Assessment of the Risk and Symptoms of SARS-CoV-2 Infection Among Healthcare Workers During the Omicron Transmission Period: A Multicentric Study from Four Hospitals of Mainland China.

Purpose: The SARS-CoV-2 omicron variant emerged and spread rapidly among the population in the early stage of China's normalized prevention and control in December 2022. Healthcare workers (HCWs) are particularly exposed to SARS-CoV-2, it is important to evaluate the impact of the omicron pandemic on HCWs in China. Methods: A self-administered online survey was conducted on infected HCWs from four hospitals of Taizhou. A total of 748 HCWs received the survey via DingTalk, and 328 responded to the questionnaire. The risk factors were investigated using univariate and multivariate logistic regression analysis. Results: By December 20, 2022, 748 HCWs tested positive by PCR, and the infection rate was 11.4% (748/6581). Among 328 respondents, the most common symptoms were cough (88.4%), fever (83.5%), runny nose (77.1%), sore throat (73.2%), headache (70.1%), muscle aches (67.1%), and fatigue (53.4%). 69.8% (229/328) of the participants had five or more major onset symptoms, while no severe case was observed. The multivariate analysis indicated that the poor sleep quality (OR = 2.29, 95% CI: 1.31-4.02, P = 0.004) was an independent risk factor for more major onset symptoms, while wore gloves ≥95% times in working (OR = 0.49, 95% CI: 0.28-0.85, P = 0.011) was significantly related to fewer symptoms. In addition, 239 (72.9%) recipients reported high fever (temperature ≥38.5°C), less common cold (≤3 vs >3 times/year, OR = 2.20, 95% CI: 1.05-4.65, P = 0.038) was significantly associated with high fever. Conclusion: Our findings imply rapid transmissibility of omicron and multiple-onset symptoms among HCWs. Improved autoimmunity and self-protection measures for HCWs may be helpful in controlling infection and clinical symptoms. Our results provide empirical reference values for improved countermeasures and protective measures for major public health emergencies.

Physical condition, psychological status, and posttraumatic stress disorder among recovered COVID-19 subjects: A mediation analysis.

The physical condition of individuals who contracted COVID-19 had a profound influence on mitigating the physical and psychological impact of the disease and the symptoms of posttraumatic stress disorder (PTSD). Little attention has been focused on the influence of physical condition on PTSD among recovered COVID-19 subjects. This study explored the relationship between physical and psychological status and PTSD and the potential mechanisms. Questionnaires were completed by 73 (50.7%, 73/144) COVID-19 recovered subjects who were diagnosed in Taizhou, Zhejiang, China. We conducted a face-to-face survey from January 17 to March 10, 2020. The mediation analysis approach was applied in this research. Our data show that recovered COVID-19 subjects who were in better physical condition exhibited fewer psychological problems [B (95%CI), (-1.65 -3.04, -0.26)] and lower PTSD [B (95%CI), -6.13 (-9.43, -2.83)]. In addition, the worse the psychological status of recovered COVID-19 subjects was, the stronger the PTSD (B [95%CI], 0.58 [0.02, 1.14]). Moreover, psychological status could significantly mediate the impact of physical condition on PTSD (ß1θ2 = -0.87). Together, COVID-19 recovered subjects who have better physical condition could decrease their PTSD, and the worse the physical condition of COVID-19 recovered subjects would increase their psychological problems. Our finding about psychological status could significantly mediate the impact of the physical condition on PTSD might be useful for medical institutions and the government seeking to help with the follow-up rehabilitation training of recovered COVID-19 subjects.

Physical condition, psychological status, and posttraumatic stress disorder among recovered COVID-19 subjects: A mediation analysis

The physical condition of individuals who contracted COVID-19 had a profound influence on mitigating the physical and psychological impact of the disease and the symptoms of posttraumatic stress disorder (PTSD). Little attention has been focused on the influence of physical condition on PTSD among recovered COVID-19 subjects. This study explored the relationship between physical and psychological status and PTSD and the potential mechanisms. Questionnaires were completed by 73 (50.7%, 73/144) COVID-19 recovered subjects who were diagnosed in Taizhou, Zhejiang, China. We conducted a face-to-face survey from January 17 to March 10, 2020. The mediation analysis approach was applied in this research. Our data show that recovered COVID-19 subjects who were in better physical condition exhibited fewer psychological problems [B (95%CI), (−1.65 −3.04, −0.26)] and lower PTSD [B (95%CI), −6.13 (−9.43, −2.83)]. In addition, the worse the psychological status of recovered COVID-19 subjects was, the stronger the PTSD (B [95%CI], 0.58 [0.02, 1.14]). Moreover, psychological status could significantly mediate the impact of physical condition on PTSD (β1θ2 = −0.87). Together, COVID-19 recovered subjects who have better physical condition could decrease their PTSD, and the worse the physical condition of COVID-19 recovered subjects would increase their psychological problems. Our finding about psychological status could significantly mediate the impact of the physical condition on PTSD might be useful for medical institutions and the government seeking to help with the follow-up rehabilitation training of recovered COVID-19 subjects.

The evaluation of the immune status of COVID-19 recovered subjects with persistent abnormal lung CT after one year: A longitudinal cohort study.

