Wearing N95 masks decreases the odor discrimination ability of healthcare workers: a self-controlled before-after study.

Objective: During the coronavirus disease 2019 (COVID-19) pandemic, the N95 mask is an essential piece of protective equipment for healthcare workers. However, the N95 mask may inhibit air exchange and odor penetration. Our study aimed to determine whether the use of N95 masks affects the odor discrimination ability of healthcare workers. Methods: In our study, all the participants were asked to complete three olfactory tests. Each test involved 12 different odors. The participants completed the test while wearing an N95 mask, a surgical mask, and no mask. The score for each olfactory test was documented. Results: The olfactory test score was significantly lower when the participants wore N95 masks than when they did not wear a mask (7 vs. 10, p < 0.01). The score was also lower when the participants wore N95 masks than surgical masks (7 vs. 8, p < 0.01). Conclusion: Wearing N95 masks decreases the odor discrimination ability of healthcare workers. Therefore, we suggest that healthcare workers seek other clues when diagnosing disease with a characteristic odor.

Wearing N95 masks decreases the odor discrimination ability of healthcare workers: a self-controlled before-after study

Objective During the coronavirus disease 2019 (COVID-19) pandemic, the N95 mask is an essential piece of protective equipment for healthcare workers. However, the N95 mask may inhibit air exchange and odor penetration. Our study aimed to determine whether the use of N95 masks affects the odor discrimination ability of healthcare workers. Methods In our study, all the participants were asked to complete three olfactory tests. Each test involved 12 different odors. The participants completed the test while wearing an N95 mask, a surgical mask, and no mask. The score for each olfactory test was documented. Results The olfactory test score was significantly lower when the participants wore N95 masks than when they did not wear a mask (7 vs. 10, p < 0.01). The score was also lower when the participants wore N95 masks than surgical masks (7 vs. 8, p < 0.01). Conclusion Wearing N95 masks decreases the odor discrimination ability of healthcare workers. Therefore, we suggest that healthcare workers seek other clues when diagnosing disease with a characteristic odor.

Semiconductor SERS on Colourful Substrates with Fabry-Pérot Cavities.

Non-metallic materials have emerged as a new family of active substrates for surface-enhanced Raman scattering (SERS), with unique advantages over their metal counterparts. However, owing to their inefficient interaction with the incident wavelength, the Raman enhancement achieved with non-metallic materials is considerably lower with respect to the metallic ones. Herein, we propose colourful semiconductor-based SERS substrates for the first time by utilizing a Fabry-Pérot cavity, which realize a large freedom in manipulating light. Owing to the delicate adjustment of the absorption in terms of both frequency and intensity, resonant absorption can be achieved with a variety of non-metal SERS substrates, with the sensitivity further enhanced by ≈100 times. As a typical example, by introducing a Fabry-Pérot-type substrate fabricated with SiO2 /Si, a rather low detection limit of 10-16  M for the SARS-CoV-2S protein is achieved on SnS2 . This study provides a realistic strategy for increasing SERS sensitivity when semiconductors are employed as SERS substrates.

COVID-19 inhibits spermatogenesis in the testes by inducing cellular senescence.

Introduction: COVID-19 (SARS-CoV-2) has been linked to organ damage in humans since its worldwide outbreak. It can also induce severe sperm damage, according to research conducted at numerous clinical institutions. However, the exact mechanism of damage is still unknown. Methods: In this study, testicular bulk-RNA-seq Data were downloaded from three COVID-19 patients and three uninfected controls from GEO to evaluate the effect of COVID-19 infection on spermatogenesis. Relative expression of each pathway and the correlation between genes or pathways were analyzed by bioinformatic methods. Results: By detecting the relative expression of each pathway and the correlation between genes or pathways, we found that COVID-19 could induce testicular cell senescence through MAPK signaling pathway. Cellular senescence was synergistic with MAPK pathway, which further affected the normal synthesis of cholesterol and androgen, inhibited the normal synthesis of lactate and pyruvate, and ultimately affected spermatogenesis. The medications targeting MAPK signaling pathway, especially MAPK1 and MAPK14, are expected to be effective therapeutic medications for reducing COVID-19 damage to spermatogenesis. Conclusion: These results give us a new understanding of how COVID-19 inhibits spermatogenesis and provide a possible solution to alleviate this damage.

Cost-Effectiveness of 12 First-Line Treatments for Patients With Advanced EGFR Mutated NSCLC in the United Kingdom and China.

