Characteristics and Occurrence Scenarios of Staff Exposed to SARS-CoV-2 Omicron in Shanghai Lingang Fangcang Shelter Hospital, CHINA.

Objective: To analyze the characteristics and occurrence scenarios of occupational exposure of staff in the Shanghai Lingang Fangcang Shelter Hospital. Methods: We collected the data of 80 staff with occupational exposure (including doctors, nurses, cleaning, security guards, and maintenance staff) in the Shanghai Lingang Fangcang Shelter Hospital from April 5 to May 20, 2022. The basic information of occupational exposure, factors influencing different occupational exposure types, ways to discover occupational exposure, discovery places of occupational exposure, and specific occurrence scenarios were compiled and analyzed among these data. Results: Occupational exposure mainly occurred in nurses (37, 46.25%), and cleaning (21, 26.25%). After the occurrence of occupational exposure, 20 staff (25%) did not know the occurrence time. Moreover, occupational exposure types were listed from high to low proportion as follows: broken protective clothing (56, 70%), mask loosening or displacement (13, 16.25%), skin exposure (6, 7.5%), and sharp object injuries (5, 6.25%). Occupational exposure was discovered mainly through self-discovery (56, 70%), while other discovery ways were majorly colleague discovery (12, 15%) and infection control supervisor discovery (12, 15%). Furthermore, occupational exposure was discovered principally in the public area (53.75%) and the office area (25%) of the cabin, but the proportion of mask loosening or displacement (38.46%) and skin exposure (50%) was also high in the first unloading area. Broken protective clothing occurred in the following scenarios: scratching while working in the cabin (37, 66.07%) and not knowing its occurrence time (25%). The occurrence scenarios of mask loosening or displacement were mainly not knowing its occurrence time (6, 46.15%), self-discovery (3, 23.08%), and at the time of removal (3, 23.08%). Conclusion: Targeted training and prevention of occupational exposure should be performed to decrease infection risk and ensure staff safety in Fangcang shelter hospitals.

Effectiveness and Safety of Lianhua Qingwen Capsules for COVID-19: A Propensity-Score Matched Cohort Study.

As a traditional Chinese medicine, Lianhua Qingwen capsules have been widely used to treat Coronavirus Disease 2019 (COVID-19). This study was aimed to demonstrate the association between treatment with Lianhua Qingwen capsules and the clinical outcomes of hospitalized patients with COVID-19. This retrospective study was conducted at four hospitals in Central China. Data of hospitalized COVID-19 patients were collected between December 19, 2019 and April 26, 2020. Based on whether Lianhua Qingwen capsules were used, patients were classified into Lianhua Qingwen and non-Lianhua Qingwen (control) groups. To control for confounding factors, we used conditional logistic regression in a propensity-score matched (PSM) cohort (1 : 1 balanced), as well as logistic regression without matching as sensitivity analysis. A total of 4918 patients were included, 2760 of whom received Lianhua Qingwen capsules and 2158 of whom did not. In the PSM model, after adjusting for confounders, the in-hospital mortality was similar between the Lianhua Qingwen group and the control group (6.8% vs. 3.3%, adjusted OR, 0.66 [95% CI, 0.38-1.15], p = 0.138). The negative conversion rate of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection was higher in the Lianhua Qingwen group (88.3% vs. 96.1%, adjusted OR, 4.02 [95% CI, 2.58-6.25], p < 0.001). The incidence of acute liver injury was comparable between the two groups (14.0% vs. 11.5%, adjusted OR: 0.85 [95% CI, 0.71-1.02], p = 0.083), and the incidence of acute kidney injury was lower in the Lianhua Qingwen group (5.3% vs. 3.0%, adjusted OR: 0.71 [95% CI, 0.50-1.00], p = 0.048). Treatment with Lianhua Qingwen capsules was not significantly associated with in-hospital mortality in COVID-19 patients. In the Lianhua Qingwen group, the negative conversion rate of SARS-CoV-2 infection was higher and the incidence of acute kidney injury was lower than in the control group.

Ambroxol for the treatment of COVID-19 among hospitalized patients: A multicenter retrospective cohort study.

Ambroxol is a commonly used mucolytic agent principally used to treat respiratory diseases, which may have a role as adjunctive therapy for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, but there is lack of evidence about its effectiveness on coronavirus disease-2019 (COVID-19) patients. To study the association between ambroxol use and clinical outcomes among hospitalized patients of COVID-19 infection. We conducted a multicenter retrospective cohort study involving 3,111 patients with confirmed SARS-CoV-2 infection from three hospitals in Wuhan from 19 December 2019 to 15 April 2020, and the primary outcome was in-hospital mortality. COVID-19 patients were classified into ambroxol and non-ambroxol groups based on the administration of ambroxol during hospitalization. Two analyses including propensity score matching (PSM) to obtain a 1:1 balanced cohort and logistic regression were used to control for confounding factors. The average age of 3,111 patients was 57.55 ± 14.93 years old, 127 of them died during hospitalization, and 924 of them used ambroxol. Treatment with ambroxol did not have a significant effect on in-hospital mortality of COVID-19 patients when compared with non-ambroxol in PSM model after adjusting for confounders (8.0% vs. 3.5%, adjusted OR, 1.03 [95% CI, 0.54-1.97], p = 0.936). Adverse events such as nausea/vomiting, headache, and rash were comparable between the two groups. Our results suggest that the use of ambroxol is not significantly associated with in-hospital mortality in COVID-19 patients, which provides evidence for evaluating the effects of ambroxol on COVID-19 patient outcomes and may be helpful for physicians considering medication alternatives for COVID-19 patients.

