Severity Of COVID-19 Pneumonia Research Articles

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.

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.

Can Increased Carbon Dioxide Gradient be Used as a Sensitive Bio-marker for COVID-19 Pneumonia Severity: An Indian Study

Abstract Background: Acute respiratory distress syndrome caused by severe acute respiratory syndrome coronavirus 2, is a challenge to health-care system in the recent times. The nonavailability of specific treatment and rapid spread through aerosols has impacted the countries worldwide. Research on the subject is continuous, to understand the pathology and pathophysiology of the condition. In this regard, diagnosis of the disease, severity stratification and clinical prognostication helps the clinician to plan the management. Literature is silent on clinical biomarkers for this novel disease. Hence, a study was carried out to find out a suitable clinical biomarker for the disease. Methodology: The author carried out a retrospective analysis of the fatal case records of a tertiary center COVID intensive care unit to evaluate whether Carbon dioxide gradient can be used as an end-stage marker of COVID pneumonia. A record-based observational study was conducted and data were collected from the fatal case documents after an institutional ethical committee clearance. Results: A total of 42 fatal cases were analyzed. Carbon dioxide retention was found in more than 90% of cases and raised carbon dioxide gradient (&gt;5 mmHg) was found in more than 50% of cases. The average days of mechanical ventilation was 9 days and on average, after 5 days of ventilation patients developed raised carbon dioxide gradient. Conclusion: We conclude that raised carbon dioxide gradient may be chosen as an end-stage marker for COVID pneumonia though large group studies are recommended.

Effect of antiviral and immunomodulatory treatment on a cytokine profile in patients with COVID-19.

The severity of COVID-19 is associated with an elevated level of a variety of inflammatory mediators. Increasing evidence suggests that the Th17 response contributes to the severity of COVID-19 pneumonia, whereas Th22 response plays a regulatory role in SARS-CoV-2 infection. Two main types of available COVID-19 treatments are antivirals and immunomodulatory drugs; however, their effect on a cytokine profile is yet to be determined. This study aim to analyse a cytokine profile in peripheral blood from patients with COVID-19 (n=44) undergoing antiviral or/and immunomodulatory treatment and healthy controls (n=20). Circulating CD4+ and CD8+ T cells and their intracellular expression of IL-17A and IL-22 were assessed by flow cytometry. Initial results showed an overexpression of IL-17F, IL-17A, CCL5/RANTES, GM-CSF, IL-4, IL-10, CXCL-10/IP-10 and IL-6 in COVID-19 patients compared to healthy controls. Treatment with remdesivir resulted in a significant decline in concentrations of IL-6, IL-10, IFN-alpha and CXCL10/IP-10. Immunomodulatory treatment contributed to a significant downregulation of IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 as well as upregulation of IL-22 and IL-1 beta. A combination of an antiviral and immunomodulatory treatment resulted in a significant decrease in IL-17F, IL-10, IFN-alpha, CXCL10/IP-10 and B7-H3 levels as well as an increase in IL-17A and IL-1 beta. We found significantly higher percentage of both CD4+ and CD8+ T cells producing IL-17A and CD4+ T cells producing IL-22 in patients with COVID-19. Administration of antiviral or/and immunomodulatory treatment resulted in a significant downregulation of pro-inflammatory cytokine expression and an upregulation of T cell absolute counts in most cases, thus showing effectiveness of treatment in COVID-19. SARS-CoV-2 infection induced cytokine overexpression in hospitalized patients with COVID-19 as well as lymphopenia, particularly a decrease in CD4+ and CD8+ T cell counts. Moreover, despite the reduced counts of CD4+ and CD8+ T cells, both subsets showed overactivation and increased expression of IL-17A and IL-22, thus targeting Th17 response might alleviate inflammatory response in severe disease.

COVID-19 Severity Prediction from Chest X-ray Images Using an Anatomy-Aware Deep Learning Model.

