Severity Of COVID-19 Pneumonia Research Articles

Early Use of Liraglutide for the Treatment of Acute COVID-19 Infection: An Open-Label Single-Center Phase II Safety Study with Biomarker Profiling.

Glucagon-like peptide-1 (GLP-1) agonists are an existing treatment option for patients with insulin-resistant states, which elicit further pleiotropic effects related to immune cell recruitment and vascular inflammation. GLP-1 agonists downregulate the cluster of differentiation 147 (CD147) receptor, one of several receptors for the SARS-CoV-2 spike protein that mediate viral infection of host cells. We conducted an open-label prospective safety and tolerability study including biomarker responses of the GLP-1 agonist Liraglutide, administered for 5 days as an add-on therapy to the standard of care within 48 h of presentation in a cohort of 13 patients hospitalized with COVID-19 pneumonia. Biomarker responses were compared in patients admitted to critical care and those not requiring critical care admission (non-critical group). Liraglutide (0.6 mg, subcutaneously) was well tolerated by all patients and all patients were alive 30 days after diagnosis. Plasma soluble CD147 levels were reduced in the non-critical patient group at day 5 in contrast to critical care-treated patients, who demonstrated an increase in soluble CD147 levels between day 0 and day 5. Patients with milder COVID-19 pneumonia severity also demonstrated improvement in echocardiographic parameters of right and left ventricular function, reduction in plasma Troponin levels, increased CD147 expression on T lymphocytes, and reduction in plasma IL-8. This first-in-disease use of the GLP-1 agonist Liraglutide demonstrates its safety and tolerability in an unselected cohort of patients hospitalized with COVID-19 pneumonia across a range of clinical severities.

Evaluation of COVID-19 Findings on Thoracic CT: Is There any Correlation with Age and Comorbidity?

Aim: To share insights gained from low-dose thoracic computed tomography (CT) findings of patients diagnosed with COVID-19. Additionally, we aimed to evaluate the correlation between the observed CT findings, CT severity index, patient age, and the presence of comorbid conditions. Material and Method: One hundred patients having a COVID-19 diagnosis were included in the study's sample. We meticulously reviewed the thoracic CT image characteristics, the lung severity index, and various clinical data related to the patients. The relationships between these factors were then analyzed to draw meaningful conclusions. Results: The study included 100 patients, consisting of 67 men and 33 women. Among these patients, 30 had at least one underlying comorbid condition, with hypertension being the most prevalent. CT scans were positive in 65 patients. Within this group, 60 patients (93.3%) exhibited ground-glass opacities (GGO), 27 patients (41.5%) showed signs of consolidation, 22 patients (33.8%) had both GGO and consolidation, and 8 patients (12.3%) displayed the crazy paving pattern. The total lung severity score (TLSS) ranged from 0 to 19, with mean score of 3.11±3.71. Each lung lobe was systematically evaluated for the extent of involvement. We found a statistically significant relationship indicating that increasing age correlated with higher grades of lung involvement. Furthermore, significant association was noted between presence of comorbidities and the lung involvement grades. Our analysis revealed a moderate positive correlation between CT lung involvement grade and patient age, alongside a weaker positive correlation between the lung involvement grade and comorbid conditions. Conclusion: CT imaging has proven to be important tool in managing patients suspected of or confirmed to have COVID-19. Notably, the CT lung severity grade was significantly elevated in patients over 65 years and those with comorbidities. These findings underscore the critical role that CT plays in evaluating and managing the severity of COVID-19 pneumonia.

Predicting the Severity of COVID-19 Pneumonia from Chest X-Ray Images: A Convolutional Neural Network Approach

