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1.
Journal of Infection and Chemotherapy ; 2021.
Article | WHO COVID | ID: covidwho-1091770

ABSTRACT

Introduction Coronavirus disease-2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) swept rapidly throughout the world So far, no therapeutics have yet proven to be effective Ribavirin was recommended for the treatment of COVID-19 in China because of its in vitro activity However, evidence supporting its clinical use with good efficacy is still lacking Methods A total of 208 confirmed severe COVID-19 patients who were hospitalized in Wuhan Union West Campus between 1 February 2020 and 10 March 2020 were enrolled in the retrospective study Patients were divided into two groups based on the use of ribavirin The primary endpoint was the time to clinical improvement The secondary endpoints included mortality, survival time, time to throat swab SARS-CoV-2 nucleic acid negative conversion, and the length of hospital stay Results 68 patients were treated with ribavirin while 140 not There were no significant between-group differences in demographic characteristics, baseline laboratory test results, treatment, and distribution of ordinal scale scores at enrollment, except for coexisting diseases especially cancer (ribavirin group vs no ribavirin group, P = 0 01) Treatment with ribavirin was not associated with a difference in the time to clinical improvement (P = 0 48, HR = 0 88, 95% CI = 0 63-1 25) There were also no significant differences between-group in SARS-CoV-2 nucleic acid negative conversion, mortality, survival time, and the length of hospital stay Conclusions In hospitalized adult patients with severe COVID-19, no significant benefit was observed with ribavirin treatment

2.
PLoS One ; 16(2): e0246715, 2021.
Article in English | MEDLINE | ID: covidwho-1079370

ABSTRACT

Control measures are necessary to contain the spread of serious infectious diseases such as COVID-19, especially in its early stage. We propose to use temporal reproduction number an extension of effective reproduction number, to evaluate the efficacy of control measures, and establish a Monte-Carlo method to estimate the temporal reproduction number without complete information about symptom onsets. The province-level analysis indicates that the effective reproduction numbers of the majority of provinces in mainland China got down to < 1 just by one week from the setting of control measures, and the temporal reproduction number of the week [15 Feb, 21 Feb] is only about 0.18. It is therefore likely that Chinese control measures on COVID-19 are effective and efficient, though more research needs to be performed.


Subject(s)
Basic Reproduction Number , /epidemiology , Algorithms , China/epidemiology , Humans , Infection Control , /isolation & purification
3.
MedComm ; n/a(n/a), 2021.
Article | WHO COVID | ID: covidwho-1062116

ABSTRACT

Abstract Novel Coronavirus disease 2019 (COVID-19) has spread rapidly around the world Individuals with immune dysregulation and/or on immunosuppressive therapy, such as rheumatic patients, are considered at greater risk for infections However, the risks of patients with each subcategory of rheumatic diseases have not been reported Here, we identified 100 rheumatic patients from 18,786 COVID-19 patients hospitalized in 23 centers affiliated to Hubei COVID-19 Rheumatology Alliance between January 1 and April 1, 2020 Demographic information, medical history, length of hospital stay, classification of disease severity, symptoms and signs, laboratory tests, disease outcome, computed tomography, and treatments information were collected Compared to gout and ankylosing spondylitis (AS) patients, patients with connective tissue disease (CTD) tend to be more severe after COVID-19 infection (p = 0 081) CTD patients also had lower lymphocyte counts, hemoglobin, and platelet counts (p values were 0 033, < 0 001, and 0 071, respectively) Hydroxychloroquine therapy and low- to medium-dose glucocorticoids before COVID-19 diagnosis reduced the progression of COVID-19 to severe/critical conditions (p = 0 001 for hydroxychloroquine;p = 0 006 for glucocorticoids) Our data suggests that COVID-19 in CTD patients may be more severe compared to patients with AS or gout

