DESIGN: Single blinded, international, multicenter randomized controlled trial with 1:1 allocation ratio.
SETTING: Tertiary and University hospitals.
INTERVENTIONS: Patients (n=10,600) undergoing coronary artery bypass graft will be randomized to receive either volatile anesthetic as part of the anesthetic plan, or total intravenous anesthesia.
MEASUREMENTS AND MAIN RESULTS: The primary end point of the study will be one-year mortality (any cause). Secondary endpoints will be 30-day mortality; 30-day death or non-fatal myocardial infarction (composite endpoint); cardiac mortality at 30day and at one year; incidence of hospital re-admission during the one year follow-up period and duration of intensive care unit, and hospital stay. The sample size is based on the hypothesis that volatile anesthetics will reduce 1-year unadjusted mortality from 3% to 2%, using a two-sided alpha error of 0.05, and a power of 0.9.
CONCLUSIONS: The trial will determine whether the simple intervention of adding a volatile anesthetic, an intervention that can be implemented by all anesthesiologists, can improve one-year survival in patients undergoing coronary artery bypass graft surgery.
METHODS: We downloaded COVID-19 outbreak data of the number of confirmed cases in all countries as of October 19, 2020. The IRT-based predictive model was built to determine the pandemic IP for each country. A model building scheme was demonstrated to fit the number of cumulative infected cases. Model parameters were estimated using the Solver add-in tool in Microsoft Excel. The absolute advantage coefficient (AAC) was computed to track the IP at the minimum of incremental points on a given ogive curve. The time-to-event analysis (a.k.a. survival analysis) was performed to compare the difference in IPs among continents using the area under the curve (AUC) and the respective 95% confidence intervals (CIs). An online comparative dashboard was created on Google Maps to present the epidemic prediction for each country.
RESULTS: The top 3 countries that were hit severely by COVID-19 were France, Malaysia, and Nepal, with IP days at 263, 262, and 262, respectively. The top 3 continents that were hit most based on IP days were Europe, South America, and North America, with their AUCs and 95% CIs at 0.73 (0.61-0.86), 0.58 (0.31-0.84), and 0.54 (0.44-0.64), respectively. An online time-event result was demonstrated and shown on Google Maps, comparing the IP probabilities across continents.
CONCLUSION: An IRT modeling scheme fitting the epidemic data was used to predict the length of IP days. Europe, particularly France, was hit seriously by COVID-19 based on the IP days. The IRT model incorporated with AAC is recommended to determine the pandemic IP.
RESULTS: During infection experiment in a series of colorectal cancer cell lines, we adventitiously observed a development of persistent infection by NDV in SW480 cells, but not in other cell lines tested. This cell population, designated as SW480P, showed resistancy towards NDV killing in a re-infection experiment. The SW480P cells retained NDV genome and produced virus progeny with reduced plaque forming ability.
CONCLUSION: These observations showed that NDV could develop persistent infection in cancer cells and this factor needs to be taken into consideration when using NDV in clinical settings.
METHODS: We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income.
RESULTS: Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19-1.94), wheeze (OR 1.37, 95% CI 1.16-1.63) and dyspnoea (OR 1.83, 95% CI 1.53-2.20), but not lower FVC (β=0.02 L, 95% CI -0.02-0.06 L) or lower FEV1/FVC (β=0.04%, 95% CI -0.49-0.58%). Some findings differed by sex and gross national income.
CONCLUSION: At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.