Endothelial Biomarkers in Patients Recovered from COVID-19 One Year after Hospital Discharge: A Cross-Sectional Study.

Background: COVID-19 is characterized by endothelial dysfunction and is presumed to have long-term cardiovascular sequelae. In this cross-sectional study, we aimed to explore the serum levels of endothelial biomarkers in patients who recovered from COVID-19 one year after hospital discharge. Methods: In this clinical follow-up study, 345 COVID-19 survivors from Huanggang, Hubei, and 119 age and gender-matched medical staff as healthy controls were enrolled. A standardized symptom questionnaire was performed, while electrocardiogram and Doppler ultrasound of lower extremities, routine blood tests, biochemical and immunological tests, serum soluble vascular cell adhesion molecule-1(VCAM-1), intercellular cell adhesion molecule-1(ICAM-1), P-selectin, and fractalkine were measured by enzyme-linked immunosorbent assays (ELISA). Results: At one year after discharge, 39% of recovers possessed post-COVID syndromes, while a few had abnormal electrocardiogram manifestations, and no deep vein thrombosis was detected in all screened survivors. There were no significant differences in circulatory inflammatory markers (leukocytes, neutrophils, lymphocytes, C-reactive protein and interleukin-6), alanine aminotransferase, estimated glomerular filtration rate, glucose, triglycerides, total cholesterol and D-dimer observed among healthy controls with previously mild or severe infected. Furthermore, serum levels of VCAM-1, ICAM-1, P-selectin, and fractalkine do not significantly differ between survivors and healthy controls. Conclusions: SARS-CoV-2 infection may not impose a higher risk of developing long-term cardiovascular events, even for those recovering from severe illness.

Lysine ß-Hydroxybutyrylation Improves Stability of COVID-19 Antibody.

ß-Hydroxybutyrate (3HB) is a small molecule produced as a ketone body in mammalian animals. It has been found that 3HB provides not only energy for a body, it also participates in cell signal transduction events as a signal molecule. This study focuses on investigation of 3HB immunomodulatory mechanisms. Proteomic analysis indicates a new post-translational modification of ß-hydroxybutyrylation (Kbhb) on antibodies. Because of the low level of Kbhb antibodies and the associated difficulty in purifying them, simulated Kbhb antibody was produced using chemical modification in vitro. The chemically modified Kbhb antibody was shown to improve the stability of antibodies to protease and heat treatments. Furthermore, Kbhb of antibodies stabilizes the antibodies in plasma. As a remarkable example, COVID-19 neutralizing antibody B38 produced by 293T cells was Kbhb modified and stabilized in vivo, providing a strategy for the possibility of extending the protection effects of COVID-19 antibodies.

Anti-SARS-CoV-2 IgG levels in relation to disease severity of COVID-19.

The durability of infection-induced severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunity has crucial implications for reinfection and vaccine effectiveness. However, the relationship between coronavirus disease 2019 (COVID-19) severity and long-term anti-SARS-CoV-2 immunoglobulin G (IgG) antibody level is poorly understood. Here, we measured the longevity of SARS-CoV-2-specific IgG antibodies in survivors who had recovered from COVID-19 1 year previously. In a cohort of 473 survivors with varying disease severity (asymptomatic, mild, moderate, or severe), we observed a positive correlation between virus-specific IgG antibody titers and COVID-19 severity. In particular, the highest virus-specific IgG antibody titers were observed in patients with severe COVID-19. By contrast, 74.4% of recovered asymptomatic carriers had negative anti-SARS-CoV-2 IgG test results, while many others had very low virus-specific IgG antibody titers. Our results demonstrate that SARS-CoV-2-specific IgG persistence and titer depend on COVID-19 severity.

Observation on distribution of TCM patterns and changes of peripheral blood cell count and chest imaging in mild and moderate COVID-19 patients

Objective: To observe distribution of traditional Chinese medicine(TCM) patterns and changes of peripheral blood cell count and chest imaging in mild and moderate COVID-19 patients.