Real-time detection of viruses in aerosols with weak light imaging based on Tesla discharge

The analysis and detection of nucleic acid and specific antigens and antibodies are the most basic technologies for virus monitoring. However, the potential window for applying these technologies exists within a late specific period in the early monitoring and control of unknown viruses, especially human and animal pathogenic viruses transmitted via aerosols, e.g., SARS-CoV-2 and its variants. This is because early, real-time, and convenient monitoring of unknown viruses in the air or exhaled gas cannot be directly achieved through existing technologies. Herein, we report a weak light spectral imaging technology based on Tesla discharge (termed T-DAI) that can quickly monitor for viruses in real time in simulated aerosols with 71% sensitivity and 76% specificity for aerosol virus concentrations exceeding approximately 2800 vp/μl. This technology realizes the rapid detection of low concentrations of viruses in aerosols and could provide an important means for predicting, screening, and monitoring unknown or pandemic pathogenic viruses in the air or exhaled breath of humans and animals. [ FROM AUTHOR] Copyright of Applied Physics Letters is the property of American Institute of Physics 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.)

[Analysis of the Characteristics of the Outcomes of Job-Transfer Subspecialty Training Program in Pediatrics in Sichuan].

Objective: To discuss the characteristics of physician trainee outcomes after completion of the job-transfer subspecialty training in pediatrics, a program designed to increase the number of pediatricians, in Sichuan Province and to provide countermeasures for alleviating the shortage of pediatricians. Methods: We collected with questionnaire surveys information on changes in the workload and salaries experienced by physicians who completed the job-transfer subspecialty training program in pediatrics between February 2017 and May 2020 in Sichuan Province. Then, we compared the characteristics of physicians who successful became pediatricians and those who did no. Results: A total of 208 physicians completed the job-transfer subspecialty training program in pediatrics. Among them, 178, accounting for 85.6%, completed the questionnaire survey, and 120, accounting for 67.4%, had a background in other subspecialties than pediatrics. The majority (>90%) of physicians who participated in the training program came from secondary or lower levels of hospitals from the cities and prefectures all over Sichuan Province. In this study, we found that the rate of successful job transfer from being a physician to being a pediatrician in Sichuan Province in the past four years was 85.0% (102/120), with the year-by-year results being 88.2% (15/17) in 2017, 72.7% (16/22) in 2018, 86.7% (39/45) in 2019, and 94.% (32/34) in 2020. There was no significant difference between physicians who had successful job transfer and became pediatricians and those who failed to do so in terms of gender, age, hospital level, specialization prior to the job transfer, whether or not the hospital had a pediatrics department, amount of support for the pediatrics department, whether or not the physician was working at a new hospital after the job transfer, salaries, and changes of responsibilities during COVID-19 (all P>0.05). There was significant difference in the change of workload after completion of the training program between physicians who had successful job transfer and became pediatricians and those who failed to do so ( χ 2=9.037, P=0.003), and 78.4% of the trainees stated that their workload had increased after the job transfer. There was a moderate correlation between successful job transfer and changes in workload after the transfer (|Phi[ψ] |=0.729). Conclusions: The policy of government-supported job-transfer subspecialty training in pediatrics has played an active and important role in the swift resolution of the shortage of pediatricians. However, finding the root cause of and addressing the problem of the overwhelming workload of pediatricians remain challenging issues to be resolved.

Critical Role of Simultaneous Reduction of Atmospheric Odd Oxygen for Winter Haze Mitigation.

The lockdown due to COVID-19 created a rare opportunity to examine the nonlinear responses of secondary aerosols, which are formed through atmospheric oxidation of gaseous precursors, to intensive precursor emission reductions. Based on unique observational data sets from six supersites in eastern China during 2019-2021, we found that the lockdown caused considerable decreases (32-61%) in different secondary aerosol components in the study region because of similar-degree precursor reductions. However, due to insufficient combustion-related volatile organic compound (VOC) reduction, odd oxygen (Ox = O3 + NO2) concentration, an indicator of the extent of photochemical processing, showed little change and did not promote more decreases in secondary aerosols. We also found that the Chinese provinces and international cities that experienced reduced Ox during the lockdown usually gained a greater simultaneous PM2.5 decrease than other provinces and cities with an increased Ox. Therefore, we argue that strict VOC control in winter, which has been largely ignored so far, is critical in future policies to mitigate winter haze more efficiently by reducing Ox simultaneously.

