Proxalutamide for the treatment of COVID-19 rebound following Paxlovid treatment: Report of four cases and review of the literature.

BACKGROUND: The pandemic the coronavirus disease 2019 (COVID-19) has created a global health crisis. Although Paxlovid is recommended for the early-stage treatment of mild-to-moderate COVID-19 in patients at increased risk of progression to severe COVID-19, more and more cases are reported a COVID-19 rebound after Paxlovid treatment. Currently, information on the additional treatment for COVID-19 rebound following Paxlovid treatment is limited. CASE REPORT: Here, we present four cases with COVID-19 who were mild on admission. All cases experienced a COVID-19 rebound and progressed to severe COVID-19, following treatment with Paxlovid (300 mg of nirmatrelvir with 100 mg ritonavir, twice daily for 5 days). After being treated with proxalutamide (300 mg/day), all cases finally turned real-time reverse transcription polymerase chain reaction (RT-PCR) negative. CONCLUSION: Our cases suggested that proxalutamide might be an effective remedial treatment option for patients experiencing a COVID-19 rebound after Paxlovid treatment.

Prediction of container port congestion status and its impact on ship's time in port based on AIS data

The growth of container throughput and the impact of COVID-19 have made container ports increasingly congested, leading to uncertain cargo transit times and high freight rates. Shipping parties want to know in advance the congestion of each port in the next phase to adjust their plans, but there are few studies involving congestion prediction, and this study hopes to make some additions. Three indicators are extracted from Automatic Identification System (AIS) data to represent the port congestion status for the sake of generalizability. And those indicators are used to predict port congestion status and further to predict container ships' time in port using the eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP) algorithms. The established models show that those indicators can improve prediction accuracy of port time compared to not considering port status. The findings also show that port congestion status contributes significantly to determining port time and makes it fluctuate by up to nearly 50 hours. The prediction results could help shipping companies to change their transportation schedules early to bypass ports with long waiting times or to arrange ships to enter the port earlier for delivering cargos on schedule. [ FROM AUTHOR]

Screening and Characterization of Shark-Derived VNARs against SARS-CoV-2 Spike RBD Protein.

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein is the major target for antibody therapeutics. Shark-derived variable domains of new antigen receptors (VNARs) are the smallest antibody fragments with flexible paratopes that can recognize protein motifs inaccessible to classical antibodies. This study reported four VNARs binders (JM-2, JM-5, JM-17, and JM-18) isolated from Chiloscyllium plagiosum immunized with SARS-CoV-2 RBD. Biolayer interferometry showed that the VNARs bound to the RBD with an affinity KD ranging from 38.5 to 2720 nM, and their Fc fusions had over ten times improved affinity. Gel filtration chromatography revealed that JM-2-Fc, JM-5-Fc, and JM-18-Fc could form stable complexes with RBD in solution. In addition, five bi-paratopic VNARs, named JM-2-5, JM-2-17, JM-2-18, JM-5-18, and JM-17-18, were constructed by fusing two VNARs targeting distinct RBD epitopes based on epitope grouping results. All these bi-paratopic VNARs except for JM-5-18 showed higher RBD binding affinities than its component VNARs, and their Fc fusions exhibited further enhanced binding affinities, with JM-2-5-Fc, JM-2-17-Fc, JM-2-18-Fc, and JM-5-18-Fc having KD values lower than 1 pM. Among these Fc fusions of bi-paratopic VNARs, JM-2-5-Fc, JM-2-17-Fc, and JM-2-18-Fc could block the angiotensin-converting enzyme 2 (ACE2) binding to the RBD of SARS-CoV-2 wildtype, Delta, Omicron, and SARS-CoV, with inhibition rates of 48.9~84.3%. Therefore, these high-affinity VNAR binders showed promise as detectors and therapeutics of COVID-19.

Usage of compromised lung volume in monitoring steroid therapy on severe COVID-19.

