1.Analysis of knowledge awareness and associated factors of chikungunya fever among medical college students in Baise City
Chinese Journal of School Health 2026;47(3):347-350
Objective:
To understand the awareness of chikungunya fever knowledge and its related factors among medical college students in Baise City, so as to provide a scientific basis to offer relevant courses and special education.
Methods:
From July to August 2025, 7 286 enrolled medical students were selected by a sampling method from a medical college in Baise City to participate in the questionnaire survey. The questionnaire covered epidemiological characteristics, clinical symptoms, and prevention/control knowledge of chikungunya fever. Statistical analyses including the Chi quare test and multivariate Logistic regression models were performed.
Results:
The overall awareness rate of chikungunya fever knowledge among the medical students was 18.89%. Among the knowledge items, the awareness rate of "the high incidence season" was the highest (84.05%), while that of "the infectious period" was the lowest (17.80%). Multivariate Logistic regression analysis showed that medical students with female (a OR= 1.37 , 95%CI =1.20- 1.57 ), the age for over 25 years old (a OR=1.76, 95%CI =1.05-2.93), whose father had a middle school educational level (a OR=1.18, 95%CI =1.05-1.31), and majored in preventive medicine (a OR=1.54, 95%CI =1.10-1.67) had relatively higher awareness rates of chikungunya fever knowledge (all P <0.05). In contrast, students of Zhuang ethnicity (a OR= 0.87 , 95%CI =0.76-0.98) and majoring in nursing (a OR=0.74, 95%CI =0.61-0.91) or pharmacy (a OR=0.70, 95%CI =0.52-0.95) had relatively lower awareness rates (all P <0.05).
Conclusions
The awareness rate of chikungunya fever related knowledge among medical college students in Baise City is relatively low. Schools should take targeted publicity measures to improve medical students awareness.
2.Clinical Advantages of Traditional Chinese Medicine in Treatment of Childhood Simple Obesity: Insights from Expert Consensus
Qi ZHANG ; Yingke LIU ; Xiaoxiao ZHANG ; Guichen NI ; Heyin XIAO ; Junhong WANG ; Liqun WU ; Zhanfeng YAN ; Kundi WANG ; Jiajia CHEN ; Hong ZHENG ; Xinying GAO ; Liya WEI ; Qiang HE ; Qian ZHAO ; Huimin SU ; Zhaolan LIU ; Dafeng LONG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):238-245
Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance, while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine (TCM) has a long history in the prevention and management of this condition, demonstrating eight distinct advantages, including systematic theoretical foundation, diversified therapeutic approaches, definite therapeutic efficacy, high safety profile, good patient compliance, comprehensive intervention strategies, emphasis on prevention, and stepwise treatment protocols. Additionally, TCM is characterized by six distinctive features: the use of natural medicinal substances, non-invasive external therapies, integration of medicinal dietetics, simple exercise regimens, precise syndrome differentiation, and diverse dosage forms. By combining internal and external treatments, TCM facilitates individualized regimen adjustment and holistic regulation, demonstrating remarkable effects in improving obesity-related metabolic indicators, regulating constitutional imbalance, and promoting healthy behaviors. However, challenges remain, such as inconsistent operational standards, insufficient high-quality clinical evidence, and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment, conducting multicenter randomized controlled trials, and fostering interdisciplinary integration, so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.
