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| 1 | 2018 Chinese Pediatric Cardiology Society(CPCS) guideline for diagnosis and treatment of syncope in children and adolescents显示文摘Syncope belongs to the transient loss of consciousness(TLOC), characterized by a rapid onset, short duration, and spontaneous complete recovery. It is common in children and adolescents, accounting for 1% to 2% of emergency department visits.Recurrent syncope can seriously affect children's physical and mental health, learning ability and quality of life and sometimes cardiac syncope even poses a risk of sudden death. The present guideline for the diagnosis and treatment of syncope in children and adolescents was developed for guiding a better clinical management of pediatric syncope. Based on the globally recent development and the evidence-based data in China, 2018 Chinese Pediatric Cardiology Society(CPCS) guideline for diagnosis and treatment of syncope in children and adolescents was jointly prepared by the Pediatric Cardiology Society, Chinese Pediatric Society, Chinese Medical Association(CMA)/Committee on Pediatric Syncope, Pediatricians Branch, Chinese Medical Doctor Association(CMDA)/Committee on Pediatric Cardiology, Chinese College of Cardiovascular Physicians, Chinese Medical Doctor Association(CMDA)/Pediatric Cardiology Society, Beijing Pediatric Society, Beijing Medical Association(BMA). The present guideline includes the underlying diseases of syncope in children and adolescents, the diagnostic procedures, methodology and clinical significance of standing test and headup tilt test, the clinical diagnosis vasovagal syncope, postural orthostatic tachycardia syndrome, orthostatic hypotension and orthostatic hypertension, and the treatment of syncope as well as follow-up. | Cheng Wang Yaqi Li Ying Liao Hong Tian Min Huang Xiangyu Dong Lin Shi Jinghui Sun Hongfang Jin Junbao Du Jindou An Jie Chen Mingwu Chen Qi Chen Sun Chen Yonghong Chen Zhi Chen Adolphus Kai-tung Chau Junbao Du Zhongdong Du Junkai Duan Hongyu Duan Xiangyu Dong Lin Feng Lijun Fu Fangqi Gong Yonghao Gui Ling Han Zhenhui Han Bing He Zhixu He Xiufen Hu Yimin Hua Guoying Huang Min Huang Ping Huang Yujuan Huang Hongfang Jin Mei Jin Bo Li Fen Li Tao Li Xiaohui Li Xiaoyan Liu Yan Li Haitao Lv Tiewei Lv Zipu Li Luyi Ma Silin Pan Yusheng Pang Hua Peng Yuming Qin Jie Shen Lin Shi Kun Sun Jinghui Sun Hong Tian Jie Tian Cheng Wang Hong Wang Lei Wang Jinju Wang Wendi Wang Yuli Wang Rongzhou Wu Tianhe Xia Yanyan Xiao Chunhong Xie Yanlin Xing Zhenyu Xiong Baoyuan Xu Yi Xu Hui Yan Shiwei Yang Qijian Yi Xia Yu Xianyi Yu Yue Yuan Hongyan Zhang Huili Zhang Li Zhang Qingyou Zhang Xi Zhang Yanmin Zhang Zhiwei Zhang Cuifen Zhao Bin Zhou Hua Zhu | 2018 | Science Bulletin2018，63，23： | 54 |
| 2 | Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China显示文摘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 unclear.Methods 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 COVID-19.Results 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 weeks.Conclusion 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. | 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 | 2020 | Biomedical and Environmental Sciences2020，33，12： | 8 |
| 3 | Inverted U-Shaped Associations between Glycemic Indices and Serum Uric Acid Levels in the General Chinese Population:Findings from the China Cardiometabolic Disease and Cancer Cohort(4C)Study显示文摘Objective The relationship between serum uric acid(SUA)levels and glycemic indices,including plasma glucose(FPG),2-hour postload glucose(2 h-PG),and glycated hemoglobin(HbA1 c),remains inconclusive.We aimed to explore the associations between glycemic indices and SUA levels in the general Chinese population.Methods The current study was a cross-sectional analysis using the first follow-up survey data from The China Cardiometabolic Disease and Cancer Cohort Study.A total of 105,922 community-dwelling adults aged≥40 years underwent the oral glucose tolerance test and uric acid assessment.The