BACKGROUND: Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of coronavirus disease 2019 (COVID-19) and for monitoring its progress. The present study aimed to assess the association between steroid therapy and quantitative CT parameters in a longitudinal cohort with COVID-19. METHODS: Between February 7 and February 17, 2020, 72 patients with severe COVID-19 were retrospectively enrolled. All 300 chest CT scans from these patients were collected and classified into five stages according to the interval between hospital admission and follow-up CT scans: Stage 1 (at admission); Stage 2 (3-7 days); Stage 3 (8-14 days); Stage 4 (15-21 days); and Stage 5 (22-31 days). QCT was performed using a threshold-based quantitative analysis to segment the lung according to different Hounsfield unit (HU) intervals. The primary outcomes were changes in percentage of compromised lung volume (%CL, - 500 to 100 HU) at different stages. Multivariate Generalized Estimating Equations were performed after adjusting for potential confounders. RESULTS: Of 72 patients, 31 patients (43.1%) received steroid therapy. Steroid therapy was associated with a decrease in %CL (- 3.27% [95% CI, - 5.86 to - 0.68, P = 0.01]) after adjusting for duration and baseline %CL. Associations between steroid therapy and changes in %CL varied between different stages or baseline %CL (all interactions, P < 0.01). Steroid therapy was associated with decrease in %CL after stage 3 (all P < 0.05), but not at stage 2. Similarly, steroid therapy was associated with a more significant decrease in %CL in the high CL group (P < 0.05), but not in the low CL group. CONCLUSIONS: Steroid administration was independently associated with a decrease in %CL, with interaction by duration or disease severity in a longitudinal cohort. The quantitative CT parameters, particularly compromised lung volume, may provide a useful tool to monitor COVID-19 progression during the treatment process. Trial registration Clinicaltrials.gov, NCT04953247. Registered July 7, 2021, https://clinicaltrials.gov/ct2/show/NCT04953247.

Air quality impacts of emissions from a typical iron and steel plant in Hebei Province during the coronavirus disease（COVID-19）

Based on the meteorological forecast data from the National Meteorological Bureau, this study developed an AERMOD-based pollution forecasting model for iron and steel plants, simulated air quality impacts of a typical iron and steel plant located in Hebei Province during the controlled period（from February to March in 2020） and the uncontrolled period（from April to October in 2020） of the COVID-19 epidemic, and validated the model with real monitoring air quality data. In case of adverse wind direction, the results showed that the average contribution of SO2, NOx and PM10 from the plant to three state-controlled monitoring stations were 20.19～33.81%, 17.49～23.46% and 2.02～2.69% respectively during the controlled period, and 13.43～21.01%, 11.09～20.92% and 1.20～2.22% during the uncontrolled period. The correlation coefficients between the forecast values of SO2, NOx and PM10 emission of the plant and the real monitoring values of the three state-controlled monitoring stations were higher in the controlled period（the highest values are 0.43,0.48 and 0.29, respectively, at individual monitoring station） compared with the uncontrolled period（the highest values are 0.42,0.39 and 0.07, respectively） due to the less interference from other anthropogenic emission sources during the controlled period.

Usage of Compromised Lung Volume in Monitoring Steroid Therapy on Severe COVID-19 (preprint)

Background: Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of coronavirus disease 2019 (COVID-19)and for monitoringits progress. The present study aimed to assess the association between steroid therapy and quantitative CT parameters in a longitudinal cohort with COVID-19. Methods: Between February 7 and February 17, 2020, 300 chest CT scans from 72 patients with severe COVID-19 were retrospectively collected and classified into five stages according to the interval between hospital admission and follow-up CT scans: Stage 1 (at admission); Stage 2 (3–7 days); Stage 3 (8–14 days); Stage 4 (15–21 days); and Stage 5 (22–31 days). QCT was performed using a threshold-based quantitative analysis to segment the lungaccording to different Hounsfield unit (HU) intervals. The primary outcomeswerechanges in percentage of compromised lung volume (%CL, –500 to 100 HU) at different stages. Multivariate Generalized Estimating Equations were performed after adjusting for potential confounders. Results: Of 72 patients, 31 patients (43.1%) received steroid therapy. Steroid therapy was associated with a decrease in %CL (-3.27% [95%CI, -5.86 to -0.68, P = 0.01]) after adjusting for duration and baseline %CL. Associations between steroid therapy and changes in %CL varied between different stages or baseline %CL (all interactions, P <0.01). Steroid therapy was associated with decrease in %CL after stage 3 (all P <0.05), but not at stage 2. Similarly, steroid therapy was associated with a more significant decrease in %CL in the high CL group ( P <0.05), but not inthe low CL group. Conclusions: Steroid administration was independently associated with a decrease in %CL, with interaction by duration or disease severity in a longitudinal cohort. The quantitative CT parameters, particularly compromised lung volume, may provide a useful tool to monitor COVID-19 progression during the treatment process. Trial registration Clinicaltrials.gov, NCT04953247. Registered July 7, 2021, https://clinicaltrials.gov/ct2/show/NCT04953247

The Impact of the SARS-COV-2 Pandemic on the Mental Health and Employment Decisions of Medical Students in North China.