Severe 2019 novel coronavirus pneumonia may cause lung bullae and bronchiectasis: A case report and concise literature review

Most of the critically ill novel coronavirus 2019 pneumonia (NCP) patients progress promptly, and soon match the ARDS diagnostic criteria. When mechanical ventilation and prone position cannot reverse the fatal hypoxia—extra-corporeal-membrane-oxygenation (ECMO) will be applied as a salvage treatment if available. Here, we report a novel coronavirus 2019 pneumonia (NCP) patient, a male, 67 years old, who was treated with ECMO for 30 days. In the midst, bronchoscopy was utilized to comprehend the airway lesions and clear secretions. And computed tomography (CT) scans were performed before and after the treatment of ECMO. In the recovering phase of his disease, the patient experienced multiple times pneumothorax on both sides. Some newly developed lung bullae in the subpleural area and modest bronchiectasis were found by the CT scan. The newly developed lung bullae was the probable cause of pneumothorax. Notably, in the whole process of his illness, the serum IL-6 only had a slight elevation in the early period, there is no typical cytokine storm as that was seen in non-COVID-19 ARDS. After 3-months meticulous treatment, the patient made a full recovery and now is discharged from our hospital. Though COVID-19 may not cause typical cytokine storm, the inflammation in lung may inflict severe damage to lung. Severe NCP may cause lung bullae and bronchiectasis, making the patients hard to be weaned from mechanical ventilation or ECMO. [ABSTRACT FROM AUTHOR] Copyright of European Journal of Inflammation (Sage Publications, Ltd.) is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Gastrointestinal Microenvironment and the Gut-Lung Axis in the Immune Responses of Severe COVID-19.

The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an unprecedented threat to the human health. A close association of the digestive tract is implied by the high frequency of gastrointestinal syndromes among COVID-19 patients. A better understanding of the role of intestinal microenvironment in COVID-19 immunopathology will be helpful to improve the control of COVID-19 associated morbidity and mortality. This review summarizes the immune responses associated with the severity of COVID-19, the current evidence of SARS-CoV-2 intestinal tropism, and the potential involvement of gut microenvironment in COVID-19 severity. Additionally, we discuss the therapeutic potential of probiotics as an alternative medicine to prevent or alleviate severe COVID-19 outcome.

A tentative discussion of medical education and cultures of science

Medical education is an important part of health care. Many medical educators have thought deeply about it since the outbreak of COVID-19. Based on my own experience and thinking during the pandemic, I now believe more strongly in the importance of the cultures of medicine and science, which reflect the views of life amongst medical and scientific professionals. The two cultures derive from the lives of medical workers and scientists and manifest in their attitudes towards clinical practice, scientific research and teaching. They also embody the spirit, essence and philosophy of the medical and scientific professions ? the common belief in seeking the truth and the common will to pursue kindness. Education today is not simply a matter of passing on knowledge. More importantly, the next generation shall inherit the scientific culture of seeking the truth, pursuing kindness and exploring beauty and humanity. This is crucial to medical education and clinical practice.

Early triage of critically ill COVID-19 patients using deep learning.

The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern. It is imperative to identify these patients early. We show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission. We develop this model using a cohort of 1590 patients from 575 medical centers, with internal validation performance of concordance index 0.894 We further validate the model on three separate cohorts from Wuhan, Hubei and Guangdong provinces consisting of 1393 patients with concordance indexes of 0.890, 0.852 and 0.967 respectively. This model is used to create an online calculation tool designed for patient triage at admission to identify patients at risk of severe illness, ensuring that patients at greatest risk of severe illness receive appropriate care as early as possible and allow for effective allocation of health resources.

Dynamic changes of throat swabs RNA and serum antibodies for SARS-CoV-2 and their diagnostic performances in patients with COVID-19.