3.Prognostic correlation analysis of multiple myeloma based on HALP score of peripheral blood before chemotherapy
Min CHEN ; Liying AN ; Xiaojing LIN ; Pan ZHAO ; Xingli ZOU ; Jin WEI ; Xun NI
Chinese Journal of Blood Transfusion 2025;38(1):61-67
[Objective] To explore the predictive value of HALP score for prognosis in patients with multiple myeloma (MM). [Methods] A retrospective analysis was conducted on laboratory indicators and related clinical data of newly diagnosed multiple myeloma (NDMM) patients, treated at the Affiliated Hospital of North Sichuan Medical College from January 2016 to October 2023, prior to their first treatment. The HALP score was calculated, and the optimal cutoff value for HALP was determined using X-tile software. Survival analysis was performed using Kaplan-Meier curves for high HALP and low HALP groups. Univariate and multivariate analyses were conducted using the Cox regression model, and a forest plot was generated using Graphpad Prism to illustrate factors that may impact patient prognosis. The predictive ability of HALP score combined with β2-microglobulin and ECOG score for prognosis in MM patients was evaluated using receiver operating characteristic curve (ROC) analysis. [Results] A total of 203 MM patients were included, with the optimal cutoff value for HALP score being 29.15 (P<0.05). Among them, 101 patients were in the low HALP score group, and 102 patients were in the high HALP score group. The results of univariate and multivariate analysis using the Cox regression model showed that a HALP score <29.15 was an independent risk factor for progression-free survival (PFS) and overall survival (OS) (P<0.05). ROC curve analysis indicated that the combination of HALP score with β2-microglobulin and ECOG score had a higher predictive value for prognosis in MM patients compared to using HALP score alone. [Conclusion] The HALP score is closely related to the prognosis of patients with NDMM. A low HALP score indicates a poorer prognosis, while the combination of HALP score with β2-microglobulin and ECOG score provides a higher predictive value when assessed together.
4.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; 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(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
5.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
6.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.
7.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.
8.Analyses of the influence of diabetes-related deaths on the probability of premature mortality and life expectancy in Minhang District, Shanghai from 2004 to 2023
Shuili XUAN ; Jingyi NI ; Jiaqi GUO ; Wei LIU ; Lijing CHEN ; Yibin ZHOU ; Linli CHEN ; Huilin XU
Shanghai Journal of Preventive Medicine 2025;37(9):752-758
ObjectiveTo analyze the impact of diabetes-related deaths on the probability of premature mortality and life expectancy in Minhang District of Shanghai from 2004 to 2023, and to provide reference data for the optimization of targeted prevention and control strategies. MethodsAll death cases involving diabetes among the registered residents of Minhang District from 2004 to 2023 were collected. The probability of premature mortality and life expectancy was computed using the abridged life table method. The average annual percent change (AAPC) was calculated with Joinpoint 4.9.0.0. The Arriaga decomposition method was employed for statistical analyses of the influence of cause-specific and age-specific mortality related to diabetes on life expectancy. ResultsThe total number of diabetes-related mortality, crude mortality, and standardized mortality for both males and females in Minhang District from 2004 to 2023 exhibited an increasing trend (P<0.001). The primary causes of death among diabetes-related cases were cardiovascular disease (37.68%), diabetes mellitus (31.95%), and malignant tumor (17.80%). From 2004 to 2023, probability of premature mortality to diabetes-related diseases demonstrated a rising trend (P<0.001), contrasting with the declining trend observed in the overall population (P=0.001). Males showed a significant upward trajectory (P<0.001), while females displayed a stable pattern. Among the diseases exerting considerable influence, cardiovascular disease and malignant tumor revealed a marked increase over time (P<0.001), whereas diabetes mellitus maintained a stable trend; both factors negatively impacted the reduction in probability of premature mortality. From 2004 to 2023, diabetes-related mortality reduced life expectancy among residents by an average of 1.22 years (-49.89%), indicating a negative impact; the reduction was 1.41 years in males and 0.90 years in females. The age groups exhibiting greater negative contributions differed by genders, namely males aged 50‒54 years and females aged 70‒74 years. Cardiovascular disease, diabetes mellitus, and malignant tumor contributed significantly to this decline (-0.46 years, -0.42 years, -0.20 years, respectively), with male experiencing higher negative contributions than females. ConclusionIn Minhang District, the rising mortality associated with diabetes-related diseases negatively impact both the reduction of the probability of premature mortality and the increase in life expectancy. This trend is primarily attributed to the rapid escalation of mortality and younger age demographic of male residents, which warrants significant attention. It is recommended that, based on the enhancement of case management, efforts should be directed towards the targeted prevention and control of risk factors and high-risk populations.
