1.Expert consensus on cryoablation therapy of oral mucosal melanoma
Guoxin REN ; Moyi SUN ; Zhangui TANG ; Longjiang LI ; Jian MENG ; Zhijun SUN ; Shaoyan LIU ; Yue HE ; Wei SHANG ; Gang LI ; Jie ZHNAG ; Heming WU ; Yi LI ; Shaohui HUANG ; Shizhou ZHANG ; Zhongcheng GONG ; Jun WANG ; Anxun WANG ; Zhiyong LI ; Zhiquan HUNAG ; Tong SU ; Jichen LI ; Kai YANG ; Weizhong LI ; Weihong XIE ; Qing XI ; Ke ZHAO ; Yunze XUAN ; Li HUANG ; Chuanzheng SUN ; Bing HAN ; Yanping CHEN ; Wenge CHEN ; Yunteng WU ; Dongliang WEI ; Wei GUO
Journal of Practical Stomatology 2024;40(2):149-155
		                        		
		                        			
		                        			Cryoablation therapy with explicit anti-tumor mechanisms and histopathological manifestations has a long history.A large number of clinical practice has shown that cryoablation therapy is safe and effective,making it an ideal tumor treatment method in theory.Previously,its efficacy and clinical application were constrained by the limitations of refrigerants and refrigeration equipment.With the development of the new generation of cryoablation equipment represented by argon helium knives,significant progress has been made in refrigeration efficien-cy,ablation range,and precise temperature measurement,greatly promoting the progression of tumor cryoablation technology.This consensus systematically summarizes the mechanism of cryoablation technology,indications for oral mucosal melanoma(OMM)cryotherapy,clinical treatment process,adverse reactions and management,cryotherapy combination therapy,etc.,aiming to provide reference for carrying out the standardized cryoablation therapy of OMM.
		                        		
		                        		
		                        		
		                        	
2.Evaluation of the activity of sturgeon cartilage peptides and preparation of ointments
Peng LEI ; Kai-chao SONG ; Zheng-wen XIE ; Yi-fan QI ; Yu-jia ZHANG ; Wen-sheng ZHENG
Acta Pharmaceutica Sinica 2024;59(7):2135-2142
		                        		
		                        			
		                        			 Sturgeon cartilage has a wide range of applications as it is rich in biologically active substances such as chondroitin sulphate and protein. In this study, the safety evaluation of sturgeon cartilage peptide in NIH/3T3 and C2C12 cells was conducted, and the results showed that sturgeon cartilage peptide did not induce apoptosis and necrosis in NIH/3T3 and C2C12 cells compared to the blank control, which provides an 
		                        		
		                        	
3.Analysis of the policy diffusion of the centralized and volume-based drug procurement in China
Yi-Bo GAO ; Zhao-Yang WANG ; Bo LYU ; Jing-Xuan ZHAO ; Jia-Xin XIE ; Yong-Xi XUE ; Yu-Run GAO ; Kai MENG
Chinese Journal of Health Policy 2024;17(9):76-82
		                        		
		                        			
		                        			Objective:To carry out the policy diffusion analysis of centralized and volume-based drug procurement in China in recent years,and to provide reference for the formulation of centralized and volume-based drug procurement policy.Methods:Through the official websites of the central and provincial governments,the official websites of the Health Commission and the official websites of the Medical Security Bureau,the policy documents related to centralized and volume-based drug procurement from January 1,2009 to December 31,2023 were searched.Based on the policy diffusion theory,the reference network analysis method is used to analyze the intensity,breadth and speed of policy diffusion,and the sequential analysis method of policy keywords is used to analyze the direction of policy diffusion.Results:In the two stages of the development of centralized and volume-based drug procurement policy,the number of policies issued in the medical insurance management stage reached the peak;The top ten policies with the highest diffusion intensity and breadth are all central policies,and most of them are notices and opinions.In addition,the newly promulgated policies have a faster diffusion speed.In the direction of diffusion,top-down and parallel diffusion trends are obvious.Conclusion:The diffusion of centralized and volume-based drug procurement policy in China focuses on the central policy,and the diffusion speed is increasing year by year.It is suggested to strengthen the policy coordination between the central and local governments,establish a unified national information platform for centralized drug procurement,optimize the learning and competition mechanism between governments at all levels,and give play to the advantages of"policy experiment".
		                        		
