TEDD: a database of temporal gene expression patterns during multiple developmental periods in human and model organisms.

Characterization of the specific expression and chromatin profiles of genes enables understanding how they contribute to tissue/organ development and the mechanisms leading to diseases. Whilst the number of single-cell sequencing studies is increasing dramatically; however, data mining and reanalysis remains challenging. Herein, we systematically curated the up-to-date and most comprehensive datasets of sequencing data originating from 2760 bulk samples and over 5.1 million single-cells from multiple developmental periods from humans and multiple model organisms. With unified and systematic analysis, we profiled the gene expression and chromatin accessibility among 481 cell-types, 79 tissue-types and 92 timepoints, and pinpointed cells with the co-expression of target genes. We also enabled the detection of gene(s) with a temporal and cell-type specific expression profile that is similar to or distinct from that of a target gene. Additionally, we illustrated the potential upstream and downstream gene-gene regulation interactions, particularly under the same biological process(es) or KEGG pathway(s). Thus, TEDD (Temporal Expression during Development Database), a value-added database with a user-friendly interface, not only enables researchers to identify cell-type/tissue-type specific and temporal gene expression and chromatin profiles but also facilitates the association of genes with undefined biological functions in development and diseases. The database URL is https://TEDD.obg.cuhk.edu.hk/.

Therapeutic potency of compound RMY-205 for pulmonary fibrosis induced by SARS-CoV-2 nucleocapsid protein.

Pulmonary fibrosis is a typical sequela of coronavirus disease 2019 (COVID-19), which is linked with a poor prognosis for COVID-19 patients. However, the underlying mechanism of pulmonary fibrosis induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. Here, we demonstrated that the nucleocapsid (N) protein of SARS-CoV-2 induced pulmonary fibrosis by activating pulmonary fibroblasts. N protein interacted with the transforming growth factor ß receptor I (TßRI), to disrupt the interaction of TßRI-FK506 Binding Protein12 (FKBP12), which led to activation of TßRI to phosphorylate Smad3 and boost expression of pro-fibrotic genes and secretion of cytokines to promote pulmonary fibrosis. Furthermore, we identified a compound, RMY-205, that bound to Smad3 to disrupt TßRI-induced Smad3 activation. The therapeutic potential of RMY-205 was strengthened in mouse models of N protein-induced pulmonary fibrosis. This study highlights a signaling pathway of pulmonary fibrosis induced by N protein and demonstrates a novel therapeutic strategy for treating pulmonary fibrosis by a compound targeting Smad3.

Evaluation of COVID-19 vaccines in primary prevention against infections and reduction in severity of illness following the outbreak of SARS-CoV-2 omicron variant in Shanghai.

Objectives: To evaluate COVID-19 vaccines in primary prevention against infections and lessen the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai. Data sources: Data from 153,544 COVID-19 patients admitted to the Shanghai "Four-Leaf Clover" Fangcang makeshift shelter hospital were collected using a structured electronic questionnaire, which was then merged with electronic medical records of the hospital. For healthy controls, data on vaccination status and other information were obtained from 228 community-based residents, using the same structured electronic questionnaire. Methods: To investigate whether inactivated vaccines were effective in protecting against SARS-CoV-2 virus, we estimated the odds ratio (OR) of the vaccination by comparing cases and matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied multivariate stepwise logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in the COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors. Results: Of the 153,544 COVID-19 patients included in the analysis, the mean age was 41.59 years and 90,830 were males (59.2%). Of the study cohort, 118,124 patients had been vaccinated (76.9%) and 143,225 were asymptomatic patients (93.3%). Of the 10,319 symptomatic patients, 10,031 (97.2%), 281 (2.7%), and 7 (0.1%) experienced mild, moderate, and severe infections, respectively. Hypertension (8.7%) and diabetes (3.0%) accounted for the majority of comorbidities. There is no evidence that the vaccination helped protect from infections (OR = 0.82, p = 0.613). Vaccination, however, offered a small but significant protection against symptomatic infections (RR = 0.92, p < 0.001) and halved the risk of moderate/severe infections (OR = 0.48, 95% CI: 0.37-0.61). Older age (≥60 years) and malignant tumors were significantly associated with moderate/severe infections. Conclusion: Inactivated COVID-19 vaccines helped provide small but significant protection against symptomatic infections and halved the risk of moderate/severe illness among symptomatic patients. The vaccination was not effective in blocking the SARS-CoV-2 Omicron Variant community spread.

