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Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China

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Biomedical and Environmental Sciences 2020年第12期33卷 893-905页

作者： MA Yan Zhu Dong Shan chen Ren Bo SHI nan nan liU Si hong fan yi Pin WU Gui hui yang Pu Ye BAI Jiang Feng chen hong chen li ying FENG Qiao GUO Tuan Mao HOU Yong hu Gui Fen hu Xiao Mei hu Yun hong huANG Jin huANG Qiu hua huANG Shao Zhen JI liang JIN Hai Hao LEI Xiao li chun Yan li Min qing li Qun Tang li Xian Yong liU hong De liU Jin Ping liU Zhang MA Yu Ting MAO Ya MO liu Fen na hui WANG Jing Wei SONG fang li SUN Sheng WANG Dong Ting WANG ming Xuan WANG Xiao Yan WANG yin Zhen WANG Yu Dong WU Wei WU Lan Ping XIAO Yan hua XIE Hai Jun XU hong ming XU Shou fang XUE Rui Xia yang chun yang Kai Jun YUAN Sheng li ZHANG Gong Qi ZHANG Jin Bo ZHANG lin Song zhao Shu Sen zhao Wan ying ZheNG Kai ZHOU ying chun Zhu Jun Teng Zhu Tian qing ZHANG hua Min WANG Yan Ping WANG Yong Yan 无 Institute of Basic Research in Clinical Medicine China Academy of Chinese Medical SciencesBeijing 100700China Centre for health Management and Policy Research School of Public HealthCheeloo College of MedicineShandong UniversityJinan 250012ShandongChina Institute of Information on Traditional Chinese Medicine China Academy of Chinese Medical SciencesBeijing 100700China Department of Tuberculosis The Public Health Clinical Center of ChengduChengdu 610066SichuanChina Department of Infectious Disease Shaanxi Infectious Disease HospitalXi'an 610113ShaanxiChina Department of Infectious Disease Yulin Chinese Medicine HospitalYulin 719000ShaanxiChina President's Office The First Hospital of QiqiharQiqihar 161005HeilongjiangChina Department of Traditional Chinese Medicine Shangluo Central HospitalShangluo 726000ShaanxiChina Department of Traditional Chinese Medicine The People's Hospital of QitaiheQitaihe 154603HeilongjiangChina Department of Scientific Research Xianyang Central HospitalXianyang 712000ShaanxiChina Department of traditional Chinese medicine The First Affiliated Hospital of Anhui University of Traditional Chinese MedicineHefei 230012AnhuiChina Department of Infectious Disease Heping Hospital Affiliated to Changzhi Medical CollegeChangzhi 046000ShanxiChina Department of Traditional Chinese Medicine Langfang Hospital of Chinese MedicineLangfang 065000HeibeiChina Department of Traditional Chinese Medicine Xingtai Hospital of Chinese MedicineXingtai 054001HeibeiChina Department of Traditional Chinese Medicine The People's Hospital of Guangxi Zhuang Autonomous RegionNanning 168600GuangxiChina Department of Traditional Chinese Medicine The First People'sHospital of FangchenggangFangchenggang 538001GuangxiChina Department of Traditional Chinese Medicine Mianyang Hospital of Traditional Chinese MedicineMianyang 621000SichuanChina Department of Traditional Chinese Medicine Liuzhou People's HospitalLiuzhou 545006GansuChina Department of Traditional Chinese Medici

Objective Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains *** A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients’ medical records. Multivariable logistic regression models were used to estimate the odds ratio(OR) and 95% confidence interval(95% CI) of the associations between comorbidities(cardiometabolic or non-cardiometabolic diseases), clinical severity, and treatment outcomes of *** Overall, 158(13.6%) patients were diagnosed with severe illness and 32(2.7%) had unfavorable outcomes. Hypertension(2.87, 1.30–6.32), type 2 diabetes(T2 DM)(3.57, 2.32–5.49),cardiovascular disease(CVD)(3.78, 1.81–7.89), fatty liver disease(7.53, 1.96–28.96), hyperlipidemia(2.15, 1.26–3.67), other lung diseases(6.00, 3.01–11.96), and electrolyte imbalance(10.40, 3.00–26.10)were independently linked to increased odds of being severely ill. T2 DM(6.07, 2.89–12.75), CVD(8.47,6.03–11.89), and electrolyte imbalance(19.44, 11.47–32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission(5.46,3.25–9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes(6.58, 1.46–29.64) within two *** Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.

