Characteristics of the Severe Acute Respiratory Syndrome Coronavirus 2 Omicron BA.2 Subvariant in Jilin, China from March to May 2022

Background and Objectives In the midst of the pandemic, new coronavirus mutants continue to emerge;the most relevant variant worldwide is omicron. Here, patients who recovered from the disease living in Jilin Province were analyzed to identify factors affecting the severity of omicron infection and to provide insights into its spread and early indication. Methods In this study, 311 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were divided into two groups. Data on the patients' demographic characteristics and laboratory tests, including platelet count (PLT), neutrophil count (NE), C-reactive protein (CRP), serum creatinine (SCR), and neutrophil-to-lymphocyte ratio (NLR), were collected. The biomarkers for moderate and severe coronavirus disease 2019 (COVID-19) and factors affecting the incubation period and time to subsequent negative nucleic acid amplification test (NAAT) were also investigated. Results Age, gender, vaccination, hypertension, stroke, chronic obstructive pulmonary disease (COPD)/chronic bronchitis/asthma, and some laboratory tests were statistically different between the two groups. In the receiver operating characteristic (ROC) analysis, PLT and CRP had higher area under the ROC curve values. In the multivariate analysis, age, hypertension, COPD/chronic bronchitis/asthma, and CRP were correlated with moderate and severe COVID-19. Moreover, age was correlated with longer incubation. In the Kaplan-Meier curve analysis, gender (male), CRP, and NLR were associated with longer time to subsequent negative NAAT. Conclusions Older patients with hypertension and lung diseases were likely to have moderate or severe COVID-19, and younger patients might have a shorter incubation. A male patient with high CRP and NLR levels might take more time to turn back negative in the NAAT.

Real-world effectiveness of primary series and booster doses of inactivated COVID-19 vaccine against Omicron BA.2 variant infection in China: a retrospective cohort study.

BACKGROUND: China has been using inactivated COVID-19 vaccines as primary series and booster doses to protect the population from severe to fatal COVID-19. We evaluated primary and booster vaccine effectiveness (VE) against Omicron BA.2 infection outcomes. METHODS: This was a 13-province retrospective cohort study of quarantined close contacts of BA.2-infected individuals. Outcomes were BA.2 infection, COVID-19 pneumonia or worse, and severe/critical COVID-19. Absolute VE was estimated by comparison with an unvaccinated group. RESULTS: There were 289,427 close-contacts ≥3 years old exposed to Omicron BA.2 cases; 31,831 turned nucleic-acid amplification test (NAAT)-positive during quarantine, 97.2% with mild or asymptomatic infection, 2.6% had COVID-19 pneumonia, and 0.15% had severe/critical COVID-19. None died. Adjusted VE against any infection was 17% for primary series and 22% when boosted. Primary series aVE in adults >18 years was 66% against pneumonia or worse infection and 91% against severe/critical COVID-19. Booster dose aVE was 74% against pneumonia or worse, and 93% against severe/critical COVID-19. CONCLUSIONS: Inactivated COVID-19 vaccines provided modest protection from infection, very good protection against pneumonia, and excellent protection against severe/critical COVID-19. Booster doses are necessary to provide strongest protection.

Characteristics of the Severe Acute Respiratory Syndrome Coronavirus 2 Omicron BA.2 Subvariant in Jilin, China from March to May 2022.

Background and Objectives: In the midst of the pandemic, new coronavirus mutants continue to emerge; the most relevant variant worldwide is omicron. Here, patients who recovered from the disease living in Jilin Province were analyzed to identify factors affecting the severity of omicron infection and to provide insights into its spread and early indication. Methods: In this study, 311 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were divided into two groups. Data on the patients' demographic characteristics and laboratory tests, including platelet count (PLT), neutrophil count (NE), C-reactive protein (CRP), serum creatinine (SCR), and neutrophil-to-lymphocyte ratio (NLR), were collected. The biomarkers for moderate and severe coronavirus disease 2019 (COVID-19) and factors affecting the incubation period and time to subsequent negative nucleic acid amplification test (NAAT) were also investigated. Results: Age, gender, vaccination, hypertension, stroke, chronic obstructive pulmonary disease (COPD)/chronic bronchitis/asthma, and some laboratory tests were statistically different between the two groups. In the receiver operating characteristic (ROC) analysis, PLT and CRP had higher area under the ROC curve values. In the multivariate analysis, age, hypertension, COPD/chronic bronchitis/asthma, and CRP were correlated with moderate and severe COVID-19. Moreover, age was correlated with longer incubation. In the Kaplan-Meier curve analysis, gender (male), CRP, and NLR were associated with longer time to subsequent negative NAAT. Conclusions: Older patients with hypertension and lung diseases were likely to have moderate or severe COVID-19, and younger patients might have a shorter incubation. A male patient with high CRP and NLR levels might take more time to turn back negative in the NAAT.

