1.Construction of Risk Prediction Model for Frequent Acute Exacerbations of Chronic Obstructive Pulmonary Disease Under Disease-syndrome Combination
Jing ZHOU ; Gang TENG ; Nianzhi ZHANG ; Yuanyuan WANG ; Qianqian ZHANG ; He HUANG ; Ling LIU ; Mei DONG ; Juan JI
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):143-151
ObjectiveTo construct a risk prediction model for frequent acute exacerbations of chronic obstructive pulmonary disease (COPD) under disease-syndrome combination, thus providing decision support for precise clinical intervention. MethodsA total of 2 029 patients with acute exacerbations of COPD admitted to the First Affiliated Hospital of Anhui University of Chinese Medicine from January 2020 to August 2024 were retrospectively included. These patients were classified into groups of frequent acute exacerbations (≥2 times/year) and infrequent acute exacerbations (<2 times/year) according to the hospitalization times per year. Risk factors were screened by LASSO regression combined with logistic regression, and a nomogram model was constructed. The model performance was assessed based on the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). ResultsThe differences in baseline characteristics between the frequent acute exacerbations group (1 196 cases) and infrequent acute exacerbations group (833 cases) were not statistically significant. LASSO regression combined with multivariate logistic regression screened the following independent risk factors: body mass index (BMI), hospitalization days, number of smoking years, place of residence, use of noninvasive ventilators, oxygen-demanding therapy, liver cirrhosis, use of systemic glucocorticosteroids, and traditional Chinese medicine syndrome (phlegm and stasis obstructing the lung). The nomogram model showed good discrimination and calibration in both the training set (AUC=0.748) and validation set (AUC=0.774). ConclusionThe risk prediction model for frequent acute exacerbations of COPD, integrating traditional Chinese medicine syndrome, constructed in this study has high accuracy. It can provide a scientific basis for early clinical identification of high-risk patients and individualized intervention.
2.Development and validation of a prognostic model for predicting the persistence of prostate-specific antigen after radical prostatectomy
Xianqi SHEN ; Wenhui ZHANG ; Jin JI ; Yan WANG ; Min QU ; Zhenyang DONG ; Jialun LI ; Zenghui ZHOU ; Jie WANG ; Xu GAO
Chinese Journal of Urology 2025;46(1):37-43
Objective:To investigate the factors influencing the persistence of prostate specific antigen(PSA) following radical prostatectomy, and to develop and validate a predictive model for PSA persistence.Methods:Clinical data from 1 828 patients who underwent radical prostatectomy at Shanghai Changhai Hospital between January 2015 and December 2023 were retrospectively analyzed. Of these, 1 295 patients from January 2015 to April 2021 comprised the modeling group, while 533 patients from May 2021 to December 2023 formed the validation group. Additionally, 109 patients who underwent radical surgery at the Third Affiliated Hospital of Naval Medical University between March and December 2023 were included as an external validation group. Patients with incomplete clinical information, serum PSA levels exceeding 100 ng/ml, or those who received preoperative neoadjuvant therapy were excluded. Ultimately, 1 003, 369, and 86 patients were included in the modeling, validation, and external validation groups, respectively. The modeling group had serum PSA of 19.29 (8.43, 23.73) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 191, 673, 123, and 16 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 460, 466, and 77 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 363, 486, and 154 patients, respectively. The validation group had serum PSA of 12.80 (6.82, 14.40) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 40, 289, 37, and 3 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 218, 145, and 6 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 140, 184, and 45 patients, respectively. The external validation group had serum PSA of 12.84 (7.11, 12.97) ng/ml; the clinical stages were distributed as T 1, T 2 and T 3 in 9, 68, and 9 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 58, 27, and 1 patient, respectively; and the secondary Gleason scores were 3, 4, and 5 in 28, 50, and 8 patients, respectively. Logistic regression analysis was used to identify independent risk factors for PSA persistence after radical prostatectomy in the modeling group and a prediction model was constructed. The predictive performance of the model was analyzed using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve, the calibration curve, and the clinical decision curve. The predictive performance of the model was verified by the ROC curve in the validation group and the external validation group. Results:The incidence of persistent PSA after surgery in the modeling group, validation group, and external validation group was 8.97% (90/1 003), 7.32% (27/369), and 17.4% (15/86), respectively. In the modeling group, univariate and multivariate logistic regression analysis revealed that serum PSA, percentage of positive needle cores, primary Gleason score on biopsy, and secondary Gleason score on biopsy were independent risk factors for PSA persistence ( P<0.05), and a prediction model was constructed based on these factors. The AUC value of this model was 0.790 (95% CI 0.745-0.835). Calibration curve and clinical decision curve analyses showed that the model's predicted probabilities aligned well with actual risks within the 0-40% prediction interval, providing clinical benefit. The AUC values of the ROC curves in the validation group and external validation group were 0.808 (95% CI 0.719-0.897) and 0.822 (95% CI 0.714-0.929), respectively, indicating that the model had good predictive performance. Conclusions:The predictive model for PSA persistence, constructed based on serum PSA, percentage of positive needle cores, primary and secondary Gleason score on biopsy, demonstrated good clinical predictive performance, exhibiting high accuracy in both internal and cross-center validation.
