1.Clinical Efficacy of Xiaoji Hufei Formula in Protecting Children with Close Contact Exposure to Influenza: A Multicenter,Prospective, Non-randomized, Parallel, Controlled Trial
Jing WANG ; Jianping LIU ; Tiegang LIU ; Hong WANG ; Yingxin FU ; Jing LI ; Huaqing TAN ; Yingqi XU ; Yanan MA ; Wei WANG ; Jia WANG ; Haipeng CHEN ; Yuanshuo TIAN ; Yang WANG ; Chen BAI ; Zhendong WANG ; Qianqian LI ; He YU ; Xueyan MA ; Fei DONG ; Liqun WU ; Xiaohong GU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(21):223-230
ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza, and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter, prospective, non-randomized, parallel, controlled trial was conducted from October 2021 to May 2022 in five hospitals, including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness (ILI) cases were collected, and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention, they were assigned to the observation group (108 cases) or the control group (108 cases). Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine (TCM) symptom score scale for influenza, influenza-related emergency (outpatient) visit rate, influenza hospitalization rate, and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled, with 108 in the observation group and 108 in the control group. Primary outcomes: (1) Incidence of ILI: The incidence was 12.0% (13/108) in the observation group and 23.1% (25/108) in the control group, with the observation group showing a significantly lower incidence (χ2=4.6, P<0.05). (2) Influenza confirmation rate: 3.7% (4/108) in the observation group and 4.6% (5/108) in the control group, with no statistically significant difference. Secondary outcomes: (1) TCM symptom score scale: after onset, nasal congestion and runny nose scores differed significantly between the two groups (P<0.05), while other symptoms such as fever, sore throat, and cough showed no significant differences. (2) Influenza-related emergency (outpatient) visit rate: 84.6% (11 cases) in the observation group and 96.0% (24 cases) in the control group, with no significant difference. (3) Time to onset after exposure: The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group, with a statistically significant difference (P<0.05). ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions, Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.
2.Clinical Efficacy of Xiaoji Hufei Formula in Protecting Children with Close Contact Exposure to Influenza: A Multicenter,Prospective, Non-randomized, Parallel, Controlled Trial
Jing WANG ; Jianping LIU ; Tiegang LIU ; Hong WANG ; Yingxin FU ; Jing LI ; Huaqing TAN ; Yingqi XU ; Yanan MA ; Wei WANG ; Jia WANG ; Haipeng CHEN ; Yuanshuo TIAN ; Yang WANG ; Chen BAI ; Zhendong WANG ; Qianqian LI ; He YU ; Xueyan MA ; Fei DONG ; Liqun WU ; Xiaohong GU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(21):223-230
ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza, and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter, prospective, non-randomized, parallel, controlled trial was conducted from October 2021 to May 2022 in five hospitals, including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness (ILI) cases were collected, and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention, they were assigned to the observation group (108 cases) or the control group (108 cases). Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine (TCM) symptom score scale for influenza, influenza-related emergency (outpatient) visit rate, influenza hospitalization rate, and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled, with 108 in the observation group and 108 in the control group. Primary outcomes: (1) Incidence of ILI: The incidence was 12.0% (13/108) in the observation group and 23.1% (25/108) in the control group, with the observation group showing a significantly lower incidence (χ2=4.6, P<0.05). (2) Influenza confirmation rate: 3.7% (4/108) in the observation group and 4.6% (5/108) in the control group, with no statistically significant difference. Secondary outcomes: (1) TCM symptom score scale: after onset, nasal congestion and runny nose scores differed significantly between the two groups (P<0.05), while other symptoms such as fever, sore throat, and cough showed no significant differences. (2) Influenza-related emergency (outpatient) visit rate: 84.6% (11 cases) in the observation group and 96.0% (24 cases) in the control group, with no significant difference. (3) Time to onset after exposure: The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group, with a statistically significant difference (P<0.05). ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions, Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.
3.Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine.
