Predictors for imaging progression on chest CT from coronavirus disease 2019 (COVID-19) patients

Yang, Zongguo; Shi, Jia; Zhang, He; Lü, Ying; Xu, Qinfeng; Wang, Hongzhi; Chen, Shishi; Tang, Bozong; Yin, Keshan; Lu, Yao; Chen, Xiaorong

doi:10.18632/aging.102999

Cited by 106 publications

(100 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Concerning new predictive parameters of specific cardiovascular risk, very recent data report that homocysteine (Hcy) (together with age, monocyte-lymphocyte ratio (MLR), and period from disease onset to hospital admission) may be a specific cardiovascular risk predictive parameter for severe pneumonia observed at chest computed tomography (CT) during the first week of COVID-19 infection; however, these observations did not report any additional organ involvement [11]. The aim of this review is to report the current state of knowledge regarding known biomarkers for COVID-19 infection, focusing on those potentially predictive of organ damage in patients with severe complications and death.…”

Section: Introductionmentioning

confidence: 99%

Biomarkers associated with COVID-19 disease progression

Ponti

Maccaferri

Ruini

et al. 2020

Critical Reviews in Clinical Laboratory Sciences

765

678

View full text Add to dashboard Cite

The coronavirus disease 2019 (COVID-19) pandemic is a scientific, medical, and social challenge. The complexity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is centered on the unpredictable clinical course of the disease that can rapidly develop, causing severe and deadly complications. The identification of effective laboratory biomarkers able to classify patients based on their risk is imperative in being able to guarantee prompt treatment. The analysis of recently published studies highlights the role of systemic vasculitis and cytokine mediated coagulation disorders as the principal actors of multi organ failure in patients with severe COVID-19 complications. The following biomarkers have been identified: hematological (lymphocyte count, neutrophil count, neutrophil-lymphocyte ratio (NLR)), inflammatory (C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), procalcitonin (PCT)), immunological (interleukin (IL)-6 and biochemical (D-dimer, troponin, creatine kinase (CK), aspartate aminotransferase (AST)), especially those related to coagulation cascades in disseminated intravascular coagulation (DIC) and acute respiratory distress syndrome (ARDS). New laboratory biomarkers could be identified through the accurate analysis of multicentric case series; in particular, homocysteine and angiotensin II could play a significant role.

show abstract

Section: Introductionmentioning

confidence: 99%

Biomarkers associated with COVID-19 disease progression

Ponti

Maccaferri

Ruini

et al. 2020

Critical Reviews in Clinical Laboratory Sciences

765

678

View full text Add to dashboard Cite

show abstract

“…Low white cells and platelet count, high D-dimer values, and high pro-thrombin time showed a correlation with mortality [8,20]. Significantly higher levels of aspartate aminotransferase, urea, creatinine, creatinine kinase, and lactate dehydrogenase were found in dead patients than in survivors [8,21,22].…”

Section: Discussionmentioning

confidence: 91%

Risk Factors of Fatal Outcome in Patients With COVID-19 Pneumonia

Cellina

Gibelli

Pittino

et al. 2020

Disaster med. public health prep.

View full text Add to dashboard Cite

Aim: To correlate the clinical, laboratory, and radiographic characteristics of patients with a confirmed diagnosis of COVID-19 disease, with fatal outcome. Methods: We reviewed Chest X-Ray (CXR) features, clinical, and laboratory data of patients with RT-PCR confirmed diagnosis of COVID-19 infection. The relationship with mortality was investigated by fitting a logistic regression model. Results: 246 patients were included (170 males; mean age: 63). Most of the patients had one or more comorbidity (62%); fever (95%) and cough (60%) were the most common symptoms; CXR detected abnormalities in 88.6%, mainly showing ground-glass opacities (GGO) (90 %) with bilateral (64%) and peripheral (46%) distribution. Multivariate analysis showed that age (p<.001; mortality of 59% in patients >66 years old; 5% at a younger age) and consolidation at CXR (p=.001; mortality of 11% with positive CXR; 2% in those without) represented the two most significant independent risk factors of mortality. Chronic pathologies such as diabetes and chronic obstructive pulmonary disease and peripheral GGO at CXR also showed a significant correlation with mortality. Conclusions: We identified predictive factors for the fatal outcome of COVID-19 patients. The prognostic value of these findings can be useful for the right patient management and resource allocation.

show abstract

“…Suppression of the EGFR pathway via the reduction of eIF2α phosphorylation increases susceptibility to cellular oxidative stress [ 39 ]. The parameters including homocysteine, urea, creatinine and serum cystatin C were significantly higher in imaging progression patients, while EGFR decreased [ 40 ]. This suggested that low levels of EGFR may be a protective factor for COVID-19.…”

Section: Discussionmentioning

confidence: 99%

Therapeutic mechanism of Toujie Quwen granules in COVID-19 based on network pharmacology

Huang

Zheng

et al. 2020

BioData Mining

View full text Add to dashboard Cite

Background Chinese medicine Toujie Quwen granule (TJQW) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases by relieving symptoms, slowing the progression of the disease, and boosting the recovery of patients. But the bioactive compounds and potential mechanisms of TJQW for COVID-19 prevention and treatment are unclear. This study aimed to explore the potential therapeutic mechanism of TJQW in coronavirus disease 2019 (COVID-19) based on an integrated network pharmacology approach. Methods TCMSP were used to search and screen the active ingredients in TJQW. The Swiss TargetPrediction was used to predict the potential targets of active ingredients. Genes co-expressed with ACE2 were considered potential therapeutic targets on COVID-19. Venn diagram was created to show correlative targets of TJQW against COVID-19. Cytoscape was used to construct a “drug-active ingredient-potential target” network, STRING were used to construct protein-protein interaction network, and cytoHubba performed network topology analysis. Enrichment of biological functions and signaling pathways of core targets was performed by using the clusterProfiler package in R software and ClueGO with CluePedia plugins in Cytoscape. Results A total of 156 active ingredients were obtained through oral bioavailability and drug-likeness screenings. Two hundred twenty-seven potential targets of TJQW were related to COVID-19. The top ten core targets are EGFR, CASP3, STAT3, ESR1, FPR2, F2, BCL2L1, BDKRB2, MPO, and ACE. Based on that, we obtained 19 key active ingredients: umbelliprenin, quercetin, kaempferol, luteolin, praeruptorin E, stigmasterol, and oroxylin A. And the enrichment analysis obtained multiple related gene ontology functions and signaling pathways. Lastly, we constructed a key network of “drug-component-target-biological process-signaling pathway”. Our findings suggested that TJQW treatment for COVID-19 was associated with elevation of immunity and suppression of inflammatory stress, including regulation of inflammatory response, viral process, neutrophil mediated immunity, PI3K-Akt signaling pathway, MAPK signaling pathway, Jak-STAT signaling pathway, Complement and coagulation cascades, and HIF-1 signaling pathway. Conclusions Our study uncovered the pharmacological mechanism underlying TJQW treatment for COVID-19. These results should benefit efforts for people around the world to gain more knowledge about Chinese medicine TJQW in the treatment of this vicious epidemic COVID-19, and help to address this pressing problem currently facing the world.

show abstract

Predictors for imaging progression on chest CT from coronavirus disease 2019 (COVID-19) patients

Cited by 106 publications

References 40 publications

Biomarkers associated with COVID-19 disease progression

Biomarkers associated with COVID-19 disease progression

Risk Factors of Fatal Outcome in Patients With COVID-19 Pneumonia

Therapeutic mechanism of Toujie Quwen granules in COVID-19 based on network pharmacology

Contact Info

Product

Resources

About