4.
Am J Clin Nutr ; 2021 Jan 29.
Article in English | MEDLINE | ID: covidwho-1054262

ABSTRACT

BACKGROUND: Previous studies have related vitamin D supplementation to a lower risk of acute respiratory tract infection. Emerging evidence suggests that vitamin D insufficiency is related to a higher risk of coronavirus disease 2019 (COVID-19) infection. OBJECTIVES: We aimed to investigate the prospective association between habitual use of vitamin D supplements and risk of COVID-19 infection, and assess whether such an association differed according to the different levels of circulating and genetically predicted vitamin D. METHODS: This study included 8297 adults who have records of COVID-19 test results from UK Biobank (from 16 March 2020 to 29 June 2020). The use of vitamin D supplements, circulating vitamin D levels, and main covariates were measured at baseline (2006-2010). Genetically predicted vitamin D levels were evaluated by genetic risk score. RESULTS: After adjustment for covariates, the habitual use of vitamin D supplements was significantly associated with a 34% lower risk of COVID-19 infection (OR, 0.66; 95% CI, 0.45-0.97; P = 0.034). Circulating vitamin D levels at baseline or genetically predicted vitamin D levels were not associated with the risk of COVID-19 infection. The association between the use of vitamin D supplements and the risk of COVID-19 infection did not vary according to the different levels of circulating or genetically predicted vitamin D (P-interactions = 0.75 and 0.74, respectively). CONCLUSIONS: Our findings suggest that habitual use of vitamin D supplements is related to a lower risk of COVID-19 infection, although we cannot rule out the possibility that the inverse association is due to residual confounding or selection bias. Further clinical trials are needed to verify these results.

5.
Pattern Recognition ; : 107826, 2021.
Article | WHO COVID | ID: covidwho-1033516

ABSTRACT

The current pandemic, caused by the outbreak of a novel coronavirus (COVID-19) in December 2019, has led to a global emergency that has significantly impacted economies, healthcare systems and personal wellbeing all around the world Controlling the rapidly evolving disease requires highly sensitive and specific diagnostics While RT-PCR is the most commonly used, it can take up to eight hours, and requires significant effort from healthcare professionals As such, there is a critical need for a quick and automatic diagnostic system Diagnosis from chest CT images is a promising direction However, current studies are limited by the lack of sufficient training samples, as acquiring annotated CT images is time-consuming To this end, we propose a new deep learning algorithm for the automated diagnosis of COVID-19, which only requires a few samples for training Specifically, we use contrastive learning to train an encoder which can capture expressive feature representations on large and publicly available lung datasets and adopt the prototypical network for classification We validate the efficacy of the proposed model in comparison with other competing methods on two publicly available and annotated COVID-19 CT datasets Our results demonstrate the superior performance of our model for the accurate diagnosis of COVID-19 based on chest CT images

6.
PLoS Comput Biol ; 16(12): e1008467, 2020 12.
Article in English | MEDLINE | ID: covidwho-999796

ABSTRACT

In January 2020, a COVID-19 outbreak was detected in Sichuan Province of China. Six weeks later, the outbreak was successfully contained. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of interventions in limiting SARS-CoV-2 transmission. We analyzed patient records for all laboratory-confirmed cases reported in the province for the period of January 21 to March 16, 2020. To estimate the basic and daily reproduction numbers, we used a Bayesian framework. In addition, we estimated the number of cases averted by the implemented control strategies. The outbreak resulted in 539 confirmed cases, lasted less than two months, and no further local transmission was detected after February 27. The median age of local cases was 8 years older than that of imported cases. We estimated R0 at 2.4 (95% CI: 1.6-3.7). The epidemic was self-sustained for about 3 weeks before going below the epidemic threshold 3 days after the declaration of a public health emergency by Sichuan authorities. Our findings indicate that, were the control measures be adopted four weeks later, the epidemic could have lasted 49 days longer (95% CI: 31-68 days), causing 9,216 more cases (95% CI: 1,317-25,545).


