1.Safety and efficacy of neoadjuvant chemotherapy combined with immunotherapy in 101 patients with muscle-invasive bladder cancer
Chaosheng GAN ; Tao LI ; Junjie FAN ; Zhangdong JIANG ; Guojing WANG ; Ke XU ; Qiyuan KANG ; Yangqingqing ZHOU ; Yuefeng DU ; Jinhai FAN ; Lei LI ; Dalin HE ; Kaijie WU
Journal of Modern Urology 2024;29(9):790-796
Objective To explore the safety and efficacy of neoadjuvant chemotherapy(NAC)combined with immunotherapy before radical cystectomy plus pelvic lymph nodes dissection(RC-PLND)for muscle-invasive bladder cancer(MIBC).Methods The clinical data of 101 patients with MIBC who underwent neoadjuvant therapy followed by RC-PLND in the Department of Urology,the First Affiliated Hospital of Xi'an Jiaotong University during Jan.2019 and Dec.2023 were retrospectively analyzed,including 71 patients(70.3%)who received NAC(NAC group)and 30(29.7%)who received NAC combined with immunotherapy(NAC combine immunotherapy group).The clinical and pathological data and adverse events during neoadjuvant therapy were compared.Logistic regression analysis was used to explore the independent predictors of pathological complete response(pCR)and pathological partial response(pPR).Results There were no significant differences in the baseline data between the two groups(P>0.05).However,the proportion of multiple tumors in patients receiving NAC before surgery was significantly higher than that in the NAC combined immunotherapy group(69.0%vs.46.7%,P=0.034).Compared with NAC group,NAC combined with immunotherapy group had significantly improved rate of pathological downstaging and pPR(60.6%vs.83.3%,P=0.026;45.1%vs.70.0%,P=0.022).Furthermore,the rate of pCR in patients undergoing NAC combined immunotherapy was higher than those undergoing NAC,but the difference was not significant(53.3%vs.33.8%,P=0.067).Logistic regression analysis revealed that clinical T-stage and tumor diameter were independent predictors of pCR and pPR(P<0.05).In addition,the most common adverse events during neoadjuvant therapy were anemia,decreased white blood cells,nausea,and vomiting,but most of them were grade 1-2 and could be relieved through symptomatic treatment.Conclusion NAC combined with immunotherapy is safe and effective,which can improve the rate of pathological downstaging,pPR and pCR,without increasing the incidence of adverse reactions.
2.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
3.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
4.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.
5.Changing distribution and resistance profiles of Klebsiella strains in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chuyue ZHUO ; Yingyi GUO ; Chao ZHUO ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; 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 WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(4):418-426
Objective To understand the changing distribution and antimicrobial resistance profiles of Klebsiella strains in 52 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Antimicrobial susceptibility testing was carried out according to the unified CHINET protocol.The susceptibility results were interpreted according to the breakpoints in the Clinical & Laboratory Standards Institute(CLSI)M100 document.Results A total of 241,549 nonduplicate Klebsiella strains were isolated from 2015 to 2021,including Klebsiella pneumoniae(88.0%),Klebsiella aerogenes(5.8%),Klebsiella oxytoca(5.7%),and other Klebsiella species(0.6%).Klebsiella strains were mainly isolated from respiratory tract(48.49±5.32)%.Internal medicine(22.79±3.28)%,surgery(17.98±3.10)%,and ICU(14.03±1.39)%were the top 3 departments where Klebsiella strains were most frequently isolated.K.pneumoniae isolates showed higher resistance rate to most antimicrobial agents compared to other Klebsiella species.Klebsiella isolates maintained low resistance rates to tigecycline and polymyxin B.ESBLs-producing K.pneumoniae and K.oxytoca strains showed higher resistance rates to all the antimicrobial agents tested compared to the corresponding ESBLs-nonproducing strains.The K.pneumoniae and carbapenem-resistant K.pneumoniae(CRKP)strains isolated from ICU patients demonstrated higher resistance rates to majority of the antimicrobial agents tested than the strains isolated from non-ICU patients.The CRKP strains isolated from adult patients had higher resistance rates to most of the antimicrobial agents tested than the corresponding CRKP strains isolated from paediatric patients.Conclusions The prevalence of carbapenem-resistant strains in Klebsiella isolates increased greatly from 2015 to 2021.However,the Klebsiella isolates remained highly susceptible to tigecycline and polymyxin B.Antimicrobial resistance surveillance should still be strengthened for Klebsiella strains.