		                        		
		                        		
		                        	
4.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
		                        		
		                        			
		                        			Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
		                        		
		                        		
		                        		
		                        	
5.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.
		                        		
		                        		
		                        		
		                        	
6.Predictive values of PNI,LMR and MELD for early lung infection after liver transplantation
Kai YANG ; Dingcong HOU ; Shaoxian DUAN ; Yi BI ; Yan XIE ; Li ZHANG ; Wentao JIANG
Tianjin Medical Journal 2024;52(10):1041-1045
		                        		
		                        			
		                        			Objective To explore risk factors of early lung infection after liver transplantation and to construct a prediction model of early lung infection after liver transplantation.Methods The clinical data of 269 patients who underwent orthotopic liver transplantation for the first time were retrospectively analyzed.Patients were divided into the infected group(n=97)and the non-infected group(n=172)according to whether pulmonary infection occurred within 30 days after operation.The preoperative general data,preoperative laboratory examination results,intraoperative and postoperative data of the patients were collected.Multivariate Logistic regression analysis were used to screen risk factors of pulmonary infection.Based on the results of multivariate analysis,the prediction model was constructed and the prediction efficiency of the model was evaluated.Results Univariate and multivariate Logistic regression analysis showed that preoperative PNI≤41.70(OR=1.972,95%CI:1.047-3.714,P=0.036),LMR≤1.52(OR=2.020,95%CI:1.102-3.705,P=0.023),MELD score>10.72(OR=1.985,95%CI:1.103-3.573,P=0.022),operative time>448.00 min(OR=2.676,95%CI:1.515-4.727,P=0.001)and intensive care unit(ICU)hospitalization time>4.0 days(OR=2.623,95%CI:1.335-5.154,P=0.005)were independent risk factors for early pulmonary infection after liver transplantation.The ROC area under the curve(AUC)of the prediction model based on the results of multivariate Logistic regression analysis was 0.768,the sensitivity was 80.41%and the specificity was 60.47%.Conclusion The prediction model based on PNI,LMR,MELD score,operation time and ICU hospitalization time can effectively predict the occurrence of early pulmonary infection after liver transplantation.
		                        		
		                        		
		                        		
		                        	
7.Predictive value of the proportion of hibernating myocardium in total perfusion defect on reverse remodeling in patients with HFrEF underwent coronary artery bypass graft.
Yao LU ; Jian CAO ; En Jun ZHU ; Ming Xin GAO ; Tian Tian MOU ; Ying ZHANG ; Xiao Fen XIE ; Yi TIAN ; Ming Kai YUN ; Jing Jing MENG ; Xiu Bin YANG ; Yong Qiang LAI ; Ran DONG ; Xiao Li ZHANG
Chinese Journal of Cardiology 2023;51(4):384-392
		                        		
