Associations between eHealth literacy, mental health-seeking attitude, and mental wellbeing among young electronic media users in China during the COVID-19 pandemic

Objective This study aimed to examine the associations among mental health related eHealth literacy (eHL), mental health-seeking attitude, and wellbeing among Chinese young electronic media users during the COVID-19 pandemic. Methods A web-based cross-sectional survey was conducted in Guangzhou, China. The modified eHealth literacy Scale, Mental Help-Seeking Attitudes Scale, and Short Warwick-Edinburgh Mental Wellbeing Scale were used. Structural equation modeling (SEM) examined the associations between them and was adjusted by several controlled variables. Results Totally, 1,008 participants completed the questionnaire and provided valid responses. The eHL showed a statistically significant and direct effect on mental wellbeing in this sample. The higher the level of eHL, the better wellbeing of the participants. The mental health-seeking attitude is also positively correlated with mental wellbeing, indicating that the more positive attitude toward seeking mental health services, the better the wellbeing participants reported. The higher level of eHL is significantly associated with a more positive attitude toward seeking mental health services. Conclusion Training to improve eHL may optimize young electronic media users' mental health outcomes. Development and use of a mental health specific eHL instrument in future studies should be encouraged.

Associations between eHealth literacy, mental health-seeking attitude, and mental wellbeing among young electronic media users in China during the COVID-19 pandemic.

Objective: This study aimed to examine the associations among mental health related eHealth literacy (eHL), mental health-seeking attitude, and wellbeing among Chinese young electronic media users during the COVID-19 pandemic. Methods: A web-based cross-sectional survey was conducted in Guangzhou, China. The modified eHealth literacy Scale, Mental Help-Seeking Attitudes Scale, and Short Warwick-Edinburgh Mental Wellbeing Scale were used. Structural equation modeling (SEM) examined the associations between them and was adjusted by several controlled variables. Results: Totally, 1,008 participants completed the questionnaire and provided valid responses. The eHL showed a statistically significant and direct effect on mental wellbeing in this sample. The higher the level of eHL, the better wellbeing of the participants. The mental health-seeking attitude is also positively correlated with mental wellbeing, indicating that the more positive attitude toward seeking mental health services, the better the wellbeing participants reported. The higher level of eHL is significantly associated with a more positive attitude toward seeking mental health services. Conclusion: Training to improve eHL may optimize young electronic media users' mental health outcomes. Development and use of a mental health specific eHL instrument in future studies should be encouraged.

Characteristics of patients with SARS-COV-2 PCR re-positivity after recovering from COVID-19.

The purpose of this study was to analyse the clinical characteristics of patients with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) PCR re-positivity after recovering from coronavirus disease 2019 (COVID-19). Patients (n = 1391) from Guangzhou, China, who had recovered from COVID-19 were recruited between 7 September 2021 and 11 March 2022. Data on epidemiology, symptoms, laboratory test results and treatment were analysed. In this study, 42.7% of recovered patients had re-positive result. Most re-positive patients were asymptomatic, did not have severe comorbidities, and were not contagious. The re-positivity rate was 39%, 46%, 11% and 25% in patients who had received inactivated, mRNA, adenovirus vector and recombinant subunit vaccines, respectively. Seven independent risk factors for testing re-positive were identified, and a predictive model was constructed using these variables. The predictors of re-positivity were COVID-19 vaccination status, previous SARs-CoV-12 infection prior to the most recent episode, renal function, SARS-CoV-2 IgG and IgM antibody levels and white blood cell count. The predictive model could benefit the control of the spread of COVID-19.

Evaluating the Value of Anti-SARS-CoV-2 Antibody-Based Tests for COVID-19 Diagnosis.

