Coronavirus Disease 2019 Subjects Research Articles

Are Changes in Serum IgG Glycosylation Related to the Severe Course of SARS-CoV-2 Infection and Recovery Process? In Search of New Diagnostic and Prognostic Biomarkers.

Immunoglobulin G (IgG) glycosylation affects its effector functions and is essential in many steps of the inflammatory cascade. Therefore, it may be an important parameter for assessing the body's immune response during the course of COVID-19 (Coronavirus disease 2019). The N- and O-glycosylation of serum IgG in severe COVID-19 patients (n=87), convalescents (n=50), and healthy subjects (n=65) were examined using a modified lectin-ELISA method with specific biotinylated lectins. The obtained data were analyzed using STATISTICA 13.3PL software. We showed significantly higher expression of Lewisx oligosaccharide structures in severe COVID-19 patients than in the other two groups. Moreover, significantly lower expression of Lewisy sugar structures in IgG glycans was observed in the convalescents when compared with COVID-19 patients and healthy subjects. The lowest expression of highly branched N-glycans in cases of severe COVID-19 indicates that the development of the disease is associated with the presence of typical IgG biantennary N-glycans. The lack of significant differences in the expression of Tn antigen in IgG between studied groups and the significantly lower expression of T antigen in convalescents compared to the patients with severe COVID-19 and healthy subjects indicates a decrease in the content of the T antigen in IgG O-glycans in subjects recovered from COVID-19. Substantially higher reactivities of IgG O-glycans with Jacalin observed in COVID-19 patients and convalescents in comparison to the control group were most probably caused by increased expression of core 3 O-glycans in IgG. Severe COVID-19 is accompanied by the expression in serum IgG of sialylated biantennary and highly branched N-glycans, decorated by fucose of Lewisx and Lewisy structures. The higher reactivity of IgG O-glycans with Jacalin in severe COVID-19 patients and convalescents indicates that the disease development and the recovery process are most probably accompanied by increased expression of the core 3 O-glycans.

COVID-19 impairs oxygen delivery by altering red blood cell hematological, hemorheological, and oxygen transport properties.

Introduction: Coronavirus disease 2019 (COVID-19) is characterized by impaired oxygen (O2) homeostasis, including O2 sensing, uptake, transport/delivery, and consumption. Red blood cells (RBCs) are central to maintaining O2 homeostasis and undergo direct exposure to coronavirus in vivo. We thus hypothesized that COVID-19 alters RBC properties relevant to O2 homeostasis, including the hematological profile, Hb O2 transport characteristics, rheology, and the hypoxic vasodilatory (HVD) reflex. Methods: RBCs from 18 hospitalized COVID-19 subjects and 20 healthy controls were analyzed as follows: (i) clinical hematological parameters (complete blood count; hematology analyzer); (ii) O2 dissociation curves (p50, Hill number, and Bohr plot; Hemox-Analyzer); (iii) rheological properties (osmotic fragility, deformability, and aggregation; laser-assisted optical rotational cell analyzer (LORRCA) ektacytometry); and (iv) vasoactivity (the RBC HVD; vascular ring bioassay). Results: Compared to age- and gender-matched healthy controls, COVID-19 subjects demonstrated 1) significant hematological differences (increased WBC count-with a higher percentage of neutrophils); RBC distribution width (RDW); and reduced hematocrit (HCT), Hb concentration, mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC); 2) impaired O2-carrying capacity and O2 capacitance (resulting from anemia) without difference in p50 or Hb-O2 cooperativity; 3) compromised regulation of RBC volume (altered osmotic fragility); 4) reduced RBC deformability; 5) accelerated RBC aggregation kinetics; and (6) no change in the RBC HVD reflex. Discussion: When considered collectively, homeostatic compensation for these RBC impairments requires that the cardiac output in the COVID cohort would need to increase by ∼135% to maintain O2 delivery similar to that in the control cohort. Additionally, the COVID-19 disease RBC properties were found to be exaggerated in blood-type O hospitalized COVID-19 subjects compared to blood-type A. These data indicate that altered RBC features in hospitalized COVID-19 subjects burden the cardiovascular system to maintain O2 delivery homeostasis, which appears exaggerated by blood type (more pronounced with blood-type O) and likely plays a role in disease pathogenesis.

