RÉSUMÉ
BACKGROUND@#This study aimed to describe the changing distribution of human brucellosis between 2004 and 2017 in mainland China and seek scientific evidence of the relationship between socio-economic, environmental, and ecological factors and human brucellosis incidence.@*METHODS@#The annual numbers of brucellosis cases and incidence rates from 31 provinces in mainland China between 2004 and 2017 were obtained from the Data-Center for China Public Health Science. The number of monthly brucellosis cases in 2018 was obtained from the Chinese Center for Disease Control and Prevention. The electronic map of the People's Republic of China was downloaded from the National Earth System Science Data Sharing Platform. Human population density, gross domestic product (GDP), and an inventory of cattle and sheep at the end of each year from 2004 to 2017 were obtained from the National Bureau of Statistics of China. Annual rainfall data from 31 provinces in the People's Republic of China from 2004 to 2017 were collected from the China Meteorological Data Service Center. The risk distribution and changing trends of human brucellosis were mapped with ArcGIS. A cluster analysis was employed to identify geographical areas and periods with statistically significant incidence rates. Multivariate linear regression was used to determine possible factors that were significantly correlated with the presence of human brucellosis cases.@*RESULTS@#Human brucellosis cases have spread throughout the whole country. Human brucellosis cases occurred mostly from March to August and were concentrated from April to July. The inventory of sheep, GDP, and climate were significantly correlated with the presence of brucellosis cases in mainland China.@*CONCLUSIONS@#The geographical expansion of human brucellosis in mainland China was observed, so did the high-incidence clusters between 2004 and 2017. Most of the cases were reported during the early spring to early summer (February-August). Results from the multivariate linear regression suggested that the inventory of sheep, GDP, and climate were significantly associated with the incidence of human brucellosis in mainland China.
RÉSUMÉ
Background@#Air pollutants and their pathogenic effects differ among regions and seasons. We aimed to explore the relationship between fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone-8 hours (O3-8h) concentrations in heating and non-heating seasons and the associated death risk due to cardiovascular diseases (CDs), respiratory diseases (RDs), and malignant tumors.@*Methods@#Data were collected in Shenyang, China, from April 2013 to March 2016. We analyzed the correlation or lagged effect of atmospheric pollutant concentration, meteorological conditions, and death risk due to disorders of the circulatory system, respiratory system, and malignant tumor in heating and non-heating seasons. We also used multivariate models to analyze the association of air pollutants during holidays with the death risk due to the evaluated diseases while considering the presence or absence of meteorological factors.@*Results@#An increase in the daily average SO2 concentration by 10 μg/m3 increased the death risk by CDs, which reached a maximum of 2.0% (95% confidence interval [CI]: 1.3%–2.7%) on lagging day 4 during the non-heating season and 0.2% (95% CI: 0.1%-0.4%) on lagging day 3 during the heating season. The risk of death caused by RDs peaked on lagging day 1 by 0.8% (95% CI: 0.4%–1.2%) during the heating season. An increase in O3-8h concentration by 10 μg/m3 increased the risk of RD-related death on lagging day 2 by 1.0% (95% CI: 0.4%–1.7%) during the non-heating season, which was significantly higher than the 0.1% (95% CI: 0–0.9%) increase during the heating season. Further, an increase in the daily average PM2.5 concentration by 10 μg/m3 increased the risk of death caused by RDs by 0.3% and 0.8% during heating and non-heating seasons, respectively, which peaked on lagging day 0. However, air pollution was not significantly associated with the risk of death caused by malignant tumors.@*Conclusion@#Short-term exposure to PM2.5, SO2, and O3 during the non-heating season resulted in higher risks of CD-related death, followed by RD-related death.
RÉSUMÉ
BACKGROUND@#Air pollutants and their pathogenic effects differ among regions and seasons. We aimed to explore the relationship between fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone-8 hours (O3-8h) concentrations in heating and non-heating seasons and the associated death risk due to cardiovascular diseases (CDs), respiratory diseases (RDs), and malignant tumors.@*METHODS@#Data were collected in Shenyang, China, from April 2013 to March 2016. We analyzed the correlation or lagged effect of atmospheric pollutant concentration, meteorological conditions, and death risk due to disorders of the circulatory system, respiratory system, and malignant tumor in heating and non-heating seasons. We also used multivariate models to analyze the association of air pollutants during holidays with the death risk due to the evaluated diseases while considering the presence or absence of meteorological factors.@*RESULTS@#An increase in the daily average SO2 concentration by 10 μg/m increased the death risk by CDs, which reached a maximum of 2.0% (95% confidence interval [CI]: 1.3%-2.7%) on lagging day 4 during the non-heating season and 0.2% (95% CI: 0.1%-0.4%) on lagging day 3 during the heating season. The risk of death caused by RDs peaked on lagging day 1 by 0.8% (95% CI: 0.4%-1.2%) during the heating season. An increase in O3-8h concentration by 10 μg/m increased the risk of RD-related death on lagging day 2 by 1.0% (95% CI: 0.4%-1.7%) during the non-heating season, which was significantly higher than the 0.1% (95% CI: 0-0.9%) increase during the heating season. Further, an increase in the daily average PM2.5 concentration by 10 μg/m increased the risk of death caused by RDs by 0.3% and 0.8% during heating and non-heating seasons, respectively, which peaked on lagging day 0. However, air pollution was not significantly associated with the risk of death caused by malignant tumors.@*CONCLUSION@#Short-term exposure to PM2.5, SO2, and O3 during the non-heating season resulted in higher risks of CD-related death, followed by RD-related death.
RÉSUMÉ
OBJECTIVE: To determine whether the introducer curving technique is useful in decreasing the degree of tilting of transfemoral Tulip filters. MATERIALS AND METHODS: The study sample group consisted of 108 patients with deep vein thrombosis who were enrolled and planned to undergo thrombolysis, and who accepted transfemoral Tulip filter insertion procedure. The patients were randomly divided into Group C and Group T. The introducer curving technique was Adopted in Group T. The post-implantation filter tilting angle (ACF) was measured in an anteroposterior projection. The retrieval hook adhering to the vascular wall was measured via tangential cavogram during retrieval. RESULTS: The overall average ACF was 5.8 +/- 4.14 degrees. In Group C, the average ACF was 7.1 +/- 4.52 degrees. In Group T, the average ACF was 4.4 +/- 3.20 degrees. The groups displayed a statistically significant difference (t = 3.573, p = 0.001) in ACF. Additionally, the difference of ACF between the left and right approaches turned out to be statistically significant (7.1 +/- 4.59 vs. 5.1 +/- 3.82, t = 2.301, p = 0.023). The proportion of severe tilt (ACF > or = 10degrees) in Group T was significantly lower than that in Group C (9.3% vs. 24.1%, chi2 = 4.267, p = 0.039). Between the groups, the difference in the rate of the retrieval hook adhering to the vascular wall was also statistically significant (2.9% vs. 24.2%, chi2 = 5.030, p = 0.025). CONCLUSION: The introducer curving technique appears to minimize the incidence and extent of transfemoral Tulip filter tilting.