Retraction Note: Modeling the progression of COVID-19 deaths using Kalman Filter and AutoML.

[This retracts the article DOI: 10.1007/s00500-020-05503-5.].

Patients with advanced pancreatic and biliary cancer appear vulnerable to SARS-CoV-2 Omicron variant: An observational study during the COVID-19 outbreak in Shanghai.

Background: The COVID-19 pandemic has spread rapidly across the globe. Cancer patients have a higher risk of severe infections and associated mortality than the general population. However, the lethal effect of Omicron-variant affection on advanced pancreatic and biliary cancer patients is still not clear. Herein, we designed an observational study to shed light on the influence of the Omicron variant on this so-called "King of Cancer" and improve management of these patients with COVID-19 in the future. Methods: Omicron-infected patients with advanced pancreatic and biliary cancer were enrolled from 15 April to 31 May 2022. Four groups were set up in this study: Group 1, Omicron-infected cancer patients (N = 4); Group 2, non-infected cancer patients (N = 4); Group 3, infected non-cancer-afflicted subjects (N = 4); Group 4, non-infected non-cancer-afflicted subjects (N = 4). On Days 0, 7, and 14 after infection, the blood samples were collected dynamically from all subjects. The primary endpoints were disease severity and survival. Results: At the endpoint of this observational study, Patient Nos. 2, 3, and 4 died separately on Days 11, 25, and 13 after viral infection. All of them had advanced cancer, with a death rate of up to 75%. Group 1 presented an overall T-cell exhaustion status compared with other groups. Group 1 had obviously lower T-cell populations and higher B-cell percentages and CD4+T/CD8+T ratios (P <0.05). Time-course cytokine monitoring results showed that IL-1ß was significantly decreased in Group 1 (P <0.05) and generally kept at a low level without obvious fluctuation. IL-6 was markedly increased in infected cancer patients (P <0.01) but remained at a low level and had no apparent change during the whole infection process in non-cancer-afflicted subjects. Furthermore, several inflammatory parameter indexes indicated a tight association of Omicron infection with the disease course and prognosis of Omicron-infected cancer patients. Conclusions: Advanced pancreatic and biliary cancer patients with Omicron infection have severe symptoms and poor outcomes. More attention, protective measures, and routine healthcare services should be recommended to these vulnerable populations in clinical practice during the pandemic in the foreseeable future.

Modeling the progression of COVID-19 deaths using Kalman Filter and AutoML.

The COVID-19 pandemic continues to have a destructive effect on the health and well-being of the global population. A vital step in the battle against it is the successful screening of infected patients, together with one of the effective screening methods being radiology examination using chest radiography. Recognition of epidemic growth patterns across temporal and social factors can improve our capability to create epidemic transmission designs, including the critical job of predicting the estimated intensity of the outbreak morbidity or mortality impact at the end. The study's primary motivation is to be able to estimate with a certain level of accuracy the number of deaths due to COVID-19, managing to model the progression of the pandemic. Predicting the number of possible deaths from COVID-19 can provide governments and decision-makers with indicators for purchasing respirators and pandemic prevention policies. Thus, this work presents itself as an essential contribution to combating the pandemic. Kalman Filter is a widely used method for tracking and navigation and filtering and time series. Designing and tuning machine learning methods are a labor- and time-intensive task that requires extensive experience. The field of automated machine learning Auto Machine Learning relies on automating this task. Auto Machine Learning tools enable novice users to create useful machine learning units, while experts can use them to free up valuable time for other tasks. This paper presents an objective method of forecasting the COVID-19 outbreak using Kalman Filter and Auto Machine Learning. We use a COVID-19 dataset of Ceará, one of the 27 federative units in Brazil. Ceará has more than 235,222 confirmed cases of COVID-19 and 8850 deaths due to the disease. The TPOT automobile model showed the best result with a 0.99 of R 2 score.

DNA damage contributes to age-associated differences in SARS-CoV-2 infection.

