1.Huachansu injection enhances anti-colorectal cancer efficacy of irinotecan and alleviates its induced intestinal toxicity through upregulating UGT1A1-OATP1B3 expression in vitro and in vivo.
Bo JIANG ; Zhao-Yang MENG ; Yu-Jie HU ; Jun-Jun CHEN ; Ling ZONG ; Ling-Yan XU ; Xiang-Qi ZHANG ; Jing-Xian ZHANG ; Yong-Long HAN
Journal of Integrative Medicine 2025;23(5):576-590
OBJECTIVE:
Huachansu injection (HCSI), a promising anti-cancer Chinese medicine injection, has been reported to have the potential for reducing the toxicity of chemotherapy and improving the quality of life for colorectal cancer (CRC) patients. The objective of this study is to explore the synergistic and detoxifying effects of HCSI when used in combination with irinotecan (CPT-11).
METHODS:
To investigate the effect of HCSI on anti-CRC efficacy and intestinal toxicity of CPT-11, we measured changes in the biological behavior of LoVo cells in vitro, and anti-tumor effects in LoVo cell xenograft nude mice models in vivo. Meanwhile, the effect of HCSI on intestinal toxicity and the uridine diphosphate-glucuronosyltransferase 1A1 (UGT1A1) expression was investigated in the CPT-11-induced colitis mouse model. Subsequently, we measured the effect of HCSI and its 13 constituent bufadienolides on the expression of UGT1A1 and organic anion transporting polypeptides 1B3 (OATP1B3) in HepG2 cells.
RESULTS:
The combination index (CI) results showed that the combination of HCSI and CPT-11 exhibited a synergistic effect (CI < 1), which significantly suppressing the LoVo cell migration, enhancing G2/M and S phase arrest, and inhibiting tumor growth in vivo. Additionally, the damage to intestinal tissues was attenuated by HCSI in CPT-11-induced colitis model, while the increased expression of UGT1A1 in HepG2 cells and in mouse was observed.
CONCLUSION
The co-therapy with HCSI alleviated the intestinal toxicity induced by CPT-11 and exerted an enhanced anti-CRC effect. The detoxifying mechanism may be related to the increased expression of UGT1A1 and OATP1B3 by HCSI and its bufadienolides components. The findings of this study may serve as a theoretical insights and strategies to improve CRC patient outcomes. Please cite this article as: Jiang B, Meng ZY, Hu YJ, Chen JJ, Zong L, Xu LY, Zhang XQ, Zhang JX, Han YL. Huachansu injection enhances anti-colorectal cancer efficacy of irinotecan and alleviates its induced intestinal toxicity through upregulating UGT1A1-OATP1B3 expression in vitro and in vivo. J Integr Med. 2025; 23(5):576-590.
Irinotecan/therapeutic use*
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Animals
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Glucuronosyltransferase/genetics*
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Humans
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Colorectal Neoplasms/metabolism*
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Drugs, Chinese Herbal/therapeutic use*
;
Mice, Nude
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Mice
;
Up-Regulation/drug effects*
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Male
;
Xenograft Model Antitumor Assays
;
Mice, Inbred BALB C
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Hep G2 Cells
;
Cell Line, Tumor
;
Intestines/drug effects*
;
Amphibian Venoms
2.Cyclin F Expression in Clear Cell Renal Cell Carcinoma and Its Effect on Biological Behavior of Renal Carcinoma Cell Lines
Min SU ; Yan WANG ; Jie HUA ; Tianyun WANG ; Shengnan XU ; Xiang KUI
Cancer Research on Prevention and Treatment 2025;52(6):474-480
Objective To investigate the expression of Cyclin F in clear cell renal cell carcinoma (ccRCC), its clinicopathological characteristics, and its effect on the biological behavior of renal cancer cell lines Methods RT-qPCR and Western blot were used to detect the mRNA and protein expression of Cyclin F in fresh ccRCC specimens. Immunohistochemistry assay was performed to detect the expression of Cyclin F protein in 80 paraffin samples. CCK-8 assay, scratch assay, and flow cytometry were conducted to determine the effects of Cyclin F overexpression on the proliferation, migration, and apoptosis of renal cancer cell lines. Results The expression of Cyclin F in cancer tissues was higher than that in adjacent tissues at the mRNA level (P<
3.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
4.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
5.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
6.Construction of a pancreatic cancer prognosis model based on immune-related genes and its application in immune microenvironment
Yan-jie XU ; Yang-dong WU ; Qiang WANG ; Cun-ying ZHOU ; Xia TIAN ; Xiao HU
Chinese Journal of Current Advances in General Surgery 2025;28(7):530-537
Objective:It is of great significance to analyze the expression characteristics of immune-related genes in pancreatic cancer and their relationship with prognosis,construct and verify a reliable prognostic model,and explore prognostic methods of pancreatic cancer from the perspective of immune microenvironment.Methods:GSEA enrich-ment analysis of differentially expressed genes in pancreatic cancer was performed to identify key immune-related pathways and genes.The genes involved in the immune pathway were screened through the STRING database and combined with univariate Cox regression and LASSO regression analysis.Three key genes,RIPK2,IRAK2 and CXCL11,were finally identified to construct the prognostic model.The accuracy of the model was evaluated using ROC curves and calibration curves,and verified in an independent verification set(GSE57495).At the same time,the expression pat-terns of key genes in the immune microenvironment were analyzed by single-cell RNA sequencing,and the expression levels of these genes were verified in pancreatic cancer cell lines by RT-qPCR.Results:The expressions of RIPK2,IRAK2 and CXCL11 in pancreatic cancer cell lines were higher than those in normal pancreatic cancer cells(P<0.05).The model based on these three genes divided the patients into a high-risk group(n=87)and a low-risk group(n=89),and the difference in survival time between the high-risk group and the low-risk group was statistically significant(P<0.001).Risk score was correlated with G stage,N stage and tumor residue(P<0.01).Single-cell analysis showed that the ex-pression of these genes was highest in tumor-associated macrophages(mean>0.5)and correlated with regulatory T cells and macrophage infiltration(P<0.05).Multivariate analysis showed that risk score was correlated with overall sur-vival after adjusting for clinical factors(P=0.0014).Conclusion:Based on three key immune-related genes(RIPK2,IRAK2 and CXCL11),we successfully constructed a model to accurately predict the prognosis of pancreatic cancer pa-tients,revealing the important role of these genes in the tumor immune microenvironment,and providing new insights and theoretical basis for pancreatic cancer prognosis assessment and immunotherapy research.
