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1.
Midwifery ; 109: 103316, 2022 Mar 19.
Article in English | MEDLINE | ID: covidwho-1747679

ABSTRACT

OBJECTIVE: We aimed to explore the lived experiences of informal caregivers for pregnant women seeking scheduled antenatal care during the early stage of China's COVID-19 lockdown and potential measures to address the challenges. DESIGN: This is a phenomenological qualitative study. SETTING: The study was carried out in a leading teaching hospital in Southwest China. PARTICIPANTS: We recruited 15 informal caregivers for healthy pregnant women on routine antenatal visits about six months after China launched the city-wide lockdown and other control measures for COVID-19, including 10 males and 5 females with diverse demographic backgrounds. MEASURES AND FINDINGS: The research team developed a demographic form and an interview outline with key questions, conducted semi-structured interviews with the informal caregivers, and analyzed the data using the Colazzie's method. Five themes of lived experiences were revealed, i.e., increased caregiving burdens, disruption of routines in family life, lack of accurate information and knowledge, active role adjustment, and positive attitudes and coping in a difficult time. Some caregivers reacted positively to the lockdown experience and saw it as an opportunity to rethink their lives and improve family relations. KEY CONCLUSIONS: The informal caregivers experienced increased physical and psychological burdens. Strategies such as adoption of a less frequent prenatal visit schedule, use of tele-medicine technologies, and provision of accurate information and knowledge may help to ease the increased informal caregiving burdens. Psychological counseling, community services and disaster response policies specially targeting pregnant women and their informal caregivers may also be valuable resources. IMPLICATIONS FOR PRACTICE: Attention should be drawn to the group of informal caregivers for pregnant women during a COVID-19 lockdown, including professional assistance delivered by nursing and other related professionals. Measures are called for to minimize exposure opportunities such as adoption of a new prenatal care schedule and tele-medicine technologies. Patient education with reliable information should be provided, preferably by nursing staff and physicians. Social support efforts including professional mental counseling may added and work with other resources such as community services and policy makers.

2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312183

ABSTRACT

Abstract There is a heated debate on whether the cancer survivors have worse outcomes in corona virus disease 2019 (COVID-2019). This study showed that both cancer survivors and cancer patients have decreased lymphocytes, partially explaining why these patients were associated with poorer prognosis in severe acute respiratory syndrome coronavirus 2 infection (SARS-CoV-2) in principle. Therefore, patients with cancer history, whether they are going active treatment or not, deserve special attention.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-308330

ABSTRACT

Background and Objective: The new type of coronavirus is also called COVID-19. It began to spread at the end of 2019 and has now spread across the world. Until October 2020, It has infected around 37 million people and claimed about 1 million lives. We propose a deep learning model that can help radiologists and clinicians use chest X-rays to diagnose COVID-19 cases and show the diagnostic features of pneumonia. Methods: The approach in this study is: 1) we propose a data enhancement method to increase the diversity of the data set, thereby improving the generalization performance of the model. 2) Our deep convolution neural network model DPN-SE adds a self-attention mechanism to the DPN network. The addition of a self-attention mechanism has greatly improved the performance of the network. 3) Use the Lime interpretable library to mark the feature regions on the X-ray medical image that helps doctors more quickly diagnose COVID-19 in people. Results: Under the same network model, the data with and without data enhancement is put into the model for training respectively. At last, comparing two experimental results: among the 10 network models with different structures, 7 network models have improved their effects after using data enhancement, with an average improvement of 1% in recognition accuracy. We propose that the accuracy and recall rates of the DPN-SE network are 93% and 98% of cases (COVID vs. pneumonia bacteria vs. viral pneumonia vs. normal). Compared with the original DPN, the respective accuracy is improved by 2%. Conclusion: The data augmentation method we used has achieved effective results on a small amount of data set, showing that a reasonable data augmentation method can improve the recognition accuracy without changing the sample size and model structure. Overall, the proposed method and model can effectively become a very useful tool for clinical radiologists.