A COVID-19 medical image classification algorithm based on Transformer.

Coronavirus 2019 (COVID-19) is a new acute respiratory disease that has spread rapidly throughout the world. This paper proposes a novel deep learning network based on ResNet-50 merged transformer named RMT-Net. On the backbone of ResNet-50, it uses Transformer to capture long-distance feature information, adopts convolutional neural networks and depth-wise convolution to obtain local features, reduce the computational cost and acceleration the detection process. The RMT-Net includes four stage blocks to realize the feature extraction of different receptive fields. In the first three stages, the global self-attention method is adopted to capture the important feature information and construct the relationship between tokens. In the fourth stage, the residual blocks are used to extract the details of feature. Finally, a global average pooling layer and a fully connected layer perform classification tasks. Training, verification and testing are carried out on self-built datasets. The RMT-Net model is compared with ResNet-50, VGGNet-16, i-CapsNet and MGMADS-3. The experimental results show that the RMT-Net model has a Test_ acc of 97.65% on the X-ray image dataset, 99.12% on the CT image dataset, which both higher than the other four models. The size of RMT-Net model is only 38.5 M, and the detection speed of X-ray image and CT image is 5.46 ms and 4.12 ms per image, respectively. It is proved that the model can detect and classify COVID-19 with higher accuracy and efficiency.

Recent advances in respiratory immunization: A focus on COVID-19 vaccines.

The development of vaccines has always been an essential task worldwide since vaccines are regarded as powerful weapons in protecting the global population. Although the vast majority of currently authorized human vaccinations are administered intramuscularly or subcutaneously, exploring novel routes of immunization has been a prominent area of study in recent years. This is particularly relevant in the face of pandemic diseases, such as COVID-19, where respiratory immunization offers distinct advantages, such as inducing systemic and mucosal responses to prevent viral infections in both the upper and lower respiratory tracts and also leading to higher patient compliance. However, the development of respiratory vaccines confronts challenges due to the physiological barriers of the respiratory tract, with most of these vaccines still in the research and development stage. In this review, we detail the structure of the respiratory tract and the mechanisms of mucosal immunity, as well as the obstacles to respiratory vaccination. We also examine the considerations necessary in constructing a COVID-19 respiratory vaccine, including the dosage form of the vaccines, potential excipients and mucosal adjuvants, and delivery systems and devices for respiratory vaccines. Finally, we present a comprehensive overview of the COVID-19 respiratory vaccines currently under clinical investigation. We hope this review can provide valuable insights and inspiration for the future development of respiratory vaccinations.

Has the "Double Reduction" policy relieved stress? A follow-up study on Chinese adolescents.

PURPOSE: "Double Reduction" Policy requires schools to reduce the burden of excessive homework and off-campus training for Chinese students to reduce their academic stress and promote mental health. We conducted a study in compulsory education students before and after the "Double Reduction" Policy to explore changes in mental health problems and relevant influential factors. METHODS: A total of 28,398 elementary and junior high school students completed both waves of the survey through electronic questionnaires. Depressive symptoms were assessed using the Patient Heath Questionnaire (PHQ-9), and anxiety symptoms were assessed using the Generalized Anxiety Disorder Scale (GDA-7). Demographic information was evaluated at baseline, and "Double Reduction" related factors and negative life events were measured at follow up. RESULTS: The overall depression and anxiety levels significantly decreased after the "Double Reduction" Policy. Girls, poor parental marital quality, chronic physical illness, and psychiatric family history were related to increased occurrence of mental health. Sleep duration > 8 h/night, reduced homework, more extracurricular activities more time with parents, and reduced academic stress were protective factors against mental health problems. CONCLUSIONS: The "Double Reduction" Policy has improved the mental health symptoms of students to a certain extent. Appropriately increasing sleep time, participating in more extracurricular activities and parental involvement, and reducing the burden of homework are effective ways to promote the development of students' mental health.

