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1.
J Viral Hepat ; 2020 Sep 14.
Article in English | MEDLINE | ID: covidwho-767586

ABSTRACT

The interaction between existing chronic liver diseases caused by Hepatitis B virus (HBV) infection and COVID-19 has not been studied. We analyzed 70 COVID-19 cases combined with HBV infection (CHI) to determine the epidemiological, clinical characteristics, treatment and outcome.We investigated clinical presentation, imaging and laboratory parameters of COVID-19 patients of seven hospitals from Jan 20 to March 20, 2020. Multivariate analysis was used to analyze risk factors for progression of patients with COVID-19 combined with HBV infection. Compared with COVID-19 without HBV infection (WHI) group, patients with dual infection had a higher proportion of severe / critically ill disease (32.86% vs. 15.27%, P = 0.000), higher levels of alanine aminotransferase (ALT), aspartate transaminase (AST) and activated partial thromboplastin (APTT) [50(28-69)vs 21(14-30), P = 0.000; 40(25-54) vs 23(18-30), P = 0.000; 34.0(27.2-38.7) vs 37.2(31.1-41.4), P = 0.031]. The utilization rates of Arbidol and immunoglobulin were significantly higher than those in the co-infected group [48.57% vs. 35.64%, P < 0.05; 21.43% vs. 8.18%, P < 0.001], while the utilization rate of chloroquine phosphate was lower (1.43% vs 14.00%, P < 0.05) in the co-infected patients group. Age and c-reactive protein (CRP) level were independent risk factors for recovery of patients with COVID-19 combined with HBV infection.The original characteristics of COVID-19 cases combined with HBV infection were higher rate of liver injury, coagulation disorders, severe/critical tendency, and increased susceptibility. The elderly and patients with higher level of CRP were more likely to experience a severe outcome of COVID-19.

2.
Annals of Translational Medicine ; 8(15), 2020.
Article | WHO COVID | ID: covidwho-749315

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) has widely spread worldwide and caused a pandemic Chest CT has been found to play an important role in the diagnosis and management of COVID-19 However, quantitatively assessing temporal changes of COVID-19 pneumonia over time using CT has still not been fully elucidated The purpose of this study was to perform a longitudinal study to quantitatively assess temporal changes of COVID-19 pneumonia Methods: This retrospective and multi-center study included patients with laboratory-confirmed COVI D-19 infection from 16 hospitals between January 19 and March 27, 2020 Mass was used as an approach to quantitatively measure dynamic changes of pulmonary involvement in patients with COVID-19 Artificial intelligence (AI) was employed as image segmentation and analysis tool for calculating the mass of pulmonary involvement Results: A total of 581 confirmed patients with 1,309 chest cr examinations were included in this study The median age was 46 years (IQR, 35-55;range, 4-87 years), and 311 (53 5%) patients were male The mass of pulmonary involvement peaked on day 10 after the onset of initial symptoms Furthermore, the mass of pulmonary involvement of older patients (>45 years) was significantly severer (P<0 001) and peaked later (day 11 vs day 8) than that of younger patients (<= 45 years) In addition, there were no significant differences in the peak time (day 10 vs day 10) and median mass (P=0 679) of pulmonary involvement between male and female Conclusions: Pulmonary involvement peaked on day 10 after the onset of initial symptoms in patients with COVID-19 Further, pulmonary involvement of older patients was severer and peaked later than that of younger patients These findings suggest that AI-based quantitative mass evaluation of COVID-19 pneumonia hold great potential for monitoring the disease progression

3.
Amcis 2020 Proceedings ; 2020.
Article | WHO COVID | ID: covidwho-746310

ABSTRACT

The recent outbreak of the coronavirus (COVID-19) brought with its public concerns and fears about a global epidemic With the increase in the popularity, usage, and reach of social media, this research examined the early public outlook on COVID-19 using SM-Platform, Twitter com The current study employed a mixed-method approach in collecting and analyzing public tweets by combining quantitative sentiment analysis with a qualitative thematic analysis Our results revealed positive sentiment prior to the spread of the disease The sentiment then turned negative as the disease spread, accompanied by a large amount of fear as rumors In a thematic analysis we also uncovered nine key topics on the disease including, but not limited to, prevention, symptoms and spread of disease Our study will provide an understanding of social media and public health outbreak surveillance The findings of the research revealed the usefulness of twitter mining to illuminate public health education