This study addresses significant limitations of previous works based on the Brixia and COVIDGR datasets, which primarily provided qualitative lung injury scores and focused mainly on detecting mild and moderate cases. To bridge these critical gaps, we developed a unified and comprehensive analytical framework that accurately assesses COVID-19-induced lung injuries across four levels: Normal, Mild, Moderate, and Severe. This approach’s core is a meticulously curated, balanced dataset comprising 9,294 high-quality chest X-ray images. Notably, this dataset has been made widely available to the research community, fostering collaborative efforts and enhancing the precision of lung injury classification at all severity levels. To validate the framework’s effectiveness, we conducted an in-depth evaluation using advanced deep learning models, including VGG16, RegNet, DenseNet, MobileNet, EfficientNet, and Vision Transformer (ViT), on this dataset. The top-performing model was further enhanced by optimizing additional fully connected layers and adjusting weights, achieving an outstanding sensitivity of 94.38%. These results affirm the accuracy and reliability of the proposed solution and demonstrate its potential for broad application in clinical practice. Our study represents a significant step forward in developing AI-powered diagnostic tools, contributing to the timely and precise diagnosis of COVID-19 cases. Furthermore, our dataset and methodological framework hold the potential to serve as a foundation for future research, paving the way for advancements in the detection and classification of respiratory diseases with higher accuracy and efficiency.

Disruption of immune responses by type 1 diabetes exacerbates SARS-CoV-2 mediated lung injury.

COVID-19 commonly presents as pneumonia, with those most severely affected progressing to respiratory failure. Patient responses to SARS-CoV-2 infection are varied, with comorbidities acting as major contributors to varied outcomes. Focusing on one such major comorbidity, we assessed whether pharmacological induction of type 1 diabetes mellitus (T1DM) would increase the severity of lung injury in a murine model of COVID-19 pneumonia utilizing wild-type mice infected with mouse-adapted SARS-CoV-2. Hyperglycemic mice exhibited increased weight loss and reduced blood oxygen saturation in comparison with their euglycemic counterparts, suggesting that these animals indeed experienced more severe lung injury. Transcriptomic analysis revealed a significant impairment of the adaptive immune response in the lungs of diabetic mice compared with those of control. To expand the limited options available for tissue analysis due to biosafety restrictions, we also employed a new technique to digest highly fixed tissue into a single-cell suspension, originally designed for scRNA-Seq, which we then adapted for flow cytometric analysis. Flow immunophenotyping and scRNA-Seq confirmed impaired recruitment of T-cells into the lungs of T1DM animals. In addition, scRNA-Seq revealed a distinct, highly inflammatory macrophage profile in the diabetic cohort that correlates with the more severe infection these mice experienced clinically, allowing insight into a possible mechanism for this phenomenon. Recognizing the near certainty that respiratory viruses will continue to present significant public health concerns for the foreseeable future, our study provides key insights into how T1DM results in a much more severe infection and identifies possible targets to ameliorate comorbidity-associated severe disease.NEW & NOTEWORTHY We define the exacerbating effects of type 1 diabetes mellitus (T1DM) on COVID-19 pneumonia severity in mice. Hyperglycemic mice experienced increased weight loss and reduced oxygen saturation. Transcriptomic analysis revealed impaired immune responses in diabetic mice, while flow cytometry and single-cell RNA sequencing confirmed reduced T-cell recruitment and an inflammatory macrophage profile. In addition, we introduced a novel technique for tissue analysis, enabling flow cytometric analysis on highly fixed tissue samples.

Is using inhaled corticosteroid effective against COVID-19 pneumonia severity and mortality?

It is known that the use of inhaled corticosteroids increases the incidence of pneumonia in patients followed up with the diagnosis of chronic asthma and chronic obstructive pulmonary disease (COPD). This study aimed to investigate the contribution of inhaled steroid use to pneumonia severity and mortality in cases with COVID-19 pneumonia. The study is a retrospective, observational study. Among the cases admitted to the pandemic clinic, patients diagnosed with COVID-19 pneumonia were included. The plan was to compare cases who received and did not receive inhaled corticosteroids in terms of pneumonia severity and mortality. In order to define risk factors for mortality, univariate and multivariable negative binomial regression analyses were performed. In our study, it was observed that n= 540 (75%) cases did not receive inhaled corticosteroids (group 1), and 180 (25%) cases used inhaled corti costeroids (group 2). Group 1 and group 2 cases were compared in terms of pneumonia severity with no significant difference between the two groups (p= 0.11). Then, risk factors affecting mortality in all cases were examined with univariate analyses. Increasing age, applying mechanical ventilation, having severe pneumonia, having interstitial lung disease, and applying prone position were found to be statistically significant factors in mortality (p < 0.05). In conclusion, in our study, it was observed that the use of inhaled corticosteroids did not increase the severity of pneumonia and mortality. It was thought that the treatment they received could be continued when the patients treated with inhaled corticosteroids due to asthma and COPD had COVID-19 pneumonia.

