Assessing an AI-based Smart Imagery Framing and Truthing (SIFT) system to assist radiologists annotating lung abnormalities on chest X-ray images for development of deep learning models

To assess a Smart Imagery Framing and Truthing (SIFT) system in automatically labeling and annotating chest X-ray (CXR) images with multiple diseases as an assist to radiologists on multi-disease CXRs. SIFT system was developed by integrating a convolutional neural network based-augmented MaskR-CNN and a multi-layer perceptron neural network. It is trained with images containing 307,415 ROIs representing 69 different abnormalities and 67,071 normal CXRs. SIFT automatically labels ROIs with a specific type of abnormality, annotates fine-grained boundary, gives confidence score, and recommends other possible types of abnormality. An independent set of 178 CXRs containing 272 ROIs depicting five different abnormalities including pulmonary tuberculosis, pulmonary nodule, pneumonia, COVID-19, and fibrogenesis was used to evaluate radiologists' performance based on three radiologists in a double-blinded study. The radiologist first manually annotated each ROI without SIFT. Two weeks later, the radiologist annotated the same ROIs with SIFT aid to generate final results. Evaluation of consistency, efficiency and accuracy for radiologists with and without SIFT was conducted. After using SIFT, radiologists accept 93% SIFT annotated area, and variation across annotated area reduce by 28.23%. Inter-observer variation improves by 25.27% on averaged IOU. The consensus true positive rate increases by 5.00% (p=0.16), and false positive rate decreases by 27.70% (p<0.001). The radiologist's time to annotate these cases decreases by 42.30%. Performance in labelling abnormalities statistically remains the same. Independent observer study showed that SIFT is a promising step toward improving the consistency and efficiency of annotation, which is important for improving clinical X-ray diagnostic and monitoring efficiency. © 2023 SPIE.

DENGUE PROGNOSTIC BIOMARKERS PREDICT DENGUE HAEMORRHAGIC FEVER WITH HIGH SENSITIVITY AND SPECIFICITY

Ninety-six million people are symptomatically infected with Dengue globally every year. Under the current standard-of-care, up to 20% of Dengue patients may be hospitalized, while only 500,000 develop Dengue Haemorrhagic Fever (DHF) and require hospitalization. This leads to unnecessary overwhelming of hospitals in tropical countries during large Dengue epidemics, especially when healthcare systems are grappling with large numbers of COVID-19 patients. Our research team set out to discover biomarkers to prognosticate Dengue patients, and augment the infectious disease clinician's decision-making process to hospitalize Dengue patients. Host biomarkers with concentrations significantly different between pooled serum samples of Dengue Fever (DF) patients and DHF patients were identified using protein array. The prognostication capabilities of selected biomarkers were then validated over 283 adult Dengue patients recruited from three Singapore tertiary hospitals, prior to the diagnosis of DHF. Three biomarkers (A2M, CMA1 and VEGFA) were identified that provide independent prognostication value from one another, and from clinical parameters commonly monitored in Dengue patients. The combination of all three biomarkers was able to identify from as early as Day 1 after the onset of fever, DF patients whose conditions will deteriorate into DHF. The biomarkers are robust and able to predict DHF well when trained on different AI/ML algorithms (logistic regression, support vector machine, decision tree, random forest, AdaBoost and gradient boosting). When stacked, prediction models based on the biomarkers were able to predict DHF with 97.3% sensitivity, 92.7% specificity, 66.7% PPV, 99.6% NPV and an AUC of 0.978. To the best of our knowledge, our panel of three biomarkers offers the highest accuracy in prognosticating Dengue to date. Further studies are required to validate the biomarkers in different geographical settings and pilot their implementation as part of the standard-of-care workflow for Dengue patients. [ FROM AUTHOR] Copyright of International Journal of Infectious Diseases is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Can CO2 be used as an indicator of the probability of cross-infection?