Subject(s)
/epidemiology , Disease Outbreaks , /virology , China/epidemiology , Female , Humans , Male , /isolation & purification
7.
Appl Soft Comput ; : 106885, 2020 Nov 06.
Article in English | MEDLINE | ID: covidwho-987084

ABSTRACT

The rapid detection of the novel coronavirus disease, COVID-19, has a positive effect on preventing propagation and enhancing therapeutic outcomes. This article focuses on the rapid detection of COVID-19. We propose an ensemble deep learning model for novel COVID-19 detection from CT images. 2933 lung CT images from COVID-19 patients were obtained from previous publications, authoritative media reports, and public databases. The images were preprocessed to obtain 2500 high-quality images. 2500 CT images of lung tumor and 2500 from normal lung were obtained from a hospital. Transfer learning was used to initialize model parameters and pretrain three deep convolutional neural network models: AlexNet, GoogleNet, and ResNet. These models were used for feature extraction on all images. Softmax was used as the classification algorithm of the fully connected layer. The ensemble classifier EDL-COVID was obtained via relative majority voting. Finally, the ensemble classifier was compared with three component classifiers to evaluate accuracy, sensitivity, specificity, F value, and Matthews correlation coefficient. The results showed that the overall classification performance of the ensemble model was better than that of the component classifier. The evaluation indexes were also higher. This algorithm can better meet the rapid detection requirements of the novel coronavirus disease COVID-19.

8.
IEEE Trans Med Imaging ; 39(8): 2626-2637, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-690465

ABSTRACT

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional healthcare strategy for tackling COVID-19. However, segmenting infected regions from CT slices faces several challenges, including high variation in infection characteristics, and low intensity contrast between infections and normal tissues. Further, collecting a large amount of data is impractical within a short time period, inhibiting the training of a deep model. To address these challenges, a novel COVID-19 Lung Infection Segmentation Deep Network (Inf-Net) is proposed to automatically identify infected regions from chest CT slices. In our Inf-Net, a parallel partial decoder is used to aggregate the high-level features and generate a global map. Then, the implicit reverse attention and explicit edge-attention are utilized to model the boundaries and enhance the representations. Moreover, to alleviate the shortage of labeled data, we present a semi-supervised segmentation framework based on a randomly selected propagation strategy, which only requires a few labeled images and leverages primarily unlabeled data. Our semi-supervised framework can improve the learning ability and achieve a higher performance. Extensive experiments on our COVID-SemiSeg and real CT volumes demonstrate that the proposed Inf-Net outperforms most cutting-edge segmentation models and advances the state-of-the-art performance.


Subject(s)
Coronavirus Infections/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Supervised Machine Learning , Tomography, X-Ray Computed/methods , Algorithms , Betacoronavirus , Humans , Lung/diagnostic imaging , Pandemics
9.
Lancet Rheumatol ; 2(9): e557-e564, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-623270

ABSTRACT

Background: In the ongoing COVID-19 pandemic, the susceptibility of patients with rheumatic diseases to COVID-19 remains unclear. We aimed to investigate susceptibility to COVID-19 in patients with autoimmune rheumatic diseases during the ongoing COVID-19 pandemic. Methods: We did a multicentre retrospective study of patients with autoimmune rheumatic diseases in Hubei province, the epicentre of the COVID-19 outbreak in China. Patients with rheumatic diseases were contacted through an automated telephone-based survey to investigate their susceptibility to COVID-19. Data about COVID-19 exposure or diagnosis were collected. Families with a documented history of COVID-19 exposure, as defined by having at least one family member diagnosed with COVID-19, were followed up by medical professionals to obtain detailed information, including sex, age, smoking history, past medical history, use of medications, and information related to COVID-19. Findings: Between March 20 and March 30, 2020, 6228 patients with autoimmune rheumatic diseases were included in the study. The overall rate of COVID-19 in patients with an autoimmune rheumatic disease in our study population was 0·43% (27 of 6228 patients). We identified 42 families in which COVID-19 was diagnosed between Dec 20, 2019, and March 20, 2020, in either patients with a rheumatic disease or in a family member residing at the same physical address during the outbreak. Within these 42 families, COVID-19 was diagnosed in 27 (63%) of 43 patients with a rheumatic disease and in 28 (34%) of 83 of their family members with no rheumatic disease (adjusted odds ratio [OR] 2·68 [95% CI 1·14-6·27]; p=0·023). Patients with rheumatic disease who were taking hydroxychloroquine had a lower risk of COVID-19 infection than patients taking other disease-modifying anti-rheumatic drugs (OR 0·09 [95% CI 0·01-0·94]; p=0·044). Additionally, the risk of COVID-19 was increased with age (adjusted OR 1·04 [95%CI 1·01-1·06]; p=0·0081). Interpretation: Patients with autoimmune rheumatic disease might be more susceptible to COVID-19 infection than the general population. Funding: National Natural Science Foundation of China and the Tongji Hospital Clinical Research Flagship Program.