Increased Levels of IFN-γ, PAI-1, and NT-proBNP are Associated with the Occurrence of Hypoxemia in COVID-19

BACKGROUND: Acute respiratory distress syndrome (ARDS) is one of the severe complications of Coronavirus disease 2019 (COVID-19) that can lead to the occurrence of hypoxemia. Hypoxemia occurs due to the role of pro-inflammatory cytokines and coagulation factors. Several studies have shown that interferon (IFN)-γ, plasminogen activator inhibitor 1 (PAI-1) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are biological markers that can be used to evaluate the severity and prognosis of the disease in severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection. This study was conducted to evaluate the association between IFN-γ, PAI-1, NT-proBNP and hypoxemia in COVID-19 patients.METHODS: This was a cross-sectional study of COVID-19 subjects with hypoxemia. Hypoxemia assessment was performed based on arterial blood gas analysis. IFN-γ and PAI-1 were measured with ELISA, while NT-proBNP levels were measured with Roche NT-proBNP.RESULTS: Fifty-five COVID-19 subjects with hypoxemia were observed. Thirty subjects experiencing moderate to severe hypoxemia and 25 with mild hypoxemia. Levels of IFN-γ, PAI-1, and NT-proBNP were higher in COVID-19 subjects with moderate to severe hypoxemia compared to those with mild hypoxemia (261.14 (121-348.60) pg/mL vs. 145.50 (59.90-348.60) pg/mL, p<0.001; 5.47 (3.50-8.50) pg/mL vs. 3.40 (2.20-9.30) pg/mL, p<0.001; 760 (112-34,066) pg/mL vs. 71 (48-364) pg/mL, p<0.001).CONCLUSION: Elevated levels of IFN-γ, PAI-1, and NT-proBNP are associated with hypoxemia in COVID-19 patients, suggesting that these markers may be useful in assessing hypoxemia in COVID-19 patients.KEYWORDS: IFN-γ, PAI-1, NT-proBNP, hypoxemia, COVID-19

Correlation of iron and related factors with disease severity and outcomes and mortality of patients with Coronavirus disease 2019

BackgroundIron is a trace element that possesses immunomodulatory properties and modulates the proneness to the course and outcome of a diverse viral diseases. This study intended to investigate the correlation of different iron-related factors with disease severity and outcomes as well as the mortality of coronavirus disease 2019 (COVID-19) patients. MethodsBlood serum samples were obtained from 80 COVID-19 cases and 100 healthy controls. Concentrations of ferritin, transferrin, total iron binding capacity (TIBC) was measured by Enzyme-linked immunosorbent assay (ELISA) and iron level was measured by immunoturbidometric method. ResultsConcentrations of iron, transferrin, and TIBC were low, while ferritin level was high in the COVID-19 cases in comparison to controls. In non-survivor (deceased) patients as well as severe subjects, the levels of iron, ferritin, transferrin, and TIBC were significantly different than survivors (discharged) and mild cases. Significant correlations were found between iron and related factors and the clinicopathological features of the patients. Based on ROC curve analysis, iron, ferritin, transferrin, and TIBC had potential to estimate disease severity in COVID-19 subjects. ConclusionIron metabolism is involved in the pathogenesis of COVID-19. Iron and related factors correlate with disease outcomes and might serve as biomarker in diagnosis of the disease severity and estimation of mortality in the COVID-19 subjects.

Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of Coronavirus Disease 2019 Recovery.