6.Changing resistance profiles of Staphylococcus isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yuling XIAO ; Mei KANG ; Yi XIE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; 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 2024;24(5):570-580
Objective To investigate the changing distribution and antibiotic resistance profiles of clinical isolates of Staphylococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Staphylococcus according to the unified protocol of CHINET(China Antimicrobial Surveillance Network)using disk diffusion method and commercial automated systems.The CHINET antimicrobial resistance surveillance data from 2015 to 2021 were interpreted according to the 2021 CLSI breakpoints and analyzed using WHONET 5.6.Results During the period from 2015 to 2021,a total of 204,771 nonduplicate strains of Staphylococcus were isolated,including 136,731(66.8%)strains of Staphylococcus aureus and 68,040(33.2%)strains of coagulase-negative Staphylococcus(CNS).The proportions of S.aureus isolates and CNS isolates did not show significant change.S.aureus strains were mainly isolated from respiratory specimens(38.9±5.1)%,wound,pus and secretions(33.6±4.2)%,and blood(11.9±1.5)%.The CNS strains were predominantly isolated from blood(73.6±4.2)%,cerebrospinal fluid(12.1±2.5)%,and pleural effusion and ascites(8.4±2.1)%.S.aureus strains were mainly isolated from the patients in ICU(17.0±7.3)%,outpatient and emergency(11.6±1.7)%,and department of surgery(11.2±0.9)%,whereas CNS strains were primarily isolated from the patients in ICU(32.2±9.7)%,outpatient and emergency(12.8±4.7)%,and department of internal medicine(11.2±1.9)%.The prevalence of methicillin-resistant strains was 32.9%in S.aureus(MRSA)and 74.1%in CNS(MRCNS).Over the 7-year period,the prevalence of MRSA decreased from 42.1%to 29.2%,and the prevalence of MRCNS decreased from 82.1%to 68.2%.MRSA showed higher resistance rates to all the antimicrobial agents tested except trimethoprim-sulfamethoxazole than methicillin-susceptible S.aureus(MSSA).Over the 7-year period,MRSA strains showed decreasing resistance rates to gentamicin,rifampicin,and levofloxacin,MRCNS showed decreasing resistance rates to gentamicin,erythromycin,rifampicin,and trimethoprim-sulfamethoxazole,but increasing resistance rate to levofloxacin.No vancomycin-resistant strains were detected.The prevalence of linezolid-resistant MRCNS increased from 0.2%to 2.3%over the 7-year period.Conclusions Staphylococcus remains the major pathogen among gram-positive bacteria.MRSA and MRCNS were still the principal antibiotic-resistant gram-positive bacteria.No S.aureus isolates were found resistant to vancomycin or linezolid,but linezolid-resistant strains have been detected in MRCNS isolates,which is an issue of concern.
7.Quantitative analysis of macular microcirculation changes in diabetic retinopathy patients by optical coherence tomography angiography
Xin LU ; Xing-Xing ZHAO ; En-Hui YI ; Yi-Ping ZHANG ; Lu YU ; Xiao-Kang HE ; Ye ZHANG ; Zhao-Jiang DU
International Eye Science 2023;23(6):1033-1039
AIM: To evaluate the macular microcirculation changes in patients with diabetic retinopathy(DR)by optical coherence tomography angiography(OCTA), and correlate the risk factors that may affect the macular microcirculation, so as to provide a clinical basis for early screening, diagnosis and therapeutic intervention for DR.METHODS: Retrospective study. A total of 75 patients(75 eyes)with type 2 diabetes mellitus(DM)who came to the ophthalmology outpatient clinic and ward of Xi'an Central Hospital from May to October 2022 were collected, and the DM patients were further divided into non-DR(NDR)group, non-proliferative DR(NPDR)group and proliferative DR(PDR)group, with 28 eyes, 25 eyes and 22 eyes in each group respectively. OCTA was applied to perform a 3mm×3mm blood flow imaging scan of the macular retina to automatically obtain the vascular density(VD)of the superficial retinal macular foveal, the parafoveal(1~3mm), as well as the macular 3mm×3mm and the area of macular foveal avascular zone(FAZ). Furthermore, the alteration of these parameters in patients with different degrees of DR was analyzed.RESULTS: Compared with the NDR group, the VD of the 3mm×3mm superficial retinal capillary(SCP)in the macular region was decreased in both PDR and NPDR group(all P<0.017), and the VD of the parafoveal was decreased in each quadrant(P<0.017), with the most significant decrease in the PDR group. The FAZ area of patients in the PDR and NPDR groups was significantly larger than that in the NDR group(P<0.017). Age, homocysteine, best corrected visual acuity(LogMAR), axial length and glycosylated hemoglobin(HbA1c)of patients with DR were negatively correlated with VD in the macular foveal(P<0.05), while homocysteine, best corrected visual acuity(LogMAR), axial length, and the duration of diabetes were negatively correlated with VD in the macular 3mm×3mm(P<0.05). Triglycerides, best corrected visual acuity(LogMAR), and HbA1c were negatively correlated with VD in the parafoveal(P<0.05), while total cholesterol and central macular thickness had no significant correlation with VD(P>0.05).CONCLUSION: The microcirculation changes in the macular area of DR patients can be monitored by OCTA, and the systemic condition of DR patients is closely related to their macular microcirculation.