Xin-Ran DU ; Meng-Yi WU ; Mao-Can TAO ; Ying LIN ; Chao-Ying GU ; Min-Feng WU ; Yi CAO ; Da-Can CHEN ; Wei LI ; Hong-Wei WANG ; Ying WANG ; Yi WANG ; Han-Zhi LU ; Xin LIU ; Xiang-Fei SU ; Fu-Lun LI
Journal of Integrative Medicine 2025;23(6):641-653
Traditional Chinese medicine (TCM) is a well-accepted therapy for atopic dermatitis (AD). However, there are currently no evidence-based guidelines integrating TCM and Western medicine for the treatment of AD, limiting the clinical application of such combined approaches. Therefore, the China Association of Chinese Medicine initiated the development of the current guideline, focusing on key issues related to the use of TCM in the treatment of AD. This guideline was developed in accordance with the principles of the guideline formulation manual published by the World Health Organization. A comprehensive review of the literature on the combined use of TCM and Western medicine to treat AD was conducted. The findings were extensively discussed by experts in dermatology and pharmacy with expertise in both TCM and Western medicine. This guideline comprises 23 recommendations across seven major areas, including TCM syndrome differentiation and classification of AD, principles and application scenarios of TCM combined with Western medicine for treating AD, outcome indicators for evaluating clinical efficacy of AD treatment, integration of TCM pattern classification and Western medicine across disease stages, daily management of AD, the use of internal TCM therapies and proprietary Chinese medicines, and TCM external treatments. Please cite this article as: Du XR, Wu MY, Tao MC, Lin Y, Gu CY, Wu MF, Cao Y, Chen DC, Li W, Wang HW, Wang Y, Wang Y, Lu HZ, Liu X, Su XF, Li FL. Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine. J Integr Med. 2025; 23(6):641-653.
Dermatitis, Atopic/drug therapy*
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Humans
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Medicine, Chinese Traditional/methods*
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Integrative Medicine
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Drugs, Chinese Herbal/therapeutic use*
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Practice Guidelines as Topic
4.Review of finite element methods applied in vascular stent research
Jian CHEN ; Hong-Mei WU ; Yu-Long GU ; Yu-Yuan LIU ; Zi-Wei ZHAO
Chinese Medical Equipment Journal 2024;45(10):107-113
The present situation of finite element methods was reviewed when applied in investigating the influences of structural type and structural parameters on mechanical properties of vascular stents,the differences in fatigue performance of vascular stents made of different materials and the interactions of vascular stents,blood vessels and blood.The shortcomings of finite element methods were analyzed,and improvement of simulation accuracy and optimization of vessel and vascular stent setup were suggested to be focused on when performing finite element analysis of vascular stents.[Chinese Medical Equipment Journal,2024,45(10):107-113]
5.Research progress of cement-augmented pedicle screw instrumentation technique
Yong-Cun WEI ; Yan-Chun XIE ; An-Wu XUAN ; Hong-Wen GU ; Bin ZHENG ; Yi LIAN ; Ze-Ning WANG ; Hai-Long YU
Journal of Regional Anatomy and Operative Surgery 2024;33(5):455-459
Osteoporosis is an important cause of internal fixation loosening after spinal surgery.Cement-augmented pedicle screw instru-mentation(CAPSI)technique is the most widely used technique in clinical practice to improve the stability of pedicle screw,mainly applied in osteoporosis and revision surgery,which included conventional solid pedicles crews and fenestrated/cannulated pedicle screws technique.CAPSI technique may cause cement leakage and pulmonary embolism,and there is no consensus on its indications or technical points.Therefore,this article reviews the research progress of CAPSI,in order to provide relevant reference for clinical practice.
6.Artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures
Kang-En HAN ; Hong-Wei WANG ; Hong-Wen GU ; Yin HU ; Shi-Lei TANG ; Zhi-Hao ZHANG ; Hai-Long YU
Journal of Regional Anatomy and Operative Surgery 2024;33(7):579-583
Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.
7.Establishment and validation of a prediction model to evaluate the prolonged hospital stay after anterior cervical discectomy and fusion
Hong-Wen GU ; Hong-Wei WANG ; Shi-Lei TANG ; Kang-En HAN ; Zhi-Hao ZHANG ; Yin HU ; Hai-Long YU
Journal of Regional Anatomy and Operative Surgery 2024;33(7):604-609
Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.
8.Risk factors for surgical site infection after transforaminal lumbar interbody fusion in treatment of lumbar degenerative diseases
Kang-En HAN ; Hong-Wei WANG ; Hong-Wen GU ; Yin HU ; Shi-Lei TANG ; Zhi-Hao ZHANG ; Hai-Long YU
Journal of Regional Anatomy and Operative Surgery 2024;33(9):810-814
Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3%.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.
9.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; 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 ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
10.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; 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 ; Chao YAN ; 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 ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.

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