Conventional whole-body static 18F-FDG PET imaging provides a semiquantitative evaluation of overall glucose metabolism without insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods: The study included 13 healthy subjects and 12 recovering COVID-19 subjects within 8 wk of confirmed diagnosis. Each subject had a 1-h dynamic 18F-FDG scan on the uEXPLORER total-body PET/CT system. Semiquantitative SUV and the SUV ratio relative to blood (SUVR) were calculated for different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify the microparametric blood-to-tissue 18F-FDG delivery rate [Formula: see text] and the phosphorylation rate k 3, as well as the macroparametric 18F-FDG net influx rate ([Formula: see text]). Statistical tests were performed to examine differences between healthy subjects and recovering COVID-19 subjects. The effect of COVID-19 vaccination was also investigated. Results: We detected no significant difference in lung SUV but significantly higher lung SUVR and [Formula: see text] in COVID-19 recovery, indicating improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k 3 but not with [Formula: see text], which suggests that glucose phosphorylation, rather than glucose delivery, drives the observed difference of glucose metabolism. Meanwhile, there was no or little difference in bone marrow 18F-FDG metabolism measured with SUV, SUVR, and [Formula: see text] but a significantly higher bone marrow [Formula: see text] in the COVID-19 group, suggesting a difference in glucose delivery. Vaccinated COVID-19 subjects had a lower lung [Formula: see text] and a higher spleen [Formula: see text] than unvaccinated COVID-19 subjects. Conclusion: Higher lung glucose metabolism and bone marrow glucose delivery were observed with total-body multiparametric 18F-FDG PET in recovering COVID-19 subjects than in healthy subjects, implying continued inflammation during recovery. Vaccination demonstrated potential protection effects. Total-body multiparametric PET of 18F-FDG can provide a more sensitive tool and more insights than conventional whole-body static 18F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.

Increasing Levels of Macrophage Migration Inhibitory Factor in COVID-19 Infection and Its Pathophysiological Role; Cut-off Value Determination Might Be Clinically Misleading

Background: The serious outbreak of coronavirus disease 2019 (COVID-19) has provoked deep concern throughout the world. The pathophysiologic network leading to severe conditions has still unsolved gaps. Considered a pleiotropic, multifaceted cytokine, macrophage migration inhibitory factor (MIF) has distinct functions, which seem to stand at the edge of distinct known mechanisms involving in COVID-19 pathogenesis. Additionally, MIF is a key mediator of acute respiratory distress syndrome and lung injury. Objectives: The current study aimed to evaluate the serum levels of MIF in COVID-19 patients, particularly in severe cases. Methods: This case control study was performed on the sera of 60 randomly selected COVID-19 patients as case group and 30 randomly selected healthy individuals as control group during November 2020 till April 2021 at Mashhad University of Medical Sciences. The case group included 30 outpatients with mild disease and 30 hospitalized severe subjects. A commercial enzyme-linked immunosorbent assay was utilized to measure serum MIF. Data were analyzed using SPSS version 16 with student t-test and chi-squared test considering a P < 0.05 as statistical significance level. Results: There was no statistical difference between two groups regarding demographic variables. According to the obtained data, significantly higher MIF levels were observed in the affected subjects than the healthy individuals, particularly in severe COVID-19 subjects (severe: 65.31 ± 6.2 ng/mL, mild: 40.45 ± 6.6 ng/mL, healthy: 20.63 ± 6.1 ng/mL P < 0.0001). The receiver operating characteristic (ROC curve) drawn for the present study illustrates that MIF amounts differentiate COVID-19 severe and mild cases with high accuracy (90.8%) (sensitivity:86.6%, specificity:96.6%). Conclusions: There might be an association between MIF concentration with respiratory failure and disease exacerbation due to COVID-19 infection. Therefore, MIF can act as a marker of clinical severity for COVID 19 infection. However, due to variations in MIF amounts a definite cut-off value might be specific to the study and should be considered with caution. MIF is supposed to be one of the most important cytokines in COVID-19 pathogenesis and might be a target for therapeutic approaches with MIF inhibitors in possible upcoming disease peaks.

Activation of Inflammasome complex in nasopharyngeal epithelial cells from patients with Coronavirus disease 2019 contributes to inflammatory state and worse disease outcomes.

Pathogenesis of Coronavirus disease 2019 (COVID-19) has been associated with dysregulation of both adaptive and innate immune systems. Hence, we determined the contribution of inflammasome in the nasopharyngeal epithelial cells isolated from COVID-19 subjects to disease pathogenesis and outcomes. Epithelial cells from 150 COVID-19 patients and 150 healthy controls were yielded through nasopharyngeal swab sampling. Patients were categorized into three groups of those with clinical presentations/need hospitalization, with clinical presentations/no need hospitalization and cases without clinical symptoms/no need hospitalization. Finally, the transcriptional amount of inflammasome related genes were assessed in the nasopharyngeal epithelial cells using qPCR. There was a significant upregulation of nod-like receptor (NLR) family pyrin domain containing 1 (NLRP1), nod-like receptor (NLR) family pyrin domain containing 3 (NLRP3), Apoptosis-associated speck-like protein containing a CARD (ASC) and Caspase-1 mRNA expressions in patients compared to controls. NLRP1, NLRP3, ASC and Caspase-1 were upregulated in epithelial cells of patients with clinical symptoms/need hospitalization and cases with clinical symptoms/no need hospitalization when compared to controls. There was a correlation between expression of inflammasome-related genes and clinicopathological features. Abnormal expression of inflammasome-related genes in the nasopharyngeal epithelial cells obtained from COVID-19 patients may be of prognostic value to determine the intensity of the disease's outcomes and requirement for alternative supports in hospitals.