The validity of using CO2 as an indicator of airborne infection probability was studied. Tracer gas measurements were conducted in a field lab with two breathing thermal manikins resembling "infected” and "susceptible” persons seated at desks. The room was ventilated with a mixing air distribution. Experiments were performed at three ventilation rates. CO2 gas was dosed into the air exhaled by the manikins to simulate the metabolic CO2 generation by people. Simultaneously, nitrous oxide (N2O) tracer gas was dosed into the air exhaled by one of the manikins ("infected person”) to simulate the emission of exhaled infectious particles. CO2 and N2O concentrations were measured at several points. The probability of infection was calculated based on the concentration of CO2 and N2O measured in the air inhaled by the exposed manikin ("susceptible person”). The results did not confirm that CO2 can be used as a proxy to assess the infection probability. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Characterization and Source Apportionment of PM in Handan—A Case Study during the COVID-19

Handan is a typical city affected by regional particulate pollution. In order to investigate particulate matter (PM) characterization, source contributions and health risks for the general populations, we collected PM samples at two sites affected by a pollution event (12–18 May 2020) during the COVID-19 pandemic and analyzed the major components (SNA, OCEC, WSIIs, and metal elements). A PCA-MLR model was used for source apportionment. The carcinogenic and non-carcinogenic risks caused by metal elements in the PM were assessed. The results show that the renewal of old neighborhoods significantly influences local PM, and primarily the PM10;the average contribution to PM10 was 27 μg/m3. The source apportionment has indicated that all other elements came from dust, except Cd, Pb and Zn, and the contribution of the dust source to PM was 60.4%. As PM2.5 grew to PM10, the PM changed from basic to acidic, resulting in a lower NH4+ concentration in PM10 than PM2.5. The carcinogenic risk of PM10 was more than 1 × 10−6 for both children and adults, and the excess mortality caused by the renewal of the community increased by 23%. Authorities should pay more attention to the impact of renewal on air quality. The backward trajectory and PSCF calculations show that both local sources and short-distance transport contribute to PM—local sources for PM10, and short-distance transport in southern Hebei, northern Henan and northern Anhui for PM2.5, SO2 and NO2. © 2023 by the authors.

A Transfer Learning Method for Covid-19 and Pneumonia Diagnosis Based on Chest Radiograph Classification

Pneumonia has been a tough and dangerous human illness for a history-long time, notably since the COVID-19 pandemic outbreak. Many pathogens, including bacteria or viruses like COVID-19, can cause pneumonia, leading to inflammation in patients' alveoli. A corresponding symptom is the appearance of lung opacities, which are vague white clouds in the lungs' darkness in chest radiographs. Modern medicine has indicated that pneumonia-associated opacities are distinguishable and can be seen as fine-grained labels, which make it possible to use deep learning to classify chest radiographs as a supplementary aid for disease diagnosis and performing pre-screening. However, deep learning-based medical imaging solutions, including convolutional neural networks, often encounter a performance bottleneck when encountering a new disease due to the dataset's limited size or class imbalance. This study proposes a deep learning-based approach using transfer learning and weighted loss to overcome this problem. The contributions of it are three-fold. First, we propose an image classification model based on pre-trained Densely Connected Convolutional Networks using Weighted Cross Entropy. Second, we test the effect of masking non-lung regions on the classification performance of chest radiographs. Finally, we summarize a generic practical paradigm for medical image classification based on transfer learning. Using our method, we demonstrate that pre-training on the COVID-19 dataset effectively improves the model's performance on the non-COVID Pneumonia dataset. Overall, the proposed model achieves excellent performance with 95.75% testing accuracy on a multiclass classification for the COVID-19 dataset and 98.29% on a binary classification for the Pneumonia dataset. © 2023 IEEE.

Epidemiological Investigation and Analysis of Bovine Coronavirus in Beef Cattle in Jilin Province.

