1.Correlation between serum inhibin B level afar treatment with gonadotropin releasing hormone agonist and outcome of in vitro fertilization-embryo transfer
Wenqin LIN ; Haiyan YANG ; Jinju LIN ; Xia CHEN ; Bilu YE
Chinese Journal of Obstetrics and Gynecology 2009;44(4):260-262
Objective To evaluate the decreased level of serum inhibin B(INHB)treated by gunadotropin releasing hormone agonist(GNRH-a)in predicting ovarian response and pregnancy in in vitro fertilization-embryo transfer(IVF-ET).Methods The prospective study enrolled 124 women given by GnRH-a+recombine follicle stimulating hormone(rFSH)+human chorionic gonadotrophin(hCG)long term stimulation protocol undergone their first cycle of IVF-ET treatment.The following predictive factors were collected and analyzed,such as age,basal level of follicle stimulating hormone(FSH),the ratio of FSH/luteinizing hormone(LH),the concentration of INHB after down-regulation,total number of antral follicle count(AFC)and mean ovarian volume. Ovarian response was evaluated by the number of oecytes obtained.A multiple regression analysis and logistic regression model were used for all possible prognostic variables to evaluate the value of difierent hormones in predicting ovariall response and pregnancy after IVF-ET.Receiver operating characteristic(ROC) analysis was used to evaluate the level of INHB in predicting the number of oocytes obtained.The sensitivity and specificity were calculated at the discriminating cut-off point Results The concentration of INHB after down-regulation showed a highly significant positive correlations with the number of oocytes obtained(r=0.435,P<0.01).The multiple regression analyses showed INHB was the most significant predictor of the number of retrieved oocytes,but INHB was not associated with IVF-ET outcome significantly(P>0.05).ROC analyses showed INHB after down-regulation had the largest area under curve(AUC)0.933(95%CI:0.878-0.988).When a threshold of 15 ng/L of INHB was established,95.5%sensitivity and 50.0% specificity in ovarian response were observed.Conclusions The level of INHB Was the best factor in predicting ovarian response in IVF-ET.Decreased level of INHB Was the early sign of ovarian reserve function failure,however,useless in predicting IVF-ET outcome.
2.Outcome of pregnancy in women with polycystic ovary syndrome treated by in vitro maturation of immature oocytes
Junzhao ZHAO ; Xia CHEN ; Peiyu WANG ; Wei ZHOU ; Jinju LIN ; Wei ZHANG ; Xuefeng HUANG ; Wenqin LIN ; Haiyan YANG ; Ya CHEN
Chinese Journal of Obstetrics and Gynecology 2009;44(6):409-412
n occurring after the treatment of IVM in women with PCOS are not mounting. However, the relative high rates of multiple pregnancies, low birth weight and preterm labor were increased.
3.Accurate imaging diagnosis and recurrence prediction of hepatocellular carcinoma based on artificial intelligence
Yiping LIU ; Xinping LI ; Lei CHEN ; Jinju XIA ; Kairong SONG ; Ningyang JIA ; Wanmin LIU
Journal of Clinical Hepatology 2022;38(3):521-527
The integration of artificial intelligence into the medical field is developing rapidly and has achieved ground-breaking advances in the diagnosis, treatment, and efficacy evaluation of imaging medicine. This article reviews the research advances in artificial intelligence in imaging diagnosis of hepatocellular carcinoma and its performance in evaluating treatment outcome and predicting prognosis in combination with clinical features and looks forward to how artificial intelligence can be better used in the practice of hepatocellular carcinoma imaging in the era of growing clinical needs and rapid advances in diagnosis and treatment techniques.
4.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.