Surfactant-derived protein type B: a new biomarker linked to respiratory failure and lung damage in mild to moderate SARS-CoV-2 pneumonia

BackgroundThe COVID-19 pandemic has led to significant concern due to its impact on human health, particularly through pneumonia-induced lung damage. Surfactant proteins A and D (SP-A and SP-D) are implicated in COVID-19 lung damage, but the role of surfactant protein B (SP-B) remains unclear.MethodsWe conducted a single-centre, prospective observational study involving 73 hospitalised COVID-19 pneumonia patients. SP-B levels were measured within 48 h of admission, alongside SP-A and SP-D in a subset. Clinical data were collected, and follow-up visits were conducted after 6 months.ResultsAt hospitalisation, circulating immature SP-B levels measured in 73 patients (median 26.31 arbitrary units (AU) (interquartile range 14.27–41.31)) correlated significantly with lung involvement (r=0.447, p&lt;0.001) and oxygen support requirement (p=0.005). SP-B levels did not predict mechanical ventilation or intensive care unit admission. SP-B decreased significantly (p&lt;0.001) from 25.53 AU (14.36–41.46) at the acute hospitalisation to 12.73 AU (9.12–20.23) at the 6-month follow-up, whereas SP-A and SP-D did not change significantly. Immature SP-B (but not SP-A and SP-D) was confirmed to be significantly associated with the need for oxygen support (n=26, 58%) during the hospitalisation (p&lt;0.05).ConclusionImmature SP-B emerges as a potential biomarker for COVID-19 pneumonia severity and prognosis. Its dynamic changes suggest utility in monitoring disease progression and long-term outcomes, despite limitations in predicting hard end-points. Larger studies are needed to validate these findings and understand the underlying mechanisms of surfactant protein dysregulation in COVID-19 pathogenesis.

Lipidomic and metabolomic changes in community-acquired and COVID-19 pneumonia

This prospective observational study compared the 1H NMR blood lipidomes and metabolomes of 71 patients with community-acquired pneumonia (CAP), 75 patients with COVID-19 pneumonia, and 75 healthy controls (matched by age and sex) to identify potential biomarkers and pathways associated with respiratory infections. Both pneumonia groups had comparable severity indices, including mortality, invasive mechanical ventilation, and intensive care unit admission rates. Patients with COVID-19 pneumonia exhibited more pronounced hypolipidemia, with significantly lower levels of total cholesterol and LDL-c compared to patients with CAP. Atherogenic lipoprotein subclasses (VLDL-cholesterol, IDL-cholesterol, IDL-triglyceride, and LDL-triglyceride/LDL-cholesterol) were significantly increased in severe cases of both pneumonia types, while lower HDL-c and small, dense HDL particles were associated with more severe illness. Both infected groups showed decreased esterified cholesterol and increased triglycerides, along with reduced phosphatidylcholine, lysophosphatidylcholine, PUFA, omega-3 fatty acids, and DHA. Additionally, infected patients had elevated levels of glucose, lactate, 3-hydroxybutyrate, and acetone, which are linked to inflammation, hypoxemia, and sepsis. Increased levels of branched-chain amino acids, alanine, glycine, and creatine, which are involved in energy metabolism and protein catabolism, were also observed. Neurotransmitter synthesis metabolites like histidine and glutamate were higher in infected patients, especially those with COVID-19. Notably, severe infections showed a significant decrease in glutamine, essential for lymphocyte and macrophage energy. The severity of COVID-19 pneumonia was also associated with elevated glycoprotein levels (glycoprotein A, glycoprotein B, and glycoprotein F), indicating an inflammatory state. These findings suggest that metabolomic and lipidomic changes in pneumonia are connected to bioenergetic pathways regulating the immune response.

The Impact of Pentraxin 3 Serum Levels and Angiotensin-Converting Enzyme Polymorphism on Pulmonary Infiltrates and Mortality in COVID-19 Patients.