In order to comprehensively understand the epidemiological situation of bovine coronavirus (BCoV) in beef cattle herds in Jilin Province, blood, nasal swabs, fecal swabs and tissue organs of clinically diseased and dead cattle were collected in different seasons from 12 counties and cities in the east, central and western regions of Jilin Province, using serological and molecular diagnostic testing techniques to conduct an epidemiological investigation of BCoV in the The epidemiological situation of BCoV in some areas of Jilin Province. A total of 1 298 clinical serum samples, 462 clinical samples (including fecal samples, liver, lung, spleen, trachea and other tissue samples) were collected, and PCR detection of clinical samples was performed by applying commercial BCoV antibody detection kits to detect serum antibodies and a novel detection technique of nano-PCR, and sequencing and analysis of positive results detected by nucleic acid. The results showed that the serum positive rate of BCoV antibodies was 1.08%, and the positive rate of clinical samples such as feces and liver was 21.10%. The BCoV prevalent strain in the investigated area was more than 99% homologous to the prevalent strain in Sichuan, China, after sequencing analysis. This study provides a comprehensive survey of BCoV prevalence in central Jilin Province, which enriches the epidemiological survey data of bovine coronavirus and lays the foundation for guiding the prevention and control of bovine coronavirus.Copyright © 2023 Acta Veterinaria et Zootechnica Sinica. All rights reserved.

Strategies for general surgery related issues in the treatment of critically ill patients diagnosed with COVID-19.

In order to improve the cure rate of critically ill patients in Wuhan epidemic area and reduce the fatality rate, the state have dispatched medical staffs from the whole country to support Wuhan and treat critically ill patients in dedicated facilities. A medical team from the First Affiliated Hospital of Xi'an Jiaotong University, consisting of 133 medical staffs major in critical care medicine, respiralogy, infection, cardiology, and general surgery, entirely took over the critical care unit of the East Hospital of the Renmin Hospital of Wuhan University, and formed a multidisciplinary collaboration team with local medical staffs to treat patients together. Up to March 13th in 2020, the author's medical team has admitted a total of 109 patients, of which 48 had been discharged up on recovery. Critically ill patients with Corona Virus Disease 2019 mainly have elder age, comorbidities, complicated conditions, and difficult diagnosis and treatment. The author and the author's team combined with clinical practice, share experience and strategies of general surgery related issues in the treatment of critically ill patients, providing reference for collegues in general surgery.Copyright © 2020 by the Chinese Medical Association.

The Credibility of Communication in a Pandemic

Social distancing measures are typically recommended to contain the spread of infectious diseases. To improve the public's voluntary compliance, governments and health authorities seek to publicize timely information about the pandemic. Yet social planners may exaggerate or downplay their private information about the disease's severity to elicit their preferred level of social distancing. This is because the relative weight they assign to the costs of isolation over public health may be unbalanced, and people may not fully consider how their social distancing may influence others' infection risk. Consequently, messages and claims about the pandemic may be distrusted. The author investigates whether and when communication can be fully or partially credible despite apparent incentives for misrepresentation. The author finds that a government would communicate truthfully in equilibrium if and only if the disease severity levels are not too close to each other in the public's prior belief. Nevertheless, an increasing difference between the severity levels need not enhance the credibility of communication. Greater communication credibility may hurt social welfare. Moreover, as the government becomes more concerned about the costs of social distancing, its equilibrium messages may become more or less trustworthy. The article's results can benefit social planners and users of their messages (e.g., analysts, researchers, investors). © American Marketing Association 2023.

Synthesis and enzymatic inhibition effects of thiazolidinedione 3C-like protease inhibitors

The 3C-like protease (also known as Mpro) plays a key role in SARS-CoV-2 replication and has similar substrates across mutant coronaviruses, making it an ideal drug target. We synthesized 19 thiazolidinedione derivatives via the Knoevenagel condensations and Mitsunobu reactions as potential 3C-like protease inhibitors. The activity of these inhibitors is screened in vitro by employing the enzymatic screening model of 3C-like protease using fluorescence resonance energy transfer. Dithiothreitol is included in the enzymatic reaction system to avoid non-specific enzymatic inhibition. Active inhibitors with diverse activity are found in this series of compounds, and two representative inhibitors with potent inhibitory activity are highlighted. © The Author(s) 2023.