Serum homocysteine level and severity of coronavirus disease-2019 (COVID-19).

Coronavirus disease-2019 (COVID-19) is still a global health problem nowadays. A particular COVID-19 patients develop severe symptoms. Some biomarkers can be used to determine disease severity and improve outcome. Homocysteine is one of the novel biomarkers. The objective of this study is to determine the role of serum homocysteine level in stratifying severity of COVID-19. A cross-sectional study was conducted in Medan, Indonesia from May to December 2021. Subjects were obtained using consecutive sampling method. Inclusion criteria was COVID-19 patients aged 18 years or older and willing to participate in the study. Patients with malignancy, chronic kidney disease, thyroid disease, coronary heart disease, and who consume several medications including cholestyramine, metformin, methotrexate, fibrate, and contraceptive pill, were excluded. Data regarding demographic, laboratory, and biomarker were gathered from each subject. Statistical analyses were conducted at 95% confidence interval. A total of 100 patients were enrolled. Most subjects were males (59%) and from Batak ethnicity (64%). Twenty percent subjects had severe COVID-19. The levels of serum high-sensitivity C-reactive protein (hs-CRP), D dimer, homocysteine, and procalcitonin were significantly higher in severe COVID-19 subjects. D dimer had the highest sensitivity (91.7%) and specificity (94.7%) in stratifying severe COVID-19, followed by hs-CRP (91.7% and 85.5%, respectively), homocysteine (87.5% and 78.9%, respectively), and procalcitonin (58.3% and 74.0%, respectively). Homocysteine can be used as a biomarker to determine COVID-19 severity.

Multi-center Integrating Radiomics, Structured Reports, and Machine Learning Algorithms for Assisted Classification of COVID-19 in Lung Computed Tomography.

To evaluate the classification performance of structured report features, radiomics, and machine learning (ML) models to differentiate between Coronavirus Disease 2019 (COVID-19) and other types of pneumonia using chest computed tomography (CT) scans. Sixty-four COVID-19 subjects and 64 subjects with non-COVID-19 pneumonia were selected. The data was split into two independent cohorts: one for the structured report, radiomic feature selection and model building (n = 73), and another for model validation (n = 55). Physicians performed readings with and without machine learning support. The model's sensitivity and specificity were calculated, and inter-rater reliability was assessed using Cohen's Kappa agreement coefficient. Physicians performed with mean sensitivity and specificity of 83.4 and 64.3%, respectively. When assisted with machine learning, the mean sensitivity and specificity increased to 87.1 and 91.1%, respectively. In addition, machine learning improved the inter-rater reliability from moderate to substantial. Integrating structured reports and radiomics promises assisted classification of COVID-19 in CT chest scans.

Diarrhea and Coronavirus Disease 2019 Infection.

