1.Real-world efficacy and safety of azvudine in hospitalized older patients with COVID-19 during the omicron wave in China: A retrospective cohort study.
Yuanchao ZHU ; Fei ZHAO ; Yubing ZHU ; Xingang LI ; Deshi DONG ; Bolin ZHU ; Jianchun LI ; Xin HU ; Zinan ZHAO ; Wenfeng XU ; Yang JV ; Dandan WANG ; Yingming ZHENG ; Yiwen DONG ; Lu LI ; Shilei YANG ; Zhiyuan TENG ; Ling LU ; Jingwei ZHU ; Linzhe DU ; Yunxin LIU ; Lechuan JIA ; Qiujv ZHANG ; Hui MA ; Ana ZHAO ; Hongliu JIANG ; Xin XU ; Jinli WANG ; Xuping QIAN ; Wei ZHANG ; Tingting ZHENG ; Chunxia YANG ; Xuguang CHEN ; Kun LIU ; Huanhuan JIANG ; Dongxiang QU ; Jia SONG ; Hua CHENG ; Wenfang SUN ; Hanqiu ZHAN ; Xiao LI ; Yafeng WANG ; Aixia WANG ; Li LIU ; Lihua YANG ; Nan ZHANG ; Shumin CHEN ; Jingjing MA ; Wei LIU ; Xiaoxiang DU ; Meiqin ZHENG ; Liyan WAN ; Guangqing DU ; Hangmei LIU ; Pengfei JIN
Acta Pharmaceutica Sinica B 2025;15(1):123-132
Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T NANC), time to symptom improvement (T SI), and time of hospital stay (T HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.
2.The value of deep learning image reconstruction algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT
Li SHEN ; Taiping HE ; Qian TIAN ; Nan YU ; Dong HAN ; Zhanli REN ; Yongjun JIA ; Yangyang YAN
Journal of Practical Radiology 2025;41(4):664-668
Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P<0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P>0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P<0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P<0.05),and there was no significant difference in the SNR(P>0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P>0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.
3.Proposal and research idea of "traditional Chinese medicine processing chemical biology".
Peng-Peng LIU ; Qian CAI ; Ji SHI ; Nan XU ; Hui GAO ; Ke-Wu ZENG ; Tian-Zhu JIA
China Journal of Chinese Materia Medica 2025;50(3):833-839
Traditional Chinese medicine(TCM) processing is a unique and highly distinctive pharmaceutical technology in China. Utilizing modern scientific methods to elucidate the connotations of traditional processing theory and its effects is expected to facilitate the inheritance, development, innovation, and enhancement of TCM processing, and lead to more original research outcomes in the field of TCM. The breakthrough in TCM processing lies in the study of its underlying principles, and analyzing these principles involves researching the transformation mechanisms of chemical components and the biological effect mechanisms of the transformed components. This paper proposed the concept of "TCM processing chemical biology"(TCMPCB) for the first time. Under the guidance of TCM theory, the active components transformed during TCM processing were used as chemical tools to study their targets and molecular regulatory mechanisms, aiming to clarify the scientific principles by which TCM processing affected biological effects in the organism. The research findings also provided new directions for discovering novel active components, new lead compounds, creating new decoction pieces, and developing new TCM drugs. This paper provided a detailed introduction to the background, definition, research content, research ideas, research methods, and prospects of TCMPCB, with the aim of offering new research perspectives for analyzing the principles of TCM processing and providing new pathways for achieving the "four new and eight transformations" in TCM processing.
Drugs, Chinese Herbal/chemistry*
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Medicine, Chinese Traditional/methods*
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Humans
;
Animals
4.The value of deep learning image reconstruction algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT
Li SHEN ; Taiping HE ; Qian TIAN ; Nan YU ; Dong HAN ; Zhanli REN ; Yongjun JIA ; Yangyang YAN
Journal of Practical Radiology 2025;41(4):664-668
Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P<0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P>0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P<0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P<0.05),and there was no significant difference in the SNR(P>0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P>0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.
5.Topic Modeling Analysis of Chinese Medicine Literature on Gastroesophageal Reflux Disease: Insights into Potential Treatment.