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is known to disproportionately affect older individuals. How aging processes affect SARS-CoV-2 infection and disease progression remains largely unknown. Here, we found that DNA damage, one of the hallmarks of aging, promoted SARS-CoV-2 infection in vitro and in vivo. SARS-CoV-2 entry was facilitated by DNA damage caused by extrinsic genotoxic stress or telomere dysfunction and hampered by inhibition of the DNA damage response (DDR). Mechanistic analysis revealed that DDR increased expression of angiotensin-converting enzyme 2 (ACE2), the primary receptor of SARS-CoV-2, by activation of transcription factor c-Jun. Importantly, in vivo experiment using a mouse-adapted viral strain also verified the significant roles of DNA damage in viral entry and severity of infection. Expression of ACE2 was elevated in the older human and mice tissues and positively correlated with γH2AX, a DNA damage biomarker, and phosphorylated c-Jun (p-c-Jun). Finally, nicotinamide mononucleotide (NMN) and MDL-800, which promote DNA repair, alleviated SARS-CoV-2 infection and disease severity in vitro and in vivo. Taken together, our data provide insights into the age-associated differences in SARS-CoV-2 infection and a novel approach for antiviral intervention.

Safety and Tolerability of COVID-19 Vaccine in Children With Epilepsy: A Prospective, Multicenter Study.

BACKGROUND: We designed this study to investigate the effects of the coronavirus disease 2019 (COVID-19) vaccine on epileptic seizures, as well as its adverse effects, in children with epilepsy (<18 years). METHODS: This anonymous questionnaire study involved a multicenter prospective survey of outpatients and inpatients with epilepsy (＜18 years) registered in epilepsy clinics in eight hospitals in six cities of Shandong Province. RESULTS: A total of 224 children with epilepsy were included in the study. Fifty of them experienced general adverse events after vaccination. The most common local adverse events were pain or tenderness at the injection site. The most common systemic adverse effects were muscle soreness and headache. No severe adverse events were reported. There were no significant differences in the number of antiseizure medications (P = 0.459), gender (P = 0.336), etiology (P = 0.449), age (P = 0.499), duration of disease (P = 0.546), or seizure type (P = 0.475) between the patients with and without general adverse events. We found that the risk of seizure after vaccination was decreased in children who were seizure free for more than six months before vaccination. There was no significant difference in the number of seizures during the first month before vaccination, the first month after the first dose, and the first month after the second dose (P = 0.091). CONCLUSION: The benefits of vaccination against COVID-19 outweighed the risks of seizures/relapses and severe adverse events after vaccination for children with epilepsy.

Effect of inactivated COVID-19 vaccines on seizure frequency in patients with epilepsy: A multicenter, prospective study.

Objectives: Several COVID-19 vaccines list "uncontrolled epilepsy" as a contraindication for vaccination. This consequently restricts vaccination against COVID-19 in patients with epilepsy (PWE). However, there is no strong evidence that COVID-19 vaccination can exacerbate conditions in PWE. This study aims to determine the impact of COVID-19 vaccination on PWE. Methods: PWE were prospectively recruited from 25 epilepsy centers. We recorded the seizure frequency at three time periods (one month before the first vaccination and one month after the first and second vaccinations). A generalized linear mixed-effects model (GLMM) was used for analysis, and the adjusted incidence rate ratio (AIRR) with 95% CI was presented and interpreted accordingly. Results: Overall, 859 PWE were included in the analysis. Thirty-one (3.6%) and 35 (4.1%) patients were found to have increased seizure frequency after the two doses, respectively. Age had an interaction with time. The seizure frequency in adults decreased by 81% after the first dose (AIRR=0.19, 95% CI:0.11-0.34) and 85% after the second dose (AIRR=0.16, 95% CI:0.08-0.30). In juveniles (<18), it was 25% (AIRR=0.75, 95% CI:0.42-1.34) and 51% (AIRR=0.49, 95% CI:0.25-0.95), respectively. Interval between the last seizure before vaccination and the first dose of vaccination (ILSFV) had a significant effect on seizure frequency after vaccination. Seizure frequency in PWE with hereditary epilepsy after vaccination was significantly higher than that in PWE with unknown etiology (AIRR=1.95, 95% CI: 1.17-3.24). Two hundred and seventeen (25.3%) patients experienced non-epileptic but not serious adverse reactions. Discussion: The inactivated COVID-19 vaccine does not significantly increase seizure frequency in PWE. The limitations of vaccination in PWE should focus on aspects other than control status. Juvenile PWE should be of greater concern after vaccination because they have lower safety. Finally, PWE should not reduce the dosage of anti-seizure medication during the peri-vaccination period.