The global coronavirus disease-2019 (COVID-19) pandemic has caused significant morbidity and mortality, thoroughly affected daily living, and caused severe economic disruption throughout the world. Pulmonary symptoms predominate and account for most of the associated morbidity and mortality. However, extrapulmonary manifestations are common in COVID-19 infections, including gastrointestinal (GI) symptoms, such as diarrhea. Diarrhea affects approximately 10% to 20% of COVID-19 patients. Diarrhea can occasionally be the presenting and only COVID-19 symptom. Diarrhea in COVID-19 subjects is usually acute but is occasionally chronic. It is typically mild-to-moderate and nonbloody. It is usually much less clinically important than pulmonary or potential thrombotic disorders. Occasionally the diarrhea can be profuse and life-threatening. The entry receptor for COVID-19, angiotensin converting enzyme-2, is found throughout the GI tract, especially in the stomach and small intestine, which provides a pathophysiologic basis for local GI infection. COVID-19 virus has been documented in feces and in GI mucosa. Treatment of COVID-19 infection, especially antibiotic therapy, is a common culprit of the diarrhea, but secondary infections including bacteria, especially Clostridioides difficile, are sometimes implicated. Workup for diarrhea in hospitalized patients usually includes routine chemistries; basic metabolic panel; and a complete hemogram; sometimes stool studies, possibly including calprotectin or lactoferrin; and occasionally abdominal CT scan or colonoscopy. Treatment for the diarrhea is intravenous fluid infusion and electrolyte supplementation as necessary, and symptomatic antidiarrheal therapy, including Loperamide, kaolin-pectin, or possible alternatives. Superinfection with C difficile should be treated expeditiously. Diarrhea is prominent in post-COVID-19 (long COVID-19), and is occasionally noted after COVID-19 vaccination. The spectrum of diarrhea in COVID-19 patients is presently reviewed including the pathophysiology, clinical presentation, evaluation, and treatment.

Evaluation of Serum Humanin and MOTS-c Peptide Levels in Patients with COVID-19 and Healthy Subjects.

Coronavirus Disease 2019 (COVID-19) is a life-threatening and persistent pandemic with high rates of mortality and morbidity. Although a dysfunction in the mitochondria occurs in COVID-19 pathogenesis, the contribution of mitochondrial-derived peptides to its pathophysiology has not yet been completely elucidated. The goals of this research were to assess the circulating humanin and mitochondrial open reading frame of the 12S rRNA-c (MOTS-c) levels in COVID-19 patients and explore the effects of antiviral drug therapy on these peptide levels. Thirty adult COVID-19 patients and 32 gender-matched healthy volunteers were enrolled in this study. Circulating humanin and MOTS-c levels were detected using the ELISA method during pretreatment (before drug therapy) and post-treatment (on the 7th day of drug therapy). We found that there was significant attenuation of the serum humanin levels in COVID-19 patients (P < 0.001). However, we detected a significant augmentation in serum MOTS-c levels when compared to controls (P < 0.01 for pre-treatment and P < 0.001 for post-treatment). Interestingly, antiviral drug therapy did not modify the serum MOTS-c and humanin levels. Our findings suggest that MOTS-c and humanin were involved in the COVID-19 pathogenesis. Our data may also imply that elevated MOTS-c could act as a compensatory mechanism to eliminate the effects of decreased humanin levels.

Parameters and Morphological Changes of Erythrocytes and Platelets of COVID-19 Subjects: A Longitudinal Cohort Study.

Information about dynamic changes occurring in the parameters and morphology of erythrocytes and platelets during the coronavirus disease 2019 (COVID-19) infection and convalescence is scarce. To explore potential associations between dynamic erythrocyte and platelet parameters, morphological changes, and the course or severity of the disease is essential. From January 17th, 2020, to February 20th, 2022, we followed up on 35 patients with non-severe and 11 patients with severe COVID-19 following their discharge. We collected clinical features, dynamic complete blood count (CBC), and peripheral blood smears (PBS) and analyzed parameter and morphological changes of erythrocytes and platelets depending on the course or severity of the disease. The course of the disease included four periods, namely onset (T1), discharge (T2), 1-year follow-up (T3), and 2-year follow-up (T4). Red blood cell (RBC) counts and hemoglobin were the lowest in T2, followed by T1, and lower in T1 and T2 than in T3 and T4. Inversely, the red blood cell distribution width (RDW) was the highest in T2, followed by T1, and higher than in T3 and T4. Compared to non-severe patients, the platelet of severe patients was lower in T1 and T2. In contrast, the mean platelet volume (MPV) and platelet distribution width (PDW) tended to be higher in severe patients. Similarly, anisocytosis was more common in peripheral blood smears at early stages and in severe patients. Finally, large platelets were more common in severe patients. Anisocytosis of erythrocytes and large platelets are found in patients with severe COVID-19, these changes may help primary hospitals to identify patients with a high risk of severe COVID-19 at an early stage.

Liver injury in COVID-19 patients with non-alcoholic fatty liver disease: an update.