4.
Epidemiol Infect ; 148: e195, 2020 09 02.
Article in English | MEDLINE | ID: covidwho-740025

ABSTRACT

We recruited 1591 patients who presented to our fever clinics from 23 January 2020 to 16 February 2020. The different imaging findings between COVID-19 pneumonia and influenza A viruses, influenza B virus pneumonia were also investigated. Most patients were infected by influenza A and B viruses in the flu-season. A laboratory kit is urgently needed to test different viruses simultaneously. Computed tomography can help early screen suspected patients with COVID-19 and differentiate different virus-related pneumonia.

6.
SN Compr Clin Med ; : 1-7, 2020 Aug 24.
Article in English | MEDLINE | ID: covidwho-731189

ABSTRACT

On February 6, 2020, Xiaogan City became the second most seriously affected city with coronavirus disease 2019 (COVID-19), outside Wuhan district, Hubei Province, China. The objectives are to study the clinical features of COVID-19 patients and assess the relationship between the severity of COVID-19, age, and C-reactive protein (CRP) levels. The retrospective data of 134 COVID-19 patients hospitalized in 3 hospitals of Xiaogan City, between February 1 and March 1, 2020, was collected. This study documented COVID-19 patients. Clinical data in terms of body temperature, history of travel, and direct contact with COVID-19 patients, and incubation period was collected. Out of the 134 patients, only 5 required intensive care. Moreover, 2 patients succumbed during this period. The median age of patients was 45 (33-56) years. The most common symptoms at the onset of disease were fever (66.4%), cough (33, 6%), and sore throat (14.7%). Amongst the medicines used, antiviral agents (92.3%) followed by the traditional Chinese medicine (89.5%) were most commonly used. In both the crude and adjusted (I to III) models, odds ratio and its 95% confidence interval for both age and CRP levels were > 1. Moreover, the smooth curve fitting graph reflected that the severity of COVID-19 was positively correlated with both age and CRP levels (all P value < 0.05). The signs and symptoms of COVID-19 patients were fairly moderate. The health care professionals treating the COVID-19 patients should be aware of the increased likelihood of progression to severe COVID-19 in elderly patients and those with high CRP levels.

7.
JCI Insight ; 2020 Aug 25.
Article in English | MEDLINE | ID: covidwho-729453

ABSTRACT

The emergence of SARS-CoV-2 has created an international health crisis. Small animal models mirroring SARS-CoV-2 human disease are essential for medical countermeasure (MCM) development. Mice are refractory to SARS-CoV-2 infection due to low affinity binding to the murine angiotensin-converting enzyme 2 (ACE2) protein. Here we evaluated the pathogenesis of SARS-CoV-2 in male and female mice expressing the human ACE2 gene under the control of the keratin 18 promotor. In contrast to non-transgenic mice, intranasal exposure of K18-hACE2 animals to two different doses of SARS-CoV-2 resulted in acute disease including weight loss, lung injury, brain infection and lethality. Vasculitis was the most prominent finding in the lungs of infected mice. Transcriptomic analysis from lungs of infected animals revealed increases in transcripts involved in lung injury and inflammatory cytokines. In the lower dose challenge groups, there was a survival advantage in the female mice with 60% surviving infection whereas all male mice succumbed to disease. Male mice that succumbed to disease had higher levels of inflammatory transcripts compared to female mice. This is the first highly lethal murine infection model for SARS-CoV-2. The K18-hACE2 murine model will be valuable for the study of SARS-CoV-2 pathogenesis and the assessment of MCMs.