Safety and tolerability of COVID-19 vaccine in children with epilepsy: a prospective, multicenter study

Introduction We designed this study to investigate the effects of the coronavirus disease 2019 (COVID-19) vaccine on epileptic seizures, as well as its adverse effects, in children with epilepsy (< 18 years). Methods This anonymous questionnaire study involved a multicenter prospective survey of outpatients and inpatients with epilepsy (＜18 years) registered in epilepsy clinics in 8 hospitals in six cities of Shandong Province. Results A total of 224 children with epilepsy were included in the study. Fifty of them experienced general adverse events after vaccination. The most common local adverse events were pain or tenderness at the injection site. The most common systemic adverse effects were muscle soreness and headache. No severe adverse events were reported. There were no significant differences in the number of anti-seizure medications (ASMs) (P =0.459), gender (P =0.336), etiology (P =0.449), age (P =0.499), duration of disease (P =0.546) or seizure type (P =0.475) between the patients with and without general adverse events. We found that the risk of seizure after vaccination was decreased in children who were seizure-free for more than 6 months before vaccination. There was no significant difference in the number of seizures during the first month before vaccination, the first month after the first dose and the first month after the second dose (P = 0.091). Conclusion The benefits of vaccination against COVID-19 outweighed the risks of seizures/relapses and severe adverse events after vaccination for children with epilepsy.

Potential Material Basis of Yupingfeng Powder for the Prevention and Treatment of 2019 Novel Coronavirus Pneumonia: A Study Involving Molecular Docking and Molecular Dynamic Simulation Technology.

Objective: In this study, we investigated the potential material basis of Yupingfeng powder in the prevention and treatment of 2019 novel coronavirus pneumonia (NCP) by applying molecular docking and molecular dynamic simulation technology. Design: The active ingredients and predictive targets of Yupingfeng powder were sourced using the TCMSP, ETCM, and TCMIP traditional Chinese medicine databases. NCP-related targets were then acquired from the DisGeNET and GeneCards databases, and common disease-drug targets were imported into the STRING database, and Cytoscape software was used to generate a protein-protein interaction network following the use of a network topology algorithm to identify key target genes. Gene Ontology (GO) and KEGG pathway enrichment analysis was then performed using the target genes and GOEAST and DAVID online tools. The mechanism of Yupingfeng powder in the prevention and treatment of NCP was analyzed with reference to the relevant literature. AutoDock software was used for molecular docking, the preliminary analysis of binding status, and to identify the best conformation. Desmond software was used to perform molecular dynamic simulations for protein and compound complexes, perform free energy calculations and hydrogen bond analysis, and to further verify the binding mode. Results: Overall, 38 main active components and 218 predictive targets of Yupingfeng powder were identified and 298 disease targets related to NCP were retrieved from disease databases. Yupingfeng powder was found to act predominantly on the TNF, Toll-like receptor, HIF-1, NOD-like receptor, cytokine-receptor interaction, MAPK, T cell receptor, and VEGF signaling pathways. Molecular docking of the three selected key active components with the 3CL-like protease (3CL-Pro) of SARS-CoV-2 showed that they each had a strong binding force and good affinity. Conclusions: Yupingfeng powder primarily acts on multiple active ingredients and potential targets through multiple action channels and signal pathways. Molecular docking and molecular dynamic simulation technology were used to effectively predict and analyze the potential mechanism by which this Chinese medicine can combat NCP. These results provide a reference for developing new modern Chinese medicine preparations against NCP in the future.

Potential mechanism of Astragalus membranaceus in the prevention of COVID-19 based on network pharmacology and molecular docking

Objective: To explore the potential molecular mechanism of Astragalus membranaceus in the treatment of coronavirus disease 2019(COVID-19)based on the network pharmacology and molecular docking. Methods The traditional Chinese medicine systems pharmacology database and analysis platform(TCMSP)and the related literature were searched to obtain the active ingredients and predictive targets of Astragalus membranaceus. The herbal targets were selected based on STRING database for PPI network construction and the results were displayed by Cytoscape software. The key targets were screened through the algorithm of network topology and the network modules were analyzed. Gene Ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were carried out on key target genes using Gene Ontology Enrichment Analysis Software Toolkit(GOEAST)and The Database for Annotation, Visualization and Integrated Discovery(DAVID)online tools. Combined with relevant literature, the mechanism of Astragalus membranaceus in the treatment of COVID-19 was analyzed. Results A total of 19 candidate active components and 889 predictive targets of Astragalus membranaceus were selected by oral bioavailability(OB)and drug-likeness(DL)values. The preventive mechanism of Astragalus membranaceus might be closely related to the signal pathways involved in the body's living nerve ligand receptor interaction, calcium signal, T cell receptor, cAMP signal pathway and chemokines. Conclusion Astragalus membranaceus mainly plays roles in many kinds of targets through multi-approach and multi-signaling pathways.