		                        			
		                        			Objective: To evaluate the predictive value of the proportion of hibernating myocardium (HM) in total perfusion defect (TPD) on reverse left ventricle remodeling (RR) after coronary artery bypass graft (CABG) in patients with heart failure with reduced ejection fraction (HFrEF) by 99mTc-methoxyisobutylisonitrile (MIBI) single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) combined with 18F-flurodeoxyglucose (FDG) gated myocardial imaging positron emission computed tomography (PET). Methods: Inpatients diagnosed with HFrEF at the Cardiac Surgery Center, Anzhen Hospital of Capital Medical University from January 2016 to January 2022 were prospectively recruited. MPI combined with 18F-FDG gated PET was performed before surgery for viability assessment and the patients received follow-up MPI and 18F-FDG gated PET at different stages (3-12 months) after surgery. Δ indicated changes (post-pre). Left ventricular end-systolic volume (ESV) reduced at least 10% was defined as RR, patients were divided into reverse remodeling (RR+) group and the non-reverse group (RR-). Binary logistic regression analysis was used to identify predictors of RR. Receiver operating characteristic (ROC) curve analysis was performed and the area under the curve (AUC) was calculated to assess the cut-off value for predicting RR. Additionally, we retrospectively enrolled inpatients with HFrEF at the Cardiac Surgery Center, Anzhen Hospital of Capital Medical University from January 2021 to January 2022 as the validation group, who underwent MPI and 18F-FDG gated PET before surgery. Echocardiography was performed before CABG and after CABG (3-12 months). In the validation group, the reliability of obtaining the cut-off value for the ROC curve was verified. Results: A total of 28 patients with HFrEF (26 males; age (56.9±8.7) years) were included in the prospective cohort. HM/TPD was significantly higher in the RR+ group than in the RR- group ((51.8%±17.9%) vs. (35.7%±13.9%), P=0.016). Binary logistic regression analysis revealed that HM/TPD was an independent predictor of RR (Odds ratio=1.073, 95% Confidence interval: 1.005-1.145, P=0.035). ROC curve analysis revealed that HM/TPD=38.3% yielded the highest sensitivity, specificity, and accuracy (all 75%) for predicting RR and the AUC was 0.786 (P=0.011). Meanwhile, a total of 100 patients with HFrEF (90 males; age (59.7±9.6) years) were included in the validation group. In the validation group, HM/TPD=38.3% predicted RR in HFrEF patients after CABG with the highest sensitivity, specificity and accuracy (82%, 60% and 73% respectively). Compared with the HFrEF patients in the HM/TPD<38.3% group (n=36), RR and cardiac function improved more significantly in the HM/TPD≥38.3% group (n=64) (all P<0.05). Conclusions: Preoperative HM/TPD ratio is an independent factor for predicting RR in patients with HFrEF after CABG, and HM/TPD≥38.3% can accurately predict RR and the improvement of cardiac function after CABG.
		                        		
		                        		
		                        		
		                        			Male
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		                        			Humans
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		                        			Middle Aged
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		                        			Aged
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		                        			Stroke Volume
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		                        			Heart Failure
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		                        			Fluorodeoxyglucose F18
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		                        			Retrospective Studies
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		                        			Reproducibility of Results
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		                        			Prospective Studies
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		                        			Coronary Artery Bypass
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		                        			Ventricular Dysfunction, Left
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		                        			Tomography, Emission-Computed, Single-Photon
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		                        			Perfusion
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		                        			Myocardium
		                        			
		                        		
		                        	
8.Predictive value of left ventricular ejection fraction reserve assessed by SPECT G-MPI for major adverse cardiovascular event in patients with coronary artery disease.
Yi Han ZHOU ; Yao LU ; Jing Jing MENG ; Tian Tian MOU ; Yu Jie BAI ; Shuang ZHANG ; Ya Qi ZHENG ; Qiu Ju DENG ; Jian JIAO ; Zhi CHANG ; Xiao Fen XIE ; Ming Kai YUN ; Hong Zhi MI ; Xiang LI ; Xiao Li ZHANG
Chinese Journal of Cardiology 2023;51(6):626-632
		                        		