Screening and Identification of Host Proteins Interacting with PDCoV S1-CTD

The C-terminal domain (CTD) of porcine deltacoronavirus S1 subunit is the main region which induces the neutralizing antibody. S1-CTD was expressed by HEK-293T eukaryotic expression system and purified, and porcine ileal epithelium cells membrane proteins were extracted to investigate porcine host proteins that interact with it. Thirty-two suspected interacting host proteins were obtained by co-inmunprecipitation (Co-IP) and mass spectrometry. Eukaryotic expression plasmid of KIF1 binding protein (KIFBP) was constructed, and the interaction between KIFBP and S1-CTD was identified by Co-IP and laser confocal microscopy. All results proved that KIFBP interacted with S1-CTD and co-located in cytoplasm. Further research indicated that overexpression of KIFBP could effectively reduce the viral mRNA level and the viral titer in which the mRNA level decreased by about 70%, and the viral titer decreased by 101.6TCID50. In conclusion, a host protein KIFBP interacting with PDCoV S1-CTD was screened and identified in this study which provides a theoretical basis for understanding the pathogenesis of PDCoV.

The reliability and integrity of overall survival data based on follow-up records only and potential solutions to the challenges

Overall survival (OS) is considered the standard clinical endpoint to support effectiveness claims in new drug applications globally, particularly for lethal conditions such as cancer. However, the source and reliability of OS in the setting of clinical trials have seldom been doubted and discussed. This study first raised the common issue that data integrity and reliability are doubtful when we collect OS information or other time-to-event endpoints based solely on simple follow-up records by investigators without supporting material, especially since the 2019 COVID-19 pandemic. Then, two rounds of discussions with 30 Chinese experts were held and 12 potential source scenarios of three methods for obtaining the time of death of participants, including death certificate, death record and follow-up record, were sorted out and analysed. With a comprehensive assessment of the 12 scenarios by legitimacy, data reliability, data acquisition efficiency, difficulty of data acquisition, and coverage of participants, both short-term and long-term recommended sources, overall strategies and detailed measures for improving the integrity and reliability of death date are presented. In the short term, we suggest integrated sources such as public security systems made available to drug inspection centres appropriately as soon as possible to strengthen supervision. Death certificates provided by participants' family members and detailed standard follow-up records are recommended to investigators as the two channels of mutual compensation, and the acquisition of supporting materials is encouraged as long as it is not prohibited legally. Moreover, we expect that the sharing of electronic medical records and the legal disclosure of death records in established health registries can be realized with the joint efforts of the whole industry in the long-term. The above proposed solutions are mainly based on the context of China and can also provide reference for other countries in the world. © 2022 The Authors

RNAi Degrades the SARS-CoV-2 Spike Protein RNA for Developing Drugs to Treat COVID-19