8.
Stem Cells International ; 2020, 2020.
Article | WHO COVID | ID: covidwho-725839

ABSTRACT

Infections of emerging and reemerging viruses (SARS-CoVs, influenza H1N1, etc ) largely and globally affect human health Animal models often fail to reflect a physiological status because of species tropism of virus infection Conventional cell lines are usually genetically and phenotypically different from primary cells Developing anin vitrophysiological model to study the infection of emerging viruses will facilitate our understanding of virus-host cell interactions, thereby benefiting antiviral drug discovery In the current work, we first established normal airway epithelial cells (upper and lower airway track) in 2D and 3D culture systems using conditional reprogramming (CR) and air-liquid interface (ALI) techniques These long-term cultures maintained differentiation potential More importantly, these cells express two types of influenza virus receptors,alpha 2-6-Gal- and alpha 2-3-Gal-linked sialic acids, and angiotensin-converting enzyme 2 (ACE2), a receptor for SARS-CoVs as well These cells were permissive to the infection of pandemic influenza H1N1 (H1N1pdm) In contrast, the lung cancer cell line A549 and immortalized airway epithelial cells (16HBE) were not susceptible to H1N1 infection A virus-induced cytopathic effect (CPE) on 2D CRC cultures developed in a time-dependent manner The pathological effects were also readily observed spreading from the apical layer to the basal layer of the 3D ALI culture This integrated 2D CRC and 3D ALI cultures provide a physiological and personalizedin vitromodel to study the infection of emerging viruses This novel model can be used for studying virus biology and host response to viral infection and for antiviral drug discovery

9.
Int J Med Sci ; 17(14): 2187-2193, 2020.
Article in English | MEDLINE | ID: covidwho-719844

ABSTRACT

Background: The number of asymptomatic infected patients with coronavirus disease 2019 (COVID-2019) is rampaging around the world but limited information aimed on risk factors of asymptomatic infections. The purpose of this study is to investigate the risk factors of symptoms onset and clinical features in asymptomatic COVID-19 infected patients. Methods: A retrospective study was performed in 70 asymptomatic COVID-2019 infected patients confirmed by nucleic acid tests in Hunan province, China between 28 January 2020 and 18 February, 2020. The epidemiological, clinical features and laboratory data were reviewed and analyzed. Presence or absence at the onset of symptoms was taken as the outcome. A Cox regression model was performed to evaluate the potential predictors of the onset of symptoms. Results: The study included 36 males and 34 females with a mean age of 33.24±20.40 years (range, 0.5-84 years). There were 22 asymptomatic carriers developed symptoms during hospitalization isolated observation, and diagnosed as confirmed cases, while 48 cases remained asymptomatic throughout the course of disease. Of 70 asymptomatic patients, 14 (14/70, 20%) had underlying diseases, 3 (3/70, 4.3%) had drinking history, and 11 (11/70, 15.7%) had smoking history. 22 patients developed symptoms onset of fever (4/22, 18.2%), cough (13/22, 59.1%), chest discomfort (2/22, 9.1%), fatigue (1/22, 4.5%), pharyngalgia (1/22, 4.5%) during hospitalization; only one (1/22, 4.5%) patient developed signs of both cough and pharyngalgia. Abnormalities on chest CT were detected among 35 of the 69 patients (50.7%) after admission, except for one pregnant woman had not been examined. 4 (4/70, 5.7%) and 8 (8/70, 11.4%) cases showed leucopenia and lymphopenia. With the effective antiviral treatment, all the 70 asymptomatic infections had been discharged, none cases developed severe pneumonia, admission to intensive care unit, or died. The mean time from nucleic acid positive to negative was 13.2±6.84 days. Cox regression analysis showed that smoking history (P=0.028, hazard ratio=4.49, 95% CI 1.18-17.08) and existence of pulmonary disease (P=0.038, hazard ratio=7.09, 95% CI 1.12-44.90) were risk factors of the onset of symptoms in asymptomatic carries. Conclusion: The initially asymptomatic patients can develop mild symptoms and have a good prognosis. History of smoking and pulmonary disease was prone to illness onset in asymptomatic patients, and it is necessary to be highly vigilant to those patients.