3.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
4.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
5.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
6.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
7.Development and validation of a prognostic model for predicting the persistence of prostate-specific antigen after radical prostatectomy
Xianqi SHEN ; Wenhui ZHANG ; Jin JI ; Yan WANG ; Min QU ; Zhenyang DONG ; Jialun LI ; Zenghui ZHOU ; Jie WANG ; Xu GAO
Chinese Journal of Urology 2025;46(1):37-43
Objective:To investigate the factors influencing the persistence of prostate specific antigen(PSA) following radical prostatectomy, and to develop and validate a predictive model for PSA persistence.Methods:Clinical data from 1 828 patients who underwent radical prostatectomy at Shanghai Changhai Hospital between January 2015 and December 2023 were retrospectively analyzed. Of these, 1 295 patients from January 2015 to April 2021 comprised the modeling group, while 533 patients from May 2021 to December 2023 formed the validation group. Additionally, 109 patients who underwent radical surgery at the Third Affiliated Hospital of Naval Medical University between March and December 2023 were included as an external validation group. Patients with incomplete clinical information, serum PSA levels exceeding 100 ng/ml, or those who received preoperative neoadjuvant therapy were excluded. Ultimately, 1 003, 369, and 86 patients were included in the modeling, validation, and external validation groups, respectively. The modeling group had serum PSA of 19.29 (8.43, 23.73) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 191, 673, 123, and 16 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 460, 466, and 77 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 363, 486, and 154 patients, respectively. The validation group had serum PSA of 12.80 (6.82, 14.40) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 40, 289, 37, and 3 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 218, 145, and 6 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 140, 184, and 45 patients, respectively. The external validation group had serum PSA of 12.84 (7.11, 12.97) ng/ml; the clinical stages were distributed as T 1, T 2 and T 3 in 9, 68, and 9 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 58, 27, and 1 patient, respectively; and the secondary Gleason scores were 3, 4, and 5 in 28, 50, and 8 patients, respectively. Logistic regression analysis was used to identify independent risk factors for PSA persistence after radical prostatectomy in the modeling group and a prediction model was constructed. The predictive performance of the model was analyzed using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve, the calibration curve, and the clinical decision curve. The predictive performance of the model was verified by the ROC curve in the validation group and the external validation group. Results:The incidence of persistent PSA after surgery in the modeling group, validation group, and external validation group was 8.97% (90/1 003), 7.32% (27/369), and 17.4% (15/86), respectively. In the modeling group, univariate and multivariate logistic regression analysis revealed that serum PSA, percentage of positive needle cores, primary Gleason score on biopsy, and secondary Gleason score on biopsy were independent risk factors for PSA persistence ( P<0.05), and a prediction model was constructed based on these factors. The AUC value of this model was 0.790 (95% CI 0.745-0.835). Calibration curve and clinical decision curve analyses showed that the model's predicted probabilities aligned well with actual risks within the 0-40% prediction interval, providing clinical benefit. The AUC values of the ROC curves in the validation group and external validation group were 0.808 (95% CI 0.719-0.897) and 0.822 (95% CI 0.714-0.929), respectively, indicating that the model had good predictive performance. Conclusions:The predictive model for PSA persistence, constructed based on serum PSA, percentage of positive needle cores, primary and secondary Gleason score on biopsy, demonstrated good clinical predictive performance, exhibiting high accuracy in both internal and cross-center validation.