Relationship between nosocomial infections and coronavirus disease 2019 in the neurosurgery unit: clinical characteristics and outcomes from a Chinese Tertiary-Care Hospital.

BACKGROUND: The COVID-19 pandemic has raised awareness of infection prevention and control. We found that the incidence of nosocomial infection in neurosurgery has changed. This study aimed to evaluate the impact of "coronavirus disease 2019 (COVID-19) prevention and control measures" on nosocomial infections in neurosurgery. METHODS: To explore changes in nosocomial infections in neurosurgery during the COVID-19 pandemic, the clinical data of inpatients undergoing neurosurgery at Taizhou Hospital of Zhejiang Province between January 1 and April 30, 2020 (COVID-19 era) were first analyzed and then compared with those from same period in 2019 (first pre-COVID-19 era). We also analyzed data between May 1 and December 31, 2020 (post-COVID-19 era) at the same time in 2019 (second pre-COVID-19 era). RESULTS: The nosocomial infection rate was 7.85% (54/688) in the first pre-COVID-19 era and 4.30% (26/605) in the COVID-19 era (P = 0.01). The respiratory system infection rate between the first pre-COVID-19 and COVID-19 eras was 6.1% vs. 2.0% (P < 0.01), while the urinary system infection rate was 1.7% vs. 2.0% (P = 0.84). Between the first pre-COVID-19 and COVID-19 eras, respiratory system and urinary infections accounted for 77.78% (42/54) vs. 46.15% (12/26) and 22.22% (12/54) vs. 46.15% (12/26) of the total nosocomial infections, respectively (P < 0.01). Between the second pre-COVID-19 and post-COVID-19 eras, respiratory system and urinary accounted for 53.66% (44/82) vs. 40.63% (39/96) and 24.39% (20/82) vs. 40.63% (39/96) of the total nosocomial infections, respectively (P = 0.02). CONCLUSIONS: The incidence of nosocomial infections in neurosurgery reduced during the COVID-19 pandemic. The reduction was primarily observed in respiratory infections, while the proportion of urinary infections increased significantly.

Rethinking Lockdown Policies in the Pre-Vaccine Era of COVID-19: A Configurational Perspective.

The significance of lockdown policies for controlling the COVID-19 pandemic is widely recognized. However, most studies have focused on individual lockdown measures. The effectiveness of lockdown policy combinations has not been examined from a configurational perspective. This research applies fuzzy-set qualitative comparative analysis (fsQCA) to examine different lockdown policy combinations associated with high-epidemic situations in 84 countries. A high-epidemic situation can occur through three different "weak-confined" patterns of lockdown policy combinations. The findings demonstrate that a combination of lockdown policies is more successful than any single lockdown policy, whereas the absence of several key measures in policy combinations can lead to a high-epidemic situation. The importance of international travel controls can become obscured when they are the only measures adopted, and a high-epidemic situation can still arise where restrictions are placed on international travel but not on public transport or when workplaces are closed but schools remain open.

Status quo and influencing factors of post-traumatic stress disorder among front-line anti-epidemic medical staff

