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1.
IEEE Access ; 10: 23167-23185, 2022.
Article in English | MEDLINE | ID: covidwho-1752326

ABSTRACT

Deep learning-based Computer-Aided Diagnosis has gained immense attention in recent years due to its capability to enhance diagnostic performance and elucidate complex clinical tasks. However, conventional supervised deep learning models are incapable of recognizing novel diseases that do not exist in the training dataset. Automated early-stage detection of novel infectious diseases can be vital in controlling their rapid spread. Moreover, the development of a conventional CAD model is only possible after disease outbreaks and datasets become available for training (viz. COVID-19 outbreak). Since novel diseases are unknown and cannot be included in training data, it is challenging to recognize them through existing supervised deep learning models. Even after data becomes available, recognizing new classes with conventional models requires a complete extensive re-training. The present study is the first to report this problem and propose a novel solution to it. In this study, we propose a new class of CAD models, i.e., Deep-Precognitive Diagnosis, wherein artificial agents are enabled to identify unknown diseases that have the potential to cause a pandemic in the future. A de novo biologically-inspired Conv-Fuzzy network is developed. Experimental results show that the model trained to classify Chest X-Ray (CXR) scans into normal and bacterial pneumonia detected a novel disease during testing, unseen by it in the training sample and confirmed to be COVID-19 later. The model is also tested on SARS-CoV-1 and MERS-CoV samples as unseen diseases and achieved state-of-the-art accuracy. The proposed model eliminates the need for model re-training by creating a new class in real-time for the detected novel disease, thus classifying it on all subsequent occurrences. Second, the model addresses the challenge of limited labeled data availability, which renders most supervised learning techniques ineffective and establishes that modified fuzzy classifiers can achieve high accuracy on image classification tasks.

2.
Immun Ageing ; 19(1): 12, 2022 Mar 05.
Article in English | MEDLINE | ID: covidwho-1724508

ABSTRACT

BACKGROUND: COVID-19 patients may experience "cytokine storm" when human immune system produces excessive cytokines/chemokines. However, it remains unclear whether early responses of inflammatory cytokines would lead to high or low titers of anti-SARS-CoV-2 antibodies. METHODS: This retrospective study enrolled a cohort of 272 hospitalized patients with laboratory-confirmed SARS-CoV-2. Laboratory assessments of serum cytokines (IL-2R, IL-6, IL-8, IL-10, TNF-α), anti-SARS-CoV-2 IgG/IgM antibodies, and peripheral blood biomarkers were conducted during hospitalization. RESULTS: At hospital admission, 36.4% patients were severely ill, 51.5% patients were ≥ 65 years, and 60.3% patients had comorbidities. Higher levels of IL-2R and IL-6 were observed in older patients (≥65 years). Significant differences of IL-2R (week 2 to week ≥5 from symptom onset), IL-6 (week 1 to week ≥5), IL-8 (week 2 to week ≥5), and IL-10 (week 1 to week 3) were observed between moderately-ill and severely ill patients. Anti-SARS-CoV-2 IgG titers were significantly higher in severely ill patients than in moderately ill patients, but such difference was not observed for IgM. High titers of early-stage IL-6, IL-8, and TNF-α (≤2 weeks after symptom onset) were positively correlated with high titers of late-stage IgG (≥5 weeks after symptom onset). Deaths were mostly observed in severely ill older patients (45.9%). Survival analyses revealed risk factors of patient age, baseline COVID-19 severity, and baseline IL-6 that affected survival time, especially in severely ill older patients. CONCLUSION: Early responses of elevated cytokines such as IL-6 reflect the active immune responses, leading to high titers of IgG antibodies against COVID-19.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-319368

ABSTRACT

COVID-19 has hit hard on the global community, and organizations are working diligently to cope with the new norm of "work from home". However, the volume of remote work is unprecedented and creates opportunities for cyber attackers to penetrate home computers. Attackers have been leveraging websites with COVID-19 related names, dubbed COVID-19 themed malicious websites. These websites mostly contain false information, fake forms, fraudulent payments, scams, or malicious payloads to steal sensitive information or infect victims' computers. In this paper, we present a data-driven study on characterizing and detecting COVID-19 themed malicious websites. Our characterization study shows that attackers are agile and are deceptively crafty in designing geolocation targeted websites, often leveraging popular domain registrars and top-level domains. Our detection study shows that the Random Forest classifier can detect COVID-19 themed malicious websites based on the lexical and WHOIS features defined in this paper, achieving a 98% accuracy and 2.7% false-positive rate.