4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-308329

ABSTRACT

The new type of coronavirus is called COVID-19. The virus can cause respiratory diseases, accompanied by cough, fever, difficulty breathing, and in severe cases, it can also cause symptoms such as pneumonia. It began to spread at the end of 2019 and has now spread to all parts of the world. The limited test kits and increasing number of cases encourage us to propose a deep learning model that can help radiologists and clinicians use chest X-rays to detect COVID-19 cases and show the diagnostic features of pneumonia. In this study, our methods are: 1) Propose a data enhancement method to increase the diversity of the data set, thereby improving the generalization performance of the network. 2) Using the deep convolutional neural network model DPN-SE, an attention mechanism is added on the basis of the DPN network, which greatly improves the performance of the network. 3) Use the lime interpretable library to mark the X-ray, the characteristic area on the medical image that is helpful for the doctor to make a diagnosis. The model we proposed can obtain better results with the least amount of data preprocessing given limited data. In general, the proposed method and model can effectively become a very useful tool for clinical practitioners and radiologists.

5.
Eur Radiol ; 32(4): 2235-2245, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1606144

ABSTRACT

BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial intelligence system based on deep learning (DL) and federated learning (FL) for the diagnosis, monitoring, and prediction of a patient's clinical course. METHODS: CT imaging derived from 6 different multicenter cohorts were used for stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data. Patients with more than 3 consecutive CT images were trained for the monitoring algorithm. FL has been applied for decentralized refinement of independently built DL models. RESULTS: A total of 1,552,988 CT slices from 4804 patients were used. The model can diagnose COVID-19 based on CT alone with the AUC being 0.98 (95% CI 0.97-0.99), and outperforms the radiologist's assessment. We have also successfully tested the incorporation of the DL diagnostic model with the FL framework. Its auto-segmentation analyses co-related well with those by radiologists and achieved a high Dice's coefficient of 0.77. It can produce a predictive curve of a patient's clinical course if serial CT assessments are available. INTERPRETATION: The system has high consistency in diagnosing COVID-19 based on CT, with or without clinical data. Alternatively, it can be implemented on a FL platform, which would potentially encourage the data sharing in the future. It also can produce an objective predictive curve of a patient's clinical course for visualization. KEY POINTS: • CoviDet could diagnose COVID-19 based on chest CT with high consistency; this outperformed the radiologist's assessment. Its auto-segmentation analyses co-related well with those by radiologists and could potentially monitor and predict a patient's clinical course if serial CT assessments are available. It can be integrated into the federated learning framework. • CoviDet can be used as an adjunct to aid clinicians with the CT diagnosis of COVID-19 and can potentially be used for disease monitoring; federated learning can potentially open opportunities for global collaboration.


Subject(s)
Artificial Intelligence , COVID-19 , Algorithms , Humans , Radiologists , Tomography, X-Ray Computed/methods
6.
J Healthc Eng ; 2021: 2770846, 2021.
Article in English | MEDLINE | ID: covidwho-1358936

ABSTRACT

Patient transfer has always been a difficult problem, usually requiring multiple caregivers to work together, which is time consuming and can easily cause secondary injuries to the patient. In addition, with the crisis of COVID-19, the issue of patient transfer is even more critical, as caregivers are at a high risk of infection, causing significant damage to healthcare resources. In this paper, a patient transfer assist system named E-pat-plus (Easy Patient Transfer plus) has been proposed; it can assist caregivers in transferring patients, reduce direct contact between them, and avoid secondary injuries. In the mechanical structure of this apparatus, a novel five-gear assembly module and a synchronous belt pulley set are proposed; they are the key points to the basic functional realization of the device and can reduce the cost of the prototype. Furthermore, a fuzzy (proportion-integration-differentiation) PID-based cross-coupling control strategy is applied to the apparatus to ensure the stability and safety of the operation. Finally, some preliminary experiments, including current experiments and error experiments, are carried out to verify the reliability of the device and lay the foundation for clinical tests.


Subject(s)
Caregivers , Equipment Design , Patient Transfer/methods , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , Female , Health Personnel , Humans , Male , Reproducibility of Results
7.
Int J Dermatol Venereol ; 2020 Mar 13.
Article in English | MEDLINE | ID: covidwho-1292185

ABSTRACT

The 2019 novel coronavirus infection has brought a great challenge in prevention and control of the national epidemic of coronavirus disease 2019 (COVID-19) in China. During the fight against the epidemic of COVID-19, properly carrying out pre-examination and triage for patients with skin lesions and fever has been a practical problem encountered in hospitals for skin diseases as well as clinics of dermatology in general hospitals. Considering that certain skin diseases may have symptom of fever, and some of the carriers of 2019 novel coronavirus and patients with COVID-19 at their early stage may do not present any symptoms of COVID-19, to properly deal with the visitors to clinics of dermatology, the Chinese Society of Dermatology organized experts to formulate the principles and procedures for pre-examination and triage of visitors to clinics of dermatology during the epidemic of COVID-19.

