Prognostic Value of Frequent Exacerbations in Bronchiectasis: The Relationship With Disease Severity

Aims To search for biochemical indicators that can identify symptomatic patients with COVID-19 whose nucleic acid could turn negative within 14 days, and assess the prognostic value of these biochemical indicators in patients with COVID-19. Patients and methods We collected the clinical data of patients with COVID-19 admitted to our hospital, by using logistic regression analysis and AUC curves, explored the relationship between biochemical indicators and nucleic acid positive duration, the severity of COVID-19, and hospital stay respectively. Results A total of two hundred and thirty-three patients with COVID-19 were enrolled in the study. We found patients whose nucleic acid turned negative within 14 days had lower LDH, CRP and higher ALB ( P < 0.05). ROC curve results indicated that lower LDH, TP, CRP and higher ALB predicted the nucleic acid of patients turned negative within 14 days with statistical significance( P < 0.05), AST, LDH, CRP and PCT predicted the severe COVID-19 with statistical significance, and CRP predicted hospital stay >31days with statistical significance ( P < 0.05). After verification, the probability of nucleic acid turning negative within 14 days in patients with low LDH (<256 U/L), CRP (<44.5 mg/L) and high ALB (>35.8 g/L) was about 4 times higher than that in patients with high LDH, CRP and low ALB ( P < 0.05). Conclusions LDH, CRP and ALB are useful prognostic marker for predicting nucleic acid turn negative within 14 days in symptomatic patients with COVID-19.

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CT pulmonary angiography in COVID-19 pneumonia: relationship between pulmonary embolism and disease severity

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-020-00389-7 ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Aya Yassin ◽

Maryam Ali Abdelkader ◽

Rehab M. Mohammed ◽

Ahmed M. Osman

Keyword(s):

Pulmonary Embolism ◽

Disease Severity ◽

Laboratory Data ◽

Pulmonary Angiography ◽

Significant Relation ◽

Ct Pulmonary Angiography ◽

Laboratory Results ◽

Severity Of The Disease ◽

The Relationship ◽

D Dimer

Abstract Background Pulmonary embolism (PE) is one of the known sequels of COVID-19 infection. We aimed to assess the incidence of PE in patients with COVID-19 infection and to evaluate the relationship between the CT severity of the disease and the laboratory indicators. This was a retrospective study conducted on 96 patients with COVID-19 infection proved by positive PCR who underwent CT pulmonary angiography (CTPA) with a calculation of the CT severity of COVID-19 infection. Available patients’ complaint and laboratory data at the time of CTPA were correlated with PE presence and disease severity. Results Forty patients (41.7%) showed positive PE with the median time for the incidence of PE which was 12 days after onset of the disease. No significant correlation was found between the incidence of PE and the patients’ age, sex, laboratory results, and the CT severity of COVID-19. A statistically significant relation was found between the incidence of PE and the patients’ desaturation, hemoptysis, and chest pain. A highly significant correlation was found between the incidence of PE and the rising in the D-dimer level as well as the progressive CT findings when compared to the previous one. Conclusion CT progression and the rising in D-dimer level are considered the most important parameters suggesting underlying PE in patients with positive COVID-19 infection which is commonly seen during the second week of infection and alert the use of CT pulmonary angiography to exclude or confirm PE. This is may help in improving the management of COVID-19 infection.

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The Analysis of PTPN6 for Bladder Cancer: An Exploratory Study Based on TCGA

Disease Markers ◽

10.1155/2020/4312629 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8

Author(s):

Chengquan Shen ◽

Jing Liu ◽

Jirong Wang ◽

Xiaokun Yang ◽

Haitao Niu ◽

...

Keyword(s):

Bladder Cancer ◽

T Cells ◽

Survival Analysis ◽

Prognostic Value ◽

Molecular Mechanisms ◽

Tyrosine Phosphatase ◽

Gene Set Enrichment Analysis ◽

Expression Level ◽

Pathologic Features ◽

The Relationship

PTPN6 (protein tyrosine phosphatase nonreceptor type 6), a tyrosine phosphatase, is known to be signaling molecules that regulate a variety of cellular processes including cell growth, differentiation, mitotic cycle, and oncogenic transformation. Previous studies have demonstrated that PTPN6 expression is relatively elevated in several malignancies. However, the role of PTPN6 in bladder cancer (BC) remains unclear. The purpose of this study was to explore the prognostic value of PTPN6 in BC. RNA-seq data from The Cancer Genome Atlas (TCGA) was used to identify the expression level of PTPN6 in BC. The relationship between clinical pathologic features and PTPN6 were analyzed with the Wilcoxon signed-rank test. The prognostic and predictive value of PTPN6 was evaluated by survival analysis and nomogram. Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential molecular mechanisms of PTPN6 in BC. Finally, Tumor Immune Estimation Resource (TIMER) was applied to investigate the relationship between PTPN6 and immune cell infiltration in the tumor microenvironment. Results indicated that PTPN6 was overexpressed in BC tissues compared with normal bladder tissues and was significantly correlated with grade, stage, T, and N. Survival analysis showed that low expression of PTPN6 was significantly related to the poor overall survival (OS) in BC patients. Coexpression analysis showed that PTPN6 and TNFRSF14 (Tumor necrosis factor receptor superfamily member 14) have a close correlation in BC. GSEA showed that multiple cancer-associated signaling pathways are differentially enriched in the PTPN6 high expression phenotype. Moreover, the expression level of PTPN6 was positively associated with the infiltration of B cells, CD4+T cells, dendritic cells, and neutrophils and negatively associated with CD8+ T cells and macrophages in BC. In conclusion, we identified that PTPN6 may be a novel prognostic biomarker in BC based on the TCGA database. Further clinical trials are needed to confirm our observations and mechanisms underlying the prognostic value of PTPN6 in BC also deserve further experimental exploration.