The coronavirus disease 2019 (COVID-19) pandemic has revolutionized the priorities of the medical society worldwide. Although most patients infected with SARS-CoV-2 exhibit respiratory symptoms, other organs may also be involved, including the liver, often resulting in liver injury. Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, and its prevalence is expected to increase together with the epidemics of type 2 diabetes and obesity. Data about liver injury during COVID-19 are numerous, while overviews of this infection in patients with NAFLD, both in terms of respiratory and liver, are emerging. In this review, we summarise the current research focusing on COVID-19 in NAFLD patients and discuss the association between liver injury in COVID-19 subjects and non-alcoholic fatty liver disease.

A Comparison of Intubation and Airway Complications Between COVID-19 and Non-COVID-19 Critically Ill Subjects.

Introduction The number of subjects infected with the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the western hemisphere increased exponentially in the later months of 2020.With this increase in infection, the number of subjects requiring advanced ventilatory support increased concomitantly.We decided to compare the survival rates between coronavirus disease 2019 (COVID-19) subjects versus non-COVID-19 subjects undergoing intubation in the intensive care unit (ICU).We hypothesized that COVID-19 subjects would have lower rates of survival post-intubation. Methods We screened all subjects admitted to the adult critical care unit between January 2020and June 2020 to determine if they met the inclusion criteria.These subjects were required to be spontaneously ventilating upon admission and eventually required intubation.Subjects were selected from our electronic health record (EHR) system EPIC© (Epic Systems, Verona, WI) through a retrospectiveICU admission analysis.We identified and included 267 non-COVID-19 subjects and 56 COVID-19 subjects.Our primary outcome of interest was intubation-related mortality.We defined intubation mortality as unexpected death (within 48 hours of intubation).Our secondary outcomes were the length of stay in the ICU, length of time requiring ventilator support, and proportion of subjects requiring tracheostomy placement. Results Compared to non-coronavirus disease (COVID) subjects, COVID subjects were more likely to be intubated for acute respiratory distress.COVID subjects had longer stays in the ICU and longer ventilator duration than non-COVID subjects.COVID-positive subjects had a decreased hazard ratio for mortality (HR = 0.42, 95% CI: 0.20-0.87, P < 0.05) and increased chances of survival compared to non-COVID subjects. Conclusions We showed therates of intubation survival were no different between the COVID and non-COVID groups.We attribute this finding to intubation preparation, a multidisciplinary team approach, and having the most experienced provider lead the intubation process.

AdaD-FNN for Chest CT-Based COVID-19 Diagnosis

Coronavirus disease 2019 (COVID-19) generated a global public health emergency since December 2019, causing huge economic losses. To help radiologists strengthen their recognition of COVID-19 cases, we developed a computer-aided diagnosis system based on deep learning to automatically classify chest computed tomography-based COVID-19, Tuberculosis, and healthy control subjects. Our novel classification model AdaD-FNN sequentially transfers the trained knowledge of an FNN estimator to the next FNN estimator while updating the weights of the samples in the training set with a decaying learning rate. This model inhibits the network from remembering the noisy information and improves the learning of complex patterns in the hard-to-identify samples. Moreover, we designed a novel image preprocessing model F-U2MNet-C by enhancing the image features using fuzzy stacking and eliminating the interference factors using U2MNet segmentation. Extensive experiments are conducted on four publicly available datasets namely, TLDCA, UCSD-Al4H, SARS-CoV-2, TCIA, and the obtained classification accuracies are 99.52%, 92.96%, 97.86%, 91.97%. Our novel system gives out compelling performance for assisting COVID-19 detection when compared with 22 state-of-the-art methods. We hope to help link together biomedical research and artificial intelligence and to assist the diagnosis of doctors, radiologists, and inspectors at each epidemic prevention site in the real world.

Radiation Exposure and Lifetime Attributable Risk of Cancer Incidence and Mortality from Low- and Standard-Dose CT Chest: Implications for COVID-19 Pneumonia Subjects.