关键词： Comorbidities COVID-19 Severity Gender Age Treatment outcome

Chinese expert consensus on the management of hypertension in the very elderly

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Journal of Geriatric Cardiology 2016年第12期13卷 945-953页

作者： Jing li yi-Xin hu Wen WANG Ning-Yuan fanG Xin-Zheng LU lin PI Mei-lin liU Wei-Min li Yan-fang li Peng QU Qi huA qing he Hai-ying WU Yuan-ming ZHANG Xiao-Ping chen Lu-Yuan chen li fan Xing-Sheng zhao Zhi-ming Zhu yi-Nong JIANG yi-fang GUO hong YUAN Ping-Jin GAO Xin-Juan XU Jun CAI liang-Di XIE Xuan Wu Hospital Capital Medical University Beijing China Chinese PLA General Hospital Beijing China Chinese Academy of Medical Science Fuwai Hospital Beijing China Renji Hospital Medical College of Shanghai Jiao Tong University ShanghaL China Jiang Su Province People's Hospital Jiangsu China Beijing chui yang liu Hospital Beijing China Peking University First Hospital Beijing China First Affiliated Hospital of Harbin Medical University Heilongjiang China Beijing An Zhen Hospital Capital Medical University Beijing China The Second Affiliated Hospital of Dalian Medical University Liaoning China Beijing Hospital Beijing China The First Hospital of Xinjiang Medical University Xinjiang Uygur Autonomous Region China West China Hospital Sichuan University Sichuan China The People's Hospital of Guangdong Province Guangdong China Inner Mongolia Autonomous Region People's Hospital Inner Mongolia Autonomous Region China Daping Hospital the Third Military Medical University Chongqing China The First Affiliated Hospital of Dalian Medical University Liaoning China hebei Province People's Hospital hebei China Xiangya Third Hospital Central South University Hunan China Shanghai Hypertension Research Institute Shanghai China The First Hospital of Fujian Medical University Fujian China

Population aging has become a major challenge for the healthcare in China. More than 23 million Chinese are cur- rently ≥ 80 years, with an annual increase of 5%. The Chi- nese population of 80 years or older is expe... 详细信息

关键词： Consensus Geriatric Hypertension Octogenarians

The first data release(DR1) of the LAMOST regular survey

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Research in Astronomy and Astrophysics 2015年第8期15卷 1095-1124页

作者： A-li Luo Yong-heng zhao Gang zhao li-Cai Deng Xiao-Wei liu yi-Peng Jing Gang Wang Hao-Tong Zhang Jian-Rong Shi Xiang-Qun Cui Yao-Quan chu Guo-Ping li Zhong-Rui Bai Yue Wu Yan Cai Shu-Yun Cao Zi-huang Cao Jeffrey L.Carlin Hai-Yuan chen Jian-Jun chen Kun-Xin chen li chen Xue-Lei chen Xiao-Yan chen ying chen Norbert Christlieb Jia-Ru chu chen-Zhou Cui yi-Qiao Dong Bing Du Dong-Wei fan Lei Feng Jian-Ning Fu Peng Gao Xue-Fei Gong Bo-Zhong Gu Yan-Xin Guo Zhan-Wen Han Bo-liang he Jin-liang Hou Yong-hui Hou Wen Hou hong-Zhuan hu Ning-Sheng hu Zhong-Wen hu Zhi-ying huo Lei Jia fang-hua Jiang Xiang Jiang Zhi-Bo Jiang Ge Jin Xiao Kong Xu Kong Ya-Juan Lei Ai-hua li Chang-hua li Guang-Wei li Hai-Ning li Jian li Qi li Shuang li Sha-Sha li Xin-nan li Yan li yin-Bi li Ye-Ping li Yuan liang Chien-cheng lin Chao liu Gen-Rong liu Guan-Qun liu Zhi-Gang liu Wen-Zhi Lu Yu Luo yin-Dun Mao heidi Newberg Ji-Jun Ni zhao-Xiang Qi Yong-Jun Qi Shi-yin Shen huo-ming Shi Jing Song yi-Han Song Ding-Qiang Su hong-Jun Su Zheng-hong Tang qing-Sheng Tao Yuan Tian Dan Wang Da-Qi Wang Feng-Fei Wang Guo-Min Wang Hai Wang hong-Chi Wang Jian Wang Jia-Ning Wang Jian-ling Wang Jian-Ping Wang Jun-Xian Wang Lei Wang Meng-Xin Wang Shou-Guan Wang Shu-qing Wang Xia Wang Ya-nan Wang You Wang Yue-Fei Wang You-Fen Wang Peng Wei ming-Zhi Wei hong Wu Ke-Fei Wu Xue-Bing Wu Yu-Zhong Wu Xiao-Zheng Xing ling-Zhe Xu Xin-Qi Xu Yan Xu Tai-Sheng Yan De-hua yang Hai-Feng yang hui-Qin yang ming yang Zheng-Qiu Yao Yong Yu hui Yuan Hai-Bo Yuan Hai-Long Yuan Wei-Min Yuan Chao Zhai En-Peng Zhang hua-Wei Zhang Jian-nan Zhang li-Pin Zhang Wei Zhang Yong Zhang Yan-Xia Zhang Zheng-Chao Zhang ming zhao fang Zhou Xu Zhou Jie Zhu Yong-Tian Zhu Si-cheng Zou fang Zuo national Astronomical Observatories Chinese Academy of Sciences Department of Astronomy Peking University Shanghai Astronomical Observatory Chinese Academy of Sciences nanjing Institute of Astronomical Optics & Technology National Astronomical ObservatoriesChinese Academy of Sciences University of Science and Technology of China Department of Physics Applied Physics and AstronomyRensselaer Polytechnic InstituteTroyNY 12180USA Department of Physics and Astronomy Earlham CollegeRichmondIN 47374USA Universitt heidelberg Zentrum für AstronomieLandessternwarteKnigstuhl 1269117 HeidelbergGermany Department of Astronomy Beijing Normal University Yunnan Observatories Chinese Academy of Sciences Purple Mountain Observatory Chinese Academy of Sciences

