Background: Central venous catheters (CVCs) are essential to current intensive care unit (ICU) practices as a tool for treating critically ill patients. However, the use of CVCs is associated with substantial risk of ...Background: Central venous catheters (CVCs) are essential to current intensive care unit (ICU) practices as a tool for treating critically ill patients. However, the use of CVCs is associated with substantial risk of infection. Central line associated bloodstream infection (CLABSI) is increasing in prevalence each year and is among the major causes of bloodstream infection in ICU patients. Therefore, investigating the epidemiology and risk factors of CLABSI in ICU patients is important. Objective: This study aimed to investigate the incidence rates, causative pathogens and risk factors of CLABSI in an ICU population. Methods: A retrospective observational study was performed in an ICU at Qilu Hospital of Shandong University in China from January 2016 to December 2020. Patients with at least one CVC were enrolled, and information relevant to CVC use was recorded. The prevalence was calculated, and related risk factors were analyzed. Results: A total of 1920 catheters were identified, 507 of which were eligible for analysis. For each of the years 2016-2020, the incidence rates of CLABSI were 1.91, 3.18, 1.69, 2.97 and 1.27 per 1000 catheter days, respectively. The yeast Candida albicans was the most prevalent pathogen (16 [(3.2%]), followed by Gram-positive methicillin-resistant Staphylococcus aureus (11 [2.2%]) and the Gram-negative multidrug-resistant pathogen Acinetobacter baumanii. Risk factors associated with CLABSI development were age, (p = 0.05), Charlson comorbidity index > 5 (p Conclusion: Candida albicans was the most common causative microorganism, which was followed by Gram positive methicillin resistant Staphylococcus, MDR K. pneumoniae and Acinetobacter baumanii.展开更多
灰狼优化算法(Grey Wolf Optimization,GWO)是一种新型的群智能优化算法。与其他智能优化算法类似,该算法仍存在收敛速度慢、容易陷入局部极小点的缺点。针对这一问题,提出了具有自适应搜索策略的改进算法。为了提高算法的收敛速度和优...灰狼优化算法(Grey Wolf Optimization,GWO)是一种新型的群智能优化算法。与其他智能优化算法类似,该算法仍存在收敛速度慢、容易陷入局部极小点的缺点。针对这一问题,提出了具有自适应搜索策略的改进算法。为了提高算法的收敛速度和优化精度,通过适应度值控制智能个体位置,并引入了最优引导搜索方程;另一方面,为提高GWO的种群多样性,改进算法利用位置矢量差随机跳出局部最优。最后对10个标准测试函数进行了仿真实验,并与其他4种算法进行了比较,统计结果和Wilcoxon符号秩检验结果均表明,所提出的改进算法在收敛速度以及搜索精度方面具有明显优势。展开更多
The second(O2)observational campaign of gravitational waves(GWs)organized by the LIGO/Virgo Collaborations has led to several breakthroughs such as the detection of GW signals from merger systems involving black holes...The second(O2)observational campaign of gravitational waves(GWs)organized by the LIGO/Virgo Collaborations has led to several breakthroughs such as the detection of GW signals from merger systems involving black holes or neutrons stars.During O2,14 GW alerts were sent to the astronomical community with sky regions mostly covering over hundreds of square degrees.Among them,six were finally confirmed as real astrophysical events.Since 2013,a new set of ground-based robotic telescopes called Ground-based Wide Angle Camera system(GWAC)project and its pathfinder mini-GWAC has been developed to contribute to the various challenges of multi-messenger and time domain astronomy.The GWAC system is built up in the framework of the ground-segment system of the SVOM mission that will be devoted to the study of the