The aim of this study was to examine the impact of the pentraxin 3 (PTX3) serum level and angiotensin-converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism on the severity of radiographic pulmonary infiltrates and the clinical outcomes of COVID-19. The severity of COVID-19 pulmonary infiltrates was evaluated within a week of admission by analyzing chest X-rays (CXR) using the modified Brixia (MBrixa) scoring system. The insertion (I)/deletion (D) polymorphism of the ACE gene and the serum levels of PTX3 were determined for all patients included in the study. This study included 80 patients. Using a cut-off serum level of PTX3 ≥ 2.765 ng/mL, the ROC analysis (AUC 0.871, 95% CI 0.787-0.954, p < 0.001) showed a sensitivity of 85.7% and specificity of 78.8% in predicting severe MBrixa scores. Compared to ACE I/I polymorphism, D/D polymorphism significantly increased the risk of severe CXR infiltrates, OR 7.7 (95% CI: 1.9-30.1), and p = 0.002. Significant independent predictors of severe CXR infiltrates include hypertension (OR 7.71), PTX3 (OR 1.20), and ACE D/D polymorphism (OR 18.72). Hypertension (OR 6.91), PTX3 (OR 1.47), and ACE I/I polymorphism (OR 0.09) are significant predictors of poor outcomes. PTX3 and ACE D/D polymorphism are significant predictors of the severity of COVID-19 pneumonia. PTX3 is a significant predictor of death.

Association of the C3953T (rs1143634) variant of the interleukin 1 beta gene with the features of a complicated course of COVID-19-associated pneumonia.

The pro-inflammatory cytokine IL-1 plays an important role in severe COVID-19. A change in IL-1 production may be associated with a mutation in the IL1Β gene. Our study analyzed the impact of the IL1Β gene variants (rs1143634) on disease progression in patients with severe COVID-19 pneumonia, taking into account treatment strategies. The study enrolled 117 patients with severe COVID-19 pneumonia. The IL1Β gene variants were identified using the polymerase chain reaction-restriction fragment length polymorphism method. In the group of patients, the following genotype frequencies were found based on the investigated rs1143634 variant of the IL1Β gene: CC-65.8%, CT-28.2%, and TT-6.0%. Our results showed that the group of patients with the T allele of the IL1Β gene had higher leukocyte counts (p = 0.040) and more pronounced lymphopenia (p = 0.007). It was determined that patients carrying the T allele stayed on ventilators significantly longer (p = 0.049) and required longer treatment with corticosteroids (p = 0.045). Identifying variants of the IL1Β gene can be used as a predictive tool for assessing the severity of COVID-19 pneumonia and tailoring personalized treatment strategies. Further research with a larger patient cohort is required to validate these findings.

Prognostic significance of the chemerin level in coronavirus disease 2019 patients.

Increased serum chemerin levels have been reported in several inflammatory diseases. Few studies have investigated the relationship between chemerin and clinical features of COVID-19. Thus, chemerin may modulate the development and progression of COVID-19. We compared the serum chemerin concentration between patients with and without SARS-CoV-2 infection and its association with the severity and prognosis of COVID-19 pneumonia. This is a prospective, single-center, cross-sectional study. We enrolled COVID-19 patients who presented to our tertiary hospital and healthy controls. The COVID-19 patients were conducted and the dates of symptom onset were recorded. After admission to the hospital and stabilization, blood samples were obtained for routine hemogram, biochemistry, and chemerin. The chemerin level was 37.93 ± 17.3 ng/mL in patients followed in the ICU, 29.41 ± 12.79 ng/mL in inpatients, 30.48 ± 10.86 ng/mL in outpatients, and 25.12 ± 9.82 ng/mL in healthy controls. The difference between patients treated in the ICU and healthy controls was significant (P < .001). The high-sensitivity C-reactive protein (hs-CRP), ferritin, procalcitonin (PCT), and D-dimer levels were significantly higher in the intensive care unit (ICU) group (P < .001). Moreover, the chemerin level of patients who died was significantly higher than that of those who survived (P < .001). The chemerin level was increased in COVID-19 patients and also increased with increasing disease severity. The chemerin level was higher in the COVID-19 patients than healthy controls and was significantly higher in patients who died compared to those who did not.