Background: Lung cancer is imposing significant pressure on the national health insurance system worldwide, especially under the COVID-19 pandemic. However, the cost-effectiveness of all available first-line treatments for patients with advanced epidermal growth factor receptor (EGFR) mutated non-small cell lung cancer (NSCLC) is still uncertain. The aim of this study was to evaluate the cost-effectiveness of 12 first-line treatments for patients with advanced EGFR mutated NSCLC from the perspective of the United Kingdom (UK) National Health Service and Chinese health care system. Methods: We used a Markov model to estimate the cost-effectiveness of 12 treatments, including 6 EGFR tyrosine kinase inhibitors, 4 combination treatments and 2 chemotherapies. The key clinical efficacy and safety data were from a network meta-analysis. The cost and health preference were mainly collected from the literature. The most cost-effective treatment was inferred through a sequential analysis. Uncertainty was tested with one-way sensitivity analyses, scenario analyses, and probabilistic sensitivity analyses. Quality-adjusted life years (QALYs), direct medical costs, and incremental cost-effectiveness ratio (ICER) were estimated, at willingness-to-pay thresholds of £20000 to £50000 and £8000 to £24000 per QALY in the UK and China respectively. Results: For clinical effectiveness, osimertinib and gefitinib plus pemetrexed based chemotherapy (PbCT) yielded the highest QALYs, while two chemotherapy treatments gained the lowest QALYs. For costs, gefitinib treatment was the cheapest option in both countries (£24529 in the UK and £12961 in China). For cost-effectiveness, 4 treatments including gefitinib, gefitinib plus pemetrexed, gefitinib plus PbCT, and osimertinib formed the cost-effectiveness frontier in both countries. Gefitinib alone (70.7% and 80.0% under the threshold of £20000 and £8000 per QALY in the UK and China, respectively) and gefitinib plus PbCT (62.3% and 71.2% under the threshold of £50000 and £24000 per QALY in the UK and China, respectively) were most likely to be cost-effective compared with other first-line treatments. Conclusions: Gefitinib and gefitinib plus PbCT were likely to be cost-effective for patients with advanced EGFR mutated NSCLC in both countries.

Investigation and precautions of SARS-CoV-2 infection among healthcare workers in Emergency Center

Objective: To analyze the causes of SARS-CoV-2 nosocomial infection among healthcare workers (HCWs) and explore the effective precaution strategies in Emergency Center.

Arbidol is associated with increased in-hospital mortality among 109 patients with severe COVID-19: A multicenter, retrospective study.

BACKGROUND: The antiviral therapy has been considered as an ordinary intervention for COVID-19 patients. However, the effectiveness of antiviral therapy is uncertain. This study was designed to determine the association between the antiviral therapy and in-hospital mortality among severe COVID-19 patients. METHODS: This study enrolled severe COVID-19 patients admitted to four designated hospitals in Wuhan, China. The use of antiviral treatments, demographics, laboratory variables, co-morbidities, complications, and other treatments were compared between survival and fatal cases. The association between antiviral agents and in-hospital mortality were analyzed. RESULTS: In total, 109 severe COVID-19 patients (mean age 65.43) were enrolled for analysis, among which, 61 (56.0%) patients were discharged alive, and 48 (44.0%) died during hospitalization. We found no association between lopinavir/ritonavir (LPV/r) treatment and the in-hospital mortality (odds ratio (OR) = 0.195, 95% confidence interval (CI) = 0.023-1.679). Besides, ribavirin (OR = 0.738, 95% CI = 0.344-1.582), oseltamivir (OR = 0.765, 95% CI = 0.349-1.636), and interferon-alpha (IFN-α) (OR = 0.371, 95% CI = 0.112-1.236) were not associated with the in-hospital mortality. However, arbidol monotherapy (OR = 5.027, 95% CI = 1.795-14.074) or the combination of arbidol and oseltamivir (OR = 5.900, 95% CI = 1.190-29.247) was associated with an increased in-hospital mortality. In addition, the multiple logistic regression identified a significant association between the use of arbidol and the in-hospital mortality (adjusted OR = 4.195, 95% CI = 1.221-14.408). CONCLUSIONS: Our findings indicated that LPV/r, IFN-α, ribavirin, or oseltamivir have no beneficial effects on the prognosis of severe COVID-19 patients, whereas the use of arbidol is associated with increased in-hospital mortality.

Correlation between white blood cell count at admission and mortality in COVID-19 patients: a retrospective study.

BACKGROUND: Coronavirus disease-19 (COVID-19) has become a world health threaten. Its risk factors with death were still not known. White blood cells (WBC) count as a reflection of inflammation has played a vital role in COVID-19, however its level with death is not yet investigated. METHODS: In this retrospective, single-center study, all confirmed patients with COVID-19 at West Branch of Union Hospital from Jan 29 to Feb 28, 2020 were collected and analyzed. Demographic and clinical data including laboratory examinations were analyzed and compared between recovery and death patients. RESULTS: A total of 163 patients including 33 death cases were included in this study. Significant association was found between WBC count and death (HR = 1.14, 95%CI: 1.09-1.20, p < 0.001). The regression analysis results showed there was a significant association between WBC count and death (HR = 5.72, 95%CI: 2.21-14.82, p < 0.001) when use the second quartile as a cutoff value (> 6.16 × 10^9/L). The difference was still exist after adjusting for confounding factors (HR = 6.26, 95%CI: 1.72-22.77, p = 0.005). In addition, Kaplan-meier survival analysis showed that there was a significant decline of the cumulative survival rate (p < 0.001) in those with WBC count ≥6.16 × 10^9/L. CONCLUSION: WBC count at admission is significantly corelated with death in COVID-19 patients. Higher level of WBC count should be given more attention in the treatment of COVID-19.

Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients.

BACKGROUND: Risk scores are needed to predict the risk of death in severe coronavirus disease 2019 (COVID-19) patients in the context of rapid disease progression. METHODS: Using data from China (training dataset, n = 96), prediction models were developed by logistic regression and then risk scores were established. Leave-one-out cross validation was used for internal validation and data from Iran (test dataset, n = 43) was used for external validation. RESULTS: A NSL model (area under the curve (AUC) 0.932) and a NL model (AUC 0.903) were developed based on neutrophil percentage and lactate dehydrogenase with and without oxygen saturation (SaO2) using the training dataset. AUCs of the NSL and NL models in the test dataset were 0.910 and 0.871, respectively. The risk scoring systems corresponding to these two models were established. The AUCs of the NSL and NL scores in the training dataset were 0.928 and 0.901, respectively. At the optimal cut-off value of NSL score, the sensitivity and specificity were 94% and 82%, respectively. The sensitivity and specificity of NL score were 94% and 75%, respectively. CONCLUSIONS: These scores may be used to predict the risk of death in severe COVID-19 patients and the NL score could be used in regions where patients' SaO2 cannot be tested.

Development and progress of clinical trials of Coronavirus Disease 2019 antiviral drugs.

INTRODUCTION: We have summarized and analyzed the clinical trial registration status and the latest research progress of eight major antiviral drugs during the epidemic of Coronavirus Disease 2019 (COVID-19), which can provide reference methods for clinical formulation of the best antiviral treatment. AREAS COVERED: We used the generic names of 8 antiviral drugs as keywords to search and analyze the COVID-19-related clinical trials registered in Chinese Clinical Trial Registry and ClinicalTrials.gov. Then, we used the keywords to obtain and summarize their clinical research results related to COVID-19 in CNKI, WANFANG, CQVIP, and PubMed database. EXPERT OPINION: The registration system of clinical trials and the level of clinical trial design need to be further improved. At present, no specific drug has been found for the treatment of COVID-19, the efficacy of antiviral drugs mostly comes from small sample studies or retrospective studies, and the level of clinical evidence is low. Besides, multi-drug combination therapy may become a more effective treatment choice, but the drug interactions and adverse drug reactions also need to be closely monitored. In summary, the safety and efficacy of various antiviral drugs need to be confirmed by large samples and high-quality RCT studies.

Scoring systems for predicting mortality for severe patients with COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been widely spread and caused tens of thousands of deaths, especially in patients with severe COVID-19. This analysis aimed to explore risk factors for mortality of severe COVID-19, and establish a scoring system to predict in-hospital deaths. METHODS: Patients with COVID-19 were retrospectively analyzed and clinical characteristics were compared. LASSO regression as well as multivariable analysis were used to screen variables and establish prediction model. FINDINGS: A total of 2529 patients with COVID-19 was retrospectively analyzed, and 452 eligible severe COVID-19 were used for finally analysis. In training cohort, the median age was 66•0 years while it was 73•0 years in non-survivors. Patients aged 60-75 years accounted for the largest proportion of infected populations and mortality toll. Anti-SARS-CoV-2 antibodies were monitored up to 54 days, and IgG levels reached the highest during 20-30 days. No differences were observed of antibody levels between severe and non-severe patients. About 60.2% of severe patients had complications. Among acute myocardial injury (AMI), acute kidney injury (AKI) and acute liver injury (ALI), the heart was the earliest injured organ, whereas the time from AKI to death was the shortest. Age, diabetes, coronary heart disease (CHD), percentage of lymphocytes (LYM%), procalcitonin (PCT), serum urea, C reactive protein and D-dimer (DD), were identified associated with mortality by LASSO binary logistic regression. Then multivariable analysis was performed to conclude that old age, CHD, LYM%, PCT and DD remained independent risk factors for mortality. Based on the above variables, a scoring system of COVID-19 (CSS) was established to divide patients into low-risk and high-risk groups. This model displayed good discrimination (AUC=0·919) and calibration (P=0·264). Complications in low-risk and high-risk groups were significantly different (P<0·05). Use of corticosteroids in low-risk groups increased hospital stays by 4·5 days (P=0·036) and durations of disease by 7·5 days (P=0·012) compared with no corticosteroids. INTERPRETATION: Old age, CHD, LYM%, PCT and DD were independently related to mortality. CSS was useful for predicting in-hospital mortality and complications, and it could help clinicians to identify high-risk patients with poor prognosis. FUNDING: This work was supported by the Key Project for Anti-2019 novel Coronavirus Pneumonia from the Ministry of Science and Technology, China (grant number 2020YFC0845500).