The Large sky Area Multi-Object Fiber Spectroscopic Telescope（LAMOST） general survey is a spectroscopic survey that will eventually cover approximately half of the celestial sphere and collect 10 million spectra of stars, galaxies and QSOs. Objects in both the pilot survey and the first year regular survey are included in the LAMOST DR1. The pilot survey started in October 2011 and ended in June 2012, and the data have been released to the public as the LAMOST Pilot Data Release in August 2012. The regular survey started in September 2012, and completed its first year of operation in June 2013. The LAMOST DR1 includes a total of 1202 plates containing 2 955 336 spectra, of which 1 790 879 spectra have observed signalto-noise ratio（SNR） ≥ 10. All data with SNR ≥ 2 are formally released as LAMOST DR1 under the LAMOST data policy. This data release contains a total of 2 204 696 spectra, of which 1 944 329 are stellar spectra, 12 082 are galaxy spectra and 5017 are quasars. The DR1 not only includes spectra, but also three stellar catalogs with measured parameters： late A,FGK-type stars with high quality spectra（1 061 918 entries）, A-type stars（100 073 entries）, and M-type stars（121 522 entries）. This paper introduces the survey design, the observational and instrumental limitations, data reduction and analysis, and some caveats. A description of the FITS structure of spectral files and parameter catalogs is also provided.

关键词： techniques: spectroscopic survey—data release—catalog

Data release of the LAMOST pilot survey

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Research in Astronomy and Astrophysics 2012年第9期12卷 1243-1246页

作者： A-li Luo Hao-Tong Zhang Yong-heng zhao Gang zhao Xiang-Qun Cui Guo-Ping li Yao-Quan chu Jian-Rong Shi Gang Wang Jian-nan Zhang Zhong-Rui Bai Xiao-Yan chen Feng-Fei Wang Yan-Xin Guo Jian-Jun chen Bing Du Xiao Kong Ya-Juan Lei yin-Bi li yi-Han Song Yue Wu Yan-Xia Zhang Xin-lin Zhou fang Zuo Peng Du lin he Wen Hou yi-Qiao Dong Jian li Guang-Wei li Shuang li Jing Song Yuan Tian Meng-Xin Wang Yong-hui Hou Zhi-ying huo hong-Zhuan hu Ning-Sheng hu Zhong-Wen hu Lei Jia fang-hua Jiang Xiang Jiang Zi-Bo Jiang Ge Jin Ai-hua li Qi li yin-Dun Mao Zheng-hong Tang qing-Sheng Tao liang-Ping Tu Da-qing Wang Dan Wang Jian-Ping Wang Lei Wang Shou-Guan Wang Shu-qing Wang Ya-nan Wang You Wang Yue-Fei Wang ming-Zhi Wei Xiang-Xiang Xue Xiao-Zheng Xing ling-Zhe Xu Xin-Qi Xu Yan Xu De-hua yang Shi-Hai yang Zheng-Qiu Yao Yong Yu hui Yuan Chao Zhai En-Peng Zhang Jing Zhang li-Ping Zhang WeiZhang Yong Zhang Zhen-Chao Zhang ming zhao fang Zhou Yong-Tian Zhu Jie Zhu Si-cheng Zou national Astronomical Observatories Chinese Academy of Sciences Beijing 100012 China lal @ lamost o rg nanjing Institute of Astronomical Optics and Technology National Astronomical ObservatoriesChinese Academy of Sciences Nanjing 210042 China University of Science and Technologyof China Hefei 230026 China Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai 200030 China Institute of Architecture Design and Research Chinese Academy of Sciences Beijing 100190China