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The relationship between tender point count and disease severity in patients with primary fibromyalgia

Rheumatology International ◽

10.1007/s00296-010-1580-5 ◽

2010 ◽

Vol 32 (1) ◽

pp. 105-107 ◽

Cited By ~ 11

Author(s):

Ali Salli ◽

Halim Yilmaz ◽

Hatice Ugurlu

Keyword(s):

Disease Severity ◽

Tender Point ◽

Point Count ◽

Primary Fibromyalgia ◽

The Relationship

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Predicting Swiss Needle Cast Disease Distribution and Severity in Young Douglas-Fir Plantations in Coastal Oregon

Phytopathology ◽

10.1094/phyto.2003.93.7.790 ◽

2003 ◽

Vol 93 (7) ◽

pp. 790-798 ◽

Cited By ~ 32

Author(s):

Pablo H. Rosso ◽

Everett M. Hansen

Keyword(s):

Prediction Model ◽

Disease Severity ◽

Pacific Northwest ◽

Regression Tree ◽

Douglas Fir ◽

Slope Aspect ◽

Disease Prediction ◽

Needle Cast ◽

Swiss Needle Cast ◽

The Relationship

Swiss needle cast (SNC), caused by the fungus Phaeocryptopus gaeumannii, is producing extensive defoliation and growth reduction in Douglas-fir forest plantations along the Pacific Northwest coast. An SNC disease prediction model for the coastal area of Oregon was built by establishing the relationship between the distribution of disease and the environment. A ground-based disease survey (220 plots) was used to study this relationship. Two types of regression approaches, multiple linear regression and regression tree, were used to study the relationship between disease severity and climate, topography, soil, and forest stand characteristics. Fog occurrence, precipitation, temperature, elevation, and slope aspect were the variables that contributed to explain most of the variability in disease severity, as indicated by both the multiple regression (r 2 = 0.57) and regression tree (RMD = 0.27) analyses. The resulting regression model was used to construct a disease prediction map. Findings agree with and formalize our previous understanding of the ecology of SNC: warmer and wetter conditions, provided that summer temperatures are relatively low, appear to increase disease severity. Both regression approaches have characteristics that can be useful in helping to improve our understanding of the ecology of SNC. The prediction model is able to produce a continuous prediction surface, suitable for hypothesis testing and assisting in disease management and research.

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Visual and quantitative assessment of COVID-19 pneumonia on chest CT: The relationship with disease severity and clinical findings

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405617666210215142528 ◽

2021 ◽

Vol 17 ◽

Author(s):

Furkan Kaya ◽

Petek Şarlak Konya ◽

Emin Demirel ◽

Neşe Demirtürk ◽

Semiha Orhan ◽

...

Keyword(s):

Hospital Stay ◽

Disease Severity ◽

Pearson Correlation ◽

Laboratory Data ◽

Length Of Hospital Stay ◽

Chest Ct ◽

Laboratory Findings ◽

Pneumonia Severity ◽

High Attenuation ◽

The Relationship

Background: Lungs are the primary organ of involvement of COVID-19, and the severity of pneumonia in COVID-19 patients is an important cause of morbidity and mortality. Aim: We aimed to evaluate the visual and quantitative pneumonia severity on chest computed tomography (CT) in patients with coronavirus disease 2019 (COVID-19) and compare the CT findings with clinical and laboratory findings. Methods: We retrospectively evaluated adult COVID-19 patients who underwent chest CT, clinical scores, laboratory findings, and length of hospital stay. Two independent radiologists visually evaluated the pneumonia severity on chest CT (VSQS). Quantitative CT (QCT) assessment was performed using a free DICOM viewer, and the percentage of the well-aerated lung (%WAL), high-attenuation areas (%HAA) at different threshold values, and mean lung attenuation (MLA) values were calculated. The relationship between CT scores and the clinical, laboratory data, and length of hospital stay were evaluated in this cross-sectional study. The student's t-test and chi-square test were used to analyze the differences between variables. The Pearson correlation test analyzed the correlation between variables. The diagnostic performance of the variables was assessed using receiver operating characteristic (ROC) analysis was used. Results: The VSQS and QCT scores were significantly correlated with procalcitonin, d-dimer, ferritin, and C-reactive protein levels. Both VSQ and QCT scores were significantly correlated with disease severity (p<0.001). Among the QCT parameters, the %HAA-600 value showed the best correlation with the VSQS (r=730,p<0.001). VSQS and QCT scores had high sensitivity and specificity in distinguishing disease severity and predicting prolonged hospitalization. Conclusion: The VSQS and QCT scores can help manage the COVID-19 and predict the duration of hospitalization.

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