		                        			
		                        			Objective: To evaluate the prognostic value of left ventricular ejection fraction (LVEF) reserve assessed by gated SPECT myocardial perfusion imaging (SPECT G-MPI) for major adverse cardiovascular event (MACE) in patients with coronary artery disease. Methods: This is a retrospective cohort study. From January 2017 to December 2019, patients with coronary artery disease and confirmed myocardial ischemia by stress and rest SPECT G-MPI, and underwent coronary angiography within 3 months were enrolled. The sum stress score (SSS) and sum resting score (SRS) were analyzed by the standard 17-segment model, and the sum difference score (SDS, SDS=SSS-SRS) was calculated. The LVEF at stress and rest were analyzed by 4DM software. The LVEF reserve (ΔLVEF) was calculated (ΔLVEF=stress LVEF-rest LVEF). The primary endpoint was MACE, which was obtained by reviewing the medical record system or by telephone follow-up once every twelve months. Patients were divided into MACE-free and MACE groups. Spearman correlation analysis was used to analyze the correlation between ΔLVEF and all MPI parameters. Cox regression analysis was used to analyze the independent factors of MACE, and the optimal SDS cutoff value for predicting MACE was determined by receiver operating characteristic curve (ROC). Kaplan-Meier survival curves were plotted to compare the difference in the incidence of MACE between different SDS groups and different ΔLVEF groups. Results: A total of 164 patients with coronary artery disease [120 male; age (58.6±10.7) years] were included. The average follow-up time was (26.5±10.4) months, and a total of 30 MACE were recorded during follow-up. Multivariate Cox regression analysis showed that SDS (HR=1.069, 95%CI: 1.005-1.137, P=0.035) and ΔLVEF (HR=0.935, 95%CI: 0.878-0.995, P=0.034) were independent predictors of MACE. According to ROC curve analysis, the optimal cut-off to predict MACE was a SDS of 5.5 with an area under the curve of 0.63 (P=0.022). Survival analysis showed that the incidence of MACE was significantly higher in the SDS≥5.5 group than in the SDS<5.5 group (27.6% vs. 13.2%, P=0.019), but the incidence of MACE was significantly lower in the ΔLVEF≥0 group than in theΔLVEF<0 group (11.0% vs. 25.6%, P=0.022). Conclusions: LVEF reserve (ΔLVEF) assessed by SPECT G-MPI serves as an independent protective factor for MACE, while SDS is an independent risk predictor in patients with coronary artery disease. SPECT G-MPI is valuable for risk stratification by assessing myocardial ischemia and LVEF.
		                        		
		                        		
		                        		
		                        			Humans
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		                        			Male
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		                        			Middle Aged
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		                        			Aged
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		                        			Coronary Artery Disease/diagnostic imaging*
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		                        			Stroke Volume
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		                        			Myocardial Perfusion Imaging
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		                        			Retrospective Studies
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		                        			Ventricular Function, Left
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		                        			Myocardial Ischemia
		                        			
		                        		
		                        	
9.Preparation of mesoporous silica nanoparticles with different sizes and study on the correlation between size and toxicity
Xiao-wei XIE ; Meng-ying CHENG ; Wei-xiang FANG ; Xue LIN ; Wen-ting GU ; Kai-ling YU ; Ting-xian YE ; Wei-yi CHENG ; Li HE ; Hang-sheng ZHENG ; Ying-hui WEI ; Ji-gang PIAO ; Fan-zhu LI
Acta Pharmaceutica Sinica 2023;58(8):2512-2521
		                        		
		                        			
		                        			 To investigate the crucial role of particle size in the biological effects of nanoparticles, a series of mesoporous silica nanoparticles (MSNs) were prepared with particle size gradients (50, 100, 150, 200 nm) with the traditional Stober method and adjusting the type and ratio of the silica source. The correlation between toxicity and size-caused biological effects were then further examined both 
		                        		
		                        	
10.The value of preoperative inflammatory markers in predicting recurrence of hepatocellular carcinoma after liver transplantation
Yan XIE ; Weiqi ZHANG ; Yabei HUANG ; Yi BI ; Kai YANG ; Jian YANG ; Jisan SUN ; Li ZHANG ; Wentao JIANG
Chinese Journal of Digestive Surgery 2023;22(2):236-243
		                        		