BACKGROUND: The early detection of COVID-19 patients is fundamental for containing the pandemic. A reverse-transcriptase quantitative polymerase chain reaction (RT-PCR), which detects SARS-CoV-2 RNA, is the gold standard diagnostic test, although it can contribute to false-negative results. Consequently, supplementary diagnostic tests are urgently needed. METHODS: To assess the value of anti-SARS-CoV-2 antibody-based tests for confirming COVID-19, a retrospective study was conducted on 3120 inbound overseas travelers who underwent a 14-day government quarantine in Xiamen from August 2020 to October 2020. The diagnostic accuracy of the total antibody that detected the anti-SARS-CoV-2 antibody and the RT-PCR that detected SARS-CoV-2 RNA was determined in comparison to the clinical diagnosis. RESULTS: The COVID-19 positive rate was 3.14% (98/3120). The sensitivity and specificity of the RT-PCR test on the first day of quarantine were 14.29% and 100%, respectively, and the sensitivity and specificity of the total antibody were 93.88% and 99.40%, respectively. The kappa value between an RT-PCR on the first day of quarantine and a clinical diagnosis was 0.24 (95% CI, 0.14-0.35), indicating poor consistency. The kappa value between total antibodies and a clinical diagnosis was 0.88 (95% CI, 0.83-0.93), indicating perfect consistency. There were no differences in the positive rates of an RT-PCR in symptomatic COVID-19 (7.41% (2/27)) and asymptomatic COVID-19 (16.90 (12/71) (p = 0.338). Similarly, the positive rate of the total antibody tests showed no difference in symptomatic COVID-19 (96.30% (26/27)) and asymptomatic COVID-19 (92.96% (66/71)) (p = 0.676). CONCLUSION: SARS-CoV-2 antibodies are developed by the body in response to an infection or after vaccination; this can easily lead to a missed diagnosis. In the context of low sensitivity for an RT-PCR, SARS-CoV-2 antibody detection is an effective adjunct to RT-PCR detection, which can improve the diagnostic accuracy of COVID-19 and provide an effective complement to the false-negative results of an RT-PCR.

Comparative efficacy of Chinese herbal injections for treating severe pneumonia: A protocol for systematic review and Bayesian network meta-analysis of randomized controlled trials.

BACKGROUND: Severe pneumonia (SP) has a high mortality and is responsible for significant healthcare cost. Chinese herbal injections (CHIs) have been widely used in China as a novel and promising treatment option for SP. Therefore, this study will assess and rank the effectiveness of CHIs to provide more sights for the selection of SP treatment. METHOD: Seven databases will be searched, including PubMed, the Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database, and the Chinese Scientific Journal Database (VIP) from their inception up to October, 2021. The literatures screening, data extraction and the quality assessment of included studies will be conducted independently by two reviewers. Then Bayesian network meta-analysis (NMA) will be performed by WinBUGS 14.0 and STATA 14.0 software. Surface under the cumulative ranking curve (SUCRA) probability values will be applied to rank the examined treatments. The risk of bias of each included study will be evaluated using the Revised Cochrane risk-of-bias tool for randomized trials (ROB 2). Publication bias will be reflected by a funnel plot. RESULTS: The results of this NMA will be disseminated through a peer-reviewed journal publication. CONCLUSION: Our study findings maybe reveal which CHI or CHIs will be better in the treatment of SP and provide more therapy strategies for clinical practitioners and patients. PROSPERO REGISTRATION NUMBER: CRD42021244587. STRENGTHS AND LIMITATIONS OF THIS STUDY: Bayesian network meta-analysis (NMA) can integrate direct evidence with indirect evidence of severe pneumonia treated by Chinese herbal injections to generate a clinically useful ranking of these regimens. This NMA will address Chinese herbal injections for SP and its findings may help to provide more sights for selection of SP treatment. Evidence drawn from an NMA is limited and should be interpreted with caution. We only included studies in Chinese and English languages, which may increase the publication bias.

A Method for Intelligent Allocation of Diagnostic Testing by Leveraging Data from Commercial Wearable Devices: A Case Study on COVID-19 (preprint)

Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing towards individuals who are most likely to be infected and, thus, increasing testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6,765 participants) and the MyPHD study (8,580 participants), including smartwatch data from 1,265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to increase the positivity rate of COVID-19 diagnostic testing. We found that resting heart rate features distinguished between COVID-19 positive and negative cases earlier in the course of the infection than steps features, as early as ten and five days prior to the diagnostic test, respectively. We also found that including steps features increased the area under the receiver operating characteristic curve (AUC-ROC) by 7–11% when compared with RHR features alone, while including RHR features improved the AUC of the ITA model’s precision-recall curve (AUC-PR) by 38–50% when compared with steps features alone. The best AUC-ROC (0.73 ± 0.14 and 0.77 on the cross-validated training set and independent test set, respectively) and AUC-PR (0.55 ± 0.21 and 0.24) were achieved by using data from a single device type (Fitbit) with high-resolution (minute-level) data. Finally, we show that ITA generates up to a 6.5-fold increase in the positivity rate in the cross-validated training set and up to a 3-fold increase in the positivity rate in the independent test set, including both symptomatic and asymptomatic (up to 27%) individuals. Our findings suggest that, if deployed on a large scale and without needing self-reported symptoms, the ITA method could improve allocation of diagnostic testing resources and reduce the burden of test shortages.

