scholarly journals Post-COVID-19 Patients Who Develop Lung Fibrotic-like Changes Have Lower Circulating Levels of IFN-β but Higher Levels of IL-1α and TGF-β

Biomedicines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1931
Author(s):  
Chiara Colarusso ◽  
Angelantonio Maglio ◽  
Michela Terlizzi ◽  
Carolina Vitale ◽  
Antonio Molino ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Ct Scan ◽  
Plasma Levels ◽  
Lung Fibrosis ◽  
Pharyngeal Swab ◽  
Reactive Protein ◽  
Scan Data ◽  
Severity Of The Disease ◽  
Circulating Levels ◽  
Chest Ct Scan

Purpose: SARS-CoV-2 infection induces in some patients a condition called long-COVID-19, herein post-COVID-19 (PC), which persists for longer than the negative oral-pharyngeal swab. One of the complications of PC is pulmonary fibrosis. The purpose of this study was to identify blood biomarkers to predict PC patients undergoing pulmonary fibrosis. Patients and Methods: We analyzed blood samples of healthy, anti-SARS-CoV-2 vaccinated (VAX) subjects and PC patients who were stratified according to the severity of the disease and chest computed tomography (CT) scan data. Results: The inflammatory C reactive protein (CRP), complement complex C5b-9, LDH, but not IL-6, were higher in PC patients, independent of the severity of the disease and lung fibrotic areas. Interestingly, PC patients with ground-glass opacities (as revealed by chest CT scan) were characterized by higher plasma levels of IL-1α, CXCL-10, TGF-β, but not of IFN-β, compared to healthy and VAX subjects. In particular, 19 out of 23 (82.6%) severe PC and 8 out of 29 (27.6%) moderate PC patients presented signs of lung fibrosis, associated to lower levels of IFN-β, but higher IL-1α and TGF-β. Conclusions: We found that higher IL-1α and TGF-β and lower plasma levels of IFN-β could predict an increased relative risk (RR = 2.8) of lung fibrosis-like changes in PC patients.

scholarly journals Post-COVID-19 pulmonary fibrosis and its predictive factors: a prospective study

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Mehrdad Nabahati ◽  
Soheil Ebrahimpour ◽  
Reza Khaleghnejad Tabari ◽  
Rahele Mehraeen
Keyword(s):  
Pulmonary Fibrosis ◽  
Ct Scan ◽  
Predictive Factors ◽  
Lung Fibrosis ◽  
Chest Ct ◽  
Clinical Severity ◽  
Secondary Outcome ◽  
Increased Risk ◽  
Chest Ct Scan

Abstract Background We aimed to prospectively assess the lung fibrotic-like changes, as well as to explore their predictive factors, in the patients who survived Coronavirus Disease 2019 (COVID-19) infection. In this prospective cross-sectional study, we recruited patients who had been treated for moderate or severe COVID-19 pneumonia as inpatients and discharged from Rohani hospital in Babol, northern Iran, during March 2020. The clinical severity of COVID-19 pneumonia was classified as per the definition by World Health Organization. We also calculated the CT severity score (CSS) for all patients at admission. Within the 3 months of follow-up, the next chest CT scan was performed. As the secondary outcome, the patients with fibrotic abnormalities in their second CT scan were followed up in the next 3 months. Results Totally, 173 COVID-19 patients were finally included in the study, of whom 57 (32.9%) were male and others were female. The mean age was 53.62 ± 13.67 years old. At 3-month CT follow-up, evidence of pulmonary fibrosis was observed in 90 patients (52.0%). Consolidation (odds ratio [OR] = 2.84), severe disease (OR 2.40), and a higher CSS (OR 1.10) at admission were associated with increased risk of fibrotic abnormalities found at 3-month CT follow-up. Of 62 patients who underwent chest CT scan again at 6 months of follow-up, 41 patients (66.1%) showed no considerable changes in the fibrotic findings, while the rest of 21 patients (33.9%) showed relatively diminished lung fibrosis. Conclusion Post-COVID-19 lung fibrosis was observed in about half of the survivors. Also, patients with severe COVID-19 pneumonia were at a higher risk of pulmonary fibrosis. Moreover, consolidation, as well as a higher CSS, in the initial chest CT scan, was associated with increased risk of post-COVID-19 lung fibrosis. In addition, some patients experienced diminished fibrotic abnormalities in their chest CT on 6-month follow-up, while some others did not.

scholarly journals Correlations of CT scan with high-sensitivity C-reactive protein and D-dimer in patients with coronavirus disease 2019

