1.Randomized, double-blind, parallel-controlled, multicenter, equivalence clinical trial of Jiuwei Xifeng Granules(Os Draconis replaced by Ostreae Concha) for treating tic disorder in children.
Qiu-Han CAI ; Cheng-Liang ZHONG ; Si-Yuan HU ; Xin-Min LI ; Zhi-Chun XU ; Hui CHEN ; Ying HUA ; Jun-Hong WANG ; Ji-Hong TANG ; Bing-Xiang MA ; Xiu-Xia WANG ; Ai-Zhen WANG ; Meng-Qing WANG ; Wei ZHANG ; Chun WANG ; Yi-Qun TENG ; Yi-Hui SHAN ; Sheng-Xuan GUO
China Journal of Chinese Materia Medica 2025;50(6):1699-1705
Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent
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Child
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Child, Preschool
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Female
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Humans
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Male
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Double-Blind Method
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Drugs, Chinese Herbal/therapeutic use*
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Tic Disorders/drug therapy*
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Treatment Outcome
2.Expert consensus on the clinical strategies for orthodontic treatment with clear aligners.
Yan WANG ; Hu LONG ; Zhihe ZHAO ; Ding BAI ; Xianglong HAN ; Jun WANG ; Bing FANG ; Zuolin JIN ; Hong HE ; Yuxin BAI ; Weiran LI ; Min HU ; Yanheng ZHOU ; Hong AI ; Yuehua LIU ; Yang CAO ; Jun LIN ; Huang LI ; Jie GUO ; Wenli LAI
International Journal of Oral Science 2025;17(1):19-19
Clear aligner treatment is a novel technique in current orthodontic practice. Distinct from traditional fixed orthodontic appliances, clear aligners have different material features and biomechanical characteristics and treatment efficiencies, presenting new clinical challenges. Therefore, a comprehensive and systematic description of the key clinical aspects of clear aligner treatment is essential to enhance treatment efficacy and facilitate the advancement and wide adoption of this new technique. This expert consensus discusses case selection and grading of treatment difficulty, principle of clear aligner therapy, clinical procedures and potential complications, which are crucial to the clinical success of clear aligner treatment.
Humans
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Consensus
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Orthodontic Appliance Design
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Orthodontic Appliances, Removable
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Tooth Movement Techniques/methods*
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Malocclusion/therapy*
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Orthodontics, Corrective/instrumentation*
3.National clinical three-tiered surveillance and stratified precision detection report on respiratory infectious pathogens in 2024
Jingwen AI ; Jikui DENG ; Min DONG ; Xiaohong GAO ; Jiawei GENG ; Xiaoli HU ; Zhu JIN ; Hongyan LIU ; Yongzhong LI ; Xi LIU ; Yuanwang QIU ; Lihong QU ; Binhuang SUN ; Wei SONG ; Hongyu WANG ; Junping WANG ; Sen WANG ; Xiaoming XIONG ; Daokun YANG ; Liaoyun ZHANG ; Yanliang ZHANG ; Xianghong ZHOU ; Wenhong ZHANG
Chinese Journal of Infectious Diseases 2025;43(2):79-89
Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.