COVID-19 is caused by severe acute respiratory SARS-CoV-2. Regardless of the availability of treatment strategies for COVID-19, effective therapy will remain essential. A promising approach to tackle the SARS-CoV-2 could be small interfering (si) RNAs. Here we designed the small hairpin RNA (named as shRNA688) for targeting the prepared 813 bp Est of the S protein genes (Delta). The conserved and mutated regions of the S protein genes from the genomes of the SARS-CoV-2 variants in the public database were analyzed. A 813 bp fragment encoding the most part of the RBD and partial downstream RBD of the S protein was cloned into the upstream red florescent protein gene (RFP) as a fusing gene in the pCMV-S-Protein RBD-Est-RFP plasmid for expressing a potential target for RNAi. The double stranded of the DNA encoding for shRNA688 was constructed in the downstream human H1 promoter of the plasmid in which CMV promoter drives enhanced green fluorescent protein (EGFP) marker gene expression. These two kinds of the constructed plasmids were co-transfected into HEK293T via Lipofectamine 2000. The degradation of the transcripts of the SARS-CoV-2 S protein fusing gene expressed in the transfected HEK293T treated by RNAi was analyzed by RT-qPCR with a specific probe of the targeted SARS-CoV-2 S protein gene transcripts. Our results showed that shRNA688 targeting the conserved region of the S protein genes could effectively reduce the transcripts of the S protein genes. This study provides a cell model and technical support for the research and development of the broad-spectrum small nucleic acid RNAi drugs against SARS-CoV-2 or the RNAi drugs for the other hazard viruses which cause human diseases. Copyright © Weiwei Zhang, Linjia Huang, Jumei Huang, Xin Jiang, Xiaohong Ren, Xiaojie Shi, Ling Ye, Shuhui Bian, Jianhe Sun, Yufeng Gao, Zehua Hu, Lintin Guo, Suyan Chen, Jiahao Xu, Jie Wu, Jiwen Zhang, Daxiang Cui, and Fangping Dai.

Epidemiology of Severe Pediatric Pneumonia in Asia: A Prospective Multinational Observational Study

INTRODUCTION: Severe pneumonia is a common indication for admission to the pediatric intensive care unit (PICU) and a leading cause of morbidity and mortality. The lack of epidemiology and outcome data from Asia is a barrier to improving outcomes of severe pneumonia in the region. METHOD(S): This is a prospective multicenter cohort study carried out from April 2019 to April 2022. Fifteen PICUs participated in this study under the Pediatric Acute & Critical Care Medicine Asian Network. Epidemiological, microbiological and outcome data were collected up to hospital discharge. Univariate logistic regression analysis were conducted to explore the association between potential risk factors and severe outcomes [acute respiratory distress syndrome (ARDS) and PICU mortality]. Multivariable analysis was performed withforward stepwise logistic regression adjusted for sites and COVID-19 pandemic including variables with p< 0.05 in univariate model. RESULT(S): There were 786 children with severe pneumonia in PICU with mean (standard deviation) age 2.8 (3.9) years. 384/786 (48.9%) had comorbidities;126/786 (16.0%) had a history of prematurity (gestational age < 37 weeks). Admission Pediatric Index of Mortality 3 (PIM3) and Pediatric Logistic Organ Dysfunction 2 (PELOD2) score were 16.2 (22.9) and 4.1(4.6). A sole viral or bacterial pathogen was identified in 179/786 (22.4%) and 165/786 (21.0%). Co-infections occurred in 114/786 (14.5%) patients. ARDS and mortality occurred in 156/786 (20.1%) and 70/786(8.9%) patients. In the multivariable model, risk factors for ARDS included PIM3 [adjusted odds ratio (aOR) [95% confidence interval (CI)] of 1.02 (1.01, 1.03)], PELOD2 [aOR 1.08 (95%CI 1.02, 1.13)] and involvement of 4 quadrants on chest-x-ray, [aOR 2.69 (95%CI 1.39, 5.18)]. Risk factors for mortality included PIM 3 [aOR 1.03 (95%CI 1.01, 1.04)], involvement of 4 quadrants on chest-x-ray [aOR 2.72 (95%CI 1.10, 6.73)], bacterial [aOR 2.61 (95%CI 1.00, 6.82)], fungus or mycobacterium [aOR 12.30 (95%CI 1.45, 104.57)] and co-infections [aOR 2.72 (95%CI 1.10, 10.35)]. CONCLUSION(S): The rate of ARDS and mortality in severe pneumonia admitted to PICU in Asia was high. Risk factors for poor outcomes were admission severity scores, generalized X-ray involvement and identification of bacteria, fungus/mycobacteria or co-infections.