XDeathDB: a visualization platform for cell death molecular interactions.

Lots of cell death initiator and effector molecules, signalling pathways and subcellular sites have been identified as key mediators in both cell death processes in cancer. The XDeathDB visualization platform provides a comprehensive cell death and their crosstalk resource for deciphering the signaling network organization of interactions among different cell death modes associated with 1461 cancer types and COVID-19, with an aim to understand the molecular mechanisms of physiological cell death in disease and facilitate systems-oriented novel drug discovery in inducing cell deaths properly. Apoptosis, autosis, efferocytosis, ferroptosis, immunogenic cell death, intrinsic apoptosis, lysosomal cell death, mitotic cell death, mitochondrial permeability transition, necroptosis, parthanatos, and pyroptosis related to 12 cell deaths and their crosstalk can be observed systematically by the platform. Big data for cell death gene-disease associations, gene-cell death pathway associations, pathway-cell death mode associations, and cell death-cell death associations is collected by literature review articles and public database from iRefIndex, STRING, BioGRID, Reactom, Pathway's commons, DisGeNET, DrugBank, and Therapeutic Target Database (TTD). An interactive webtool, XDeathDB, is built by web applications with R-Shiny, JavaScript (JS) and Shiny Server Iso. With this platform, users can search specific interactions from vast interdependent networks that occur in the realm of cell death. A multilayer spectral graph clustering method that performs convex layer aggregation to identify crosstalk function among cell death modes for a specific cancer. 147 hallmark genes of cell death could be observed in detail in these networks. These potential druggable targets are displayed systematically and tailoring networks to visualize specified relations is available to fulfil user-specific needs. Users can access XDeathDB for free at https://pcm2019.shinyapps.io/XDeathDB/ .

Attitudes to Being Vaccinated Against COVID-19: A Survey of People With Epilepsy in China.

Objective: We conducted a survey to assess vaccination coverage, vaccination willingness, and variables associated with vaccination hesitancy to provide evidence on coronavirus disease (COVID-19) vaccination strategies. Methods: This anonymous questionnaire study conducted a multicenter, cross-sectional survey of outpatients and inpatients with epilepsy (PWE) registered in epilepsy clinics, in 2021, in 10 hospitals in seven cities of Shandong Province. Results: A total of 600 questionnaires were distributed, and 557 valid questionnaires were returned. A total of 130 people were vaccinated against COVID-19. Among 427 unvaccinated participants, 69.32% (296/427) were willing to receive the COVID-19 vaccine in the future, and the remaining 30.68% (131/427) were unwilling to receive vaccination. Most (89.9%) of the participants believed that the role of vaccination was crucial in response to the spread of COVID-19. A significant association was found between willingness to receive the COVID-19 vaccine and the following variables: age, marital status, level of education, occupation, residence, seizure type, and seizure control after antiepileptic drug therapy. It is noteworthy that education level, living in urban areas, and seizure freedom were significantly related to willingness to receive COVID-19 vaccination. Conclusions: Vaccination is a key measure for the prevention and control of COVID-19, and most PWE are willing to be vaccinated. Vaccine safety, effectiveness, and accessibility are essential in combatting vaccine hesitation and increasing vaccination rates.

Research on Kinematics Analysis and Trajectory Planning of Novel EOD Manipulator

To address the problems of mismatch, poor flexibility and low accuracy of ordinary manipulators in the complex special deflagration work process, this paper proposes a new five-degree-of-freedom (5-DOF) folding deflagration manipulator. Firstly, the overall structure of the explosion-expulsion manipulator is introduced. The redundant degrees of freedom are formed by the parallel joint axes of the shoulder joint, elbow joint and wrist pitching joint, which increase the flexibility of the mechanism. Aiming at a complex system with multiple degrees of freedom and strong coupling of the manipulator, the virtual joint is introduced, the corresponding forward kinematics model is established by D–H method, and the inverse kinematics solution of the manipulator is derived by analytical method. In the MATLAB platform, the workspace of the manipulator is analyzed by Monte Carlo pseudo-random number method. The quintic polynomial interpolation method is used to simulate the deflagration task in joint space. Finally, the actual prototype experiment is carried out using the data obtained by simulation. The trajectory planning using the quintic polynomial interpolation method can ensure the smooth movement of the manipulator and high accuracy of operation. Furthermore, the trajectory is basically consistent with the simulation trajectory, which can realize the work requirements of putting the object into the explosion-proof tank. The new 5-DOF folding deflagration manipulator designed in this paper has stable motion and strong robustness, which can be used for deflagration during the COVID-19 epidemic.