Expressions and Significances of CTSL, The Target of COVID‐19 on GBM (preprint)

CTSL is one of the SARS-entry-associated CoV-2's proteases and plays a key role in the virus's entry into the cell and subsequent infection. We investigated the association between the expression level of CTSL and overall survival in TCGA and CGGA databases, in order to better understand the possible route and risks of new coronavirus infection for patients with GBM. Meanwhile, the relationship between CTSL and immune infiltration levels was analyzed by means of the TIMER database. The impact of CTSL inhibitors on GBM biological activity was tested. The findings revealed that GBM tissues had higher CTSL expression levels than that of normal brain tissues, which was associated with a significantly lower survival rate in GBM patients. Meanwhile, CTSL was very negatively correlated with purity, B cell and CD8+ T cell in GBM. CTSL inhibitor significantly reduced U251 cell growth and invasion in vitro and induced mitochondrial apoptosis. According to the findings of this study, CTSL acts as an independent prognostic factor and can be considered as promising therapeutic target for GBM.

Development and external validation of a COVID-19 mortality risk prediction algorithm: a multicentre retrospective cohort study.

OBJECTIVE: This study aimed to develop and externally validate a COVID-19 mortality risk prediction algorithm. DESIGN: Retrospective cohort study. SETTING: Five designated tertiary hospitals for COVID-19 in Hubei province, China. PARTICIPANTS: We routinely collected medical data of 1364 confirmed adult patients with COVID-19 between 8 January and 19 March 2020. Among them, 1088 patients from two designated hospitals in Wuhan were used to develop the prognostic model, and 276 patients from three hospitals outside Wuhan were used for external validation. All patients were followed up for a maximal of 60 days after the diagnosis of COVID-19. METHODS: The model discrimination was assessed by the area under the receiver operating characteristic curve (AUC) and Somers' D test, and calibration was examined by the calibration plot. Decision curve analysis was conducted. MAIN OUTCOME MEASURES: The primary outcome was all-cause mortality within 60 days after the diagnosis of COVID-19. RESULTS: The full model included seven predictors of age, respiratory failure, white cell count, lymphocytes, platelets, D-dimer and lactate dehydrogenase. The simple model contained five indicators of age, respiratory failure, coronary heart disease, renal failure and heart failure. After cross-validation, the AUC statistics based on derivation cohort were 0.96 (95% CI, 0.96 to 0.97) for the full model and 0.92 (95% CI, 0.89 to 0.95) for the simple model. The AUC statistics based on the external validation cohort were 0.97 (95% CI, 0.96 to 0.98) for the full model and 0.88 (95% CI, 0.80 to 0.96) for the simple model. Good calibration accuracy of these two models was found in the derivation and validation cohort. CONCLUSION: The prediction models showed good model performance in identifying patients with COVID-19 with a high risk of death in 60 days. It may be useful for acute risk classification. WEB CALCULATOR: We provided a freely accessible web calculator (https://www.whuyijia.com/).

Changes in non-linear and time-domain heart rate variability indices between critically ill COVID-19 and all-cause sepsis patients -a retrospective study (preprint)

Objective: To measure heart rate variability metrics in critically ill COVID-19 patients with comparison to all-cause critically ill sepsis patients. Design and patients: Retrospective analysis of COVID-19 patients admitted to an ICU for at least 24h at any of Emory Healthcare ICUs between March and April 2020. The comparison group was a cohort of all-cause sepsis patients prior to COVID-19 pandemic. Interventions: none. Measurements: Continuous waveforms were captured from the patient monitor. The EKG was then analyzed for each patient over a 300 second (s) observational window, that was shifted by 30s in each iteration from admission till discharge. A total of 23 HRV metrics were extracted in each iteration. We use the Kruskal-Wallis and Steel-Dwass tests (p < 0.05) for statistical analysis and interpretations of HRV multiple measures. Results: A total of 141 critically-ill COVID-19 patients met inclusion criteria, who were compared to 208 patients with all-cause sepsis. Demographic parameters were similar apart from a high proportion of African-Americans in the COVID-19 cohort. Three non-linear markers, including SD1:SD2, sample entropy, approximate entropy and four linear features mode of Beat-to-Beat interval (NN), Acceleration Capacity (AC), Deceleration Capacity (DC), and pNN50, were statistical significance between more than one binary combinations of the sub-groups (comparing survivors and non-survivors in both the COVID-19 and sepsis cohorts). The three nonlinear features and AC, DC, and NN (mode) were statistically significant across all four combinations. Temporal analysis of the main markers showed low variability across the 5 days of analysis, compared with sepsis patients. Conclusions: Heart rate variability is broadly implicated across patients infected with SARS-CoV-2, and admitted to the ICU for critical illness. Comparing these metrics to patients with all-cause sepsis suggests a unique set of expressions that differentiate this viral phenotype. This finding could be investigated further as a potential biomarker to predict poor outcome in this patient population, and could also be a starting point to measure potential autonomic dysfunction in COVID-19.