2020 ◽  
Vol 36 (6) ◽  
Author(s):  
Jin Zhu ◽  
Cheng Chen ◽  
Rongshu Shi ◽  
Bangguo Li
Keyword(s):  
Ct Scan ◽  
High Sensitivity ◽  
Chest Ct ◽  
Ground Glass ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Group 2 ◽  
Chest Ct Scan ◽  
D Dimer ◽  
Group 1

Objectives: To study the correlations of CT scan with high-sensitivity C-reactive protein (hs-CRP) and D-dimer in patients with coronavirus disease 2019 (COVID-2019). Methods: From January to March 2020, COVID-19 patients were divided into two groups according to the Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (trial version 7), with mild and ordinary cases as Group-1 and critical and severe cases as Group-2. The chest CT scan results, hs-CRP, D-dimmer levels of the two groups from admission to discharge were compared by the c2 test or Fisher’s exact test. The quantitative data were represented as mean ± standard deviation (±s). Intergroup comparisons were performed by the independent samples t test, and the ineligible data were subjected to the nonparametric rank sum test. Binary logistic regression model was used for multivariate correlation analysis, using independent variables that were significant in univariate analysis. The correlations between the above indices were analyzed. Results: In Group-1, there were two cases of normal chest CT scan results, one case of fibrosis, and 25 cases of abnormalities during the first diagnosis, mainly manifested as single or scattered ground-glass shadows. After treatment, the CT scan results became normal. The chest CT scan of Group-2 showed abnormalities, including 21 cases of multiple ground-glass shadows, and six cases of multiple consolidations accompanied by ground-glass shadows, who were critically ill and died. In addition, there were 16 cases of multiple ground glass shadows with partial consolidation, and the CRP and D-dimer levels of Group-2 were significantly higher than those of Group-1. Chest CT scan results were significantly positively correlated with CRP and D-dimer levels (P<0.05). Conclusion: The chest CT scan results of COVID-19 patients are characteristic, being correlated with CRP and D-dimer levels. D-dimer and CRP levels significantly increase in most severe and critical patients, which are closely related to their prognosis. The indices may play predictive roles in clinical treatment and prognosis evaluation. doi: https://doi.org/10.12669/pjms.36.6.2961 How to cite this:Zhu J, Chen C, Shi R, Li B. Correlations of CT scan with high-sensitivity C-reactive protein and D-dimer in patients with coronavirus disease 2019. Pak J Med Sci. 2020;36(6):1397-1401. doi: https://doi.org/10.12669/pjms.36.6.2961 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

CNN-based Prediction of COVID-19 using Chest CT Images

2021 ◽  
pp. 2250039
Author(s):  
Tanvi Arora
Keyword(s):  
Ct Scan ◽  
Good Accuracy ◽  
Ct Images ◽  
Chest Ct ◽  
X Ray ◽  
Infected People ◽  
The World ◽  
Severity Of The Disease ◽  
Application Programs ◽  
Chest Ct Scan

The coronavirus disease (COVID-19) pandemic that is caused by the SARS-CoV2 has spread all over the world. It is an infectious disease that can spread from person to person. The severity of the disease can be categorized into five categories namely asymptomatic, mild, moderate, severe, and critical. From the reported cases thus, it has been seen that 80% of the cases that test positive with COVID-19 infection have less than moderate complications, whereas 20% of the positive cases develop severe and critical complications. The virus infects the lungs of an individual, therefore, it has been observed that the X-ray and computed tomography (CT) scan images of the infected people can be used by the machine learning-based application programs to predict the presence of the infection. Therefore, in the proposed work, a Convolutional Neural Network model based upon the DenseNet architecture is being used to predict the presence of COVID-19 infection using the CT scan images of the chest. The proposed work has been carried out using the dataset of the CT images from the COVID CT Dataset. It has 349 images marked as COVID-19 positive and 397 images have been marked as COVID-19 negative. The proposed system can categorize the test set images with an accuracy of 91.4%. The proposed method is capable of detecting the presence of COVID-19 infection with good accuracy using the chest CT scan images of the humans.

scholarly journals 538. The Role of N-acetylcysteine on Post Covid-19 Pulmonary Fibrosis

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S370-S371
Author(s):  
Bernard Demot ◽  
Kristin Ivan Mark Hizon
Keyword(s):  
Pulmonary Fibrosis ◽  
Ct Scan ◽  
Chest Ct ◽  
Ct Scans ◽  
Ground Glass ◽  
Nasopharyngeal Swab ◽  
High Dose ◽  
Pulmonary Consolidation ◽  
Chest Ct Scan