8.Research Progress on Microbial Community Succession in the Postmortem Interval Estimation.
Qing-Qing XIANG ; Li-Fang CHEN ; Qin SU ; Yu-Kun DU ; Pei-Yan LIANG ; Xiao-Dong KANG ; He SHI ; Qu-Yi XU ; Jian ZHAO ; Chao LIU ; Xiao-Hui CHEN
Journal of Forensic Medicine 2023;39(4):399-405
The postmortem interval (PMI) estimation is a key and difficult point in the practice of forensic medicine, and forensic scientists at home and abroad have been searching for objective, quantifiable and accurate methods of PMI estimation. With the development and combination of high-throughput sequencing technology and artificial intelligence technology, the establishment of PMI model based on the succession of the microbial community on corpses has become a research focus in the field of forensic medicine. This paper reviews the technical methods, research applications and influencing factors of microbial community in PMI estimation explored by using high-throughput sequencing technology, to provide a reference for the related research on the use of microbial community to estimate PMI.
Humans
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Postmortem Changes
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Artificial Intelligence
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Autopsy
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Cadaver
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Microbiota
9.A multicenter epidemiological study of acute bacterial meningitis in children.
Cai Yun WANG ; Hong Mei XU ; Jiao TIAN ; Si Qi HONG ; Gang LIU ; Si Xuan WANG ; Feng GAO ; Jing LIU ; Fu Rong LIU ; Hui YU ; Xia WU ; Bi Quan CHEN ; Fang Fang SHEN ; Guo ZHENG ; Jie YU ; Min SHU ; Lu LIU ; Li Jun DU ; Pei LI ; Zhi Wei XU ; Meng Quan ZHU ; Li Su HUANG ; He Yu HUANG ; Hai Bo LI ; Yuan Yuan HUANG ; Dong WANG ; Fang WU ; Song Ting BAI ; Jing Jing TANG ; Qing Wen SHAN ; Lian Cheng LAN ; Chun Hui ZHU ; Yan XIONG ; Jian Mei TIAN ; Jia Hui WU ; Jian Hua HAO ; Hui Ya ZHAO ; Ai Wei LIN ; Shuang Shuang SONG ; Dao Jiong LIN ; Qiong Hua ZHOU ; Yu Ping GUO ; Jin Zhun WU ; Xiao Qing YANG ; Xin Hua ZHANG ; Ying GUO ; Qing CAO ; Li Juan LUO ; Zhong Bin TAO ; Wen Kai YANG ; Yong Kang ZHOU ; Yuan CHEN ; Li Jie FENG ; Guo Long ZHU ; Yan Hong ZHANG ; Ping XUE ; Xiao Qin LI ; Zheng Zhen TANG ; De Hui ZHANG ; Xue Wen SU ; Zheng Hai QU ; Ying ZHANG ; Shi Yong ZHAO ; Zheng Hong QI ; Lin PANG ; Cai Ying WANG ; Hui Ling DENG ; Xing Lou LIU ; Ying Hu CHEN ; Sainan SHU
Chinese Journal of Pediatrics 2022;60(10):1045-1053
Objective: To analyze the clinical epidemiological characteristics including composition of pathogens , clinical characteristics, and disease prognosis acute bacterial meningitis (ABM) in Chinese children. Methods: A retrospective analysis was performed on the clinical and laboratory data of 1 610 children <15 years of age with ABM in 33 tertiary hospitals in China from January 2019 to December 2020. Patients were divided into different groups according to age,<28 days group, 28 days to <3 months group, 3 months to <1 year group, 1-<5 years of age group, 5-<15 years of age group; etiology confirmed group and clinically diagnosed group according to etiology diagnosis. Non-numeric variables were analyzed with the Chi-square test or Fisher's exact test, while non-normal distrituction numeric variables were compared with nonparametric test. Results: Among 1 610 children with ABM, 