10.
Preprint | medRxiv | ID: ppmedrxiv-20120808

ABSTRACT

BackgroundSo far, there has been no published population study on the relationship between COVID-19 infection and publics risk perception, information source, knowledge, attitude and four non-pharmaceutical interventions(NPI: hand washing, proper coughing habits, social distancing and mask wearing) during the COVID-19 outbreak in China. MethodsAn online survey of 8158 Chinese adults between 22 February to 5 March 2020 was conducted. Bivariate associations between categorical variables were examined using Fisher exact test. We also explored the determinants of four NPIs as well as their association with COVID-19 infection using logistic regression. ResultsOf 8158 adults included, 57 (0.73%) were infected with COVID-19. The overwhelming majority of respondents showed a positive attitude (99.2%), positive risk perception (99.9%) and high knowledge levels that were among the strongest predictors of four highly adopted NPIs (hand washing:96.8%; proper coughing: 93.1%; social distancing:87.1%; mask wearing:97.9%). There was an increased risk of COVID-19 infection for those who not washing hands (2.28% vs 0.65%; RR=3.53: 95%CI: 1.53-8.15; P<0.009); not practicing proper coughing (1.79% vs 0.73%; RR=2.44: 95%CI: 1.15-5.15;P=0.026); not practicing social distancing (1.52% vs 0.58%; RR=2.63:95%CI:1.48 - 4.67; P=0.002); and not wearing a mask (7.41% vs 0.6%; RR=12.38:95%CI:5.81-26.36; P<0.001). For those who did practice all other three NPIs, wearing mask was associated with significantly reduced risk of infection compared to those who did not wear a mask (0.6% vs 16.7%; p=0.035). Similarly, for those who did not practice all or part of the other three NPIs, wearing mask was also associated with significantly reduced risk of infection. In a penalised logistic regression model including all four NPIs, wearing a mask was the only significant predictor of COVID-19 infection among four NPIs (OR=7.20; 95%CI:2.24-23.11; p<0.001). ConclusionsWe found high levels of risk perception, positive attitude, desirable knowledge as well as a high level of adopting four NPIs. The relevant knowledge, risk perception and attitude were strong predictors of adapting the four NPIs. Mask wearing, among four personal NPIs, was the most effective protective measure against COVID-19 infection with added preventive effect among those who practised all or part of the other three NPIs.

11.
Head Neck ; 42(7): 1374-1381, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-305887

ABSTRACT

BACKGROUND: An increasing number of COVID-19 patients worldwide will probably need tracheostomy in an emergency or at the recovering stage of COVID-19. We explored the safe and effective management of tracheostomy in COVID-19 patients, to benefit patients and protect health care workers at the same time. METHODS: We retrospectively analyzed 11 hospitalized COVID-19 patients undergoing tracheostomy. Clinical features of patients, ventilator withdrawal after tracheostomy, surgical complications, and nosocomial infection of the health care workers associated with the tracheostomy were analyzed. RESULTS: The tracheostomy of all the 11 cases (100%) was performed successfully, including percutaneous tracheostomy of 6 cases (54.5%) and conventional open tracheostomy of 5 cases (45.5%). No severe postoperative complications occurred, and no health care workers associated with the tracheostomy are confirmed to be infected by SARS-CoV-2. CONCLUSION: Comprehensive evaluation before tracheostomy, optimized procedures during tracheostomy, and special care after tracheostomy can make the tracheostomy safe and beneficial in COVID-19 patients.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Cross Infection/prevention & control , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Occupational Health , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Tracheostomy/methods , Adult , Aged , Aged, 80 and over , China , Cohort Studies , Female , Humans , Intubation, Intratracheal , Male , Middle Aged , Minimally Invasive Surgical Procedures , Pandemics/statistics & numerical data , Retrospective Studies , Risk Assessment , Tertiary Care Centers
12.
J Am Pharm Assoc (2003) ; 60(3): 431-438.e1, 2020.
Article in English | MEDLINE | ID: covidwho-47500