Abstract Background Covid 19 have long lasting complications, from myalgia, body weakness to life debilitating strokes, and pulmonary fibrosis. Several mechanisms had been described but mostly viral or autoimmune which causes damages which leads to Acute respiratory distress syndrome. There is no approved treatment as of this time. Antifibrotic drugs use had been limited due to hepatoxicity, on top of Covid 19 hepatopathy. This study aims to describe the role of N-acetylcysteine on Post COVID 19 pulmonary fibrosis as an alternative treatment. Methods Patients are admitted at Baguio General Hospital and Medical Center at the COVID wards. Patients are COVID confirmed by RT PCR nasopharyngeal swab. Patient who are classified as severe were given Dexamethasone, Enoxaparin and Remdesivir for 5-10 days. Patients who are not weaned off from O2 support underwent Chest CT scan. Patients with Extensive Fibrosis were then consented to undergo High Dose IV Infusion of N-acetylcysteine. (150mg/kg in 1st hour, 50mg/kg next 4 hours and 100mg/kg last 20 hours). Repeat Chest CT Scan was done. Results Peripheral Bilateral Ground Glass Opacities and Pulmonary Consolidation was seen on pre-treatment CT Scans. Repeat CT scans showed significant regression of Ground Glass Opacities and Pulmonary Consolidation. CT SCAN pre and post treatment Conclusion High dose N-acetylcysteine showed promising results on Post COVID 19 Pulmonary Fibrosis. Disclosures All Authors: No reported disclosures

scholarly journals AI-based multi-modal integration (ScanCov scores) of clinical characteristics, lab tests and chest CTs improves COVID-19 outcome prediction of hospitalized patients

2020 ◽  
Author(s):  
Nathalie Lassau ◽  
Samy Ammari ◽  
Emilie Chouzenoux ◽  
Hugo Gortais ◽  
Paul Herent ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ct Scan ◽  
Chest Ct ◽  
Biological Data ◽  
Learning Models ◽  
Prognostic Information ◽  
Radiology Reports ◽  
Early Predictors ◽  
Scan Data ◽  
Chest Ct Scan

The SARS-COV-2 pandemic has put pressure on Intensive Care Units, and made the identification of early predictors of disease severity a priority. We collected clinical, biological, chest CT scan data, and radiology reports from 1,003 coronavirus-infected patients from two French hospitals. Among 58 variables measured at admission, 11 clinical and 3 radiological variables were associated with severity. Next, using 506,341 chest CT images, we trained and evaluated deep learning models to segment the scans and reproduce radiologists’ annotations. We also built CT image-based deep learning models that predicted severity better than models based on the radiologists’ reports. Finally, we showed that adding CT scan information—either through radiologist lesion quantification or through deep learning—to clinical and biological data, improves prediction of severity. These findings show that CT scans contain novel and unique prognostic information, which we included in a 6-variable ScanCov severity score.

scholarly journals Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Nathalie Lassau ◽  
Samy Ammari ◽  
Emilie Chouzenoux ◽  
Hugo Gortais ◽  
Paul Herent ◽  
...  
Keyword(s):  
Deep Learning ◽  
Ct Scan ◽  
Learning Model ◽  
Ct Scans ◽  
Clinical Variables ◽  
Biological Variables ◽  
Severity Scores ◽  
Scan Data ◽  
Deep Learning Model ◽  
Chest Ct Scan

AbstractThe SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning model based on CT scans to predict severity. We then construct the multimodal AI-severity score that includes 5 clinical and biological variables (age, sex, oxygenation, urea, platelet) in addition to the deep learning model. We show that neural network analysis of CT-scans brings unique prognosis information, although it is correlated with other markers of severity (oxygenation, LDH, and CRP) explaining the measurable but limited 0.03 increase of AUC obtained when adding CT-scan information to clinical variables. Here, we show that when comparing AI-severity with 11 existing severity scores, we find significantly improved prognosis performance; AI-severity can therefore rapidly become a reference scoring approach.

Elevated Tissue Factor and Tissue Factor Pathway Inhibitor Circulating Levels in Ischaemic Heart Disease Patients

1998 ◽  
Vol 79 (03) ◽  
pp. 495-499 ◽  
Author(s):  
Anna Maria Gori ◽  
Sandra Fedi ◽  
Ludia Chiarugi ◽  
Ignazio Simonetti ◽  
Roberto Piero Dabizzi ◽  
...  
Keyword(s):  
Heart Disease ◽  
Ischaemic Heart Disease ◽  
Tissue Factor ◽  
Plasma Levels ◽  
Tissue Factor Pathway Inhibitor ◽  
Common Source ◽  
Previous Myocardial Infarction ◽  
Control Subjects ◽  
Tissue Factor Pathway ◽  
Circulating Levels