Comparative Efficacy of Chinese Herbal Injections for Treating Severe Pneumonia: A Systematic Review and Bayesian Network Meta-Analysis of Randomized Controlled Trials.

Background: Severe pneumonia (SP) has a high mortality rate and is responsible for significant healthcare costs. Chinese herbal injections (CHIs) have been widely used in China as a novel and promising treatment option for SP. Therefore, this study assessed and ranked the effectiveness of CHIs to provide more sights for the selection of SP treatment. Method: Seven databases were searched from their inception up to April 1, 2021. The methodological quality of included study was evaluated by the Cochrane risk-of-bias tool. Then, a Bayesian network meta-analysis (NMA) was performed by OpenBUGS 3.2.3 and STATA 14.0 software. The surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the examined treatments. A clustering analysis was utilized to compare the effect of CHIs between two different outcomes. Results: A total of 64 eligible randomized controlled trials (RCTs) involving 5,904 participants were identified for this analysis. Six CHIs including Xuebijing injection (XBJ), Tanreqing injection (TRQ), Reduning injection (RDN), Xiyanping injection (XYP), Shenfu injection (SF), and Shenmai injection (SM) were included. The results of the NMA showed that XBJ [odds ratio (OR) = 0.24, 95% credible interval (CI): 0.19, 0.30], TRQ (OR = 0.22, 95% CI: 0.12, 0.37), RDN (OR = 0.29, 95% CI: 0.04, 0.94), and SM (OR = 0.27, 95% CI: 0.08, 0.63) combined with conventional Western medicine (WM) improved the clinical effective rate more significantly than WM alone. Based on SUCRA values, TRQ + WM (SUCRA: 66.4%) ranked the highest in improving the clinical effective rate, second in four different outcomes, and third in only one. According to the cluster analysis, TRQ + WM exerted a positive effect on improving the efficacy of SP. As for safety, less than 30% (18 RCTs) of the included studies reported adverse drug reactions/adverse drug events (ADRs/ADEs), including 14 RCTs of XBJ, 3 RCTs of TRQ, and 1 RCT of RDN. Conclusion: In conclusion, the study found that the CHIs as co-adjuvant therapy could be beneficial for patients with SP. TRQ + WM showed an outstanding improvement in patients with SP considering both the clinical effective rate and other outcomes. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42021244587].

Clinical efficacy and safety of acupuncture combined with western medicine in treatment of 3 cases of severe COVID-19

OBJECTIVE: To observe the clinical efficacy and safety of the intradermal acupuncture combined with western medicine treatment of three severe crona virus disease 2019 (COVID-19). METHODS: The clinical data of three severe COVID-19 confirmed patients were retrospectively analyzed.On the basis of conventional western medical treatment, intradermal embedding treatment was used for the Kongzu, Dazhui, and Feishu points. Lung CT reports of patients before and after treatment were compared, including the percentage of neutrophil, lymphocyte, hypersensitive C-reactive protein, oxygen index and other indicators. RESULTS: The three severe COVID-19 patients were discharged from hospital after treatment with significant relief of symptoms. Lung CT re-examination showed absorption of lesions and normal inflammatory indicators, and nucleic acid reexamination was negative. CONCLUSION: At present, elderly patients with severe COVID-19 have complicated conditions and high mortality. As an auxiliary means, intradermal acupuncture combined with western medicine therapy is simple, safe and effective in the treatment of severe COVID-19, which is a new exploration for the treatment of complicated COVID-19 conditions.

Novel neutralization mechanism of a human antibody with pan-coronavirus reactivity (preprint)

The recurrent outbreak of coronaviruses and variants underscores the need for broadly reactive antivirals and vaccines. Here, a novel broad-spectrum human antibody named 76E1 was isolated from a COVID-19 convalescent patient and showed broad neutralization activity against multiple α- and β-coronaviruses, including the SARS-CoV-2 variants and also exhibited the binding breath to peptides containing the epitope from γ- and δ- coronaviruses. 76E1 cross-protects mice from SARS-CoV-2 and HCoV-OC43 infection in both prophylactic and treatment models. The epitope including the fusion peptide and S2’ cleavage site recognized by 76E1 was significantly conserved among α-, β-, γ- and δ- coronaviruses. We uncovered a novel mechanism of antibody neutralization that the epitope of 76E1 was proportionally less exposed in the prefusion trimeric structure of spike protein but could be unmasked by binding to the receptor ACE2. Once the epitope exposed, 76E1 inhibited S2’ cleavage, thus blocked the membrane fusion process. Our data demonstrate a key epitope targeted by broadly-neutralizing antibodies and will guide next-generation epitope-based pan-coronavirus vaccine design.