8.
Vaccine ; 39(8): 1241-1247, 2021 02 22.
Article in English | MEDLINE | ID: covidwho-1039581

ABSTRACT

Without approved vaccines and specific treatments, COVID-19 is spreading around the world with above 26 million cases and approximately 864 thousand deaths until now. An efficacious and affordable vaccine is urgently needed. The Val308 - Gly548 of spike protein of SARS-CoV-2 linked with Gln830 - Glu843 of Tetanus toxoid (TT peptide) (designated as S1-4) and without TT peptide (designated as S1-5) were expressed and renatured. The antigenicity and immunogenicity of S1-4 were evaluated by Western Blotting (WB) in vitro and immune responses in mice, respectively. The protective efficiency was measured preliminarily by microneutralization assay (MN50). The soluble S1-4 and S1-5 protein was prepared to high homogeneity and purity. Adjuvanted with Alum, S1-4 protein stimulated a strong antibody response in immunized mice and caused a major Th2-type cellular immunity supplemented with Th1-type immunity. Furthermore, the immunized sera could protect the Vero E6 cells from SARS-CoV-2 infection with neutralizing antibody titer 256. Recombinant SARS-CoV-2 RBD with a built in T helper epitope could stimulate both strong humoral immunity supplemented with cellular immunity in mice, demonstrating that it could be a promising subunit vaccine candidate.


Subject(s)
Antibodies, Viral/immunology , COVID-19 Vaccines/immunology , Epitopes, T-Lymphocyte/immunology , Spike Glycoprotein, Coronavirus/immunology , Animals , Antibodies, Neutralizing/immunology , Antibody Formation , COVID-19 , Female , Humans , Mice , Mice, Inbred BALB C , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/genetics
9.
Cell Res ; 31(1): 17-24, 2021 01.
Article in English | MEDLINE | ID: covidwho-953056

ABSTRACT

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic worldwide. Currently, however, no effective drug or vaccine is available to treat or prevent the resulting coronavirus disease 2019 (COVID-19). Here, we report our discovery of a promising anti-COVID-19 drug candidate, the lipoglycopeptide antibiotic dalbavancin, based on virtual screening of the FDA-approved peptide drug library combined with in vitro and in vivo functional antiviral assays. Our results showed that dalbavancin directly binds to human angiotensin-converting enzyme 2 (ACE2) with high affinity, thereby blocking its interaction with the SARS-CoV-2 spike protein. Furthermore, dalbavancin effectively prevents SARS-CoV-2 replication in Vero E6 cells with an EC50 of ~12 nM. In both mouse and rhesus macaque models, viral replication and histopathological injuries caused by SARS-CoV-2 infection are significantly inhibited by dalbavancin administration. Given its high safety and long plasma half-life (8-10 days) shown in previous clinical trials, our data indicate that dalbavancin is a promising anti-COVID-19 drug candidate.


Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , Antiviral Agents , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/metabolism , Teicoplanin/analogs & derivatives , Animals , Antiviral Agents/pharmacokinetics , Antiviral Agents/pharmacology , Caco-2 Cells , Chlorocebus aethiops , Disease Models, Animal , Humans , Mice , Mice, Transgenic , Protein Binding/drug effects , Teicoplanin/pharmacokinetics , Teicoplanin/pharmacology , Vero Cells
11.
Dermatol Ther ; 33(4): e13310, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-767240

ABSTRACT

Health professions preventing and controlling Coronavirus Disease 2019 are prone to skin and mucous membrane injury, which may cause acute and chronic dermatitis, secondary infection and aggravation of underlying skin diseases. This is a consensus of Chinese experts on protective measures and advice on hand-cleaning- and medical-glove-related hand protection, mask- and goggles-related face protection, UV-related protection, eye protection, nasal and oral mucosa protection, outer ear, and hair protection. It is necessary to strictly follow standards of wearing protective equipment and specification of sterilizing and cleaning. Insufficient and excessive protection will have adverse effects on the skin and mucous membrane barrier. At the same time, using moisturizing products is highly recommended to achieve better protection.


Subject(s)
Coronavirus Infections/therapy , Health Personnel , Mucous Membrane/pathology , Occupational Diseases/prevention & control , Pneumonia, Viral/therapy , Skin/pathology , COVID-19 , China , Consensus , Emollients/administration & dosage , Gloves, Protective , Hand Disinfection/methods , Humans , Masks , Pandemics , Personal Protective Equipment
12.
Eur Respir J ; 55(6)2020 06.
Article in English | MEDLINE | ID: covidwho-622479

ABSTRACT

BACKGROUND: During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences. METHODS: Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined. RESULTS: At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7 versus 44.9 years), had more cases with comorbidity (32.9% versus 19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7 versus 4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0% versus 11.1%, death rate 7.3% versus 0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4 versus 4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)). CONCLUSION: There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.