SummarySeveral studies have shown that thrombosis and inflammation play an important role in the pathogenesis of Ischaemic Heart Disease (IHD). In particular, Tissue Factor (TF) is responsible for the thrombogenicity of the atherosclerotic plaque and plays a key role in triggering thrombin generation. The aim of this study was to evaluate the TF/Tissue Factor Pathway Inhibitor (TFPI) system in patients with IHD.We have studied 55 patients with IHD and not on heparin [18 with unstable angina (UA), 24 with effort angina (EA) and 13 with previous myocardial infarction (MI)] and 48 sex- and age-matched healthy volunteers, by measuring plasma levels of TF, TFPI, Prothrombin Fragment 1-2 (F1+2), and Thrombin Antithrombin Complexes (TAT).TF plasma levels in IHD patients (median 215.4 pg/ml; range 72.6 to 834.3 pg/ml) were significantly (p<0.001) higher than those found in control subjects (median 142.5 pg/ml; range 28.0-255.3 pg/ml).Similarly, TFPI plasma levels in IHD patients were significantly higher (median 129.0 ng/ml; range 30.3-316.8 ng/ml; p <0.001) than those found in control subjects (median 60.4 ng/ml; range 20.8-151.3 ng/ml). UA patients showed higher amounts of TF and TFPI plasma levels (TF median 255.6 pg/ml; range 148.8-834.3 pg/ml; TFPI median 137.7 ng/ml; range 38.3-316.8 ng/ml) than patients with EA (TF median 182.0 pg/ml; range 72.6-380.0 pg/ml; TFPI median 115.2 ng/ml; range 47.0-196.8 ng/ml) and MI (TF median 213.9 pg/ml; range 125.0 to 341.9 pg/ml; TFPI median 130.5 ng/ml; range 94.0-207.8 ng/ml). Similar levels of TF and TFPI were found in patients with mono- or bivasal coronary lesions. A positive correlation was observed between TF and TFPI plasma levels (r = 0.57, p <0.001). Excess thrombin formation in patients with IHD was documented by TAT (median 5.2 μg/l; range 1.7-21.0 μg/l) and F1+2 levels (median 1.4 nmol/l; range 0.6 to 6.2 nmol/l) both significantly higher (p <0.001) than those found in control subjects (TAT median 2.3 μg/l; range 1.4-4.2 μg/l; F1+2 median 0.7 nmol/l; range 0.3-1.3 nmol/l).As in other conditions associated with cell-mediated clotting activation (cancer and DIC), also in IHD high levels of circulating TF are present. Endothelial cells and monocytes are the possible common source of TF and TFPI. The blood clotting activation observed in these patients may be related to elevated TF circulating levels not sufficiently inhibited by the elevated TFPI plasma levels present.

The Pathogenesis of Thrombotic Thrombocytopenic Purpura

1979 ◽  
Author(s):  
H. C. Kwaan
Keyword(s):  
Plasminogen Activator ◽  
Thrombotic Thrombocytopenic Purpura ◽  
Degradation Products ◽  
Vascular Lesions ◽  
Local Defect ◽  
Laboratory Findings ◽  
Thrombocytopenic Purpura ◽  
Fibrin Degradation Products ◽  
Severity Of The Disease ◽  
Circulating Levels

The vascular lesions with microthrombi were studied in 12 patients with thrombotic thrombocytopenic purpura (TTP), diagnosed by the characteristic clinical and laboratory findings and confirmed histologically in each case. While defibrination was not observed, and with only minimal changes in the circulating levels of fibrinogen, fibrin degradation products and plasminogen activator, the microthrombotic lesion was invariably present. Immunofluorescent and histochemical studies indicated that both platelet and fibrin were present in the microthrombi with the platelet components dominant in many cases. Using the fibrin slide method, plasminogen activator was demonstrated in the uninvolved blood vessels but totally absent in the vessels occluded by microthrombi. in contrast, fibrinolysis is always present in the vessels afflicted with other types of thrombosis, such as the microthrombi in disseminated intravascular coagulation. Since circulating fibrinolytic activity was normal in TTP, the absence of vascular fibrinolysis is a local defect due to either inhibition by the platelet deposits or by local vascular damage. The inability of thrombolysis may explain the absence of systemic defibrination and the severity of the disease.

Surfactant alterations and lung fibrosis in a murine model of amiodarone-induced pulmonary fibrosis

Pneumologie ◽  
2008 ◽  
Vol 62 (S 2) ◽  
Author(s):  
P Mahavadi ◽  
L Schwertner ◽  
T Morky ◽  
I Henneke ◽  
M Korfei ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Murine Model ◽  
Lung Fibrosis
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