Since the novel coronavirus disease 2019 (COVID-19) outbreak, there has been an unprecedented increase in the acquisition of chest computed tomography (CT) scans. Nearly 616 million people have been infected by COVID-19 worldwide to date, of whom many were subjected to CT scanning. CT exposes the patients to hazardous ionizing radiation, which can damage the genetic material in the cells, leading to stochastic health effects in the form of heritable genetic mutations and increased cancer risk. These probabilistic, long-term carcinogenic effects of radiation can be seen over a lifetime and may sometimes take several decades to manifest. This review briefly describes what is known about the health effects of radiation, the lowest dose for which there exists compelling evidence about increased radiation-induced cancer risk and the evidence regarding this risk at typical CT doses. The lifetime attributable risk (LAR) of cancer from low- and standard-dose chest CT scans performed in COVID-19 subjects is also discussed along with the projected number of future cancers that could be related to chest CT scans performed during the COVID-19 pandemic. The LAR of cancer Incidence from chest CT has also been compared with those from other radiation sources, daily life risks and lifetime baseline risk.

A Multi-centric Evaluation of Deep Learning Models for Segmentation of COVID-19 Lung Lesions on Chest CT Scans

Background: Chest computed tomography (CT) scan is one of the most common tools used for the diagnosis of patients with coronavirus disease 2019 (COVID-19). While segmentation of COVID-19 lung lesions by radiologists can be time-consuming, the application of advanced deep learning techniques for automated segmentation can be a promising step toward the management of this infection and similar diseases in the future. Objectives: This study aimed to evaluate the performance and generalizability of deep learning-based models for the automated segmentation of COVID-19 lung lesions. Patients and Methods: Four datasets (2 private and 2 public) were used in this study. The first and second private datasets included 297 (147 healthy and 150 COVID-19 cases) and 82 COVID-19 subjects. The public datasets included the COVID19-P20 (20 COVID-19 cases from 2 centers) and the MosMedData datasets (50 COVID-19 patients from a single center). Model comparisons were made based on the Dice similarity coefficient (DSC), receiver operating characteristic (ROC) curve, and area under the curve (AUC). The predicted CT severity scores by the model were compared with those of radiologists by measuring the Pearson’s correlation coefficients (PCC). Also, DSC was used to compare the inter-rater agreement of the model and expert against that of 2 experts on an unseen dataset. Finally, the generalizability of the model was evaluated, and a simple calibration strategy was proposed. Results: The VGG16-UNet model showed the best performance across both private datasets, with a DSC of 84.23% ± 1.73% on the first private dataset and 56.61% ± 1.48% on the second private dataset. Similar results were obtained on public datasets, with a DSC of 60.10% ± 2.34% on the COVID19-P20 dataset and 66.28% ± 2.80% on a combined dataset of COVID19-P20 and MosMedData. The predicted CT severity scores of the model were compared against those of radiologists and were found to be 0.89 and 0.85 on the first private dataset and 0.77 and 0.74 on the second private dataset for the right and left lungs, respectively. Moreover, the model trained on the first private dataset was examined on the second private dataset and compared against the radiologist, which revealed a performance gap of 5.74% based on DSCs. A calibration strategy was employed to reduce this gap to 0.53%. Conclusion: The results demonstrated the potential of the proposed model in localizing COVID-19 lesions on CT scans across multiple datasets; its accuracy competed with the radiologists and could assist them in diagnostic and treatment procedures. The effect of model calibration on the performance of an unseen dataset was also reported, increasing the DSC by more than 5%.

Association of COVID-19 Real-Time Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Cycle Threshold Value With Surrogate Markers of Disease Severity.

Introduction The cycle threshold (Ct) value in real-time reverse transcription-polymerase chain reaction (RT-PCR) serves as a criterion to diagnose coronavirus disease 2019 (COVID-19) and is inversely proportional to viral load. Levels of inflammatory markers such as aspartate aminotransferase (AST), ferritin, D-dimer, high sensitivity C-reactive protein (hs-CRP), and lactate dehydrogenase (LDH) are used as quantitative measures of COVID-19 severity. We examined the association between these markers and Ct values. Methodology This retrospective data analysis included 400 patients with positive RT-PCR results for COVID-19 who were admitted to a tertiary care hospital. Clinical and biochemical data were accessed from the hospital information management system. Associations of clinical parameters and markers of disease severity (e.g., polymorph, AST, hs-CRP, D-dimer, LDH, and ferritin levels) with Ct values were assessed. Observations LDH, ferritin, D-dimer, and hs-CRP were found to be significantly higher in moderate and severe groups than in the mild COVID-19 group. AST, ferritin, and hs-CRP levels were also significantly higher in severe COVID-19 subjects, compared to moderate COVID-19 subjects.Ct values for the E (envelop) gene and ORF (open reading frame) 1b gene were found to be significantly higher in those with severe COVID-19. Polymorph counts in subjects with Ct values of 25 or higher were significantly increased, compared to those with Ct values under 30. LDH, D-dimer, and hs-CRP levels in subjects with Ct values over 30 were significantly lower than for those with Ct values under 30. Ferritin was the best independent predictor of non-survival in study subjects, with an area under the curve (AUC) of 85.5% (95% confidence interval = 73.2-95.9). The Ct value for the E gene had an AUC of 75.1%, and the ORF1b gene had an AUC of 64.5%. However, no significant correlation was detected between any parameter and Ct value. Conclusion Polymorph, LDH, ferritin, D-dimer, and hs-CRP levels were significantly elevated in subjects with low E gene Ct values. Also, these subjects were at risk of severe disease and fatality. Ct values for the E gene thus could serve as an early indicator for patients at risk of severe disease and death.