This paper describes the data release of the LAMOST pilot survey, which includes data reduction, calibration, spectral analysis, data products and data access. The accuracy of the released data and the information about the FITS headers of spectra are also introduced. The released data set includes 319 000 spectra and a catalog of these objects.

关键词： techniques: spectroscopic survey — data reduction — data release

CEPC Technical Design Report

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Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia hua Cai Wenyong Cai Wujun Cai yijian Cai yizhou Cai Yuchen Cai Haiying Cai huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti yimin Che Yuzhi Che Bin chen Danping chen Fuqing chen Fusan chen Gang chen Guoming chen hua-Xing chen huirun chen Jinhui chen Ji-Yuan chen Kai chen Mali chen mingjun chen mingshui chen Ning chen Shanhong chen Shanzhen chen Shao-Long chen Shaomin chen Shiqiang chen Tianlu chen Wei chen Xiang chen Xiaoyu chen Xin chen Xun chen Xurong chen Ye chen ying chen Yukai chen Zelin chen Zilin chen Gang chen Boping chen chunhui chen Hok chuen cheng huajie cheng Shan cheng Tongguang cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho ming-chung chu Xiaotong chu Ziliang chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui zhaoyuan Cui Brunella D'Anzi ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang University HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China University of Geosciences Beijing China University of Geosciences WuhanHubei China University of Mining and Technology XuzhouJiangsu China West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing chulalongkorn University Bangkok City University of hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhu&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China University Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical Design Report(TDR)follows the Preliminary Conceptual Design Report(Pre-CDR,2015)and the Conceptual Design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

三聚氰胺污染奶粉相关泌尿系结石危险因素的多中心巢式病例-对照研究

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北京大学学报（医学版） 2010年第6期42卷 690-696页

作者：管娜姚晨黄松明胡宝金张东风方琪纬范青锋徐国兵朱赛楠张爱华刘洪刘玲张格妙陶立源常艳美刘晓宇艾乙赵一鸣丁洁北京大学第一医院儿科北京100034 北京大学第一医院医学统计室南京市儿童医院肾脏科江西省儿童医院肾脏科河北省儿童医院肾脏科山西省儿童医院肾脏科北京大学第一医院检验科北京大学第三医院临床流行病学研究中心北京大学第三医院儿科

目的:通过多中心大样本资料验证和探讨三聚氰胺相关婴幼儿泌尿系结石发生的危险因素。方法:对来自5省市6家医院年龄36个月及以下参加泌尿系结石筛查的婴幼儿进行了巢式病例-对照研究,根据结石病例数按1∶1的比例从符合条件的对照组人群... 详细信息

目的:通过多中心大样本资料验证和探讨三聚氰胺相关婴幼儿泌尿系结石发生的危险因素。方法:对来自5省市6家医院年龄36个月及以下参加泌尿系结石筛查的婴幼儿进行了巢式病例-对照研究,根据结石病例数按1∶1的比例从符合条件的对照组人群中随机抽取对照组。对泌尿系结石的危险因素进行了单因素分析和多因素Logistic分析,以OR为主要指标进行评价。中心4的对照组缺乏呕吐、腹泻和发热信息,分析这部分信息时删除了中心4的数据。结果:病例组1329例,对照组1317例,其中男1568例,女1078例,平均年龄18.4个月。来自6个中心的数据分析证实服用高三聚氰胺含量奶粉的婴幼儿患结石的OR为6.26(P<0.01),早产的OR为2.03(P<0.01)。随年龄增长结石发生的风险下降,0.5岁以下、0.5～1.0岁、1.0～1.5岁、1.5～2.0岁、2.0～2.4岁婴幼儿发生结石的OR分别是2.78(P<0.01)、2.61(P<0.01)、2.09(P<0.01)、1.57(P<0.01)和1.44(P<0.05)。男性发生结石的OR为1.19(P<0.05),人工喂养儿童发生结石的OR为1.94(P<0.01)。删除中心4的数据后多因素分析显示,1岁以下婴幼儿发生结石的OR为2.24(P<0.01),1～2岁婴幼儿发生结石的OR为1.31(P<0.05)。人工喂养儿童发生结石的OR为1.67(P<0.01)。诊断前3天内有呕吐、腹泻、发热中两个及以上症状的婴幼儿发生结石的OR为15.21(P<0.05)。结论:多中心研究再次证实食用高三聚氰胺含量奶粉和早产是婴幼儿泌尿系结石的危险因素,人工喂养的婴幼儿易发生泌尿系结石,结石发生风险随年龄增高而下降,有呕吐、腹泻、发热症状的婴幼儿结石发生风险高,男孩发生结石的风险高于女孩。