955 were male and 650 were female (5 cases were not provided with gender information), and the age of onset was 1.5 (0.5, 5.5) months. There were 588 cases age from <28 days, 462 cases age from 28 days to <3 months, 302 cases age from 3 months to <1 year of age group, 156 cases in the 1-<5 years of age and 101 cases in the 5-<15 years of age. The detection rates were 38.8% (95/245) and 31.5% (70/222) of Escherichia coli and 27.8% (68/245) and 35.1% (78/222) of Streptococcus agalactiae in infants younger than 28 days of age and 28 days to 3 months of age; the detection rates of Streptococcus pneumonia, Escherichia coli, and Streptococcus agalactiae were 34.3% (61/178), 14.0% (25/178) and 13.5% (24/178) in the 3 months of age to <1 year of age group; the dominant pathogens were Streptococcus pneumoniae and the detection rate were 67.9% (74/109) and 44.4% (16/36) in the 1-<5 years of age and 5-<15 years of age . There were 9.7% (19/195) strains of Escherichia coli producing ultra-broad-spectrum β-lactamases. The positive rates of cerebrospinal fluid (CSF) culture and blood culture were 32.2% (515/1 598) and 25.0% (400/1 598), while 38.2% (126/330)and 25.3% (21/83) in CSF metagenomics next generation sequencing and Streptococcus pneumoniae antigen detection. There were 4.3% (32/790) cases of which CSF white blood cell counts were normal in etiology confirmed group. Among 1 610 children with ABM, main intracranial imaging complications were subdural effusion and (or) empyema in 349 cases (21.7%), hydrocephalus in 233 cases (14.5%), brain abscess in 178 cases (11.1%), and other cerebrovascular diseases, including encephalomalacia, cerebral infarction, and encephalatrophy, in 174 cases (10.8%). Among the 166 cases (10.3%) with unfavorable outcome, 32 cases (2.0%) died among whom 24 cases died before 1 year of age, and 37 cases (2.3%) had recurrence among whom 25 cases had recurrence within 3 weeks. The incidences of subdural effusion and (or) empyema, brain abscess and ependymitis in the etiology confirmed group were significantly higher than those in the clinically diagnosed group (26.2% (207/790) vs. 17.3% (142/820), 13.0% (103/790) vs. 9.1% (75/820), 4.6% (36/790) vs. 2.7% (22/820), χ2=18.71, 6.20, 4.07, all P<0.05), but there was no significant difference in the unfavorable outcomes, mortility, and recurrence between these 2 groups (all P>0.05). Conclusions: The onset age of ABM in children is usually within 1 year of age, especially <3 months. The common pathogens in infants <3 months of age are Escherichia coli and Streptococcus agalactiae, and the dominant pathogen in infant ≥3 months is Streptococcus pneumoniae. Subdural effusion and (or) empyema and hydrocephalus are common complications. ABM should not be excluded even if CSF white blood cell counts is within normal range. Standardized bacteriological examination should be paid more attention to increase the pathogenic detection rate. Non-culture CSF detection methods may facilitate the pathogenic diagnosis.
Adolescent
;
Brain Abscess
;
Child
;
Child, Preschool
;
Escherichia coli
;
Female
;
Humans
;
Hydrocephalus
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Infant
;
Infant, Newborn
;
Male
;
Meningitis, Bacterial/epidemiology*
;
Retrospective Studies
;
Streptococcus agalactiae
;
Streptococcus pneumoniae
;
Subdural Effusion
;
beta-Lactamases

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