multi-wavelength transient sky in the next decade.During O2,only the mini-GWAC telescope network was fully operational.Due to the wide field of view and fast automatic follow-up capabilities of the mini-GWAC telescopes,they were adept to efficiently cover the sky localization areas of GW event candidates.In this paper,we present the mini-GWAC pipeline we have set up to respond to GW alerts and we report our optical follow-up observations of eight GW alerts detected during the O2 run.Our observations provided the largest coverage of the GW localization areas with a short latency made by any optical facility.We found tens of optical transient candidates in our images,but none of those could be securely associated with any confirmed black hole-black hole merger event.Based on this first experience and the near future technical improvements of our network system,we will be more competitive in detecting the optical counterparts from some GW events that will be identified during the upcoming O3 run,especially those emerging from binary neutron star mergers.展开更多
目的:比较玻璃体切割联合内界膜剥除术或内界膜覆盖术治疗高度近视黄斑裂孔视网膜脱离(MHRD)的疗效。方法:回顾性临床研究。选取2020-01/2021-06于我院行玻璃体切割联合内界膜剥除术或内界膜覆盖术治疗的高度近视MHRD患者38例38眼,根据...目的:比较玻璃体切割联合内界膜剥除术或内界膜覆盖术治疗高度近视黄斑裂孔视网膜脱离(MHRD)的疗效。方法:回顾性临床研究。选取2020-01/2021-06于我院行玻璃体切割联合内界膜剥除术或内界膜覆盖术治疗的高度近视MHRD患者38例38眼,根据手术方式分为对照组(行玻璃体切割联合内界膜剥除术)和观察组(行玻璃体切割联合内界膜覆盖术)。随访至术后3mo,比较两组患者手术时间、最佳矫正视力(BCVA)、黄斑裂孔闭合和视网膜复位情况。结果:两组患者手术时间无差异(30.71±4.55min vs 35.20±5.44min,P=0.384)。末次随访时,两组患者BCVA均较术前明显改善(均P<0.01),但两组患者BCVA(LogMAR)无差异(1.39±0.24 vs 1.46±0.27,P=0.700);观察组患者黄斑裂孔闭合率高于对照组(100%vs 71%,P=0.024),但两组患者视网膜再脱离率比较无差异(0 vs 10%,P=0.492)。结论:两种手术方式均可改善患者视力,但玻璃体切割联合内界膜覆盖术后黄斑裂孔闭合率更高。展开更多
文摘Background: Central venous catheters (CVCs) are essential to current intensive care unit (ICU) practices as a tool for treating critically ill patients. However, the use of CVCs is associated with substantial risk of infection. Central line associated bloodstream infection (CLABSI) is increasing in prevalence each year and is among the major causes of bloodstream infection in ICU patients. Therefore, investigating the epidemiology and risk factors of CLABSI in ICU patients is important. Objective: This study aimed to investigate the incidence rates, causative pathogens and risk factors of CLABSI in an ICU population. Methods: A retrospective observational study was performed in an ICU at Qilu Hospital of Shandong University in China from January 2016 to December 2020. Patients with at least one CVC were enrolled, and information relevant to CVC use was recorded. The prevalence was calculated, and related risk factors were analyzed. Results: A total of 1920 catheters were identified, 507 of which were eligible for analysis. For each of the years 2016-2020, the incidence rates of CLABSI were 1.91, 3.18, 1.69, 2.97 and 1.27 per 1000 catheter days, respectively. The yeast Candida albicans was the most prevalent pathogen (16 [(3.2%]), followed by Gram-positive methicillin-resistant Staphylococcus aureus (11 [2.2%]) and the Gram-negative multidrug-resistant pathogen Acinetobacter baumanii. Risk factors associated with CLABSI development were age, (p = 0.05), Charlson comorbidity index > 5 (p Conclusion: Candida albicans was the most common causative microorganism, which was followed by Gram positive methicillin resistant Staphylococcus, MDR K. pneumoniae and Acinetobacter baumanii.