COVID-19 Vaccination Leads to Less Pneumonia at Chest CT

The study’s objective was to assess, using CT scans, the impact of vaccinations and booster shots on the severity of COVID-19 pneumonia. In this retrospective analysis, 210 Covid-19 patients were included. Within six weeks of receiving a COVID-19 diagnosis, every patient who was included had at least one CT scan and had received a full, partial, or no vaccination. Patients were separated in three groups. A 6-point scale called the Pneumonia Score was used to compare the severity of pneumonia across the three groups. Hypertension, CAD, DM and CKD were the most common comorbidities among all cases. Mean CRP in group I was 94.7±15.63 mg/dl, in group II mean CRP was 96.9±11.44 mg/dl and in group III mean CRP was 97.3±5.35 mg/dl. We found that severity of pneumonia score 5 was higher in group III in 16 (22.8%) as compared to group I in 4 (5.7%) and group II in 8 (11.4%) cases with p value 0.003. Hospital stays and ICU admission was also higher in non-vaccinated case with p value 0.004. Rate of mortality in group I was 7 (10%), in group II was 13 (18.6%) cases while in group III was 15 (21.4%) cases.

Predictive Value of RDW/PLT for Progression of COVID-19 Pneumonia: A Potential Biomarker for Disease Severity

Identifying reliable predictors for COVID-19 pneumonia progression is crucial for effective patient management. The purpose of this study is to evaluate the Red Cell Distribution Width to Platelet Ratio (RDW/PLT) as a potential predictive biomarker for the development of moderate to severe COVID-19 pneumonia. Conducting a retrospective analysis from August 2021 to March 2023, we categorized patients with moderate COVID-19 pneumonia at admission into different severity groups. The objective was to explore clinical and laboratory variables associated with disease progression. Fifty-three patients initially diagnosed with moderate COVID-19 were studied, of which 17 progressed to severe disease. Univariate logistic regression analyzed various factors, including age, PLT, RDW-SD, RDW/PLT, AST, ALB, CRP, and IL-6, evaluating their correlation (P &lt; 0.05) with higher odds ratios of a poor prognosis. To ascertain these factors’ predictive power, Receiver Operating Characteristic (ROC) curve analysis was used. Univariate logistic regression highlighted several factors associated with increased odds ratios for poor prognosis. Notably, RDW/PLT exhibited the highest predictive value (AUC: 0.925, 95% CI 0.858–0.991) among single parameters in predicting the risk of COVID-19 progression. This study underscores the potential of RDW/PLT as an accessible and cost-effective biomarker for determining COVID-19 pneumonia severity. The findings support its utility in risk stratification and clinical decision-making, offering valuable insights for effective patient management strategies.

Comparison of the Discrimination Performance of AI Scoring and the Brixia Score in Predicting COVID-19 Severity on Chest X-Ray Imaging: Diagnostic Accuracy Study.

The artificial intelligence (AI) analysis of chest x-rays can increase the precision of binary COVID-19 diagnosis. However, it is unknown if AI-based chest x-rays can predict who will develop severe COVID-19, especially in low- and middle-income countries. The study aims to compare the performance of human radiologist Brixia scores versus 2 AI scoring systems in predicting the severity of COVID-19 pneumonia. We performed a cross-sectional study of 300 patients suspected with and with confirmed COVID-19 infection in Jakarta, Indonesia. A total of 2 AI scores were generated using CAD4COVID x-ray software. The AI probability score had slightly lower discrimination (area under the curve [AUC] 0.787, 95% CI 0.722-0.852). The AI score for the affected lung area (AUC 0.857, 95% CI 0.809-0.905) was almost as good as the human Brixia score (AUC 0.863, 95% CI 0.818-0.908). The AI score for the affected lung area and the human radiologist Brixia score had similar and good discrimination performance in predicting COVID-19 severity. Our study demonstrated that using AI-based diagnostic tools is possible, even in low-resource settings. However, before it is widely adopted in daily practice, more studies with a larger scale and that are prospective in nature are needed to confirm our findings.