Severity Assessment and Progression Prediction of COVID-19 Patients Based on the LesionEncoder Framework and Chest CT

Automatic severity assessment and progression prediction can facilitate admission, triage, and referral of COVID-19 patients. This study aims to explore the potential use of lung lesion features in the management of COVID-19, based on the assumption that lesion features may carry important diagnostic and prognostic information for quantifying infection severity and forecasting disease progression. A novel LesionEncoder framework is proposed to detect lesions in chest CT scans and to encode lesion features for automatic severity assessment and progression prediction. The LesionEncoder framework consists of a U-Net module for detecting lesions and extracting features from individual CT slices, and a recurrent neural network (RNN) module for learning the relationship between feature vectors and collectively classifying the sequence of feature vectors. Chest CT scans of two cohorts of COVID-19 patients from two hospitals in China were used for training and testing the proposed framework. When applied to assessing severity, this framework outperformed baseline methods achieving a sensitivity of 0.818, specificity of 0.952, accuracy of 0.940, and AUC of 0.903. It also outperformed the other tested methods in disease progression prediction with a sensitivity of 0.667, specificity of 0.838, accuracy of 0.829, and AUC of 0.736. The LesionEncoder framework demonstrates a strong potential for clinical application in current COVID-19 management, particularly in automatic severity assessment of COVID-19 patients. This framework also has a potential for other lesion-focused medical image analyses.

Single-cell analysis of angiotensin-converting enzyme II expression in human kidneys and bladders reveals a potential route of 2019 novel coronavirus infection.

BACKGROUND: Since 2019, a novel coronavirus named 2019 novel coronavirus (2019-nCoV) has emerged worldwide. Apart from fever and respiratory complications, acute kidney injury has been observed in a few patients with coronavirus disease 2019. Furthermore, according to recent findings, the virus has been detected in urine. Angiotensin-converting enzyme II (ACE2) has been proposed to serve as the receptor for the entry of 2019-nCoV, which is the same as that for the severe acute respiratory syndrome. This study aimed to investigate the possible cause of kidney damage and the potential route of 2019-nCoV infection in the urinary system. METHODS: We used both published kidney and bladder cell atlas data and new independent kidney single-cell RNA sequencing data generated in-house to evaluate ACE2 gene expression in all cell types in healthy kidneys and bladders. The Pearson correlation coefficients between ACE2 and all other genes were first generated. Then, genes with r values larger than 0.1 and P values smaller than 0.01 were deemed significant co-expression genes with ACE2. RESULTS: Our results showed the enriched expression of ACE2 in all subtypes of proximal tubule (PT) cells of the kidney. ACE2 expression was found in 5.12%, 5.80%, and 14.38% of the proximal convoluted tubule cells, PT cells, and proximal straight tubule cells, respectively, in three published kidney cell atlas datasets. In addition, ACE2 expression was also confirmed in 12.05%, 6.80%, and 10.20% of cells of the proximal convoluted tubule, PT, and proximal straight tubule, respectively, in our own two healthy kidney samples. For the analysis of public data from three bladder samples, ACE2 expression was low but detectable in bladder epithelial cells. Only 0.25% and 1.28% of intermediate cells and umbrella cells, respectively, had ACE2 expression. CONCLUSION: This study has provided bioinformatics evidence of the potential route of 2019-nCoV infection in the urinary system.

Development and Validation of a Machine Learning Approach for Automated Severity Assessment of COVID-19 Based on Clinical and Imaging Data: Retrospective Study.

BACKGROUND: COVID-19 has overwhelmed health systems worldwide. It is important to identify severe cases as early as possible, such that resources can be mobilized and treatment can be escalated. OBJECTIVE: This study aims to develop a machine learning approach for automated severity assessment of COVID-19 based on clinical and imaging data. METHODS: Clinical data-including demographics, signs, symptoms, comorbidities, and blood test results-and chest computed tomography scans of 346 patients from 2 hospitals in the Hubei Province, China, were used to develop machine learning models for automated severity assessment in diagnosed COVID-19 cases. We compared the predictive power of the clinical and imaging data from multiple machine learning models and further explored the use of four oversampling methods to address the imbalanced classification issue. Features with the highest predictive power were identified using the Shapley Additive Explanations framework. RESULTS: Imaging features had the strongest impact on the model output, while a combination of clinical and imaging features yielded the best performance overall. The identified predictive features were consistent with those reported previously. Although oversampling yielded mixed results, it achieved the best model performance in our study. Logistic regression models differentiating between mild and severe cases achieved the best performance for clinical features (area under the curve [AUC] 0.848; sensitivity 0.455; specificity 0.906), imaging features (AUC 0.926; sensitivity 0.818; specificity 0.901), and a combination of clinical and imaging features (AUC 0.950; sensitivity 0.764; specificity 0.919). The synthetic minority oversampling method further improved the performance of the model using combined features (AUC 0.960; sensitivity 0.845; specificity 0.929). CONCLUSIONS: Clinical and imaging features can be used for automated severity assessment of COVID-19 and can potentially help triage patients with COVID-19 and prioritize care delivery to those at a higher risk of severe disease.