[Background] Front-line medical staff are an important group in fighting against Coronavirus Disease 2019 (COVID-19), and their mental health should not be ignored. [Objective] This study investigates the current situation and influencing factors of post-traumatic stress disorder (PTSD) among front-line anti-epidemic medical staff during COVID-19 epidemic. [Methods] Medical staff who had participated in fighting against the COVID-19 epidemic wereselected from three grade III Class A hospitals and four grade II Class A hospitals in a city of Hubei Province by convenient sampling method in May 2020. The survey was conducted online using the Post-traumatic Stress Checklist-Civilian Version (PCL-C) as the main survey tool to investigate current situation and characteristics of PTSD among these participants. A total of 1120 questionnaires were collected, of which 1071 were valid, and the effective rate was 95.6%. [Results] Of the 1071 participants, the average age was (32.59±5.21) years;the ratio of male to female was 1: 5.02;the ratio of doctor to nurse was 1:5.8;nearly 70% participants came from grade III Class A hospitals;married participants accounted for 75.4%;most of them held a bachelor degree or above (86.5%);members of the Communist Party of China (CPC) accounted for 22.9%;50.9% had junior titles;the working years were mainly 5−10 years (42.8%);more than 80.0% participants volunteered to join the front-line fight;95.1% participants received family support;43.0% participated in rescue missions;78.1% participants fought the epidemic in their own hospitals;more than 60% participants considered the workload was greater than before;34.4% participants fought in the front-line for 2−4 weeks, and 23.5% participants did for more than 6 weeks. There were 111 cases of positive PTSD syndromes (PCL-C total score ≥38) with an overall positive rate of 10.4%, and the scores of reexperience [1.40 (1.00, 1.80)] and hypervigilance [1.40 (1.00, 2.00)] were higher than the score of avoidance [1.14 (1.00, 2.57)]. The results of univariate analysis revealed that PTSD occurred differently among participants grouped by age, political affiliation, working years, anti-epidemic activities location, accumulated working hours in fighting against COVID-19, having child parenting duty, voluntariness, family support, whether family members participated in front-line activities, and rescue mission assignment (P<0.05). The results of logistic regression analysis showed that the incidence rates of reporting PTSD syndromes in medical personnel aged 31−40 years (OR=0.346, 95%CI: 0.164−0.730) and aged 41 years and above (OR=0.513, 95%CI: 0.319-0.823) were lower than that in those aged 20−30 years;the incidence rates of reporting PTSD syndromes in medical staff who were CPC members (OR=0.499, 95%CI: 0.274−0.909), volunteered to participate (OR=0.584, 95%CI: 0.360−0.945), and received family support (OR=0.453, 95%CI: 0.222-0.921) were lower than those did not (P<0.05);the incidence rates of reporting PTSD syndromes among medical workers who had child parenting duty (OR=2.372, 95%CI: 1.392−4.042), whose family members participated in front-line activities (OR=1.709, 95%CI: 1.135−2.575), and who participated in rescue missions (OR=1.705, 95%CI: 1.133-2.565) were higher than those who did not (P<0.05). [Conclusion] The positive PTSD syndrome rate is 10.4% in the front-line anti-epidemic medical staff. Age, political affiliation, voluntariness, family support, having child parenting duty, with a family members participating in the fight, and rescue mission assignment are the influencing factors of PTSD.

T-cell receptor repertoires as potential diagnostic markers for patients with COVID-19.

OBJECTIVE: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an ongoing global health emergency. T-cell receptors (TCRs) are crucial mediators of antiviral adaptive immunity. This study sought to comprehensively characterize the TCR repertoire changes in patients with COVID-19. METHODS: A large sample size multi-center randomized controlled trial was implemented to study the features of the TCR repertoire and identify COVID-19 disease-related TCR sequences. RESULTS: It was found that some T-cell receptor beta chain (TCRß) features differed markedly between COVID-19 patients and healthy controls, including decreased repertoire diversity, longer complementarity-determining region 3 (CDR3) length, skewed utilization of the TCRß variable gene/joining gene (TRBV/J), and a high degree of TCRß sharing in COVID-19 patients. Moreover, this analysis showed that TCR repertoire diversity declines with aging, which may be a cause of the higher infection and mortality rates in elderly patients. Importantly, a set of TCRß clones that can distinguish COVID-19 patients from healthy controls with high accuracy was identified. Notably, this diagnostic model demonstrates 100% specificity and 82.68% sensitivity at 0-3 days post diagnosis. CONCLUSIONS: This study lays the foundation for immunodiagnosis and the development of medicines and vaccines for COVID-19 patients.

Advancedoral vaccine delivery strategies for improving the immunity.