Association of Inflammatory Markers With Disease Progression and the Severity of COVID-19.

Introduction InDecember 2019, there was a massive outbreak of viral pneumonia, which had a high case fatality rate. Genetic sequencing of the virus showed similarity with severe acute respiratory syndrome coronavirus (SARS-CoV). It was later named novel coronavirus 2019 while the disease it caused was given the nomenclature of COVID-19. This deadly pneumonia outbreak was declared a pandemic by the World Health Organization (WHO). Aim To derive the strength of the correlation between blood levels of various inflammatory markers with the severity of COVID-19 pneumonia in patients affected with novel coronavirus 2019. Materials and methodology A prospective study was conducted on 300 confirmed cases of COVID-19 infection from August 2020 to July 2021 in SSG Hospital, Vadodara. Diagnosis of patients as confirmed cases of COVID-19 infection was done according to the WHO interim guidance for COVID-19. Their inflammatory markers were done for this study. All COVID-19-positive patients who had given negative consent for enrollment were excluded from the study. Patients were classified based on the severity of acute respiratory distress syndrome (ARDS). Comprehensive medical record information, encompassing biodata, clinical symptoms, comorbidities, and laboratory investigations, was systematically collected. Patients were given the standard treatment protocol as per guidelines. Patients were subjected to detailed investigations comprising complete blood counts and inflammatory markers like C-reactive protein (CRP), lactate dehydrogenase (LDH), serum ferritin, and D-dimer. Patients were further investigated by chest X-ray (posteroanterior view) or high-resolution computed tomography of the thorax. Results A total of 300 confirmed cases of COVID-19 infection were included in this study. Most of them were males (52%) with a mean age of 51 years and 48% were females with a mean age of 55 years. The majority of patients(40%) did not have ARDS, 23.3% of patients had mild, 16.7% of patients had moderate, and 20% of patients had severe ARDS. Higher CRP levels, serum ferritin, and serum D-dimer were significantly associated with the severity of COVID-19 infection as compared to those having no symptoms (p < 0.05). Increased levels were associated with severe clinical manifestations of COVID-19. The sensitivity of CRP is 69% and specificity is 100% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. The sensitivity of ferritin is 88% and specificity is 81% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. The sensitivity of D-dimer is 94% and specificity is 89% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. The sensitivity of LDH is 93% and specificity is 84% as a diagnostic marker for COVID-19 pneumonia in terms of ARDS. Conclusions Current evidence from our study showed that higher levels of inflammatory markers such as CRP, LDH, D-dimer, and ferritin are associated with the severity of COVID-19 in terms of ARDS and thus could be used as significant prognostic factors of the disease.These indicators might support clinical decisions to identify highfatality casesand poor diagnosis in the initial admission phase.

Investigating the Effect of Type II Diabetes on COVID-19 Pneumonia Severity Using Computed Tomography: A Comparative Analysis

The aim of this study was to determine the factors affecting the severity of COVID-19 pneumonia in patients with type 2 diabetes using computed tomography severity scores. Computed tomography findings and pneumonia scores of 136 patients with type 2 diabetes and 136 patients without diabetes (n=272) with positive polymerase chain reaction test between January 2020 and January 2021 were compared using the hospital information system. The number of patients with moderate and severe pneumonia was significantly higher in the type 2 diabetes group (p&lt;0.05). Pneumonia scores were significantly higher in type 2 diabetic patients older than 60 years (p&lt;0.05). No significant correlation was found between pneumonia scores and hemoglobin A1c (p=0.865) and fasting blood glucose (p=0.78). No negative effect of hypertension on pneumonia score was observed in diabetic patients. Pneumonia scores of diabetic patients with renal insufficiency were higher than those of diabetic patients aged &lt;60 years (P&lt;0.05). In conclusion, the present study results revealed that the severity of COVID-19 pneumonia in patients with type 2 diabetes is higher than in healthy subjects. However, there was no significant positive correlation between pneumonia severity, hyperglycemia, and hemoglobin A1c levels in patients with type 2 diabetes.

CT semi-quantitative score used as risk factor for hyponatremia in patients with COVID-19: a cross-sectional study.