Subject(s)
Coronavirus Infections/mortality , Hospitalization , Pneumonia, Viral/mortality , Adult , Aged , Betacoronavirus , COVID-19 , Cardiovascular Diseases/epidemiology , China , Cohort Studies , Comorbidity , Coronavirus Infections/complications , Coronavirus Infections/diagnostic imaging , Cough/etiology , Diabetes Mellitus/epidemiology , Disease Outbreaks , Dyspnea/etiology , Fatigue/etiology , Female , Fever/etiology , Geography , Humans , Hypertension/epidemiology , Intensive Care Units/statistics & numerical data , Lung/diagnostic imaging , Male , Middle Aged , Pandemics , Pharyngitis/etiology , Pneumonia, Viral/complications , Pneumonia, Viral/diagnostic imaging , Prognosis , Proportional Hazards Models , Respiration, Artificial/statistics & numerical data , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index , Time Factors , Time-to-Treatment/statistics & numerical data , Tomography, X-Ray Computed
13.
Gut ; 69(6): 1002-1009, 2020 06.
Article in English | MEDLINE | ID: covidwho-18560

ABSTRACT

OBJECTIVE: The SARS-CoV-2-infected disease (COVID-19) outbreak is a major threat to human beings. Previous studies mainly focused on Wuhan and typical symptoms. We analysed 74 confirmed COVID-19 cases with GI symptoms in the Zhejiang province to determine epidemiological, clinical and virological characteristics. DESIGN: COVID-19 hospital patients were admitted in the Zhejiang province from 17 January 2020 to 8 February 2020. Epidemiological, demographic, clinical, laboratory, management and outcome data of patients with GI symptoms were analysed using multivariate analysis for risk of severe/critical type. Bioinformatics were used to analyse features of SARS-CoV-2 from Zhejiang province. RESULTS: Among enrolled 651 patients, 74 (11.4%) presented with at least one GI symptom (nausea, vomiting or diarrhoea), average age of 46.14 years, 4-day incubation period and 10.8% had pre-existing liver disease. Of patients with COVID-19 with GI symptoms, 17 (22.97%) and 23 (31.08%) had severe/critical types and family clustering, respectively, significantly higher than those without GI symptoms, 47 (8.14%) and 118 (20.45%). Of patients with COVID-19 with GI symptoms, 29 (39.19%), 23 (31.08%), 8 (10.81%) and 16 (21.62%) had significantly higher rates of fever >38.5°C, fatigue, shortness of breath and headache, respectively. Low-dose glucocorticoids and antibiotics were administered to 14.86% and 41.89% of patients, respectively. Sputum production and increased lactate dehydrogenase/glucose levels were risk factors for severe/critical type. Bioinformatics showed sequence mutation of SARS-CoV-2 with m6A methylation and changed binding capacity with ACE2. CONCLUSION: We report COVID-19 cases with GI symptoms with novel features outside Wuhan. Attention to patients with COVID-19 with non-classic symptoms should increase to protect health providers.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques , Coronavirus Infections , Gastrointestinal Tract , Pandemics , Pneumonia, Viral , Adult , COVID-19 , COVID-19 Testing , China , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Coronavirus Infections/virology , Female , Gastrointestinal Tract/physiopathology , Gastrointestinal Tract/virology , Humans , Male , Middle Aged , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Pneumonia, Viral/virology , Risk Factors , SARS-CoV-2
14.
Eur Respir J ; 55(5)2020 05.
Article in English | MEDLINE | ID: covidwho-18269

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. OBJECTIVE: To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status. METHODS: We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities. RESULTS: The mean age was 48.9 years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424-5.048)), diabetes (1.59 (1.03-2.45)), hypertension (1.58 (1.07-2.32)) and malignancy (3.50 (1.60-7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16-2.77) among patients with at least one comorbidity and 2.59 (1.61-4.17) among patients with two or more comorbidities. CONCLUSION: Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Adult , COVID-19 , China/epidemiology , Comorbidity , Coronavirus Infections/diagnosis , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Prognosis , Risk Factors , SARS-CoV-2
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