Association of the matrix metalloproteinases (MMPs) family gene polymorphisms and the risk of coronavirus disease 2019 (COVID-19); implications of contribution for development of neurological symptoms in the COVID-19 patients.

Seemingly, the Matrix metalloproteinases (MMPs) play a role in the etiopathogenesis of coronavirus disease 2019 (COVID-19). Here in this study, we determined the association of MMP9 rs3918242, MMP3 rs3025058, and MMP2 rs243865 polymorphisms with the risk of COVID-19, especially in those with neurological syndrome (NS). We enrolled 500 patients with COVID-19 and 500 healthy individuals. To genotype the target SNPs, the Real-time allelic discrimination technique was used. To determine serum levels of MMPs, Enzyme-linked immunosorbent assay (ELISA) was exerted. The MMP9 gene rs3918242 and MMP3 gene rs3025058 SNP were significantly associated with increased COVID-19 risk and susceptibility to COVID-19 with NS. The serum level of MMP-9 and MMP-3 was significantly higher in COVID-19 cases compared with the healthy controls. Serum MMP-9 and MMP-3 levels were also higher in COVID-19 subjects with NS in comparison to the healthy controls. The polymorphisms in MMP genes were not associated with serum level of MMPs. MMP9 and MMP3 gene polymorphisms increases the susceptibility to COVID-19 as well as COVID-19 with neurologic syndrome, but they probably have no role in the regulation of serum MMP-9 and MMP-3 levels.

A Retrospective Analysis of the Importance of Biochemical and Hematological Parameters for Mortality Prediction in COVID-19 Cases.

Introduction The recent coronavirus disease 2019 (COVID-19) pandemic has devastated the world's health and economy and has devastatingly affected social and emotional spheres. Although it was the older population who faced the worst, a good number of the younger population also lost their lives. It was very important to predict who will progress to the worst clinical outcome. Consequently, quick and accurate ways of forecasting mortality in COVID-19 cases are essential to save lives. In this study, 11 predictive parameters, namely, D-dimer, creatinine, C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), systemic inflammatory index (SII), platelet count, absolute neutrophil count (ANC), and absolute lymphocyte count (ALC), were studied for determining their significance as predictive parameters of mortality in COVID-19-affected patients. Methods We conducted a retrospective study of essential parameters, namely, D-dimer, creatinine, CRP, LDH, ferritin, NLR, PLR, SII, platelet count, ANC, and ALC, in confirmed COVID-19 cases for one year between 2020 and 2021. The medical information was obtained from the digital storage sources of the hospital. All cases were segregated into surviving and non-surviving cases. All parameters were collected, results were tabulated, and each individual parameter wasthen analyzed to see if it showed any significantdeviations in non-surviving cases and could help predict mortalities. Statistical analysis was conducted using the latest version of the Statistical Package for the Social Sciences(SPSS) software (IBM SPSS Statistics, Armonk, NY, USA). Results Each of the parameters was individuallystudied. D-dimer, creatinine, LDH, ferritin, CRP, NLR, PLR, SII, and ANC showed a statistically significant increase in non-surviving cases. Compared to surviving cases, ALC and platelets showed a statistically significant decrease in non-surviving instances. Conclusion All the studied parameters showed significant deviations in non-surviving cases and could help predict mortalities. This study also stresses the utility of readily available hematological ratios such as NLR and SII for prognosis in COVID-19 subjects.