4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-319367

ABSTRACT

COVID-19 (Coronavirus) hit the global society and economy with a big surprise. In particular, work-from-home has become a new norm for employees. Despite the fact that COVID-19 can equally attack innocent people and cybercriminals, it is ironic to see surges in cyberattacks leveraging COVID-19 as a theme, dubbed COVID-19 themed cyberattacks or COVID-19 attacks for short, which represent a new phenomenon that has yet to be systematically understood. In this paper, we make the first step towards fully characterizing the landscape of these attacks, including their sophistication via the Cyber Kill Chain model. We also explore the solution space of defenses against these attacks.

5.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-315190

ABSTRACT

Online exams have become widely used to evaluate students' performance in mastering knowledge in recent years, especially during the pandemic of COVID-19. However, it is challenging to conduct proctoring for online exams due to the lack of face-to-face interaction. Also, prior research has shown that online exams are more vulnerable to various cheating behaviors, which can damage their credibility. This paper presents a novel visual analytics approach to facilitate the proctoring of online exams by analyzing the exam video records and mouse movement data of each student. Specifically, we detect and visualize suspected head and mouse movements of students in three levels of detail, which provides course instructors and teachers with convenient, efficient and reliable proctoring for online exams. Our extensive evaluations, including usage scenarios, a carefully-designed user study and expert interviews, demonstrate the effectiveness and usability of our approach.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324761

ABSTRACT

Background: : In the recent outbreak of novel coronavirus infection worldwide, the risk of thrombosis and bleeding should be concerned. Objectives: We aimed to observe the dynamic changes of D-dimer levels during disease progression to evaluate their value for thrombosis. Methods: : In this study, we report the clinical and laboratory results of 57 patients with confirmed COVID-19 pneumonia and 46 patients with confirmed community-acquired bacterial pneumonia (CAP). And their concentrations of D-dimer, infection-related biomarkers, and conventional coagulation were retrospectively analyzed. Results: : On admission, both in COVID-19 patients and CAP patients, D-dimer levels were significantly increased, and compared with CAP patients, D-Dimer levels were higher in COVID-19 patients (P<0.05). Besides, we found that in COVID-19 patients, D-dimer were related with markers of inflammation, especially with hsCRP (R=0.426, P<0.05), and after treatments, D-dimer levels decreased which was synchronous with hsCRP levels in patients with good clinical prognosis, but there were still some patients with anomalous increasing D-dimer levels after therapy. Conclusions: : Elevated baseline D-dimer levels are associated with inflammation in COVID-19 patients, and the abnormal changes of D-dimer and inflammatory factors suggest that anticoagulant therapy might be needed.

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-324313

ABSTRACT

HBV infection is a major global health burden that needs novel immunotherapeutic approaches. Herein, we show that heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) is a novel drug target for HBV infection. We reveal the new target with highly selective probes of PAC5, a natural sesquiterpene derivative. PAC5 show potent anti-HBV activity in vivo and in vitro. Further studies on its mode of action indicate that PAC5 binds to the residue Asp49 and a deep groove in the RNA recognition motif1 (RRM1) region of hnRNPA2B1. PAC5-bound hnRNPA2B1 is activated, dimerized, and translocated to the cytoplasm where it activates the TBK1-IRF3 pathway, leading to the production of type I interferons (IFNs). Furthermore, PAC5 also suppresses other viral replications, such as SARS-CoV-2 and vesicular stomatitis virus (VSV). Our results indicate that PAC5 is the first small molecule agonist of hnRNPA2B1, a drug target potentially valid for broad-spectrum viral infections, providing a novel strategy for viral immunotherapy.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321460