7.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
8.Collection and determination of clinical issues in Clinical practice guidelines for postoperative pain management in adults ( 2024 edition) based on Delphi method
Yan WANG ; Yingying ZHAO ; Younian XU ; Yuanyuan YAO ; Jie ZHANG ; Junxian ZHAO ; Tianhu LIANG ; Yaolong CHEN ; Qinjun CHU ; Xiangdong CHEN ; Yunshui PENG ; Jianjun YANG
Chinese Journal of Anesthesiology 2025;45(7):802-807
Objective:To determine the clinical issues in the Clinical practice guidelines for postoperative pain management in adults (2024 edition). Methods:A preliminary list of clinical issues for the guidelines was developed through literature review, clinical surveys, and expert interviews. This was followed by two rounds of Delphi questionnaire surveys, with quality control and statistical analysis conducted using expert positive coefficient, mean item scores, full score ratio, coefficient of variation, Cronbach′s α coefficient, and expert authority level to finalize the list of clinical issues.Results:The experts participating in the Delphi questionnaire surveys had multidisciplinary collaborative backgrounds and regional representativeness, with a high level of authority. The overall positive coefficient of expert participation in the surveys was 78.9%. Through two rounds of the Delphi method and based on the screening criteria of a mean score ≥3.5, coefficient of variation ≤30%, and full score ratio ≥30%, 17 clinical issues were ultimately included following an expert consensus meeting.Conclusions:Through the Delphi method and rigorous quality control, the clinical issues in the Clinical practice guidelines for postoperative pain management in adults (2024 edition) are determined, laying a foundation for the subsequent development of the guidelines.
9.Construction of a machine learning model based on the Ki67 positive index to predict the recurrence risk of hepatocellular carcinoma
Haoran LI ; Yan YU ; Fangying FAN ; Wenzhen DING ; Hui FENG ; Minghua YING ; Jiawei LI ; Qingqing SUN ; Lele BIAN ; Haokai XU ; Zhanyue CHEN ; Jie YU ; Ping LIANG
Chinese Journal of Hepatology 2025;33(9):898-909
Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.
10.Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures (version 2025)
Yong YANG ; Xiaoguang ZHOU ; Qixin CHEN ; Jian CHEN ; Jian DONG ; Liangjie DU ; Shunwu FAN ; Jin FAN ; Zhong FANG ; Haoyu FENG ; Shiqing FENG ; Haishan GUAN ; Aiguo GAO ; Yanzheng GAO ; Yong HAI ; Da HE ; Dengwei HE ; Haiyi HE ; Dianming JIANG ; Xuewen KANG ; Bin LIN ; Baoge LIU ; Changqing LI ; Fang LI ; Li LI ; Fangcai LI ; Weishi LI ; Xiaoguang LIU ; Hongjian LIU ; Xinyu LIU ; Yong LIU ; Zhongjun LIU ; Shibao LU ; Xuhua LU ; Fei LUO ; Yuhai MA ; Keya MAO ; Xuexiao MA ; Bin MENG ; Xu NING ; Limin RONG ; Hongxun SANG ; Jun SHU ; Tiansheng SUN ; Dasheng TIAN ; Zheng WANG ; Bing WANG ; Linfeng WANG ; Qingde WANG ; Qinghe WANG ; Lan WEI ; Jigong WU ; Baoshan XU ; Youjia XU ; Guoyong YIN ; Jinglong YAN ; Feng YAN ; Cao YANG ; Huilin YANG ; Qiang YANG ; Bin ZHAO ; Jie ZHAO ; Yue ZHU ; Jianguo ZHANG ; Wenzhi ZHANG ; Zhongmin ZHANG ; Zhaomin ZHENG ; Yan ZENG ; Baorong HE ; Wei MEI
Chinese Journal of Trauma 2025;41(7):613-626
Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.

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