The COVID-19 pandemic has been adversely affecting the patient management systems in hospitals around the world. Radiological imaging, especially chest x-ray and lung Computed Tomography (CT) scans, plays a vital role in the severity analysis of hospitalized COVID-19 patients. However, with an increasing number of patients and a lack of skilled radiologists, automated assessment of COVID-19 severity using medical image analysis has become increasingly important. Chest x-ray (CXR) imaging plays a significant role in assessing the severity of pneumonia, especially in low-resource hospitals, and is the most frequently used diagnostic imaging in the world. Previous methods that automatically predict the severity of COVID-19 pneumonia mainly focus on feature pooling from pre-trained CXR models without explicitly considering the underlying human anatomical attributes. This paper proposes an anatomy-aware (AA) deep learning model that learns the generic features from x-ray images considering the underlying anatomical information. Utilizing a pre-trained model and lung segmentation masks, the model generates a feature vector including disease-level features and lung involvement scores. We have used four different open-source datasets, along with an in-house annotated test set for training and evaluation of the proposed method. The proposed method improves the geographical extent score by 11% in terms of mean squared error (MSE) while preserving the benchmark result in lung opacity score. The results demonstrate the effectiveness of the proposed AA model in COVID-19 severity prediction from chest X-ray images. The algorithm can be used in low-resource setting hospitals for COVID-19 severity prediction, especially where there is a lack of skilled radiologists.

A deficient immune response to SARS-CoV-2 in the nasopharynx is associated with severe COVID-19 pneumonia

ObjectivesWe analyzed the expression of inflammatory and antiviral genes in the nasopharynx of SARS-CoV-2 infected patients and their association with the severity of COVID-19 pneumonia. MethodsWe conducted a cross-sectional study on 223 SARS-CoV-2 infected patients. Clinical data were collected from medical records, and nasopharyngeal samples were collected in the first 24 hours after admission to the emergency room. The gene expression of eight proinflammatory/antiviral genes (plasminogen activator urokinase receptor [PLAUR], interleukin [IL]-6, IL-8, interferon [IFN]-β, IFN-stimulated gene 15 [ISG15], retinoic acid-inducible gene I [RIG-I], C-C motif ligand 5 [CCL5], and chemokine C-X-C motif ligand 10 [CXCL10]) were quantified by real-time polymerase chain reaction. Outcome variables were: (i) pneumonia; (ii) severe pneumonia or acute respiratory distress syndrome. Statistical analysis was performed using multivariate logistic regression analyses. ResultsWe enrolled 84 mild, 88 moderate, and 51 severe/critical cases. High expression of PLAUR (adjusted odds ratio [aOR] = 1.25; P = 0.032, risk factor) and low expression of CXCL10 (aOR = 0.89; P = 0.048, protective factor) were associated with pneumonia. Furthermore, lower values of ISG15 (aOR = 0.88, P = 0.021), RIG-I (aOR = 0.87, P = 0.034), CCL5 (aOR = 0.73, P <0.001), and CXCL10 (aOR = 0.84, P = 0.002) were risk factors for severe pneumonia/acute respiratory distress syndrome. ConclusionAn unbalanced early innate immune response to SARS-CoV-2 in the nasopharynx, characterized by high expression of PLAUR and low expression of antiviral genes (ISG15 and RIG-I), and chemokines (CCL5 and CXCL10), was associated with COVID-19 severity.

Lung ultrasound score severity cut-off points in COVID-19 pneumonia. A systematic review and validating cohort

ObjectivesOur purpose was to establish different cut-off points based on the lung ultrasound score (LUS) to classify COVID-19 pneumonia severity. MethodsInitially, we conducted a systematic review among previously proposed LUS cut-off points. Then, these results were validated by a single-centre prospective cohort study of adult patients with confirmed SARS-CoV-2 infection. Studied variables were poor outcome (ventilation support, intensive care unit admission or 28-days mortality) and 28-days mortality. ResultsFrom 510 articles, 11 articles were included. Among the cut-off points proposed in the articles included, only the LUS>15 cut-off point could be validated for its original endpoint, demonstrating also the strongest relation with poor outcome (odds ratio [OR]=3.636, confidence interval [CI] 1.411–9.374). Regarding our cohort, 127 patients were admitted. In these patients, LUS was statistically associated with poor outcome (OR=1.303, CI 1.137–1.493), and with 28-days mortality (OR=1.024, CI 1.006–1.042). LUS>15 showed the best diagnostic performance when choosing a single cut-off point in our cohort (area under the curve 0.650). LUS≤7 showed high sensitivity to rule out poor outcome (0.89, CI 0.695–0.955), while LUS>20 revealed high specificity to predict poor outcome (0.86, CI 0.776–0.917). ConclusionsLUS is a good predictor of poor outcome and 28-days mortality in COVID-19. LUS≤7 cut-off point is associated with mild pneumonia, LUS 8–20 with moderate pneumonia and ≥20 with severe pneumonia. If a single cut-off point were used, LUS>15 would be the point which better discriminates mild from severe disease.