ABSTRACT

Background: Aged people is more susceptible and vulnerable to COVID-19 pneumonia. As the “super-elderly” group, octogenarian COVID-19 patients is not rare in current world-wide common healthy event. Object: To describe clinical features in octogenarian with severe COVID-19. And try to find out the differences with other non-octogenarian adult patients. Materials: and Methods: We studied a small cohort of octogenarian COVID-19 patients at a hospital in Wuhan from 10 February to 15 March. We recorded interested clinical data including chest CT in the octogenarian patients. In order to know the differences of clinical characteristics between octogenarian and other adult patients, we included the number of non-octogenarian patients cohort as ratio of 1:3. Result: For octogenarian patients, the age is 83.33±3.08 and 4 are female (4/6,66.7%). For non-octogenarian patients, the age is 60.72±8.28 years and 5 are female(5/18, 27.8%). and 59% were men. Compared non-octogenarian patients, octogenarian patients’ hospital stay duration is significantly longer ( p =0.0052*). WBC is obvious elevated in octogenarian( p =0.0494*). BUN ( p =0.0377*) and Cr ( p =0.0112*) is with obvious differences between two group patients. No obvious differences in CT findings between two groups. Conclusion: The severe COVID-19 pneumonia octogenarian may have more chance to combined with bacterial infection. Octogenarian has worse baseline kidney function than non-octogenarian. In individual cases, the broader lesion and more lesion types may be found in octogenarian CT image.

9.
Chinese Journal of Nosocomiology ; 31(19):2891-2895, 2021.
Article in Chinese | CAB Abstracts | ID: covidwho-1519490

ABSTRACT

OBJECTIVE To evaluate the implementation of normalization prevention and control measures for the COVID-2019 epidemic by quantitative assessment, and to evaluated the effectiveness of epidemic prevention and control and its impact on the quality of nosocomial infection management. METHODS The infection control measures of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology were summarized and refined them into 16 quantitative assessment indicators, which will be inspected and assessed throughout the hospital from from Jul. to Dec. 2020. Data on epidemic prevention and control, incidence of nosocomial infection, hand hygiene related data during the same period were collected. RESULTS No confirmed cases of novel coronavirus pneumonia were found, and no asymptomatic infection cases were found to infect others. The incidence of nosocomial infection from July to December 2020 decreased compared with the same period in 2019. Stratified analysis showed that the infection of upper respiratory tract, urinary tract and gastrointestinal tract were significantly reduced, while there was no significant change in the infection rate of the type I incision surgical sites, the incidence of intravascular catheter related bloodstream infection, the incidence of ventilator-associated pneumonia and the incidence of catheter-related urinary tract infection. The compliance of hand hygiene, the accuracy of hand hygiene and the standard rate of hand disinfectant consumption were significantly improved, while there was no significant change in the consumption of dry hand tissue and hand sanitizer. CONCLUSION Quantitative assessment can effectively evaluate the implementation of normalized prevention and control measures of epidemic situation. The timely detection and elimination of potential epidemic hazards will have a positive impact on the improvement of the quality of nosocomial infection management.