文摘灰狼优化算法(Grey Wolf Optimization,GWO)是一种新型的群智能优化算法。与其他智能优化算法类似,该算法仍存在收敛速度慢、容易陷入局部极小点的缺点。针对这一问题,提出了具有自适应搜索策略的改进算法。为了提高算法的收敛速度和优化精度,通过适应度值控制智能个体位置,并引入了最优引导搜索方程;另一方面,为提高GWO的种群多样性,改进算法利用位置矢量差随机跳出局部最优。最后对10个标准测试函数进行了仿真实验,并与其他4种算法进行了比较,统计结果和Wilcoxon符号秩检验结果均表明,所提出的改进算法在收敛速度以及搜索精度方面具有明显优势。
基金supported by the National Natural Science Foundation of China(Grant Nos.11533003,11673006,U1331202,U1931133 and U1938201)the Guangxi Science Foundation(2016GXNSFFA380006,AD17129006and 2018GXNSFGA281007)+3 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB23040000)the Strategic Pioneer Program on Space Science,Chinese Academy of Sciences(XDA15052600)financial support from the Chinese Academy of Sciences PIFI post-doctoral fellowship program(program C)financial support of the Univ Earth S Labex program at Sorbonne Paris Cité(ANR-10-LABX-0023 and ANR-11-IDEX-0005-02)
文摘The second(O2)observational campaign of gravitational waves(GWs)organized by the LIGO/Virgo Collaborations has led to several breakthroughs such as the detection of GW signals from merger systems involving black holes or neutrons stars.During O2,14 GW alerts were sent to the astronomical community with sky regions mostly covering over hundreds of square degrees.Among them,six were finally confirmed as real astrophysical events.Since 2013,a new set of ground-based robotic telescopes called Ground-based Wide Angle Camera system(GWAC)project and its pathfinder mini-GWAC has been developed to contribute to the various challenges of multi-messenger and time domain astronomy.The GWAC system is built up in the framework of the ground-segment system of the SVOM mission that will be devoted to the study of the multi-wavelength transient sky in the next decade.During O2,only the mini-GWAC telescope network was fully operational.Due to the wide field of view and fast automatic follow-up capabilities of the mini-GWAC telescopes,they were adept to efficiently cover the sky localization areas of GW event candidates.In this paper,we present the mini-GWAC pipeline we have set up to respond to GW alerts and we report our optical follow-up observations of eight GW alerts detected during the O2 run.Our observations provided the largest coverage of the GW localization areas with a short latency made by any optical facility.We found tens of optical transient candidates in our images,but none of those could be securely associated with any confirmed black hole-black hole merger event.Based on this first experience and the near future technical improvements of our network system,we will be more competitive in detecting the optical counterparts from some GW events that will be identified during the upcoming O3 run,especially those emerging from binary neutron star mergers.
文摘目的:比较玻璃体切割联合内界膜剥除术或内界膜覆盖术治疗高度近视黄斑裂孔视网膜脱离(MHRD)的疗效。方法:回顾性临床研究。选取2020-01/2021-06于我院行玻璃体切割联合内界膜剥除术或内界膜覆盖术治疗的高度近视MHRD患者38例38眼,根据手术方式分为对照组(行玻璃体切割联合内界膜剥除术)和观察组(行玻璃体切割联合内界膜覆盖术)。随访至术后3mo,比较两组患者手术时间、最佳矫正视力(BCVA)、黄斑裂孔闭合和视网膜复位情况。结果:两组患者手术时间无差异(30.71±4.55min vs 35.20±5.44min,P=0.384)。末次随访时,两组患者BCVA均较术前明显改善(均P<0.01),但两组患者BCVA(LogMAR)无差异(1.39±0.24 vs 1.46±0.27,P=0.700);观察组患者黄斑裂孔闭合率高于对照组(100%vs 71%,P=0.024),但两组患者视网膜再脱离率比较无差异(0 vs 10%,P=0.492)。结论:两种手术方式均可改善患者视力,但玻璃体切割联合内界膜覆盖术后黄斑裂孔闭合率更高。
基金supported by the National Natural Science Foundation of China(No.52005132)the Key Research and Development Program of Shandong Province,China(No.2021ZLGX01)+1 种基金the Natural Science Foundation of Shandong Province,China(No.ZR2019PEE038)the Heilongjiang Touyan Team for the funding support。