		                        			
		                        			Objective:To investigate the value of aspartate aminotransferase/lymphocyte ratio (ALR), γ-glutamyltranspeptidase/lymphocyte ratio (GLR) and aspartate aminotransferase/alanine aminotransferase ratio (AAR) in predicting the recurrence of hepatocellular carcinoma after liver transplantation.Methods:The retrospective cohort study was conducted. The clinicopathological data of 178 patients with hepatocellular carcinoma who underwent liver transplantation in Tianjin First Central Hospital from July 2014 to June 2018 were collected. There were 156 males and 22 females, aged (54±9)years. All patients received the first time of orthotopic liver transplantation. Observation indicators: (1) follow-up; (2) the predictive value and cutoff value of each index for tumor recur-rence of patients with hepatocellular carcinoma after liver transplantation; (3) analysis of risk factors for tumor recurrence of patients with hepatocellular carcinoma after liver transplantation; (4) cons-truction and evaluation of the predictive model for tumor recurrence of patients with hepatocellular carcinoma after liver transplantation. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were expressed as absolute numbers, and comparison between groups was conducted using the chi-square test or Fisher exact probability. The Kaplan-Meier method was used to draw survival curve and the Log-rank test was used for survival analysis. Factors with P<0.05 in univariate analysis were included in multivariate analysis. Univariate analysis and multivariate analysis were performed by COX proportional risk regression model with forward method. The regression coefficient was used to build the prediction model. The receiver operating characteristic curve was drawn, and the area under curve (AUC) was used to evaluate the predictive ability of prediction model. Results:(1) Follow-up. All 178 patients with hepatocellular carcinoma were followed up for 36(range, 1?74)months after liver transplantation. During the follow-up, there were 41 patients died, 61 patients with tumor recurrence and 117 cases without tumor recurrence. The 3-, 5-year overall survival rates and 3-, 5-year tumor recurrence free survival rates of patients after liver transplantation were 72.8%, 69.9% and 57.3%, 52.8%, respectively. (2) The predictive value and cutoff value of each index for tumor recurrence of patients with hepatocellular carcinoma after liver transplantation. The AUC of preoperative serum alpha fetoprotein (AFP), tumor diameter, ALR, GLR, neutrophil to lymphocyte ratio, AAR in recipients were 0.76, 0.70, 0.69, 0.65, 0.64, 0.65 (95% confidence interval as 0.68?0.83, 0.61?0.79, 0.61?0.77, 0.57?0.74, 0.56?0.73, 0.56?0.74, P<0.05), and the corresponding best cutoff value of each index were 228.00 μg/L, 5.25 cm, 92.90, 122.40, 3.00, 2.42. (3) Analysis of risk factors for tumor recurrence of patients with hepato-cellular carcinoma after liver transplantation. Results of multivariate analysis showed the preoperative serum AFP >228.88 μg/L, number of tumor as multiple, tumor diameter >5.25 cm, ALR >92.90, AAR >2.42 were indepen-dent risk factors for tumor recurrence of hepatocellular carcinoma after liver transplantation ( hazard ratio=3.13, 1.90, 2.66, 2.40, 2.75, 95% confidence interval as 1.81?5.41, 1.08?3.35, 1.49?4.74, 1.40?4.11, 1.54?4.91, P<0.05). (4) Construction and evaluation of the predictive model for tumor recurrence of patients with hepatocellular carcinoma after liver transplantation. According to the results of multivariate analysis, the preoperative serum AFP, number of tumor, tumor diameter, ALR, AAR were used to construct the predictive model for tumor recurrence of hepatocellular carcinoma after liver transplantation. The AUC, best cutoff value, specificity and sensitivity of the predictive model were 0.83 (95% confidence interval as 0.76?0.89, P<0.05), 5.5, 80.3% and 73.8%. Of the 178 patients, there were 110 patients with low risk of tumor recurrence (scoring as 0?5) and 68 patients with high risk of tumor recurrence (scoring as 6?16) after liver transplantation. The 1-, 3-, 5-year tumor recurrence free survival rates and 1-, 3-, 5-year overall survival rates of patients with high risk of tumor recurrence were 27.7%, 18.2%, 18.2% and 63.7%, 48.9%, 48.9%, respectively. The above indicators of patients with low risk of tumor recurrence were 92.3%, 82.4%, 74.6% and 90.4%, 87.7%, 83.6%, respectively. There were significant differences of the above indicators between patients with high risk of tumor recurrence and low risk of tumor recurrence ( χ2=67.83, 21.95, P<0.05). Conclusions:The preoperative serum AFP, number of tumor, tumor diameter, ALR, AAR are independent influencing factors for tumor recurrence of hepato-cellular carcinoma after liver transplantation. The predictive model constructed based on the above indexes has a good prediction efficiency.
		                        		
		                        		
		                        		
		                        	
            
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