9.Value of dual-energy CT quantitative parameters combined with clinical features in diagnosis of stages T2 and T3 colorectal cancer
Ni FANG ; Xin WEI ; Weijuan CHEN ; Mei FENG ; Lingjing ZHANG ; Yuexi LIU ; Qi LAI ; Xuan DING ; Xinjie LIU ; Wei JIANG ; Han YU
Journal of Army Medical University 2025;47(2):177-185
Objective To investigate the diagnostic value of our regression model based on quantitative parameters of dual-energy CT and clinical features for stages T2 and T3 colorectal cancer.Methods A cross-section study was performed on 91 patients with colorectal cancer confirmed by postoperative pathology in our hospital from January 2022 to November 2023.All of them underwent dual-energy CT examination.According to the pathological T staging criteria of Chinese Colorectal Cancer Diagnosis and Treatment Standard(2020 Edition),they were divided into T2 group(n=43)and T3 group(n=48).Univariate analysis was used to compare the differences in quantitative CT parameters and clinical features between the 2 groups,and the obtained significant variables were employed to construct diagnosis models by univariate or multivariate logistic regression analysis.The area under receiver operating characteristic curve(AUC)of the CT parametric model and the model combined with clinical features was compared to evaluate the efficacy of diagnosing T2 and T3 stages.Results Univariate analysis showed that carcinoembryonic antigen(CEA),N stage,tumor location,tumor longest diameter(LD),CT value of virtual noncontrast(CT-VNC),fat fraction,electron density(Rho)and dual energy index(DEI)were significantly different between the T2 and T3 groups(P<0.05).Multivariate logistic regression analysis found that N stage,tumor location,LD,fat fraction and DEI were independent risk factors for the diagnosis of stage T3.The AUC value of the model of above CT parameters in diagnosing stage T3 colorectal cancer was 0.671(95%CI:0.558~0.783),and the AUC value of the combined model of above CT parameters and clinical features was 0.886(95%CI:0.815~0.957),and statistical difference was observed in the AUC value between the combined model and the CT parametric model(P<0.01).Conclusion The regression model constructed with dual-energy CT quantitative parameters combined with clinical features has high value in the preoperative diagnosis of stages T2 and T3 colorectal cancer before surgery.
10.The application of virtual navigation bronchoscopy assisted localization in thoracoscopic sublobectomy and its impact on perioperative outcomes
Yu HUANG ; Longyu JIN ; Wei FENG ; Yuyang NI ; Yingji CHEN ; Hongchun XU ; Yuchao MA
Chinese Journal of Thoracic and Cardiovascular Surgery 2025;41(4):212-219
Objective:To investigate the impact of virtual navigation bronchoscopy on perioperative information in patients undergoing thoracoscopic pulmonary resection.Methods:Employed three distinct propensity score matching models to effectively address the baseline data disparities among patients undergoing thoracoscopic pulmonary resection. Categorized the patients into two groups: pulmonary wedge resection and pulmonary segmentectomy. Compared the disparities in clinical characteristics, intraoperative lesion resection, and postoperative recovery between patients who underwent virtual navigation bronchoscopy assisted localization prior to surgery and those who did not employ any specific localization methods.Results:This reserch included a total of 127 patients who underwent localization assisted by virtual navigation bronchoscopy, and 122 patients who did not undergo specialized localization. After propensity score matching, the navigation group demonstrated a statistically significant reduction in intraoperative blood loss[model 3, 40(20, 50) ml vs. 50(20, 100) ml, P=0.027], drainage volume on the first day post-surgery[model 3, 100(50, 175) ml vs. 150(100, 220) ml, P=0.023], and incidence of residual pleural effusion(model 3, 31 cases vs. 38 cases, P=0.046) compared to the non-positioning group among patients undergoing pulmonary wedge resection. In the pulmonary segmentectomy group, we observed a reduction in intraoperative blood loss[model 3, 50(30, 100) ml vs. 100(50, 100) ml, P=0.003] and incidence of residual pneumothorax(model 3, 18 cases vs. 28 cases, P=0.012) in patients who underwent navigation-assisted procedures compared to those without specialized positioning. Conclusion:The utilization of virtual navigation bronchoscopy for preoperative localization assistance in thoracoscopic sublobectomy(including wedge resection and segmental resection) may represent a viable approach to mitigate intraoperative injury and facilitate postoperative recovery.


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