10.
Comput Biol Med ; 137: 104834, 2021 10.
Article in English | MEDLINE | ID: covidwho-1385350

ABSTRACT

Novel coronavirus disease 2019 (COVID-19) is an infectious disease that spreads very rapidly and threatens the health of billions of people worldwide. With the number of cases increasing rapidly, most countries are facing the problem of a shortage of testing kits and resources, and it is necessary to use other diagnostic methods as an alternative to these test kits. In this paper, we propose a convolutional neural network (CNN) model (ULNet) to detect COVID-19 using chest X-ray images. The proposed architecture is constructed by adding a new downsampling side, skip connections and fully connected layers on the basis of U-net. Because the shape of the network is similar to UL, it is named ULNet. This model is trained and tested on a publicly available Kaggle dataset (consisting of a combination of 219 COVID-19, 1314 normal and 1345 viral pneumonia chest X-ray images), including binary classification (COVID-19 vs. Normal) and multiclass classification (COVID-19 vs. Normal vs. Viral Pneumonia). The accuracy of the proposed model in the detection of COVID-19 in the binary-class and multiclass tasks is 99.53% and 95.35%, respectively. Based on these promising results, this method is expected to help doctors diagnose and detect COVID-19. Overall, our ULNet provides a quick method for identifying patients with COVID-19, which is conducive to the control of the COVID-19 pandemic.


Subject(s)
COVID-19 , Pandemics , Humans , SARS-CoV-2 , X-Rays
11.
BMC Med ; 19(1): 191, 2021 08 09.
Article in English | MEDLINE | ID: covidwho-1344106

ABSTRACT

BACKGROUND: Knowledge about the 1-year outcome of COVID-19 is limited. The aim of this study was to follow-up and evaluate lung abnormalities on serial computed tomography (CT) scans in patients with COVID-19 after hospital discharge. METHODS: A prospective cohort study of patients with COVID-19 from the First Affiliated Hospital, Zhejiang University School of Medicine was conducted, with assessments of chest CT during hospitalization and at 2 weeks, 1 month, 3 months, 6 months, and 1 year after hospital discharge. Risk factors of residual CT opacities and the influence of residual CT abnormalities on pulmonary functions at 1 year were also evaluated. RESULTS: A total of 41 patients were followed in this study. Gradual recovery after hospital discharge was confirmed by the serial CT scores. Around 47% of the patients showed residual aberration on pulmonary CT with a median CT score of 0 (interquartile range (IQR) of 0-2) at 1 year after discharge, with ground-glass opacity (GGO) with reticular pattern as the major radiologic pattern. Patients with residual radiological abnormalities were older (p = 0.01), with higher rate in current smokers (p = 0.04), higher rate in hypertensives (p = 0.05), lower SaO2 (p = 0.004), and higher prevalence of secondary bacterial infections during acute phase (p = 0.02). Multiple logistic regression analyses indicated that age was a risk factor associated with residual radiological abnormalities (OR 1.08, 95% CI 1.01-1.15, p = 0.02). Pulmonary functions of total lung capacity (p = 0.008) and residual volume (p < 0.001) were reduced in patients with residual CT abnormalities and were negatively correlated with CT scores. CONCLUSION: During 1-year follow-up after discharge, COVID-19 survivors showed continuous improvement on chest CT. However, residual lesions could still be observed and correlated with lung volume parameters. The risk of developing residual CT opacities increases with age.


Subject(s)
COVID-19 , Diabetes Mellitus, Type 2 , Adult , COVID-19/diagnostic imaging , Female , Follow-Up Studies , Humans , Male , Middle Aged , Prospective Studies , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed
12.
JAMA Netw Open ; 4(6): e2111621, 2021 06 01.
Article in English | MEDLINE | ID: covidwho-1251879