OBJECTIVES: COVID-19 is an immune-related disease caused by novel Coronavirus SARS-COV-2. Lung lesions persist in some recovered patients, making long-term follow-up monitoring of their health necessary. The mechanism of these abnormalities is still unclear. In this study, the immune status was observed to explore the immune mechanism of persistent lung CT abnormalities in one-year COVID-19 recovered subjects. METHODS: One-year follow-up of 73 recovered patients from COVID-19 confirmed in Taizhou City, Zhejiang Province, was conducted to collect laboratory indicators such as blood immune cells, cytokines, complement series, immunoglobulin, and lung imaging; According to the results of lung CT, 60 patients were divided into normal CT group (n = 40) and abnormal CT group (n = 20). We compared the dynamic changes of immune indexes at three timepoints namely onset (T1), discharge (T2), and 1-year follow-up (T3), and studied the relationship between immune indexes and pulmonary sequelae. RESULTS: Compared with the healthy control, there was no significant difference in immune-related indexes, and immune levels had recovered. Patients with elder age, high BMI, severe patients, and those with underlying diseases (hypertension or diabetes) had a higher CT abnormal rate after recovery. Longitudinal observation showed that immunoglobulin increased first and then decreased, immune cell TBNK decreased in the onset period and increased in the recovery period, cytokine level increased significantly in the onset period and decreased to the normal level in the recovery period, and complement series C1q, C3 and C4 increased at the onset and decreased during the one-year follow-up. Complement C3 remained at a high level in the CT abnormal group (CT normal group vs CT abnormal group; P = 0.036). Correlation analysis showed that C3 negatively correlated restrictive ventilation index (TLC-He (ratio) (r = -0.302, P = 0.017). The above results suggest that complement C3 is a negative factor correlating abnormal pulmonary function 1 year after the recovery. CONCLUSION: After one year recovering from COVID-19, the subjects were with stable immune indicators. High levels of complement C3 were associated with persistent lung abnormalities in COVID-19 recovered subjects.

Gut microbiota, inflammation, and molecular signatures of host response to infection.

Gut microbial dysbiosis has been linked to many noncommunicable diseases. However, little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection. Here, we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers, which have recently been identified as molecular signatures predicting the progression of the COVID-19. We demonstrate that in our cohort of 990 healthy individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals. Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation. Overall, our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals. These results may provide novel insights into the cross-talk between gut microbiota and host immune system.

Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements.

Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort, resulting in a data matrix containing 3,065 readings for 124 types of measurements over 52 days. A machine learning model was established to predict the disease progression based on the cohort consisting of training, validation, and internal test sets. A panel of eleven routine clinical factors constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 98% in the discovery set. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.70, 0.99, 0.93, and 0.93, respectively. Our model captured predictive dynamics of lactate dehydrogenase (LDH) and creatine kinase (CK) while their levels were in the normal range. This model is accessible at https://www.guomics.com/covidAI/ for research purpose.

Pulmonary function of patients with 2019 novel coronavirus induced-pneumonia: a retrospective cohort study.

BACKGROUND: The aim of this study was to investigate the pulmonary function of patients with 2019 novel coronavirus (COVID-19)-induced pneumonia. METHODS: A retrospective analysis of 137 patients with COVID-19-induced pneumonia who were discharged from the Enze Hospital, Taizhou Enze Medical Center (Group) from January 31 2020 to March 11 2020 was conducted. Follow-up occurred 2 weeks after hospital discharge, during which patients underwent a pulmonary function test. RESULTS: Of the 137 patients who underwent a pulmonary function test 2 weeks after discharge, 51.8% were male, and the mean age was 47 years. Only 19.7% of the patients were identified as having severe COVID-19-induced pneumonia. The pulmonary function tests showed that for a small number of patients the forced expiratory volume in one second/forced vital capacity ratio (FEV1/FVC)/% values were <70%, and the mean forced inspiratory volume (IVC) and FVC values were 2.4±0.7 and 3.2±0.8 L, respectively. In severe cases, 88.9% of patients had an IVC <80% of the predicted value, and 55.6% of patients had an FVC <80% of the predicted value. The proportion of patients with maximum expiratory flow rate at 25%, 50% and 75% of the vital capacity (MEF25, MEF50, and MEF75) values <70% were 55.6%, 40.7%, and 25.9%, respectively. In the non-severe group, 79.1% of patients had an IVC <80% of the predicted value, and 16.4% of patients had an FVC <80% of the predicted value. The mean MEF25, MEF50, and MEF75 <70% values were 57.3%, 30%, and 13.6%, respectively. CONCLUSIONS: Our results demonstrated that the pulmonary function of patients with COVID-19-induced pneumonia predominantly manifested as restrictive ventilation disorder and small airway obstruction, which was increased in critically ill patients.

Relationship between chest CT manifestations and immune response in COVID-19 patients.

OBJECTIVES: To study the correlations of lymphocytes and cytokines between changes of lung lesion volumes in patients with COVID-19, and to predict these correlations. METHODS: 93 patients with COVID-19 were divided into mild and severe groups. The data of lymphocyte subgroups and cytokines were collected, the imaging characteristics were measured, and correlation analysis was performed to analyze the differences. RESULTS: 60 mild and 33 severe patients were included. Lymphocyte subsets decreased in both groups. The reduction percentages of the absolute lymphocytes value in mild and severe groups were 32% and 64%, respectively. The lung CT lesion volume of all patients was 241.45 ± 282.92 cm3, among which the mild group was 151.29 ± 226.04 cm3, and the severe group was 405.38 ± 304.90 cm3, respectively. In critically ill patients, the decrease of the absolute value of CD4+ T cells and the increase of IL-6 levels are significantly correlated with the volume of lung lesions. CONCLUSIONS: The absolute values of CD3+, CD4+, and CD8+ T cells are lower in patients with COVID-19, while the levels of IL-6 and IL-10 are increased. The severity of lung lesions predicts poor clinical outcomes and may be a predictor of the transition from mild to severe.