To Study the Correlation of Clinical Severity and Cytokine Storm in COVID-19 Pulmonary Embolism Patients by Using Computed Tomography Pulmonary Angiography (CTPA) Qanadli Clot Burden Scoring System.

Pulmonary embolism (PE) is a fatal form of venous thromboembolism (VTE), with an overall untreated mortality of up to 30%. Greater than 50% of patients with lower extremity proximal DVT have concurrent PE at presentation. VTE has been seen in up to one-third of patients with COVID-19 infections requiring intensive care unit (ICU) admission.The objective of this study is to determine the correlation between CT pulmonary angiography, pulmonary embolism clot burden, and the Qanadli scoring system with clinically severe COVID-19 pneumonia and cytokine storm. 153 COVID-19 hospitalized patients who underwent CT pulmonary angiography (CTPA) for likelyPE on pretest probability modified Wells criteriawere enrolled. COVID-19 pneumonia was classified as URTI (upper respiratory tract infection), mild, severe, and critical COVID pneumonia. For data analysis, we categorized into two groups: (1) the non-severe group included URTI and mild pneumonia, and (2) the severe group included severe and critical pneumonia. We used the Qanadli scoring system to assess the PE percentages of pulmonary vascular obstruction using CTPA. Results: 41.8% (64) of COVID-19 patients were diagnosed with pulmonary embolism (PE) on CTPA. The majority of 51.6% of pulmonary vascular occlusions using the Qanadli scoring system for pulmonary embolism were at segmental arterial levels. Out of 104 COVID-19 cytokine storm patients, 45 (43%)were associated with pulmonary embolism. Overall, a 25% (16) mortality rate wasobserved in COVID-19 patients with pulmonary embolism. The pathogenesis of hypercoagulability in COVID-19 may include direct endothelial cell invasion by the virus, microvascular inflammation, endothelial exocytosis, and endotheliitis. A meta-analysis of 71 studies to investigate the occurrence of PE on CTPA in COVID-19 patients found 48.6% in ICU settingsand 65.3% of patients have clots in the peripheral pulmonary vasculature. There is a significant correlation between pulmonary embolism and high clot burdenQanadli CTPA scores, as well as between the severity of COVID-19 pneumonia and mortality. The association between critically ill COVID-19 pneumonia and pulmonary embolism may result in higher mortality and a poor prognostic marker.

Artificial intelligence guided HRCT assessment predicts the severity of COVID-19 pneumonia based on clinical parameters

BackgroundThe purpose of the study was to compare the results of AI (artificial intelligence) analysis of the extent of pulmonary lesions on HRCT (high resolution computed tomography) images in COVID-19 pneumonia, with clinical data including laboratory markers of inflammation, to verify whether AI HRCT assessment can predict the clinical severity of COVID-19 pneumonia.MethodsThe analyzed group consisted of 388 patients with COVID-19 pneumonia, with automatically analyzed HRCT parameters of volume: AIV (absolute inflammation), AGV (absolute ground glass), ACV (absolute consolidation), PIV (percentage inflammation), PGV (percentage ground glass), PCV (percentage consolidation). Clinical data included: age, sex, admission parameters: respiratory rate, oxygen saturation, CRP (C-reactive protein), IL6 (interleukin 6), IG - immature granulocytes, WBC (white blood count), neutrophil count, lymphocyte count, serum ferritin, LDH (lactate dehydrogenase), NIH (National Institute of Health) severity score; parameters of clinical course: in-hospital death, transfer to the ICU (intensive care unit), length of hospital stay.ResultsThe highest correlation coefficients were found for PGV, PIV, with LDH (respectively 0.65, 0.64); PIV, PGV, with oxygen saturation (respectively − 0.53, -0.52); AIV, AGV, with CRP (respectively 0.48, 0.46); AGV, AIV, with ferritin (respectively 0.46, 0.45). Patients with critical pneumonia had significantly lower oxygen saturation, and higher levels of immune-inflammatory biomarkers on admission. The radiological parameters of lung involvement proved to be strong predictors of transfer to the ICU (in particular, PGV ≥ cut-off point 29% with Odds Ratio (OR): 7.53) and in-hospital death (in particular: AIV ≥ cut-off point 831 cm3 with OR: 4.31).ConclusionsAutomatic analysis of HRCT images by AI may be a valuable method for predicting the severity of COVID-19 pneumonia. The radiological parameters of lung involvement correlate with laboratory markers of inflammation, and are strong predictors of transfer to the ICU and in-hospital death from COVID-19.Trial registrationNational Center for Research and Development CRACoV-HHS project, contract number SZPITALE-JEDNOIMIENNE/18/2020.