关键词：三聚氰胺尿石症多中心研究危险因素病例对照研究

Small P values may not yield robust findings:an example using REST-meta-PD

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Science Bulletin 2021年第21期66卷 2148-2152,M0003页

作者： Xi-Ze Jia na zhao Hao-ming Dong Jia-Wei Sun Marek Barton Roxana Burciu Nicolas Carrière Antonio Cerasa Bo-Yu chen Jun chen Stephen Coombes Luc Defebvre Christine Delmaire Kathy Dujardin Fabrizio Esposito Guo-Guang fan Federica Di nardo yi-Xuan Feng Brett W.Fling Saurabh Garg Moran Gilat Martin Gorges Shu-Leong Ho Fay BHorak Xiao hu Xiao-Fei hu Biao huang Pei-Yu huang Ze-Juan Jia Christina Jones Jan Kassubek Lenka Krajcovicova Ajay Kurani Jing li qing li Ai-Ping liu Bo liu hu liu Wei-Guo liu Renaud Lopes Yu-Ting Lou Wei Luo Tara Madhyastha Ni-Ni Mao Grainne McAlonan Martin J.McKeown Shirley Pang Andrea Quattrone Irena Rektorova Alessia Sarica hui-fang Shang James M.Shine Priyank Shukla Tomas Slavicek Xiao-Peng Song Gioacchino Tedeschi Alessandro Tessitore David Vaillancourt Jian Wang Jue Wang Z.Jane Wang Lu-qing Wei Xia Wu Xiao-Jun Xu Lei Yan Jing yang Wan-Qun yang nai-lin Yao De-Long Zhang Jiu-Quan Zhang Min-ming Zhang Yan-ling Zhang Cai-hong Zhou Chao-Gan Yan Xi-Nian Zuo Mark Hallett Tao Wu Yu-Feng Zang Center for Cognition and Brain Disorders the Affiliated HospitalHangzhou Normal UniversityHangzhou 310015China Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments Hangzhou 311121China national Basic Science Data Center Beijing 100190China State Key Laboratory of Cognitive Neuroscience and Learning&McGovern Institute for Brain Research Beijing Normal UniversityBeijing 100875China School of Information and Electronics Technology Jiamusi UniversityJiamusi 154007China Neuroscience Program Central European Institute of TechnologyCEITECMasaryk UniversityBrno 62500Czech Republic Department of Applied Physiology and Kinesiology University of FloridaGainesville FL 32611USA Univ.lille InsermCHU LilleU1172-LilNCog-Lille Neuroscience&CognitionLille F-59000France The Institute for Biomedical Research and Innovation National Research CouncilMangone CS 87050Italy Department of Radiology The First Affiliated Hospital of China Medical UniversityShenyang 110001China Department of Radiology Guangdong Provincial Hospital of Chinese MedicineGuangzhou 510120China Department of Medicine Surgery and DentistryScuola Medica SalernitanaUniversity of SalernoFiscianoSA 132-84084Italy Department of Advanced Medical and Surgery Sciences University of Campania“Luigi Vanvitelli”Caserta 81100Italy Eye Center of the 2nd Affiliated Hospital Medical College of Zhejiang UniversityHangzhou 310020China Zhejiang Provincial Key Lab of Ophthalmology Hangzhou 310020China Department of health and Exercise Science Colorado State UniversityFort Collins CO 80523USA Pacific Parkinson’s Research Centre University of British ColumbiaVancouver BC V6E 2M6Canada Department of Medicine(Neurology)University of British Columbia Vancouver BC V6T 1B7Canada Brain and Mind Center The University of SydneySydney NSW 2006Australia Department of Neurology Ulm UniversityUlm 89081Germany Division of Neurology Department of MedicineQueen Mary HospitalUniversity of Hong KongHong Kong 999077China Department of

Thousands of resting state functional magnetic resonance imaging(RS-f MRI)articles have been published on brain *** precise localization of abnormal brain activity,a voxel-level comparison is *** of the large number of voxels in the brain,multiple comparison correction(MCC)must be performed to reduce false positive rates,and a smaller P value(usually including either liberal or stringent MCC)is widely recommended[1].