Infectious diseases continue to inflict a high global disease burden. The consensus is that vaccination is the most effective option against infectious diseases. Oral vaccines have unique advantages in the prevention of global pandemics due to their ease of use, high compliance, low cost, and the ability to induce both systemic and mucosal immune responses. However, challenges of adapting vaccines for oral administration remain significant. Foremost among these are enzymatic and pH-dependent degradation of antigens in the stomach and intestines, the low permeability of mucus barrier, the nonspecific uptake of antigens at the intestinal mucosal site, and the immune suppression result from the elusive immune tolerance mechanisms. Innovative delivery techniques promise great potential for improving the flexibility and efficiency of oral vaccines. A better understanding of the delivery approaches and the immunological mechanisms of oral vaccine delivery systems may provide new scientific insight and tools for developing the next-generation oral vaccine. Here, an overview of the advanced technologies in the field of oral vaccination is proposed, including mucus-penetrating nanoparticle (NP), mucoadhesive delivery vehicles, targeting antigen-presenting cell (APC) nanocarriers and enhanced paracellular delivery strategies and so on. Meanwhile, the mechanisms of delivery vectors interact with mucosal barriers are discussed.

A multi-scale gated multi-head attention depthwise separable CNN model for recognizing COVID-19.

Coronavirus 2019 (COVID-19) is a new acute respiratory disease that has spread rapidly throughout the world. In this paper, a lightweight convolutional neural network (CNN) model named multi-scale gated multi-head attention depthwise separable CNN (MGMADS-CNN) is proposed, which is based on attention mechanism and depthwise separable convolution. A multi-scale gated multi-head attention mechanism is designed to extract effective feature information from the COVID-19 X-ray and CT images for classification. Moreover, the depthwise separable convolution layers are adopted as MGMADS-CNN's backbone to reduce the model size and parameters. The LeNet-5, AlexNet, GoogLeNet, ResNet, VGGNet-16, and three MGMADS-CNN models are trained, validated and tested with tenfold cross-validation on X-ray and CT images. The results show that MGMADS-CNN with three attention layers (MGMADS-3) has achieved accuracy of 96.75% on X-ray images and 98.25% on CT images. The specificity and sensitivity are 98.06% and 96.6% on X-ray images, and 98.17% and 98.05% on CT images. The size of MGMADS-3 model is only 43.6 M bytes. In addition, the detection speed of MGMADS-3 on X-ray images and CT images are 6.09 ms and 4.23 ms for per image, respectively. It is proved that the MGMADS-3 can detect and classify COVID-19 faster with higher accuracy and efficiency.

Observation on distribution of TCM patterns and changes of peripheral blood cell count and chest imaging in mild and moderate COVID-19 patients

Objective: To observe distribution of traditional Chinese medicine(TCM) patterns and changes of peripheral blood cell count and chest imaging in mild and moderate COVID-19 patients.

Insomnia and other sleep-related problems during the remission period of the COVID-19 pandemic: A large-scale survey among college students in China.

This study aimed to evaluate the sleep-related problems and predictors of probable clinical insomnia among college students during the COVID-19 remission period in China. 146,102 college students from 22 colleges/universities in Guangdong province participated in this study from 1th to 15th June, 2020. Self-administered questionnaires were used to assess demographic characteristics. Sleep-related problems, depression and anxiety symptoms were measured by Youth Self-Rating Insomnia Scale, Patient Health Questionnaire-9 and Generalized Anxiety Disorder Scale-7, respectively. The prevalence of difficulty in initiating sleep, difficulty in maintaining sleep, early morning awakening, sleep insufficiency, unrefreshing sleep and daytime functioning impairment were 7.2%, 3.4%, 3.5%, 9.6%, 14.6%, and 7.6%, respectively. 16.9% students had varying degrees of insomnia and 6.3% were considered as displaying probable clinical insomnia. Moreover, being urban residents, having a history of physical or mental illness, and probable clinical depression or anxiety were significant risk factors of probable clinical insomnia, while college senior degree and 7-8 hours' sleep duration per day was the protective factor for probable clinical insomnia. Unrefreshing sleep was the most prominent sleep problem among college students during COVID-19 remission in China. Good sleep hygiene practices are strongly suggested to develop in the time of prolonged home isolation.