ABSTRACT

Importance: The influence of the COVID-19 pandemic on fertility rates has been suggested in the lay press and anticipated based on documented decreases in fertility and pregnancy rates during previous major societal and economic shifts. Anticipatory planning for birth rates is important for health care systems and government agencies to accurately estimate size of economy and model working and/or aging populations. Objective: To use projection modeling based on electronic health care records in a large US university medical center to estimate changes in pregnancy and birth rates prior to and after the COVID-19 pandemic societal lockdowns. Design, Setting, and Participants: This cohort study included all pregnancy episodes within a single US academic health care system retrospectively from 2017 and modeled prospectively to 2021. Data were analyzed September 2021. Exposures: Pre- and post-COVID-19 pandemic societal shutdown measures. Main Outcomes and Measures: The primary outcome was number of new pregnancy episodes initiated within the health care system and use of those episodes to project birth volumes. Interrupted time series analysis was used to assess the degree to which COVID-19 societal changes may have factored into pregnancy episode volume. Potential reasons for the changes in volumes were compared with historical pregnancy volumes, including delays in starting prenatal care, interruptions in reproductive endocrinology and infertility services, and preterm birth rates. Results: This cohort study documented a steadily increasing number of pregnancy episodes over the study period, from 4100 pregnancies in 2017 to 4620 in 2020 (28 284 total pregnancies; median maternal [interquartile range] age, 30 [27-34] years; 18 728 [66.2%] White women, 3794 [13.4%] Black women; 2177 [7.7%] Asian women). A 14% reduction in pregnancy episode initiation was observed after the societal shutdown of the COVID-19 pandemic (risk ratio, 0.86; 95% CI, 0.79-0.92; P < .001). This decrease appeared to be due to a decrease in conceptions that followed the March 15 mandated COVID-19 pandemic societal shutdown. Prospective modeling of pregnancies currently suggests that a birth volume surge can be anticipated in summer 2021. Conclusions and Relevance: This cohort study using electronic medical record surveillance found an initial decline in births associated with the COVID-19 pandemic societal changes and an anticipated increase in birth volume. Future studies can further explore how pregnancy episode volume changes can be monitored and birth rates projected in real-time during major societal events.


Subject(s)
Birth Rate , COVID-19 , Pandemics , Physical Distancing , Social Isolation , Academic Medical Centers , Adult , Birth Rate/trends , COVID-19/prevention & control , Electronic Health Records , Female , Fertility , Forecasting , Humans , Interrupted Time Series Analysis , Pregnancy , Prospective Studies , Retrospective Studies , SARS-CoV-2 , United States , Universities
13.
Knowledge-Based Systems ; 223:107041, 2021.
Article in English | ScienceDirect | ID: covidwho-1188850

ABSTRACT

The occurrence of natural disasters or accidents causes the obstruction or interruption of road traffic connectivity and affects the transportation of essential materials, especially for cross-regional delivery under emergency situations. Affected by COVID-19, government administrators establish cross-regional quarantine roadblocks to reduce the risk of virus transmission caused by cross-regional transportation. In this study, we propose an emergency logistics network design problem with resource sharing under collaborative alliances. We construct a state–space–time network-based bi-objective mixed integer programming model to optimize the vehicle routes in order to meet customer demands for essential materials with the lowest cost and highest emergency response speed under limited transportation resources. A two-stage hybrid heuristic algorithm is then proposed to find good-quality solutions for the problem. Clustering results are obtained using a 3D k-means clustering algorithm with the consideration of time and space indices. The optimization of the initial population generated by the improved Clarke and Wright saving method and improved nondominated sorting genetic algorithm-II with elite retention strategy provides stable and excellent performance for the searching of Pareto frontier. The cost difference of the entire emergency logistics network before and after collaboration, i.e., the profit, is fairly allocated to the participants (i.e., logistics service providers) through the Shapley value method. A real-world case in Chongqing City, China is used to validate the effectiveness of the proposed model and algorithm. This study contributes to smart transportation and logistics system in emergency planning and has particular implications for the optimal response of existing logistics system to the current COVID-19 pandemic.

15.
Int J Environ Res Public Health ; 18(7)2021 03 30.
Article in English | MEDLINE | ID: covidwho-1161042

ABSTRACT

Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. The study uses the retrospective analysis of space-time scan statistic to detect the clusters of COVID-19 in mainland China with a different maximum clustering radius at the family-level based on case dates of onset. The results show that the detected clusters vary with the clustering radius. Forty-three space-time clusters were detected with a maximum clustering radius of 100 km and 88 clusters with a maximum clustering radius of 10 km from 2 December 2019 to 20 June 2020. Using a smaller clustering radius may identify finer clusters. Hubei has the most clusters regardless of scale. In addition, most of the clusters were generated in February. That indicates China's COVID-19 epidemic prevention and control strategy is effective, and they have successfully prevented the virus from spreading from Hubei to other provinces over time. Well-developed provinces or cities, which have larger populations and developed transportation networks, are more likely to generate space-time clusters. The analysis based on the data of cases from onset may detect the start times of clusters seven days earlier than similar research based on diagnosis dates. Our analysis of space-time clustering based on the data of cases on the family-level can be reproduced in other countries that are still seriously affected by the epidemic such as the USA, India, and Brazil, thus providing them with more precise signals of clustering.