Jia-Nan QIAN ; Yan-Lan KANG ; You-Cheng HE ; Hong-Yi HU
Chinese journal of integrative medicine 2024;30(12):1128-1136
OBJECTIVE:
To analyze Chinese medicine (CM) prescriptions for gastroesophageal reflux disease (GERD), we model topics on GERD-related classical CM literature, providing insights into the potential treatment.
METHODS:
Clinical guidelines were used to identify symptom terms for GERD, and CM literature from the database "Imedbooks" was retrieved for related prescriptions and their corresponding sources, indications, and other information. BERTopic was applied to identify the main topics and visualize the data.
RESULTS:
A total of 36,207 entries are queried and 1,938 valid entries were acquired after manually filtering. Eight topics were identified by BERTopic, including digestion function abate, stomach flu, respiratory-related symptoms, gastric dysfunction, regurgitation and gastrointestinal dysfunction in pediatric patients, vomiting, stroke and alcohol accumulation are associated with the risk of GERD, vomiting and its causes, regurgitation, epigastric pain, and symptoms of heartburn.
CONCLUSIONS
Topic modeling provides an unbiased analysis of classical CM literature on GERD in a time-efficient and scale-efficient manner. Based on this analysis, we present a range of treatment options for relieving symptoms, including herbal remedies and non-pharmacological interventions such as acupuncture and dietary therapy.
Humans
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Gastroesophageal Reflux/drug therapy*
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Medicine, Chinese Traditional/methods*
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Drugs, Chinese Herbal/therapeutic use*
;
Models, Theoretical
6.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
7.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
8.Identification and expression analysis of AP2/ERF gene family in Artemisia argyi
Xue-xue YUE ; Chuang XIAO ; Qian-wen ZHANG ; Sai-nan PENG ; Chang-jie CHEN ; Jia ZHOU ; Jin-xin LI ; Yu-kun LI ; Yu-huan MIAO ; Da-hui LIU
Acta Pharmaceutica Sinica 2024;59(9):2634-2647
italic>Artemisia argyi is a traditional Chinese medicine in China, which is used as medicine with its leaves. The leaves of
9.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
10.Analysis of the risk factors for poor prognosis and recurrence in patients with anti-NMDAR encephalitis.
Qian WU ; Xiao Nan WANG ; Qing Lin YANG ; Lei LIU ; Yu Jing PENG ; Zhi Xin QIAO ; Jia Wei WANG
Chinese Journal of Preventive Medicine 2023;57(2):247-252
To investigate the risk factors of poor prognosis and recurrence in patients with anti-NMDAR encephalitis. A single center, observational cohort study was used to retrospectively analyze 44 patients with anti NMDAR encephalitis hospitalized in the Department of Neurology of Beijing Tong Ren Hospital from January 2014 to October 2020. The results showed that the interval from onset to immunotherapy in the poor prognosis group was significantly longer than that in the good prognosis group (t=2.045,P=0.047), and the course of disease in the poor prognosis group was significantly longer than that in the good prognosis group (t=4.127,P=0.000 2). The number of patients with clinical manifestations of dyskinesia was significantly increased (Fisher exact test: P=0.014). The patients with abnormal brain MRI in the poor prognosis group were significantly more than those in the good prognosis group (Fisher exact test: P=0.017), and the patients with slow wave>50% in the poor prognosis group were significantly more than those with slow wave <50% (Fisher exact test: P<0.001). Patients with the first onset of immunotherapy time <3 months, long course of disease, high intracranial pressure, and high cerebrospinal fluid protein are prone to relapse. Bivariate logistic regression analysis showed that patients with dyskinesia, abnormal brain MRI, and slow wave EEG more than 50% were risk factors for poor prognosis (OR values were 4.687, 4.978, and 24.500, respectively; P values were 0.018, 0.016, and 0.000, respectively). The time of first-line immunotherapy for the first onset<3 months was the risk factor for recurrence (OR 17.231, P=0.010). In conclusion, dyskinesia, abnormal brain MRI and slow wave of EEG more than 50% may be the risk factors for poor prognosis of patients. The duration of immunotherapy less than 3 months after the first onset might be the risk factor for recurrence.
Humans
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Anti-N-Methyl-D-Aspartate Receptor Encephalitis/cerebrospinal fluid*
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Retrospective Studies
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Neoplasm Recurrence, Local
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Risk Factors
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Dyskinesias

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