Chest computed tomography (CT) is used to determine the severity of COVID-19 pneumonia, and pneumonia is associated with hyponatremia. This study aims to explore the predictive value of the semi-quantitative CT visual score for hyponatremia in patients with COVID-19 to provide a reference for clinical practice. In this cross-sectional study, 343 patients with RT-PCR confirmed COVID-19, all patients underwent CT, and the severity of lung lesions was scored by radiologists using the semi-quantitative CT visual score. The risk factors of hyponatremia in COVID-19 patients were analyzed and combined with laboratory tests. The thyroid function changes caused by SARS-CoV-2 infection and their interaction with hyponatremia were also analyzed. In patients with SARS-CoV-2 infection, the total severity score (TSS) of hyponatremia was higher [M(range), 3.5(2.5-5.5) vs 3.0(2.0-4.5) scores, P=0.001], implying that patients with hyponatremia had more severe lung lesions. The risk factors of hyponatremia in the multivariate regression model included age, vomiting, neutrophils, platelet, and total severity score. SARS-CoV-2 infection impacted thyroid function, and patients with hyponatremia showed a lower free triiodothyronine (3.1 ± 0.9 vs 3.7 ± 0.9, P=0.001) and thyroid stimulating hormone level [1.4(0.8-2.4) vs 2.2(1.2-3.4), P=0.038]. Semi-quantitative CT score can be used as a risk factor for hyponatremia in patients with COVID-19. There is a weak positive correlation between serum sodium and free triiodothyronine in patients with SARS-CoV-2 infection.

Severe acute respiratory syndrome Coronavirus-2 GenoAnalyzer and mutagenic anomaly detector using FCMFI and NSCE

In order to deepen our understanding of the virus and help guide the creation of efficient therapies, this study uses artificial intelligence tools to thoroughly explore the genetic sequences of the SARS-CoV-2 virus. The process starts by using the Fuzzy Closure Miner for Frequent Itemsets (FCMFI) on a large corpus of SARS-CoV-2 genomic sequences to reveal hidden patterns, including nucleotides base sequences, repeating motifs, and corresponding interchanges. Then, using the Nucleotide Sequence Comprehension Engine (NSCE) technique, we were able to precisely define the genomic areas for mutation analysis. Structured and unstructured proteins are both strongly impacted by virus mutations, with spike proteins that are linked to the severity of COVID-19 pneumonia being particularly affected. Notably, the Mutagenic Anomaly Detector shows a 65 % efficiency boost in computing genome mutation rates compared to conventional point mutation analysis, while GenoAnalyzer offers a remarkable 93.33 % improvement over existing approaches in recognizing common genomic sequence patterns. These results highlight the potential of FCMFI to reveal complex genomic patterns and significant insights in COVID-19 genetic sequences when combined with mutation analysis. The Mutagenic Anomaly Detector and GenoAnalyzer show promise for revealing hidden genomic patterns and precisely estimating the SARS-CoV-2 mutation rate.

Radiographic patterns and severity scoring of COVID-19 pneumonia in children: a retrospective study

BackgroundChest radiography (CXR) is an adjunct tool in treatment planning and monitoring of the disease course of COVID-19 pneumonia. The purpose of the study was to describe the radiographic patterns and severity scores of abnormal CXR findings in children diagnosed with COVID-19 pneumonia.MethodsThis retrospective study included children with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction test who underwent CXR at the arrival. The CXR findings were reviewed, and modified radiographic scoring was assessed.ResultsThe number of abnormal CXR findings was 106 of 976 (10.9%). Ground-glass opacity (GGO) was commonly found in children aged > 9 years (19/26, 73.1%), whereas peribronchial thickening was predominantly found in children aged < 5 years (25/54, 46.3%). Overall, the most common radiographic finding was peribronchial thickening (54/106, 51%). The lower lung zone (56/106, 52.8%) was the most common affected area, and there was neither peripheral nor perihilar predominance (84/106, 79.2%). Regarding the severity of COVID-19 pneumonia based on abnormal CXR findings, 81 of 106 cases (76.4%) had mild lung abnormalities. Moderate and severe lung abnormalities were found in 21 (19.8%) and 4 (3.8%) cases, respectively. While there were no significant differences in the radiographic severity scores among the various pediatric age groups, there were significant disparities in severity scores in the initial CXR and medical treatments.ConclusionsThis study clarified the age distribution of radiographic features across the pediatric population. GGO was commonly found in children aged > 9 years, whereas peribronchial thickening was predominant in children aged < 5 years. The lower lung zone was the most common affected area, and the high severity lung scores required more medical treatments and oxygen support.