Generation and Characterization of a Nanobody Against SARS-CoV.

The sudden emergence of severe acute respiratory syndrome coronavirus (SARS-CoV) has caused global panic in 2003, and the risk of SARS-CoV outbreak still exists. However, no specific antiviral drug or vaccine is available; thus, the development of therapeutic antibodies against SARS-CoV is needed. In this study, a nanobody phage-displayed library was constructed from peripheral blood mononuclear cells of alpacas immunized with the recombinant receptor-binding domain (RBD) of SARS-CoV. Four positive clones were selected after four rounds of bio-panning and subjected to recombinant expression in E. coli. Further biological identification demonstrated that one of the nanobodies, S14, showed high affinity to SARS-CoV RBD and potent neutralization activity at the picomole level against SARS-CoV pseudovirus. A competitive inhibition assay showed that S14 blocked the binding of SARS-CoV RBD to either soluble or cell-expressed angiotensin-converting enzyme 2 (ACE2). In summary, we developed a novel nanobody targeting SARS-CoV RBD, which might be useful for the development of therapeutics against SARS.

Comprehensive Mapping of Binding Hot Spots of SARS-CoV-2 RBD-specific Neutralizing Antibodies for Tracking Immune Escape Variants (preprint)

The receptor-binding domain (RBD) variants of SARS-CoV-2 could impair antibody-mediated neutralization of the virus by host immunity; thus, prospective surveillance for such antibody escape mutants is urgently needed. Here, we comprehensively profiled four antigenic sites of the RBD and mapped the binding hot spots for a panel of RBD-specific monoclonal antibodies isolated from COVID-19 convalescents, especially dominant VH3-53/3–66 antibodies, which are valuable indicators of antigenic changes in the RBD. We further demonstrated that several natural mutations, namely, K417N, F486L, N450K, L452R, E484K, F490S and R346S, significantly decreased the neutralizing activity of multiple human monoclonal antibodies and of human convalescent plasma obtained in the early stage of the COVID-19 pandemic. Of note, among the natural escape mutations, L452R enhanced ACE2 binding affinity, indicating that it potentially increased virulence. Overall, the in-depth maps may have far-reaching value for surveillance of SARS-CoV-2 immune escape variants and guidance of vaccine design.

Correlation Between Local Air Temperature and the COVID-19 Pandemic in Hubei, China.

Objective: To clarify the correlation between temperature and the COVID-19 pandemic in Hubei. Methods: We collected daily newly confirmed COVID-19 cases and daily temperature for six cities in Hubei Province, assessed their correlations, and established regression models. Results: For temperatures ranging from -3.9 to 16.5°C, daily newly confirmed cases were positively correlated with the maximum temperature ~0-4 days prior or the minimum temperature ~11-14 days prior to the diagnosis in almost all selected cities. An increase in the maximum temperature 4 days prior by 1°C was associated with an increase in the daily newly confirmed cases (~129) in Wuhan. The influence of temperature on the daily newly confirmed cases in Wuhan was much more significant than in other cities. Conclusion: Government departments in areas where temperatures range between -3.9 and 16.5°C and rise gradually must take more active measures to address the COVID-19 pandemic.

Longitudinal transcriptome analyses show robust T cell immunity during recovery from COVID-19.

Understanding the processes of immune regulation in patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for improving treatment. Here, we performed longitudinal whole-transcriptome RNA sequencing on peripheral blood mononuclear cell (PBMC) samples from 18 patients with coronavirus disease 2019 (COVID-19) during their treatment, convalescence, and rehabilitation. After analyzing the regulatory networks of differentially expressed messenger RNAs (mRNAs), microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) between the different clinical stages, we found that humoral immunity and type I interferon response were significantly downregulated, while robust T-cell activation and differentiation at the whole transcriptome level constituted the main events that occurred during recovery from COVID-19. The formation of this T cell immune response might be driven by the activation of activating protein-1 (AP-1) related signaling pathway and was weakly affected by other clinical features. These findings uncovered the dynamic pattern of immune responses and indicated the key role of T cell immunity in the creation of immune protection against this disease.