4.A chest CT report conclusion generation system based on mT5 large language model for residency training
Yanfei HU ; Ai WANG ; Yaping ZHANG ; Keke ZHAO ; Zhijie PAN ; Qingyao LI ; Min XU ; Xifu WANG ; Xueqian XIE
Chinese Journal of Medical Education Research 2025;24(8):1016-1021
Objective:To fine-tune the mT5 (massively multilingual pre-trained text-to-text transformer) large language model, automatically generate report conclusions for teaching purposes from chest CT image descriptions, and assess the quality of automatically generated conclusions.Methods:The training set included 3 000 high-quality physical examination chest CT reports from one hospital, and the external validation set consisted of 600 physical examination chest CT reports from two other hospitals. Experienced radiology teaching physicians assessed the consistency between the generated conclusions and the original physician-written conclusions in the external validation set using a 5-point Likert scale across five linguistic indicators (correctness of examination information, correctness of lesion detection, standardization of terminology, applicability of the conclusions, and simplicity of conclusions). Using the original report conclusions as the reference, the accuracy of the conclusions generated based on the external validation set in describing four major thoracic conditions (pulmonary nodules, pneumonia, emphysema, pleural effusion) was evaluated. Perform chi square test using SPSS 25.0.Results:In the external validation set, the mean consistency score between the generated conclusions and the original conclusions given by the radiology teaching physicians was >4 points, indicating agreement with the original conclusions. In the generated conclusions, the description of the four major thoracic conditions demonstrated 0.95-1.00 (95% CI=0.91-1.00) accuracy, 0.76-1.00 (95% CI=0.59-1.00) sensitivity, and 0.97-1.00 (95% CI=0.91-1.00) specificity. Conclusions:The chest CT report conclusion generation system based on the mT5 large language model demonstrated high accuracy and is expected to provide immediate and efficient automated guidance for standardized residency training.
5.A chest CT report conclusion generation system based on mT5 large language model for residency training
Yanfei HU ; Ai WANG ; Yaping ZHANG ; Keke ZHAO ; Zhijie PAN ; Qingyao LI ; Min XU ; Xifu WANG ; Xueqian XIE
Chinese Journal of Medical Education Research 2025;24(8):1016-1021
Objective:To fine-tune the mT5 (massively multilingual pre-trained text-to-text transformer) large language model, automatically generate report conclusions for teaching purposes from chest CT image descriptions, and assess the quality of automatically generated conclusions.Methods:The training set included 3 000 high-quality physical examination chest CT reports from one hospital, and the external validation set consisted of 600 physical examination chest CT reports from two other hospitals. Experienced radiology teaching physicians assessed the consistency between the generated conclusions and the original physician-written conclusions in the external validation set using a 5-point Likert scale across five linguistic indicators (correctness of examination information, correctness of lesion detection, standardization of terminology, applicability of the conclusions, and simplicity of conclusions). Using the original report conclusions as the reference, the accuracy of the conclusions generated based on the external validation set in describing four major thoracic conditions (pulmonary nodules, pneumonia, emphysema, pleural effusion) was evaluated. Perform chi square test using SPSS 25.0.Results:In the external validation set, the mean consistency score between the generated conclusions and the original conclusions given by the radiology teaching physicians was >4 points, indicating agreement with the original conclusions. In the generated conclusions, the description of the four major thoracic conditions demonstrated 0.95-1.00 (95% CI=0.91-1.00) accuracy, 0.76-1.00 (95% CI=0.59-1.00) sensitivity, and 0.97-1.00 (95% CI=0.91-1.00) specificity. Conclusions:The chest CT report conclusion generation system based on the mT5 large language model demonstrated high accuracy and is expected to provide immediate and efficient automated guidance for standardized residency training.
6.National clinical three-tiered surveillance and stratified precision detection report on respiratory infectious pathogens in 2024
Jingwen AI ; Jikui DENG ; Min DONG ; Xiaohong GAO ; Jiawei GENG ; Xiaoli HU ; Zhu JIN ; Hongyan LIU ; Yongzhong LI ; Xi LIU ; Yuanwang QIU ; Lihong QU ; Binhuang SUN ; Wei SONG ; Hongyu WANG ; Junping WANG ; Sen WANG ; Xiaoming XIONG ; Daokun YANG ; Liaoyun ZHANG ; Yanliang ZHANG ; Xianghong ZHOU ; Wenhong ZHANG
Chinese Journal of Infectious Diseases 2025;43(2):79-89
Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.