Differences in the severity and mortality risk factors for patients hospitalized for COVID-19 pneumonia between the early wave and the very late stage of the pandemic.

Since China's dynamic zero-COVID policy is cancelled on December 7, 2022, the rapidly growing number of patients has brought a major public health challenge. This study aimed to assess whether there were differences in the severity and mortality risk factors for patients hospitalized for COVID-19 pneumonia between the early wave and the very late stage of the pandemic. A retrospective cross-sectional study was carried out using data from 223 hospitalized patients diagnosed with COVID-19 pneumonia during the Omicron surge in Xi'an People's Hospital (Xi'an Fourth Hospital) from December 8, 2022, to January 31, 2023. Univariable and multivariable logistic regression analyses were used to identify potential risk factors associated with the severity and mortality of COVID-19 pneumonia during the first wave of the pandemic after the dynamic zero-COVID policy was retracted. Differences in the severity and mortality risk factors were assessed at different stages of the pandemic, mainly from demographic, clinical manifestation, laboratory tests and radiological findings of patients on admission. The mean age of the 223 participants was 71.2 ± 17.4. Compared with the patients in the initial stage of the pandemic, the most common manifestation among patients in this study was cough (90.6%), rather than fever (79.4%). Different from the initial stage of the pandemic, older age, chest tightness, elevated neutrophil-to-lymphocyte ratio (NLR), decreased albumin (ALB) level and ground glass opacification (GGO) in radiological finding were identified as severity risk factors, instead of mortality risk factors for COVID-19 patients in the very late stage of the pandemic. Arterial partial pressure of oxygen/fraction of inspired oxygen (PaO2/FiO2) ≤300 mmHg, cardiovascular disease and laboratory findings including elevated levels of D-dimer, α-hydroxybutyrate dehydrogenase (α-HBDH), total bilirubin (TBIL), alanine aminotransferase (ALT), urea nitrogen (BUN), creatinine (CR), fasting blood glucose (FBG) and decreased platelet count (PLT) were still associated with mortality in the very late stage of the pandemic. Monitoring continuously differences in the severity and mortality risk factors for COVID-19 patients between different stages of the pandemic could provide evidence for exploring uncharted territory in the coming post-pandemic era.

Comparison of the computed tomography COVID-19 pneumonia severity scores in vaccinated and unvaccinated individuals without comorbidities

Aims: The aim of this study to investigate the effect of vaccines on pneumonia severity by comparing the computed tomography pneumonia scores of vaccinated and unvaccinated individuals with COVID-19 without known comorbidities. Methods: Between January 2020 and January 2022. A total of 270 patients, 133 vaccinated and 137 unvaccinated, with positive polymerase chain reaction test and without any significant co-morbidity were included in the study. Computed tomography pneumonia scores, demographic characteristics, and vaccination information were evaluated through the hospital’s electronic registry system. Results: Mean pneumonia scores of individuals vaccinated for 1 dose were higher than individuals vaccinated for 2 or more doses. The shortest duration of infection after vaccination was determined in the group with 1 dose of vaccine, and the longest in the group with 2 doses of vaccine. There was no significant difference between mean pneumonia scores of vaccinated and unvaccinated individuals (P &gt; 0.05). Pneumonia scores were found to be significantly lower in individuals over 70 years of age in vaccinated compared to unvaccinated individuals. A statistically significant positive correlation was found between the age of the patients and the pneumonia scores (Rho = 0.293). Conclusion: There is no significant difference in the pneumonia scores of vaccinated and unvaccinated Covid 19 pneumonia patients without comorbidities, except for patients over 70 years of age. There is a significant correlation between pneumonia score and age.