Relevance to COVID-19

The emergence of SARS-CoV-2, and the ensuing global pandemic, has resulted in an unprecedented response to identify therapies that can limit uncontrolled inflammation observed in patients with moderate to severe COVID-19. The immune pathology behind COVID-19 is complex and involves the activation and interaction of multiple systems including, but not limited to, complement, inflammasomes, endothelial as well as innate and adaptive immune cells to bring about a convoluted profile of inflammation, coagulation and tissue damage. To date, therapeutic approaches have focussed on inhibition of coagulation, untargeted immune suppression and/or cytokine-directed blocking agents. Regardless of recently achieved improvements in individual patient outcomes and survival rates, improved and focussed approaches targeting individual systems involved is needed to further improve prognosis and wellbeing. This review summarizes the current understanding of molecular and cellular systems involved in the pathophysiology of COVID-19, and their contribution to pathogen clearance and damage to then discuss possible therapeutic options involving immunomodulatory drug delivery systems as well as summarising the complex interplay between them.

Mechanisms of immunothrombosis in COVID-19

PURPOSE OF REVIEW

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus-2. Over the past year, COVID-19 has posed a significant threat to global health. Although the infection is associated with mild symptoms in many patients, a significant proportion of patients develop a prothrombotic state due to a combination of alterations in coagulation and immune cell function. The purpose of this review is to discuss the pathophysiological characteristics of COVID-19 that contribute to the immunothrombosis.

RECENT FINDINGS

Endotheliopathy during COVID-19 results in increased multimeric von Willebrand factor release and the potential for increased platelet adhesion to the endothelium. In addition, decreased anticoagulant proteins on the surface of endothelial cells further alters the hemostatic balance. Soluble coagulation markers are also markedly dysregulated, including plasminogen activator inhibitor-1 and tissue factor, leading to COVID-19 induced coagulopathy. Platelet hyperreactivity results in increased platelet-neutrophil and -monocyte aggregates further exacerbating the coagulopathy observed during COVID-19. Finally, the COVID-19-induced cytokine storm primes neutrophils to release neutrophil extracellular traps, which trap platelets and prothrombotic proteins contributing to pulmonary thrombotic complications.

SUMMARY

Immunothrombosis significantly contributes to the pathophysiology of COVID-19. Understanding the mechanisms behind COVID-19-induced coagulopathy will lead to future therapies for patients.

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.

The Development of Ecchymosis after Administration of Convalescent Serum in a Patient with COVID-19 Associated with Thrombocytosis

COVID-19 can have an unpredictable and severe course, leading to many hypotheses regarding its pathophysiology and clinical manifestations. Haematological manifestations are a significant predictor of disease severity. The most common observation is lymphopenia with an increased neutrophil:lymphocyte ratio. Platelets have been implicated in thrombogenic events, but the most frequently reported abnormality is mild thrombocytopenia. Here we present an interesting case of a patient with moderate COVID-19 who presented with cutaneous ecchymoses and thrombocytosis, and discuss this paradox.

LEARNING POINTS

Bleeding manifestations such as ecchymoses can occur as an idiosyncratic reaction to the administration of convalescent plasma therapy in COVID-19.Thrombocytosis can occur in COVID-19 and could be a contributory factor to disease vasculopathy.

Endothelial Activation and Stress Index (EASIX) as an Early Predictor for Mortality and Overall Survival in Hematological and Non-Hematological Patients with COVID-19: Multicenter Cohort Study

COVID-19, as a disease involving the endothelium of multiple organs, is characterized by high mortality rates among hospitalized patients. Patients with hematological malignancies are particularly at risk of an unfavorable course of COVID-19. The endothelial activation and stress index (EASIX) score has been used as a simple predictor of overall survival (OS) in specific groups of hematological cancer patients. EASIX, as a biomarker of endothelial dysfunction, might play a prognostic role in patients with COVID-19. Here, we performed a comprehensive retrospective analysis of the EASIX score in 523 hospitalized COVID-19 patients with or without coexisting hematological cancer. Hematological cancer COVID-19 patients had higher EASIX scores compared to the overall population with COVID-19. In hematological patients, EASIX was a strong predictor of the occurrence of sepsis during COVID-19. Our findings demonstrated EASIX as a strong predictor of intensive care unit admission, in-hospital mortality, the occurrence of acute renal failure and the need for hemodialysis, both in hematological and non-hematological COVID-19 patients. Patients with a high EASIX score on COVID-19 diagnosis had significantly inferior OS compared to patients with low EASIX. We showed for the first time that EASIX might serve as a simple, universal prognostic tool of OS in both hematological and non-hematological COVID-19 patients.

Association of HScore Parameters with Severe COVID-19: A Systematic Review and Meta-Analysis

BACKGROUND

Several reports have associated the severe Coronavirus disease-2019 (sCOVID-19) with secondary-hemophagocytic lymphohistiocytosis (sHLH) and proposed utilizing the hemophagocytic syndrome diagnostic score (HScore) for sCOVID-19 patients. We conducted a systematic review and meta-analysis to find the possible association of HScore parameters with severity in COVID-19 patients.

METHODS

A systematic search was performed in Medline via PubMed, EMBASE, and Cochrane databases using all HScore and COVID-19 keywords. The studies were all from 2020, and the study language was limited to English. The records were screened based on inclusion/exclusion criteria. Random/fixed-effect models were employed for meta-analysis, based on the I2 index of parameters. The pooled mean differences were estimated for continuous parameters. The pooled odds-ratio was estimated for fever. The level of significance was set at 0.05.