Background: The outbreak of severe respiratory syndrome coronavirus 2 (SARS-COV-2) has led to long periods of social isolation for individuals across the world. Although medical students generally have a high prevalence of mental health problems, they have received less attention than other groups concerning the impact of SARS-COV-2. Therefore, the present study investigated the mental health status, risk factors, and protective factors for mental health problems in medical students in North China during the SARS-COV-2 pandemic. Methods: A WeChat-based survey, which included the Depression Anxiety Stress Scale-21 and measures of social demographics, was performed twice. Risk and protective factors were identified by binary logistic regression analysis. Results: A total of 702 effective questionnaires were collected in two separate surveys. In total, 24.55% of medical students were suffering anxiety to different degrees of severity, 13.18% were suffering depression in the first survey, and 3.71% wanted to give up working in primary medical care during the SARS-COV-2 pandemic in the second survey. In contrast, during the SARS-COV-2 pandemic, a risk factor for anxiety and depression was gender which is male, while being knowledgeable about the SARS-COV-2 pandemic and having a lower academic burden were both protective factors. Conclusions: Measures are required to prevent increases in mental health problems in medical students. Our findings suggest that increasing knowledge about the SARS-COV-2 pandemic and reducing academic burden in medical students is extremely important during the SARS-COV-2 pandemic.

Prognostic Accuracy of Early Warning Scores for Clinical Deterioration in Patients With COVID-19.

Background: Early Warning Scores (EWS), including the National Early Warning Score 2 (NEWS2) and Modified NEWS (NEWS-C), have been recommended for triage decision in patients with COVID-19. However, the effectiveness of these EWS in COVID-19 has not been fully validated. The study aimed to investigate the predictive value of EWS to detect clinical deterioration in patients with COVID-19. Methods: Between February 7, 2020 and February 17, 2020, patients confirmed with COVID-19 were screened for this study. The outcomes were early deterioration of respiratory function (EDRF) and need for intensive respiratory support (IRS) during the treatment process. The EDRF was defined as changes in the respiratory component of the sequential organ failure assessment (SOFA) score at day 3 (ΔSOFAresp = SOFA resp at day 3-SOFAresp on admission), in which the positive value reflects clinical deterioration. The IRS was defined as the use of high flow nasal cannula oxygen therapy, noninvasive or invasive mechanical ventilation. The performances of EWS including NEWS, NEWS 2, NEWS-C, Modified Early Warning Scores (MEWS), Hamilton Early Warning Scores (HEWS), and quick sepsis-related organ failure assessment (qSOFA) for predicting EDRF and IRS were compared using the area under the receiver operating characteristic curve (AUROC). Results: A total of 116 patients were included in this study. Of them, 27 patients (23.3%) developed EDRF and 24 patients (20.7%) required IRS. Among these EWS, NEWS-C was the most accurate scoring system for predicting EDRF [AUROC 0.79 (95% CI, 0.69-0.89)] and IRS [AUROC 0.89 (95% CI, 0.82-0.96)], while NEWS 2 had the lowest accuracy in predicting EDRF [AUROC 0.59 (95% CI, 0.46-0.720)] and IRS [AUROC 0.69 (95% CI, 0.57-0.81)]. A NEWS-C ≥ 9 had a sensitivity of 59.3% and a specificity of 85.4% for predicting EDRF. For predicting IRS, a NEWS-C ≥ 9 had a sensitivity of 75% and a specificity of 88%. Conclusions: The NEWS-C was the most accurate scoring system among common EWS to identify patients with COVID-19 at risk for EDRF and need for IRS. The NEWS-C could be recommended as an early triage tool for patients with COVID-19.

The preventive effect of Xuebijing injection against cytokine storm for severe patients with COVID-19: A prospective randomized controlled trial.

INTRODUCTION: COVID-19 is severely affecting countries globally and mortality is high. Xuebijing (XBJ) injection is widely used in the treatment of severe pneumonia and sepsis in China due to its anti-inflammatory effect and immunoregulation. This study investigated whether Xuebijing injection can prevent the cytokine storm and reduce the mortality from severe COVID-19. METHODS: This was a randomized, double-blinded trial in which 60 eligible patients were recruited from the First people's Hospital of Jingzhou from February 16 to March 25 in 2020. A total of 57 completed the trial, 3 dropped out. The treatment group received routine medication plus Xuebijing injection while the control group received routine medication plus saline. RESULTS: The secretion of interleukin-6(IL-6), interleukin-8(IL-8) and tumor necrosis factor-α(TNF-α) was suppressed significantly (P < 0.05) by Xuebijing. After 14 days treatment, lymphocyte levels in Xuebijing group was substantially higher than control, C-reactive protein (CRP) level in Xuebijing group was remarkably lower. The 28-day mortality was not significantly different between the two group. After 14 days of treatment, there were significant differences in the rate of mechanical ventilation, rate of septic shock, the proportion of patients severely affected who became critically ill, the duration of improvement of main clinical symptoms (P < 0.05) and the length of ICU hospitalization stay (P < 0.01) for the Xuebijing group compared with controls. No serious adverse reactions were identified in either group. CONCLUSIONS: This study demonstrates that Xuebijing injection may suppress the cytokine storm in severe COVID-19 patients by regulating the secretion of pro- inflammatory cytokine IL-6, IL-8 and TNF -α. However, Xuebijing did not significantly reduce the 28-day mortality.

