Significance of heparin induced thrombocytopenia (HIT) in COVID-19: a systematic review and meta-analysis.

Heparin-induced thrombocytopenia (HIT) occurs in approximately 3% of patients receiving heparinoids. About 30-75% of patients with type 2 of HIT develop thrombosis as a result of platelet activation. The most important clinical symptom is thrombocytopenia. Patients with severe COVID-19 are among those receiving heparinoids. This meta-analysis performed to picture the current knowledge and results of published studies in this field. Three search engines were searched and 575 papers were found. After evaluation, 37 articles were finally selected of which 13 studies were quantitatively analyzed. The pooled frequency rate of suspected cases with HIT in 13 studies with 11,241 patients was 1.7%. The frequency of HIT was 8.2% in the extracorporeal membrane oxygenation subgroup with 268 patients and 0.8% in the hospitalization subgroup with 10,887 patients. The coincidence of these two conditions may increase the risk of thrombosis. Of the 37 patients with COVID-19 and confirmed HIT, 30 patients (81%) were treated in the intensive care unit or had severe COVID-19. The most commonly used anticoagulants were UFH in 22 cases (59.4%). The median platelet count before treatment was 237 (176-290) x 103/µl and the median nadir platelet count was 52 (31-90.5) x 103/µl.

Deregulation of the Expression of Beclin1 and Light Chain 3(LC3), Autophagy-Related Genes, in COVID-19 Patients.

Background: The autophagy machinery is reported to be employed by Coronaviruses during their replication. Beclin-1 (BECN1) and protein 1 light chain 3 (LC3) are two key elements in the autophagy process, and their inhibition can prevent the replication of some coronaviruses in vitro. Here, we aimed to investigate the expression levels of Beclin-1 and LC3 in COVID-19 patients and healthy controls, hoping to find new therapeutic targets. Methods: This cross-sectional study was conducted in Imam Reza and Ghaem University Hospitals, Mashhad, Iran. Nasopharyngeal samples of 68 consecutive Covid-19 patients and 61 healthy controls, who have been referred to the laboratories for COVID-19 PCR testing between 21 March to 21 September 2021, were used in order to evaluate the expression of BECN1 and LC3 genes using the Real-time quantitative PCR method. Demographic and other laboratory findings of patients were extracted from the hospital electronic system. SPSS Statistics 16.0 and Graph Pad Prism 8.4.2 soft wares were used for statistical analysis. Non-parametric tests were used. Results: BECN1 expression was significantly higher in COVID-19 patients compared to the controls (14.37±18.84 vs. 4.26±7.39, p=0.001). The expression of LC3 gene was significantly lower in patients compared to the controls (1.01±1.06 vs. 1.49±1.12, p=0.007). There was no significant correlation between the expression levels of BECN1 and LC3. Patients with lower BECN1 expression showed significantly higher RBC counts, higher Urea and lower HCO3 levels. The patients in LC3Low group showed significantly lower MCH, MCHC and PH levels compared to the others. Conclusion: Regarding the significant difference in the expression of BECN1 and LC3 in COVID-19 patients compared to the controls, these molecules may have a role in the pathogenesis of this disease. In case of further confirmation of this role, these molecules may be used as possible therapeutic targets.

Trend of fluctuations of antithrombin in plasma of patients with COVID-19: a meta-analysis and systematic review.

BACKGROUND: Antithrombin is considered as one of the accused markers for the development of thrombosis in patients with COVID-19. Because plasma levels of antithrombin vary in patients with COVID-19, a meta-analysis was performed to determine the trend of antithrombin levels in patients with COVID-19. RESEARCH DESIGN AND METHODS: A literature search was performed on PubMed, Scopus, and the Web of Science to find papers on antithrombin levels in patients with COVID-19. After removing duplicate papers, inclusion and exclusion criteria were applied. The full texts of the articles were read to select relevant articles and then to identify the data needed. All meta-analyses were performed using Stata software v16.0. RESULTS: Testing for differences between subgroups showed a significant difference between ICU and non-ICU patients. Analysis showed a significant decrease in antithrombin level in patients with severe COVID-19. Analysis showed that the mean value of antithrombin level was 89.65% in all patients. The antithrombin level was significantly lower in the non-survivor group (87.52%) than in the survivor group (92.38%). CONCLUSION: Determination of antithrombin may be useful to determine the susceptibility of COVID-19 patients to hypercoagulability and to indicate the severity of COVID-19 infection.

A novel explainable COVID-19 diagnosis method by integration of feature selection with random forest.

