5G-Based Telerobotic Ultrasound System Improves Access to Breast Examination in Rural and Remote Areas: A Prospective and Two-Scenario Study.

OBJECTIVE: Ultrasound (US) plays an important role in the diagnosis and management of breast diseases; however, effective breast US screening is lacking in rural and remote areas. To alleviate this issue, we prospectively evaluated the clinical availability of 5G-based telerobotic US technology for breast examinations in rural and remote areas. METHODS: Between September 2020 and March 2021, 63 patients underwent conventional and telerobotic US examinations in a rural island (Scenario A), while 20 patients underwent telerobotic US examination in a mobile car located in a remote county (Scenario B) in May 2021. The safety, duration, US image quality, consistency, and acceptability of the 5G-based telerobotic US were assessed. RESULTS: In Scenario A, the average duration of the telerobotic US procedure was longer than that of conventional US (10.3 ± 3.3 min vs. 7.6 ± 3.0 min, p = 0.017), but their average imaging scores were similar (4.86 vs. 4.90, p = 0.159). Two cases of gynecomastia, one of lactation mastitis, and one of postoperative breast effusion were diagnosed and 32 nodules were detected using the two US methods. There was good interobserver agreement between the US features and BI-RADS categories of the identical nodules (ICC = 0.795-1.000). In Scenario B, breast nodules were detected in 65% of the patients using telerobotic US. Its average duration was 10.1 ± 2.3 min, and the average imaging score was 4.85. Overall, 90.4% of the patients were willing to choose telerobotic US in the future, and tele-sonologists were satisfied with 85.5% of the examinations. CONCLUSION: The 5G-based telerobotic US system is feasible for providing effective breast examinations in rural and remote areas.

Understanding metabolic alterations after SARS-CoV-2 infection: insights from the patients' oral microenvironmental metabolites.

BACKGROUND: Coronavirus disease 2019 is a type of acute infectious pneumonia and frequently confused with influenza since the initial symptoms. When the virus colonized the patient's mouth, it will cause changes of the oral microenvironment. However, few studies on the alterations of metabolism of the oral microenvironment affected by SARS-CoV-2 infection have been reported. In this study, we explored metabolic alterations of oral microenvironment after SARS-CoV-2 infection. METHODS: Untargeted metabolomics (UPLC-MS) was used to investigate the metabolic changes between oral secretion samples of 25 COVID-19 and 30 control participants. To obtain the specific metabolic changes of COVID-19, we selected 25 influenza patients to exclude the metabolic changes caused by the stress response of the immune system to the virus. Multivariate analysis (PCA and PLS-DA plots) and univariate analysis (students' t-test) were used to compare the differences between COVID-19 patients and the controls. Online hiplot tool was used to perform heatmap analysis. Metabolic pathway analysis was conducted by using the MetaboAnalyst 5.0 web application. RESULTS: PLS-DA plots showed significant separation of COVID-19 patients and the controls. A total of 45 differential metabolites between COVID-19 and control group were identified. Among them, 35 metabolites were defined as SARS-CoV-2 specific differential metabolites. Especially, the levels of cis-5,8,11,14,17-eicosapentaenoic acid and hexanoic acid changed dramatically based on the FC values. Pathway enrichment found the most significant pathways were tyrosine-related metabolism. Further, we found 10 differential metabolites caused by the virus indicating the body's metabolism changes after viral stimulation. Moreover, adenine and adenosine were defined as influenza virus-specific differential metabolites. CONCLUSIONS: This study revealed that 35 metabolites and tyrosine-related metabolism pathways were significantly changed after SARS-CoV-2 infection. The metabolic alterations of oral microenvironment in COVID-19 provided new insights into its molecular mechanisms for research and prognostic treatment.

Do COVID-19 pandemic-related behavior changes affect perioperative respiratory adverse events in children undergoing cardiac interventional catheterization?