Clinical Characteristics of Patients With Progressive and Non-progressive Coronavirus Disease 2019: Evidence From 365 Hospitalised Patients in Honghu and Nanchang, China.

Background: Coronavirus disease (COVID-19) has swept around the globe and led to a worldwide catastrophe. Studies examining the disease progression of patients with non-severe disease on admission are scarce but of profound importance in the early identification of patients at a high risk of deterioration. Objectives: To elucidate the differences in clinical characteristics between patients with progressive and non-progressive COVID-19 and to determine the risk factors for disease progression. Study design: Clinical data of 365 patients with non-severe COVID-19 from 1 January 2020 to 18 March 2020 were retrospectively collected. Patients were stratified into progressive and non-progressive disease groups. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for disease progression. Results: Compared with patients with non-progressive disease, those who progressed to severe COVID-19 were older and had significantly decreased lymphocyte and eosinophil counts; increased neutrophil and platelet counts; lower albumin levels; higher levels of lactate dehydrogenase, C-reactive protein (CRP), creatinine, creatinine kinase, and urea nitrogen; and longer prothrombin times. Hypertension, fever, fatigue, anorexia, bacterial coinfection, bilateral patchy shadowing, antibiotic and corticosteroid administration, and oxygen support had a significantly higher incidence among patients with progressive disease. A significantly longer duration of hospital stay was also observed in patients with progressive disease. Bilateral patchy shadowing (OR = 4.82, 95% CI: 1.33-17.50; P = 0.017) and elevated levels of creatinine (OR =6.24, 95% CI: 1.42-27.40; P = 0.015), and CRP (OR = 7.28, 95% CI: 2.56-20.74; P < 0.001) were independent predictors for disease progression. Conclusion: The clinical characteristics of patients with progressive and non-progressive COVID-19 were significantly different. Bilateral patchy shadowing and increased levels of creatinine, and CRP were independent predictors of disease progression.

COVID-19 data visualization public welfare activity

The coronavirus disease 2019 (COVID-19) pandemic started in early 2020. At the beginning of February, a public welfare activity in epidemic data visualization, jointly launched by China Computer Federation CCF CAD & CG Technical Committee, Alibaba Cloud Tianch, JiqiZhixin, Alibaba Cloud DataV, and DataWhale, was launched with the theme “Fighting the Epidemic with One Mind and Talents like Tianchi.” Developers in general are expected to focus on several demand scenarios, such as epidemic situation display, epidemic popular science, trend prediction, material-supply situation, and rework and return situation of employees from all sectors and areas, to discover the relationship between complex heterogeneous multi-source data, develop various upbeat works and present useful information to the public in a coherent manner. The entry works take the form of data visualization and are divided into two categories: popular science publicity and application scenarios. The popular science publicity category includes works for the public, focused on epidemic situation display, epidemic popular science publicity, epidemic prevention and control, and others. The application scenario category consists of the works of frontline officers, which can provide anti-epidemic workers with effective data tools for efficient and intuitive epidemic analysis;offer reliable, understandable, and easily transmitted information for disease prevention;and assist governments, enterprises, and institutions in the fight against COVID-19.

Development and Validation of a Deep Learning-Based Model Using Computed Tomography Imaging for Predicting Disease Severity of Coronavirus Disease 2019.

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is sweeping the globe and has resulted in infections in millions of people. Patients with COVID-19 face a high fatality risk once symptoms worsen; therefore, early identification of severely ill patients can enable early intervention, prevent disease progression, and help reduce mortality. This study aims to develop an artificial intelligence-assisted tool using computed tomography (CT) imaging to predict disease severity and further estimate the risk of developing severe disease in patients suffering from COVID-19. MATERIALS AND METHODS: Initial CT images of 408 confirmed COVID-19 patients were retrospectively collected between January 1, 2020 and March 18, 2020 from hospitals in Honghu and Nanchang. The data of 303 patients in the People's Hospital of Honghu were assigned as the training data, and those of 105 patients in The First Affiliated Hospital of Nanchang University were assigned as the test dataset. A deep learning based-model using multiple instance learning and residual convolutional neural network (ResNet34) was developed and validated. The discrimination ability and prediction accuracy of the model were evaluated using the receiver operating characteristic curve and confusion matrix, respectively. RESULTS: The deep learning-based model had an area under the curve (AUC) of 0.987 (95% confidence interval [CI]: 0.968-1.00) and an accuracy of 97.4% in the training set, whereas it had an AUC of 0.892 (0.828-0.955) and an accuracy of 81.9% in the test set. In the subgroup analysis of patients who had non-severe COVID-19 on admission, the model achieved AUCs of 0.955 (0.884-1.00) and 0.923 (0.864-0.983) and accuracies of 97.0 and 81.6% in the Honghu and Nanchang subgroups, respectively. CONCLUSION: Our deep learning-based model can accurately predict disease severity as well as disease progression in COVID-19 patients using CT imaging, offering promise for guiding clinical treatment.

Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019.

BACKGROUND: Information regarding risk factors associated with severe coronavirus disease (COVID-19) is limited. This study aimed to develop a model for predicting COVID-19 severity. METHODS: Overall, 690 patients with confirmed COVID-19 were recruited between 1 January and 18 March 2020 from hospitals in Honghu and Nanchang; finally, 442 patients were assessed. Data were categorised into the training and test sets to develop and validate the model, respectively. FINDINGS: A predictive HNC-LL (Hypertension, Neutrophil count, C-reactive protein, Lymphocyte count, Lactate dehydrogenase) score was established using multivariate logistic regression analysis. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC]=0.861, 95% confidence interval [CI]: 0.800-0.922; P<0.001); Honghu internal validation cohort (AUC=0.871, 95% CI: 0.769-0.972; P<0.001); and Nanchang external validation cohort (AUC=0.826, 95% CI: 0.746-0.907; P<0.001) and outperformed other models, including CURB-65 (confusion, uraemia, respiratory rate, BP, age ≥65 years) score model, MuLBSTA (multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension, and age) score model, and neutrophil-to-lymphocyte ratio model. The clinical significance of HNC-LL in accurately predicting the risk of future development of severe COVID-19 was confirmed. INTERPRETATION: We developed an accurate tool for predicting disease severity among COVID-19 patients. This model can potentially be used to identify patients at risks of developing severe disease in the early stage and therefore guide treatment decisions. FUNDING: This work was supported by the National Nature Science Foundation of China (grant no. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015).

Clinical features of COVID-19 patients in one designated medical institutions in Chengdu, China (preprint)

OBJECTIVE: To study the clinical characteristics of patients infected with the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) responsible for coronavirus disease (COVID-2019).METHODS: Data were collected from 20 patients admitted to the Pidu District People’s Hospital in Chengdu from January 26, 2020 to March 1, 2020 with laboratory-confirmed SARS-Cov-2 infection. Clinical data were collected using the World Health Organization (WHO) nCoV CASE RECORDFORM Version 1.2 28JAN2020, which includes parameters such as: temperature, epidemiological characteristics, social network, history of exposure, and incubation period. If information was unclear, the team reviewed the original data and contacted patients directly if necessary.RESULTS: The median age of the 20 COVID-19 infected patients studied was 42.5 years. In this cohort, four patients became severely ill and one deteriorated rapidly during treatment. This patient was transferred to another medical center with an intensive care unit (ICU) for treatment. This patient died after admission to the ICU. Two of the twenty patients remained positive SARS-Cov-2 more than three weeks, and they were quarantined in a medical facility without medication. According to our analysis, all of the studied cases were infected by human-to-human transmission due to the lack of protective measures; transmission through contact within families requires confirmation. The most common symptoms at onset of illness were fever in 13 (65%) patients, cough in 9 (45%), headache in 3 (15%), fatigue in 6 (30%), diarrhea in 3 (15%), and abdominal pain in 2 (10%). Six patients (30%) developed shortness of breath upon admission. The median time from exposure to onset of illness was6.5 days (interquartile range 3.25–9 days), and from the onset of symptoms to first hospital admission was 3.5 (1.25–7) days.CONCLUSION: Compared with patients infected with SARS-Cov-2 in Wuhan (up to the end of February 2020), the symptoms of patients in one hospital in Chengdu, Sichuan Province, were relatively mild and patients were discharged from the hospital after only a short stay. However, the fasting blood glucose of the infected individuals was found to be slightly elevated because of the state of emergency. The dynamic changes in lymphocyte levels can predict disease status of COVID-19. They are also suggestive of changes in mean platelet volume during disease progression. This suggests that the patients had mild cases of COVID-19. However, because there is no effective drug treatment for COVID-19, it is important to detect and identify severe cases from mild cases early.