Sputum characteristics and airway clearance methods in patients with severe COVID-19.

Critically ill patients with coronavirus disease 2019 (COVID-19) have a high case fatality rate. Hence, controlling the disease progression of severely ill COVID-19 patients to avoid the development of severe-to-critical COVID-19 is the most important target of COVID-19 treatment. The latest autopsy results of COVID-19 patients have shown the presence of viscous secretions in the airways. However, no studies are available that specifically describe and analyze the sputum characteristics and the effects of various sputum drainage methods on the prognosis of COVID-19 patients. In our study, we found that elderly COVID-19 patients were more susceptible to progression to critical illness (P = .024) and were likely to have accompanying lymphopenia (P = .035) or increased neutrophil counts (P = .019). We observed that there was a higher proportion of patients with Grade 3 sticky sputum in the critically ill group than in the noncritically ill group (P = .026), suggesting that changes in sputum characteristics may be one of the early warning signs of critical COVID-19. In addition, we found that the application rates of large doses of ambroxol (P = .043) and prone-position drainage (P = .037) were relatively high in COVID-19 patients with good prognoses, suggesting that the early application of large doses of expectorant drugs and prone-position drainage in COVID-19 patients may avoid progression to critical illness and improve the prognosis.

Clinical characteristics of asymptomatic carriers of novel coronavirus disease 2019: A multi-center study in Jiangsu Province.

Asymptomatic SARS-CoV-2-infected individuals are thought to play major roles in virus transmission. This study aimed to analyze the characteristics of asymptomatic carriers with COVID-19 to control the spread of the virus. We retrospectively investigated the clinical characteristics of 648 consecutive subjects who were enrolled in the study and were divided into asymptomatic carriers, mild cases, ordinary cases, severe or critical cases, and evaluated their impact on disease severity by means of Spearman correlation and multiple regression analyses. Receiver operating characteristic curve analysis was conducted to determine the optimum cutoff levels of laboratory findings for diagnostic predictors of asymptomatic carriers of COVID-19. In our study, a total of 648 subjects on admission with a mean age of 45.61 y including 345 males and 303 females were enrolled in our study. The leukocyte, lymphocyte, eosinophil, platelet, C-reactive protein, interleukin-6, CD3+, CD4+, and CD8 + T lymphocyte levels, and the erythrocyte sedimentation rate differed significantly among the groups (all p ≤ 0.05). Disease severity was negatively associated with the CD3+ (r = -0.340; p < 0.001), CD4+ (r = -0.290; p = 0.001) and CD8+ (r = -0.322; p < 0.001) T lymphocyte levels. The significant diagnostic predictors of asymptomatic carriers of COVID-19 included the blood cell, cytokine, and T lymphocyte subset levels. Inflammation and immune response may play important roles in disease progression. Hence, the laboratory parameters identified should be considered in clinical practice, which provide new insights into the identification of asymptomatic individuals and the prevention of virus transmission.

Analysis of 2019-nCoV receptor ACE2 expression in different tissues and its significance study.