Antibody response in COVID-19 patients with and without re-positive RT-PCR results during the convalescent phase.

Nucleic acid testing and antibody testing data from 143 recovered COVID-19 patients during the convalescent phase were retrospectively analyzed. A total of 23 (16.1%) recovered patients re-tested positive for SARS-CoV-2 RNA by RT-PCR. Three months after symptom onset, 100% and 99.3% of the patients remained positive for total and IgG antibodies, and the antibody levels remained high. IgM antibodies declined rapidly, with a median time to seroconversion of 67 (95% CI: 59, 75) days after onset. Approximately 25% of patients were seronegative for IgA antibodies at three months after onset. There was no statistically significant difference in antibody kinetics between patients with and without re-positive RT-PCR results during the convalescent phase.

Corticosteroid therapy for coronavirus disease 2019-related acute respiratory distress syndrome: a cohort study with propensity score analysis.

BACKGROUND: The impact of corticosteroid therapy on outcomes of patients with coronavirus disease 2019 (COVID-19) is highly controversial. We aimed to compare the risk of death between COVID-19-related ARDS patients with corticosteroid treatment and those without. METHODS: In this single-center retrospective observational study, patients with ARDS caused by COVID-19 between January 20, 2020, and February 24, 2020, were enrolled. The primary outcome was 60-day in-hospital death. The exposure was prescribed systemic corticosteroids or not. Time-dependent Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for 60-day in-hospital mortality. RESULTS: A total of 382 patients [60.7 ± 14.1 years old (mean ± SD), 61.3% males] were analyzed. The median of sequential organ failure assessment (SOFA) score was 2.0 (IQR 2.0-3.0). Of these cases, 94 (24.6%) patients had invasive mechanical ventilation. The number of patients received systemic corticosteroids was 226 (59.2%), and 156 (40.8%) received standard treatment. The maximum dose of corticosteroids was 80.0 (IQR 40.0-80.0) mg equivalent methylprednisolone per day, and duration of corticosteroid treatment was 7.0 (4.0-12.0) days in total. In Cox regression analysis using corticosteroid treatment as a time-varying variable, corticosteroid treatment was associated with a significant reduction in risk of in-hospital death within 60 days after adjusting for age, sex, SOFA score at hospital admission, propensity score of corticosteroid treatment, comorbidities, antiviral treatment, and respiratory supports (HR 0.42; 95% CI 0.21, 0.85; p = 0.0160). Corticosteroids were not associated with delayed viral RNA clearance in our cohort. CONCLUSION: In this clinical practice setting, low-dose corticosteroid treatment was associated with reduced risk of in-hospital death within 60 days in COVID-19 patients who developed ARDS.

Coagulopathy is a major extrapulmonary risk factor for mortality in hospitalized patients with COVID-19 with type 2 diabetes.