8.Comprehensive Evaluation of Original Research Sodium-glucose Transporters 2 Inhibitors Based on A Quick Guideline for Drug Evaluation and Selection in Chinese Medical Institutions(the Second Edition)
Cheng JI ; Bing ZHOU ; Pengli ZHU ; Chao WANG ; Xunlong ZHONG ; Aizong SHEN ; Yi ZHANG ; Ruolun WANG ; Weihong GE ; Zhanjun DONG ; Zhigang ZHAO
Herald of Medicine 2025;44(2):251-258
Objective In order to provide a better reference and basis for the selection of reasonable hypoglycemic drugs for clinical treatment,the study conducted a comprehensive clinical evaluation of the innovator sodium-glucose transporters 2(SGLT-2)inhibitors,based on A Quick Guideline for Drug Evaluation and Selection in Chinese Medical Institutions(the Second Edition).Methods The real-world studies,randomized controlled trials,Meta-analysis/systematic review,drug clinical use guidelines,expert consensus and drug description evaluation evidence were collected,and the included drugs were assigned and evaluated from five dimensions:pharmaceutical characteristics,efficacy,safety,economy and other attributes.Results All SGLT-2 inhibitors had evaluation scores above 75,with dagaglifloztin tablets having the highest score of 84.6,and canaglifloztin having the lowest score of 75.1.Conclusions All five original SGLT-2 inhibitors showed good clinical utility,the difference is that the participating original drugs have different advantageous intervals in clinical use.The results show that dagliflozin has the most ideal clinical utility,and its clinical use should be safer and more effective.Due to the short time on the market and insufficient evidence-based reasons,the advantages of clinical use of proline hemegliflozin are not obvious compared with other evaluated drugs.
9.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
10.Clinicopathologic characteristics and prognosis of early-onset pancreatic cancer:a single-center retrospective analysis
Dong LUO ; Qizhen CHEN ; Yebin LU ; Jun ZHOU ; Qun HE ; Shuai LIANG ; Wei WEI ; Shuai ZHU ; Yixiong LI ; Xuejun GONG ; Liandong JI
Chinese Journal of General Surgery 2025;34(9):1946-1952
Background and Aims:Pancreatic cancer is one of the most aggressive malignancies of the digestive system and is associated with an inferior prognosis.In recent years,its incidence has shown a trend toward younger onset.Early-onset pancreatic cancer(EOPC),defined as pancreatic cancer diagnosed at≤50 years of age,has been increasing annually and may possess distinct biological and prognostic characteristics.Given the limited data from China,this study aimed to investigate the clinicopathological features and prognostic outcomes of EOPC patients.Methods:Clinical data of 113 patients with EOPC admitted to Xiangya Hospital,Central South University,from January 2017 to December 2023 were retrospectively analyzed.Variables included demographic characteristics,clinicopathological features,and survival information.Kaplan-Meier survival curves were plotted,and differences in survival between the surgical and non-surgical groups were compared.Results:The median age at diagnosis was 46(42-49)years,and males accounted for 65.49%of cases.Blood type A(40.71%)and type O(34.51%)were most common.The main presenting symptoms were abdominal pain(69.91%),weight loss(62.83%),jaundice(43.36%),and abdominal distension(36.28%).Imaging findings showed bile duct dilation in 32.74%,pancreatic duct dilation in 39.82%,vascular invasion in 59.29%,and distant metastasis in 52.21%of patients.Histopathology revealed that adenocarcinoma and ductal adenocarcinoma accounted for 93.81%of all cases,with predominantly moderate or poor differentiation(76.10%).Tumors were the most frequently located in the pancreatic head(65.42%).TNM staging showed lymph node metastasis in 77.88%and stage Ⅳ disease in 52.21%.Laboratory tests demonstrated markedly elevated CA19-9 levels.Kaplan-Meier analysis indicated a median overall survival of 18.6 months for the entire cohort,with significantly longer survival in the surgical group compared with the non-surgical group(29.4 months vs.13.8 months,P=0.001 5).Conclusion:EOPC predominantly affects males and tends to arise in the pancreatic head.It is often diagnosed at an advanced stage or with distant metastasis and is characterized by poor differentiation and strong invasiveness.Surgical resection markedly improves survival and remains the key to prolonged prognosis.Young individuals presenting with unexplained abdominal pain,weight loss,or jaundice should be carefully evaluated through imaging to enable early diagnosis and timely surgical intervention.Future multicenter,large-sample prospective studies are warranted to validate these findings further.

Result Analysis
Print
Save
E-mail