BACKGROUND: On March 11, 2020, the World Health Organization (WHO) officially announced that the coronavirus disease 2019 (COVID-19) had reached global pandemic status. Current studies have found that angiotensin-converting enzyme 2 (ACE2) is a cell surface receptor of the novel coronavirus that plays a vital role in the pathogenesis of COVID-19. It is of immense importance for the prevention of virus transmission and treatment to clarify the distribution and expression of ACE2 in various tissues and organs of the body. METHODS: RNAseq transcriptome data and sex data were obtained from the genotype-tissue expression (GTEx) and the Cancer Genome Atlas (TCGA) databases. We separately analyzed the distribution of ACE2 expression in different tissues in the GTEx and TCGA database, and explored the correlation between sex and ACE2 expression levels. Next, the expression levels of ACE2 in different tissues and organs and its correlation with sex were analyzed once again after combing all samples from the two databases. RESULTS: ACE2 expression data were collected from the GTEx database for 6738 normal tissues. Six hundred eighteen tumor tissue data were collected from the TCGA database. The results of the analysis are consistent from different databases. The results indicated that the expression of ACE2 was the highest in the small intestines, higher in tissues such as salivary glands in the testicular, kidney, heart, thyroid and adipose tissues, while the expression of ACE2 was lower in tissues such as the spleen, brain, muscle, pituitary, and skin. There were no significant differences in the expression of ACE2 in the different organs when it came to the individual's sex. CONCLUSIONS: Our study deeply explored the distribution and expression of ACE2 in various tissues of the human body. The tissues and organs with high ACE2 expression were consistent with the current clinical and basic research results of the novel coronavirus. Our study is conducive to the discovery of potential target organs for viral infection, to provide a reference for the development of clinical progress of patients with novel coronavirus infection.

[Clinical analysis of 23 patients with coronavirus disease 2019 in Xinyang City of Henan Province].

OBJECTIVE: To analyze the epidemiological characteristics and clinical features of the patients with coronavirus disease 2019 (COVID-19), so as to provide basis for clinical diagnosis. METHODS: The epidemiology, clinical symptoms, laboratory and radiologic data of 23 patients with COVID-19 admitted to the Fifth People's Hospital of Xinyang City from January 22nd to January 29th, 2020 were retrospectively analyzed. RESULTS: There was 23 patients with COVID-19, with 15 men and 8 women, and the median age was 46.0 (40.5, 52.0) years old (ranged from 27 years old to 80 years old). Nine patients had basic disease (39.1%), including hypertension (17.4%), cardiovascular diseases (17.4%), diabetes (8.7%), hypothyroidism (4.3%) and past history of tuberculosis (4.3%). All the 23 patients had contact history in Wuhan area or with confirmed cases. Clinical symptoms included fever (100%), cough (69.6%), expectoration (43.5%), myalgia (26.1%), headache (17.4%) and dyspnea (17.4%), and the less common symptom was diarrhea (4.3%). Blood routine tests showed leukocytopenia in 11 patients (47.8%), normal leukocyte counts in 10 patients (43.5%), and leukocytosis in 2 patients (8.7%); lymphopenia was found in 13 patients (56.5%). All 23 patients had different degrees of infective lesions in chest CT, with 7 patients (30.4%) on one side and 16 patients (69.6%) on both sides. There were 19 mild patients, 4 severe patients, and no critical or death case. Complications included acute respiratory distress syndrome (17.4%). No patient was reported with liver, kidney or heart dysfunction or secondary infection. CONCLUSIONS: Epidemic history of contact, fever, pneumonia signs of chest CT, normal or decreased count of leukocyte and lymphopenia are the clinical basis for diagnosis of COVID-19. However, at present, the treatment of patients has not been completed, and the effective treatment strategy and final prognosis are unclear.

Clinical and Autoimmune Characteristics of Severe and Critical Cases of COVID-19.

In this study we report on the clinical and autoimmune characteristics of severe and critical novel coronavirus pneumonia caused by severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2). The clinical, autoimmune, and laboratory characteristics of 21 patients who had laboratory-confirmed severe and critical cases of coronavirus disease 2019 (COVID-19) from the intensive care unit of the Huangshi Central Hospital, Hubei Province, China, were investigated. A total of 21 patients (13 men and 8 women), including 8 (38.1%) severe cases and 13 (61.9%) critical cases, were enrolled. Cough (90.5%) and fever (81.0%) were the dominant symptoms, and most patients (76.2%) had at least one coexisting disorder on admission. The most common characteristics on chest computed tomography were ground-glass opacity (100%) and bilateral patchy shadowing (76.2%). The most common findings on laboratory measurement were lymphocytopenia (85.7%) and elevated levels of C-reactive protein (94.7%) and interleukin-6 (89.5%). The prevalence of anti-52 kDa SSA/Ro antibody, anti-60 kDa SSA/Ro antibody, and antinuclear antibody was 20%, 25%, and 50%, respectively. We also retrospectively analyzed the clinical and laboratory data from 21 severe and critical cases of COVID-19. Autoimmune phenomena exist in COVID-19 subjects, and the present results provide the rationale for a strategy of preventing immune dysfunction and optimal immunosuppressive therapy.