Association Between Clinical Characteristics and Short-Term Outcomes in Adult Male COVID-19 Patients With Mild Clinical Symptoms: A Single-Center Observational Study.

Majority of patients with 2019 novel coronavirus infection (COVID-19) exhibit mild symptoms. Identification of COVID-19 patients with mild symptoms who might develop into severe or critical illness is essential to save lives. We conducted an observational study in a dedicated make-shift hospital for adult male COVID-19 patients with mild symptoms between February and March 2020. Baseline characteristics, medical history, and clinical presentation were recorded. Laboratory tests and chest computed tomography were performed. Patients were observed until they were either transferred to a hospital for advanced care owing to disease exacerbation or were discharged after improvement. Patients were grouped based on their chest imaging findings or short-term outcomes. A total of 125 COVID-19 patients with mild symptoms were enrolled. Of these, 7 patients were transferred for advanced care while 118 patients were discharged after improvement and showed no disease recurrence during an additional 28-day follow-up period. Eighty-five patients (68.0%) had abnormal chest imaging findings. Patients with abnormal chest imaging findings were more likely to have disease deterioration and require advanced care as compared to those with normal chest imaging findings. Patients with deteriorated outcomes were more likely to have low peripheral blood oxygen saturation and moderately-elevated body temperature. There were no significant differences between patients with deteriorated or improved outcomes with respect to age, comorbidities, or other clinical symptoms (including nasal congestion, sore throat, cough, hemoptysis, sputum production, shortness of breath, fatigue, headache, nausea or vomiting, diarrhea). Abnormal chest imaging findings, low peripheral blood oxygen saturation, and elevated temperature were associated with disease deterioration in adult male COVID-19 patients with mild clinical symptoms. Clinical Trial Registration: https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S0009RA3&selectaction=Edit&uid=U0003F4L&ts=2&cx=-ajpsbw, identifier NCT04346602.

Epidemiological and clinical characteristics of 2019 novel coronavirus disease (COVID-19) in Jilin, China: A descriptive study.

Coronavirus diseases 2019 (COVID-19) has become a global pandemic. To add to the scarce information on this disease, here, we investigated the epidemiological and clinical characteristics of 93 hospitalized patients with COVID-19 in Jilin, China from January 22 to March 15, 2020.We retrospectively investigated the demographic information, recent exposure history, clinical symptoms or signs, comorbidity, chest computed tomographic (CT) scan or X-ray results, laboratory test results, diagnostic classification, treatment, length of hospitalization, complications, and outcomes.Of the 93 patients, 54 were male and 39 female. More than half of these patients had a history of exposure to infected patients. The mean incubation period was 10.4 days in 87 patients, where the data was available. The 5 most common symptoms of illness onset were fever, cough, expectoration, fatigue, and dyspnea. One patient was asymptomatic. The imaging results were abnormal in majority of the patients. Almost one-third of the patients had lymphopenia. All patients received antiviral therapy, 84 patients were treated with antibiotics and 54 received different doses of the hormone for methylprednisolone. In addition, 72 patients used traditional Chinese medicine. Oxygen therapy, high nasal flow oxygen, non-invasive ventilator, invasive ventilator and extracorporeal membrane oxygenation (ECMO) were used symptomatically in different patients. Except 1 patient who died during treatment, all others were discharged.The average incubation time is prolonged in the present analysis, as compared to that in other reports. A few patients symptoms improved but CT exacerbated. Therefore, we suggest that close follow-up observation is still required after discharge.

Management of gynecology patients during the coronavirus disease 2019 pandemic: Chinese expert consensus

Since December 2019, the outbreak of novel coronavirus disease 2019 became a major epidemic threat in China and later spread worldwide. During the coronavirus disease 2019 outbreak in mainland China, the Chinese Obstetricians and Gynecologists Association distributed guidelines regarding the care of gynecologic patients. These guidelines were developed by the Department of Obstetrics and Gynecology at the Peking Union Medical College Hospital and represent an effort to integrate infection control strategy and promote professionalism in medical practice. The guidelines represent collaboration with experts from 31 provinces and autonomous regions of mainland China over 2 weeks' time. With the implementation of these guidelines, no nosocomial infections of coronavirus disease 2019 have been identified at the Peking Union Medical College Hospital. We think these guidelines might be helpful to departments of obstetrics and gynecology internationally during these unprecedented times. In our guidelines, we describe basic infection precaution principles, an epidemiologic screening tool, prioritization of surgical procedures, and operating room requirements. Using these principles, we then review the management of gynecologic patients during the coronavirus disease 2019 epidemic in the outpatient and operative and nonoperative inpatient settings and in clinical trials.