Establishment and Evaluation of a Prediction Model of BLR for Severity in Coronavirus Disease 2019

Background:Coronavirus disease 2019 (COVID-19) is an emerging infectious disease and has spread worldwide. Clinical risk factors associated with the severity in COVID-19 patients have not yet been well delineated. The aim of this study was to explore the risk factors related with the progression of severe COVID-19 and establish a prediction model for severity in COVID-19 patients.Methods:We retrospectively recruited patients with confirmed COVID-19 admitted in Enze Hospital, Taizhou Enze Medical Center (Group) and Nanjing Drum Tower Hospital between January 24 and March 12, 2020. Take the Taizhou cohort as the training set and the Nanjing cohort as the validation set. Severe case was defined based on the World Health Organization Interim Guidance Report criteria for severe pneumonia. The patients were divided into severe and non-severe groups. Epidemiological, laboratory, clinical, and imaging data were recorded with data collection forms from the electronic medical record. The predictive model of severe COVID-19 was constructed, and the efficacy of the predictive model in predicting the risk of severe COVID-19 was analyzed by the receiver operating characteristic curve (ROC).Results:A total of 402 COVID-19 patients were included in the study, including 98 patients in the training set (Nanjing cohort) and 304 patients in the validation set (Nanjing cohort). There were 54 cases (13.43%) in severe group and 348 cases (86.57%) in non-severe group. Logistic regression analysis showed that body mass index (BMI) and lymphocyte count were independent risk factors for severe COVID-19 (all P < 0.05). Logistic regression equation based on risk factors was established as follows: Logit (BL)=-5.552-5.473 ×L + 0.418 × BMI. The area under the ROC curve (AUC) of the training set and the validation set were 0.928 and 0.848, respectively (all P < 0.001). The model was simplified to get a new model (BMI and lymphocyte count ratio, BLR) for predicting severe COVID-19 patients, and the AUC in the training set and validation set were 0.926 and 0.828, respectively (all P < 0.001).Conclusions:Higher BMI and lower lymphocyte count are critical factors associated with severity of COVID-19 patients. The simplified BLR model has a good predictive value for the severe COVID-19 patients. Metabolic factors involved in the development of COVID-19 need to be further investigated. © 2021 The Chinese Medical Association, Published by Wolters Kluwer Health, Inc.

Body Mass Index (BMI) and serum levels of SARS-Co-V-2 specific antibodies in a group of Healthcare Workers after COVID-19 vaccination

Introduction: Obesity is considered one of the possible risk factors for hospitalization and intensive care in Covid-19 patients. It is believed that obesity may compromise some steps of the immune response and may affect the development of post-vaccine immunological memory. The aim of our study was to assess the post-vaccination IgG response against the spike protein (S-RBD IgG) in relation to age, gender and body mass index (BMI). Material and Methods: The study involved 766 Healthcare Workers who received two doses of BioNTech/Pfizer vaccination (December 2020-March 2021) and were tested for S-RBD IgG (CMIA) 20-40 days after the second vaccine dose. These subjects were always negative to SARS CoV-2 nasopharyngeal periodical swabs and were negative to Ab anti SARS-CoV-2 S1/S2 IgG (CLIA) measured before the first dose of vaccine. Results: The 766 workers (70.8% female and 29.2% male) were all positive for the antibody levels determined after the second dose of vaccine (S-RDB IgG range: 190.8-63093 AU/mL). Multivariable data analysis showed that the increase in the S-RBD IgG was more pronounced in younger subjects (p<0.001) and in women (p<0.05). Data analysis also showed an increase in the levels of S-RDB IgG in subjects with greater BMI (p<0.05). Conclusion: At a first check (20-40 days after the vaccination), the SARS-Co-V-2 antibody levels in the studied sample were influenced by age and gender, as expected. Contrary to data reported by others, subjects with greater BMI showed an increased antibody response, but this finding, as well as the temporal trend of antibody levels, need to be further investigated.

COVID-19 outbreaks in hospital workers during the first COVID-19 wave.

BACKGROUND: Health care workers (HCWs) are on the frontline, playing a crucial role in the prevention of infection and treatment of patients. AIMS: This study was aimed to evaluate the prevalence of hospital-acquired coronavirus disease 2019 (COVID-19) infection at work and related factors at the University Hospital of Trieste workers exposed to COVID-19 patients. METHODS: From March 1 to May 31, of 4216 employees, 963 were in contact with COVID-19 patients or colleagues and were followed up. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in nasopharyngeal swabs was determined every 3 days, by RT-PCR. RESULTS: During the follow-up period, 193 workers were positive for COVID-19 (5%), and 165 of these (86%) were symptomatic. We identified five major cluster outbreaks of COVID-19 infection in Trieste Hospitals, four of which occurred before the implementation of universal masking for HCWs and patients (1-14 March 2020). COVID-19 infection was significantly higher in high-risk ward workers (Infectious Diseases, and Geriatric and Emergency Medicine, odds ratio [OR] 13.4; 95% confidence interval [CI] 5.8-31), in subjects with symptoms (OR 5.4; 95% CI 2.9-10) and in those with contacts with COVID-19 patients and colleagues (OR 2.23; 95% CI 1.01-4.9). CONCLUSIONS: Hospital workers were commonly infected due to contact with COVID-19 patients and colleagues, mainly in the first 15 days of the pandemic, before the implementation of universal mask wearing of HCWs and patients. Repetitive testing and follow-up permitted the identification of COVID-19 cases before symptom onset, obtaining better infection prevention and control.

Evidence-based recommendations for gastrointestinal cancers during the COVID-19 pandemic by the Brazilian Gastrointestinal Tumours Group.

PURPOSE: As of 2020, the world is facing the great challenge of the COVID-19 (Coronavirus disease 2019) pandemic, caused by the SARS-CoV-2 virus. While the overall mortality is low, the virus is highly virulent and may infect millions of people worldwide. This will consequently burden health systems, particularly by those individuals considered to be at high risk of severe complications from COVID-19. Such risk factors include advanced age, cardiovascular and pulmonary diseases, diabetes and cancer. However, few data on the outcomes of cancer patients infected by SARS CoV-2 exist. Therefore, there is a lack of guidance on how to manage cancer patients during the pandemic. We sought to propose specific recommendations about the management of patients with gastrointestinal malignancies. METHODS: The Brazilian Gastrointestinal Tumours Group board of directors and members sought up-to-date scientific literature on each tumour type and discussed all recommendations by virtual meetings to provide evidence-based-and sometimes, expert opinion-recommendation statements. Our objectives were to recommend evidence-based approaches to both treat and minimise the risk of COVID-19 for cancer patients, and simultaneously propose how to decrease the use of hospital resources at a time these resources need to be available to treat COVID-19 patients. RESULTS: Overall and tumour-specific recommendations were made by stage (including surgical, locoregional, radiotherapy, systemic treatments and follow-up strategies) for the most common gastrointestinal malignancies: esophagus, gastric, pancreas, bile duct, hepatocellular, colorectal, anal cancer and neuroendocrine tumours. CONCLUSIONS: Our recommendations emphasise the importance of treating cancer patients, using the best evidence available, while simultaneously taking into consideration the world-wide health resource hyperutilisation to treat non-cancer COVID-19 patients.