Subject(s)
COVID-19 , Brazil , China/epidemiology , Cities , Cluster Analysis , Humans , India , Retrospective Studies , SARS-CoV-2 , Spatio-Temporal Analysis
16.
Psychol Health Med ; 27(2): 312-324, 2022 02.
Article in English | MEDLINE | ID: covidwho-1155733

ABSTRACT

The aims of the study were to assess the contribution of resilience, coping style, and COVID-19 stress on the quality of life (QOL) in frontline health care workers (HCWs). The study was a cross-sectional surveyperformed among 309 HCWs in a tertiaryhospital during the outbreak of COVID-19 in China. Data were collected through an anonymous, self-rated questionnaire, including demographic data, a 10-item COVID-19 stress questionnaire, Generic QOL Inventory-74, Connor-Davidson Resilience Scale, and the Simplified Coping Style Questionnaire. Hierarchical regression was used to analyse the relationship between the study variables and the QOL. Among the 309 participants, resilience and active coping were positively correlated with the QOL (P<0.001), whereas, working in confirmed case wards, COVID-19 stress, and passive coping were negatively correlated with the QOL (P<0.001). Resilience and the active coping were negatively correlated with COVID-19 stress (P<0.001). Resilience, coping style,and COVID-19 stressaccounted for 32%, 13%, and 8% of the variance in predicting the Global QOL, respectively. In conclusion, working in confirmed COVID-19 case wards and COVID-19 stress impaired the QOL in HCWs. Psychological intervention to improve the resilience and coping style, and reduce COVID-19 stress are important in improving the QOL and mental health of HCWs.


Subject(s)
COVID-19 , Resilience, Psychological , Adaptation, Psychological , COVID-19/epidemiology , Cross-Sectional Studies , Health Personnel/psychology , Humans , Quality of Life , SARS-CoV-2
17.
Proc Natl Acad Sci U S A ; 118(15)2021 04 13.
Article in English | MEDLINE | ID: covidwho-1152940

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) research and antiviral discovery are hampered by the lack of a cell-based virus replication system that can be readily adopted without biosafety level 3 (BSL-3) restrictions. Here, the construction of a noninfectious SARS-CoV-2 reporter replicon and its application in deciphering viral replication mechanisms and evaluating SARS-CoV-2 inhibitors are presented. The replicon genome is replication competent but does not produce progeny virions. Its replication can be inhibited by RdRp mutations or by known SARS-CoV-2 antiviral compounds. Using this system, a high-throughput antiviral assay has also been developed. Significant differences in potencies of several SARS-CoV-2 inhibitors in different cell lines were observed, which highlight the challenges of discovering antivirals capable of inhibiting viral replication in vivo and the importance of testing compounds in multiple cell culture models. The generation of a SARS-CoV-2 replicon provides a powerful platform to expand the global research effort to combat COVID-19.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/virology , High-Throughput Screening Assays/methods , Replicon/drug effects , SARS-CoV-2/drug effects , A549 Cells , Animals , Chlorocebus aethiops , Coronavirus RNA-Dependent RNA Polymerase/genetics , HEK293 Cells , Humans , Replicon/genetics , SARS-CoV-2/genetics , Vero Cells , Virus Replication/drug effects
18.
Open Forum Infect Dis ; 7(6): ofaa220, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-1109310

ABSTRACT

Secondary bacterial infections occurred in 13.9% (5 of 36) of critical ill patients with coronavirus disease 2019. All 5 patients had been admitted to intensive care unit and received mechanical ventilation before developing bacterial infection. Active surveillance of culture should be performed for critically ill patients. Prevention of nosocomial infection should to be taken seriously.