Several Artificial Intelligence-based models have been developed for COVID-19 disease diagnosis. In spite of the promise of artificial intelligence, there are very few models which bridge the gap between traditional human-centered diagnosis and the potential future of machine-centered disease diagnosis. Under the concept of human-computer interaction design, this study proposes a new explainable artificial intelligence method that exploits graph analysis for feature visualization and optimization for the purpose of COVID-19 diagnosis from blood test samples. In this developed model, an explainable decision forest classifier is employed to COVID-19 classification based on routinely available patient blood test data. The approach enables the clinician to use the decision tree and feature visualization to guide the explainability and interpretability of the prediction model. By utilizing this novel feature selection phase, the proposed diagnosis model will not only improve diagnosis accuracy but decrease the execution time as well.

Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods.

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients' characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.

Hemostatic System (Fibrinogen Level, D-Dimer, and FDP) in Severe and Non-Severe Patients With COVID-19: A Systematic Review and Meta-Analysis.

SARS-CoV-2 in COVID-19 triggers abnormalities in coagulation parameters that can contribute to thrombosis. The goals of this research were to determine the levels of fibrinogen, D-dimer and FDP in COVID-19 patients. Following a systematic study, among 1198 articles, 35 studies were included in the meta-analysis of fibrinogen levels in both severe and non-severe groups. The funnel plot, Egger's regression asymmetry test, and Begg's test used to measure the bias of publications. All meta-analysis performed by comprehensive meta-analysis version 2 (CMA2). The pooled findings of fibrinogen levels revealed a significant rise in fibrinogen levels in severe COVID-19 than non-severe patients with COVID-19. The D-dimer and FDP levels were significantly higher in severe patients than non-severe patients with COVID-19 were. The levels of fibrinogen, D-dimer, and FDP have increased significantly in ICU patients compared to non-ICU patients. Although, levels of clotting parameters do not always correlate with the severity of disease, these findings showed the diagnostic importance for fibrinogen, D-dimer, and FDP in COVID-19. The presence of a continuous rise in serial measurements of fibrinogen, D-dimer, and FDP may predict that patients with COVID-19 may become critically ill.

High levels of Von Willebrand factor markers in COVID-19: a systematic review and meta-analysis.

The SARS-CoV-2 virus has spread to all corners of the world. Thrombosis is the cause of organ failure and subsequent death in COVID-19. The pathophysiology of thrombosis in COVID-19 needs to be further explored to shed light on its downside. For this reason, this meta-analysis of Von Willebrand Factor profile (VWF: Ag, VWF: activity, VWF: RCo), ADAMTS-13, and factor VIII levels in COVID-19 was performed. To obtain data on the status of the aforementioned hemostatic factors, a systematic literature review and meta-analysis were performed on COVID-19. After reviewing the evaluation of 348 papers, 28 papers included in the meta-analysis, which was performed using STATA. The analysis showed an increase in VWF: Ag levels in COVID-19 patients. VWF: Ac was higher in all COVID-19 patients, while it was lower in the COVID-19 ICU patients. The pooled mean of VWF: RCO in all patients with COVID-19 was 307.94%. In subgroup analysis, VWF: RCO was significantly higher in ICU patients than in all COVID-19 patients. The pooled mean of ADAMTS-13 activity was 62.47%, and 58.42% in ICU patients. The pooled mean of factor VIII level was 275.8%, which was significantly higher in ICU patients with COVID-19 than all patients with COVID-19. Levels of VWF: Ag, VWF: activity, VWF: ristocetin, and factor VIII are increased in patients with COVID-19. The elevated levels in ICU patients with COVID-19 suggest that these markers may have prognostic value in determining the severity of COVID-19. New therapeutic programs can be developed as a result.

D-dimer level in COVID-19 infection: a systematic review.

INTRODUCTION: COVID-19 disease has spread worldwide from December 2019 to the present day; the early stage of this disease can be associated with high D-dimer, prolonged PT, and elevated levels of fibrinogen, indicating activation of coagulation pathways and thrombosis. In this article, we analyze the levels of D-dimer in patients with COVID-19. AREA COVERED: In the current study, three databases, PubMed, Scopus, Web of Science, searched using related keywords and information extracted from articles such as location, sample size, gender, age, coagulation test values, patient results, and disease severity. EXPERT OPINION: D-dimer level is one of the measures used in patients to detect thrombosis. Studies have reported an increase in D-dimer and fibrinogen concentrations in the early stages of COVID-19 disease a 3 to 4-fold rise in D-dimer levels is linked to poor prognosis. In addition, underlying diseases such as diabetes, cancer, stroke, and pregnancy may trigger an increase in D-dimer levels in COVID-19 patients. Measuring the level of D-dimer and coagulation parameters from the early stage of the disease can also be useful in controlling and managing of COVID-19 disease.