BACKGROUND: The novel coronavirus disease (COVID-19) suddenly broke out in China in December 2019. Pandemic-related behavioral changes can cause perioperative respiratory adverse events in children with congenital heart disease (CHD). Here, we compared the incidence of perioperative respiratory adverse events (PRAEs) in CHD children with and without upper respiratory infection (URI) undergoing the cardiac catheterization before and during the COVID-19 pandemic. METHODS: This prospective observational single-center study was based at a tertiary care center in Shanghai, China. A total of 359 children with CHD with and without recent URI were included between January 2019 and March 2021. The overall incidence of PRAEs (laryngospasm, bronchospasm, coughing, airway secretion, airway obstruction, and oxygen desaturation) in non-URI and URI children undergoing elective cardiac catheterization was compared before and during the COVID-19 pandemic. A logistic regression model was fitted to identify the potential risk factors associated with PRAEs. RESULTS: Of the 564 children enrolled, 359 completed the study and were finally analyzed. The incidence of URIs decreased substantially during the COVID-19 pandemic (14% vs. 41%, P < 0.001). Meanwhile, the overall PRAEs also significantly declined regardless of whether the child had a recent URI (22.3% vs. 42.3%, P = 0.001 for non-URI and 29.2% vs. 58.7%, P = 0.012 for URI, respectively). Post-operative agitation in children without URI occurred less frequently during the pandemic than before (2.3% vs. 16.2%, P = 0.001). Behaviors before the COVID-19 pandemic (odds ratio = 2.84, 95% confidence interval [CI] 1.76-4.58) and recent URI (odds ratio = 1.79, 95% CI 1.09-2.92) were associated with PRAEs. CONCLUSIONS: COVID-19 pandemic-related behavioral changes were associated with a reduction in PRAEs in non-URI and URI children undergoing elective therapeutic cardiac catheterization.

Control of infection of medical team assisting Wuhan during COVID-19 epidemic

OBJECTIVE: To explore the control of infection in living places of medical teams assisting Wuhan during COVID-19 epidemic so as to offer help and reference for members of the medical teams. METHODS: The plans and measures for control of infection in working and living places of the medical teams were formulated based on the etiological and epidemiological characteristics of SARS-CoV-2 as well as national guidelines for diagnosis, treatment, control and prevention. RESULTS: The regulations, flow charts and plans have been formulated, involving the medical teams' responsibilities in prevention and control of infection, on-duty and off-duty flow charts and daily living management of team members, active health monitoring, emergency treatment of fever patients, and cleaning and disinfection of living places. CONCLUSION: The prevention and control of infection in the living places is one of the key links to prevent the infection in the team members and the spread of the epidemic, and the medical teams must pay great attention to and rigidly put the infection control measures into practice.

Combination of four clinical indicators predicts the severe/critical symptom of patients infected COVID-19.

BACKGROUND: Despite the death rate of COVID-19 is less than 3%, the fatality rate of severe/critical cases is high, according to World Health Organization (WHO). Thus, screening the severe/critical cases before symptom occurs effectively saves medical resources. METHODS AND MATERIALS: In this study, all 336 cases of patients infected COVID-19 in Shanghai to March 12th, were retrospectively enrolled, and divided in to training and test datasets. In addition, 220 clinical and laboratory observations/records were also collected. Clinical indicators were associated with severe/critical symptoms were identified and a model for severe/critical symptom prediction was developed. RESULTS: Totally, 36 clinical indicators significantly associated with severe/critical symptom were identified. The clinical indicators are mainly thyroxine, immune related cells and products. Support Vector Machine (SVM) and optimized combination of age, GSH, CD3 ratio and total protein has a good performance in discriminating the mild and severe/critical cases. The area under receiving operating curve (AUROC) reached 0.9996 and 0.9757 in the training and testing dataset, respectively. When the using cut-off value as 0.0667, the recall rate was 93.33 % and 100 % in the training and testing datasets, separately. Cox multivariate regression and survival analyses revealed that the model significantly discriminated the severe/critical cases and used the information of the selected clinical indicators. CONCLUSION: The model was robust and effective in predicting the severe/critical COVID cases.