INTRODUCTION: To investigate the risk factors for the death in patients with COVID-19 with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: We retrospectively enrolled inpatients with COVID-19 from Wuhan Jinyintan Hospital (Wuhan, China) between December 25, 2019, and March 3, 2020. The epidemiological and clinical data were compared between non-T2DM and T2DM or between survivors and non-survivors. Univariable and multivariable Cox regression analyses were used to explore the effect of T2DM and complications on in-hospital death. RESULTS: A total of 1105 inpatients with COVID-19, 967 subjects with without T2DM (n=522 male, 54.0%) and 138 subjects with pre-existing T2DM (n=82 male, 59.4%) were included for baseline characteristics analyses. The complications were also markedly increased in patients with pre-existing T2DM, including acute respiratory distress syndrome (ARDS) (48.6% vs 32.3%, p<0.001), acute cardiac injury (ACI) (36.2% vs 16.7%, p<0.001), acute kidney injury (AKI) (24.8% vs 9.5%, p<0.001), coagulopathy (24.8% vs 11.1%, p<0.001), and hypoproteinemia (21.2% vs 9.4%, p<0.001). The in-hospital mortality was significantly higher in patients with pre-existing T2DM compared with those without T2DM (35.3% vs 17.4%, p<0.001). Moreover, in hospitalized patients with COVID-19 with T2DM, ARDS and coagulopathy were the main causes of mortality, with an HR of 7.96 (95% CI 2.25 to 28.24, p=0.001) for ARDS and an HR of 2.37 (95% CI 1.08 to 5.21, p=0.032) for coagulopathy. This was different from inpatients with COVID-19 without T2DM, in whom ARDS and cardiac injury were the main causes of mortality, with an HR of 12.18 (95% CI 5.74 to 25.89, p<0.001) for ARDS and an HR of 4.42 (95% CI 2.73 to 7.15, p<0.001) for cardiac injury. CONCLUSIONS: Coagulopathy was a major extrapulmonary risk factor for death in inpatients with COVID-19 with T2DM rather than ACI and AKI, which were well associated with mortality in inpatients with COVID-19 without T2DM.

Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China.

Importance: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China, and has subsequently spread worldwide. Risk factors for the clinical outcomes of COVID-19 pneumonia have not yet been well delineated. Objective: To describe the clinical characteristics and outcomes in patients with COVID-19 pneumonia who developed acute respiratory distress syndrome (ARDS) or died. Design, Setting, and Participants: Retrospective cohort study of 201 patients with confirmed COVID-19 pneumonia admitted to Wuhan Jinyintan Hospital in China between December 25, 2019, and January 26, 2020. The final date of follow-up was February 13, 2020. Exposures: Confirmed COVID-19 pneumonia. Main Outcomes and Measures: The development of ARDS and death. Epidemiological, demographic, clinical, laboratory, management, treatment, and outcome data were also collected and analyzed. Results: Of 201 patients, the median age was 51 years (interquartile range, 43-60 years), and 128 (63.7%) patients were men. Eighty-four patients (41.8%) developed ARDS, and of those 84 patients, 44 (52.4%) died. In those who developed ARDS, compared with those who did not, more patients presented with dyspnea (50 of 84 [59.5%] patients and 30 of 117 [25.6%] patients, respectively [difference, 33.9%; 95% CI, 19.7%-48.1%]) and had comorbidities such as hypertension (23 of 84 [27.4%] patients and 16 of 117 [13.7%] patients, respectively [difference, 13.7%; 95% CI, 1.3%-26.1%]) and diabetes (16 of 84 [19.0%] patients and 6 of 117 [5.1%] patients, respectively [difference, 13.9%; 95% CI, 3.6%-24.2%]). In bivariate Cox regression analysis, risk factors associated with the development of ARDS and progression from ARDS to death included older age (hazard ratio [HR], 3.26; 95% CI 2.08-5.11; and HR, 6.17; 95% CI, 3.26-11.67, respectively), neutrophilia (HR, 1.14; 95% CI, 1.09-1.19; and HR, 1.08; 95% CI, 1.01-1.17, respectively), and organ and coagulation dysfunction (eg, higher lactate dehydrogenase [HR, 1.61; 95% CI, 1.44-1.79; and HR, 1.30; 95% CI, 1.11-1.52, respectively] and D-dimer [HR, 1.03; 95% CI, 1.01-1.04; and HR, 1.02; 95% CI, 1.01-1.04, respectively]). High fever (≥39 °C) was associated with higher likelihood of ARDS development (HR, 1.77; 95% CI, 1.11-2.84) and lower likelihood of death (HR, 0.41; 95% CI, 0.21-0.82). Among patients with ARDS, treatment with methylprednisolone decreased the risk of death (HR, 0.38; 95% CI, 0.20-0.72). Conclusions and Relevance: Older age was associated with greater risk of development of ARDS and death likely owing to less rigorous immune response. Although high fever was associated with the development of ARDS, it was also associated with better outcomes among patients with ARDS. Moreover, treatment with methylprednisolone may be beneficial for patients who develop ARDS.