7.A multi-center epidemiological study on pneumococcal meningitis in children from 2019 to 2020
Cai-Yun WANG ; Hong-Mei XU ; Gang LIU ; Jing LIU ; Hui YU ; Bi-Quan CHEN ; Guo ZHENG ; Min SHU ; Li-Jun DU ; Zhi-Wei XU ; Li-Su HUANG ; Hai-Bo LI ; Dong WANG ; Song-Ting BAI ; Qing-Wen SHAN ; Chun-Hui ZHU ; Jian-Mei TIAN ; Jian-Hua HAO ; Ai-Wei LIN ; Dao-Jiong LIN ; Jin-Zhun WU ; Xin-Hua ZHANG ; Qing CAO ; Zhong-Bin TAO ; Yuan CHEN ; Guo-Long ZHU ; Ping XUE ; Zheng-Zhen TANG ; Xue-Wen SU ; Zheng-Hai QU ; Shi-Yong ZHAO ; Lin PANG ; Hui-Ling DENG ; Sai-Nan SHU ; Ying-Hu CHEN
Chinese Journal of Contemporary Pediatrics 2024;26(2):131-138
Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]
8.Distribution and antimicrobial resistance profiles of clinical isolates from blood samples:results from China Antimicrobial Surveillance Network (CHINET) from 2015 to 2021
Min ZHONG ; Xiangning HUANG ; Hua YU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Shanmei WANG ; Yafei CHU ; Wenen LIU ; Yanming LI ; Dawen GUO ; Jinying ZHAO ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Ziyong SUN ; Zhongju CHEN ; Yunsong YU ; Jie LIN ; Jihong LI ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Fang DONG ; Zhiyong LÜ ; Han SHEN ; Wanqing ZHOU ; Sufang GUO ; Zhidong HU ; Jin LI ; Chuanqing WANG ; Pan FU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Lixia ZHANG ; Juan MA ; Yuxing NI ; Jingyong SUN ; Jinju DUAN ; Jianbang KANG ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Xuesong XU ; Chao YAN ; Yunjian HU ; Xiaoman AI ; Jinsong WU ; Yuemei LU ; Fangfang HU ; Lianhua WEI ; Fengmei ZOU ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Xiaobo MA ; Yanping ZHENG ; Kaizhen WEN ; Yirong ZHANG ; Yunsheng CHEN ; Qing MENG ; Xuefei HU ; Ruizhong WANG ; Hua FANG ; Ruyi GUO ; Yan ZHU ; Jilu SHEN ; Wenhui HUANG ; Bixia YU ; Jiao FENG ; Yong ZHAO ; Ping GONG ; Shunhong XUE ; Hongqin GU ; Wen HE ; Jiangshan LIU ; Chunlei YUE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(6):664-677
Objective To investigate the distribution and antimicrobial resistance of bacterial isolates from blood samples in the hospitals participating in China Antimicrobial Surveillance Network (CHINET) from 2015 to 2021.Methods Bacterial strains isolated from blood samples were collected from 52 medical centers participating in CHINET from 2015 to 2021 for analysis of bacetrial distribution and antimicrobial resistance.Results A total of 153591 isolates were collected,48.8% of which were gram-positive bacteria and 51.2% were gram-negative bacteria.The top five bacterial strains were coagulase negative Staphylococcus (28.2%),Escherichia coli (20.7%),Klebsiella (13.7%),Enterococcus (7.2%),and Staphylococcus aureus (6.6%).Compard to female patients,male patients showed lower proportion of E.coli and higher proportions of other bacterial species in all the bacterial isolaets from blood samples.The proportions of Streptococcus pneumoniae and Salmonella in all the bacterial isolaets from blood samples were higher in children compared to adults.Enterobacterales species showed various resistance rates to antimicrobial agents.Overall,≥58.0%,≥36.8% and ≥56.8% of E.coli strains were resistant to cefotaxime,gentamicin and levofloxacin respectively over the 7-year period.However,less than 2.5% of the E.coli strains were resistant to carbapenems.K.pneumoniae showed higher resistance rates to imipenem and meropenem than other Enterobacterales species.During the 7-year period,the prevalence of imipenem-resistant and meropenem-resistant K.pneumoniae increased from 21.4% and 19.9% in 2015 to 25.7% and 26.6% in 2021,respectively.However,carbapenems still maintained good antibacterial activity against other Enterobacterales,associaetd with lower resistance rates.In the 7-year period,Acinetobacter baumannii showed a dwonward trend in the resistance rates to imipenem and meropenem,but remained 72.9% and 73.2% respectively in 2021.The prevalence of