10.
J Am Psychiatr Nurses Assoc ; : 1078390320946825, 2020 Aug 13.
Article in English | MEDLINE | ID: covidwho-713746
11.
Clin Infect Dis ; 71(15): 706-712, 2020 07 28.
Article in English | MEDLINE | ID: covidwho-708751

ABSTRACT

BACKGROUND: We aimed to report the clinical characteristics of imported cases of coronavirus disease 2019 (COVID-19) in Jiangsu Province. METHODS: We retrospectively investigated the clinical, imaging, and laboratory characteristics of confirmed cases of COVID-19 with World Health Organization interim guidance in 3 grade IIIA hospitals of Jiangsu from 22 January to 14 February 2020. Real-time RT-PCR was used to detect the new coronavirus in respiratory samples. RESULTS: Of the 80 patients infected with COVID-19, 41 were female, with a median age of 46.1 years. Except for 3 severe patients, the rest of the 77 patients exhibited mild or moderate symptoms. Nine patients were unconfirmed until a third nucleic acid test; 38 cases had a history of chronic diseases. The main clinical manifestations of the patients were fever and cough, which accounted for 63 (78.75%) and 51 (63.75%) cases, respectively. Only 3 patients (3.75%) showed liver dysfunction. Imaging examination showed that 55 patients (68.75%) showed abnormal density shadow and 25 cases (31.25%) had no abnormal density shadow in the parenchyma of both lungs. Currently, 21 cases have been discharged from the hospital, and no patient died. The average length of stay for discharged patients was 8 days. CONCLUSIONS: Compared with the cases in Wuhan, the cases in Jiangsu exhibited mild or moderate symptoms and no obvious gender susceptibility. The proportion of patients having liver dysfunction and abnormal CT imaging was relatively lower than that in Wuhan. Notably, infected patients may be falsely excluded based on 2 consecutively negative respiratory pathogenic nucleic acid test results.


Subject(s)
Coronavirus Infections/pathology , Coronavirus Infections/virology , Pneumonia, Viral/pathology , Pneumonia, Viral/virology , Adolescent , Adult , Aged , Betacoronavirus/pathogenicity , China , Cough/virology , Female , Fever/virology , Humans , Lung/virology , Male , Middle Aged , Pandemics , Patient Discharge , Retrospective Studies , Young Adult
12.
Radiology ; 296(2): E41-E45, 2020 08.
Article in English | MEDLINE | ID: covidwho-697187

ABSTRACT

Some patients with positive chest CT findings may present with negative results of real-time reverse-transcription polymerase chain reaction (RT-PCR) tests for coronavirus disease 2019 (COVID-19). In this study, the authors present chest CT findings from five patients with COVID-19 infection who had initial negative RT-PCR results. All five patients had typical imaging findings, including ground-glass opacity (five patients) and/or mixed ground-glass opacity and mixed consolidation (two patients). After isolation for presumed COVID-19 pneumonia, all patients were eventually confirmed to have COVID-19 infection by means of repeated swab tests. A combination of repeated swab tests and CT scanning may be helpful for individuals with a high clinical suspicion of COVID-19 infection but negative findings at RT-PCR screening.


Subject(s)
Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Adult , Aged , Betacoronavirus , Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnostic imaging , False Negative Reactions , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted/methods , Reproducibility of Results , Reverse Transcriptase Polymerase Chain Reaction , Tomography, X-Ray Computed/methods
13.
BMC Med ; 18(1): 250, 2020 08 06.
Article in English | MEDLINE | ID: covidwho-695766