关键词：帕金森病 precise correction

2017年中国ICU患者营养治疗实施状况横断面调查

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解放军医学杂志 2019年第5期44卷 388-393页

作者：邢娟章仲恒柯路周晶秦秉玉梁宏开陈晓梅刘文明刘忠民艾宇航王迪芬王秋卉周青山张福森钱克俭蒋东坡臧彬黎毅敏黄晓波曲彦谢颖光许东琳邹志强郑祥德刘建波郭丰梁亚风孙强高红梅刘阳常平程爱斌杨荣利么改琦孙昀王晓蓉张怡熊旭明于健孙荣青李志伟袁世荧宋云林高培阳刘海燕张朝辉吴允孚马标郭强山峰杨明施李海玲李圆菲鲁卫华王磊钱传云王智勇林建东张汝敏万鹏彭志勇龚裕强黄林喜伍国宝孙洁邓义军师东武周立新周发春石秦东郭晓东刘雪燕武卫东孟祥忠李连弟陈炜炜李树生万献尧曹志新张安古利明陈炜吴京兰周丽华张震环翁以炳封永顺杨春丽冯永健赵素民佟飞郝东韩辉付宝才巩传勇李志平胡琨琳寇秋野张晗刘洁樊楚明周新陈秀梅孙俊丽周学军宋斌孙诚赵丽芸董兴鲁张琳琳佟大为潘志国蔡常洁王东浩董英俊龚园其吴志松孟新科王平李维勤南京医科大学金陵临床医学院南京210002 无锡人民医院江苏无锡214001 北京市密云区医院北京101500 洛阳市中心医院河南洛阳471009 北京市怀柔区第一医院北京101400 陆军总医院北京100700 广东省人民医院广州510080 广东省第二中医院广州510095 北京中医医院北京100010 安徽省立医院西院区合肥230001 沈阳市第一人民医院沈阳110041 南部战区总医院广州510050 湖北省人民医院武汉430060 中山大学附属第一医院广州510080 天津市肿瘤医院天津300060 山西省肿瘤医院太原030000 南昌大学第二附属医院南昌330006 北京中医药大学东方医院北京100029 深圳第二人民医院广东深圳100730 成都市第五人民医院成都611130 泰安市中心医院山东泰安271000 南昌大学第一附属医院南昌330006 陆军军医大学大坪医院重庆400042 中国医科大学附属第二医院沈阳110004 广州医科大学附属第一医院广州510120 四川省人民医院成都610072 青岛市立医院青岛266071 济宁市第一人民医院山东济宁272000 浙江大学医学院附属邵逸夫医院杭州310016 广州市第一人民医院广州510000 福建医科大学附属协和医院福州350001 达州市中心医院四川达州635000 内蒙古自治区人民医院呼和浩特010017 烟台毓璜顶医院山东烟台264000 天津市人民医院天津300000 天津市第一中心医院天津300192 唐山市工人医院河北唐山063000 南方医科大学珠江医院广州510515 华北理工大学附属医院河北唐山063210 河南省人民医院郑州450003 大连市中心医院辽宁大连116033 北京大学第三医院北京100083 安徽医科大学第二附属医院合肥230601 温州医科大学附属第一医院浙江温州325000 陕西省人民医院西安710068 广州医科大学附属第二医院广州510120 大连医科大学附属第二医院辽宁大连116011 郑州大学第一附属医院郑州450052 昆明市第一人民医院昆明650011 华中科技大学同济医学院附属协和医院武汉430030 中山市人民医院广东中山528403 新疆医科大学第一附属医院乌鲁木齐830054 成都中医药大学附属医院成都610075 安徽医科大学第一附属医院合肥230032 宜昌市中心人民医院湖北宜昌443003 苏州市立医院东区江苏苏州215008 济宁医学院附属医院山东济宁272000 苏州大学附属第一人民医院江苏苏州215006 青岛大学医学院附属医院东院区山东青岛266071 中南大学湘雅三医院长沙410013 海军第971医院山东青岛266073 山东大学齐鲁医院济南250012 长沙市中心医院长沙410000 皖南医学院弋矶山医院安徽芜湖241002 山西医科大学第一医院太原030001 昆明医科大学第一附属医院昆明650032 河北医科大学第三医院石家庄050017 福建医科大学附属第一医院福州350004 淄博市中心医院山东淄博100085 宜昌市第一人民医院湖北宜昌443003 武汉大学中南医院武汉430071 温州医科大学附属第二医院浙江温州325035 常州市第二人民医院江苏常州213003 汕头大学医学院第一附属医院广东汕头515041 中南大学湘雅二医院长沙410013 云南省第二人民医院昆明650021 盐城市第一人民医院江苏盐城224006 山西省人民医院太原030012 佛山市第一人民医院广东佛山528000 重庆医科大学附属第一医院重庆400016 西安交通大学第一附属医院西安710061 解放军总医院第三医学中心北京100039 深圳市人民医院广东深圳518001 吉林大学第一医院长春130031 山西医学科学院山西大医院太原030032 解放军第254医院天津300142 青岛大学附属医院山东青岛266003 临海市第一人民医院浙江台州317000 华中科技大学同济医学院附属同济医院武汉430030 大连医科大学附属第一医院辽宁大连116011 北京朝阳医院京西院区北京100043 重庆医科大学附属第二医院重庆400016 玉溪市人民医院云南玉溪653405 首都医科大学世纪坛医院北京100036 中南大学湘雅医院长沙410013 深圳市南山人民医院广东深圳518067 内蒙古医科大学附属医院呼和浩特010050 南京明基医院南京210019 首都医科大学附属北京潞河医院北京101149 京煤集团总医院北京102300 江西省人民医院南昌330006 暨南大学附属第一医院广