ABSTRACT

OBJECTIVES: To describe the pharmacy administration and pharmaceutical care in a module hospital during the coronavirus disease 2019 (COVID-19) epidemic and provide reference for domestic and foreign pharmacists participating in the epidemic prevention and control. SETTING: The study was performed in a Jianghan module hospital constructed at the Wuhan Convention and Exhibition Center in Wuhan, China. This is 1 of the first 3 module hospitals. PRACTICE DESCRIPTION: One thousand eight hundred forty-eight patients were admitted to the Jianghan module hospital, and 1327 cases (71.81% of the total number) were cured and discharged. Pharmacists have successfully completed the tasks of purchase, storage, and free distribution of drugs worth ¥1.03 million (approximately $146,000), reviewed about 20,000 electronic orders, provided one-on-one online medication consultation for 484 patients, and held 5 lectures on rational drug use knowledge, which could help reduce irrational drug use and minimize the risk involved. PRACTICE INNOVATION: The new COVID-19 "module" pharmaceutical care model is equipped with new features such as pharmacy emergency command group, organizational structure for pharmacy administration, electronic control of drug prescription, and "zero contact" pharmaceutical care relying on the new media platform "WeChat." This platform provides relevant pharmaceutical care for patients, such as ensuring drug supply, setting up critical care drug trolleys, designing specific drug packaging bags, creating a module radio station to broadcast rational drug use information to the patients, and other aspects. EVALUATION: With the continuous improvement of the module hospital and the progress in in-depth knowledge about COVID-19, some aspects such as patient admission criteria and variety of drugs need to be adjusted depending on the actual situation. RESULTS: The pharmacists provided pharmaceutical care for 1848 patients with mild COVID-19 disease. They not only ensured the timely supply of the drugs but also reduced the incidence of drug-induced risks through medication review and guidance, thereby improving patient compliance and helping the patients rebuild their confidence in overcoming the disease. CONCLUSION: The new COVID-19 module pharmaceutical care model has played an important role in overcoming the epidemic situation of COVID-19 in China and thus can be implemented on a broader scale.


Subject(s)
Coronavirus Infections/drug therapy , Hospitals, Special/organization & administration , Pharmacists/organization & administration , Pharmacy Service, Hospital/organization & administration , Pneumonia, Viral/drug therapy , Adolescent , Adult , Aged , China/epidemiology , Coronavirus Infections/epidemiology , Hospitalization , Humans , Male , Middle Aged , Pandemics , Pharmacy Administration , Pneumonia, Viral/epidemiology , Professional Role , Young Adult
13.
J Evid Based Med ; 13(1): 3-7, 2020 Feb.
Article in English | MEDLINE | ID: covidwho-707

ABSTRACT

OBJECTIVES: To estimate the basic reproduction number of the Wuhan novel coronavirus (2019-nCoV). METHODS: Based on the susceptible-exposed-infected-removed (SEIR) compartment model and the assumption that the infectious cases with symptoms occurred before 26 January, 2020 are resulted from free propagation without intervention, we estimate the basic reproduction number of 2019-nCoV according to the reported confirmed cases and suspected cases, as well as the theoretical estimated number of infected cases by other research teams, together with some epidemiological determinants learned from the severe acute respiratory syndrome (SARS). RESULTS: The basic reproduction number fall between 2.8 and 3.3 by using the real-time reports on the number of 2019-nCoV-infected cases from People's Daily in China and fall between 3.2 and 3.9 on the basis of the predicted number of infected cases from international colleagues. CONCLUSIONS: The early transmission ability of 2019-nCoV is close to or slightly higher than SARS. It is a controllable disease with moderate to high transmissibility. Timely and effective control measures are needed to prevent the further transmissions.


Subject(s)
Basic Reproduction Number , Betacoronavirus , Coronavirus Infections , Pneumonia, Viral , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Forecasting , Humans , Models, Theoretical , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission
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