ABSTRACT

BACKGROUND: COVID-19 is an extremely severe infectious disease. However, few studies have focused on the epidemiological and clinical characteristics of pediatric COVID-19. This study conducted a retrospective review of the epidemiological and clinical features of COVID-19 in children. METHODS: A retrospective study was conducted on children with a definite diagnosis of COVID-19 in mainland China using the web crawler technique to collect anonymous COVID-19 updates published by local health authorities. RESULTS: Three hundred forty-one children aged 4 days to 14 years with a median age of 7 years were included. Sixty-six percent of pediatric patients were infected via family members with COVID-19. The median incubation period was 9 days (interquartile range, 6 to 13). Asymptomatic cases accounted for 5.9%, of which 30% had abnormal chest radiologic findings. A majority of pediatric COVID-19 cases showed mild to moderate clinical features, and only a few developed severe or critical diseases (0.6% and 0.3%, respectively). Fever (77.9%) and cough (32.4%) were the predominant presenting symptoms of pediatric COVID-19. The pediatric patients had fewer underlying diseases and complications than adults. The treatment modalities for pediatric COVID-19 patients were not as complex as those of adult COVID-19 patients. The overall prognosis of pediatric COVID-19 was benign with a decent recovery. The median time from onset to cure was 16 days (interquartile range, 13 to 21). CONCLUSIONS: Compared to adults, COVID-19 in children has distinct features of epidemiology and clinical manifestations. The findings from this study might help to guide the development of measures to prevent and treat this ongoing global pandemic. TRIAL REGISTRATION: Chinese Clinical Trial Registry ( chictr.org.cn ) identifier: ChiCTR2000030464.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Adolescent , Child , Child, Preschool , China/epidemiology , Cough/etiology , Female , Fever/etiology , Humans , Infant , Infant, Newborn , Male , Pandemics , Retrospective Studies
14.
PLoS Med ; 17(7): e1003195, 2020 07.
Article in English | MEDLINE | ID: covidwho-691282

ABSTRACT

BACKGROUND: As of June 1, 2020, coronavirus disease 2019 (COVID-19) has caused more than 6,000,000 infected persons and 360,000 deaths globally. Previous studies revealed pregnant women with COVID-19 had similar clinical manifestations to nonpregnant women. However, little is known about the outcome of neonates born to infected women. METHODS AND FINDINGS: In this retrospective study, we studied 29 pregnant women with COVID-19 infection delivered in 2 designated general hospitals in Wuhan, China between January 30 and March 10, 2020, and 30 neonates (1 set of twins). Maternal demographic characteristics, delivery course, symptoms, and laboratory tests from hospital records were extracted. Neonates were hospitalized if they had symptoms (5 cases) or their guardians agreed to a hospitalized quarantine (13 cases), whereas symptom-free neonates also could be discharged after birth and followed up through telephone (12 cases). For hospitalized neonates, laboratory test results and chest X-ray or computed tomography (CT) were extracted from hospital records. The presence of antibody of SARS-CoV-2 was assessed in the serum of 4 neonates. Among 29 pregnant COVID-19-infected women (13 confirmed and 16 clinical diagnosed), the majority had higher education (56.6%), half were employed (51.7%), and their mean age was 29 years. Fourteen women experienced mild symptoms including fever (8), cough (9), shortness of breath (3), diarrhea (2), vomiting (1), and 15 were symptom-free. Eleven of 29 women had pregnancy complications, and 27 elected to have a cesarean section delivery. Of 30 neonates, 18 were admitted to Wuhan Children's Hospital for quarantine and care, whereas the other 12 neonates discharged after birth without any symptoms and had normal follow-up. Five hospitalized neonates were diagnosed as COVID-19 infection (2 confirmed and 3 suspected). In addition, 12 of 13 other hospitalized neonates presented with radiological features for pneumonia through X-ray or CT screening, 1 with occasional cough and the others without associated symptoms. SARS-CoV-2 specific serum immunoglobulin M (IgM) and immunoglobulin G (IgG) were measured in 4 neonates and 2 were positive. The limited sample size limited statistical comparison between groups. CONCLUSIONS: In this study, we observed COVID-19 or radiological features of pneumonia in some, but not all, neonates born to women with COVID-19 infection. These findings suggest that intrauterine or intrapartum transmission is possible and warrants clinical caution and further investigation. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2000031954 (Maternal and Perinatal Outcomes of Women with coronavirus disease 2019 (COVID-19): a multicenter retrospective cohort study).