nonlinear relationships between glycemic indices and SUA levels were explored using generalized additive models.Results A total of 30,941 men and 62,361 women were eligible for the current analysis.Generalized additive models verified the inverted U-shaped association between glycemic indices and SUA levels,but with different inflection points in men and women.The thresholds for FPG,2 h-PG,and HbA1 c for men and women were 6.5/8.0 mmol/L,11.0/14.0 mmol/L,and 6.1/6.5,respectively(SUA levels increased with increasing glycemic indices before the inflection points and then eventually decreased with further increases in the glycemic indices).Conclusion An inverted U-shaped association was observed between major glycemic indices and uric acid levels in both sexes,while the inflection points were reached earlier in men than in women. | ZHU Yuan Yue ZHENG Rui Zhi WANG Gui Xia CHEN Li SHI Li Xin SU Qing XU Min XU Yu CHEN Yu Hong YU Xue Feng YAN Li WANG Tian Ge ZHAO Zhi Yun QIN Gui Jun WAN Qin CHEN Gang GAO Zheng Nan SHEN Fei Xia LUO Zuo Jie QIN Ying Fen HUO Ya Nan LI Qiang YE Zhen ZHANG Yin Fei LIU Chao WANG You Min WU Sheng Li YANG Tao DENG Hua Cong ZHAO Jia Jun CHEN Lu Lu MU Yi Ming TANG Xu Lei HU Ru Ying WANG Wei Qing NING Guang LI Mian LU Jie Li BI Yu Fang | 2021 | Biomedical and Environmental Sciences2021，34，1： | 2 |
| 4 | The correlation between monocyte chemoattractant protein-1 and the arthritis of systemic lupus erythematosus among Chinese显示文摘 | Dong Qing Ye Yi Song Hu Xiang Pei Li Shi Gui Yang Jia Hu Hao Fen Huang Xue Jun Zhang | 2005 | Archives of Dermatological Research2005，，8： | 1 |
| 5 | Large area^(3)He tube array detector with modular design for multi‑physics instrument at CSNS显示文摘The multi-physics instrument(MPI)is the first user cooperative instrument at the China Spallation Neutron Source(CSNS).It was designed to explore the structures of complex materials at multiple scales based on the neutron total scattering technique.This imposes the requirements for the detector,including a high detection efficiency to reduce the measurement time and a large solid angle coverage to cover a wide range of momentum transfers.To satisfy these demands,a large-area array of 3He-filled linear position-sensitive detectors(LPSDs)was constructed,each with a diameter of 1 inch and pressure of 20 atm.It uses an orbicular layout of the detector and an eight-pack module design for the arrangement of 3He LPSDs,covering a range of scattering angles from 3°to 170°with a total detector area of approximately 7 m2.The detector works in air,which is separated from the vacuum environment to facilitate installation and maintenance.The characteristics of the MPI detector were investigated through Monte Carlo(MC)simulations using Geant4 and experimental measurements.The results suggest that the detectors are highly efficient in the wavelength range of the MPI,and an efficiency over 25%is achievable for above 0.1 A neutrons.A minimal position resolution of 6.4 mm full width at half maximum(FWHM)along the tube length was achieved at a working voltage of 2200 V,and a deviation below 2 mm between the real and measured positions was attained in the beam experiment.The detector module exhibited good consistency and an excellent counting rate capacity of up to 80 kHz,which satisfied the requirements of experiments with a high event rate.Observations of its operation over the past year have shown that the detector works steadily in sample experiments,which allows the MPI to serve the user program successfully. | Lin Zhu Jian‑Rong Zhou Yuan‑Guang Xia Liang Xiao Hong Luo Xiao‑Juan Zhou Wen‑Qin Yang Bei‑Ju Guan Xing‑Fen Jiang Yan‑Feng Wang Hong Xu Hai‑Yun Teng Li‑Xin Zeng Jia‑Jie Li Lei Hu Ke Zhou Yong‑Xiang Qiu Pei‑Xun Shen Jun Xu Li‑Jiang Liao Xiao‑Zhuang Wang Gui‑An Yang Huai‑Chan Chen Ju‑Ping Xu Zhi‑Duo Li Song‑Lin Wang Jian Zhuang Yu‑Bin Zhao Jun‑Rong Zhang Wen Yin Zhi‑Jia Sun Yuan‑Bo Chen | 2023 | Nuclear Science and Techniques2023，34，1： | 0 |
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