Pre-existing Health Conditions and Epicardial Adipose Tissue Volume: Potential Risk Factors for Myocardial Injury in COVID-19 Patients.

Background: Myocardial injury is a life-threatening complication of coronavirus disease 2019 (COVID-19). Pre-existing health conditions and early morphological alterations may precipitate cardiac injury and dysfunction after contracting the virus. The current study aimed at assessing potential risk factors for COVID-19 cardiac complications in patients with pre-existing conditions and imaging predictors. Methods and Results: The multi-center, retrospective cohort study consecutively enrolled 400 patients with lab-confirmed COVID-19 in six Chinese hospitals remote to the Wuhan epicenter. Patients were diagnosed with or without the complication of myocardial injury by history and cardiac biomarker Troponin I/T (TnI/T) elevation above the 99th percentile upper reference limit. The majority of COVID-19 patients with myocardial injury exhibited pre-existing health conditions, such as hypertension, diabetes, hypercholesterolemia, and coronary disease. They had increased levels of the inflammatory cytokine interleukin-6 and more in-hospital adverse events (admission to an intensive care unit, invasive mechanical ventilation, or death). Chest CT scan on admission demonstrated that COVID-19 patients with myocardial injury had higher epicardial adipose tissue volume ([EATV] 139.1 (83.8-195.9) vs. 92.6 (76.2-134.4) cm2; P = 0.036). The optimal EATV cut-off value (137.1 cm2) served as a useful factor for assessing myocardial injury, which yielded sensitivity and specificity of 55.0% (95%CI, 32.0-76.2%) and 77.4% (95%CI, 71.6-82.3%) in adverse cardiac events, respectively. Multivariate logistic regression analysis showed that EATV over 137.1 cm2 was a strong independent predictor for myocardial injury in patients with COVID-19 [OR 3.058, (95%CI, 1.032-9.063); P = 0.044]. Conclusions: Augmented EATV on admission chest CT scan, together with the pre-existing health conditions (hypertension, diabetes, and hyperlipidemia) and inflammatory cytokine production, is associated with increased myocardial injury and mortality in COVID-19 patients. Assessment of pre-existing conditions and chest CT scan EATV on admission may provide a threshold point potentially useful for predicting cardiovascular complications of COVID-19.

Epidemic Dynamics and Clinical Features of COVID-19 and Government Measures to Control Disease Transmission in Southern Hainan Island, China (preprint)

Objective: The objective of this study is to determine the epidemic dynamics and clinical features of COVID-19 in southern Hainan Island, China, and provide experience for other tropical areas of the world. Methods: This retrospective study included confirmed cases of COVID-19 in southern Hainan. All enrolled patients were treated in Sanya, and data on epidemiological and clinical features of the disease and infection prevention and control measures adopted by the local government during the epidemic were collected. Results: Of the 74 cases, 71 (95.95%) were imported from Wuhan, Hubei Province (47, 63.51%), other cities in Hubei Province (11, 14.86%), or provinces other than Hubei and Hainan (13, 17.57%). Three (4.06%) patients were infected in southern Hainan, including one autochthonous case in Sanya. Fifty-four cases (72.97%) were detected in Sanya, and 27 cases (27.03%) were diagnosed in other cities. The rate of severe or critical cases was 28.38% (21/74), and mortality was 2.7% (2/74). The serum lactate levels and base excess of severe-critical patients were higher than those of patients with mild-moderate disease. Multivariate logistic regression analysis showed that chronic conditions were risk factors for severe and critical COVID-19. Seventy-four patients were diagnosed with COVID-19 over a 22-day period in Sanya, and the epidemic period in the city was 48 days. The outbreak was controlled rapidly because the local government adopted strict infection prevention and control measures. Conclusions: The clinical characteristics of COVID-19 in Hainan Island were similar to those reported in other regions. In Sanya, the rate of severe and very severe cases was higher than in other regions; however, most cases were imported, and there was only one autochthonous case. The rapid control of the outbreak in Sanya may be related to the tropical climate, adoption of strict infection prevention and control measures, daily reporting of new cases, increased public awareness about the epidemic, and other emergency actions implemented by the local government.