Subject(s)
Coronavirus Infections/pathology , Pneumonia, Viral/pathology , Pregnancy Complications, Infectious/virology , Adult , Betacoronavirus/isolation & purification , China/epidemiology , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Female , Humans , Infant, Newborn , Infectious Disease Transmission, Vertical , Male , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Pregnancy , Pregnancy Complications, Infectious/diagnosis , Pregnancy Complications, Infectious/epidemiology , Pregnancy Complications, Infectious/pathology , Retrospective Studies
15.
IEEE Trans Med Imaging ; 39(8): 2595-2605, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-690930

ABSTRACT

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper healthcare to the patients and also to protect the uninfected population. To this end, we develop a dual-sampling attention network to automatically diagnose COVID-19 from the community acquired pneumonia (CAP) in chest computed tomography (CT). In particular, we propose a novel online attention module with a 3D convolutional network (CNN) to focus on the infection regions in lungs when making decisions of diagnoses. Note that there exists imbalanced distribution of the sizes of the infection regions between COVID-19 and CAP, partially due to fast progress of COVID-19 after symptom onset. Therefore, we develop a dual-sampling strategy to mitigate the imbalanced learning. Our method is evaluated (to our best knowledge) upon the largest multi-center CT data for COVID-19 from 8 hospitals. In the training-validation stage, we collect 2186 CT scans from 1588 patients for a 5-fold cross-validation. In the testing stage, we employ another independent large-scale testing dataset including 2796 CT scans from 2057 patients. Results show that our algorithm can identify the COVID-19 images with the area under the receiver operating characteristic curve (AUC) value of 0.944, accuracy of 87.5%, sensitivity of 86.9%, specificity of 90.1%, and F1-score of 82.0%. With this performance, the proposed algorithm could potentially aid radiologists with COVID-19 diagnosis from CAP, especially in the early stage of the COVID-19 outbreak.


Subject(s)
Coronavirus Infections/diagnostic imaging , Deep Learning , Image Interpretation, Computer-Assisted/methods , Pneumonia, Viral/diagnostic imaging , Algorithms , Betacoronavirus , Community-Acquired Infections/diagnostic imaging , Humans , Pandemics , ROC Curve , Radiography, Thoracic , Tomography, X-Ray Computed
16.
Diabetes Res Clin Pract ; 167: 108351, 2020 Jul 22.
Article in English | MEDLINE | ID: covidwho-664109

ABSTRACT

AIMS: Coronavirus disease (COVID-19), also referred to as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is instigated by a novel coronavirus. The disease was initially reported in Wuhan, China, in December 2019. Diabetes is a risk factor associated with adverse outcomes. Herein, our objective was to investigate the characteristics of laboratory findings of type 2 diabetes mellitus (T2DM) patients infected with SARS-CoV-2. METHODS: This was a retrospective study and included 80 T2DM patients of Jinling Hospital from 2010 to 2020, as well as 76 COVID-19 patients without T2DM and 55 COVID-19 patients with T2DM who were treated at Huoshen hill Hospital from February 11 to March 18, 2020. We then compared the differences in laboratory test results between the three groups. RESULTS: The levels of lymphocytes, uric acid (UA), and globulin in the T2DM group were significantly higher. In contrast, C-reactive protein (CRP), creatinine, and lactic dehydrogenase (LDH)levels were lower than those in the COVID-19 (p < 0.05) and COVID-19 + T2DM groups (p < 0.05). No considerable difference was observed regarding the levels of alanine aminotransferase (ALT), white blood cell (WBC), aspartate aminotransferase (AST), globulin, and blood urea nitrogen (BUN) in the three groups (p > 0.05). CONCLUSION: T2DM patients infected with SARS-CoV-2 showed decreased levels of body mass index (BMI), lymphocytes, UA, and albumin, and increased CRP levels. The decreased BMI, UA, and albumin levels may be associated with oxidative stress response and nutritional consumption. The decreased lymphocyte counts and increased CRP levels may be related to the infection.

17.
J Infect Public Health ; 2020 Jul 01.
Article in English | MEDLINE | ID: covidwho-633870

ABSTRACT

BACKGROUND AND OBJECTIVES: Since December 2019, the rapid epidemic spread of COVID-19 in China has aroused the attention of the government and the public. The purpose of this study is to investigate the attitude and knowledge among medical students and non-medical students toward SARS-CoV-2 infection. METHODS: A web-based survey was disseminated to the students from medical colleges and comprehensive universities via the survey website (www.wjx.cn) and via WeChat. Participation in the study was voluntary with the instruction to click on the website or scan the QR code to complete the anonymous electronic questionnaire from February 5 to 7, 2020. RESULTS: The questionnaire was completed by 588 students from 20 colleges and universities in China. Of the respondents, 66.0% were medical students and 34.0% were non-medical students. 99.6 % of the students held an optimistic attitude toward the COVID-19 epidemic situation. The majority of participants had a good level of knowledge of common symptoms, transmission, and prevention of the disease. In a comparison between non-medical students with medical students, the medical students had a deeper understanding of COVID-19. In this study, we also found that female students had a better understanding of transmission and prevention than male students did. CONCLUSIONS: The majority of students who participated in the questionnaire had a positive attitude and a good perception about COVID-19.