The review of COVID-19 and the current progress in intervention and diagnostics

COVID-19 was first reported in Wuhan city of Hubei Province of China in December 2019, becoming a pandemic declared by the world health organization. This article is a review of the novel coronavirus disease (COVID-19). It typically informs the genome structure of the SARS-CoV-2 and its pathogenic mechanisms, concludes a series of non-pharmaceutical control methods, and focuses on several testing measures. The inventions of the disease treatments remain an important challenge to all medical institutions while a series ofmedications have been brought to the public. © The Authors, published by EDP Sciences.

[Epidemiological characteristics of an epidemic of 2019-nCoV Omicron variant infection in Beijing].

Objective: To analyze the epidemiological characteristics and transmission chain of an epidemic of COVID-19 in Haidian district, Beijing. Methods: Descriptive epidemiological method was used to analyze the epidemiological characteristics of the epidemic, and field investigation and big data technology were used to analyze the transmission chain of the epidemic. Results: From April 27 to May 13, 2022, an epidemic of COVID-19 occurred in Haidian district. The strains isolated from the cases were identified by whole genome sequencing as Omicron variant (BA.2.2 evolutionary branch). A total of 38 infection cases were detected, including 34 confirmed cases and 4 asymptomatic cases. Most cases were mild ones (88.2%), no severe, critical or death cases occurred. The early clinical symptoms were mainly sore throat (50.0%) and cough (29.4%). The epidemic lasted for 17 days, resulting in 7 generations of the cases and involving 3 community transmissions, 2 working place transmissions and 8 family transmissions; the main infection routes were co-residence (47.6%) and co-space exposure (31.6%). The intergenerational interval M(Q1, Q3)was 3 (1, 6) days. The overall secondary attack rate was 1.5% (37/2 482), and the family secondary attack rate was 36.7% (18/49). Conclusions: The cases in this COVID-19 epidemic caused by Omicron variant had mild clinical symptoms, but the case clustering in families and communities was obvious, the transmission was rapid, and the risk for co-space exposure was high. It is necessary to use information technology to identify close contacts in the local population for the rapid and effective blocking of the epidemic spread.

Longitudinal Assessment for Anxiety and Depression among Frontline Medical Staff at a Specialized Hospital to Admit Patients with COVID-19

Longitudinal alterations of mental health problems still lack clarity among frontline medical staff treating patients with coronavirus disease 2019 (COVID-19). Mental health surveys were conducted from February 19 to 23 (n = 222), from March 3 to 10 (n = 364), from March 15 to 22 (n = 446), and from March 25 to April 3 (n = 174), 2020, of medical staff working at medical staff at a specializ ed hospital to admit patients with COVID-19 in China. The rate of reporting anxiety remained unchanged within 6 weeks, but the rate of reporting depression increased at week 3 and remained unchanged afterwards. Age was an independent risk factor for symptoms of anxiety and depression, and working days were independent risk factors for symptoms of depression. These results highlight the importance of dynamic assessment. Copyright © 2022, Universidade de Sao Paulo. Museu de Zoologia. All rights reserved.

The Topic Evolution of Danmaku Text Based on BTM-Taking the Context of COVID-19 as an Example

The danmaku text is a popular interactive mode of instantaneous video comment. Websites with danmaku texts have been widely used recently, and this vast number of texts can be regarded as a short text mining resource. This paper uses Perplexity and Renyi entropy to evaluate the BTM (Biterm Topic Model), by extracting the topic from the danmaku texts to explore the evolution of danmaku text topics in videos relevant to COVID-19. The results show that Renyi entropy is an effective way to decide the optimal number of topics, and the topics captured by BTM indicate that video viewers showed positive attitudes in the face of this public health emergency. © 2022 IEEE.

