scholarly journals In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Joonho Park ◽  
Hyeyoon Kim ◽  
So Yeon Kim ◽  
Yeonjae Kim ◽  
Jee-Soo Lee ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Good Prognosis ◽  
Severe Illness ◽  
Proteome Profiling ◽  
T Cell Suppression ◽  
Cell Suppression ◽  
Profiling Analysis ◽  
Necrosis Factor

AbstractThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over forty million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed in-depth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.

scholarly journals In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients

2020 ◽  
Author(s):  
Joonho Park ◽  
Hyeyoon Kim ◽  
So Yeon Kim ◽  
Yeonjae Kim ◽  
Jee-Soo Lee ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Good Prognosis ◽  
Severe Illness ◽  
Proteome Profiling ◽  
T Cell Suppression ◽  
Cell Suppression ◽  
Profiling Analysis ◽  
Necrosis Factor

ABSTRACTThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over ten million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed indepth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1,222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.

scholarly journals Clinical decision making and research in hepatocellular carcinoma: Pivotal role of imaging techniques

Hepatology ◽  
2011 ◽  
Vol 54 (6) ◽  
pp. 2238-2244 ◽  
Author(s):  
Jordi Bruix ◽  
Maria Reig ◽  
Jordi Rimola ◽  
Alejandro Forner ◽  
Marta Burrel ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Imaging Techniques ◽  
Clinical Decision ◽  
Pivotal Role

Practice Guidelines for the Diagnosis of COVID-19-Associated Pulmonary Aspergillosis in an Intensive Care Setting

2021 ◽  
pp. 088506662110471
Author(s):  
Zia Hashim ◽  
Zafar Neyaz ◽  
Rungmei S.K. Marak ◽  
Alok Nath ◽  
Soniya Nityanand ◽  
...  
Keyword(s):  
Intensive Care ◽  
Practice Guidelines ◽  
Clinical Management ◽  
Care Setting ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Third Wave ◽  
Intensive Care Setting ◽  
Pulmonary Aspergillosis

Coronavirus disease-2019 (COVID-19)-associated pulmonary aspergillosis (CAPA) is a new disease characterized by secondary Aspergillus mold infection in patients with COVID-19. It primarily affects patients with COVID-19 in critical state with acute respiratory distress syndrome, requiring intensive care and mechanical ventilation. CAPA has a higher mortality rate than COVID-19, posing a serious threat to affected individuals. COVID-19 is a potential risk factor for CAPA and has already claimed a massive death toll worldwide since its outbreak in December 2019. Its second wave is currently progressing towards a peak, while the third wave of this devastating pandemic is expected to follow. Therefore, an early and accurate diagnosis of CAPA is of utmost importance for effective clinical management of this highly fatal disease. However, there are no uniform criteria for diagnosing CAPA in an intensive care setting. Therefore, based on a review of existing information and our own experience, we have proposed new criteria in the form of practice guidelines for diagnosing CAPA, focusing on the points relevant for intensivists and pulmonary and critical care physicians. The main highlights of these guidelines include the role of CAPA-appropriate test specimens, clinical risk factors, computed tomography of the thorax, and non-culture-based indirect and direct mycological evidence for diagnosing CAPA in the intensive care unit. These guidelines classify the diagnosis of CAPA into suspected, possible, and probable categories to facilitate clinical decision-making. We hope that these practice guidelines will adequately address the diagnostic challenges of CAPA, providing an easy-to-use and practical algorithm to clinicians for rapid diagnosis and clinical management of the disease.

scholarly journals A novel severity score to predict inpatient mortality in COVID-19 patients

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
David J. Altschul ◽  
Santiago R. Unda ◽  
Joshua Benton ◽  
Rafael de la Garza Ramos ◽  
Phillip Cezayirli ◽  
...  
Keyword(s):  
Severity Score ◽  
Clinical Decision Making ◽  
Risk Model ◽  
Validation Cohort ◽  
Clinical Decision ◽  
International Normalized Ratio ◽  
Severe Illness ◽  
Roc Curve Analysis ◽  
Derivation Cohort ◽  
Mortality Incidence

Abstract COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality. 4711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n = 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814–0.851) and an AUC of 0.798 (95% CI 0.789–0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0–3), moderate (4–6) and high (7–10) COVID-19 severity score. This developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

scholarly journals Current Role of Surgery in Pancreatic Cancer With Synchronous Liver Metastasis

2020 ◽  
Vol 27 (1) ◽  
pp. 107327482097659
Author(s):  
Wentao Zhou ◽  
Dansong Wang ◽  
Wenhui Lou
Keyword(s):  
Pancreatic Cancer ◽  
Liver Metastasis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Synchronous Liver Metastasis ◽  
Long Term Outcomes ◽  
Short And Long Term ◽  
Current Guidelines

Pancreatic cancer with synchronous liver metastasis has an extremely poor prognosis, and surgery is not recommended for such patients by the current guidelines. However, an increasing body of studies have shown that concurrent resection of pancreatic cancer and liver metastasis is not only technically feasible but also beneficial to the survival in the selected patients. In this review, we aim to summarize the short- and long-term outcomes following synchronous liver metastasectomy for pancreatic cancer patients, and discuss the potential criteria in selecting appropriate surgical candidates, which might be helpful in clinical decision-making.

scholarly journals Treatment selection of early stage non-small cell lung cancer: the role of the patient in clinical decision making

BMC Cancer ◽  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
S. Mokhles ◽  
J. J. M. E. Nuyttens ◽  
M. de Mol ◽  
J. G. J. V. Aerts ◽  
A. P. W. M. Maat ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Decision Making ◽  
Small Cell Lung Cancer ◽  
Clinical Decision Making ◽  
Early Stage ◽  
Clinical Decision ◽  
Small Cell ◽  
Small Cell Lung ◽  
Selection Of
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