目的了解国内ICU收治患者的营养治疗实施状况。方法对国内116家医院的118个ICU内的患者进行营养治疗实施状况的横断面调查。以2017年4月26日0时所有在ICU内治疗的患者为调查对象,收集患者基本信息、2017年4月25日(即调查日)的营养实施... 详细信息

目的了解国内ICU收治患者的营养治疗实施状况。方法对国内116家医院的118个ICU内的患者进行营养治疗实施状况的横断面调查。以2017年4月26日0时所有在ICU内治疗的患者为调查对象,收集患者基本信息、2017年4月25日(即调查日)的营养实施和胃肠道耐受情况,以及患者的28 d临床转归情况。结果调查共收集病例1953例,女631例(32.4%),男1306例(66.9%),缺失16例(0.7%);年龄(64.1±19.3)岁(1950例)。患者GCS、SOFA和APACheⅡ评分分别为(10.76±4.35)分(1749例)、(5.65±3.52)分(1783例)、(17.14±7.31)分(1792例)。28 d临床转归存活1483例(75.9%),死亡312例(16.0%),失访+缺失158例(8.1%)。除身高和体重(P=0.000)外,男性与女性患者在年龄、病情严重程度及28 d临床转归等方面差异均无统计学意义。1953例患者中,胃肠功能评估为正常或轻度损害占73.7%(1440例),中-重度损害占10.8%(210例),衰竭占1.7%(33例),13.2%(258例)的患者未做评估。截至调查日,69.4%(1356例)的患者已启动肠内营养(EN),36.4%(711例)的患者已启动肠外营养(PN)。调查日有营养摄入的患者1720例(88.1%)。1953例患者中明确有恶心、呕吐反流、误吸、腹痛、腹胀、腹泻(大便次数≥3次/d且量≥500 ml/d)等胃肠道不耐受表现的分别占总人数的4.8%(93例)、5.4%(105例)、0.9%(17例)、8.7%(170例)、27.5%(538例)和4.3%(84例)。在1270例使用EN的病例中,明确存在恶心、呕吐反流、误吸、腹痛、腹胀、腹泻等不耐受症状的分别占3.2%(40例)、4.3%(54例)、0.8%(10例)、4.4%(56例)、26.9%(341例)和5.4%(69例)。入ICU后24 h内开始EN治疗的患者占22.4%(437/1953),48 h内开始的占38.6%(754/1953),72 h内开始的占46.6%(911/1953)。患者入ICU后3 d总热卡(EN+PN非蛋白热卡)达标率为12.9%(78/607),7 d总热卡达标率为18.7%(189/1010),14 d总热卡的达标率为23.0%(305/1325)。入ICU后3、7、14 dEN达标率分别为9.9%(60/607)、15.0%(151/1010)和18.6%(246/1325)。结论目前我国ICU内的绝大多数患者均接受了营养治疗,其中EN的使用率明显高于PN;但EN的开始时间和达标情况仍不理想,且实施营养治疗时未能体现个体化差异,营养治疗的细节仍需要提高。