Dynamic changes of RNA and antibodies in SARS-CoV-2 infected patients remain largely unknown, and influence factors for antibody production have not been fully clarified. In this study, consecutive throat swabs specimens (n = 1875) from 187 patients were collected to analyse the dynamic changes of RNA. Moreover, 162 serial serum samples from 31 patients were tested for seroconversion of IgM and IgG. Meanwhile, IgM and IgG were also detected in 409 COVID-19 patients and 389 controls. Additionally, the logistic regression analysis was executed to identify the possible influence factors for antibody production. The median positive conversion time for RNA was day 7 (IQR, 3-11), and the positive rate was highest in day 1-5 (74.59 %) and then gradually decreased. The median time of seroconversion for IgM and IgG were both day 12 (IQR, 10-15). The sensitivity and specificity for IgM (or IgG) was 87.04% and 96.92%, respectively. Multivariate logistic regression indicated that reduced lymphocytes and short positive conversion time for SARS-CoV-2 RNA were independent factors for negative results of IgM and IgG. In conclusion, RNA and antibodies should be combined for COVID-19 diagnosis, and delayed seroconversion was influenced by the decreased lymphocytes and short positive conversion time for RNA.

Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19.

Importance: Early identification of patients with novel coronavirus disease 2019 (COVID-19) who may develop critical illness is of great importance and may aid in delivering proper treatment and optimizing use of resources. Objective: To develop and validate a clinical score at hospital admission for predicting which patients with COVID-19 will develop critical illness based on a nationwide cohort in China. Design, Setting, and Participants: Collaborating with the National Health Commission of China, we established a retrospective cohort of patients with COVID-19 from 575 hospitals in 31 provincial administrative regions as of January 31, 2020. Epidemiological, clinical, laboratory, and imaging variables ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive risk score (COVID-GRAM). The score provides an estimate of the risk that a hospitalized patient with COVID-19 will develop critical illness. Accuracy of the score was measured by the area under the receiver operating characteristic curve (AUC). Data from 4 additional cohorts in China hospitalized with COVID-19 were used to validate the score. Data were analyzed between February 20, 2020 and March 17, 2020. Main Outcomes and Measures: Among patients with COVID-19 admitted to the hospital, critical illness was defined as the composite measure of admission to the intensive care unit, invasive ventilation, or death. Results: The development cohort included 1590 patients. the mean (SD) age of patients in the cohort was 48.9 (15.7) years; 904 (57.3%) were men. The validation cohort included 710 patients with a mean (SD) age of 48.2 (15.2) years, and 382 (53.8%) were men and 172 (24.2%). From 72 potential predictors, 10 variables were independent predictive factors and were included in the risk score: chest radiographic abnormality (OR, 3.39; 95% CI, 2.14-5.38), age (OR, 1.03; 95% CI, 1.01-1.05), hemoptysis (OR, 4.53; 95% CI, 1.36-15.15), dyspnea (OR, 1.88; 95% CI, 1.18-3.01), unconsciousness (OR, 4.71; 95% CI, 1.39-15.98), number of comorbidities (OR, 1.60; 95% CI, 1.27-2.00), cancer history (OR, 4.07; 95% CI, 1.23-13.43), neutrophil-to-lymphocyte ratio (OR, 1.06; 95% CI, 1.02-1.10), lactate dehydrogenase (OR, 1.002; 95% CI, 1.001-1.004) and direct bilirubin (OR, 1.15; 95% CI, 1.06-1.24). The mean AUC in the development cohort was 0.88 (95% CI, 0.85-0.91) and the AUC in the validation cohort was 0.88 (95% CI, 0.84-0.93). The score has been translated into an online risk calculator that is freely available to the public (http://118.126.104.170/). Conclusions and Relevance: In this study, a risk score based on characteristics of COVID-19 patients at the time of admission to the hospital was developed that may help predict a patient's risk of developing critical illness.