imipenem-resistant and meropenem-resistant P.aeruginosa decreased from 26.7% and 22.9% in 2015 to 18.5% and 14.7% in 2021,respectively.The prevalence of PRSP was 1.5% in the isolaets from adults and and 0.8% in the isolates from children.Less than 3.0% of the Enterococcus faecium and Enterococcus faecalis strains were resistant to vancomycin,teicolanin,or linezolid.The prevalence of methicillin-resistant S.aureus (MRSA) and coagulase negative Staphylococcus (MRCNS) was 32.1% and 81.0%,respectively.The prevalence of MRSA was relatively stable,28.5% in 2015 and 28.0% in 2021.Conclusions Coagulase negative Staphylococcus,E.coli and K.pneumoniae were the main bacterial species isolated from blood samples in the hospitals participaing in the CHINET from 2015 to 2021.Significant sex and age differences were found in the distribution of bcterial isolates from blood samples.The overall resistance rates of the top bacetrial strains from blood samples to antimicrobial agents showed a downward trend.Ongoing surveillance of antimicrobial resistance for the isolates from blood samples is still essential for prescribing rational antimicrobial therapies and curbing bacterial resistance.
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.Influencing factors for surgical site infection after gastrointestinal perfora-tion repair surgery:analysis based on decision tree and logistic regression model
Deng-Min HU ; Run XU ; Jian LI ; Yu AI
Chinese Journal of Infection Control 2024;23(7):826-832
Objective To analyze the influencing factors for surgical site infection(SSI)after gastrointestinal per-foration repair surgery by decision tree and logistic regression model.Methods Patients who underwent gastroin-testinal perforation repair surgery at a hospital of Mianyang City from January 2018 to January 2023 were selected as the research subjects.Clinical data of the patients were collected.Patients were divided into the SSI(+)group(n-41)and the SSI(-)group(n-322)based on whether SSI occurred after surgery.Influencing factors for SSI after gastrointestinal perforation repair surgery were analyzed by univariate and multivariate logistic regression.Re-levant decision tree prediction model was constructed.Results Among the 363 patients who underwent gastrointes-tinal perforation repair surgery,41 developed postoperative SSI,with an incidence of 11.29%.Univariate analysis results showed that there were statistically significant differences between two groups of patients in body mass index(BMI),albumin level,preoperative antimicrobial use,duration of preoperative abdominal pain,and duration of sur-gery(all P<0.05).Multivariate logistic regression analysis showed that higher BMI(OR=2.059,95%CI:1.103-3.842),albumin levels<35 g/L(OR=2.761,95%CI:1.312-5.811),duration of preoperative abdominal pain≥24 hours(OR=3.589,95%CI:1.659-7.763),and duration of surgery ≥2 hours(OR=3.314,95%CI:1.477-7.435)were independent risk factors for postoperative SSI in patients after gastrointestinal perforation re-pair surgery(P<0.05),while preoperative antimicrobial use was a protective factor(OR=0.338,95%CI:0.166-0.690,P<0.05).The decision tree model based on the above factors was constructed to predict the risk of SSI in patients after gastrointestinal perforation repair surgery.Validation of the model showed that the area under the re-ceiver operating characteristic(ROC)curve(AUC)was 0.811(95%CI:0.794-0.825).Conclusion The risk factors for postoperative SSI in patients after gastrointestinal perforation repair surgery include high BMI,albumin level<35 g/L,duration of preoperative abdominal pain ≥24 hours,and duration of surgery ≥2 hours.The pro-tective factor is antimicrobial use before surgery.The decision tree model constructed based on the influencing factors has good predictive ability for the risk of postoperative SSI in patients after gastrointestinal perforation repair surgery.

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