关键词：横断面研究肠内营养重症监护病房胃肠道耐受性营养达标率

2015-2021年CHINET临床分离肠球菌属细菌耐药性变迁

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中国感染与化疗杂志 2024年第3期24卷 300-308页

作者：陈娜季萍杨洋胡付品朱德妹徐英春张小江谢轶康梅王传清付盼徐元宏黄颖孙自镛陈中举倪语星孙景勇褚云卓田素飞胡志东李金俞云松林洁单斌杜艳郭素芳魏莲花邹凤梅张泓王春胡云建艾效曼卓超苏丹虹郭大文赵金英喻华黄湘宁刘文恩李艳明金炎邵春红徐雪松鄢超王山梅楚亚菲张利侠马娟周树平周艳朱镭孟晋华董方吕志勇胡芳芳沈瀚周万青贾伟李刚吴劲松卢月梅李继红段金菊康建邦马晓波郑燕萍郭如意朱焱陈运生孟青王世富胡雪飞沈继录汪瑞忠房华俞碧霞赵勇龚萍温开镇张贻荣刘江山廖龙凤顾洪芹姜琳贺雯薛顺虹冯佼岳春雷新疆医科大学第一附属医院医学检验中心新疆830000 复旦大学附属华山医院抗生素研究所北京协和医院四川大学华西医院复旦大学附属儿科医院安徽医科大学第一附属医院华中科技大学同济医学院附属同济医院上海交通大学医学院附属瑞金医院中国医科大学附属第一医院天津医科大学总医院浙江大学医学院附属邵逸夫医院昆明医科大学第一附属医院内蒙古医科大学附属医院甘肃省人民医院上海交通大学医学院附属儿童医院北京医院广州医科大学附属第一医院哈尔滨医科大学附属第一医院四川省人民医院中南大学湘雅医院山东省立医院吉林大学中日联谊医院河南省人民医院陕西省人民医院江西省儿童医院山西省儿童医院首都医科大学附属北京儿童医院贵州省人民医院南京大学医学院附属鼓楼医院宁夏医科大学总医院深圳市人民医院河北医科大学第二医院山西医科大学第二医院厦门大学附属第一医院福建省泉州市第一医院深圳市儿童医院山东大学齐鲁儿童医院南昌大学第一附属医院安徽医科大学第四附属医院上海市浦东新区人民医院浙江省宁波市镇海龙赛医院湖北省秭归县人民医院福建省晋江市医院甘肃省金昌市中西医结合医院江西省赣县区人民医院山东省广饶县人民医院河南省辉县市人民医院辽宁省营口市经济技术开发区中心医院青海省互助县人民医院四川省邻水县人民医院吉林省九台区人民医院

目的了解2015-2021年中国主要地区临床分离肠球菌属细菌的分布及耐药性变迁。方法按CHINET统一技术方案,采用自动化仪器法、纸片扩散法或E试验条法对CHINET成员单位临床分离的肠球菌属细菌进行药物敏感性试验,结果参照2021年CLSI标准判... 详细信息

目的了解2015-2021年中国主要地区临床分离肠球菌属细菌的分布及耐药性变迁。方法按CHINET统一技术方案,采用自动化仪器法、纸片扩散法或E试验条法对CHINET成员单位临床分离的肠球菌属细菌进行药物敏感性试验,结果参照2021年CLSI标准判读,采用WHONET 5.6软件进行统计分析。结果7年间共分离肠球菌属细菌124565株,主要分离菌仍为屎肠球菌(50.7%)、粪肠球菌(41.5%)。标本来源主要为尿道标本(46.9%±2.6%),科室来源主要分离自内科、外科、ICU。屎肠球菌和粪肠球菌对万古霉素、替考拉宁、利奈唑胺的耐药率均保持在较低水平(≤3.6%)。万古霉素耐药的粪肠球菌和屎肠球菌检出率为0.1%和1.3%,利奈唑胺耐药的粪肠球菌从2015年的0.7%上升至2021年的3.4%、屎肠球菌的检出率为0.3%。结论肠球菌属临床分离菌对万古霉素、替考拉宁、利奈唑胺保持较好的体外敏感性,细菌耐药率低。但利奈唑胺耐药的粪肠球菌检出率有逐年增高的趋势,应加强细菌耐药监测,及时发现耐药菌的发生和遏制耐药菌播散。

关键词：肠球菌属细菌耐药性监测耐药性变迁