NOS3 (rs61722009) gene variants testing in prediction of COVID-19 pneumonia severity

BackgroundThere is a hypothesis that a sufficient level of endothelial nitric oxide synthase is important for reliable protection against COVID-19. Theoretical ideas about the NOS3 gene demonstrated that it can have an effect on links of the complications pathogenesis in COVID-associated pneumonia. We determined the goal – to investigate the association of the NOS3 gene variants with the occurrence of the disease and its clinical course in patients of the intensive care unit. MethodsThe study group included 117 patients with a diagnosis of severe “viral COVID-19 pneumonia”. Determination of NOS3 gene variants was performed using the PCR method. The probability of differences in the quantitative results were determined using ANOVA or Kruskal-Wallis test (depend of normality of studied parameters). ResultsOur results indicate that the presence of the NOS3 gene 4a allele increase the risk of complicated COVID-19-associated pneumonia (χ2 = 18.84, p = 0.00001, OR = 3.53 (1.95–6.39)). It was showed, that carriers of the 4aa genotype had a significantly higher ratio of SpO2/FiO2 on the first and second days after hospitalization (p = 0.017 and p = 0.03, respectively). Patients with the 4aa genotype also had the acid-base imbalances, as showed by indicators of base deficiency and standard bicarbonate, which were beyond the reference values. Potassium and sodium concentrations on the first and second day after hospitalization were also significantly lower in patients with 4aa genotype (p = 0.009 and p = 0.048, respectively), for whom, in the same time, the concentrations of C-reactive protein and total bilirubin were significantly higher (p = 0.002 and p = 0.033, respectively). ConclusionsOur results confirmed that the rs61722009 variant of the NOS3 gene is associated with an increased risk of severe СOVID-19-associated pneumonia and its adverse clinical course with potential progression of kidney and liver damage, and occurrence risk of systemic inflammatory response syndrome. These results require further research for the new metabolic strategy formation, in order to prevent the severe COVID-19 associated pneumonia and its complications.

Neutrophil Lymphocyte Ratio (NLR) as a Prognostic Marker in COVID-19 Infection

Objectives: To determine the efficacy of Neutrophil/Lymphocyte ratio (NLR) as a marker of the severity of COVID-19 pneumonia. The neutrophilto-lymphocyte ratio (NLR) in peripheral blood has been studied as a systemic inflammatory marker and various studies have shown that it is a valid prognostic factor in various solid tumours and other chronic diseases such as lung, cardiovascular and kidney diseases. Emerging evidences suggested that peripheral blood neutrophil to lymphocyte ratio (NLR) can be used as a marker of systemic inflammation. Furthermore, NLR has shown good predictive values on progression and clinical outcomes in Covid-19 severity. Our study aims at evaluating whether NLR can help clinicians identify potentially severe cases early, conduct early triage and initiate effective management in time, which may reduce the overall mortality of COVID-19. Material and Methods: This was a retrospective study done from January 2021 to August 2021 in Breach candy hospital Mumbai. A group of 100 patients with confirmed COVID-19 infection hospitalised in our centre were retrospectively analysed. COVID-19 diagnosis was performed via RTPCR from nasopharyngeal and oropharyngeal swabs. For each patient, demographic data, clinical history, laboratory tests specially CBC and treatment measures during hospitalisation were collected. Results: NLR can be used to determine on disease severity and mortality in patients with COVID infection. Conclusion: Evaluating NLR can help clinicians identify potentially severe cases early, conduct early triage and initiate effective management in time, which may reduce the overall mortality of COVID-19.