RESULTS

Eighteen studies (comprising 2459 patients) out of 26151 screened studies were included in this meta-analysis. The results showed that the level of leukocyte, neutrophil, aspartate transaminase (AST), ferritin, and fibrinogen were significantly higher in sCOVID-19 patients than in non-severe ones. Significant lower levels of lymphocyte, platelet, and hemoglobin were also found in sCOVID-19 patients than non-severe patients. Fever was nearly associated with two times increased odds of sCOVID-19 (P=0.051).

CONCLUSION

Lymphopenia, thrombocytopenia, hypohemoglobinemia, hyperferritinemia, high levels of AST, and fever are common features of both sCOVID-19 and HLH. However, the leukocytosis, neutrophilia, and hyperfibrinogenemia found in sCOVID-19 are in contrast with HScore. Conclusively, HScore parameters could be risk factors for sCOVID-19. However, some parameters' roles are contradictory, suggesting the need for further investigation and a new way of HScore interpretation in sCOVID-19 patients.A preprint of this study was published at https://www.researchsquare.com/article/rs-54490/v2.

The effectiveness of blood routine parameters and some biomarkers as a potential diagnostic tool in the diagnosis and prognosis of Covid-19 disease

Since February-2020, the world has been battling a tragic public-health crisis with the emergence and spread of 2019-nCoV. Due to the lack of information about the pathogenesis-specific treatment of Covid-19, early diagnosis and timely treatment are important. However, there is still a lack of information about routine-blood-parameteres (RBP) findings and effects in the disease process. Although the literature includes various interventions, existing studies need to be generalized and their reliability improved. In this study, the efficacy of routine blood values used in the diagnosis and prognosis of Covid-19 and independent biomarkers obtained from them were evaluated retrospectively in a large patient group. Low lymphocyte (LYM) and white-blood-cell (WBC), high CRP and Ferritin were effective in the diagnosis of the disease. The (d-CWL) = CRPWBC∗LYM and (d-CFL) = CRP∗FerritinLYM biomarkers derived from them were the most important risk factors in diagnosing the disease and were more successful than direct RBP values. High d-CWL and d-CFL values largely confirmed the Covid-19 diagnosis. The most effective RBP in the prognosis of the disease was CRP. (d-CIT) = CRP*INR*Troponin; (d-CT) = CRP*Troponin; (d-PPT) = PT*Troponin*Procalcitonin biomarkers were found to be more successful than direct RBP values and biomarkers used in previous studies in the prognosis of the disease. In this study, biomarkers derived from RBP were found to be more successful in both diagnosis and prognosis of Covid-19 than previously used direct RBP and biomarkers.

Thrombosis in COVID-19 infection: Role of platelet activation-mediated immunity

Background

Thrombosis plays an important role in the Coronavrus Disease 2019 (COVID-19) infection-related complications such as acute respiratory distress syndrome and myocardial infarction. Multiple factors such as oxygen demand injuries, endothelial cells injury related to infection, and plaque formation.

Main body

Platelets obtained from the patients may have severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, showing that the increased activation potential recommends platelet can be hyper-activated in severely ill SARS-CoV-2 cases. Platelets contain multiple receptors that interact with specific ligands. Pathogen’s receptors such as Toll-like receptors (TLRs), NOD-like receptor, C-type lectin receptor family, glycoprotein (GP) such as GPαIIbβ3 and GPIbα which allow pathogens to interact with platelets. Platelet TLRs and NOD2 are involved in platelet activation and thrombosis. Accordingly, TLRs are critical receptors that could recognize various endogenous damage-associated molecular patterns and exogenous pathogen-associated molecular patterns (PAMPs). TLRs are considered as important components in the activation of innate immunity response against pathogenic and non-pathogenic components like damaged tissues. TLRs-1,-2,-4,-6,-7 expression on or within platelets has been reported previously. Various PAMPs were indicated to be capable of binding to platelet-TLRs and inducing both the activation and promotion of downstream proinflammatory signaling cascade.

Conclusion

It is possible that the increased TLRs expression and TLR-mediated platelets activation during COVID-19 may enhance vascular and coronary thrombosis. It may be hypothesized using TLRs antagonist and monoclonal antibody against P-selectin, as the marker of leukocyte recruitment and platelet activation, besides viral therapy provide therapeutic advances in fighting against the thrombosis related complications in COVID-19.

Nebulization with alkaline hipertonic ibuprofen induces a rapid increase in platelets circulating in COVID-19 patients but not in healthy subjects

We analyze changes in circulating platelets in COVID-19 positive patients who received conventional treatment Dexamethasone and Enoxaparin (Dexa-Enoxa) compared to patients treated with conventional therapy plus nebulization with alkaline hypertonic ibuprofenate (AHI). Results show that after 24 h of nebulization with AHI, circulating platelets shows an increase about 40% at 24 h and reach 65% at 96 h. In patients with platelets content below 200,000 by microliter the increase was 49% and 79% at 24 and 96 h respectively. In patients with platelets above 200,000 by microliter the increase was 24% and 31% at 24 and 96 h, respectively. The increase of platelets via AHI was similar in both, men and women.To evaluate whether this action of AHI was related to platelets from COVID-19 positive patients or also for healthy people, two controls were included: one of them with 10 healthy volunteers and another one with COVID-19 positive patients hospitalized and treated only with Dexa-Enoxa. Results show that, in healthy volunteers, the number of circulating platelets remains unchanged even after 7 days of treatment with AHI. In COVID-19 positive patients treated only with Dexa-Enoxa for 4 days, platelets increased only 16%.