19.
Aging (Albany NY) ; 13(5): 7020-7034, 2021 02 26.
Article in English | MEDLINE | ID: covidwho-1106628

ABSTRACT

BACKGROUND: The inflammatory reaction is the main cause of acute respiratory distress syndrome and multiple organ failure in patients with Coronavirus disease 2019, especially those with severe and critical illness. Several studies suggested that high-dose vitamin C reduced inflammatory reaction associated with sepsis and acute respiratory distress syndrome. This study aimed to determine the efficacy and safety of high-dose vitamin C in Coronavirus disease 2019. METHODS: We included 76 patients with Coronavirus disease 2019, classified into the high-dose vitamin C group (loading dose of 6g intravenous infusion per 12 hr on the first day, and 6g once for the following 4 days, n=46) and the standard therapy group (standard therapy alone, n=30). RESULTS: The risk of 28-day mortality was reduced for the high-dose vitamin C versus the standard therapy group (HR=0.14, 95% CI, 0.03-0.72). Oxygen support status was improved more with high-dose vitamin C than standard therapy (63.9% vs 36.1%). No safety events were associated with high-dose vitamin C therapy. CONCLUSION: High-dose vitamin C may reduce the mortality and improve oxygen support status in patients with Coronavirus disease 2019 without adverse events.


Subject(s)
Ascorbic Acid/therapeutic use , COVID-19/drug therapy , Vitamins/therapeutic use , Aged , Ascorbic Acid/administration & dosage , Ascorbic Acid/adverse effects , COVID-19/diagnosis , Dose-Response Relationship, Drug , Female , Humans , Male , Middle Aged , Retrospective Studies , SARS-CoV-2/drug effects , SARS-CoV-2/isolation & purification , Treatment Outcome , Vitamins/administration & dosage , Vitamins/adverse effects
20.
J Med Virol ; 93(7): 4446-4453, 2021 07.
Article in English | MEDLINE | ID: covidwho-1064383

ABSTRACT

This study aims to comparatively analyze the therapeutic efficacy upon multiple medication plans over lopinavir/ritonavir (LPV/r), arbidol (ARB), and methylprednisolone on patients with coronavirus disease 2019 (COVID-19). Totally, 75 COVID-19 patients admitted to The First Affiliated Hospital, Zhejiang University School of Medicine from January 22, 2020 to February 29, 2020 were recruited and grouped based on whether or not LPV/r and ARB were jointly used and whether or not methylprednisolone was used. Indexes including body temperature, time for nucleic acid negative conversion, hospital stays, and laboratory indexes were examined and compared. For all patients, there were no significant differences in the change of body temperature, the time for negative conversion, and hospital stays whether LPV/r and ARB were jointly used or not. While for severe and critically severe patients, methylprednisolone noticeably reduced the time for negative conversion. Meanwhile, the clinical efficacy was superior on patients receiving methylprednisolone within 3 days upon admission, and the duration of hospital stays was much shorter when methylprednisolone was given at a total dose of 0-400 mg than a higher dose of >400 mg if all patients received a similar dose per day. Nonetheless, no significant changes across hepatic, renal, and myocardial function indexes were observed. LPV/r combined with ARB produced no noticeably better effect on COVID-19 patients relative to the single-agent treatment. Additionally, methylprednisolone was efficient in severe and critically severe cases, and superior efficacy could be realized upon its early, appropriate, and short-term application.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/drug therapy , Indoles/therapeutic use , Lopinavir/therapeutic use , Methylprednisolone/therapeutic use , Ritonavir/therapeutic use , China , Drug Combinations , Female , Fever/drug therapy , Humans , Length of Stay , Male , Middle Aged , Retrospective Studies , SARS-CoV-2/drug effects
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