18.
J Infect ; 2020 Jul 04.
Article in English | MEDLINE | ID: covidwho-629626

ABSTRACT

OBJECTIVE: Coronavirus Disease 2019 (COVID-19) is a pandemic. This systematic review compares mortality risk factors including clinical, demographic and laboratory features of COVID-19, Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). The aim is to provide new strategies for COVID-19 prevention and treatment. METHODS: We performed a systematic review with meta-analysis, using five databases to compare the predictors of death for COVID-19, SARS and MERS. A random-effects model meta-analysis calculated odds ratios (OR) and 95% confidence intervals (95% CI). RESULTS: 845 articles up through 11/4/2020 were retrieved, but only 28 studies were included in this meta-analysis. The results showed that males had a higher likelihood of death than females (OR = 1.82, 95% CI 1.56-2.13). Age (OR = 7.86, 95% CI 5.46-11.29), diabetes comorbidity (OR = 3.73, 95% CI 2.35-5.90), chronic lung disease (OR = 3.43, 95% CI 1.80-6.52) and hypertension (OR = 3.38, 95% CI 2.45-4.67) were the mortality risk factors. The laboratory indicators lactic dehydrogenase (OR = 37.52, 95% CI 24.68-57.03), C-reactive protein (OR = 12.11, 95% CI 5.24-27.98), and neutrophils (OR = 17.56, 95% CI 10.67-28.90) had stronger correlations with COVID-19 mortality than with SARS or MERS mortality. Consolidation and ground-glass opacity imaging features were similar among COVID-19, SARS, and MERS patients. CONCLUSIONS: COVID-19's mortality factors are similar to those of SARS and MERS. Age and laboratory indicators could be effective predictors of COVID-19 mortality outcomes.

19.
Engineering (Beijing) ; 2020 Jun 27.
Article in English | MEDLINE | ID: covidwho-623838

ABSTRACT

The real-time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral RNA from sputum or nasopharyngeal swab had a relatively low positive rate in the early stage of coronavirus disease 2019 (COVID-19). Meanwhile, the manifestations of COVID-19 as seen through computed tomography (CT) imaging show individual characteristics that differ from those of other types of viral pneumonia such as Influenza-A viral pneumonia (IAVP). This study aimed to establish an early screening model to distinguish COVID-19 pneumonia from IAVP and healthy cases through pulmonary CT images using deep learning techniques. A total of 618 CT samples were collected: 219 samples from 110 patients with COVID-19 (mean age 50 years; 63 (57.3%) male patients); 224 samples from 224 patients with IAVP (mean age 61 years; 156 (69.6%) male patients); and 175 samples from 175 healthy cases (mean age 39 years; 97 (55.4%) male patients). All CT samples were contributed from three COVID-19-designated hospitals in Zhejiang Province, China. First, the candidate infection regions were segmented out from the pulmonary CT image set using a 3D deep learning model. These separated images were then categorized into the COVID-19, IAVP, and irrelevant to infection (ITI) groups, together with the corresponding confidence scores, using a location-attention classification model. Finally, the infection type and overall confidence score for each CT case were calculated using the Noisy-or Bayesian function. The experimental result of the benchmark dataset showed that the overall accuracy rate was 86.7% in terms of all the CT cases taken together. The deep learning models established in this study were effective for the early screening of COVID-19 patients and were demonstrated to be a promising supplementary diagnostic method for frontline clinical doctors.

20.
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 , 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 , Severity of Illness Index , Time Factors , Time-to-Treatment/statistics & numerical data , Tomography, X-Ray Computed
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