Study on electron beam radiation sterilization process for disposable medical protective clothing

The outbreak of COVID-19 has led to a sharp increase in the demand for disposable medical protective clothing in the short term. In order to shorten the marketing cycle, a large number of domestic disposable medical protective clothing products have been sterilized by electron beam irradiation, which is more efficient than ethylene oxide sterilization. However, the performance of such clothing must adhere to strict requirements and the process parameters of this sterilization method still lack systematic data support. In order to ensure the reliability of electron beam sterilization of disposable medical protective clothing, research on a corresponding process was carried out. Typical disposable medical protective clothing available on the market made of polypropylene (PP) and coated with polyethylene (PE) was selected as the material studied. An appropriate method was selected to establish the corresponding sterilization dose with reference to the standard methods—“Disposable medical protective clothing irradiation sterilization emergency specification (temporary)”and“ISO 11137-2:2013 Sterilization of health care products—Radiation—Part 2: Establishing the sterilization dose.”The change in material properties after irradiation sterilization with different absorbed doses was studied. Based on the obtained parameters, an algorithm for the average absorbed dose on irradiation by an irradiation electron linac was proposed. Results showed that absorbed doses of 20.3 kGy and 31.5 kGy allowed the products to achieve sterility assurance levels of 10−3 and 10−6, respectively. The material performance of the products after irradiation at 25.0 kGy, 30.0 kGy and 35.0 kGy were able to meet national standard requirements such as elongation at break, breaking strength, impermeability, and filtration efficiency. Thus, a satisfactory electron beam irradiation sterilization process for medical disposable protective clothing has been established. © 2021 The authors.

Comparison of clinical features of Omicron and Delta cases

Objective: To compare the clinical features of Omicron and Delta cases, so as to provide scientific basis for the prevention and treatment of COVID-19. Methods: The case-control study method was used to retrospectively analyze the clinical data of the Omicron cases admitted to the designated hospital for the treatment of COVID-19 in Xi'an from December 2021 to January 2022. and the Delta cases admitted during the same period were used as the control group. The demographic data, epidemiological history, vaccination status, clinical characteristics, laboratory tests, nucleic acid and antibody levels, and outcomes of patients in the two groups were collected and compared. Results: A total of 21 patients were included in the study, 5 were Omicron patients and 16 were Delta cases. The mean age of the patients in the two groups were (38.20±15.07) and (37.69±10.39) years, respectively.The time interval between the last vaccination and the diagnosis was (145.40±77.92) days and (159.00±99.74) days, respectively. For the initial symptoms, the patients with Omicron were mainly characterized by throat discomfort (3, 60%), cough and sputum (2, 40%), and the patients with Delta were mainly characterized by throat discomfort (5, 31.25%), fatigue (5, 31.25%), cough and sputum (4, 25%). On admission, laboratory tests showed that 60% of Omicron patients had low lymphocytes and elevated erythrocyte sedimentation rate, and 50% of patients in the delta group had elevated hemoglobin. The Ct values of ORFlab gene, N gene and E gene with Omicron were lower than those with Delta. And the difference of E gene between the two groups was statistically significant (t=-2.711, P=0.024). IgG antibody levels increased in both groups.The time for nucleic acid to turn negative with Omicron was (28.20±5.89) days, and it was (18.50±7.73) days with Delta, and the difference between the groups was statistically significant (t=2.565, P=0.019). The length of hospitalization with Omicron was (30.60±4.88) days, and that with Delta was (22.13±7.81) days, and the difference was statistically significant (t=2.270, P =0.035). Conclusions: The initial symptoms of Omicron patients are mainly throat discomfort, cough and sputum. The clinical manifestations are generally mild. The nucleic acid test Ct value is lower. The time for nucleic acid to turn negative and the time for hospitalization are longer, and the potential infectiousness is stronger. Those eligible for vaccination should complete the full course of vaccination and booster vaccination as soon as possible. At the same time, the management of "early detection, early reporting, early isolation, and early treatment" should be implemented.